2001 An investigation of capture effects in IEEE 802.11 ...

University of WollongongResearch Online

University of Wollongong Thesis Collection University of Wollongong Thesis Collections

2001

An investigation of capture effects in IEEE 802.11networksChristopher Graham WareUniversity of Wollongong

Research Online is the open access institutional repository for theUniversity of Wollongong. For further information contact the UOWLibrary: [email protected]

Recommended CitationWare, Christopher Graham, An investigation of capture effects in IEEE 802.11 networks, Doctor of Philosophy thesis, School ofElectrical, Computer and Telecommunications Engineering, University of Wollongong, 2001. http://ro.uow.edu.au/theses/1941

http://ro.uow.edu.au/


http://ro.uow.edu.au

http://ro.uow.edu.au/theses

http://ro.uow.edu.au/thesesuow



A n Investigation of Capture Effects in IEEE 802.11 Networks

A thesis submitted in fulfilment of the requirements for the award of the degree

Doctor of Philosophy

from

THE UNIVERSITY OF WOLLONGONG

by

Christopher Graham Ware

Bachelor of Engineering (Honours Class I) Bachelor of Science (Physics) University of Wollongong, 1997

SCHOOL OF ELECTRICAL, COMPUTER AND TELECOMMUNICATIONS ENGINEERING

AUGUST 2001

Abstract

Local area wireless networking is quickly becoming a preferred technology for

many networking applications. This is driven by the introduction of the IEEE

802.11 and ETSI HiperLAN standards, combined with the promise of explicit

quality of service mechanisms designed to support exciting new services over

wireless media. These developments have the potential to fundamentally alter

the way a user interacts with the network, as well as opening a raft of potential

new applications able to exploit the inherent benefits of wireless media.

Incorporating both the wireless local area and mobile ad hoc network paradigm,

this thesis presents a comprehensive investigation of the impact of capture ef

fects on the fairness properties of the IEEE 802.11 wireless Medium Access

Control ( M A C ) protocol in topologies involving hidden terminals. Through

empirical investigation, a strong relationship between the relative received sig

nal power of contending hidden connections and the fairness behaviour of the

network is identified. A signal power difference of greater than 5dB between

competing connections was observed to result in a channel capture state for

the stronger connection. This behaviour has a significant impact on the ability

of the M A C to provide fair service to all contending nodes, and in extreme

circumstances can result in extremely poor performance for the weaker hidden

nodes in the network. The signal strength dependent capture behaviour iden

tified in this thesis has been presented within the IEEE 802.1 Working Group,

having significant influence on the design of the Hybrid Co-ordination Function

centralised QoS M A C .

ii

Abstract iii

Analytical investigation of the impact of c o m m o n spreading code interference

confirms the empirical observation, with a received signal power difference of

greater than 2dB found to be sufficient to result in the observed bias. Simulation

tools such as ns-2 play a significant role in the development of new wireless pro

tocols and services. The ability of current receiver models to accurately match

empirical data is investigated. A new model based on the physical operation of

an IEEE 802.11 interface is introduced in response to inadequacies identified in

current receiver models. This model, termed Message Retraining, is shown to

provide a significant improvement over current receiver models in terms of the

ability to match the m o d e m capture characteristics of an IEEE 802.11 network

interface.

Finally, techniques designed to prevent unfair behaviour resulting from relative

signal power dependent capture effects are presented. These techniques are able

to operate within a distributed or centralised M A C . A n algorithm is developed

employing the relative observed signal power to determine a probability variable

for each identified hidden neighbour. This variable is then employed by one of

three separate techniques designed to provide additional transmission opportu

nities for hidden nodes at a relative disadvantage. Each scheme is shown to be

able to significantly improve the fairness characteristics for hidden connections,

preventing stronger hidden hosts from dominating the radio resource. However,

the three schemes are differentiated on the basis of the impact on aggregate

throughput, implementation complexity, and flexibility.

Statement of Originality

This is to certify that the work described in this thesis is entirely m y own,

except where due reference is made in the text.

No work in this thesis has been submitted for a degree to any other university

or institution.

Signed

Christopher Graham Ware

August, 2001

IV

Acknowledgments

Firstly, I would like to thank m y supervisors, Associate Professor Tadeusz

Wysocki and Professor Joe Chicharo. Their advice and support as proven in

valuable throughout this project.

I would like to thank my colleagues in the 'SNRC lab', Paul, Phil, Ben, Ricky,

Chun Tung, and Justin. The technical discussions, coffee, and endless distrac

tions have all contributed significantly to the development of this work. I must

also thank Eryk Dutkiewicz and John Judge for their assistance in the early

stages of this project.

I am also greatful for the support of my parents, Graham and Adele, my brother

Brad, and sister Julie through the years of study. This is it guys, I promise.

And finally, to my wonderful girlfriend Jane whose support and patience has

formed the solid ground that allowed m e to pursue this dream.

v

Contents

1 Introduction 1

1.1 Background 1

1.2 Thesis Outline 2

1.3 Contributions 4

1.4 Publications 6

2 Literature Review 8

2.1 Introduction 8

2.2 Medium Access Control Protocols for

Shared Wireless Media 9

2.2.1 Access Mechanisms 11

2.2.2 Signalling Mechanisms 16

2.2.3 Collision Resolution Algorithms 23

2.2.4 QoS Mechanisms 24

2.2.5 MAC Comparison Matrix 26

2.3 The IEEE 802.11 MAC/PHY Protocol 28

2.3.1 Medium Access Control Layer 29

2.3.2 Direct Sequence Spread Spectrum Physical Layer .... 33

2.3.3 Future Extensions to 802.11 PHY 36

vi

C O N T E N T S vii

2.4 Packet and Channel Capture Phenomena in Wireless Networks . 36

2.4.1 Packet Capture 37

2.4.2 Capture Probability Analysis 37

2.4.3 Channel Capture 39

2.5 Investigation of the Fairness Properties of Wireless LAN's ... 41

2.5.1 Fairness Definitions 42

2.5.2 Experimental Fairness Investigations 43

2.5.3 Mechanisms to Prevent Unfair Behaviour 46

2.5.4 Discussion 50

2.6 Summary 51

2.6.1 Summary of Open Research Issues Identified In Current Literature 52

3 Experimental Investigation of Capture Effects and Fairness Behaviour 54

3.1 Introduction 54

3.2 Experimental Motivation 55

3.3 Experimental Methodology 59

3.4 TCP Experiments 60

3.4.1 RTS Handshake - Hidden Terminals 62

3.4.2 Impact of Varying Signal Strength 65

3.5 UDP Experiments 68

3.5.1 Equal Signal Power 69

3.5.2 Unequal Signal Power 70

3.6 Conclusions 74

CONTENTS viii

4 Error Probability Analysis - Hidden Terminal Jamming 77

4.1 Introduction 77

4.2 Spread Spectrum Error Probability

Analysis 78

4.3 Error Probability of Captured Frame 81

4.3.1 DSSS Basic Rate Physical Layer 83

4.3.2 DSSS High Rate Physical Layer 84

4.4 Numerical Results 85

4.4.1 Single Interferer, K = 2 85

4.4.2 Multiple Interferers, K > 2 86

4.5 The Retraining Hypothesis 88

4.6 Conclusion 91

5 Modelling Packet Capture Behaviour 93

5.1 Introduction 93

5.2 Capture Models 94

5.2.1 Delay Capture 97

5.2.2 Power Capture 98

5.2.3 Hybrid Capture 98

5.3 Message Retraining Reception Model 99

5.4 Simulation Investigation 101

5.4.1 Methodology 101

5.4.2 Simulation Environment 103

5.4.3 UDP Results 104

5.4.4 TCP Results 109

C O N T E N T S ix

5.5 Fairness Study 116

5.5.1 Jain's Fairness Index 117

5.5.2 Kullback-Leibler Fairness Index 117

5.5.3 Results 118

5.5.4 Discussion 123

5.6 Conclusions 124

6 Prevention Of Signal Strength Dependent Unfairness 126

6.1 Introduction 126

6.2 Analysis of Topology Dependent

Unfairness Prevention Algorithms 127

6.3 Average Signal Strength Based

Probability 129

6.3.1 Identification of Hidden Nodes 131

6.4 Algorithms to Control Signal Strength

Dependent Unfairness in Hidden Node

Scenarios 132

6.4.1 Probabilistic Access at Backoff Countdown 136

6.4.2 Probabilistic Discard 137

6.4.3 Enhanced CTS Suppression 137

6.5 Performance Investigation and Comparison 140

6.5.1 Simulation Methodology 140

6.5.2 Comparison Criteria 141

6.5.3 Simple Case - Static Hidden Nodes 143

6.5.4 Static Scenario Discussion 148

6.5.5 General Dynamic Case - Hidden and

In-Range Nodes 150

CONTENTS x

6.5.6 Dynamic Scenario Discussion 155

6.6 Conclusions and Recommendations 157

7 Conclusions 161

7.1 Overview 161

7.2 Significant Results 161

7.3 Further Work 164

A Hidden Node Detection Mechanisms 177

B Additional Fairness Algorithm Results 183

B.l 3 Node TCP Results 183

B.l.l Static topology Results 183

B.l.2 Dynamic Topology Results 187

List of Abbreviations

ACK

AP

BB

BER

BPSK

BSS

CCK

CDMA

CFP

CP

CTS

CW

DBPSK

DCF

DIFS

DSSS

ECTS

EDCF

EIFS

ERTS

FAMA

FHSS

FTP

GAMA

Acknowledgement

Access Point

Black Burst

Bit Error Rate

Binary Phase Shift Keying

Basic Service Set

Complementary Code Keying

Code Division Multiple Access

Contention Free Period

Contention Period

Clear To Send

Contention Window

Differential Binary Phase Shift Keying

Distributed Co-ordinate Function

Distributed (co-ordinate function) Interframe Space

Direct Sequence Spread Spectrum

Enhanced C T S

Enhanced D C F

Extended Interframe Space

Enhanced RTS

Floor Acquisition Multiple Access

Frequency Hopping Spread Spectrum

File Transfer Protocol

Group Allocation Multiple Access

xi

List of Abbreviations xii

HCF

IEEE

IETF

IP

ISM

LAN

LRC

MAC

MACA

MACA-BI

MACAW

MANET

MIB

MMPDU

MPDU

MSDU

NAV

OFDM

PCF

PHY

PLCP

QPSK

QoS

RA

RF

RIMA

RTS

SA

SIFS

SNR

SRAM

Hybrid Co-ordination Function

Institution of Electrical and Electronic Engineers

Internet Engineering Task Force

Internet Protocol

Industrial, Scientific, and Medical

Local Area Network

Long Retry Count

Medium Access Control

Multiple Access Collision Avoidance

M A C A By Invitation

M A C A for Wireless

Mobile Ad Hoc Network

Management Information Base

M A C Management Protocol Data Unit

M A C Protocol Data Unit

M A C Service Data Unit

Network Allocation Vector

Orthogonal Frequency Division Multiplexing

Point Co-ordinate Function

Physical Layer

Physical Layer Convergence Protocol

Quadrature Phase Shift Keying

Quality of Service

Receiver Address

Radio Frequency

Receiver Initiated Multiple Access

Request To Send

Source Address

Short Interframe Space

Signal to Noise Ratio

Split channel Reservation Multiple Access

List of Abbreviations xiii

SSMA Spread Spectrum Multiple Access

SSRC Station Short Retry Count

STA 802.11 Network Station

TCP Transport Control Protocol

UDP User Datagram Protocol

W A N Wide Area Network

W G Working Group

List of Figures

2.1 Illustration of non-persistent C S M A Operation (Tobagi and Klein-

rock, 1976) 12

2.2 The Hidden terminal problem, Node A and C cannot sense each

other's carrier 13

2.3 The Exposed terminal problem, Node B prevents Node C from

transmitting 14

2.4 The Collision Avoidance handshake using RTS/CTS messages . 15

2.5 The FAMA CTS message dominates RTS messages. Host A will

detect the CTS message and backoff accordingly (Fullmer and

Garcia-Luna-Aceves, 1997b) 20

2.6 Hidden terminal collisions with the RTS/CTS exchange. Trans

mission of the RTS at t2 by node C collides with the C T S from

node B at t2, or the RTS from node C at t\ collides with the

D A T A frame from node A. F A M A attempts to prevent collisions

of this type by enforcing dominance of C T S messages over the

RTS (Fullmer and Garcia-Luna-Aceves, 1995) 21

2.7 Elimination Yield NMPA Channel Access Cycles (European Telecom

munications Standards Intsitute, 1998) 28

2.8 Interframe Space Relationships (Institution of Electrical and Elec

tronic Engineers, 1999a) 30

2.9 RTS/CTS/DATA/ACK and NAV Setting. 'Other' node is a node

within range of either Source or Destination. Receipt of RTS or

C T S M M P D U will set N A V accordingly (Institution of Electrical

and Electronic Engineers, 1999a) 31

2.10 PCF Frame Exchange Sequence (Institution of Electrical and

Electronic Engineers, 1999a) 32

xiv

LIST OF FIGURES xv

2.11 Square Experimental Topology (Gerla et al., 1999a) 41

2.12 Example wireless network topology including both hidden and

visible stations (Ozugur et al., 1998). Link access probabilities

are assigned to each logical network link in accordance with Equa

tions 2.6 and 2.7. Arrows indicate the logical links, and probabil

ity pij assigned to each link. Node A has a set of neighbours B.

The set of nodes C are hidden from A, having at least one con

nection with a neighbour of A. All other nodes in the network

belong to a separate set, D 47

3.1 Experimental Topology 56

3.2 Simulation Experiment - Hidden terminals, DATA/ACK only.

Connection A captures the resource until approximately 3 sec

onds when Connection B is able to access the channel. The abil

ity of either connection to capture the channel is random in this experiment 57

3.3 Simulation Experiment - Hidden terminals, RTS/CTS/DATA/ACK 58

3.4 Experiment 1: Lucent Barker PHY Equal SNR 25dB, No RTS/CTS

Handshake 63

3.5 Experiment 2a: Lucent Barker PHY - Equal SNR 25dB for both

connections, aRTSThreshold 500 bytes 64

3.6 Experiment 2b: Cisco CCK PHY - Equal SNR 25dB for both

connections, aRTSThreshold 500 bytes 64

3.7 Experiment 3a: Lucent Barker Code PHY - Unequal SNR Con

nection A 25dB and Connection B 20dB, aRTSThreshold 500

bytes 66

3.8 Experiment 3b: Cisco CCK PHY - Unequal SNR Connection A

20dB and Connection B 25dB, aRTSThreshold 500 bytes .... 66

3.9 Experiment 4: Lucent Barker Code PHY - Controlled SNR, aRT

SThreshold 500 bytes 67

3.10 Experiment 5a: Lucent Chipset CCK PHY - UDP Trace - both

connections 25dB 69

3.11 Experiment 5b: Cisco Chipset CCK PHY - UDP Trace - both

connections 25dB 70

LIST OF FIGURES xvi

3.12 Experiment 6a: Lucent CCK P H Y - UDP Trace - stronger host

(Connection A - 25dB) commencing prior to weaker host (Con

nection B - 20dB) 71

3.13 Experiment 6b: Cisco CCK PHY - UDP Trace - stronger host (Connection A - 25dB) commencing prior to weaker host (Con

nection B - 20dB) 71

3.14 Experiment 7a: Lucent CCK PHY UDP Trace - stronger host

(Connection A - 25dB) commencing after weaker host (Connec

tion B - 20dB) 72

3.15 Experiment 7b: Cisco CCK PHY - UDP Trace - stronger host

(Connection A - 25dB) commencing after weaker host (Connec

tion B - 20dB) 73

4.1 DSSS System Model (Pursley, 1977) 79

4.2 Autocorrelation function for 11-chip Barker sequence, +1,-1,+1,+1,-

1,+1,+1,+1,-1,-1,-1, employed in the 802.11 DSSS PHY 84

4.3 Correlator Output BER Experienced by ith Frame for 2 Mbit/s

Barker spreading code 87

4.4 Correlator Output BER Experienced by Initial Frame for 5.5

Mbit/s C C K Spreading Sequence Set 88

4.5 Correlator Output BER Experienced by Initial Frame for 11

Mbit/s CCK Spreading Sequence Set 89

4.6 Barker Code {K - 1) interferers, Ebk/N0 = 20dB 89

4.7 CCK codes, (K - 1) interferers, Ebk/N0 = 20dB 90

5.1 Potential Slot Time Error 97

5.2 Operation of the Message Retraining model 100

5.3 Trace Data UDP Transport: Lucent Chipset 105

5.4 No Capture Model UDP Transport 106

5.5 Delay Capture Model UDP Transport 107

5.6 Power Capture Model UDP Transport 107

LIST OF FIGURES xvii

5.7 Hybrid Capture Model UDP Transport 108

5.8 Message Retraining Capture Model UDP Transport 109

5.9 Trace Data TCP Transport: Lucent Chipset 110

5.10 No Capture Model TCP Transport Ill

5.11 Delay Model TCP Transport 112

5.12 Power Model TCP Transport 113

5.13 Hybrid Model TCP Transport 114

5.14 Message Retraining Model TCP Transport 114

5.15 UDP Experimental Data Trace obtained with Cisco chipset. Con

nection A commences with an SNR of 20dB 1 second later Con

nection B commences with an SNR of 25dB 119

5.16 Comparison of model fairness performance against experimental

UDP trace data. Top Figure is Jain's index, bottom Figure is

Kullback-Leibler index. Both indices illustrate the ability of the

Message Retraining model to provide an improved match with

empirical data with respect to the Power, Delay and Hybrid models 120

5.17 TCP Experimental Data Trace obtained with Cisco chipset. Con

nection B commences with an SNR of 20dB, 1 second later Con

nection A commences with an SNR of 25dB 121

5.18 Comparison of model fairness performance against experimental

TCP trace data. Top Figure is Jain's index, bottom Figure is

Kullback-Leibler index. Both indices illustrate the ability of the

Message Retraining model to provide an improved match with

empirical data with respect to other models for a fairness horizon

of less than 400 frames 122

6.1 Diagramatic representation of ECTS Suppression Scheme. Nodes

C and D are identified through group address as hidden from

Node A. Node B determines when an Enhanced CTS reply is re

quired to suppress Nodes C and D, allowing Node A fair channel

access. The duration set within the ECTS can be tuned to meet

the specific fairness objective 139

6.2 Three Node Hidden Terminal Topology 144

LIST OF FIGURES xviii

6.3 Three node topology, static scenario for p-Persistence on Backoff

Countdown algorithm using U D P - /3 — 0.25 146

6.4 Three node topology, static scenario for Probabilistic Discard

algorithm using U D P - 0 = 0.40 147

6.5 Three node topology, static scenario for enhanced CTS Suppres

sion algorithm using U D P - /3 = 0.75 149

6.6 Example received SNR trace during dynamic experiment .... 151

6.7 Three node topology, dynamic scenario for p-Persistence on Back

off Countdown algorithm using U D P /3 = 0.25 152

6.8 Three node topology, dynamic scenario for Probabilistic Discard

algorithm using U D P 0 = 0.30 154

6.9 Three node topology, dynamic scenario for Enhanced CTS Sup

pression algorithm using U D P j3 = 0.55 156

A.l Hidden Terminal Message Exchange Semantics. Node 3 observes

node 1 as hidden via C TS and A C K frames 178

A.2 STA 3 observes STA 1 as hidden through the timing constraints

places on C T S and A C K frames. In (a) STA 3 is not hidden from

STA 1, hence Duration and SA fields are consistent. In case (b)

where STA 3 is hidden from STA 1, the cached Duration and SA

fields will be inconsistent with the values observed in the C T S or A C K frames 180

A.3 STA 3 observes STA 1 as hidden as no RTS or DATA frames

have been received to update known neighbour list in STA 3. In

(a) STA 3 is not hidden from STA 1, hence STA 3 is able to

identify and maintain STA 1 in the known neighbours list. In

case (b) where STA 3 is hidden from STA 1, the R A within C TS

and A C K frames will not be found in the known neighbours list 181

B.l 3 node topology, static scenario for p-Persistence on Backoff Count

down algorithm using T C P - optimal /J = 0.25 184

B.2 3 node topology, static scenario for Probabilistic Discard algo

rithm using T C P - optimal j3 = 0.40 185

B.3 3 node topology, static scenario for Enhanced CTS Suppression

algorithm using T C P - optimal 0 = 0.55 186

LIST O F FIGURES xix

B.4 3 node topology, static scenario for p-Persistence on Backoff Count

down algorithm using T C P - optimal /? = 0.05 188

B.5 3 node topology, dynamic scenario for Probabilistic Discard al

gorithm using T C P - optimal /5 = 0.30 189

B.6 3 node topology, dynamic scenario for Enhanced CTS Suppres

sion algorithm using T C P - optimal /3 = 0.25 190

List of Tables

2.1 MAC protocol comparison matrix and summary 27

2.2 Modulation Techniques and Spreading Codes for 802.11 DSSS

PHY 34

2.3 802.11 DSSS PHY Parameters 35

2.4 QPSK Encoding Scheme 35

2.5 Comparison of Fairness Definitions 44

3.1 Summary of Experimental Trials 61

5.1 Modem Simulation Parameters 104

6.1 Comparison of improvement in fairness index and reduced aggre

gate normalised throughput for static and dynamic UDP scenar

ios with each fairness control technique 157

xx

Chapter 1

Introduction

1.1 Background

The recent explosion in popularity of local area wireless networks can be at

tributed to the availability of a standardised Medium Access Control (MAC)

and Physical Layer (PHY) protocol, the IEEE 802.11 standard for wireless Lo

cal Area Networks (LAN's). The standard initially defined a signalling rate of

2 Mbit/s, though several recent enhancements have resulted in the addition of

signalling rates up to 54 Mbit/s to the standard. Traditionally, wireless data

networks have been used in an access paradigm, in which terminals obtain access

to the fixed network via a centralised base station. In addition to the tradi

tional access paradigm, a new application has recently been developed based

on the Mobile A d Hoc Network ( M A N E T ) paradigm. A M A N E T allows nodes

to form a dynamic network configured to suit the application requirements of

participating nodes. Nodes within the network are able to act as both an end

terminal and a router, forwarding packets to the destination via neighbouring

nodes. The dynamic nature of a M A N E T is such that node mobility results

in an ever changing topology. In such circumstances, both hidden nodes and

varying propagation conditions are expected to present significant challenges

for the M A C protocol.

Further, wireless MAC protocols are currently being developed whose aim is

1

Introduction 2

to implement Quality of Service (QoS) mechanisms capable of supporting the

requirements of future demanding applications. Central to the provision of a

QoS guarantee, is the ability of the M A C protocol to provide fair channel access

for competing nodes across a range of scenarios. A significant cause of unfair

behaviour is the so called channel capture problem, in which a given host is able

to dominate the channel at the expense of other hosts in the network. In wireless

networks, this is further complicated by the intrinsic packet capture behaviour of

a radio receiver. Accordingly, a solid understanding of the relationship between

packet and channel capture behaviour, and the impact this has on the overall

fairness properties of the network is extremely important.

1.2 Thesis Outline

This thesis aims to provide a detailed investigation of the impact capture be

haviour has on the fairness properties exhibited in an IEEE 802.11 network.

Chapter 2 initially reviews the development of wireless M A C protocols, leading

to the IEEE 802.11 M A C / P H Y protocol. Following this, literature investigat

ing capture phenomena and related fairness issues is reviewed. In particular, a

lack of empirical work investigating the fairness properties of the IEEE 802.11

M A C in general topology scenarios is identified.

An experimental investigation of the fairness properties of a physical IEEE

802.11 network is presented in Chapter 3. The performance of the 802.11

M A C / P H Y protocol in general topology scenarios involving hidden terminals is

presented. Of specific interest is the ability of the M A C to provide fair channel

access for all competing connections through the R T S / C T S handshake designed

to set up clear transmission opportunities for competing hidden nodes. The im

pact of varying signal strength conditions on the performance of the protocol

are investigated in detail. Throughout this thesis, the terms node, host and

Station (STA) are used interchangeably. In general, the term S T A is employed

when discussing an issue directly related to the IEEE 802.11 standard.

Introduction 3

A significant observation from Chapter 3 is that the ability of the network to

avoid channel capture in hidden terminal scenarios is strongly dependent on

the relative received signal power between hidden connections. In response to

the observations in Chapter 3, Chapter 4 presents an analytic investigation of

the impact interfering transmissions have on the reception of an 802.11 frame.

The scenario under investigation is based on the topology employed in the

experimental investigation of Chapter 3. This analysis investigates the impact

a common code interfering signal has on the successful reception of a frame. The

results of this investigation confirm empirical measurements, indicating that a

difference of greater than 2dB is sufficient to afford preferential reception to a

stronger signal. This analysis has application in the development of appropriate

receiver models for accurate simulation of an IEEE 802.11 radio interface.

Chapter 5 investigates the necessary features required of a packet capture model

to match the empirical data when employed in a simulation environment. Fair

ness indices are employed as criteria to determine the ability of significant cap

ture models to match fairness characteristics of empirical trace data. A new

capture model, based on the design of a physical 802.11 R F front-end, is pro

posed to address shortcomings in current models. The outcome of Chapter 5 is

an accurate simulation technique with specific application in the development

of mechanisms to prevent the unfair behaviour observed in physical systems.

Combining the results of previous chapters, Chapter 6 develops techniques to

overcome the significant unfairness evident in hidden terminal scenarios. Given

the number of different P H Y protocols defined within the current IEEE 802.11

standard, the development of specific techniques to prevent such behaviour

within each P H Y is not practical. Any mechanism designed to prevent relative

signal power dependent unfairness must be able to operate with any P H Y ,

in the same manner as the M A C . Therefore, the techniques developed in this

chapter use information taken from the P H Y to provide the M A C with the

ability to identify and prevent relative signal power dependent unfair behaviour.

A mechanism to identify potential unfairness based on average relative signal

Introduction 4

power amongst neighbouring nodes is developed. This mechanism determines

a probability variable for each identified neighbour based on observations of

received signal power. This probability variable is then employed one of three

by techniques developed to provide additional transmission opportunities for

weaker nodes. The three techniques presented are:

• p-Persistence on Backoff Count down, in which the channel access prob

ability of offending nodes is controlled in proportion to their received

relative signal power

• Probabilistic Discard, in which a common node is able to discard RTS or

D A T A frames from offending nodes thereby forcing the offending node

into a backoff period

• Enhanced CTS Suppression, making use of a new interpretation of the

R T S / C T S exchange to enforce a suppression period on an offending node

The performance of each scheme is determined, along with analysis of imple

mentation issues within the IEEE 802.11 M A C framework.

Finally, Chapter 7 concludes the thesis with a summary of the major results

obtained in earlier chapters, as well as presenting a summary of related open

research issues in the area of wireless local area networks.

1.3 Contributions

Below is a list of the major contributions of this thesis, and the section in which

they appear. Relevant publications are also cited with each contribution.

1. Empirical investigation of fairness properties of a CSMA/CA MAC em

ploying an R T S / C T S / D A T A / A C K handshake (IEEE 802.11) using both

greedy U D P sources and T C P sources in hidden terminal topologies (Sec-

Introduction 5

tions 3.4 and 3.5) (Ware et al., 2000; Ware et al., 2001b; Ware and

Dutkiewicz, 2001)

2. Experimental analysis of fairness properties observed with hidden termi

nals in dynamic signal strength scenarios for an IEEE 802.11 wireless

local area network. This investigation identifies a 5dB threshold effect

in the fairness characteristics of the IEEE 802.11 M A C / P H Y protocol

(Sections 3.4 and 3.5) (Ware et al., 2000; Ware et al., 2001b; Ware and

Dutkiewicz, 2001)

3. Derivation of analytical expressions describing the characteristics of a hid

den terminal collision for the 802.11 1, 2, 5.5 and 11 Mbit/s physical layers,

assuming a B P S K modulated signal. This provides an analytical basis for

the threshold effect at 3-5 dB in the relative signal power based unfair

behaviour (Sections 4.3) (Ware et al., 2001a; Ware et al., 2001b)

4. Application of network layer fairness, measured through both Jain's Fair

ness Index (Jain et al., 1984) and the Kullback Leibler Index (Koksal et al.,

2000), in determining the suitability of packet capture models for accurate

802.11 network interface simulation. This work involves a detailed quanti

tative comparison of empirical data with simulation trace data generated

using Delay, Power, and Hybrid capture models (Sections 5.4 and 5.5).

The Delay, Power, and Hybrid capture models are shown to be unable

to accurately match the fairness characteristics of the empirical data in

terms of either magnitude or timescale of fairness behaviour (Ware et al.,

2001c; Ware et al., 2001d; Ware et al., 2001e)

5. Development and performance characterisation of the Message Retrain

ing capture model based on operation of IEEE 802.11 radio interface de

sign. This is developed in response to identified inadequacies in the Delay,

Power, and Hybrid packet capture models in terms of ability to match rel

evant fairness characteristics. The message retraining model is shown to

more accurately match the fairness characteristics, in terms of both fair

ness index magnitude and timescale of the empirical data, than the Delay,

Introduction 6

Power, and Hybrid models (Section 5.3) (Ware et al., 2001c; Ware et al.,

2001d; Ware et al., 2001e)

6. Development of the relative signal strength based heuristic technique to

identify unfair network conditions due to relative received signal power

differences in hidden terminals scenarios (Section 6.3)

7. Development and detailed performance investigation of the p-Persistence

on Backoff Count down fairness control mechanism (Section 6.4.1)

8. Development and detailed performance investigation of the Probabilistic

Discard mechanism to control relative received signal power dependent

unfairness (Section 6.4.2)

9. Development and detailed performance investigation of the Enhanced

C T S Suppression mechanism to control relative received signal power de

pendent unfairness (Section 6.4.3)

1.4 Publications

Publications arising from work directly related to this thesis are listed below:

Journal Publications

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001c). Simulating Capture

Behaviour in IEEE 802.11 Radio Modems. Journal of Telecommunications and

Information Technology.

International Conferences

Ware, C. G., Judge, J., Chicharo, J. F., and Dutkiewicz, E. (2000). Unfairness

and Capture Behaviour in 802.11 Adhoc Networks. In International Conference

on Communications, ICC 2000, volume 1, pp 159-163 New Orleans. IEEE Press.

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001a). Hidden Terminal

Jamming Problems in IEEE 802.11 Mobile Ad Hoc Networks. In International

Introduction 7

Conference on Communications, ICC 2001, volume 1, Helsinki.

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001e). Modelling Capture

Behaviour In IEEE 802.11 Radio Modems. In International Conference on

Telecommunications, ICT 2001, Special Sessions Volume, Bucharest. IEE /

IEEE.

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001d). Simulation of Capture

Behaviour In IEEE 802.11 Radio Modems. Vehicular Technology Conference,

Fall 2001, New Jersey. IEEE V T C FALL.

IEEE 802.11 Working Group Contributions

Document IEEE 802.11-01/058, "Network Capture and DCF QoS", Monterey

January 2001.

Document IEEE 802.11-01/232, "Packet Capture UDP Experiments", Florida,

May 2001.

Patents

Provisional Patent has been filed regarding the fairness control mechanisms

presented in Chapter 6

Journal Papers currently under review

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001b). On The Hidden Termi

nal Jamming Problem in IEEE 802.11 Ad Hoc Networks, submitted to: IEEE

Transactions on Vehicular Technology.

Chapter 2

Literature Review

2.1 Introduction

In recent years there has been a significant increase in the popularity of Wire

less LAN's, driven by the development of the IEEE 802.11 standard. Initially,

wireless LAN's were significantly slower than wired counterparts, operating at 1

or 2 Mbit/s. However, recent improvements in the IEEE 802.11 standard have

increased channel bit rates to 11 Mbit/s and with the addition of the 5.2 G H z

band and Orthogonal Frequency Division Multiplexing ( O F D M ) signalling, up

to 54 Mbit/s will be possible in the near future. With this increase in bit

rate, multimedia applications will inevitably be possible, and therefore issues

regarding quality of service and network fairness will come to the fore.

A further driving force behind local area wireless networking is the development

of the M A N E T . A M A N E T is a network in which nodes are mobile, and able

to form dynamic connections with neighbours. Nodes may even act as routers,

forwarding traffic through the network on behalf of other nodes. The Inter

net Engineering Task Force (IETF) are currently developing network routing

protocols which will allow a group of nodes to form a M A N E T .

The removal of the need for physical connectivity with the network introduces

great flexibility in the way users are able to interact with and use the network.

8

Literature Review 9

Fundamental to each of these developments is the performance of the P H Y

and M A C protocols used in each network interface. The combination of the

M A C and P H Y must be able to provide fair access to the channel, within the

constraints of the broadcast medium, and also within the physical constraints

of an R F signal environment. Fair access is required to allow the development

of suitable QoS mechanisms. In this thesis, a local area wireless network is

considered to constitute any wireless network that covers a local geographic

area, either a traditional base station - client style wireless L A N , or a M A N E T .

In this chapter, we review the current state of wireless MAC protocol research,

with a specific aim of identifying key research issues which remain to be ad

dressed. Section 2.2 provides an overview of current wireless M A C protocols

proposed in the literature. As the IEEE 802.11 protocol is the most widely

available, Section 2.3 describes in detail the operation of the M A C and P H Y

layers of the IEEE 802.11 protocol. As capture effects may adversely effect the

fairness properties of the network, Sections 2.4 and 2.5 review the current state

of capture model development and analysis, and literature on fairness properties

in wireless M A C protocols respectively. Section 2.6 outlines key research issues

remaining to be resolved.

2.2 Medium Access Control Protocols for Shared Wireless Media

Given recent advances in VLSI technology, bringing down the cost of compo

nents enabling high speed wireless packet networks, it comes as no surprise the

significant number of wireless M A C protocols having been proposed in litera

ture. Packet radio networks were first introduced in the late 1960's with the

A L O H A system (Abramson, 1970). However, a revolution has taken place in

recent years with the introduction of the IEEE 802.11 wireless L A N standard

(Institution of Electrical and Electronic Engineers, 1999a), and the ETSI Hiper-

L A N I standard (European Telecommunications Standards Intsitute, 1998).

Literature Review 10

M A C protocols perform a number of vital functions. The basic task is to de

termine when a transmit opportunity exists for each node, thereby providing a

mechanism to provide access to a shared medium for a large number of nodes. In

the case where a node is unable to transmit immediately, a backoff mechanism

is required. The M A C must also provide reliable data transfer through retrans

mission of lost frames. The M A C also provides an interface to the P H Y , acting

as a buffer between the network layer and the timing constraints introduced by

the P H Y .

In this review, we describe and categorise the mechanisms employed by signifi

cant M A C protocols proposed in literature. This should be considered as an in

troduction to the historical development of wireless M A C protocols. This review

will lead to the combination of various features that have been standardised in

the IEEE 802.11 (Institution of Electrical and Electronic Engineers, 1999a) and

HiperLAN (European Telecommunications Standards Intsitute, 1998) Wireless

L A N M A C standards. In this review, we restrict the discussion to random ac

cess approaches, as fixed assignment time division approaches have been shown

to be very inefficient when the number of terminals is large and each terminal

is transmitting a bursty traffic stream (Tobagi and Kleinrock, 1976). Further,

M A C protocols implemented in wireless LAN's today (Institution of Electri

cal and Electronic Engineers, 1999a),(European Telecommunications Standards

Intsitute, 1998) are based on random access approaches. While polling based ap

proaches (Section 2.2.1.2) may also be considered as fixed assignment schemes

when employed in certain scenarios, we are considering applications in both

wireless LAN's and M A N E T ' s in which dynamic random access is achieved us

ing a contention free polling mechanism. The aim of this discussion is to group

M A C protocols into relevant categories, identifying the important features of

each before highlighting mechanisms that have been incorporated into the M A C

protocols employed in current wireless LAN's and MANET's.


2.2.1 Access Mechanisms

The mechanism employed to determine when a node is able to transmit is

a fundamental property of the M A C protocol, and can be used to categorise

M A C protocols into two main groups. The first are those that rely on a physical

or virtual carrier sense (Kleinrock and Tobagi, 1975; Tobagi and Kleinrock,

1975; Kara, 1990; Fullmer and Garcia-Luna-Aceves, 1995), and the second

are those that rely on the reception of a polling beacon indicating a current

transmit opportunity (Tobagi and Kleinrock, 1976; Tzamaloukas and Garcia-

Luna-Aceves, 1999; Talucci et al., 1997; Garcia-Luna-Aceves and Tzamaloukas,

1999). Whether the node senses the physical channel, a separate signalling

channel or a virtual channel, the basic technique remains common: listen to the

channel, if an ongoing transmission is detected defer and backoff, otherwise this

is a potential transmission opportunity. The alternative is to rely on another

controlling entity to poll each node, indicating the transmit opportunity for the

polled node. In this section we outline the mechanisms employed by the major

M A C protocols.

2.2.1.1 Carrier Sense Approaches

A carrier sense mechanism provides a terminal with sufficient information to

prevent collisions occurring in the immediate area. The basic approach was

initially proposed and analysed by Tobagi and Kleinrock as an improvement

on slotted A L O H A , (Kleinrock and Tobagi, 1975). Carrier Sense Multiple Ac

cess (CSMA) is a multiple access technique where each node senses the channel

thereby avoiding collisions before transmission. A significant number of M A C

protocols have extended this approach (Tobagi and Kleinrock, 1975; Tobagi and

Kleinrock, 1976; Karn, 1990; Bharghavan et al., 1994; Fullmer and Garcia-Luna-

Aceves, 1995; Institution of Electrical and Electronic Engineers, 1999a; Euro

pean Telecommunications Standards Intsitute, 1998; W u et al., 2000), though

the basic carrier sense access mechanism remains the same.

CSMA has been proposed in both a p-persistent form, where a node transmits

3 0009 03287429 4


Unsuccessful Transmission

Vulnerable Period Successful Transmission

I I Node D - Busy channel, defer 2nd Collision - Node C

1st Collision - Node B

Busy Period \ Channel sensed idle Node A Transmission Attempt

Idle Period Busy Period All Stations Backoff Station A returns, senses idle

channel and transmits

Figure 2.1 Illustration of non-persistent C S M A Operation (Tobagi and Kleinrock, 1976)

onto an idle channel with probability p or defers to the next timeslot with prob

ability (1 — p), and a non-persistent form where a node will undertake a binary

exponential backoff on sensing a busy channel (backoff approaches will be dis

cussed in Section 2.2.2.1). The non-persistent form of C S M A is illustrated in

Figure 2.1. Each station senses the channel, and if no carrier is detected, trans

mission commences. The vulnerable period at the start of each transmission

period is the interval during which a carrier sense operation may not detect a

transmission having just commenced from another node. In Figure 2.1, node

A commences transmission on detection of an idle channel. Nodes B and C

also detecting an idle channel during the vulnerable period, commence trans

mission. Node D however, senses the channel after the vulnerable period, and

detecting carrier, enters a backoff state. Node A is the first to sense the channel

again after an idle backoff period, and there being no transmissions during the

vulnerable period, successfully transmits the packet.

The most significant problem for common channel carrier sense wireless MAC

protocols is known as the hidden terminal problem. Both the hidden terminal

and exposed terminal problems, have a significant impact on the performance


Q Node A

Carrier Sense- Idle Channel

Collision

Q NodeC

Carrier Sense- Idle Channel

Figure 2.2 The Hidden terminal problem, Node A and C cannot sense each other's carrier

of the C S M A protocol, reducing performance to a level equal with the A L O H A

protocol (Tobagi and Kleinrock, 1975). The hidden node problem arises when

two nodes attempting to communicate with a common node, are unable to

sense a carrier from each other. In Figure 2.2, nodes A and C are attempting

to transmit a frame to node B. Node A senses a clear channel and commences

transmission. Node C's carrier sense also finds the channel clear, and therefore

commences transmission. The result is a collision at node B which is unde

tectable by either node A or C. This is a significant problem, as neither node

A or C has any ability to prevent such a collision. Also, as all collisions occur

at the receiver, node A and C are forced to wait for a timeout on each packet

before retransmitting.

The exposed terminal problem, as illustrated in Figure 2.3, arises when a trans

mission from node B to node A prevents node C from transmitting, even when

the indented recipient from node C (i.e. node D ) is out of range of node A. In

this case, node C would be able to transmit without colliding with the trans-

o NodeB


/

i i i i J . — » .

t Carrier Sense - Busy Channel Cannot transmit to Node D

Figure 2.3 The Exposed terminal problem, Node B prevents Node C from transmitting

mission from B to A, but is prevented as the carrier sense operation detects the

transmission from B to A.

To solve the hidden terminal problem, a signalling mechanism is required to

indicate when a node intends to transmit a data packet. This will then allow

potential interferers an opportunity to defer a transmission that would oth

erwise resulted in a receiver side collision. C S M A with Collision Avoidance

( C S M A / C A ) (Colvin, 1983) was one of the first protocols proposing a mech

anism to implement such a handshake. The collision avoidance mechanism is

based around a control message handshake between the intending transmitter

and receiver. As illustrated in Figure 2.4, a Request-To-Send (RTS) message

is sent by the intending transmitter. The intended receiver then responds with

a Clear-To-Send (CTS) message indicating the transmitter may now send the

impending data frame. Nodes in range of either the transmitter or receiver will

receive the R T S or C T S message addressed to another node and will be able to

determine the duration of the impending transmission and defer until after this

transmission concludes. C S M A / C A is the basic access mechanism employed in

o Node A

o NodeB

Node D O o NodeC


0 Node A Node A Receives CTS

RTS CTS DATA

Idle Channel Send RTS

Node A Commences DATA Tx

0 NodeB RTS CTS DATA

Node B receives RTS, Responds with CTS

Node C Detects CTS, defers Tx

0 NodeC CTS

Figure 2.4 The Collision Avoidance handshake using RTS/CTS messages

IEEE 802.11.

2.2.1.2 Polling Based Approaches

The main alternative to C S M A style approaches, are those based on a polling

mechanism. A node is unable to transmit until it receives a token, or polling

beacon indicating a transmit opportunity. The mechanism must also include a

mechanism to add a new node to the polling list which is maintained by a cen

tralised node, such as a base station. This technique results in a contention free

transmission mechanism generally not requiring carrier sense for normal data

transmission. The allocation (or election) of the node controlling the polling

process provides a distinction between proposals of this type. In a wireless L A N

paradigm, a base station acts as a centralised co-ordinator, alternatively in an

ad hoc paradigm, the polling may be receiver based (Garcia-Luna-Aceves and

Tzamaloukas, 1999).

Analysis of the basic polling approach following a simple roll call process is

provided by (Tobagi and Kleinrock, 1976). This idea is extended to include a


separate reservation channel on which a station is able to request bandwidth.

The polling station places each request in a queue. Stations are then polled

in accordance with individual requests. The reservation channel may use a

contention mechanism, allowing stations to place themselves on the polling list.

This technique, termed Split Channel Reservation Multiple Access (SRMA) is

very similar in nature to the Point Co-Ordinate Function (PCF) adopted within

the IEEE 802.11 M A C .

Many schemes have been presented which attempt to reverse the collision avoid

ance mechanisms. Proposals such as Multiple Access Collision Avoidance By In

vitation (MACA-BI) (Talucci et al., 1997; Talucci and Gerla, 1997) and Receiver

Initiated Multiple Access (RIMA) (Garcia-Luna-Aceves and Tzamaloukas, 1999;

Tzamaloukas and Garcia-Luna-Aceves, 2001; Tzamaloukas, 2000) require each

station to poll surrounding nodes indicating a readiness to receive. While such

schemes have been shown to provide good performance in the presence of hid

den terminals, they require a potential receiver to have excellent knowledge of

a potential neighbours traffic pattern in the form of either a statistical history

or detailed traffic model. For this reason, receiver polling schemes are still in

the relatively early stages of development.

2.2.2 Signalling Mechanisms

As discussed in Section 2.2.1.1, solving the hidden node problem requires a

signalling mechanism to provide information about impending transmissions

for all nodes that may potentially cause interference. In this section, we out

line the two basic approaches used to solve this problem; mechanisms using a

common channel approach (Karn, 1990; Bharghavan et al., 1994; Fullmer and

Garcia-Luna-Aceves, 1995; Fullmer and Garcia-Luna-Aceves, 1997b; Fullmer

and Garcia-Luna-Aceves, 1997a), and those which split the available radio chan

nel and create a separate signalling channel. As outlined in Section 2.2.1.2, there

are also a group of schemes which attempt to reverse the collision avoidance

handshake, relying on the receiver to initiate a data transfer from an intending


transmitter (Tzamaloukas, 2000; Garcia-Luna-Aceves and Tzamaloukas, 1999;

Tzamaloukas and Garcia-Luna-Aceves, 2001; Talucci et al., 1997; Talucci and

Gerla, 1997). With the exception of the M A C A - B I scheme (Talucci et al., 1997;

Talucci and Gerla, 1997), schemes such as Receiver Initiated Collision Avoid

ance (RICA) are designed for slow frequency hopped channels (Tzamaloukas,

2000; Garcia-Luna-Aceves and Tzamaloukas, 1999) and will not be considered

further. Finally, we highlight likely performance issues for each scheme in real

network environments where transmission is unreliable. A significant shortcom

ing of work in this area is a lack of rigorous investigation in realistic propagation

environments.

2.2.2.1 Common Channel Signalling

A popular technique to overcome hidden terminal collisions is to use a common

channel signalling mechanism. The majority of schemes are based around the

RTS/CTS handshake, with C S M A / C A being the most simple protocol of this

type. As mentioned earlier, many protocols have extended the basic C S M A ac

cess technique to handle hidden node problems through a variety of signalling

handshakes. Another key feature of each single channel approach is the backoff

algorithm invoked when a busy channel is detected. The following discussion

highlights significant features of M A C protocols proposed in the literature em

ploying a common channel signalling technique.

(a) Multiple Access with Collision Avoidance - MACA

MACA was first proposed by Karn (Karn, 1990) as a new channel access tech

nique for packet radio, inspired by the C S M A / C A method which was used in

Apple Localtalk networks. The mechanism removes the carrier sense compo

nent of C S M A / C A . The author (Karn, 1990) argues that in cases where hidden

and exposed terminals are present, the carrier sense mechanism will provide an

inaccurate result at the receiver. A n indication that transmission is possible

when this may in fact result in a collision at the receiver, or vice versa, is highly

probable. A n R T S message is transmitted before every data frame. If a C T S


is not received, the sender will undergo binary exponential backoff where the

backoff counter is doubled every collision and reset to the minimum value on

successful transmission.

MACA was extended by Bharghavan (Bharghavan et al., 1994), with the ad

dition of a link layer positive acknowledgement (ACK) packet, and the inclu

sion of a mechanism to distribute backoff counter values amongst competing

nodes. The resulting protocol, M A C A W , is designed for a pico-cellular envi

ronment where hidden and exposed terminals are very common. The additions

to M A C A are in response to a channel capture state which may arise when

two stations compete for the same shared resource using standard M A C A . One

station is able to maintain a continuously lower average backoff window, and

therefore achieve access to the channel more frequently. The distribution of the

backoff counter value with each data packet forces each node to have the same

backoff window value at the start of the next contention period. The authors

(Bharghavan et al., 1994) claim this mechanism allows the M A C protocol to

distribute bandwidth fairly amongst nodes, though does so at the expense of

overall throughput.

In addition to this, the backoff mechanism was adjusted to implement a mul

tiplicative increase linear decrease algorithm rather than the binary exponen

tial backoff algorithm which can lead to significant oscillation in the backoff

window values. O n each collision, the backoff window is increased by a mul

tiplicative factor of 1.5, and decreased by 1 for each successful transmission.

Results presented in (Bharghavan et al., 1994) illustrate that the combination

of mechanisms included in M A C A W are able to overcome the channel capture

problem.

However, potential problems exist in exposed terminal configurations. The Data

Send (DS) packet was therefore introduced by the authors (Bharghavan et al.,

1994) to indicate that the R T S / C T S exchange was successful. This is designed

to alleviate cases where an exposed terminal cannot receive a C T S when the

common middle node is transmitting, effectively preventing the exposed node


from transmitting. The additional D S signalling packet is designed to increase

the robustness of the RTS/CTS exchange. Interestingly, there has been no

additional work on the inclusion of the additional signalling packet, and interest

in standardisation groups never materialised.

(b) Floor Acquisition Multiple Access - FAMA

FAMA, initially proposed by Garcia-Luna-Aceves, (Fullmer and Garcia-Luna-

Aceves, 1995; Fullmer and Garcia-Luna-Aceves, 1997b; Fullmer and Garcia-

Luna-Aceves, 1997a), is an attempt to unify many of the single channel RTS/CTS

based M A C protocols. The design of F A M A aims to overcome scenarios where

RTS, C T S and D A T A frames may collide, by forcing correct acquisition of the

'floor' prior to transmission (equivalent to the geographic area defined by the

transmission radius of a specified node). F A M A has been presented with a

number of variations:

1. FAMA employing RTS/CTS without carrier sense (Fullmer and Garcia-

Luna-Aceves, 1995). This is identical to the M A C A protocol.

2. F A M A - N C S employing RTS/CTS with a non-persistent carrier sense

mechanism (Fullmer and Garcia-Luna-Aceves, 1995; Fullmer and Garcia-

Luna-Aceves, 1997b). This is similar to the IEEE 802.11 C S M A / C A

approach, however, C T S packets are lengthened to be larger than the

aggregate of an RTS message, one maximum round trip time, transmit

to receive turnaround time, and any processing time. As illustrated in

Figure 2.5, this gives the C T S dominance over RTS messages. In the two

cases illustrated, station A either transmits an RTS frame just after or

before station B commences a C T S transmission. The length of the C T S

message has the effect of an in-band busy tone, jamming station A as a

potential interferer who will backoff after the unsuccessful RTS.

3. F A M A employing non-persistent packet sensing designed for a peer re

ceiver (Fullmer and Garcia-Luna-Aceves, 1997b; Fullmer and Garcia-Luna-

Aceves, 1997a). In this variant all stations are assumed to have the same


A

B

, *—*

RTS

i '

i

/ ' i

i ,

/

i

CTS

h *-

e - * •

receiver

e

4 i

noise/jamming at A

RTS| e

\ i

\ 1 \ 1 \ 1

\ 1

\ 1

» 1 I t > 1 1 i

1 /

>

< ••' >

/

CTS ;

t

i

e RX/TX turnaround time t Propagation delay

Figure 2.5 The F A M A CTS message dominates RTS messages. Host A will detect

the CTS message and backoff accordingly (Fullmer and Garcia-Luna-Aceves, 1997b)

functionality, following the M A N E T paradigm. Timing constraints are

quite tight in order to force correct 'acquisition' of the floor.

4. FAMA employing non-persistent packet sensing with a base station re

ceiver (Fullmer and Garcia-Luna-Aceves, 1997a). This scheme is similar

to the peer receiver scheme, though the timing constraints are relaxed on

the base station node when an RTS message is received. In this variant,

the base station is assumed to be able to sense carrier from all nodes, and

is the intended recipient of all frames from surrounding terminals.

Analytical performance studies (Fullmer and Garcia-Luna-Aceves, 1998) ap

plied to F A M A - N C S in an ad hoc network scenario illustrate that F A M A - N C S

outperforms A L O H A , C S M A , C S M A / C A , M A C A , and M A C A W when hid

den terminals are present in the network. In cases where no hidden terminals

are present, F A M A - N C S suffers with the extra overhead introduced by the ex

tended duration CTS. These results are not surprising, as F A M A - N C S is able


RTS DATA t2 tl

A and C hidden A and C hidden

Figure 2.6 Hidden terminal collisions with the RTS/CTS exchange. Transmission of the RTS at t2 by node C collides with the CTS from node B at t2, or the RTS from node C at t\ collides with the D A T A frame from node A. F A M A attempts to prevent collisions of this type by enforcing dominance of CTS messages over the RTS (Fullmer and Garcia-Luna-Aceves, 1995)

to prevent potential hidden interferers from transmitting, rather than reacting

to hidden terminal collisions as in the basic R T S / C T S approaches. This is il

lustrated in Figure 2.5 where F A M A attempts to prevent collisions of this type

through the extended duration of the C T S message. F A M A trades off increased

overhead against a reduced number of uncontrolled collisions. IEEE 802.11 out

lined in Section 2.3 does not use the lengthened C T S message, as the additional

overhead would significantly reduce effective network capacity.

2.2.2.2 Multi Channel Signalling

A second approach to the prevention of hidden terminal collisions is to split the

radio channel into separate data and control channels, using the control channel

exclusively to prevent potentially interfering transmissions.

Busy Tone Multiple Access (BTMA) was first proposed in the seminal paper

identifying the hidden terminal problem by Tobagi and Kleinrock (Tobagi and

Kleinrock, 1975). The basic operation of the protocol requires that the available

resource is split into a messaging channel and a busy tone channel. W h e n a

station senses carrier on the messaging channel, a tone is broadcast on the busy


tone channel. This is a receiver based scheme where each node that is receiving

a transmission is able to block any other node from colliding with the ongoing

transmission. Prior to transmission, a node will sense the busy tone channel,

and when carrier is detected, transmission will be deferred.

An extension to the BTMA concept has since been proposed, termed Dual

Busy Tone Multiple Access ( D B T M A ) (Deng and Haas, 1998; Deng and Haas,

1999). D B T M A includes a busy transmit tone, as well as a busy receive tone.

A separate control channel is also introduced, on which nodes will employ an

RTS/CTS exchange prior to an attempted transmission on the data channel. In

a similar manner to B T M A , a node will transmit a tone on the busy transmit

channel while transmitting, or on the busy receive tone while receiving. Before

transmitting an R T S message, a node will sense the busy receive channel. A

clear channel indicates that no nodes are receiving and the transmission can go

ahead. W h e n a node receives an RTS, it must sense the busy transmit channel

to ensure it is able to reply with a CTS. This basic mechanism is followed

for all transmissions. Combined with the RTS/CTS exchange, the mechanism

decouples the transmission directions allowing an otherwise exposed node to

transmit. Analysis of this mechanism (Deng and Haas, 1999) illustrates that

the benefit of continual channel sensing provided by the additional tones leads

to a throughput performance improvement over M A C A of up to 60-70% in

scenarios where hidden and exposed nodes are present.

Extension of the DBTMA protocol to include power control (Wu et al., 2000)

again shows further improvement in ad hoc network scenarios. Power control is

employed to manage the topology, thereby reducing the number of interfering

nodes for a given transmission pair. The RTS/CTS handshake is employed to

gauge the appropriate power level for the data transmission. A number of other

multi-channel M A C protocols (Nasipuri et al., 1999; Chandra et al., 2000; Tang

and Garcia-Luna-Aceves, 2000) have been proposed in the literature, however;

in terms of implementation, multi-channel M A C protocols are not popular.

Multi-channel mechanisms introduce significant complexity in the receiver, for


example D B T M A requires 3 separate channels, and also requires the receiver

to be capable of transmitting a busy tone at the same time as receiving a data

frame without causing interference to the data frame. This has been a significant

hurdle for R F interface designs to overcome. However, the recent development

of O F D M systems will potentially open the way for the implementation of

multichannel M A C protocols.

2.2.3 Collision Resolution Algorithms

The mechanism employed to resolve collisions can be broken into two ap

proaches; those employing a backoff mechanism, and those which employ per

sistence. Backoff mechanisms have long been the preferred collision resolution

mechanism in both wired and wireless M A C protocols. The most common

technique, originally applied in Ethernet C S M A / C D networks was a binary

exponential backoff, where the backoff period was successively doubled each

time a busy medium or collision is detected. Binary exponential backoff has

been shown to be unfair in many cases (Bharghavan et al., 1994) and may lead

to a channel capture state where one station is able to maintain a statistically

lower average backoff counter, thereby gaining preferential access to the channel.

Improvements have been made to this basic algorithm, for example the Multi

plicative Increase, Linear Decrease (MILD) approach presented by Bharghavan

(Bharghavan et al., 1994). A backoff distribution algorithm is also presented by

the authors (Bharghavan et al, 1994) to prevent a station from maintaining a

continuously lower backoff counter than surrounding neighbours. The approach

taken in the IEEE 802.11 M A C is to use a backoff period dictated by a uniform

random variable drawn on [0,CWmax\. CWmax increases exponentially with

each successive backoff.

Persistence approaches can considered to be a statistical technique of imple

menting a backoff counter (Cali and Gregori, 2000; Geraniotis and Soroushne-

jad, 1987). Each station attempts to access the channel, and on finding a clear

channel will transmit with a probability of p, or defers for a slot time with prob-


ability (1 — p). W h e n a busy channel is detected, the station delays transition

by a single slot time. If the channel is detected free after the deferred period,

the same process is repeated. If the channel is busy, the station will continue

waiting until the channel is free, then engage in the channel access procedure.

This technique combines the contention resolution algorithm with the channel

access mechanism.

The application of a persistence technique has the disadvantage of requiring sta

tions to generate a pseudo-random variable prior to each packet transmission.

However, persistence techniques are considered to have superior fairness proper

ties and resilience to channel capture behaviour often observed with exponential

backoff mechanisms (Bharghavan et al., 1994).

2.2.4 QoS Mechanisms

Recently, the inclusion of mechanisms to support quality of service differenti

ation at the M A C layer has become an important feature of a wireless M A C

protocol. From the preceding discussion, it is evident that most M A C protocols

proposed in recent years have been designed with best effort traffic in mind.

This is partially a result of the difficulty involved in building a physical wireless

packet network, and the lack of a need historically for quality of service differ

entiation. This is no longer the case, and a number of M A C protocols and QoS

mechanisms have been developed recently to address this need.

Transmission scheduling approaches have been presented in (Lu et al., 1999;

Luo et al., 2000). These schemes rely on nodes to schedule the transmission

of data packets and are generally considered as a network wide optimisation

problem that, given the level of complexity, must be solved using approximate

methods. The most common approaches are based on the use of utility func

tions. Scheduling mechanisms of this type typically attempt to provide bounds

on throughput, delay, delay jitter, and loss for individual traffic stream. The

main drawback of such approaches is the requirement for accurate distributed

knowledge of the network state. This limits the ability of the scheduling ap-


proach to maintain a steady state, particularly in a dynamic network.

Tiered contention or virtual MAC schemes are currently being considered for

inclusion in the IEEE 802.11 M A C protocol (Chesson et al., 2001). In schemes

of this type, each node maintains a number of M A C queues, with a virtual

C S M A / C A M A C applied on each queue. Differentiation between streams is

achieved by weighting the deferral period between detection of an idle channel

and eventual transmission (the DIFS in the case of 802.11). A higher priority

queue has a shorter interval, and will generally be served before a lower priority

queue. This results in a statistically higher throughput for classes with a lower

deferral period. Disadvantages with a tiered contention approach include an

inability to provide bounds or guarantees on delay, throughput, or delay jitter.

The quality of service provided is in the form of differentiation between service

classes.

Group Allocation Multiple Access (GAMA) has been proposed in (Muir and

Garcia-Luna-Aceves, 1997) as a technique to provide guarantees to real time

traffic through the allocation of groups. Nodes are allocated positions in a

transmission group. The channel is divided into a contention period, and a

group transmission period. Each node uses the RTS/CTS exchange during the

contention period to assert a position within a group, corresponding to a trans

mit opportunity within the group transmission period. Each node maintains a

group position while it has data to transmit.

A similar, more rigorous scheme termed Black Burst Contention is presented

by the authors of (Sobrinho and Krishnakumar, 1999). In this scheme, nodes

contend for the channel using a Black Burst (BB) jamming tone of a length pro

portional to the period of time the impending packet has been queued. Each

node senses the channel at the end of a B B to determine if it was the longest of

the contending BB's. The winning node then transmits the impending packet

without delay, while other nodes wait for the channel to become idle again, be

fore commencing another round of BB's. Nodes requiring time bounded service

employ this method, while nodes carrying best effort traffic revert to standard


C S M A / C A . This scheme is shown to provide an upper bound on delay for real

time traffic, without significantly increasing average delay for best effort traffic.

The performance of B B Contention and G A M A with hidden nodes has not been

established. The analysis presented thus far in the literature assumes all nodes

have perfect carrier sense information.

Ideas from both GAMA and the BB Contention MAC have been incorporated

in Elimination Yield Non-pre-emptive Priority Multiple Access (EY-NPMA),

which has been included as the primary M A C in the HiperLAN I standard (Eu

ropean Telecommunications Standards Intsitute, 1998). This approach can be

based on either a synchronised channel access cycle which includes a number of

distinct phases to establish priority amongst contending nodes prior to trans

mission, or a channel free access cycle containing only the transmission phase

as illustrated in Figure 2.7. In the synchronised access cycle, the role of the

Prioritisation phase is to allow each node to establish the priority of impending

transmissions. Nodes surviving this phase all have an equal priority transmis

sion pending. The Elimination phase then eliminates as many as possible of

the remaining nodes. The Yield phase is the final stage in this process, com

plementing the elimination phase by resolving any further contention. Finally,

the transmission phase allows transmission for the successful node.

This is quite a complex approach to a distributed MAC QoS mechanism, though

several researchers have illustrated that the E Y - N P M A M A C is able to pro

vide reasonable, stable performance for higher priority streams (Anastasi et al.,

2000).

2.2.5 MAC Comparison Matrix

Table 2.1 provides a summary and a useful comparison of the MAC protocols

presented in this section in terms of the salient features identified in the preced

ing discussion. That is, each M A C protocol is classified in terms of the access

technique, signalling mechanism, and the QoS mechanism employed.


03

=3 CO

X • -H SH

c3

(=1 O CO i-i

o3 ft

a o CJ

"o u o +3

o FH

ft

U m

i — i

F Q

0

a • FH

a CO

.a o

CO

o

or

a • F H

F-H

a a bX)

• FH

CO

CD

a • FH

a Fa u

8 CO CO CD

u u < o o 0 FH

OH

O

CO

a o I=I

a CI 03

.a o a o

a a o CJ

co

a o a

co i=l

o a

a a a CJ

a o

a a o

CO

a o a

1

co a o a

hO

a CO =3

a <$ a a «3 M

.FH "-1

H-=

13 & FO T—1

a

co a eg a Si ^ CO _FH

CO *§ CO >> • H CO

£ a 03 -Q

o

H PQ

CO

a o a

faC

a , --H

CO !=H

a «§ a a • -H «

-a * a ce

H

CO CO

a CO CO F H

CO • F H F H

FH

03 CJ

a -a

H PQ Q

CO

a o a

a a o3

.a o a o

a a o CJ

a • H

ft

l-H

CQ i

<

CO

a o a

r—H

CO

a a 03

•6 a o

a a o CO

FH co a ci

o § ., - F H

si FH a CO 03 03 F-,

" 13

<

time bounded

transmission

"co

a a 03 Fa CJ

a o

a a o o

a o

• F-H

03 H-3

co a co S

a « M Is FH CO

CO 03 •C FO

«3 & CJ a

o FH

bO

<

time bounded

transmission

"co

a a 03

-a CJ

a o

a a o CJ

Fa a

•S -2

< ° co a O FQ

a o

• F H

a CO

-s o O PQ PQ

possible EDCF

HCF combines EDCF and scheduler

a

•s a o

a a o CJ

-a a o3

O O

CO

O

i-H H

CN O 00

2 •FH

a o

• F H

-F^

03

a

a 3

"co

a a o3 Fa CJ

a o

a a o CJ <

Pu

F—1

F5

< F-3

OH h—1


1

«= 9»

Prioritisation Phase

3hase < >

Phase ^ >

< ;»<

Contention Phase

Transmission Phase

Channel Free Channel Access Cycle

—=»

|

Synchronised Channel Access Cycle

Figure 2.7 Elimination Yield N M P A Channel Access Cycles (European Telecommunications Standards Intsitute, 1998)

2.3 The IEEE 802.11 MAC/PHY Protocol

The IEEE 802.11 standard (Institution of Electrical and Electronic Engineers,

1999a), combined with subsequent enhancements, 802.11b (Institution of Elec

trical and Electronic Engineers, 1999b) and 802.11a (Institution of Electrical

and Electronic Engineers, 1999c), defines a M A C Protocol, and four distinct

P H Y protocols. This includes; an Infra-Red (IR) P H Y , a Frequency Hopping

Spread Spectrum (FHSS) P H Y operating in the 2.4 G H z Industrial Scientific

and Medical (ISM) band, a Direct Sequence Spread Spectrum (DSSS) P H Y

in the same 2.4 G H z ISM band, and a P H Y operating in the 5.2 G H z ISM

band employing Orthogonal Frequency Division Multiplexing ( O F D M ) . In the

following sections, the basic operation of the M A C protocol and DSSS P H Y are

outlined. Future planned enhancements are discussed in Sections 2.3.1.3 and

2.3.3.


2.3.1 Medium Access Control Layer

The MAC layer within 802.11 employs one of two distinct techniques to solve

the multiple access problem. The first, a distributed contention based approach

employing C S M A / C A , is termed the Distributed Co-ordinate Function (DCF)

and is described in Section 2.3.1.1. The second is a contention free polling

based mechanism, termed the Point Co-ordinate Function (PCF), and will be

described in Section 2.3.1.2.

2.3.1.1 Distributed Co-ordinate Function

The Distributed Co-ordinate Function (DCF) is a contention based approach

employing C S M A / C A with a random backoff time following the detection of

a busy channel. All D A T A frame transmissions are immediately positively ac

knowledged by an A C K frame. The sender is then able to schedule retransmis

sion of the D A T A frame if an A C K is not received within a specified time. The

basic access mechanism is described as follows:

1. Prior to a Station (STA) transmitting, the medium is sensed to determine

if another STA is transmitting

2. If the medium is determined to be busy, the STA will defer until the end

of the current transmission then undergo a backoff period governed by

equation (2.1) before attempting retransmission

3. If the medium is determined to be free, the STA will defer for a D C F Inter-

Frame Space (DIFS) period, ensuring the media has been idle throughout

this period before transmitting the frame

Timing relationships are illustrated in Figure 2.8. Two additional guard times

are shown in this Figure; the Short InterFrame Space (SIFS) used to separate a

D A T A and A C K frame, and the Point Coordination Function InterFrame Space

(PIFS) used by the Point Co-ordinator in the Point Co-ordination Function

mode. Several enhancements to the C S M A / C A mechanism are also included.


Immediate access when medium is free > DIFS

DCS

Busy Medium

DIFS Contention Window

Backoff Window Next Frame

Defer Access

Slot time

Select Slot and Decrement Backoff as long as medium is idle

Figure 2.8 Interframe Space Relationships (Institution of Electrical and Electronic Engineers, 1999a)

A Request-to-Send (RTS) and Clear-to-Send (CTS) exchange may be employed

prior to the transmission of a M A C Protocol Data Unit ( M P D U ) or M A C

Management Protocol Data Unit ( M M P D U ) . As described in Section 2.2.2, the

RTS/CTS exchange is a mechanism to prevent hidden terminal collisions, by

way of reservation of the Wireless Medium ( W M ) for the duration of the planned

D A T A transmission. Several simulation studies (Gerla et al., 1999b; Fullmer

and Garcia-Luna-Aceves, 1997a; Bharghavan et al., 1994) have illustrated that

the RTS/CTS exchange is able to provide good immunity to hidden terminal

collisions in cases, whilst maintaining good fairness properties. W e investigate

the performance of this mechanism in later sections of this thesis.

Virtual carrier sense is employed through the Network Allocation Vector (NAV).

The N A V is a counter which counts down to zero, representing the time at

which the wireless medium will become idle. RTS, CTS, and D A T A frames

may set the N A V of an STA with the Duration field, indicating the period of

time the impending transmission will occupy the W M . Figure 2.9 illustrates the

RTS/CTS handshake, and setting of the N A V for neighbouring stations. When

a station senses the W M , the N A V is also checked. If the counter is zero the

W M is considered idle, and when non-zero the W M is considered busy. The

carrier sense operation combines the physical detection and virtual carrier sense

indication to determine the state of the W M .


Source

DIFS

RTS

Destination

Other

SIFS SIFS

CTS

DATA

SIFS

ACK

N A V (RTS)

N A V (CTS)

Defer Access

DIFS Contention Window

/ / /

Backoff After

Defer

Figure 2.9 RTS/CTS/DATA/ACK and N A V Setting. 'Other' node is a node within range of either Source or Destination. Receipt of RTS or C T S M M P D U will set N A V accordingly (Institution of Electrical and Electronic Engineers, 1999a)

A random backoff mechanism is used for all PDU's (with the exception of

A C K frames) when carrier sense indicates a busy channel. The backoff pe

riod commences once an S T A has deferred through an impending transmis

sion, then determined the medium to be free for a DIFS period. A random

value, RandomQ, is drawn from a uniform distribution on the interval [0, C W ]

where C W represents the current Contention Window, an integer in the range

[CWmin, CWmax]. aSlotTime is a Management Information Base (MIB) vari

able defined independently for each P H Y . With each successive backoff, CW is

increased exponentially. The backoff interval is then calculated as:

Backoff Time = RandomQ x aSlotTime (2.1)

The D C F can operate in either an Access Point (AP) mode, where each station

is associated with an AP, or in an ad hoc mode where peer-to-peer connections

are made possible with each neighbour by the distributed nature of the D C F .

In this case, the D C F M A C is reasonably well suited to the M A N E T multiple

access application.


Contention Free Repetition Interval

Contention Free Period

SIFS SIFS SIFS PIFS SIFS

Beacon Dl + Poll D2 + ACK

+ poll

D3+ACK

+poIl D 4 + poll

D x = Frames sent by Point Co-oidinator Ux = Frames sent by polled stations

— Contention Period

PIFS

NAV

Ul+ACK + poll U2 + ACK

U4 + ACK CF-END

Reset NAV SIFS SIFS SIFS

Figure 2.10 PCF Frame Exchange Sequence (Institution of Electrical and Electronic Engineers, 1999a)

2.3.1.2 Point Co-ordinate Function

The Point Co-ordinate Function (PCF) is a mechanism to provide contention

free M P D U transfer. In this mode, the A P assumes the role of a Point Co

ordinator (PC), which by implication prohibits ad hoc mode operation. Fig

ure 2.10 illustrates the polling technique, and the co-existence of the Contention

Free Period (CFP) with the Contention Period (CP). The P C maintains a

polling list of STA's to poll during the CFP. STA's are able to request ad

dition to the polling list during the CP. A beacon frame is used to signify the

start of the CFP. During the C F P the P C sequentially sends any D A T A frames

along with a polling beacon to each STA on the polling list. STA's respond

with a D A T A frame (if there is D A T A to send). ACK's are piggy backed onto

D A T A frames, along with Polling frames from the AP.

During the CFP, the NAV is set to the duration of the CFP by the point

co-ordinator. This effectively prevents any station transmitting during this

period without the permission of the point co-ordinator. Non CF-Pollable STA's

are able to operate as normal, with the C F P appearing as a (large) single

transmission. This mechanism, while being complex, is very stable under high


load.

2.3.1.3 Future QoS Extensions

Currently, the IEEE 802.11 Working Group (WG) is making a significant effort

to add QoS mechanisms to the 802.11 M A C protocols (TGe, 2001). Extensions

are currently under development for the D C F (Chesson et al., 2001), along with

a new M A C termed the Hybrid Co-Ordinate Function (HCF) (Fischer, 2001).

The H C F is designed operate in place of the P C F to provide a centralised QoS

enabled M A C . The tiered contention, or virtual D C F scheme (Chesson et al.,

2001) discussed in Section 2.2.4 is currently quite advanced through the IEEE

802.11 W G , though a final QoS enhancement for 802.11 is still in early stages

of development. A final QoS standard is anticipated for early 2002.

2.3.2 Direct Sequence Spread Spectrum Physical Layer

The DSSS PHY in 802.11 currently provides 4 different bit rates. As illustrated

in Table 2.2, each of the 4 data rates employ a unique combination of modulation

technique and spreading code to achieve the desired symbol rate, and number of

bits per symbol. The Basic Rate (BR) comprises the 1 and 2 Mbit/s data rates,

and employs a Barker spreading code with D B P S K or D Q P S K respectively.

The common 11 chip code used by all stations for both the 1 and 2 Mbit/s

physical layers is:

-r-1,-1,+1,+1,-1,+1,+1,+1,-1,-1,-1

The High Rate DSSS (HR-DSSS) physical layer, comprising the 5.5 and 11

Mbit/s rates, employs Complementary Code Keying (CCK) with a spreading

code of length 8, generated by a generalised Hadamard transform, Equation

(2.2), where 4>i is added to all code chips, <j)2 to all odd code chips, 03 to all odd

pairs, and 04 to all odd quads of code chips. In each case, the chipping rate is


Table 2.2 Modulation Techniques and Spreading Codes for 802.11 DSSS PHY

Bit Rate (Mbit/s)

1 2 5.5 11

Coding Scheme

Barker Sequence (11 Chip) Barker Sequence (11 Chip) CCK or optional BCC CCK or optional BCC

Modulation Technique

DBPSK DQPSK DQPSK QPSK

Bits per Symbol

1 2 4 8

11 Mchip/sec.

c _ eJ(<t>l+<p2+(t>3+(p4) eJ(01+03+04) eJ{<t>l+<t>2 + <t>i)

_eJ(</»l+04) eJ(<t>l+<t>2 + <!>3) eJ{<Pl+<l>3) _ g j ( 0 1 + 0 2 ) eJ4>l (2.2)

Equation (2.2) is used to create 8 complex chips (c0 to CT) with c0 transmitted

first in time. For CCK 5.5 Mbit/s modulation at 4 bits/symbol, 0i is encoded

by data bits d0 and d\ based on DQPSK. Data bits d2 and d3 CCK encode the

basic symbol by:

02 = d2 X 7T + | (2.3)

03 = 0 (2.4)

04 = di X 7T (2.5)

This leads to a family of 16 distinct spreading sequences which are used to

indicate the symbol transferred.

Table 2.3 lists several key parameter values for the DSSS PHY.

For CCK 11Mbit/sec modulation (at 8 bits/symbol), 0i is again encoded by

d0 and dl using DQPSK. Data bits (d2,dz), (d4,d5),and (d6,d7) are used to

QPSK encode 02, 03, and 04 respectively, as shown in Table 2.4 This leads to

a matrix of 256 spreading sequences, which support the transmission of 8 bits

per symbol.


Table 2.3 802.11 DSSS PHY Parameters

Parameter

aSlotTime aSIFSTime aCCATime aCWmin aCWmax DIFS PIFS EIFS

Value

20 /is 10 lis < 15/zs

31 1023

aSIFSTime + 2 x aSlotTime aSIFSTime + aSlotTime aSIFS + (8xACKSize)

Table 2.4 QPSK Encoding Scheme

Bit Pattem[di, di+i]

00 01 10 11

Phase

0 TT/2

7T

3TT/2


2.3.3 Future Extensions to 802.11 P H Y

Work is already underway within the IEEE 802.11 WG to extend bit rates

supported by the P H Y protocol (Webster and Halford, 2000; Institution of

Electrical and Electronic Engineers, 1999c). The first of these is the recently

standardised 802.11a (Institution of Electrical and Electronic Engineers, 1999c)

employing an O F D M physical layer at 5.2 GHz. The O F D M P H Y employs

52 sub-carriers, spaced at 0.3125 M H z intervals within the allocated frequency

band, comprising 48 data sub-carriers and 4 pilot sub-carriers. Prior to trans

mission, the data is encoded, interleaved, then mapped to a series of complex

numbers according to the BPSK, Q P S K , 16-QAM, or 64-QAM encoding ta

ble. A n inverse Fourier transform is then performed on the data stream, and

the result mapped to the 48 data sub-carriers to form the O F D M symbol for

transmission. The receiver essentially reverses this operation. The choice of

modulation technique is based on the bit rate required.

There are also a number of additional extensions to the 802.11 standard under

development. In addition to the QoS mechanisms mentioned in Section 2.3.1.3,

there is a proposal before the 802.11 W G aiming to provide bit rates beyond

11 Mbit/s in the 2.4 G H z band (Webster and Halford, 2000). A power control

mechanism is also under development, with two competing proposals (Hansen

et al., 2001; Choi et al., 2001) currently before the working group.

2.4 Packet and Channel Capture Phenomena in Wireless Networks

Capture behaviour is a crucial aspect of the performance characteristic of any

practical wireless network. T w o distinct capture phenomena can be identified:

Packet Capture, and Protocol Capture. In the following discussion, we review

both capture phenomena, describing the significance of each in the context of a

wireless M A C protocol.


2.4.1 Packet Capture

Packet, or modem capture is a result of the ability of a modem to 'lock' onto a

signal in the presence of received interference caused by either an external noise

source or another transmission within the same region. This behaviour is a re

sult of the combination of both m o d e m design and the P H Y protocol employed.

In particular, both Frequency Modulation and Spread Spectrum receivers which

use a phase locked loop or correlation detection circuit display this ability (Rap-

paport, 1996). A number of authors have illustrated the improved throughput

performance of a network with some form of capture capability, with (Lau and

Leung, 1992; Arnbak, 1987; Goodman and Saleh, 1987) representing the most

significant work in this area. In each case, the approach has been to determine

the improvement in channel throughput a specific capture model may provide.

This is outlined in the following section.

2.4.2 Capture Probability Analysis

Over the past 25 years, a significant body of literature has developed investi

gating the impact packet capture behaviour has on network throughput across

a range of scenarios. The original wireless M A C protocol, A L O H A , was first

analysed in the late 70's by Abramson (Abramson, 1977). In this seminal paper,

Abramson determined the throughput performance of both a pure and slotted

A L O H A system employing a very basic capture model. The model dictates the

successful reception of a packet transmitted from a distance r from the receiver

unless overlapped by another packet broadcast from another user at a distance

slightly greater than r. In the latter case, both packets would be lost at the re

ceiver. The analysis presented in (Abramson, 1977) illustrates how the capture

effect increases the throughput obtained for users inside a critical radius, the so

called Sisyphus distance, outside which a user would expect to receive little or

no access to the slotted A L O H A channel.

Goodman and Saleh also identified the Near-Far effect in slotted ALOHA

(Goodman and Saleh, 1987), in which stations closer to the receiver are able


to achieve higher throughput than stations at a greater distance from the re

ceiver. The authors illustrate that under a Poisson traffic assumption for all

nodes in the network, capture has a beneficial impact on system throughput,

helping all nodes including those further from the base station to achieve higher

throughput than would otherwise be the case.

These fundamental results (Abramson, 1977; Goodman and Saleh, 1987) have

since formed the basis of almost all published work investigating the perfor

mance of wireless M A C protocols, for example (Davis and Gronemeyer, 1980;

Arnbak, 1987; Lau and Leung, 1992; Cheun and Kim, 1998). The general

technique employed throughout the literature is to determine the probability

with which a packet will be captured by the receiver, then determine channel

throughput as the product of offered load and capture probability. This involves

assuming a model for the packet arrival process, node distribution, and signal

fading or variation. Three main capture models have since been assumed:

Delay Capture in which the arrival time of each packet is randomised

over a defined interval, corresponding to the different propagation delays

experienced by packets emanating from nodes at different distances from

the receiver (Davis and Gronemeyer, 1980). The first arriving packet is

assumed to be captured by the receiver if no other packet arrives within

the acquisition time required by the receiver to successfully detect and

commence reception of the first packet.

Power Capture in which the strongest packet arriving in a timeslot is

received, provided that the strongest packet has a power that is greater

than the sum of all other packets by at least the capture ratio (Arnbak,

1987). This model requires the assumption that each signal varies quickly

enough to allow incoherent addition of the phasors of each signal. This is

the most common model used in simulation of wireless receivers.

Hybrid Capture combining the power and delay capture models (Cheun

and Kim, 1998). This model attempts to describe the behaviour of a re-


ceiver more accurately, by allowing the first frame to be received provided

that the total power received during the acquisition time is less than the

first arriving packet by at least the capture threshold. This approach at

tempts to model the operation of a spread spectrum receiver having good

noise immunity during the initial detection and synchronisation stages of

reception.

Capture probability analysis is based on modelling the operation of an ideal

receiver. In each case, only the initial capture probability is analysed, making no

guarantees with regard to the retention of the packet once capture has occurred.

A n opportunity exists to compare the performance of simulation models with

empirical measurements from a physical network, and subsequently investigate

the fairness properties of a network with packet capture capabilities. A further

opportunity exists to identify appropriate characteristics of a simulation model

for an IEEE 802.11 DSSS receiver.

2.4.3 Channel Capture

Protocol, or channel, capture is a state that may arise when a given host is

able to monopolise the channel at the expense of contending hosts. This is typ

ically the result of interactions between timers at various protocol layers (Gerla

et al., 1999b; Gerla et al., 1999a; Tang and Gerla, 1999; Holland and Vaidya,

1999). In particular, the Transport Control Protocol (TCP) is quite vulnerable

to the interaction between transport layer timers and the M A C layer. This

sensitivity is multiplied in a multihop wireless network, where repeated channel

contention severely affects transport layer timers. Delayed acknowledgements

are often treated as a sign of congestion, when in fact the channel may have

been in a capture state. The resulting backoff period and transmission window

reductions will, in effect, contribute to the capture state by preventing the host

from transmitting when it may have been able to do so. This is a separate

problem from that of acknowledgement or data frames that are affected by an

error burst and incorrectly interpreted as congestion by the sender.


The authors of (Gerla et al., 1999b; Gerla et al., 1999a) have performed a sim

ulation study of T C P performance over various wireless network architectures,

focusing on interactions with the M A C layer. Three different M A C protocols

are investigated, C S M A / C A , Multiple Access Collision Avoidance for Wireless

( M A C A W ) (Bharghavan et al., 1994), and Floor Acquisition Multiple Access

(FAMA) (Fullmer and Garcia-Luna-Aceves, 1995). Their results indicate that

in many circumstances, T C P requires a window size of 1 packet (effectively

becoming a stop and wait protocol) in order to achieve any throughput across

a multiple number of hops. Further experimental investigation has illustrated

that T C P does not alleviate, and may even complicate, channel capture when

the hidden terminal problem arises while using a non reservation based M A C

protocol.

Simulation experiments performed by the authors of (Gerla et al., 1999b), fo

cus on interactions between the M A C and transport layer protocols in multihop

scenarios. This work also includes an experimental component, in which pro

prietary (non-802.11) C S M A / C A wireless L A N equipment is used to examine

the protocol channel capture problem. Nodes were arranged in a square topol

ogy, with single hop connections along each side of the square as illustrated

in Figure 2.11. This topology combines the hidden and exposed terminals.

The results indicate how protocol timers interact and result in protocol capture

states. The M A C protocol employed did not include an RTS/CTS signalling

mechanism, allowing the T C P retransmission timers to interact with the M A C

backoff mechanism. In each trial, a single connection was able to gain signifi

cantly greater channel access than the other three. As this behaviour is a result

of protocol interaction between two connections competing for a common re

ceiver, a simpler topology with a single pair of hidden terminals will provide the

same result when no signalling mechanism is employed to minimise the impact

of hidden terminal collisions.

Tang (Tang and Gerla, 1999) presented simulation results which illustrate that

the C S M A / C A with an R T S / C T S / D A T A / A C K 4 way handshake is able to


o ••a

GO

V

TCP Stream A

Hidden s/

.•' Terminals '•.

TCP Stream C

H

n on

u w

Figure 2.11 Square Experimental Topology (Gerla et al., 1999a)

provide fair channel access in hidden terminal scenarios. The simulation envi

ronment used in (Gerla et al., 1999b; Gerla et al., 1999a; Tang and Gerla, 1999)

is based on an ideal channel, in which each host receives all intended packets

without error, and with a fixed propagation delay. Using an ideal channel does

not allow the authors to investigate the impact that varying radio conditions

may have on the performance of the protocols. A n accurate indication of per

formance in a true mobile environment, in which signal detection and reception

are unreliable, and propagation delays are constantly changing is required.

Both packet and channel capture effects can be expected to have an impact on

the fairness properties of the network. Accordingly, we present a discussion of

work investigating the fairness properties of wireless networks.

2.5 Investigation of the Fairness Properties of Wireless LAN's

Unfair behaviour in wireless networks can result from of a number of distinct

physical effects and protocol interactions. The combination of protocol induced

channel capture, hidden terminal collisions, and m o d e m capture can result in

significant unfairness for hosts in a general topology wireless network. Recently,


a number of publications have appeared in the literature examining fairness

problems in wireless networks from both an experimental and analytical view

point. This literature can be divided into two groups. The first, discussed

in Section 2.5.2, investigates the performance of a variety of M A C protocols

but do not propose mechanisms to overcome the identified unfairness. The

second group, discussed in Section 2.5.3, propose algorithms to prevent unfair

behaviour caused by exposed nodes in disconnected topologies.

The first requirement of an examination of the fairness properties of a wireless

network or protocol is to define behavioural characteristics which are considered

indicative of fair behaviour. W e present a discussion of the many possible

fairness definitions and how each may be applied to local area wireless networks.

This discussion is followed by a review of relevant work in this area.

2.5.1 Fairness Definitions

The view of which characteristics constitute fairness in a distributed wireless

network will vary in accordance with the applications and services the network is

supporting. For example, a real time voice connection would consider a network

unfair if one or a group of nodes was able to gain immediate access to the

channel at the expense of other connections of the same type. Or, alternatively

a data transfer m a y consider a network unfair if throughput was not shared

proportionally amoung similar connections. These simple examples illustrate

how the definition of fairness will depend on the application, data type, or

service being supported by the wireless network. Accordingly, a number of

fairness definitions are possible in a general topology wireless network, including

for example:

• the ability of the network to allow each node access to the channel on

demand, with a transmission rate that is proportional to the required or

requested data rate

• the ability of a node to access the channel within a defined interval of the


initial attempt

• the ability of the network to prevent a single user from monopolising the

channel

• the ability of the network to allow equal sharing of capacity amongst nodes

attempting to access the network

• the ability of the network to provide equal performance in terms of spec

ified metrics such as loss, delay, or throughput for contending nodes

Each of the above fairness definitions can be categorised in terms of their scope,

timescale, potential application and other characteristics as illustrated in Ta

ble 2.5. In this comparison we group the above definitions into one of 4 broad

areas, though as mentioned previously, a significant range of definitions is possi

ble depending on the specific circumstances involved. The type category (qual

itative or quantitative) represents whether the fairness behaviour can be mea

sured against a specified metric. The potential application category gives an

indication of how the performance achieved with a specific traffic type may be

assessed.

A suitable exact fairness definition will be necessary in the later stages of this

thesis, and as such it will draw on appropriate elements of this discussion.

2.5.2 Experimental Fairness Investigations

Investigation of wireless network fairness properties presented to date has typ

ically been simulation based, with a small number of publications presenting

empirical results. Simulation investigations in (Tang and Gerla, 1999) and

(Tang et al., 2001) attempt to quantify the interactions between the transport

protocol and M A C backoff timing mechanisms. The performance of several

M A C protocols supporting T C P streams are investigated in a number of differ

ent topologies including hidden terminal scenarios. Results for the C S M A / C A

M A C with an R T S / C T S / D A T A / A C K handshake, illustrate that this variant of


en

a o a mi o

Q CO CO O)

PI • i — I

PI O co • H fH 03

ft O

O

CN

i—i

Potential

Application

CP

>>

H

CP

0

o CO

CP >

s

CP >

O

CP

CP

o

S CP

CO

0

CP

P CO CO

CP

a u

real time

data streams

(voice/video)

>

X

X

>

>

Bounded

Access

Delay

transport protocols

including re

transmission timers

X

>

X

X

>

Prevention

of Capture

State

co o

O* • i-H

fH

O

PI

>

X

>

X

X

Throughput

Proportional to

Population

CO

o

CD CO 03

a 03 O) fH -t-a CO

>

X

>

X

>

Equal

Throughput

to Demand ratio


the C S M A / C A protocol is able to provide fair access to the resource for both

connections. This is the mechanism employed in 802.11, and as such, an imple

mentation of 802.11 would be expected to perform in a similar manner when

deployed in such a topology.

However, the simulation environment used in (Tang and Gerla, 1999) and (Tang

et al., 2001) includes an ideal channel in which all packets are received by

all nodes in range without error. This approach, while providing a means of

investigating the protocol interactions in isolation through the initial stages of

an investigation, does not allow for a detailed investigation in a similar manner

for a physical implementation.

An empirical investigation is presented by (Koksal et al., 2000), and (Swan

and Raman, 2000). While not considering fairness as a primary objective, the

authors of (Gerla et al., 1999b) present simple empirical results from a wireless

L A N testbed employing a basic C S M A M A C without any signalling mechanism

to prevent hidden terminal losses.

The authors of (Pagtzis et al., 2001) present an empirical investigation of the

fairness properties of the 802.11 M A C / P H Y in a W L A N configuration carrying

a U D P traffic stream. The results indicate that the rate selection algorithm

may result in unfairness for nodes further from the base station, who have a

lower received signal power as a consequence of their relative position. As the

802.11 standard requires that all packets headers be transmitted at the lowest

possible rate, IMbit/s, the authors claim this unfairly penalises stations that

are capable of transmitting at higher rates. This is due to the time taken to

transmit the header compared with the time taken to transmit the payload at a

higher rate. The authors then propose an extension to the M A C which includes

proportional bandwidth allocation within the P C F as a means of preventing

this unfairness.

The requirement for a common header rate is included in the 802.11b standard

to ensure backward compatibility across all DSSS PHY's. Further, the authors


(Pagtzis et al., 2001) neglect the short P H Y header option described in the

802.11b standard, which is employed between all stations capable of transmit

ting at either the 5.5 Mbit/s or 11 Mbit/s rates. This reduces the P H Y header

overhead significantly, thus ameliorating the negative impact of the requirement

for a common header transmission rate.

The performance of the MAC protocol using a UDP transport layer requires

further investigation. The majority of work presented to date employs T C P as a

higher layer transport, and while this provides useful information regarding the

interactions between protocol timers and retransmission mechanisms, isolation

of M A C performance in these scenarios becomes difficult.

2.5.3 Mechanisms to Prevent Unfair Behaviour

Schemes which aim to prevent unfair behaviour maintain a precise definition

of fairness and are able to move the measured behaviour closer to the required

operating point by adjusting parameters either individually within each node,

or in concert within a larger groups of nodes across the network. Three distinct

approaches have appeared in the literature aiming to provide network wide fair

medium access, and in the following sections we provide an overview of each

approach.

• Link Access Probability Techniques

Techniques based on the calculation of a link access probability have been pre

sented by the authors of (Ozugur et al., 1998; Ozugur et al., 1999). The tech

nique is based on a mechanism which assigns a predefined access probability for

each link with a neighbour. This is illustrated in Figure 2.12. W h e n the backoff

counter expires, node i will contend for the link with node j with probability

Pij. In this case the normal backoff mechanism is retained. Each node has a

visible set of neighbours, denoted by VJ. Each neighbour in the set then broad

casts the number of logical connections available, Sj. If the number of logical

connections for node i, Si = Y^j&v SJ> then node *is a central node and nas n0


Figure 2.12 Example wireless network topology including both hidden and visible stations (Ozugur et al., 1998). Link access probabilities are assigned to each logical network link in accordance with Equations 2.6 and 2.7. Arrows indicate the logical links, and probability pij assigned to each link. Node A has a set of neighbours B. The set of nodes C are hidden from A, having at least one connection with a neighbour of A. All other nodes in the network belong to a separate set, D.

hidden terminals. In this case, Pij = 1, V? G V;.

If Si < Yljev Sj ^nen n°de i will have hidden stations in the vicinity and must

choose the link access probabilities more judiciously. The maximally connected

neighbouring node for node i has a number of connections, 5™°*. In this case,

the link access probability is selected based on the link node i is attempting to

access. If node i is attempting to access the maximally connected node, then

Pij is chosen as:

ftj = mtn|l,-^b| (2-6)


And in the case where node i attempts to access any other node A;:

p^ = mm |l,-^M (2.7)

where Sk is the number of logical connections for node k, the intended recipient.

This can be performed as a dynamic process, provided that each node is able to

maintain an accurate account of the variables Si and Sj each time the network

topology changes.

A second method is presented (Ozugur et al., 1998), which uses a time based

approach to determine the appropriate link access probability. Each node is

required to periodically broadcast a traffic descriptor Lij used to indicate the

presence of traffic destined on the link from i to j. A measure of the contention

period duration is also required at each node to determine the link access prob

ability as the average contention period by the mean value of the contention

periods of all neighbouring links.

The connection based scheme provides a relatively simple mechanism to prevent

unfair behaviour on a traffic flow basis (where a flow is defined as the data

flowing along a logical link between two nodes). However, this scheme is based

only on topology information, or the measured contention period experienced

by each node. Accordingly, these mechanisms require detailed knowledge of the

congestion state of the network, or the topology and flow information within

the extended local region. The performance of these mechanisms in dynamic

environments is unknown, particularly in cases where the topology is rapidly

changing (in a M A N E T for example), or the congestion state of the network is

difficult to accurately assess for the M A C layer. Further, the requirement for

this additional knowledge introduces significant additional complexity to the

M A C layer, greatly expanding the scope of a distributed M A C protocol.

• Backoff Window Adjustment

A technique which adjusts the backoff window has been proposed in (Bensaou

et al., 2000). In this technique, a node requires a pre-defined indication of the


fractional throughput fa it may expect to achieve. Combined with the actual

throughput achieved W j , and the offered load Li, a fairness index is defined as

a function of the ratio of the achieved load to the fractional throughput:

{max (^rS^-J | V i,j : ) * *j( } (2.8)

• (Wi Wj\ | v '

mm U' t) J The task is then to minimise this fairness index for each node in the network.

This is achieved by each node estimating the throughput neighbouring nodes

obtain W0, through observation of all visible packets. A dynamic fairness index

variable is maintained, Fid = 0ji)/(^s-), and used to either double or half the

maximum contention window when compared with another constant C. This

approach requires two variables which must be tuned to operate effectively. It

also applies the contention window change to all logical connections.

Mechanisms to distribute the backoff counter value amoung neighbouring nodes

have also been presented in (Bharghavan et al., 1994). This technique attempts

to ensure each node starts each contention period on the same footing after

periods of extended backoff. The authors then illustrate that this is able to

prevent a node from suffering unfair excessive backoff periods. In the case

of both (Bensaou et al., 2000) and (Bharghavan et al., 1994), ideal channel

characteristics have been assumed.

• Generalised Persistence Techniques

A generalised analytic framework to determine fair rate adaptation algorithms

is presented in (Nandagopal et al., 2000). Identifying the spatial dependence

of contention in a wireless network, the authors propose a general framework

for the derivation of a fairness algorithm to suit a specified fairness objective.

Using a graph theory approach, combined with a utility function defining the

fairness objective, a rate adaptation algorithm can be derived which is shown

to converge on a fair service for all nodes in the network.


The example given is a proportional fair contention resolution mechanism de

rived using this framework. Proportional fairness is defined by the utility func

tion U(r) = log(r), where r is the rate allocation vector for a given node. The

channel allocation algorithm derived using this technique is:

fi = a- PPM (2.9)

where a and /? are parameters used to control the efficiency (increasing a, de

creasing 0) and fairness (decreasing a, increasing /?). Each node in the network

implements this rate adaptation algorithm, resulting in an approximation of

the network wide fairness objective. Through comparison of the proportional

rate control scheme with 802.11 and other M A C protocols in a number of static

topologies, the authors illustrate (Nandagopal et al., 2000) that the proportional

rate control mechanism provides an improved measure of fairness throughout

the network.

The stability and convergence properties of this method has not been analysed

or tested, particularly in a mobile network. Further, the selection of the two pa

rameters, a and /? is a not trivial concern for a general network. The suitability

of this scheme for a network in which the topology is dynamically changing is

unknown.

2.5.4 Discussion

Each of the schemes presented in Section 2.5.3 are designed to solve the fairness

problems resulting from adverse protocol interactions arising in both discon

nected and hidden terminal topologies. The impact of variable propagation

environments, unreliable signal detection and reception, and packet capture ef

fects have not been considered in any of these mechanism. Further issues that

must be addressed with each scheme include:

1. How each algorithm operates within the MAC/PHY relationship

2. The processing and messaging overhead associated with each scheme


3. Implementation complexity

4. Practical incorporation into relevant standards (802.11, HiperLAN I)

5. The sensitivity of each scheme to realistic propagation conditions and

radio m o d e m behaviours

From the above discussion, we contend that while each scheme may operate well

when considering protocol based unfairness problems, suitable performance in

a realistic network environment can only be obtained when signal strength vari

ability and realistic packet capture mechanisms are taken into account. The

motivation for this is that both packet capture and variable propagation condi

tions may result in unfair behaviour outside the scope of the schemes outlined

above. Based on the above discussion, it is evident that fairness algorithms re

quire the following attributes when applied in a dynamic network environment:

• Minimal 'protocol' overhead, in terms of additional messaging and infor

mation gathering processes

• Minimal additional resource requirements on each node, including pro

cessing overhead and implementation complexity

• Adaptive to changes in network topology

• Robust in the presence of variable propagation environments

• Ability to operate within current and future standards

2.6 Summary

Throughout this chapter, we have concentrated on the development of wire

less M A C protocols contributing to the development of the IEEE 802.11 M A C

protocol, and tried to focus on areas in which this thesis provides new contri

butions, namely the impact of capture effects on the fairness properties of a


wireless L A N . Whilst this review has shown wireless M A C protocol research

to be quite advanced in several aspects, there are clearly many areas in which

significant work is required. Our approach is to build on the existing state of

wireless M A C performance studies from the specific viewpoint of fairness in

the presence of capture effects. Issues identified in the literature which require

further investigation are summarised in the following section.

2.6.1 Summary of Open Research Issues Identified In

Current Literature

• The RTS/CTS handshake relies on all potentially interfering nodes being

able to successfully receive either the R T S or C T S message. Practical

wireless networks are characterised by noisy, lossy environments where

messages may or may not be correctly received. The performance of the

R T S / C T S mechanism in a real environment when supporting T C P and

U D P traffic streams is yet to be established.

• A n investigation of the sensitivity of the R T S / C T S handshake to node

movement and other signal degrading effects has not been presented.

• Detailed investigation of the performance of the IEEE 802.11 M A C pro

tocol in hidden terminal topologies is required.

• Investigation of the relative fairness properties of the significant capture

models presented in literature is required. A comparison of simulation

data generated by each capture model with empirical data has not been

undertaken.

• The salient features required from a capture model suitable for accurate

simulation of an IEEE 802.11 m o d e m need to be established.

• N o clear understanding of the empirical fairness properties of an IEEE

802.11 network in hidden terminal topologies exists.

• N o analysis of the detailed requirements of a fairness control scheme suit

able for the IEEE 802.11 M A C protocol has been undertaken.


The IEEE 802.11 M A C protocol has combined many of the features described

in earlier M A C protocols proposed in literature. The remainder of this thesis

will be concerned with an investigation of the fairness properties exhibited by

the IEEE 802.11 protocol.

Chapter 3

Experimental Investigation of Capture Effects and Fairness Behaviour

3.1 Introduction

A significant body of literature exists investigating the performance of various

M A C protocols, retransmission schemes, and hidden terminal avoidance mech

anisms across a range of circumstances. However, as discussed in Chapter 2, an

experimental investigation of these mechanisms will allow us to evaluate interre

lationships between protocol layers, as well as the impact variable propagation

conditions have on signalling mechanisms within the M A C .

Further, the tendency of communications systems to exhibit some form of cap

ture behaviour has been an issue for many years (Jain et al., 1984). In partic

ular, Chapter 2 illustrated how capture behaviour is observed at two separate

levels: the packet level due to physical layer mechanisms, and the protocol level

due to interactions between transmission timers. The combination of these two

capture effects can greatly impact on the fairness behaviour of a shared me

dia wireless network. Therefore, the remainder of this thesis focuses on the

investigation, modelling and analysis, and prevention of such capture effects in

physical wireless networks.

54

Experimental Investigation of Capture Effects and Fairness Behaviour 55

In this chapter, we present an experimental investigation of the fairness prop

erties of a C S M A / C A network employing the RTS/CTS common channel sig

nalling technique. W e concentrate on scenarios where hidden terminals are

present, or where carrier sense mechanisms may be unreliable. Section 3.2 out

lines our motivation for the experiments performed, while Section 3.3 outlines

the experimental methodology employed throughout the chapter. Section 3.4

presents experimental results obtained using T C P as the higher layer transport

protocol. Section 3.5 then presents results obtained using U D P as a higher layer

transport. Conclusions are drawn in Section 3.6, which provide direction for the

following chapters.

3.2 Experimental Motivation

Given the mobile, dynamic nature of an ad hoc network, it is anticipated that

hidden terminals are likely to be a common problem in typical network topolo

gies. Also, in a typical indoor wireless L A N , the characteristics of an indoor

office environment imply that absolute carrier sense information cannot be guar

anteed for all nodes throughout the network. Walls and other obstacles result in

significant signal attenuation and multipath components in the signal. There

fore, the performance of data streams competing for a common radio resource

in the presence of hidden terminals is an important issue.

The poor performance displayed by TCP over the MAC protocol (Gerla et al.,

1999b; Holland and Vaidya, 1999) is also a problem for shared media wireless

networks. The performance of a M A C protocol in terms of fairness and delay

is critical to the performance of the transport protocol. In this context, there

are two major interactions of interest: one between the M A C retransmission

timers and the T C P timers, and another between the routing protocol and T C P

retransmission timers. Investigations into both areas form the basis of much of

the published work in the area of wireless data transport (Tang and Gerla, 1999;

Gerla et al., 1999b; Holland and Vaidya, 1999; Chandran et al., 1998; Gerla

et al., 1999a). In our investigation, we consider single hop connections only,


Connection A

Transmission and C O Carrier Sense Range

Hidden Nodes

Figure 3.1 Experimental Topology

and therefore will be concerned with the M A C and transport layer interaction.

Tang (Tang et al., 2001; Tang and Gerla, 1999) presents simulation results il

lustrating that the IEEE 802.11 M A C protocol is able to provide fair channel

access in hidden terminal scenarios when the RTS/CTS/DATA/ACK 4-way

handshake is employed. To confirm this result, we have performed experiments

simulating two competing F T P file transfers over hidden terminal connections,

with the topology illustrated in Figure 3.1. The simulation environment is a

modified version of the Berkeley ns-2 network simulator (UCB/LBNL/VINT,

1999). ns is a detailed protocol simulation tool implementing the IEEE 802.11

M A C and T C P protocols. A two-ray ground propagation model with an Addi

tive White Gaussian Noise ( A W G N ) channel has been employed for these tests.

A power modem capture model (Arnbak, 1987) has been employed. In this

trial, each connection has an equal average Signal-to-Noise Ratio (SNR), as the

nodes are equally distant from the common host.

The results of these basic trials in Figures 3.2 and 3.3 confirm the result pre

sented by Tang (Tang et al., 2001), that the RTS/CTS handshake is able to

prevent adverse timing interactions between the M A C and TCP. Figure 3.2

provides evidence of the protocol capture problem without an RTS/CTS hand

shake. This behaviour is explained by the interaction between T C P timers and

the M A C retransmission and backoff counters. Connection B is started 0.1

seconds after Connection A, and is unable to gain access to the channel until

approximately 3 seconds. During this period, Connection A has captured the


1200

1000

- 800

I , 1 600 '8 tr M ^ J A M

Q 400

200

Connection A Connection B

3

Time (seel

Figure 3.2 Simulation Experiment - Hidden terminals, D A T A / A C K only. Connection A captures the resource until approximately 3 seconds when Connection B is able to access the channel. The ability of either connection to capture the channel is random in this experiment

radio resource. Figure 3.3 illustrates how the RTS/CTS signalling mechanism

attains a fair distribution of channel access for the competing connections.

The simulation environment used by the authors of (Tang et al., 2001; Gerla

et al., 1999a; Tang and Gerla, 1999) is based on an ideal channel, in which

each host receives all intended packets without error, and no m o d e m capture

ability is present. This allows investigation of the protocol mechanisms and

interactions in isolation, but will provide limited insight into the behaviour and

fairness properties that may be expected from a physical M A C / P H Y protocol.

In this section, we have illustrated that simulation with an A W G N channel and a

simple power capture model indicates behaviour consistent with that presented

by Tang (Tang et al., 2001; Gerla et al., 1999a; Tang and Gerla, 1999).

The critical questions is whether the RTS/CTS/DATA/ACK mechanism ex

hibits the same robust behaviour in real propagation environments with physical


1200

1000 -

~ 800 eft

f CO § 600

DC

2 S 400

200

Connection A o Connection B x

Figure 3.3 Simulation Experiment - Hidden terminals, RTS/CTS/DATA/ACK

signal detection and demodulation hardware, as opposed to the ideal receivers

modelled in previous simulation. H o w well this mechanism operates when signal

propagation conditions are not ideal (multipath, fading etc) remains an open

question. It is also unlikely that the channel conditions will be equal on each

of the contending connections as is the case with simulation results presented

thus far. These factors, combined with a lack of experimental results examining

the fairness properties of a wireless L A N involving hidden terminals, motivate

an investigation of the impact varying S N R conditions have on the fairness

performance of the R T S / C T S mechanism.

Through investigation of the dynamic behaviour of competing hidden connec

tions over an IEEE 802.11 network, this experimental study will address the

following issues:

1. the ability of the R T S / C T S / D A T A / A C K handshake to prevent adverse

protocol interactions, and associated protocol capture states when a higher

layer backoff and retransmission mechanism is employed.


2. the ability of the RTS/CTS/DATA/ACK handshake able to alleviate hid

den terminal collisions in a real propagation environment.

3. the resistance of the R T S / C T S / D A T A / A C K mechanism to protocol cap

ture induced by synchronisation of backoff timers at the M A C layer.

4. the fairness performance of the R T S / C T S / D A T A / A C K mechanism in a

practical propagation environment.

We are interested in instantaneous, dynamic behaviour of each connection rather

than longer term average behaviour, as this gives an accurate description of the

short term fairness properties of the system. This is important from the view

point of the QoS experienced by an individual user. If a system was asymptot

ically fair, but significantly unfair at shorter timescales, then the QoS experi

enced by an end user, in terms of channel access delay, instantaneous through

put, and bit error rate will be less than ideal. For the purposes of the exper

iments of this chapter, we use a relatively simple definition of fairness, one in

which both nodes should gain relatively equal access to the radio resource, and

no connection should be able to prevent another from gaining appropriate ac

cess to the channel for an extended period. This is a reasonable definition for

the current experiments, given that both data transfers utilise the same M A C

protocol, whose aim is to provide equivalent access for all nodes. More detailed

quantitative fairness studies are undertaken in Chapter 5.

3.3 Experimental Methodology

The aim of this investigation is not to determine absolute throughput perfor

mance, nor benchmark the equipment used to perform the experiments. W e are

interested in the ability of the M A C to provide fair channel access in hidden

terminal scenarios, and the susceptibility of the 802.11 M A C / P H Y to protocol

and other capture effects.

The experimental topology, illustrated in Figure 3.1, has hosts 1 and 3 mutually


out of range, attempting to communicate with host 2. Each experiment consists

of a simultaneous data transfer from hosts 1 and 3 to host 2. The network

sniffing program, tcpdump (Lawrence Berkeley Laboratories, 1999), is used at

host 2 to trace the progress of each data transfer. Each host has an 802.11b

wireless network interface, and is used in either the ad hoc mode or standard

access point mode, and employs a collision avoidance R T S / C T S handshake

governed by the aRTSThreshold parameter. The results are presented as traces

illustrating the time evolution of each transfer (data received vs time) to provide

a clear indication of the timescale of unfairness that may be present. The signal

strength, noise power, and S N R on each connection is measured using a software

package which sends test packets each second and records the signal strength

parameters reported by the R F interface. The results are averaged over 2 minute

intervals to provide an indication of the average link quality. The individual

experiments presented in the following sections (Section 3.4 and Section 3.5)

are summarised in Table 3.1.

Following the results presented in Section 3.2 combined with previously pub

lished simulation results (Tang et al., 2001; Tang and Gerla, 1999), it was antic

ipated that the reservation mechanism should enable reasonable sharing of the

radio resource. It was also anticipated that T C P connections should suffer no

serious ill effects (in terms of excessive retransmission or timeouts), given that

each connection is only a single hop, and that the M A C protocol employs im

mediate positive acknowledgement with retransmission. The experiments were

performed using three laptop PCs. Each P C was equipped with IEEE 802.11

network interface cards, and the experiments were performed using the Linux

operating system, and repeated using Windows 98 operating systems to test for

any operating system or driver dependent artifacts.

3.4 TCP Experiments

A number of separate experiments were undertaken to investigate the perfor

mance of T C P over competing hidden connections. This series of experiments


Table 3.1 Summary of Experimental Trials

Experiment

1

2a

2b

3a

3b

4

5a

5b

6a

6b

7a

7b

Figure

3.4

3.5

3.6

3.7

3.8

3.9

3.10

3.11

3.12

3.13

3.14

3.15

Scenario

no-RTS/CTS equal SNR

RTS/CTS equal SNR

RTS/CTS

equal SNR

RTS/CTS

unequal SNR

RTS/CTS unequal SNR

controlled

controlled SNR

RTS/CTS equal SNR

RTS/CTS

equal SNR

RTS/CTS unequal

stronger first

RTS/CTS unequal stronger first

RTS/CTS unequal

weaker first

RTS/CTS unequal

weaker first

Transport

TCP

TCP

TCP

TCP

TCP

TCP

UDP

UDP

UDP

UDP

UDP

UDP

P H Y Mbit/s

Barker

Barker

CCK

Barker

CCK

Barker

CCK

CCK

CCK

CCK

CCK

CCK

Vendor

Lucent

Lucent

Cisco

Lucent

Cisco

Lucent

Lucent

Cisco

Lucent

Cisco

Lucent

Cisco


examines both the performance of TCP under these conditions, and the abil

ity of the M A C protocol to avoid protocol channel capture under heavy load

conditions. These experiments were performed using both Orinoco WaveLAN

Lucent and Aironet 340 Cisco IEEE 802.11 cards. This is a deliberate choice, as

the Lucent and Cisco cards employ different R F front end designs. The Lucent

R F front end was developed by Lucent, while the Cisco cards employ a front

end designed by Intersil (formerly Harris Semiconductor). The overwhelming

majority of 802.11 interfaces available today employ one of these two R F front

ends.

3.4.1 RTS Handshake - Hidden Terminals

Initially, the performance without the RTS/CTS handshake and an equal SNR

on each connection is investigated. The resulting trace, illustrated in Figure 3.4,

show that even though connections A and B have an equal S N R as measured

at host 2, Connection A is able to capture the channel for the duration of

the transfer. The results in this simple case, mirroring those of Figure 3.2,

illustrate the impact timing mechanisms can have on contending connection.

Connection B has commenced transferring data when Connection A commences.

This leads to a period of receiver side collisions, won by Connection A, which

eventually manages to capture the channel. Host 3 (Connection B) now invokes

T C P congestion control measures, and undergoes periods of exponential backoff.

During this period, host 3 is unable to receive an acknowledgement for any data

frame it has attempted to transmit as host 1 has monopolised the channel.

The second experiment is a simple case where the SNR of each connection is

equal and the aRTSThreshold is set to 500 bytes. A typical example of the

resulting traces are shown in Figures 3.5 and 3.6. In this example, Connection

A is commenced a few seconds after Connection B. Even though T C P connec

tion setup (SYN) messages of 40 bytes are exchanged without an RTS/CTS

handshake, the channel is effectively shared until connection B finishes. This

experiment was run numerous times with a range of aRTSThreshold parameter


500

450

400

350

2- 300

250

200

150

100

50

0 M 6 8

Time (sec)


10 12 14

Figure 3.4 Experiment 1: Lucent Barker P H Y Equal SNR 25dB, No RTS/CTS Handshake

values from 0 bytes to the maximum T C P segment size of 512 bytes, with little

impact on the relative fairness provided by the M A C .

The delayed start of the Connection A data transfer in Figures 3.5 and 3.6 is

due to the lack of precise control over the exact time at which a connection

will commence. This is not significant from a fairness point of view, and may

be considered to represent a case where an ongoing connection is joined by a

competing hidden terminal connection part way through. It can be seen that

the R T S / C T S handshake has an impact on the fairness of the channel access

achieved by each connection. Each host maintains a roughly equal share of the

channel capacity throughout the common period of each transfer, observed as

the parallel gradient of the individual traces between 4 seconds where connection

A commences, and 14 seconds where connection B finishes. The most interesting

result is the sensitivity of the capture behaviour. A very subtle change in

physical orientation of a terminal was able to sufficiently alter the received

signal strength, preventing fair access for both connections to the channel.


1200

1000 -

« 800

I CO | 600 -

'8 CD OC M

co a 400

200 -

I

-

-

/

/ ,

1 — 1 1

y-

X

i i

S"

I I

1 1 1


• >

-

-

-

0 X

8 10 12

Time (sec)

14 16 18 20

Figure 3.5 Experiment 2a: Lucent Barker P H Y - Equal SNR 25dB for both connec

tions, aRTSThreshold 500 bytes

3500

3000

2500

2000

» 1500 a co Q 1000

500


6

Time (sec)

10 12

Figure 3.6 Experiment 2b: Cisco C C K P H Y - Equal SNR 25dB for both connections,

aRTSThreshold 500 bytes


From these experiments, it is apparent that the RTS/CTS mechanism is able to

provide reasonable sharing of the channel when T C P is used as a higher layer

transport protocol and the signal strength on each connection is equal. This

is in accordance with the simulation results of Section 3.2. In the following

section, we investigate the sensitivity of this behaviour to the signal strength

conditions on each connection.

3.4.2 Impact of Varying Signal Strength

The next experiment, in which Connection A has an SNR 5dB higher than

Connection B, again uses an aRTSThreshold of 500 bytes. The scenario inves

tigates the performance under a 'near-far' hidden terminal scenario. The trial

results in behaviour illustrated in the examples shown in Figures 3.7 and 3.8

where Connection A is able to dominate, capturing the channel. Here, Con

nection A starts marginally after Connection B, yet manages to dominate the

contending host. None of the randomness of the previous two experiments was

evident. Over multiple trials the connection associated with the higher S N R

always captured the channel.

A 5dB difference between connections is quite minor and in practice can be

simply due to subtle variations in multipath propagation as the surrounding

environment changes. W e expect the scenario presented in the first experiment

(equal S N R ) will rarely arise with a hidden terminal topology in a multihop

wireless network, particularly given the number of factors affecting the S N R

observed on each connection. These results demonstrate the sensitivity of the

R T S / C T S mechanism within 802.11 to the S N R seen on competing hidden

connections.

To test the dependence on relative signal strength of which connection is able

to capture the channel, the fourth experiment involves reducing the S N R on

the stronger connection, Connection A, to a point below the weaker Connec

tion B midway through the file transfer. It is anticipated that Connection B

should be able to capture the channel at the expense of Connection A. This


500

450

400

350

2r 3 0° 250

OC co co Q

200

150

100


10 12

Figure 3.7 Experiment 3a: Lucent Barker Code P H Y - Unequal SNR Connection A

25dB and Connection B 20dB, aRTSThreshold 500 bytes

2500

2000

ft 15 0°

1000

500 -


12

Figure 3.8 Experiment 3b: Cisco C C K P H Y - Unequal SNR Connection A 20dB

and Connection B 25dB, aRTSThreshold 500 bytes


1200

15 20

Time (sec) 25


30 35 40

Figure 3.9 Experiment 4: Lucent Barker Code P H Y - Controlled SNR, aRTSThresh

old 500 bytes

experiment provided a concrete test of the S N R dependence observed in previ

ous trials. Connections A and B commence the test with a S N R of 25dB and

20dB respectively. Five seconds into the trial the S N R of Connection A was

reduced using R F absorbing foam to approximately 17dB through to the end of

the experiment. A n example of the resulting trace is shown in Figure 3.9. Here,

the sensitivity to the signal strength is clearly illustrated. The new stronger

host, Connection B, manages to 're-capture' the channel once the S N R of Con

nection A is sufficiently reduced. Once Connection B has finished Connection

A is able to regain access to the channel, after a significant timeout period be

tween 5 seconds and 33 seconds. In the above experiments, the M A C is unable

to provide fair access amoung the contending hidden terminals. In each case,

the connection which is able to capture the channel suffers relatively few T C P

timeouts, and transmission errors are simply handled by the M A C and T C P

retransmission mechanisms. Conversely, the contending connection undergoes

continual timeout and exponential backoff at both the M A C and T C P levels.

In all cases, the connection with the stronger signal strength measured at the


common receiver is able to capture the channel. The experiments have been

performed in an indoor office environment subject to multipath and other sig

nal degrading effects. The propagation delay over the links employed in the

experiment is 50 nsec, significantly less than the 10 //sec SIFS, and the 50 / sec

DIFS. Multipath reflections were eliminated as a potential factor through sub

sequent experiments in a controlled multipath environment illustrating identical

behaviour.

In each of the static and controlled SNR experiments, it is obvious that TCP

is exacerbating the channel capture problem. The result is a series of signifi

cant periods of protocol induced capture for either connection whilst the other

connection is forced to repeatedly backoff and eventually timeout. This raises

a question regarding how significant a component protocol capture is in this

behaviour. If a more suitable transport layer protocol were employed then the

protocol capture state may be avoided. To test this, we undertake a number of

experiments using the User Datagram Protcol (UDP) as a transport protocol

in the following section.

3.5 UDP Experiments

In order to quantify the impact TCP timing interactions have on the fairness

on each connection, we perform experiments in this section in which we remove

TCP. In this series of experiments, a transport layer is used which has been

written to flood each connection with U D P packets of a specified size instead of

F T P / T C P used in the previous experiments. A n application sends a specified

number of packets to a remote machine on a given port number. The applica

tion will send packets as quickly as the network interface allows, without any

retransmission or timeout mechanisms. The network connection will not accept

packets from the transport layer (through the network socket) while the socket

and M A C buffers are full. The receiver runs a similar application which listens

to the identified port, and accepts the data from each host. The resulting sys

tem is one with two greedy traffic sources transmitting to a common traffic sink



20 25

Time (sec) 50

Figure 3.10 Experiment 5a: Lucent Chipset C C K P H Y - U D P Trace - both con

nections 25dB

over contending hidden connections.

To test for artifacts that may be specific to a particular 802.11 interface imple

mentation, we continue experiments with both Orinoco 802.11 Lucent interfaces

and Aironet 340 Cisco interfaces. Each connection consists of either 5000 or

10000 512 byte U D P frames to introduce variability into the experiment.

3.5.1 Equal Signal Power

Experiment five was performed with an equal signal power on each connection,

as measured at the common receiver. The topology is again the hidden terminal

topology illustrated in Figure 3.1. In this scenario, only the 802.11b UMbit/s

P H Y is employed as the previous results have indicated there to be little dif

ference between the 2Mbit/s Barker code P H Y and the UMbit/s C C K P H Y .

In each experiment, hosts 1 and 3 send a total of 10,000 U D P packets (512

bytes) to the receiver. The results of the equal signal power experiments are

illustrated in Figures 3.10 and 3.11. In these traces, fair sharing of the channel


2500

6

Time (sec)

Connection A O Connection B x

12

Figure 3.11 Experiment 5b: Cisco Chipset C C K P H Y - U D P Trace - both connec

tions 25dB

is obvious. Neither host gains preferential access to the channel, and there is

no visual evidence of any unfairness due to M A C backoff timer synchronisation.

As mentioned earlier, more detailed investigation of the quantitative fairness

properties of the experimental traces is undertaken in Chapter 5.

3.5.2 Unequal Signal Power

The sixth experiment was performed with one of the connections at a relative

difference of 5dB. In this case, the stronger host commences transmission prior

to the weaker connection. The resulting traces are shown in Figures 3.12 and

3.13. In both cases Connection A is the stronger connection with an average

measured S N R of 25dB and Connection B the weaker host, 5dB weaker with

an average measured S N R of 20dB. Both Figures 3.12 and 3.13 illustrate the

relative difference between the stronger and weaker connections. During the life

time of the stronger connection, the weaker connection suffers continual timeout

and retransmission of M A C frames, resulting in the much lower throughput ob-



40 45

Figure 3.12 Experiment 6a: Lucent C C K P H Y - U D P Trace - stronger host (Con

nection A - 25dB) commencing prior to weaker host (Connection B - 20dB)

2500

2000

£ 1500

1000

500 -


o X

12

Figure 3.13 Experiment 6b: Cisco C C K P H Y - U D P Trace - stronger host (Con

nection A - 25dB) commencing prior to weaker host (Connection B - 20dB)


5000

4500

4000

3500

§• 3000

1 2500 co

8 01 2000 CO CO Q

1500 1000

500

0 0 5 10 15 20 25 30 35 40 45

Time (sec)

Figure 3.14 Experiment 7a: Lucent CCK PHY UDP Trace - stronger host (Con

nection A - 25dB) commencing after weaker host (Connection B - 20dB)

served during this period. Each frame suffers a significantly higher delay for

this reason. The weaker connection suffers a significantly higher average backoff

period, and will require a higher number of retransmission attempts than the

stronger host. Combined with the fact that the greedy source is unable to send

packets while the socket and M A C buffers are fully occupied and will therefore

pause until room is made available in the local socket and M A C buffer. The

latter explains the small gaps in time present in the weaker trace, corresponding

to periods where the M A C cannot successfully access the radio channel.

Experiment seven is identical to experiment six, with the exception that the

starting order of the data transfers is reversed, and the stronger connection

commences after the weaker connection. This experiment, combined with the

previous experiment, provides a mechanism to investigate the impact a stronger

connection has on a weaker connection. The resulting traces are shown in

Figures 3.14 and 3.15. In both traces, the stronger host again prevents the

weaker host from gaining equal access to the channel. Once the stronger host

J i_

Connection A o Connection B *


2500

2000

| 1500

1000

500


12

Figure 3.15 Experiment 7b: Cisco C C K P H Y - U D P Trace - stronger host (Con

nection A - 25dB) commencing after weaker host (Connection B - 20dB)

has commenced, the weaker host is again prevented from gaining equal access to

the channel. The weaker host suffers significantly higher loss and delay during

the period of the stronger connection. Each of the traces from experiments

using U D P (Figures 3.10 to 3.15) display the same behaviour as the T C P based

results of the previous section. The stronger of the hidden connections will gain

preferential access to the channel at the expense of weaker connections.

Mitigation of physical artifacts or other factors in the above experiments was

an important aspect of the experimental process. Experiments were repeated

with updated versions of drivers, card firmware, and operating systems. M A C

parameters were also carefully controlled, including fixing the transmission rate

to prevent auto rate selection reducing the transmit rate when an increased

B E R is observed.

In each experiment described in this chapter, a consistent result is evident.

W h e n a signal power difference of greater than 5 dB exists between two hidden

connections, the stronger connection will gain preferential access to the channel


at the expense of the weaker connection.

3.6 Conclusions

In this chapter, we have presented a detailed empirical investigation of the per

formance of a C S M A / C A M A C protocol using an common channel RTS/CTS

signalling technique to guard against hidden terminal collisions. The experi

ments have examined the performance of the M A C protocol from the viewpoint

of the higher layer protocols, in a real propagation environment. Through in

vestigation of hidden terminal topologies, the experiments performed in this

chapter have illustrated a strong signal power dependence of channel capture

behaviour with the IEEE 802.11 M A C / P H Y protocol. The various scenarios

investigated have illustrated that the RTS/CTS handshake, is unable to pre

vent unfair behaviour in the form of channel capture in near-far signal power

scenarios. A S N R differential as small as 5dB was shown to result in capture

for the stronger connection. A log-distance path loss model with exponent 4

(corresponding to an indoor nlos environment) and an experimentally measured

reference of 25dB at 15m results in a 5dB path loss corresponds at an additional

spacial separation of only 4.74m.

Under all but the most ideal of conditions, channel capture is evident during

periods of high traffic load. The mechanisms behind this require detailed inves

tigation.

In terms of the aims outlined in Section 3.2, the experiments performed in this

chapter have illustrated the following:

• The RTS/CTS/DATA/ACK handshake is able to support fair channel

access for both T C P and U D P connections in hidden terminal scenarios

where the average signal power measured at the receiver is equal for both

connections. There is no evidence of adverse interactions between the

transport protocol and the M A C in the case where the S N R is equal on


each competing connection.

• The RTS/CTS/DATA/ACK handshake is able to successfully alleviate

hidden terminal collisions only in scenarios where the signal power mea

sured at the receiver is equal amongst all hidden nodes. The results of the

equal S N R U D P and T C P experiments provide strong evidence of this.

In scenarios where the received signal power is not equal on each connec

tion, the R T S / C T S / D A T A / A C K handshake appears unable to support

fair access for all hidden connections. The reasons why this is the case

require further investigation.

• The RTS/CTS/DATA/ACK handshake does not illustrate the propensity

to suffer adverse synchronisation of M A C backoff timers in scenarios where

the received signal power is equal on each connection. In scenarios where

the received signal power is not equal, the U D P experiments illustrate that

the weaker host suffers significantly longer average backoff period, and

requires a greater number of transmission attempts. This is not direct

evidence of synchronisation of backoff timers, rather an indication that

the congestion state of the network observed by the stronger and weaker

connections differ in accordance with their relative received signal power.

The stronger host does not observe significant congestion, while the weaker

host observes significant congestion through continual timeout, backoff

and retransmission cycles.

• The RTS/CTS/DATA/ACK handshake is unable to provide reasonable

fairness in scenarios where the received signal power is not equal on all

hidden connections. In such cases, the fairness properties are heavily

skewed towards the stronger connection. With TCP, the stronger connec

tion suffers no serious ill effects, whilst the weaker connection will suffer

significant loss and timeout at the M A C layer. This causes the T C P

congestion control mechanisms to undergo continual backoff and retrans

mission, preventing the weaker connection from gaining equal access to

the channel. With a U D P based greedy source, the stronger connection is


able to occupy the significant majority of the radio resource at the expense

of the weaker connection.

The most fundamental contribution arising from the experiments presented in

this chapter, is the sensitive dependence on signal strength of the fairness prop

erties observed empirically. This indicates that the M A C protocol operates

effectively in cases where the signal power observed at the receiver is equal for

all competing hidden nodes. The M A C is unable to provide fair access in cases

where a relative received signal strength of greater than 5dB is present between

two competing hidden connections. Relative received power has a strong in

fluence on the fairness properties of the M A C , indicating that m o d e m capture

behaviour may have a significant influence on the performance of the M A C pro

tocol. In the following chapter we undertake an investigation of the physical

layer signal reception process in order to investigate the impact this has on the

ability of the M A C protocol to provide equal access for all hidden connections

across a suitable range of signal conditions.

Chapter 4

Error Probability Analysis -Hidden Terminal Jamming

4.1 Introduction

Detection and subsequent reception of a spread spectrum signal is a fundamental

aspect of the performance of the P H Y protocol. One of the fundamental reasons

behind the selection of a direct sequence spread spectrum physical layer in the

IEEE 802.11 standard is the inherent immunity to noise and multipath achieved

with a spread spectrum signalling technique. In an ideal system, a receiver

should be able to receive a given signal in the presence of a reasonable level of

background interference

However, in the previous chapter, it was shown that the relative received sig

nal power is a significant factor in determining the performance of competing

traffic flows in network scenarios involving hidden terminals. In cases with a

small relative difference in received signal strength, the stronger connection re

ceives a favourable throughput over weaker connections, despite the physical

and virtual carrier sense mechanisms within the 802.11 C S M A / C A multiple

access technique. This result adds an unexpected dimension to the protocol

capture problems already known. The theory behind this behaviour will be

investigated in this chapter.

77

Error Probability Analysis - Hidden Terminal Jamming 78

Through investigation of the reception mechanism within an 802.11 spread spec

trum receiver, we aim to determine the impact interfering signals have on the

probability of successful reception of a given frame. The remainder of this

chapter is organised as follows: Section 4.2 provides background on the analysis

techniques employed, outlining the analytical results used in following sections.

In Section 4.3 we derive closed form expressions describing the bit error rate for

a received frame in the presence of hidden terminal interference for each of the

802.11 DSSS P H Y protocols under the assumption of a B P S K modulated signal.

Section 4.4 presents numerical results obtained with these expressions which il

lustrate how a m o d e m will be unable to receive a transmission in the presence

of an interferer with a relative signal power between the signals of greater than

2dB. Finally, Section 4.6 draws conclusions, describing the key points from this

analysis that must be considered in the development of a model to accurately

reflect empirical behaviour.

4.2 Spread Spectrum Error Probability

Analysis

The initial analysis of the multiple access interference problem was undertaken

in the late 70's by Pursley (Pursley, 1977) with later extension by Geraniotis

(Geraniotis and Pursley, 1982). (Pursley, 1977) presents a method to deter

mine the level of multiple access interference caused by other users in a spread

spectrum multiple access system. W e briefly review this result here.

Phase coded spread spectrum systems allow multiple access by assigning each

user a unique spreading code. The receiver is then able to detect and receive

a signal from a given user at the same time as a number of other users are

transmitting. In this model, we consider an asynchronous system, being an

accurate description of the IEEE 802.11 system. Spreading sequences are of

length N, with a total of K active users. The signal is assumed to be B P S K

modulated.


b(t)

»2W

b(t)

\^a(t)cos(<ot+e,) Delay

V2Paa)cos(o)t+e,) 2 C L

\/Sa^t)cos((»,t + eK)

KO Receiver

n(t)

Figure 4.1 DSSS System Model (Pursley, 1977)

A direct sequence spread spectrum signal transmitted by the kth user under

these assumptions can be represented as:

sk(t) = V2Pak(t)bk(t) cos (ujct + 0k), k = l,...,K (4.1)

where ak(t) is the spreading code, bk(t) the data signal, 9k the phase of the

kth. carrier, UJC the centre frequency, and P the signal power. A n asynchronous

DSSS system model is illustrated in Figure 4.1.

After passing through the channel and incurring both channel noise and delay,

the received signal, r(t), is then described as:

K

r{t) = n{t) + ^2 V2Pak(t - rk)b(t - rk) cos(ujct + 0k - ucTk) (4.2)

fc=i

where n(t) is a two sided gaussian noise process of spectral density N0/2, and rk

is the delay of the /cth signal. The signal is then passed to a correlation receiver.

The output of the receiver at time t = T, written in terms of the component

data signals bk(t), is given by:

K

Zt = y/P/2hi)0T+ ^2 [h,-iRk,i{Tk) + bk,oRk,i{n)]-cos9k

+ / n(t)ai(t) Jo

k=l,k^i

cos ujctdt (4.3)


Where Rkji and Rkii are the continuous time partial cross correlation functions

for sequences (af^), (of). Rk)i and Rkji are expressed in terms of the aperi

odic cross correlation functions for the spreading sequences, defined in Equa

tion (4.4): ( N-l-l

J2 °*0'KO' + 0 o</<iv-i 3=0

N-l+l

£ ak(j-l)a*(j) 1-N<1<0 3=0

0 elsewhere

ck,S) = { (4.4)

To determine the average signal to noise ratio at the output of the ith. correlation

receiver, the Root Mean Square (RMS) noise component in the correlator output

is required. This is given by Equation (4.5):

VarZi = PT2

12N3 £ rkA+\N0T (4.5)

To simplify the S N R calculation, Pursley defined (Pursley, 1977) an average

interference parameter, rk)i in terms of the aperiodic cross correlation for the

two sequences defined in Equation (4.4). Using the cross-correlation parameters:

N-l

»kAn)= 1 3 Ck,i{l)Ck>i(l + n) (4.6) /=1-JV

the average interference parameter is written as:

r*,t = 2/4^(0)+//*,< (1) (4.7)

The signal to noise ratio is then expressed as y/P/2T divided by the R M S noise

component in the correlator output as described by Equation (4.5). The final

signal to noise ratio is given by Equation (4.8):

-1/2

SNRi = 1% , _1_ A 9 B? R A^3 2-^i 2E 6N3

Th,i

fc=l,/t

(4.8)

Equation (4.8) describes the signal-to-noise ratio experienced by a single user

in spread spectrum multiple access systems, as a result of multiple access inter

ference due to other active users in the system. Given that the channel model


assumes no spatial isolation of transmitters, path loss need not be considered.

In the following sections, we apply this result to the IEEE 802.11 P H Y , as a

special case of an S S M A system, in which each user employs identical spread

ing codes, in an effort to describe the impact an interfering signal has on the

reception of a specified frame.

4.3 Error Probability of Captured Frame

The experimental results presented in Chapter 3 illustrate a distinct relation

ship between the ability of a host to capture the radio channel, and the relative

received signal power of each contending frame measured at the receiver. This

is a problem specific to topologies where the standard C S M A / C A access mech

anism is unable to sense a transmission that may result in a collision at the

intended receiver. A successful transmission relies on the reception of an R T S

frame by the intended receiver and the subsequent successful reception of a C T S

message by all potential interfering nodes.

When two or more hidden terminals are attempting to communicate with a

common receiver, we consider two possible collisions which may occur at the

receiver:

1. an RTS frame from connection A collides with a DATA frame from con

nection B

2. an RTS frame from connection A collides with an RTS currently under

reception from connection B

In each case the eventual behaviour will be dependent on many additional fac

tors, including the timing of the interfering frame arrival, and the relative signal

power of both transmissions. In case 1, the contention will be handled by the

M A C protocol. However, the measurements in Chapter 3 show that the stronger

host will be able to capture the channel after a number of backoff periods. Even


though the R T S frame is relatively small, 40 bytes compared to several hun

dred for the D A T A frame, there is a high probability that the data frame will

be corrupted by the collision if the signal power is sufficiently high. This then

provides an opportunity for the stronger host to prevent a weaker host from

gaining access to the channel through a number of timeout and retransmission

cycles. This case is further complicated by the fact that all control messages

(RTS/CTS etc.) are transmitted at the 1 or 2 Mbit/sec transmission rate, re

sulting in the potential for a signal spread using the Barker sequence to collide

with a signal spread using the C C K codes generated with (2.2).

In case 2, the receiver will either retain capture of the original RTS frame and

return a valid CTS, or will loose both of the frames, unable to respond with

a C T S until an R T S has been received correctly. The experimental results in

Chapter 3 suggest that the stronger host will win this contention period, and

be able to capture the channel.

To examine the impact of an interfering transmission on the reception of a

previously acquired frame, we investigate the resulting B E R obtained at the

output of a correlation spread spectrum receiver. The model assumes that the

initial signal, i, is currently being received, at T > Ta, where Ta is the time

required by the correlation receiver to acquire and achieve synchronisation with

the signal, the acquisition time. A n asynchronous interfering signal, k, arrives

at a time T2 > Ta. For both the BR-DSSS and HR-DSSS physical layers,

we determine the impact this has on the correlation receiver output B E R as

a function of the relative power difference between the signals, and hence the

ability of the receiver to maintain capture of the initial signal.

Our analysis for the DSSS physical layer is based on the results described in

Section 4.2. W e consider the IEEE 802.11 as a restricted case of a spread

spectrum multiple access system in which all users employ a common sequence

or set of sequences (in the case of C C K ) . This has not been examined previously

in literature.


W e define the relative signal strength between the contending signals as

ft = §* (4-9)

where Ebk and E^ are the respective bit energies for each signal.

The SNR experienced by the original (ith) signal, at the correlator output of a

B P S K asynchronous D S - C D M A receiver due to the presence of the interfering

(kth) signal is given by Equation (4.8). In the case under investigation, K is the

total number of concurrent signals received (including the ith signal whose B E R

we are investigating), iV0 the one sided noise power spectral density, Ebi the bit

energy of the zth signal, N the sequence length, and rkj is the Average Inter

ference Parameter (AIP). It has been shown that the AIP can be approximated

(Karkkainen, 1992) as: N-l

rk,i~2 J2 \Ck,M2 (4-10) 1=1-N

where Ckji is the aperiodic cross correlation between the two sequences a,j and ic \^k i s.a tiic opcuuuii- uuaa I^VJIICICILUJII uciwccu LU G IJWU D C ^ U C U L C O 0

Oj , as defined in Equation (4.4). If we assume that the interfering signal A;

arrives with a power 5k times greater than the current frame i, (4.8) can be

written as:

SNRi = N0 1 K N-1

+ i E « E iwIs 2EM 3N3 bl k=l,k^i 1=1-N

(4.11)

The B E R is then expressed as:

BERi = Q (SNRi) (4.12)

where Q is the complementary error function.

4.3.1 DSSS Basic Rate Physical Layer

The use of a single spreading sequence for the both basic rates allows us to

simplify (4.11). The aperiodic cross correlation Ck>i is replaced by the autocor

relation function, Ck>k for the specific Barker sequence employed. The autocor

relation sequence for the 11-chip Barker sequence employed in an IEEE 802.11


• 4 - 2 0 2

Delay (chips)

Figure 4.2 Autocorrelation function for 11-chip Barker sequence, +1,-1,+1,-1-1, 1,+1,+1,+1,-1,-1,-1, employed in the 802.11 DSSS P H Y

DSSS receiver is illustrated in Figure 4.2. Combined with the approximation

derived in (Karkkainen, 1992), the final S N R expression reduces to:

SNRi = INo 2Ebi

K

k=l,k^y

(4.13)

where a — 480.3. The value of a is determined using the autocorrelation

function for the Barker sequence illustrated in Figure 4.2, and the length of the

sequence, iV = 11. This analysis assumes B P S K modulation. The BR-DSSS

P H Y employs D B P S K for the 1 Mbit/s rate, and D Q P S K for the 2 Mbit/s rate.

A practical system employing differential modulation will require even higher

S N R at the receiver to achieve equivalent B E R performance (Proakis, 1995).

4.3.2 DSSS High Rate Physical Layer

Spreading codes for the high rate physical layer are generated using Equation

(2.2) resulting in 16 complex codes for the 5.5 Mbit/s rate at to 4 bits per

symbol, and 256 distinct complex spreading codes for the 11 Mbit/s rate at 8


bits per symbol. For each rate, we use Equation (4.11) to generate an expression

for the output B ER.

If we again use the ratio of bit energies for the current and interfering signals,

Sk, and the approximations of the previous section, we can use Equation (4.11)

to determine the S N R experienced by the ith frame, averaging this result across

all sequences in the set to determine the average probability of error.

4.4 Numerical Results

4.4.1 Single Interferer, K = 2

This scenario corresponds to Host 1 in Figure 3.1 attempting to send an RTS

or D A T A frame to Host 2, which is currently involved in the reception of a

frame from Host 3. The B E R given by (4.12), using (4.11) and (4.13) has

been calculated for a range of Eu/N0 values, as a function of 5k. In this case,

the i sequence corresponds to the signal currently being received, and the k

sequence the interfering signal. In each of Figures 4.3, 4.4, and 4.5 the presence

of the interfering signal from Host 1 (the A;th signal) significantly effects the

received B E R of the signal from Host 3, ith signal. This is observed through

the increased B E R as the value of 6k increases (i.e. the relative power of the

kth signal from Host 1 increases).

The results for the BR-DSSS 1 and 2 Mbit/s rates are shown in Figure 4.3.

With Sk - 0 dB, the interfering signal (A;) arrives with a power equal to the

current signal (i). At higher Eu/N0 the presence of the interfering signal will

increase the B E R of the initial signal, but will still allow a high probability of

successful reception of the initial frame. In this case, both connections will have

an equal impact on the other, providing the M A C protocol with a relatively fair

scenario to operate. This provides a strong basis for the fair channel access

observed with the equal S N R T C P and U D P experiments of Figures 3.5, 3.6,

3.10, and 3.11.


With Sk = 5 dB, the presence of the interfering frame raises the B E R to ~ 10 _ L 5 ,

significantly reducing the probability of successful reception of the initial frame.

If the A;th signal arrives with Sk < 0 dB, then the current ith signal will suffer

little increase in B E R and retain a high probability of successful reception.

The calculations for the HR-DSSS were performed by averaging the SNR as

given by (4.11) across the entire number of sequences in the set. This requires

the calculation of the interference parameter, rkj for each sequence in the set.

The number of codes in the set represents the number of interfering transmis

sions across which the result must be averaged.

For the 5.5 Mbit high rate sequence set shown in Figure 4.4 the BER follows very

closely that of the single Barker sequence employed by the BR-DSSS. In the case

of the 11 Mbit/s rate (Figure 4.5) the B E R impact is marginally worse, being

approximately 10~0-5 higher than for the BR-DSSS at Sk = 0 dB. This difference

is relatively insignificant, as in either case, the presence of an interfering frame

with Sk > 0 dB will, with a high probability, corrupt the current transmission.

4.4.2 Multiple Interferers, K > 2

Figure 4.6 illustrates the impact multiple interferers have on the average BER

for the BR-DSSS 1 and 2 Mbit/s rates. As the number of interfering frames is

increased from 1 to 4, the average B E R is increased from 10 - 7 to 10~4, 10~3,

and 10-2-5 respectively.

Figure 4.7 illustrates this for 11 Mbit/s with Ebi/N0 = 20 dB. Again, as the

number of interferers is increased, the B E R is significantly greater. In practice,

a single interferer with 6k > 2 d B will be sufficient to jam a competing hidden

connection. With these results we have assumed each interfering signal arrives

with equal <5fc. This result indicates that a host may be unable to success

fully access the radio channel when competing with a hidden terminal having

a marginally higher received signal power. Transmissions from any terminal

with a weaker received signal power are potentially jammed by the stronger


Figure 4.3 Correlator Output B E R Experienced by ith Frame for 2 Mbit/s Barker spreading code

connection, making the R T S / C T S handshake effective for the strongest host

only. As stated earlier, this analysis is based on the assumption of a B P S K

modulated signal. More complex modulation schemes require a higher signal

to noise ratio at the receiver to achieve equivalent B E R performance (Proakis,

1995). Analysis of differential and quadrature modulation schemes is considered

unnecessary for two reasons. Firstly, this analysis based on B P S K shows quite

conclusively that an interfering signal arriving with a relative signal power of

greater than 2dB will result in the corruption of the original signal. Secondly,

unless the short header option is employed (as part of the IEEE 802.11b ex

tension (Institution of Electrical and Electronic Engineers, 1999b)), the P H Y

header and frame preamble are transmitted using BPSK. Collisions are most

likely to involve this section of the frame.


10°

10"1

a: UJ

2io"2

2

6 § 1 0 J

a

DC

O ,„-4 s 10 & S ° n-5 E 10 2 £

R10"6

& <

10"7

10"*#

i;;:}|i;;;;;:|;;;i;il};;|:;;;;;;;;iS|

• ' • ' * * ^ ^ ^ ^ ^ T T T T I : | i |

'.'.•'.'•'•'.'.'.','.'.'.'.'.'.'.'.'. .,V 1 ; i • V •

H •::::::::::: ::::::::::'/::: ::::!;*

' ;> ; /,' r: :: : : : :,M : ::::::•:::::::: ^f; : : : ; : i • •

l-i-iill:!!!!!!!"!!!!!!*!!!!?!!!!!! ^ — # / >

.' / sijiiMji: ;•:••• i:Mfi::!<t::: ::::•!::

/ '

- / /

/ / '"

I:::*::::::::?::;::::::::::::::::;::

! 0 2

....*''.. >:!!-v* >::::/>:: •••••••

*::::::::

:::•!:::::'

• ;'''':«» ^ -

4 SdB

its** • i • •

; I ; ;

! /!'.

: > : :

; H :

.', . .

I 6

\&$

:::::::*::::::

it:::::-:::::::

: :

:::::::::::::: -

:::::: :-. : : ; : : ; I : : : : : : : : : : i 1:

-

:::::::•:::::::

Eb/No = Eb/No = Eb/No =

- - Eb/No = 1 8

! = :::!••-

::::::: Tz

= 5dB . 10dB :

= 15dB : = 20dB

10

Figure 4.4 Correlator Output B E R Experienced by Initial Frame for 5.5 Mbit/s C C K Spreading Sequence Set

4.5 The Retraining Hypothesis

The analysis presented in previous sections investigates a scenario where two

signals arrive at a common receiver, separated in time. W e investigate the

impact the later arriving signal has on the reception of the first arriving signal.

As each signal will arrive with an independent signal power, the relative power

between the signals is employed as the control parameter in the investigation.

IEEE 802.11 is different from a typical C D M A system, as all users employ the

same spreading code rather than rely on separate orthogonal codes to provide

multiple access. The assumption in this analysis is that the earlier arriving

frame has been detected, the receiver is synchronised and reception is underway.

This will involve detection of the peak in the correlator output signal.

The results in Section 4.4 illustrate that if the later arriving frame has a received

signal power greater than 2dB stronger than the earlier arriving frame, the B E R


10"

10- -

DC UJ CD 1 0 -

S

a

§ 1 0 r

o O 10"

s _ '5 10

10

10

:::::

1 1 1 !

f>:*!

:::::

" : : : ::::: '.'.'.'.'

iji<^

- • : •

~ : : :

:::..:...!::,.:.::....1 . , : . • ' • T - - - V V 1 ,:::

I:::;:;::::::::::::::::::::::;:: \\\\\\\\\\\\\\±\*\*Uj&^.V.\\\\\ :•::::::::::::::::::::;:::::r.±;.«>.r.U^jijj#*\\::::;::::::::

; ^ • * < * ' ; ; • * / & * •

;u<~'*\ ;"'V<-;—« « ! « ? |t =' "='= M = = = = = = = = = ! = = = i i • - ^ i * ^ - = i= = = = = = . = = = = ; ::::::::::::•:::::::::::::::: ;.:•:: : • > ( ' * : : : : : : :::::: I::::::::;::: I ••::

..•'"• x V v-. . . . !>««*> ;.. . .

!!!!! M M ! i!:!! = i«fn!! = = /!!M!M:::!M:=3 = iM = :::i: = = = : = ! = : = = : = = : •••:::::::::::. ;!! I!!;:/; !/!;•;: •:::::::::!:::::::::::!: ::::>:!::::::

::::;••' . *. .. ,.•'...: /r.. >...: ;

/ / it!! = !!!n!!:!i!!!l/!^!!;i!i!!!!!!!i!!i!!!!!:!!!!!!!!!!!!!!!!!!!!!!!!! ::::::::::::::::: l/l :/:::::::::::::::::::: :::•:•::::::::::::: •/•*•

: ' • / • / : •

= = = = = = = = = = = =><;=#= = = = = = = = = = = ! = = = = = = = = = = = = = = = = = = = = = = : = = = : = : ====== = f ' '/••I

/ : / /• T ;=•;;=:

/ f ••'•/• ir

/ = = i = = = t\ '.'.'•'. \\ = = i i = = I : = = :• = 1 = M = = = = = = = = = : : =:= : = = = = = = = = = = = i = = : = = : =

t '

' i i i i

._.

— —

"s • ••

: : • : : : : : : :

:'; : : : : : :

Eb/No=

Eb/No= Eb/No= Eb/No= i

i::i:::::i

:! = = = = = = -::::;

_ ::::::::::

: : : -::::::::::

1:: = :::: "

: : : : : : : : n

::::::::::

::::::: :-

5dB 10 dB i 15 dB : 20 dB

4

SdB 10

Figure 4.5 Correlator Output BER Experienced by Initial Frame for 11 Mbit/s C C K

Spreading Sequence Set

10"

10"

210" Q.

| 10"3

§ 1 0 Jo

o O 10

3 10

S

10"

10-

! !"::*::,: ' ••••-•n

* v- -" ' *». .^r:.. ..,<'. * V ^ .•' ..,i* *.. yr.;,.-.'. .<:-. ••*• jT .„"•=••'•' -.•#• :'

• " / .,=-*•' « < *

::::::::::::::::*::^:::;;-::;:::::::>::::::::::. z'y'-y :-y

- = = = = :M = =*::=>n = = = =>?=M = = :: = ;:=J«: = = = = = = i = = M:= = * / 1 /

/ / >

/ / / • • /

::/:::/:::::-::::::::::::/::::::::::::::::::::::::: > y .-...: / .../„„o*=.. =:= = = = = = !/: = . = = = = = : : / ,-? ' / y .-•• /

{ ~ ' - ; ' • • ! ' • • •

:::::•::::: : :::::;:*:::::::::::::.!::::::::::::::::::: '•":•'' /

n!r!;i!!!!!ii!!<:!!!i!!!!!!!!!!!!i!!!!i!!!i!MM!!:i! /

•-" / • • : • : • •

T^nTH ' • : • : • $ * :

.<.

<•

:: >

•:;

• ; .;

• •

: :

1

TTiTi »

::••:•*

?2*^iV~~

•

• : I : : :3 : : : : : :

::::::'::::::; !!!!!!"!!!!!!

::::::;::::::

r

•Sli w

....

::::::::::

:•:•:::: fl

-

::;::::;-!

K = 1 .

K = 2 :

K = 3 : K = 4 •

4

SdB

10

Figure 4.6 Barker Code (K - 1) interferers, Ehk/N0 = 2MB


10°

10"'

Receiver Output BE

o

o

Aquired Fr

ame Correlator

o

o

o

4,

i,

i.

10"7

10 ,

.*.~£j*^r^'"'':'~ >•>'"*'"•

::>::::y :i :::£::::: ::::::#:!::::: / / 0;.i *...

_...; :./

/ ' " • * " : ' '

'•

i!!ll!!!!!!i!!i!!!!r

!iH = ;;!!!;i!i = !i = r=

:::*:::::::::::::::::

_

• . . . i i i i

0 2 4 6 SdB

K=1 . K=2 ! K=3 :

- - K=4

8 10

Figure 4.7 C C K codes, (K - 1) interferers, Ehk/N0 = 20dB

at the output of the correlation receiver will be intolerably high, thus destroying

the earlier frame. This result in itself is not unexpected, as the later arriving

frame is simply a 'loud' noise source from the perspective of the the earlier frame.

However, if the later frame is sufficiently strong, the signal detection mechanism

can be effectively reset when this later frame arrives. The correlator output will

include both frames, offset in time, and m a y result in the re-synchronisation of

the receiver with the new stronger correlator output.

Therefore, in certain scenarios the receiver m a y be able to re-train onto the

new signal (Kim et al., 1995). IEEE 802.11 interfaces have been designed to

exploit this, and attempt to successfully receive both signals (Mud et al., 1999).

However, the results of this investigation suggest that the interfering signal will

have an intolerable impact on the received B E R of the initial signal. It is also

possible to reverse this scenario such that the interfering signal has a lower re

ceived power than the original signal. In this case, the B E R experienced by

the original signal will not be significantly increased by the interfering signal.


Further, if the receiver is retrained onto the interfering signal, the scenario is

effectively reversed with the weaker signal becoming the new source of inter

ference for the stronger signal. The stronger signal will be received will little

impact on the B E R . The impact of this behaviour will be examined in greater

detail in the following chapter.

4.6 Conclusion

Understanding the impact an interfering signal will have on the reception of a

previously arriving signal is important for the development of a suitable model

to accurately describe the behaviour of a radio modem. In this chapter, we

have extended previous analysis to determine closed form expressions for the

bit error probability observed at the correlator output for a given signal in the

presence of a c o m m o n code interferer. Numerical results illustrate that the

strong relative received signal power dependence of channel capture behaviour

with the IEEE 802.11 M A C protocol described in Chapter 3 can be attributed

to the impact of an interfering signal.

Analytical expressions describing the BER of a received signal in the presence of

multiple access interference for a number of IEEE 802.11 DSSS physical layers

have been developed. Numerical results indicating that a received signal power

difference of greater than 2dB is sufficient for the stronger signal to effectively

jam a weaker signal, closely match the experiments presented in Chapter 3. This

renders the R T S / C T S handshake ineffective for all but the connection with the

highest received signal power.

The major contribution arising from this analysis is the qualification that rel

ative received signal power between contending hidden connections is the sig

nificant parameter in determining which connection is able to gain preferential

access to the radio resource. A relative signal power of greater than 2dB is suf

ficient to result in a channel capture state for the stronger connection. In the

following chapter, we investigate modelling capture behaviour, with respect to


the ability of a specified model to match properties of empirical trace data. W e

employ the quantitative results derived in this chapter to develop an improved

model which allows for accurate simulation of the behaviour of an IEEE 802.11

radio modem.

Chapter 5

Modelling Packet Capture Behaviour

5.1 Introduction

In this chapter, we present an investigation of techniques used to model the

packet capture behaviour of an IEEE 802.11 wireless network interface. Chap

ter 2 outlined a number of capture models which have appeared in the literature

(Cheun and Kim, 1998; Davis and Gronemeyer, 1980; Arnbak, 1987). Capture

models are generally employed to either determine the channel throughput as

a function of offered load, or alternatively as a technique to model the radio

interface in a simulation environment. The ability of a capture model to ac

curately reflect empirically observed behaviour when employed in a simulation

application is an important aspect of capture model performance. The aim of

this chapter is to investigate the features a capture model should exhibit in

order to support improved simulation of an IEEE 802.11 radio interface. Meth

ods required to provide a reliable simulation tool will also be investigated. This

is performed through both a qualitative and quantitative comparison of sim

ulation results with empirical trace data. A second aim of this chapter is to

address the shortcomings of existing models through a new model, designed to

meet the requirements for improved simulation of an 802.11 radio interface.

93

Modelling Packet Capture Behaviour 94

Section 5.2 presents an overview of the significant capture models presented in

the literature. The results presented in Chapters 3 and 4 motivate the introduc

tion of a new model designed to represent the salient features of an IEEE 802.11

radio modem. Therefore, in Section 5.3 we introduce the Message Retraining

model based on the design of an IEEE 802.11 radio m o d e m (Mud et al., 1999)

and the results presented in Chapter 4, combined with previous work on parallel

receiver structures (Kim et al., 1995), and multiple access interference (Ware

et al., 2001a; Pursley, 1977). Improved simulation models are necessary for the

future development of mechanisms to overcome or prevent the unfair behaviour

observed in Chapter 3.

Section 5.4 presents the results of a qualitative analysis in which we compare

trace data obtained via simulation with empirical trace data. Given that T C P

timers were shown to have a significant impact in Chapter 3, we undertake initial

experiments with U D P as the primary transport. This will remove the poten

tial for adverse interaction between the T C P timers, and M A C retransmission

timers, and allow a study of the capture effect in isolation. T C P results are

included for completeness. As Chapter 3 has illustrated that fairness proper

ties are a key element of the performance characteristic in a physical network,

Section 5.5 presents a quantitative analysis of simulation and empirical trace

data using two fairness indices. The analysis presented in these two sections

will provide insight into the ability of each capture model match the fairness

behaviour of a physical system, and in doing so re-create salient features of

actual system performance. This will provide an indication of which model is

most applicable for a given scenario. Finally, Section 5.6 concludes the chapter.

5.2 Capture Models

A significant body of literature (Cheun and Kim, 1998; Davis and Gronemeyer,

1980; Arnbak, 1987) exits investigating the development of models describing

the initial capture of a frame by a radio modem. The common goal of each model

is to determine the probability with which a given frame may be captured by


the receiver as a function of the number of active stations. This probability

is then used to determine the channel throughput achieved, as the product of

capture probability and offered load.

As discussed in Chapter 2, capture can be considered to occur at two levels:

• Packet Capture, also termed Modem Capture is a property of both

the radio m o d e m and modulation technique employed (Soroushnejad and

Geraniotis, 1991). Packet capture results in a given transmission being

'captured' by the receiver while rejecting interfering frames as noise. Sev

eral models based on either power (Arnbak, 1987), time of arrival (Davis

and Gronemeyer, 1980), or both, (Cheun and Kim, 1998) have been pro

posed to evaluate the probability of a frame being captured by a receiver

as a function of the number of interfering frames.

• Protocol Capture, also termed Channel Capture is induced by protocol

timing, and results in a channel being monopolised by a single node, or

subset of nodes in a given geographic region. Protocol capture has been

identified as a significant problem for multihop packet networks in many

scenarios where disconnected topologies exist (Nandagopal et al., 2000;

Bensaou et al., 2000), or higher layer retransmission and backoff timers

are employed (Gerla et al., 1999a; Tang and Gerla, 1999).

Two significant stages are present in the successful reception of a frame by a

radio modem. Initially, the frame must be successfully detected and captured by

the receiver. Following this, successful reception of the frame must be achieved

in the presence of interference, from other transmissions and external noise

sources. Most literature (Cheun and Kim, 1998; Davis and Gronemeyer, 1980)

has considered only the probability with which successful detection and capture

of a frame at the start of a transmission slot occurs. The second aspect requires

an understanding of the impact multiple access interference will have on the

captured frame (Soroushnejad and Geraniotis, 1991; Pursley, 1977; Ware et al.,


2001a) and depends significantly on the modulation technique and spreading

codes employed.

Capture models are often used when simulating the performance of wireless

networks. The results presented in Chapters 3 and 4 suggest a more complex

capture behaviour is present in the case of an IEEE 802.11 radio interface,

resulting in the significant unfairness evident in experimental data. Further

complications arise in cases where hidden nodes are likely (e.g. a mobile ad hoc

network). Specifically, there is a strong probability of late starting transmissions

colliding with other signals at the common receiver. In a scenario where all

nodes are able to sense carrier, slot boundaries are easily identified and defined,

thereby reducing significantly the probability of a new transmission interfering

with an ongoing reception.

In scenarios where carrier sense mechanisms are unreliable, it is possible for

a node to have little knowledge of an ongoing hidden transmission. This in

troduces the potential for an interfering transmission to arrive at a common

receiver at any time during a slot. As illustrated in Figure 5.1, this can be due

to differences in the slot time boundaries observed by both hidden nodes. This

is further complicated by the slot timing mechanisms within 802.11. Rigid slot

boundaries are not maintained, requiring nodes to infer slot boundaries from the

beginning and end of surrounding transmissions. Data transmissions are able

to occupy multiple 'slot times'. Guard times are inserted between sensing an

idle channel and transmitting (DIFS), or returning management frames (SIFS)

to maintain the semi-slotted channel. However, the lack of carrier from an op

posing hidden node increases the possibility that a hidden node will transmit at

what appear random times to the central node at which the collision occurs. In

the example shown in Figure 5.1, Host 3 has commenced a data transfer prior

to Host 1 (being hidden from Host 3) initiating a carrier sense operation. O n

sensing a clear channel, Host 1 defers for a DIFS then transmits an R T S mes

sage. This collides with the data frame from Host 3, illustrating the potential

for a late starting transmission to interfere with an ongoing transmission.


HOST1

HOST 2

HOST 3

Sense Clear Channel

i i Slot Time/ / /

Error / DIFS / RTS /

\

1

/ReceiveDATA / Collision

4 / /

/ Transmit DATA / 1 'II / Time

Figure 5.1 Potential Slot Time Error

In the following sections we briefly review the significant capture models pre

sented in the literature.

5.2.1 Delay Capture

Delay capture originally described by Davis and Gronemeyer (Davis and Grone

meyer, 1980), enables the capture of a frame in a given timeslot, provided no

other frame arrives within a given capture time, Tc of the initial frame. Only

the initial frame is able to be received. Frame arrivals are assumed uniformly

distributed on the interval [0,TU], where Tu represents the maximum variation

in packet arrival times at the receiver. The initial frame arrives at time T\, and

may be captured by the receiver provided that Tt > Tx + Tc, where Tt is the

arrival time of the ith frame. This model is chiefly controlled by the parameter

Tc, governing the period of time required by a receiver to detect, correlate with,

and lock onto the received signal. The larger the Tc/Tu ratio, the less effective

the m o d e m is at capturing a frame.


5.2.2 Power Capture

Power capture, originally described with Rayleigh fading, and constant trans

mitter power (Arnbak, 1987), is described by the following inequality over the

interval [0,TC]:

N

Pmax > 7 ^ Pi (5.1) i=l

where Pmax is the power of the strongest of N arriving signals, each with power

Pi, within the capture time Tc. The model allows a frame to be captured pro

vided Pmax is greater than the sum of the power of all other received signals,

Pi, times the capture ratio, 7. The received signals are assumed to have phase

terms varying quickly enough to allow incoherent addition of the received power

of each frame. This model is the most commonly employed in the simulation

of radio modems, allowing the first arriving frame in a slot to be received pro

vided no other frame arrives within the capture time, Tc having a signal power

violating Equation (5.1). In the case where Equation (5.1) is violated, no frame

is captured.

5.2.3 Hybrid Capture

The hybrid model was originally proposed by Cheun and Kim (Cheun and Kim,

1998). The power capture effect is used to increase the capture probability of

the first arriving frame in a given timeslot, even though the delay model would

otherwise indicate capture has not occurred. Capture occurs when the following

inequality holds:

N

1Y,pi\Ti+Tc-Ti]<TcPi (5-2)

i=2

where T\ and Pi are the time of arrival and power of the initial signal respec

tively, Tc the capture time required by the receiver to synchronise with and


prepare to receive the initial signal, T; and Pi the time of arrival and power of

the zth arriving signal respectively, and 7 the capture ratio. The total accu

mulated energy must be less than the energy received from the first packet, Pi

over the capture interval Tc. This model results in a greater capture probability,

reflecting the ability of a direct sequence spread spectrum receiver to correlate

with the initially detected signal and reject other signals as noise.

5.3 Message Retraining Reception Model

As discussed in Section 4.5, contrary to each of the models presented above,

(Mud et al., 1999) describes an enhanced capture technique which allows a mo

dem to successfully receive a signal that would otherwise be considered lost by

the previous models. The m o d e m implements a Message In Message process,

whose function is to monitor the energy received on either antenna during re

ception of a frame. If an increase in energy beyond a given threshold, jmr is

observed, the m o d e m attempts to synchronise with and demodulate the new

energy as a potential new signal. If this is achieved, a retraining process allows

the m o d e m to prepare to receive this new signal once the prior transmission has

finished.

Another factor which motivates the introduction of a new model is the behaviour

of the correlation detector when a new stronger signal arrives. The new signal

is a source of interference for an ongoing reception process. In cases where the

power of the new signal is sufficiently higher than the initial signal, then the

potential exists for the correlation detector to be 'reset' by this increase in signal

power. This is due to the use of common spreading codes for all users in the

network, as the output of the correlator appears identical for all signals, simply

offset in time. The result may be the subsequent loss of the initial signal, and

successful reception of the new signal. In cases where the detection circuit does

not employ multiple reception paths discriminating between users through time

separation of the arriving signals (Kim et al., 1995), the receiver will be unable

to receive the initial signal in the case where an interfering signal has sufficient


HOST1

HOST 2/ AP

Rx Message

Rx Signal

HOST 3

/ Signal 2 /

/ Rx Signal 1 / Rx Signal 2 /

, J r 1 Y

1

/ - //////////////

Signal 1 Starts > Signal 2 Starts Time ' Rx signal level increases

If Increase in Rx Signal >y ml

Signal 1 corrupted, Signal 2 received Else, standard power capture

Figure 5.2 Operation of the Message Retraining model

power. In the alternate case, a stronger signal would suffer little interference as

a result of the weaker signal.

In either case, each of the capture models previously described will result in a

pessimistic capture probability for a frame over a given duration. The message

retraining ability of the m o d e m also extends the time scale over which capture

must be considered. Retraining may take place at any time during frame recep

tion, as opposed to the delay, power and hybrid capture models which consider a

short duration at the start of a frame or slot. W e therefore propose an extended

capture model, termed Message Retraining which incorporates this enhanced

capture behaviour.

The model allows the modem to receive a new signal (Signal 2 in Figure 5.2),

which may arrive at a random time during the reception of a previous signal

(Signal 1 in Figure 5.2), provided the new signal has sufficient relative power

to enable successful synchronisation and demodulation of the frame preamble.


In Chapter 4, we illustrated that the Eh/N0 associated with the new signal

will have a significant impact on the B E R observed at the correlator output

for the original signal. Results indicate the previous signal will be corrupted

if the power difference between the new and existing signals is greater than a

threshold of greater than 2dB. The Message Retraining model accounts for this

by dropping the initial frame if a new frame is detected with a signal power

greater than the current by the Message Retraining threshold, jmr. Successful

reception of a frame, Fj will occur provided that over the duration of this

transmission: N

Imr J2 P i < P J (5-3)

This model allows for the successful reception of the frame received with the

strongest power throughout its own duration, i.e. Fj will be successfully received

provided no other frame arrives over the duration of Fj with a signal power

greater than Pj + jmr (measured in d B m ) . Furthermore, the initial frame may

be successfully received provided that power capture described by Equation

(5.1) holds.

5.4 Simulation Investigation

5.4.1 Methodology

The aim of this experiment is to perform a qualitative comparison of the trace

output of simulation trials obtained with each capture model against the em

pirical trace data. The scenario under investigation involves controlling the

received signal power on each connection throughout the experiment, using the

topology illustrated in Figure 3.1. Each node initiates a data transfer into the

common node.

In the UDP experiments, both connections commence with an equal received

S N R of 25dB. 10 seconds into the experiment, the signal power of Connection

A is reduced by approximately 8dB through to the end of the experiment,


thus making Connection B the stronger connection from this time on. In each

experiment, Connection B commences 0.5 seconds after Connection A.

With the TCP experiments, Connection A commences the experiment with a

received S N R of 25dB, Connection B with a received S N R of 20dB. 5 seconds

after the start of the Connection A trace, the signal power scenario is reversed

with Connection B made the stronger of the two connections.

Both signal power scenarios are examined as a means of introducing variability

into the results. Through this method, it also becomes possible to examine

the impact a change in received signal power has on the performance of both

the M A C protocol and the transport protocol with each capture model. In

the case of U D P , a single change is employed to examine the ability of each

capture model to cause M A C behaviour matching the empirical data. With the

T C P experiment, a different scenario is employed in which the signal power on

each connection is reversed. This is to investigate the ability of the capture

model to accurately induce the interactions between transport and M A C layer

retransmission timers observed in the empirical data. The assists with the

qualitative analysis in which the ability of the model to match the characteristic

shape of the empirical trace.

The series of results presented in this section involve the transfer of a constant

number of bytes. The differences between each model are illustrated in the char

acteristics of each curve, including the different duration of each trial. Therefore

when presenting these results it is more beneficial to be able to examine the

progress of each trace in a manner which allows the instantaneous behaviour

of each connection to be observed, rather than comparing the aggregate perfor

mance over a fixed timescale. This provides the reader the ability to visually

determine which connection is gaining preferential access to the channel and

how the related capture effect is evolving throughout the experiment.

Simulation trials have been undertaken with the environment described in the

following section. Results for the U D P and T C P experiments are presented in


Sections 5.4.3 and 5.4.4.

5.4.2 Simulation Environment

Each of the capture models described previously has been implemented within

the ns-2 simulation package (version 2.1b3) (UCB/LBNL/VINT, 1999). This

package contains a detailed 802.11 P H Y / M A C layer model, as well as provid

ing excellent implementations of higher layer protocols such TCP/IP, UDP,

F T P etc. The channel model employed is an Additive White Gaussian Noise

( A W G N ) Two-Ray Ground model. Capture decisions are made within each

modem based on the received signal strength, capture threshold, and other rel

evant parameters for each model. Each node receives a copy of the transmitted

packet and based on the received power, determines whether the transmission

was observable or not. If the frame is received with sufficient signal power, a

capture decision in accordance with each model is made prior to passing the

frame up to the M A C protocol. The network model considered is one involv

ing hidden terminals over a semi-slotted 802.11 M A C / P H Y layer, illustrated in

Figure 3.1. All nodes employ a common spreading code with no power control.

Parameters for the radio interface are listed in Table 5.1. The capture thresh

old, 7, is selected based on measurements presented in Chapter 3, results of

analysis performed in Chapter 4, and design parameters of the message retrain

ing process in an 802.11 modem (Mud et al., 1999). Pt represents the nominal

transmitter power of the radio modem, Rb the channel bit rate (determined by

the combination of spreading sequence and modulation technique employed),

/ the operating frequency, and Tc the capture interval which corresponds to

the duration of the preamble and sync bits in the 802.11 P H Y header. As the

802.11 standard requires that the P H Y preamble and header are transmitted at

IMbit/s with an 11 chip Barker code using D B P S K modulation, or possibly 2

Mbit/s with the 11 chip Barker code using D Q P S K modulation where the short

P L C P preamble/header option is available, we use a value of R B at 2Mbit/s.

Simulation trials are also performed over shorter time scales than the experi-


Table 5.1 Modem Simulation Parameters

Parameter

7 Pt (Nominal)

Rb Sensitivty

/

Tc

Value

2dB 15dBm

2 MBit/sec -95 dBm 2.412 GHz 120/zs

mental trace as we are investigating the ability of the simulation model to react

to changes in the received signal power scenario. Accordingly, we are not using

comparative aggregate throughput as a performance metric.

5.4.3 UDP Results

The following results are from experimental trials employing a UDP transport

layer. Each source is modelled as a greedy source which transmits packets from

the network layer as quickly as the M A C layer will allow. In each case, it is

important to acknowledge that we are examining the ability of the simulation

model to match the dynamic behaviour of the real system, therefore we are

examining instantaneous results, rather than comparing longer term averages.

The behaviour we are attempting to match through simulation is in itself an

instantaneous behaviour. Therefore, in an effort to provide an equivalent basis

for comparison, each simulation trial is performed with the same random num

ber generation seed for all capture models. Complete sets of experiments were

repeated with a number of different random seeds. The results presented in this

and the following section represent typical results from this process.

Trace Data

The empirical trace data presented in Figure 5.3 illustrates similar unfairness to

the trace data presented in Section 3.5. The reduction in received signal power



30

Time (sec) 40 50 60

Figure 5.3 Trace Data U D P Transport: Lucent Chipset

of Connection A just before the 10 second point is obvious in the trace. Again,

the horizontal axis represents time, the vertical axis data successfully received

at the common node. The received signal power is reduced using R F absorbing

foam at the transmitting node.

No Capture

Figure 5.4 illustrates a simulation trial without a capture model. Any colliding

frame at the receiver will result in both frames being corrupted. Accordingly,

there is no indication of any change in the behaviour when the signal power

of connection A is reduced. This is to be expected as signal power plays no

role in determining the reception of a frame in the event of a collision with

this model. The trace exhibits short periods where either connection is able to

dominate the channel. This behaviour is random, and due to the ability of a

node to maintain a lower average backoff window over the period in which it has

captured the channel. Obviously, this trace does not exhibit similar behaviour

to the empirical trace of Figure 5.3.


1400

1200

1000

s m £. 800

DC co

a

600

400

200

_

-

1 1

/ /

— * — ^ - 1

1 1 1

/ / /' /

i i i

i i • I

/ X ,

f -y


i i i

-

+ X

8 9 Time (sec)

10 11 12 13

Figure 5.4 No Capture Model U D P Transport

Delay Capture

Figure 5.5 illustrates a simulation trial with the delay capture model described

in Section 5.2.1. Again, this trace exhibits alternate periods of channel capture,

where either connection gains access to the channel at the expense of the other

host. Between 7 and 9 seconds, Connection A has captured the channel, then at

9 seconds, Connection B manages to reverse this scenario. There is no indication

that the relative signal power change has had any impact at 10 seconds, as is

evident in the empirical trace after the signal power of connection A is reduced.

Power Capture

The power capture trace illustrated in Figure 5.6 again illustrates periods of

random capture through the period where signal power is equal. After Connec

tion A is reduced at 10 seconds, random periods of capture appear to remain as

both connections are still able to capture the channel for short periods. Between

approximately 10 and 11 seconds, Connection A is able to maintain preferential

access to the channel despite being the weaker connection. This behaviour is


1400

1200

1000

m * 800

| 600 eg eo a 400

200


8 9

Time (sec) 10 11 12 13

Figure 5.5 Delay Capture Model U D P Transport

1600

1400

1200

£ m vr

T& > 0>

ai CC ra a a

1000

800

son

400

200 •

_

-

-

•

-

-

— 1

/

1 1

..J

1 1 i

/

<

1 1

, . /

/


/

X

-

-

-

-

-

-

8 9

Time (sec) 10 11 12 13

Figure 5.6 Power Capture Model U D P Transport


1600

1400

1200

5, 1000 m

> 800 o a d>

IT 2 600 CO

a 400

200

I •

-

-

-4

/

<- * — t —

1 1

ry ' >

/ / /

• 1 1

/

i i i

i 1 —


> •

/

-

•

_

-t-

X

8 9

Time (sec) 10 11 12 13

Figure 5.7 Hybrid Capture Model U D P Transport

not in concert with the empirical trace in Figure 5.3.

Hybrid Capture

The Hybrid model results illustrated in Figure 5.7 illustrates much less exag

gerated periods of capture for each host, with improved sharing throughout

much of the period, though Connection B does achieve a higher throughput

than Connection A. W h e n the signal power is reduced on Connection A at 10

seconds, Connection B is able to achieve greatly improved access to the channel,

matching the empirical data more closely than the previous models.

Message Retraining Capture

The Message Retraining model results illustrated in Figure 5.8 exhibit approx

imate fair sharing through until the signal power change at 10 seconds, when

Connection B is able to capture the radio channel. Short periods where either

connection is able to slightly dominate the channel are present until this point

(as with the Hybrid model). The resulting trace illustrates an improved ability


1600

1400

1200 •

<D

co

i > <D O <D

tr (0 CO

D

1000

/

Connection A + Connection B *

8 9 10

Time (sec)

13 14

Figure 5.8 Message Retraining Capture Model U D P Transport

to match the empirical data compared with the Delay and Power models.

Both the Hybrid and Message Retraining models illustrate improved ability

to match the experimental data. In particular, both are able to match the

behaviour after the change in relative signal strength occurs 10 seconds into

the experiment. This result indicates that from a qualitative viewpoint, the

Delay, and Power models do not model the necessary features of an 802.11 radio

interface in order to support accurate simulation. Additional investigation of the

performance of the Hybrid and Message Retraining model supporting T C P data

streams will further establish the ability of each model to reflect the empirical

data.

5.4.4 TCP Results

Trace Data

Figure 5.9 illustrates the time evolution of the T C P experiment used for com

parison with simulation. Connection A commences as the stronger connection


1200

1000

•5T 800

£ m 5 600 -

tr

Q 400

200 i

f

10 15 20

Time (sec)

25


30 35 40

Figure 5.9 Trace Data T C P Transport: Lucent Chipset

with an S N R of 25dB. Connection B remains at 20dB throughout. 5 seconds

into the experiment, the scenario is reversed with the received signal power

of Connection A reduced by 8dBm using R F absorbent foam. Connection B

then manages to capture the channel, preventing Connection A from accessing

the channel. In this example, Connection A suffers a significant T C P time

out between approximately 5 and 33 seconds though the experiment. In this

case we would expect the simulation traces to match the changes in behaviour

at approximately 5 seconds, through the common period of each connection.

The stronger host should gain preferential access to the channel, with the trace

having the same characteristic shape.


2500

2000

& m 1500

i > O « 1000 To Q

500

0 4 6 8 10 12 14 16 18 20 22 24

Time (sec)

Figure 5.10 No Capture Model T C P Transport

No Capture

In the case where no modem capture is implemented, any colliding signal at the

common receiver will result in both frames being lost. Backoff and retransmis

sion then results in approximate sharing of the radio channel. In Figure 5.10,

alternating periods where either connection is able to dominate the radio re

source are due to protocol timing interactions between the M A C timers in each

node, the M A C and T C P retransmission timers, and the T C P timers in each

node (Gerla et al., 1999b). These periods are similar in nature to those caused

by the M A C layer with the U D P experiment. In this case, it is not possible to

identify which interaction results in the alternating channel capture periods.

Delay Capture

The Delay capture model makes no account of signal strength characteristics.

Figure 5.11 exhibits random periods during which one of the connections is

able to capture the majority of the channel resource. This is again due to the

interaction between M A C backoff timers and the T C P timers at the transport

1 1

-

• y //:' ,

i i i

/ /

/

1 1 1

1 " t 1

• <

i i

r

Connection A + Connection B x

< •


y / , ,+ Connection A +

/ Connection B x * rL i i i i i i i i

4 6 8 10 12 14 16 18 20 22 Time (sec)

Figure 5.11 Delay Model T C P Transport

layer. Connection B also gains a slightly higher transfer rate than Connection

A, showing no evidence of the changed signal power at 10 seconds. This is due to

Connection B starting before Connection A, and therefore having a larger T C P

window at the time Connection A commences. Connection B is able to expand

it's T C P window without contention for the channel, whereas Connection A

must contend from the establishment of the T C P connection. The connection

start times were staggered in this manner to match the experimental data.

Power Capture

The power capture model trace in Figure 5.12 displays similar behaviour to

the Delay capture model. Neither connection is able to dominate. There is

no evidence of the sustained channel capture exhibited in Figure 5.9, nor any

evidence of the transmission power change at 10 seconds.

As with the UDP experiments, the Power and Delay models are again unable

to accurately reflect the performance of an actual 802.11 radio interface. As

both these models tend to be reasonably pessimistic, destroying both inter-

ilJUU

2000

m 1500

£ co Q

1000

500


2500

2000

m 1500

1000

500

0 <* 4


10 12 14

Time (sec) 16 18 20 22

Figure 5.12 Power Model TCP Transport

fering frames in many circumstances, is would be reasonable to expect that a

more suitable model should behave in a more robust manner when considering

collisions. Both the Hybrid and Message Retraining models fit this criteria.

Hybrid Capture

Connection B again gains the advantage of a larger TCP window at the time

Connection A commences. Unfortunately, as with the Power model, there is

no evidence of behaviour approaching that observed in the empirical data of

Figure 5.9. This is relatively unexpected, as the Hybrid model was able to

reflect empirically observed behaviour with U D P quite well. However, this result

indicates that the Hybrid model does not reflect the appropriate behaviour

required to accurately model an IEEE 802.11 receiver.

Message Retraining

The trace for the Message Retraining model in Figure 5.14 appears to match the

measured data of Figure 5.9 in terms of characteristic shape, and response to


2500

2000

m 1500

0)

8 OC CO CO Q

1000

500

0 <>• 4

1 I

-

/y " ,

i

s

/

i

y y

i

i • 1 — i 1

, • / /

-x /

/

/

/

Connection A + Connection B x

i i i i

6 8 10 12 14

Time (sec)

16 18 20 22

Figure 5.13 Hybrid Model TCP Transport

2500

2000

m 1500

1000

500 -

n 1 1 1 r -i r

_i i


j i 12 14 16

Time (sec)

24

Figure 5.14 Message Retraining Model TCP Transport


the changes in signal strength. Once Connection A commences as the stronger

connection, Connection B is prevented from gaining reliable channel access.

10 seconds into the trace, Connection B, the new stronger connection, is able

to capture the channel from Connection A, which is in turn prevented from

gaining fair access until Connection B finishes. In this experiment, neither

connection suffers a timeout of a similar magnitude to that of Connection A in

the empirical trace, however, both connections do suffer timeouts in excess of 2

seconds throughout the experiment.

The changes in received signal power throughout the experiment which have

such a dramatic impact in the empirical trace data, are not reflected in Fig

ures 5.11, 5.12, and 5.13. This represents a significant shortcoming for the

Delay, Power and Hybrid capture models, which this investigation shows are

unable to accurately reflect the impact of changes in relative signal strength on

the fairness performance of each connection. This can be attributed to the be

haviour of each model in cases where a collision of signals with a relative power

difference above a specified threshold occurs. In each model, once a collision

is determined to have occurred (as opposed to the capture of a frame), both

frames are assumed lost. One conclusion from this investigation is that this is

a pessimistic assumption, resulting in a model which displays a greater level of

fairness than is present in a physical system.

The results presented in both this and the previous section indicate that from

a qualitative viewpoint, the Message Retraining capture model is capable of

providing the basis of an improved simulation technique for an 802.11 radio

interface. However, this comparison is on the basis of a qualitative visual com

parison of trace data only. In the following section, we employ two fairness

indices in a more detailed investigation which will quantify the relative perfor

mance of each model against empirical data using fairness indices.


5.5 Fairness Study

Fairness in wireless networks can be a difficult quantity to define. In the cur

rent context we require that each node is able to access the channel without

sustained delay, and that no node is able to monopolise the radio channel at

the expense of other nodes. This should be independent of the physical network

topology. In cases where the M A C does aim to provide a guarantee on delay

bound or throughput, a more detailed definition of the fairness properties would

be necessary.

Previous experiments in Chapters 3 and 4 have illustrated the significance of

relative signal power in determining the distribution of channel access. There

fore we have designed a hidden terminal experiment for this investigation in

corporating signal power changes throughout the data transfer. Connection B

commences the data transfer with a received S N R of 20dB. Connection A then

commences a data transfer with a received S N R of 25dB, 1 second after Connec

tion B. This experiment examines the ability of each model to reflect the impact

of a change in the relative received signal power at the common receiver. This

experiment is performed with greedy U D P sources. The experiment is then

repeated with with greedy T C P sources, and both the received signal power

and starting order of each connection reversed.

To make a quantitative comparison of the results obtained with each capture

model, a fairness metric is required. Following (Koksal et al., 2000), we employ

two fairness indices : Jain's Fairness Index (Jain et al., 1984), and a new index

proposed in (Koksal et al., 2000), the Kullback-Leibler Fairness Index. In each

case, a sliding window method is used to calculate the fairness over a specified

horizon. The window slides along a packet sequence which indicates which

node has successfully gained access to the channel. A n instantaneous value is

determined for each index, with the average calculated across the entire trace.

Results are presented as curves illustrating the fairness index as a function of

window size. This provides an indication of the fairness horizon, or time scale


over which a user may expect a specified level of fairness measured with an

appropriate index.

As the TCP trace records successfully acknowledged data, this investigation will

provide an indication of the fairness associated with the data transfer at the

transport layer, including effects from the M A C and P H Y layers. W e include the

transport protocol in this manner, as T C P is the most common transport pro

tocol in use today, and any wireless M A C / P H Y protocol should be expected to

support competing T C P streams without imposing additional fairness charac

teristics. Further, comparison with the U D P results also provides useful insight

into the impact protocol timing interactions have on the observed performance

of the network.

5.5.1 Jain's Fairness Index

This index has been used widely in the literature to describe the fairness char

acteristics in both congestion control (Jain et al., 1984) and wireless M A C pro

tocols (Koksal et al., 2000). A n ideal fair distribution of channel access would

result in a value of 1 for this index, though values above 0.95 are typically con

sidered to indicate excellent fairness properties. The index , Fja, is defined in

Equation (5.4) below:

(5>) Fja = - = £ (5.4)

1=1

where pi is the fractional share achieved by the ith connection, and N is the

number of active connections. A value of 0.7 would imply that 3 0 % of nodes

were suffering significant unfairness.

5.5.2 Kullback-Leibler Fairness Index

The Kullback-Leibler Fairness Index was first proposed in (Koksal et al., 2000).

The technique considers the distribution of channel access for each node as a


probability distribution, f. The Kullback-Leibler distance D (T\\T\ , an entropy

measure of the 'distance' between two probability distributions, is calculated

between the desired distribution T, and the measured distribution, f. This

index is defined below in Equation (5.6):

" 1 1 1 D(r||f) = D ([Pl,p2...pn] N' N'" N

(5.5)

N

= [Y^Pi l0S2 Pi + loS2 N

J=l

where N is the number of nodes, and pi the fractional share achieved by the

ith node. A value of 0 corresponds to a perfectly fair system, with values below

0.05 typically indicating a system with excellent fairness properties.

5.5.3 Results

Simulation trials of the UDP and TCP experiments were undertaken, and both

fairness indices calculated as a function of the sliding window size. Figures 5.15,

and 5.17 illustrate the experimental data used for comparison with the simu

lation models. Figures 5.16, and 5.18, present both fairness indices for each

capture model described in previous sections, the empirical data, and a simula

tion trial employing no capture. The window size in each case does not extend

beyond 1000 frames, as this represents a very large fairness horizon of several

seconds.

UDP

Commencing with the UDP experiment, the Power, Delay, and Hybrid models

over estimate the measured fairness as the window increases in size. At very

small window sizes, all models illustrate significant unfairness. The Power,

Delay, and Hybrid models quickly display increased fairness as the window

increases. Figure 5.16 illustrates the significant difference between the Power,

Delay, and Hybrid capture models and experiment. Both Jain's index and the

Kullback-Leibler index indicate the Message Retraining model is able to provide

an accurate estimate of the fairness properties. Jain's index indicates that


2500

2000

s m 1500

1 O

« 1000 co Q

500

0 0 2 4 6 8 10 12

Time (sec)

Figure 5.15 U D P Experimental Data Trace obtained with Cisco chipset. Connection A commences with an SNR of 20dB 1 second later Connection B commences with an SNR of 25dB

the Message Retraining model matches the trace data within 2% for windows

between 50 and 500 frames, and within 5 % for fairness windows greater than

500 frames. Alternatively, the Kullback-Leibler index matches within 1 % for

windows greater than 50 frames. Conversely, for windows between 100 and 500

frames, the Power, Delay and Hybrid models over estimate fairness with Jain's

index by an average of 30%, and an average of 4 2 % with the Kullback Leibler

index.

With respect to the trace data, over a fairness horizon of less than 500 frames,

the Message Retraining model represents an average improvement over the

Power, Delay and Hybrid models of 2 8 % with Jain's index, and greater than

4 0 % with the Kullback-Leibler index.

TCP

The TCP experiment illustrated in Figure 5.18 also demonstrates how Message

Retraining results in improved accuracy in the fairness properties observed with


i


CD •o

CD

0.85

0.8

0.75

0.7

0.65

0.6

0.55 -

CD

9

0.5

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

^.& .© © or'

Message Retraining + Hybrid * Power » Delay °

No Capture • Trace Data ° 0 100 200 300 400 500 600 700 800 900

Window (frames)

1000

V* 5>X-;

TV \ h *

- r\ k\

1 1 1 1 1 1 1 1 1

Message Retraining Hybrid Power Delay

No Capture Trace Data

" • — • • » - • *

*—---:•*.,;-.;.. ' * • • - . - • • •

V *-•-—»^, \

""" fc —.~ y*-~

^s^-^t. 1 1 1 1 1 1 1 I 1

+

X

u a •

o

~ " -H

100 200 300 400 500 600

Window (frames) 700 800 900 1000

Figure 5.16 Comparison of model fairness performance against experimental U D P

trace data. Top Figure is Jain's index, bottom Figure is Kullback-Leibler index. Both

indices illustrate the ability of the Message Retraining model to provide an improved

match with empirical data with respect to the Power, Delay and Hybrid models


2500

2000

m 1500

1000

500

/

/

/

/

/

/

/ /


6

Time (sec) 10 12

Figure 5.17 T C P Experimental Data Trace obtained with Cisco chipset. Connection B commences with an SNR of 20dB, 1 second later Connection A commences with an SNR of 25dB

the simulation trace. For fairness windows less than 400 frames, the Message

Retraining matches trace data within 4 % on Jain's index, and within 1% on the

Kullback-Leibler index. The Power, Delay, and Hybrid models over estimate

the fairness on the Kullback Leibler index by approximately 6 5 % at 200 frames,

and approximately 4 8 % at 100 frames. Using Jain's index, the Power, Delay,

and Hybrid models overestimate fairness by approximately 2 8 % and 2 5 % at 200

and 100 frame windows respectively.

As with the UDP experiment, with respect to the trace data the Message re

training model proves a minimum improvement of 2 1 % on Jain's index and 4 7 %

on the Kullback-Leibler index over the Power, Delay, and Hybrid models for a

fairness horizon of less than 400 frames.


0.95

0.9 -

0.85

£ 0.8 -

« 0.75 h CD

CD

3 0.7

0.65

0.6

0.55

1 1

" A**

/ y*' y s

// r a/ p •r / y

/ /y •'/ fy

7 * 7 / W // ?// - Ml

T -•**"

" >F ."a"'-

5 r + ,7 •*a •••'*

(Srl-I-F

1

.a'

y

.

^ - U l

I

1 1

^ — i n w r f ^ " " * *"'"'

--»*"* ^ «.-

. - • " * '

i '

1

• • - & —

..+ "'

„,

* • » '

1

i r i "

D -Q "

«- -»

..+ ""

,--°" --•°'~

„--'

Message Retraining Hybrid Power Delay

No Capture Trace Data

i i i

+

X

* D

•

0

...--

y

-

-

_

0 100 200 300 400 500 600 700 800 900 1000 Window (frames)

0.8

0.7

0.6

0.5

S 0.4 -CO

0.3

0.2

0.1

Message Retraining + Hybrid » Power « Delay °

No Capture • Trace Data °

0 100 200 300 400 500 600 700 800 900 100Q Window (frames)

Figure 5.18 Comparison of model fairness performance against experimental TCP

trace data. Top Figure is Jain's index, bottom Figure is Kullback-Leibler index. Both

indices illustrate the ability of the Message Retraining model to provide an improved

match with empirical data with respect to other models for a fairness horizon of less

than 400 frames


5.5.4 Discussion

The experiments described in Section 5.5.3 illustrate that the Delay, Power and

Hybrid capture models provide a significant overestimate of the fairness proper

ties observed in the experimental trace data. However, the Message Retraining

model provides an improved indication of the fairness properties present in the

experimental data over a horizon of less than 400 frames.

Matching the fairness characteristics of an empirical trace represents a chal

lenging task for each capture model. The introduction of a competing hidden

connection has a significant impact on the fairness properties of the empirical

data, which should be reflected in the simulation traces also. As illustrated

qualitatively in Sections 5.4.3 and 5.4.4, this was not the case. W e would there

fore expect the Delay, Power and Hybrid models to significantly overestimate

the fairness achieved for each connection. The results in the previous section

confirm this, with the Delay, Power and Hybrid models all significantly overesti

mating the fairness present in the experimental data. The Message Retraining

model is shown to provide an improved indication of the fairness properties

present in the empirical trace data.

The two fairness indices employed in this experiment exhibit similar behaviour.

However, due to the logarithmic nature of the Kullback-Leibler index, there

is a tendency for this index to be more stable than Jain's index across the

range of windows investigated. Conversely, Jain's index is more variable over

shorter timescales. Both indices demonstrate agreement between the Message

Retraining model and the empirical data for a fairness horizon less than 400

frames. The results presented in this chapter will assist with the selection of a

fairness index, and appropriate fairness horizon in the following chapter.


5.6 Conclusions

Simulation plays an important role in performance evaluation of wireless MAC

protocols. Therefore, accurate simulation models are vital if simulation tech

niques are to provide a reliable indication of the performance of a protocol in

a specific scenario. Previous m o d e m capture models have not been designed

with a specific receiver in mind, and with the development of the IEEE 802.11

M A C / P H Y protocol, this situation needed to be addressed. In particular, rela

tive fairness has not traditionally been considered a significant aspect of capture

model performance. However, assessment of the features a capture model should

exhibit in order to accurately model an IEEE 802.11 receiver indicates that fair

ness should be considered a significant factor. Our results in Chapters 3 and

4 indicate that in cases where fairness is an important component of network

performance, a more detailed capture model is required to reflect the impact

varying signal strength characteristics have on the fairness characteristics ob

served between competing traffic streams.

Building on the empirical and analytic evidence presented in Chapters 3 and 4,

this chapter has proposed a new m o d e m capture model, termed Message Re

training. A detailed qualitative investigation of the performance of a number of

common m o d e m capture models presented in literature, in terms of their abil

ity to accurately reflect fairness properties of empirical trace data, illustrates

that the Message Retraining model is able to model the dynamic fairness prop

erties of the IEEE 802.11 M A C / P H Y protocol under varying signal strength

conditions more accurately than either the Delay, Power, or Hybrid capture

models.

Quantitative comparison between experimental trace data and simulation traces

for each capture model using both Jain's Fairness index and the Kullback-

Leibler fairness index, illustrates than the Delay, Power, and Hybrid capture

models provide an overly optimistic estimate of the fairness afforded to the

contending hidden connections. The Hybrid, Power, and Delay models were


shown to overestimate fairness indices by as much as 3 0 % on Jain's index and

6 5 % on the Kullback-Leibler index in certain cases. The Message Retraining

model is shown to match the experimental data within 4 % on Jain's index, and

1 % on the Kullback-Leibler index for a fairness horizon of less than 400 frames.

In terms of the ability to exhibit fairness characteristics, the Message Retraining

model is shown to provide an improved technique for IEEE 802.11 M A C / P H Y

interface simulation.

Understanding the fairness horizon associated with a MAC protocol is impor

tant in achieving good performance for real time multimedia traffic flows, and

smoothing the flow of T C P acknowledgements. The Message Retraining model

can be employed in situations where varying signal strength is expected to im

pact on system performance. This has specific relevance in cases where nodes

in a given topology are unable to sense carrier from near neighbours. The

Message Retraining model will provide a solid basis on which to develop and

test mechanisms to prevent the unfair behaviour observed in empirical traces.

The Message Retraining model may also have application in the development

of quality of service mechanisms for the IEEE 802.11 wireless M A C protocols.

Chapter 6

Prevention Of Signal Strength Dependent Unfairness

6.1 Introduction

In previous chapters we have investigated the nature of packet capture behaviour

observed with IEEE 802.11 radio modems, and the impact this has on the

ability of the M A C to provide adequate performance for higher layer protocols.

In particular, the results in Chapter 3 have illustrated the distinct unfairness

suffered by weaker connections in hidden terminal topologies. In this chapter

we introduce techniques to restore the fairness characteristics of the network to

a state equivalent to a scenario without hidden nodes. The desired outcome is

a state in which connections are able to gain fair access to the radio channel

independent of relative signal strength. Therefore, in this chapter, we make use

of the analysis and modelling presented in Chapters 4 and 5 to develop and

analyse techniques to correct the unfairness present in near-far signal strength

conditions when hidden terminals are present in an 802.11 network.

Several techniques have been presented in the literature which attempt to cor

rect for protocol based unfair behaviour in disconnected topologies where hid

den nodes are present (Nandagopal et al., 2000; Bensaou et al., 2000; Ozugur

et al., 1998; Ozugur et al., 1999). These are outlined in Section 6.2. None

126

Prevention Of Signal Strength Dependent Unfairness 127

of these schemes take the relative signal power dependent nature of the unfair

behaviour identified in Chapter 3 into account. Therefore, in Section 6.3, we

present a mechanism which uses the average relative signal strength to deter

mine a probability variable. This is then employed in one of three techniques

outlined in Section 6.4 to prevent unfair behaviour as a result of relative signal

strength. In Section 6.5 we undertake an investigation of the performance of

each scheme in a number of distinct topologies and scenarios, with conclusions

and recommendations presented in Section 6.6.

While the primary focus of this thesis has been the MAC and PHY protocols

defined in the IEEE 802.11 standard, the mechanisms presented in this chap

ter are more general in nature, and are equally applicable within any general

contention based M A C protocol.

6.2 Analysis of Topology Dependent Unfairness Prevention Algorithms

Several algorithms have been presented in recent literature which aim to pro

vide fair access to the radio channel in cases where specific topologies result

in poor performance of the C S M A / C A mechanism (Nandagopal et al., 2000;

Bensaou et al., 2000; Ozugur et al., 1998; Ozugur et al., 1999). Each of these

schemes or protocol enhancements aim to meet a different fairness objective

through control of either the channel access persistence or backoff window. The

problem identified in this thesis requires consideration of an additional factor -

the relative signal strength between competing hidden connections.

The backoff window adjustment scheme presented in (Bensaou et al., 2000)

requires each node to estimate the amount of traffic other nodes in the network

are transmitting. It then uses a pre-defined fair share to control the transmission

rate of each individual node. Detailed operation of this scheme is outlined in

Section 2.5.3. T w o significant problems exist with this approach. The first is

that each node is required to estimate the quantity of traffic due to surrounding


nodes. As we have illustrated, a frame transmitted over a weaker connection

will incur a significantly higher loss probability if a stronger signal collides at the

receiver. In this scenario, a node will not be able to gain an accurate measure of

the traffic being carried through the network, leading to an inaccurate estimate

of the network fairness metric. Secondly, each node is pre-programmed with

an identified 'fair share' of network capacity. A share of 0.5 indicates that this

node should obtain 5 0 % of the available bandwidth. The manner in which the

node adjusts the contention window it tied to this fair share parameter. Setting

such a parameter is a complex problem in a dynamic network, particularly a

multihop topology employing a M A N E T routing protocol in which nodes may

be acting as both end stations and routers.

The generalised persistence control approach presented in (Nandagopal et al.,

2000) is derived through a graph theoretic technique. The result is a rate control

mechanism applied by each node in the network. The operation of this scheme

is outlined in Section 2.5.3. This scheme requires a detailed indication of the

topology with which to derive the eventual rate control algorithm. Further,

in a dynamic network topology, convergence of node transmission rates will be

an issue. One advantage of the approach is the ability to define any fairness

model in terms of a utility function which then determines the appropriate

rate control algorithm. However, this algorithm is based on the assumption of

perfect knowledge of the contention state in the network. Contention is used as

implicit feedback to control the transmission rate of each node. Disparity exists

in a case when two hidden terminals compete at different signal levels. The

stronger node observes no significant contention or loss, while the weaker node

observes significant contention, loss and delay. In a manner similar to T C P

congestion control, the rate control algorithm will reduce the transmission rate

for the weaker node in response to the observed congestion, while the stronger

node will increase the transmission rate as no congestion is observed. This will

lead to an imbalance in the fairness properties observed in the network with

both nodes assuming fairness is being achieved.


Similar problems also exist with the contention approach presented in (Ozugur

et al., 1998; Ozugur et al., 1999) where each node calculates a link access prob

ability based on the surrounding topology. This probability is used to control

the rate at which a node is able to transmit. In cases where two hidden nodes

have individually defined access probabilities, there is a potential for significant

disparity to occur. The weaker of the hidden nodes will be restricted in the

number of packets it is able to transmit by the given link access probability.

As packets from the weaker nodes suffer a greater loss probability, the node is

forced to retransmit lost packets yet receives no additional link access to account

for the lost frames. The stronger node suffers no restriction and the majority

of packets are successfully received by the common node.

Each of these schemes aim to solve topology and protocol dependent unfairness

problems. However, as the examples discussed above illustrate, additional con

sideration of the relative signal strength amoung nodes will be required. In the

following section we introduce a technique to determine a probability variable

proportional to the relative signal strength of a given connection. Algorithms to

correct for signal strength dependent unfairness are introduced in Section 6.4.

6.3 Average Signal Strength Based Probability

The aim of this chapter is to develop mechanisms to control unfair behaviour

resulting from signal power differences in the presence of hidden terminals. Sec

tion 6.4 below outlines three proposed mechanisms. In this section we outline

a mechanism which maintains a probability variable based on the average re

ceived signal strength for each neighbour. The probability determined with this

mechanism is then employed by each of the fairness control techniques outlined

in the following section.

The proposed mechanism to determine the relevant probability variable is based

on an average signal strength metric for each node. As each connection will


have a dynamic signal strength due to fading, shadowing, and mobility, signal

strength averages should be filtered through a standard 1st order delay filter of

the form:

Pi = a- Pi(n) + (1 - a) • P^n - 1) (6.1)

where a, often termed the 'forgetting factor', is typically within the range 0.5

to 0.9, and n is the sample number index. Each node records a historic average

signal strength for each neighbour using Equation (6.1). The average signal

power relative to the all other neighbours is determined for each logical con

nection. Using the algorithm outlined in Equation (6.2) below, a probability

variable for each of the N total neighbours is maintained:

5i = max(Pi(m) - Pj(m), me[l,N], ie V)dB (6.2)

where V is the set of neighbours who have hidden nodes within range of the

node performing this calculation, m is an index variable, and the max function

selects the largest value in the set. The relative power is then used to calculate

a probability value, pi for each neighbour i € V according to:

, 1 , Si<y Pi={ (6.3)

U(Si), otherwise

where 7 is the observed unfairness threshold, and may be tuned to a specific

P H Y . U(8i) represents a utility function, continuous over the range [0,1]. In

Chapter 4 we illustrated that a relative difference of greater than 2dB will

result in the corruption of the weaker signal. Therefore, a threshold of 7 = ZdB

is selected. A utility function is employed which reduces the probability in

proportion to 7:

U(6i) = 1 - ^ (6.4) 7

where # is the control parameter. This algorithm is maintained by each re

ceiver in the network for all identified neighbours. Neighbours are identified by

the Source Address (SA) field of observed RTS, D A T A and other M M P D U ' s ,


and maintained in a cache of MAC addresses. The probability variable for the

ith neighbour, pt, is updated on reception of each valid frame. Once a neigh

bour is identified as having a hidden neighbour (Section 6.3.1), the current

probability for that neighbour is employed with one of the schemes outlined in

Sections 6.4.1, 6.4.2, and 6.4.3.

To prevent excessive restriction of a stronger node in cases where the traffic from

a weaker node is bursty, or a weaker node has little impending traffic, a lifetime

parameter Tj is associated with the average signal strength measurements, Pi.

Reception of a new frame from the ith node resets the lifetime of the average

signal strength variable Pj. O n expiration of the lifetime for Pi, the value is

set to zero, and the neighbour is removed from the set of identified neighbours,

V. Once the neighbour has been removed from V the relative probabilities will

readjust for all other neighbours within V accordingly.

Further, the control parameter j3 must be chosen to control the aggressiveness

of the correction mechanism. A higher /3 value will result in a more aggressive

control scheme. The selection of an appropriate /? for each scheme in various

scenarios is discussed in Section 6.5.

6.3.1 Identification of Hidden Nodes

Identification of hidden nodes is a key issue for the performance of any tech

nique designed to control unfair behaviour as a result of hidden terminals in

a practical implementation. The mechanism to identify potential hidden node

pairs should operate within the 802.11 framework. This can then be employed

to instigate the fairness control algorithms under development. Within the

context of a C S M A / C A M A C , a potential mechanism to identify hidden nodes

exists through observation of message exchange semantics within either the

R T S / C T S / D A T A / A C K or D A T A / A C K handshake. The reader is referred to

Appendix A for details of the proposed mechanism based on message exchange

semantics.


The aim of this chapter is to investigate the performance of the fairness con

trol schemes outlined in Section 6.4, rather than the performance of a hidden

node detection algorithm. Therefore the initial performance investigation is

Section 6.5 will assume that all hidden nodes are identified to the common

node. This assumption allows investigation of the fairness control mechanism

in isolation, free from potential interactions with the hidden node detection

mechanism.

6.4 Algorithms to Control Signal Strength Dependent Unfairness in Hidden Node Scenarios

The analysis in Chapter 4 illustrates that a relative signal power between two

interfering signals of greater than 2dB is sufficient to result in the unfairness as

measured experimentally. In this chapter, we focus on mechanisms to correct

unfairness due to relative signal strength variation in general hidden terminal

scenarios.

The effect we are attempting to correct for exhibits threshold behaviour. Once

the relative signal strength is greater than a given value, unfairness becomes evi

dent. Once the average relative signal strength is below the threshold identified,

we have observed in Chapter 3 that reasonable fairness results. Accordingly we

can restrict ourselves to a mechanism aiming to correct signal strength imbal

ances above the threshold to a point where the fairness performance matches

that observed with a relative signal strength below the threshold on each con

nection.

A significant issue is the positioning of a scheme designed to prevent unfair be

haviour due to relative signal power within the layered protocol structure. The

capture effect responsible for the unfair behaviour is an intrinsic feature of both

the P H Y and the receiver. To this extent, it m a y seem appropriate to improve

the P H Y to increase the robustness in the presence of multiple access interfer-


ence. However, given the number of P H Y protocols currently defined within

the IEEE 802.11 framework, a significant number of different solutions would

be required. A more generic solution would provide significant advantages, al

lowing the introduction of new P H Y protocols requiring tuning of the generic

solution rather than the development of a new control mechanism. Therefore,

the mechanisms proposed in this chapter are designed to reside between the

P H Y and M A C layer. This allows the mechanism to use information obtained

from the P H Y to correct the contention state observed by the M A C .

Closed loop power control also represents a potential mechanism to prevent

an unfair state due to relative received signal power differences arising in the

network. In this case, very fine control within a few dB would be required. In a

dynamic, general topology M A N E T , this is a non-trivial problem. Controlling

the transmission power of a competing hidden node will potentially result in

significant 'knock-on' effects through the network. For example, increasing or

decreasing transmission power will have a significant impact on the routing

protocol and the reliability of links throughout the network.

Another important issue requiring investigation is whether the scheme should be

receiver or sender based. A receiver based scheme will require the transmission

of information to each sender at appropriate intervals, however, if this can be

incorporated within existing M A C frame exchanges (in a field within an A C K

or another M M P D U frame for example) the impact on channel efficiency will

be negligible. Also, mechanisms such as the probabilistic discard or enhanced

C T S suppression (outlined in Section 6.4.3) are only possible in a receiver based

context. A sender based scheme in which an S T A was able to identify when

it is causing problems for another S T A in the network follows the paradigm

presented in (Bensaou et al., 2000; Nandagopal et al., 2000). However, we are

attempting to solve a problem that exists at a receiver where a transmitter

has no prior knowledge of the signal strength the receiver observes, nor any

knowledge of the relative strength of other hidden transmissions a receiver may

be able to observe. This requires information from the receiver before any


action can be taken to correct an unfair state. This separation implies that a

transmitter based scheme will be unable to take signal strength information into

account. In this context, a transmitter based scheme which includes received

signal strength as a parameter is not possible without significant dissemination

of information throughout the network. Therefore, we will focus on schemes in

which the receiver undertakes the majority of the required processing and is able

to minimise additional transmission, or where possible, incorporate information

transfer within the current 802.11 M A C frame exchange sequences and formats.

The fairness goal we aim to achieve through a control scheme of this type is

not one based on differentiation between nodes or traffic classes. As we are

correcting for an inherent bias in the system towards stronger connections, we

can only aim to remove this bias, and return the network to a state where each

connection achieves equal opportunity to access the channel over a specified

time. This also corresponds to maximising the fairness index. This implicit

fairness goal is the only goal we can attempt to achieve in a best effort network

where no differentiation between services is provided. In cases where service

differentiation were applied, a mechanism to correct for the signal strength

dependent unfair behaviour would provide a fair basis on which to apply service

differentiation.

Finally, complexity is a significant issue in terms of future adoption within the

802.11 standard. A preferred scheme will not introduce significant additional

complexity in terms of random number generation, or signal strength sampling

for example. However, while reduction of undue complexity should be a con

sideration, complexity itself should not be an overriding factor in determining

the suitability of a particular scheme.

From the above discussion, we are able to identify features a suitable fairness

control scheme should exhibit:

• the scheme should be as simple as possible

• the scheme should be able to be integrated into the existing standard


with minimal effort, or alternatively operate within the constraints of the

(future) standard in terms of available messaging syntax

• the scheme should take the results presented in Chapter 4 into account

when considering signal thresholds

• the scheme should be dynamic, adjusting to changes in signal strength,

and the introduction and departure of STA's from the network

In the light of the above feature requirements, we propose three potential options

to correct for signal strength dependent unfairness:

p-Persistence at Backoff Countdown: Each STA retains the nor

mal backoff process. O n detection of a clear channel, the node will defer

again with probability 1 — p determined in accordance with the relative

signal strength at a common receiver. This method is outlined in Sec

tion 6.4.1.

Probabilistic Discard: A receiver probabilistically discards data frames

from stronger STA's, forcing the offender to backoff and retransmit. This

method is outlined in Section 6.4.2.

Enhanced CTS Suppression: A receiver is able to direct a C T S mes

sage to a given STA, forcing suppression for the indicated interval. This

method is outlined in Section 6.4.3.

For each of the proposed mechanisms, distinction must be made between traffic

destined for an S T A that has no hidden terminals, and traffic that will compete

over a hidden connection for a common receiver. In random network topologies,

STA's may have traffic destined for multiple local STA's which raises the issue

of whether each of the above schemes should be applied on a per STA basis

or on a per traffic stream basis. The correction techniques listed below adjust

different parameters in an offending STA, which may or may not be capable

of distinguishing traffic streams. This will be discussed in greater detail in the

following sections.


6.4.1 Probabilistic Access at Backoff Countdown

This technique builds on the basic mechanism presented by Ozugur (Ozugur

et al., 1998; Ozugur et al., 1999). The idea is to apply a channel access proba

bility (or persistence) whilst retaining the standard backoff mechanism. W h e n

an S T A senses an idle channel, the transmission proceeds with probability p, or

defers with probability 1 — p. The normal backoff mechanism is retained.

Once a pair of hidden STA's have been identified through mechanisms outlined

in Appendix A, the algorithm outlined in Section 6.3 is employed to determine a

probability value in proportion to the relative received signal power between the

competing hidden STA's. O n reception of a valid D A T A frame, the common

STA includes the probability value in an 'enhanced' A C K reply (or possibly

another M M P D U ) . The station receiving the A C K then records the persistence

value and interprets this as a channel access probability when attempting to

transmit to the host sending the A C K .

The introduction of an additional field into an ACK frame will result in a

lack of compatibility with original versions of the 802.11 standard, and as such

represents a potential drawback for this approach. However, STA's supporting

the probabilistic access method will consider the A C K a valid frame and given

that the A C K is a directed frame (i.e. not a broadcast or multicast frame), such

an S T A will receive this frame. This mechanism relies on the inclusion of a single

additional field in an A C K frame which represents a very small overhead. It

may also become possible to distribute the persistence variable within another

M M P D U , as the current 802.11e W G (TGe, 2001) will introduce several new

M M P D U frames into the standard.

This scheme can be applied on a per-flow or per-node basis, as the probability

variable is only employed when attempting to transmit to the common STA.

Traffic not destined for this STA need not use this access control probability.

The detailed performance of this approach is investigated in Section 6.5 below.


6.4.2 Probabilistic Discard

In the probabilistic discard approach, the receiving STA interprets the prob

ability calculation of (6.2) as a drop probability for incoming D A T A or RTS

frames from identified stronger hidden STA's.

The common STA having identified a stronger hidden STA, will drop received

D A T A or R T S frames with probability 1 — p and deliberately fail to respond

with an A C K or C T S frame as would normally be required. This forces the

transmitting S T A to backoff more often than would otherwise be the case. This

approach makes use of the native backoff and timeout mechanisms within the

M A C protocol, and does not require information to be sent to the offending

STA's. Feedback is in the form of an apparently higher loss probability which

the offending S T A will (correctly) assume is due to congestion. This allows

the weaker S T A an opportunity to transmit. In the uncorrected situation, the

stronger S T A receives an incorrect indication of the actual congestion state of

the network, as it's transmissions are preferentially received. The probabilistic

dropping of frames from a stronger hidden STA corrects this by introducing

additional congestion specific to this connection.

This is a simple scheme which places very little additional requirement on each

STA, and is controlled by a single parameter. Information is implicitly dis

seminated through the network in the form of 'forced congestion' an offending

STA would otherwise not observe. No messaging is required, and each STA can

choose when to apply the scheme individually. This scheme could be applied to

all D A T A and R T S frames from an offending STA. The detailed performance

of this scheme is investigated in Section 6.5.

6.4.3 Enhanced CTS Suppression

This approach makes use of an enhancement to the interpretation of RTS and

C T S control messages proposed in (Sherman, 2001). W e propose the applica

tion of the Enhanced R T S (ERTS) and Enhanced C T S (ECTS) messages in


suppressing a stronger STA through the virtual carrier sense mechanism out

lined in Section 2.3.1.1. The common STA uses the probability variable to

determine when to force a suppression period upon a stronger hidden STA.

The enhanced RTS/CTS frame rules currently before the IEEE 802.11 WG

(Sherman, 2001) allow an STA to intentionally suppress an STA, or group of

STA's, identified by a special range of group or multicast addresses. In the

current context, an STA will maintain a list of group or multicast addresses,

and use these to identify hidden STA's. O n receipt of an RTS or E R T S from

an offending hidden STA, the common STA has the ability to set the duration

field in an E C T S reply to a value which provides a weaker STA an opportunity

to attempt a transmission. O n receipt of the E C T S (addressed to the offending

STA via a specified multicast address) the STA will then update the N A V to

the value returned via the ECTS. The stronger STA requires suppression for a

period of at least several hundred microseconds, which allows a competing hid

den STA to perform a successful RTS/CTS exchange. This will extend the N A V

of the stronger STA through the normal RTS/CTS N A V update mechanism,

and allow the weaker STA an opportunity to transmit. This mechanism is only

applicable on a per-STA basis, as it makes use of the NAV, which will return

a busy indication regardless of the destination address of any impending data

frame. Figure 6.1 illustrates this mechanism in a scenario where the stronger

STA group (Nodes C and D) is suppressed for a period allowing the weaker

STA (Node A) to transmit several data frames.

This alternative is attractive from the point of view that the technique may

easily be implemented using the ERTS/ECTS mechanism within an 802.lie

network. This is inter-operable with legacy stations, which are not affected

by the E C T S mechanism. While there are still many issues to be addressed

within the IEEE 802.11 W G , in particular the allocation of group and multi

cast addresses, given that the E R T S / E C T S mechanism allows the potential for

a directed R T S or C T S message, there is a potential application for this mech

anism with the probability determination algorithm as a method of controlling


Node A Sends RTS, Receives ECTS Node A Commences DATA Tx

0 Node A RTS ECTS

0 NodeB RTS ECTS

DATA DATA ACK

Multiple Frame Exchanges Possible While Nodes C and D Suppressed

DATA DATA ACK

Node B receives RTS, Responds with ECTS

0 0 ECTS

Node D Node C Nodes C & D identified through Group Address as hidden from A

Node C and Node D Detect Group Addressed ECTS Defer For Duration specified in ECTS Allows Node A additional access to channel

Figure 6.1 Diagramatic representation of ECTS Suppression Scheme. Nodes C and

D are identified through group address as hidden from Node A. Node B determines

when an Enhanced CTS reply is required to suppress Nodes C and D, allowing Node

A fair channel access. The duration set within the ECTS can be tuned to meet the

specific fairness objective.


signal strength dependent unfairness.

6.5 Performance Investigation and Comparison

Sections 6.4.1, 6.4.2, and 6.4.3 have described three proposed mechanisms to

correct for relative signal strength dependent unfairness when hidden terminals

are present in a general topology network. In this section, we undertake a

detailed performance analysis and comparison of each scheme. Our aim is to

determine the optimal performance range for each scheme, and identify scenarios

in which each scheme may be more appropriate. This will be achieved through

a number of performance and comparison criteria.

6.5.1 Simulation Methodology

The simulation techniques employed are identical to those of the previous chap

ter, though we present a brief review here. Each technique has been imple

mented within the ns-2 simulation package (version 2.1b3) (UCB/LBNL/VINT,

1999), incorporating the Message Retraining capture model developed in the

previous chapter, ns contains a detailed 802.11 P H Y / M A C layer model, as well

as providing excellent implementations of higher layer protocols such TCP/IP,

U D P , F T P etc. The channel model employed is an Additive White Gaussian

Noise ( A W G N ) Two-Ray Ground model. Capture decisions are made within

each m o d e m based on the received signal power, channel noise power, and cap

ture threshold. Each node receives a copy of the transmitted packet and based

on the received power, determines whether the signal is observable. If the signal

is received with sufficient power, the message retraining capture model deter

mines the appropriate course of action prior to passing the completed frame

up to the M A C protocol. In order to examine the performance of the fairness

control mechanisms in isolation, it is also assumed that each hidden node has

been identified to the common node.


6.5.2 Comparison Criteria

In the previous chapter we employed two fairness metrics to compare the per

formance of the capture models under investigation. Chapter 5 illustrated how

both the Kullback-Leibler and Jain's index show good agreement between ex

perimental trace data and simulation using the Message Retraining model for

fairness horizon's less than 400 frames. In this chapter, we employ Jain's fair

ness index over a fairness horizon of 100 frames as the main aim of each scheme

is to improve the relative fairness over short timescales.

The basis on which we compare the performance of the three mechanisms will

include the following:

• Qualitative improvement in trace characteristics, (plots a and c)

• Qualitative improvement in channel access times (plots b and d)

• Per connection and aggregate normalised throughput (plots f and h)

• Instantaneous and average fairness index throughout the experiment (plots

e and g)

Results are presented as a combination of 8 individual graphs presented for

each scenario. Figures 6.3, 6.4, 6.5, 6.7, 6.8, and 6.9 combine the 8 individual

graphs outlined below. Each graph highlights a specific aspect of the behaviour

of the fairness control mechanism. The 8 graphs presented, and the relevant

information each presents is as follows:

Plot a Presents Received Data vs time with no fairness control (/3 = 0).

This illustrates the relative fairness between contending connections at

the network layer. The relative slope of the graph indicates the differing

channel access obtained by the competing nodes in the network.

Plot b Presents Relative channel access times for each node without fair

ness control (/3 = 0). Again, this illustrates the relative access between


contending nodes.

Plot c Presents Received Data vs time with the optimal ft value, deter

mined in plots (g) and (h). This illustrates improvement in relative per

formance observed at the network layer with each mechanism operating

at the optimal point.

Plot d Presents Relative channel access times for each node with pre

ferred /3 value, illustrating the effect the fairness control algorithm has on

the ability of each connection to access the channel.

Plot e Presents Jain's fairness index over the length of the preferred

f3 trace, illustrating how the fairness properties varies throughout the

experiment. The average value over the entire experiment is included. A

value over 0.95 is considered to represent excellent fair behaviour.

Plot f Presents Normalised throughput for each connection over the length

of the preferred fi trace, averaged over 2 second intervals. This indi

cates the ability of each fairness control algorithm to prevent a stronger

connection from gaining appreciably greater channel access than weaker

connections.

Plot g Presents Jain's fairness index over the range of /3 values exam

ined. This illustrates the preferred /3 value as the peak in this curve.

Again, the fairness horizon is 100 frames.

Plot h Presents Normalised average throughput for each connection over

the range of /3 values examined. A preferred j3 value can be observed with

this trace as the point at which each connection achieves equal average

throughput. This corresponds to a long term fair allocation of bandwidth.

The combination of these criteria allow both a qualitative and quantitative com

parison between the fairness control mechanisms. As outlined in previously, the

reasons for implementing a particular scheme are based on additional factors

including implementation and standards inter-operability issues. The primary


aims of this investigation are to establish the performance of each scheme on

both a qualitative and quantitative basis, as well as a range of appropriate /3

values for each mechanism. The preferred /3 values for each mechanism are de

termined as the range of j3 combining the highest fairness measured with Jain's

index, with the range over which the average throughput for each connection

does not illustrate the distinct unfairness evident without fairness control. This

may have future application in an adaptive mechanism to control ft.

Using the criteria presented in this section, each of the schemes will be com

pared, and the range of /3 values for optimum performance identified.

6.5.3 Simple Case - Static Hidden Nodes

Initially, we investigate the performance of each mechanism in a simple case

where two hidden nodes compete for a common receiver using both U D P and

T C P traffic streams. Results for the three node topology using U D P traffic

streams, illustrated in Figure 6.2 are included in this chapter, while the results

obtained with T C P are included in Appendix B . U D P is used exclusively here

as it removes potential interactions between M A C and higher layer protocol

timers, illustrated in Chapters 2 and 3 to have an additional effect on network

layer fairness. This allows examination of the ability of each mechanism to

remove bias due to relative signal strength.

In this static scenario, distance from the central node is fixed and equal for

both nodes. The stronger Connection A has a transmit power adjusted to

achieve a received signal power of -87 d B m , corresponding to an average S N R

of approximately 27dB. The transmit power of the weaker Connection B is

adjusted to achieve a received average signal power of-90dBm, corresponding to

an average S N R of approximately 24dB. Transmit power and distance from the

central node remain constant throughout the experiment. Dynamic scenarios

are considered in later sections. This scenario, whilst potentially representing a

limited physical scenario, is investigated primarily as a means of verifying the

ability of each mechanism to effectively control unfair behaviour.


Connection A y^ >v Connection B

,0 (r®0 j © >-- \ y •*

'^•Hidden Nodes •' '

Figure 6.2 Three Node Hidden Terminal Topology

The results for each algorithm with the 3 node topology are presented in Fig

ures 6.3 through 6.5.


p-Persistence on Backoff C o u n t d o w n

Figures 6.3(a) and (b) clearly illustrate the advantage Connection A obtains over

Connection B without a fairness control mechanism. Employing a value of f3 =

0.25, Figures 6.3(c) and (d) illustrate the ability of the p-Persistence mechanism

to provide increased access opportunities for Connection B at the expense of

Connection A. Figures 6.3(e) and (f) illustrate the variation of Jain's index and

the per connection throughput throughout the experiment respectively. In this

case, the fairness index is increased from 0.52 with 0 = 0 to 0.83 with {3 = 0.25.

Figures 6.3(g) and (h) indicate that the preferred (3 value lies between 0.25 and

0.35, corresponding to the range over which Jain's fairness index is maximised

and the throughput on each connection is equal.

Probabilistic Discard

Figures 6.4(a) and (b) again illustrate the advantage Connection A obtains

over Connection B without a control mechanism. Figures 6.4(c) and (d) il

lustrate the ability of this mechanism to increase channel access opportunities

for Connection B at the expense of Connection A. However, compared to the

p-Persistence scheme, this mechanism appears to enact a much more course

grained level of control in this scenario, evidenced through the variability in the

progress of the data traces in Figure 6.4(c). Figures 6.4(g) and (h) indicate that

the preferred 0 value lies in the region of 0.40, with j3 = 0.40 the point where

throughput is equal on each connection. Using this value, Figures 6.4(e) and (f)

again illustrate the variation of Jain's index and the per connection throughput

throughout the experiment respectively. The fairness index is increased from

0.52 with 0 = 0 to 0.72 with fi = 0.40.

Enhanced CTS Suppression

Using the ECTS scheme, Figures 6.5(c) and (d) clearly illustrate how this mech

anism provides very fair channel access for both nodes employing a value of

ft = 0.75. Figures 6.5(e) and (f) illustrate the variation of Jain's index and the

per connection throughput throughout the experiment respectively, both ex-


(a) Data Trace - Evolution p = 0 (b) Data Trace - Access Times p = 0

2000

_ 1800

& 1600

m 1400

« 1200

g 1000

S 800

| 600

o 400

200

0

1000


2 4 6 8 10 12 14 16 18 20

Time (sec)

(c) Data Trace - Evolution p = 0.25

3 CO Q TJ (1)

>

8 at

tr

900 •

800

700

600

500

400

300

200

100 r


2 4 6 8 10 12 14 16 18 20

Time (sec)

(g) Jain's Fairness Index vs p

Connection A Connection B «

0 2 4 6 8 10 12 14 16 18 20

Time (sec)

(d) Data Trace - Access Times p = 0.25

1 •

X o c CO CO 0)

c

s LL

0

1.1 1

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2

0.1 0

-

•

2 4 6 8 10 12 14 16

Time (sec)

(e) Jain's Fairness Index

'W flfLrlij.t! W* 't^W $&• ' V

'^-~i

Jain's, Index: Average 0.83

18

•

»\

•

20

•

•

Q.

I-•a

<o tn

E o Z

0

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

a E o z

0.6 0.55 0.5 0.45 0.4

0.35 0.3 0.25 0.2 0.15 0.1 0.05

0

Connection A Connection B *

' •

2 4 6 8 10 12 14 16 18 20

Time (sec)

(f) Normalised Throughput p = 0.25

0 2 4 6 8 10 12 14 16 18 20

Time (sec)

(h) Normalised Throughput vs p


0.1 0.2 0.3 0.4 0.5 0.6

Figure 6.3 Three node topology, static scenario for p-Persistence on Backoff Count

down algorithm using U D P - /? = 0.25


CO

s m 3 ra Q •a

s CD

DC

2000

1800

1600

1400

1200

1000

800

600

400

200


1200

<g 1000

m

CO CO Q T3

>

"8 V

800

600 •

400 •

200

CD

E co U-


CD TJ

c CO

"c 'ra ~3 0) O)

s

I

1.1

1

0.9

0.8

0.7

0.6 r

0.5

4 6 8 10 12 14 16 18 20

Time (sec)

(c) Data Trace • Evolution p = 0.40


t/y./

-

/

y /'" /

y

i

1 1 -)

,/ ~~~

6 8 10 12 14 16 18 20

Time (sec)


2 4 6 8 10 12 14 16 18 20

Time (sec)


100 Frame Window

•

* • + / \

/ \ / \ * \ •'

..+ ••+

'- ....-i- \

0.1 0.2 0.3 0.4 0.5 0.6

0) n

•Z 2

73 O

z

0.6

0.5

0.4

0.3

0.2

0.1


0 2 4 6 8 10 12 14 16 18 20

Time (sec)



0 2 4 6 8 10 12 14 16 18 20

Time (sec)



4 6 8 10 12 14 16 18

Time (sec)


0.6

3

n r: C7> 3 O sz r-

CI) O)

ni F o Z

05

0.4

0.3

0.2

0.1

0


0.1 0.6

Figure 6.4 Three node topology, static scenario for Probabilistic Discard algorithm

using U D P - 0 = 0.40


hibiting significantly less variability when compared with the previous schemes.

Figure 6.5(g) indicates a clear peak in the fairness index for 0 between 0.7 and

0.9. However, the aggregate channel throughput in Figure 6.5(h) is significantly

lower at the preferred 0 = 0.75, being reduced from 0.58 with 0 = 0 to an ag

gregate of 0.24. This represents a significant drawback for this technique. The

fairness index however is significantly improved over the previous two schemes,

from 0.52 with 0 = 0 to 0.93 with 0 = 0.75.

6.5.4 Static Scenario Discussion

In all three cases, the fairness control schemes are able to provide improved

throughput for the weaker connections by preventing the stronger connection

from gaining unfair channel access. Examining the performance as a function

of 0 indicates there is a well defined peak in each case, corresponding to the

maximum in Jain's index, as well as the point where throughput is equal on each

connection. In each case, the optimal point with respect to the fairness index

corresponds to a point where aggregate throughput performance is quite low.

This is common across each scheme, with the Enhanced C T S scheme resulting in

the highest aggregate throughput reduction of 56%. The Probabilistic Discard

scheme suffers an aggregate throughput reduction of 6%, while the p-Persistence

of Backoff Countdown scheme results in an aggregate throughput reduction of

only 2%.

The reduced throughput obtained with the Enhanced CTS scheme represents a

significant disadvantage for this approach in comparison with the p-Persistence

and Probabilistic Discard schemes. Aggregate throughput is expected to be

reduced in this manner as a result of increased contention introduced by the

fairness control scheme. In multiple access systems, a single user is able to

achieve greater throughput than the sum of a number of users, due to the

increased contention for the channel as the number of users increases. In the

trials without fairness control, the stronger user is effectively a single user as

the contention information they infer from the network indicates there are no



CO CD

m

8 CO

Q •a

s

CO CD

8 to Q •a

> CD CJ CD

DC

4000

3500

3000

2500

2000

1500

1000

500

0

1000

900

800

700

600

500

400

300

200

100

0


5 10 15 20 25 30

Time (sec)



,y

.y

.*£ /-,*>*•'

10 15 20 25 30

Time (sec)


0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

T3 O

z

T3 O

z

X CD TJ C CO

CD

c S U-

s •o

c CO

c CO —i CD CD

3

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 (

1.1

1

0.9

0.8

0.7

0.6

0.5

w i t$ n mwv .n/fw W A A /"!<. rr> m

•

Jajn's Index: Average 0.93 i *

) 5 10 15 20 25

Time (sec)


100 Frame Window

••-•-*

1 — - — t i • i • i i i i i

\T\i

-

3

* .

•

3

a a o 1-T3 CD W

"co E o z

0

3

a. CD 3 O J=

H T3 CD CO E o z

0.4

0.3

0.2

0.1

0.6

0.5

0.4

0.3

0.2

0.1


5 10 15 20 25

Time (sec)




10 15 20

Time (sec)



30

10 15 20 25 30

Time (sec)


0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

P

Figure 6.5 Three node topology, static scenario for enhanced CTS Suppression algorithm using U D P - 0 = 0.75


other users contending for the channel. The weaker node in this case suffers

significant contention. In the case where control is employed, the stronger user

is forced to contend for the channel which has the effect of reducing overall

system throughput. A n obvious tradeoff exists between fairness and system

throughput and must be considered when formulating fairness goals for the

network.

For TCP results in this scenario, the reader is referred to Appendix B. These

results exhibit lower throughput than the U D P results. This is due to the ineffi

ciency of the combined 802.11 M A C employing RTS/CTS with T C P Reno. The

static case investigated here may be representative of certain W L A N scenarios,

though is not a realistic scenario for a more general W L A N or M A N E T . Nodes

are able to move, and the propagation environment may change in a manner

not accounted for in our propagation model. Therefore, in the following section

we continue this investigation in a scenario where nodes move throughout the

experiment. This examines the dynamic behaviour of the algorithms, as well as

their ability to operate is scenarios where both hidden and in-range nodes are

present.

6.5.5 General Dynamic Case - Hidden and In-Range Nodes

In the scenario employed for this series of experiments the nodes move in to

wards the common node 15 seconds into the experiment. Through until 20

seconds, both nodes are no longer hidden from each other. At 20 seconds, both

nodes move back to become hidden again, though this time Connection B is

the stronger of the two. This scenario combines hidden nodes, in-range nodes,

as well as introducing variability into the received average signal strength as a

result of node mobility. In this case, nodes are physically moved at 10 m/sec

rather than having their signal power adjusted.

An example signal trace is shown in Figure 6.6. This illustrates the received

S N R of each connection throughout the experiment. Connection B commences


Figure 6.6 Example received SNR trace during dynamic experiment

as the weaker connection, evidenced by the weaker signal of approx 22dB op

posed to 27dB for connection A between 5 and 15 seconds on the S N R trace.

15 seconds into the experiment, both nodes move towards a point equidistant

from the common node. 20 seconds into the experiment, the nodes move back

outwards to the original (hidden) positions. The distance of each node from

the common node is swapped. Connection B then maintains a stronger average

signal strength of approximately 27dB as opposed to the 22dB average obtained

by Connection A.

In this scenario, using the equal throughput criteria to identify a preferred 0 is

not possible, as the dominating host changes throughout the experiment. This

results in relatively equal throughput for each connection throughout the exper

iment, as both hosts spend an equal time dominating the channel. Accordingly,

per connection throughput as a function of 0 does not vary as widely as in the

static scenario.

p-Persistence on Backoff Countdown

Figures 6.7(a) and (b) illustrate the traces without fairness control. In this



, ^ CD

m

ra CO

Q

>

8 cu DC

2000

1800

1600

1400

1200

1000

800

600 400

200

2000

_ 1800

8 1600

m 1400

« 1200

§ 1000

E 80° I 600 8 400 DC

200 0

X CD T3

1.1

1 (• 0.9 0.8 r 0.7 0.6

8 0.5

CO IX.

0.4 0.3 0.2 0.1 0

1.1

cu

- 0.9

CD

if 0.7

I 0.6 0.5

Connection A • Connection B *

5 10 15 20

Time (sec)



10 15 20

Time (sec)


i / R ^ . f fc IVf"*"""^! .fMU/liW

5 10 15 20

Time (sec)


.

•

•

\

/

/

100 Frame Window •

•

\ \

0.1 0.2 0.3 0.4 0.5 0.6

TJ O

z

0.5

o. 0.4 £: O)

1 0.3

| 0.2 co E o 0.1

0.6

3 n £ rn 3

o sz. •n CD CO a f-o

0 5

U.4

0.3

0.2

0.1


5 10 15 20 25

Time (sec)



10 15 20 25

Time (sec)


i 10 15 20

Time (sec)



0.1 0.2 0.3

P 0.4

30

30

0.5 0.6

Figure 6.7 Three node topology, dynamic scenario for p-Persistence on Backoff

Countdown algorithm using U D P 0 = 0.25


scenario, periods where either connection is able to dominate the radio resource

correspond to the period where that connection was the stronger of the two.

Between approximately 15 and 20 seconds, the resource is effectively shared as

both hosts move in towards the common node. Once the nodes are in range of

each other, reliable carrier sense information prevents either host from domi

nating the radio resource.

Employing a value of 0 = 0.25, Figures 6.7(c) and (d) illustrate the ability of

this mechanism to increase the access opportunities of the weaker connection,

and react to the changes in relative signal strength. The slope of both traces

in Figure 6.7(c) remains constant throughout the experiment, indicating the

ability of this mechanism to control unfair behaviour the network environment

changes. As each connection spends an equal time dominating the channel in

this scenario, determination of a preferred 0 from Figures 6.7(g) and (h) is

not as clear as in the static case. Figure 6.7(g) indicates that a peak in the

fairness index was present at in the region of 0 = 0.25, where the fairness index

has increased by 31%, and the aggregate average throughput suffers a 1 3 %

reduction.

Probabilistic Discard

In this case, it is again evident that the mechanism is able to control the stronger

connection. In this dynamic scenario the performance has improved over the

static scenario. The period during which the nodes are within range is obvious

in Figures 6.8(a), (c) and (e) between 15 and 20 seconds. Through this period,

the network is inherently fair as each node has reliable carrier sense information,

and the mechanism does not appear to adversely effect either trace throughout

this period. Figure 6.8(g) indicates the a preferred 0 lies between 0.3 and 0.4.

Using a value of 0 = 0.35, the fairness index is increased to 0.89, an increase of

37%. Figures 6.8(c), (e), and (f) illustrate the coarseness evident in the static

trial is not present in this dynamic scenario. However, throughput is reduced

by 3 9 % with 0 = 0.35


(a) Data Trace - Evolution p = 0 2000

_ 1800

|! 1600

g 1400

« 1200 g 1000 •a

s

(b) Data Trace - Access Times p = 0

CD

DC

800

600

400 •

200

0

1600

9 1400 CD

•S. 1200 co * 1000 8 CO Q T3

I 8 400 CD c 200

800

600

CD T3

CO CO CD

E co LL

1.1 1

0.9 0.8 0.7 0.6 0.5 0.4 0.3 r 0.2 0.1 0

1.1

x 1 CD

^ 0.9

CD

2 0.7

< 0.6

0.5


25 5 10 15 20

Time (sec)


30


10 15 20 25 30

Time (sec)


M M ppi w>, .n,\rvT^n~*'H n ufi,

Jain's Index: Average 0.89 i *

10 15 20 25

Time (sec)


30

•

i r

/ /

h /

1_

100 Frame Window

.

•

\ + •' \

* v

i 1 1

3 •

1 •

O z

z>

s SI

H TJ CD CO

ra E o

0.6

0.5

0.4

0.3

0.2

0.1

0

0.1 0.2 0.3 0.4 0.5 0.6

0.6

0.5

0.4 f

0.3

0.2

0.1

0



5 10 15 20 25

Time (sec)


Connection A Connection B »

i 10 15 20 25

Time (sec)



5 10 15 20 25 30

Time (sec)


30

30

0.1 0.2 0.3 0.4 0.5 0.6

Figure 6.8 Three node topology, dynamic scenario for Probabilistic Discard algo

rithm using U D P 0 = 0.30


Enhanced CTS Suppression

The enhanced CTS results in Figure 6.9 illustrate the effectiveness of this mech

anism in controlling signal strength dependent unfairness. A 0 value of 0.55

provides an average fairness index of 0.91. However, the aggregate throughput

has been reduced while again reducing the aggregate throughput by 53%. The

average fairness index is increased by 40%, similar to the 3 7 % achieved with the

Probabilistic Discard technique. Figure 6.9(g) illustrates that a good fairness

outcome will be achieved in the range of 0 between 0.5 and 0.65.

6.5.6 Dynamic Scenario Discussion

The dynamic experiments have illustrated that each of the three mechanisms

are able to control hidden nodes responsible for significant unfairness suffered

by weaker hidden nodes. During periods where the stronger host changes, the

algorithm defined in Equation (6.2) is able to adapt quickly, allowing each

mechanism to then retain the fair behaviour during changes in the localised

topology. The reader is referred to Appendix B for T C P results in this scenario.

Table 6.1 summarises the percentage change in aggregate throughput and fair

ness index achieved with each scheme. This summary illustrates that while the

Enhanced C T S Suppression provides the greatest improvement in the fairness

index, there is a corresponding significant reduction in aggregate throughput.

This is a significant disadvantage for the Enhanced C T S Suppression mech

anism. The results in Table 6.1 illustrate that the p-Persistence on Backoff

Countdown mechanism offers a preferred combination of fairness improvement

and corresponding throughput reduction.

In each case the unfairness control schemes are again shown to be capable of

providing improved throughput for the weaker connections by preventing the

stronger connection from gaining unfair channel access. The well defined peak

in the fairness index as a function of 0 is present in each case, as with the static

scenarios.


2000 _ 1800 S 1600 m 1400 « 1200 § 1000 S 800 §3 600 | 400 200


1200

<g 1000

£ 800 CO CO Q •o CD

> CD CJ CD

DC

600

400

200

x CD TJ c

1.1 1

0.9 0.8 0.7

» 0.6 SS 0.5 I 0.4 "- 0.3

0.2 r 0.1 0


25 5 10 15 20 Time (sec)


30


10 15 20 25 30 Time (sec)


!Wf\, m i n./Mi* If j

in H \i

Jain's Index: Average 0.91

10 15 20 Time (sec)


25 30

•a

o Z

co E o Z

0.5

0.4

0.3

0.2

0.1



10 15 20 25 Time (sec)



i 10 15 20 25 Time (sec)



5 10 15 20 25 30 Time (sec)


30

30

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Figure 6.9 Three node topology, dynamic scenario for Enhanced CTS Suppression

algorithm using UDP 0 = 0.55


Table 6.1 Comparison of improvement in fairness index and reduced aggregate normalised throughput for static and dynamic UDP scenarios with each fairness control technique

Mechanism

p-Persistence

on Backoff

Countdown

Probabilistic

Discard

Enhanced

CTS Suppression

Static Scenario Fairness

Index

Increase

60%

39%

79%

Aggregate

Throughput

Reduction

2%

6%

56%

Dynamic Scenario

Fairness

Index

Increase

31%

37%

40%

Aggregate Throughput

Reduction

13%

39%

53%

6.6 Conclusions and Recommendations

In this chapter we have considered three schemes to correct for the relative

signal strength based unfairness identified, analysed, and modelled in previous

chapters. The investigation presented here was designed to establish the per

formance of each mechanism across a range of realistic network topologies and

signal strength scenarios.

The mechanisms proposed comprise two components. The first is a technique

to determine a probability variable for each hidden node in proportion to the

relative signal strength amongst all identified hidden nodes. This component is

common in all three mechanisms, and may be tuned through the capture param

eter, 7 to suit any specific P H Y displaying relative signal power based unfair

behaviour. The probability variable is then employed by each mechanism to

provide weaker connections with additional transmission opportunities. Three

mechanisms have been proposed, namely: p-Persistence on Backoff Countdown,

Selective Discard, and Enhanced CTS Suppression.


Through both the static and dynamic experiments outlined in previous sections,

the performance of the three fairness control mechanisms has been established.

The results of this investigation illustrate that all three mechanisms provide

a significant increase in the fairness properties and from this aspect would

be suitable for implementation in a physical system. However, the Enhanced

C T S Suppression technique results in an unacceptable reduction in aggregate

throughput. The Probabilistic Discard technique provides a smaller increase in

fairness index than the p-Persistence on Backoff Countdown technique, and a

larger reduction in aggregate throughput in dynamic scenarios. Combined with

the relative simplicity of the Probabilistic Discard technique, this implies that

the choice becomes one of trading implementation complexity and flexibility

against fairness and throughput performance.

In terms of performance, implementation complexity, and flexibility, results for

the p-Persistence on Backoff Countdown, Probabilistic Discard, and Enhanced

C T S mechanisms can be summarised in the following manner:

• The Enhanced CTS Suppression mechanism results in the greatest im

provement in the fairness index, though has the greatest impact on aggre

gate throughput. The range of 0 values required for optimal performance

is greater with this technique than the other mechanisms, ranging from

0.55 in the dynamic scenario up to 0.75 in the static scenario. This scheme

requires careful selection of 0 to achieve optimal performance. The im

plementation of this technique will make use of a planned enhancement

to the IEEE 802.11 standard allowing a node to forcibly suppress another

specified node, and therefore represents a flexible technique requiring no

additional changes to the standard outside those already planned. This

technique offers increased flexibility over the other mechanisms through

an implementation employing an enhancement to the IEEE 802.11 stan

dard. The reduction in throughput observed with this scheme represents a

significant disadvantage compared to the p-Persistence on Backoff Count

down and Probabilistic Discard techniques.


• The p-Persistence on Backoff Countdown mechanism results in a smaller

increase in the fairness index than the Enhanced C T S mechanism, being

approximately equal to the Probabilistic Discard technique in the dynamic

scenario. This technique has the smallest impact on aggregate throughput

of the three. This technique did not require any adjustment in the control

parameter as dynamic node behaviour was introduced, maintaining a con

stant value of 0 = 0.25 to achieve the optimal fairness outcome. However,

implementation of this scheme represents a significant problem in cases

where inter-operability and standards compliance are significant issues.

The mechanism proposed is to include the variable in a field within an

A C K frame, as it is directed, and therefore only interpreted by the receiv

ing node. However, this raises compatibility issues for stations employing

this technique with legacy IEEE 802.11 stations, who will be unable to

interpret an extended A C K frame format. In these cases, another option

is distribution of the probability variable within a new M M P D U control

frame format.

• The Probabilistic Discard mechanism whilst representing the most course

grained technique the three approaches, still provides good improvement

in the fairness properties while having and a moderate impact on aggregate

throughput. A control parameter of between 0 = 0.35 and 0 = 0.40 was

found to be suitable for the dynamic and static scenarios respectively.

The simplicity with which this scheme may be implemented represents

the biggest single advantage over other schemes. N o explicit information

exchange is required, as each node simply drops D A T A and R T S frames

from offending nodes. This mechanism trades simplicity against improved

performance, control, and flexibility.

The most important aspect of each scheme is the selection of the 0 value required

to optimise the fairness performance. The experiments have identified a defined

range of 0 values for each mechanism, suitable for the scenarios investigated

here. Investigation of other factors affecting the selection of an appropriate 0


is an issue requiring future study, including the development of an adaptive

technique to control 0. Further, the scalability of each mechanism with respect

to the number of nodes requires investigation.

The major recommendations for each technique arising from this investigation

are:

• In scenarios where aggregate throughput is significant, the p-Persistence

on Backoff Countdown mechanism appears to be the preferred alternative.

This is provided that compatibility and implementation issues can be

addressed.

• In scenarios where simplicity is the overriding concern, the Probabilis

tic Discard scheme has been shown to perform well in terms of fairness

outcomes.

• In scenarios where per connection fairness is the overriding factor, the

Enhanced C T S Suppression mechanism represents a more suitable option.

This comes at the expense of a significant reduction in aggregate through

put. The ability to tune the Enhanced C T S Suppression mechanism to

improve the aggregate throughput though adaption of the suppression

period, or the control parameter 0, requires further investigation.

Chapter 7

Conclusions

7.1 Overview

The popularity of high speed local area wireless networks has been driven in

recent years by the introduction of the IEEE 802.11 M A C / P H Y protocol. Ac

cordingly, there has been continued research effort examining many aspects of

the performance of wireless M A C protocols with respect to the quality of service

they are able to provide. While many early problems have been covered by ex

isting literature, this thesis has presented an investigation of capture effects and

fairness behaviour arising from an investigation of physical system performance.

This thesis has followed a path of identification, empirical investigation, anal

ysis, modelling, leading to the identification and evaluation of options for the

prevention of capture effects present in a range of physical IEEE 802.11 network

scenarios. This chapter presents a summary of the major results presented in

this thesis.

7.2 Significant Results

The literature review in Chapter 2 identified a need for an experimental inves

tigation of the fairness properties of the C S M A / C A M A C protocol employing

the R T S / C T S / D A T A / A C K handshake in a real propagation environment, with

161

Conclusions 162

particular reference to the capture behaviour of the system in terms of both

m o d e m and protocol capture. This is addressed in Chapter 3 through a de

tailed series of experiments in hidden terminal topologies with the IEEE 802.11

M A C / P H Y protocol. This investigation has uncovered a reliable and repeat-

able relationship between the relative signal strength of hidden connections and

the ability of a host to capture the radio channel. In all experiments involving

a measured difference in signal power of greater than 5dB, the stronger of two

hidden connections is able to gain preferential access to the channel, despite the

use of the R T S / C T S handshake to reserve transmission opportunities equally

for both nodes. The effect is observed with all current 802.11 DSSS PHY's,

and with the two radio front end circuits employed in all current 802.11 radio

interfaces.

Experiments performed with TCP illustrate that the adverse interaction be

tween the T C P and M A C retransmission timers is not present in cases where

the signal strength is equal on each connection. Experiments performed using

greedy U D P sources confirm this behaviour, with the stronger connection gain

ing significantly greater throughput than the weaker connection. Again, the

measured relative signal power threshold of 5dB was observed. In cases with an

equal received signal power on each connection, effective sharing is observed.

These results suggest a complex m o d e m capture behaviour biased in favour of

packets arriving at the receiver with a higher signal power.

Following the empirical identification of the relative signal strength dependence

in Chapter 3, Chapter 4 presents an analysis of the mechanisms behind this

behaviour. The scenario under investigation is one where a radio frame is as

sumed to be under reception when an interfering frame arrives at the receiver.

Expressions relating the B E R experienced by the original signal at the output

of the correlation receiver to the relative signal power between the interfering

and original signals are derived through a modification of the techniques used

to determine the magnitude of multiple access interference in C D M A systems.

This investigation illustrates that an interfering signal arriving with a relative

Conclusions 163

power of greater than 2dB will result in the effective corruption of the original

signal. Conversely, the interfering frame will suffer little impact from the origi

nal frame provided the receiver is able to resolve the two signals. This threshold

matches the empirical measurements presented in Chapter 3.

The results of Chapters 3 and 4 raise significant issues for the validity of sim

ulation models for physical IEEE 802.11 networks. In particular, the ability of

current receiver models to accurately model the effects identified and analysed

in previous chapters must be established. Chapter 5 presents an investigation

of the behaviour of packet capture models in terms of their ability to match

empirical data when employed in a simulation environment. Further, network

fairness at the transport layer is introduced as a metric to compare simulation

with packet capture models against empirical data. In response to an apparent

inability of current packet capture models to accurately reflect the empirical

data, a new model is proposed based on the physical operation of an IEEE

802.11 radio interface. The new model, termed Message Retraining, is shown

to be significantly more accurate in matching the fairness behaviour of empirical

data in terms of both magnitude of the fairness index, and the fairness horizon

or timescale over which the network is considered fair. This model is shown

to provide an accurate basis for the development of mechanisms to prevent

unfairness of this type arising in hidden terminal topologies.

Employing the model developed and validated in Chapter 5, Chapter 6 intro

duces a number of techniques to prevent unfair behaviour arising in hidden

terminal topologies as a result of relative signal power differences. Chapter 6

presents a utility function based mechanism, employing the average relative

signal power for identified hidden neighbours to determine a probability vari

able for each hidden connection. This is coupled with one of three mechanisms

designed to provide additional transmission opportunities for weaker connec

tions. Performance analysis indicates that all three techniques are effective in

providing improved fairness outcomes for network scenarios involving hidden

terminals, though a significant reduction in aggregate throughput was observed

Conclusions 164

for the Enhanced C T S Suppression technique. This reduced throughput, com

bined with implementation issues dictate that either the Probabilistic Discard

or p-Persistence on Backoff Countdown technique be employed in a physical

network. In terms of implementation, the p-Persistence on Backoff Countdown

technique requires the distribution of a probability variable to identified hidden

nodes. In comparison to the Probabilistic Discard technique which requires no

additional messaging. The three mechanisms aim to return the network to the

state where each connection has reliable carrier sense information. The mecha

nisms presented in Chapter 6 do require further investigation, though the results

obtained are very promising, considering the minimal cost required to provide

a significantly improved fairness outcome.

7.3 Further Work

This thesis has addressed a number of significant issues associated with capture

effects and related fairness properties in physical IEEE 802.11 networks. How

ever, there are still a number of issues that require further investigation. These

are described below.

• Extension of multiple access analysis to consider an OFDM physical layer.

Almost all new wireless P H Y proposals are based on an O F D M signalling

technique. The extension of the multiple access interference analysis pre

sented in Chapter 4 will be of significant benefit in identifying similar

behaviour in future O F D M systems. Further, due to a lack of O F D M

hardware available on the market at the time, the empirical performance

of an O F D M system in the hidden terminal topologies requires investiga

tion when suitable IEEE 802.11a O F D M systems are available.

• An opportunity exists to extend the development of the Message Retrain

ing capture model to determine the capture probability as a function of

the number of interfering hidden nodes. This may then be used with an

Conclusions 165

appropriate analytical model of the IEEE 802.11 M A C protocol to deter

mine the aggregate channel throughput achieved.

• An assumption made during the performance investigation of the fairness

control schemes is that all hidden nodes are identified to the common node.

Further investigation of suitable mechanisms to identify hidden nodes in

a general topology network is an issue requiring investigation. Potential

interactions between a hidden terminal identification mechanism and the

fairness control schemes proposed require examination.

• The scalability of each fairness control mechanism proposed in Chapter 6

with respect to the number of supported nodes requires investigation.

• A thorough investigation of the stability of each fairness control mecha

nism with respect to the control parameter, 0 will enable each mechanism

to enact more precise control.

• An adaptive mechanism to control 0 will require development.

• A detailed investigation of the interaction between MAC level QoS schemes

proposed for IEEE 802.11 and the fairness control mechanisms proposed

in Chapter 6 will be required before the fairness control techniques can

be employed in scenarios requiring service differentiation.

• A limitation in the performance analysis of the fairness control schemes

in Chapter 6 is the inability to test each scheme when employed in an

IEEE 802.11 radio interface. Investigation of the performance of the

Enhanced C T S Suppression, Probabilistic Discard, and p-Persistence on

Backoff Countdown mechanisms when implemented in an 802.11 radio

interface will provide additional insight into the range of 0 values over

which each scheme will provide reliable, stable operation.

• Merging fairness control mechanisms with schemes designed to control

general protocol or topology dependent unfairness is also a significant issue

requiring investigation. This may include the ability to incorporate traffic

Conclusions 166

observations as a decision making variable. This has the potential to allow

a combined scheme to provide a generalised fairness control technique.

• The investigation of power control mechanisms to prevent the unfair be

haviour observed in this thesis is an area for future investigation. The

results presented in Chapters 3 and 4 indicate that very fine power control

system capable of maintaining the range of received powers at a common

node within a 3dB range may provide a means of controlling the packet

capture problem. This may be possible in a traditional wireless L A N base

station - client topology, particularly given current power control efforts

within the IEEE 802.11 W G . Designing a power control mechanism to

achieve this aim in a general topology M A N E T style network is a non-

trivial problem.

• Detailed investigation of the Point Co-ordinate Function and the Hybrid

Co-ordinate Function M A C protocols within 802.11 in similar scenarios to

those investigated here. As these M A C protocols are centrally controlled,

hidden stations will not be forced to contend for channel access. This has

the potential to remove the relative signal strength basis, though other

issues with polling beacon reception may arise. This area requires detailed

investigation.

• Refinement and extension of the interpretation of fairness in both a per

user and global sense is required.

Bibliography

Abramson, N. (1970). The ALOHA System - Another Alternative for Com

puter Communications. In 1970 Fall Joint Computer Conference, AFIPS

Conference Proceedings, volume 37, pages 281-285.

Abramson, N. (1977). The Throughput of Packet Broadcasting Channels. IEEE

Transactions on Communications, 25(1):117—128.

Anastasi, G., Lenzini, L., and Mingozzi, E. (2000). HIPERLAN/1 M A C Proto

col: Stability and Performance Analysis. IEEE Journal on Selected Areas

in Communications, 18(9):1787-1798.

Arnbak, J. C. (1987). Capacity of Slotted ALOHA in Rayleigh fading channels.

IEEE Journal on Selected Areas in Communications, 5:261-269.

Bensaou, B., Wang, Y., and Ko, C. C. (2000). Fair medium access in 802.11

based wireless ad-hoc networks. In Mobile and Ad Hoc Networking and

Computing, 2000. Mobihoc. 2000, pages 99-106, Boston, MA.

Bharghavan, V., Demers, A., Shenker, S., and Zhang, L. (1994). M A CAW:

A Media Access Protocol for Wireless LAN's. In SIGCOMM 94, pages

212-225. ACM.

Cali, F. Conti, M. and Gregori, E. (2000). IEEE 802.11 Protocol: Design and

Performance Evaluation of an Adaptive Backoff Algorithm. IEEE Journal

on Selected Areas in Communications, 18(9): 1774-1786.

Chandra, A., Gummalla, V., and Limb, J. O. (2000). Wireless Collision Detect

(WCD): Multiple Access with Receiver Initiated Feedback and Carrier De-

167

BIBLIOGRAPHY 168

tect Signal. In IEEE International Conference on Communications, ICC,

volume 1, pages 397-401.

Chandran, K., Raghunathan, S., Venkatesan, S., and Prakash, R. (1998). A

Feedback Based Scheme For Improving TCP Performance In AdHoc Wire

less Networks. In Papazoglou, M., editor, Distributed Computing Systems,

volume 1, pages 472 - 479, Dallas, Tx, USA. IEEE.

Chesson, G., Diepstraten, W., Hoeben, M., Singla, A., Teunissen, A., and

Wentink, M. (2001). IEEE 802.11-01/131rl Proposed VDCF Draft Text.

IEEE 802 LAN/MAN Standards Committee, P802.ll Working Group,

Task Group E: M A C QoS Enhancements.

Cheun, K. and Kim, S. (1998). Joint Delay-Power Capture in spread-spectrum

packet radio networks. IEEE Transactions on Communications, 46(4):450

-453.

Choi, S., Gray, S., Kasslin, M., Mangold, S., Soomro, A., Myles, D., Skellern,

D., and Ecclesine, P. (2001). IEEE 802.11-01/169r2 Transmitter Power

Control (TPC) / Dynamic Frequency Selection (DFS) Joint Proposal for

802.11h W L A N . IEEE 802 LAN/MAN Standards Committee, P802.ll

Working Group, Task Group H: Spectrum and Transmit Power Manage

ment in 5GHz BAND.

Colvin, A. (1983). CSMA with Collision Avoidance. Computer Communica

tions, 6(5):227-235.

Davis, D. H. and Gronemeyer, S. (1980). Performance of slotted ALOHA ran

dom access with delay capture and randomised time of arival. IEEE Trans

actions on Communications, 28:703 - 710.

Deng, J. and Haas, Z. J. (1998). Dual Busy Tone Multiple Access (DBTMA):

A New Medium Access Control for Packet Radio Networks. In IEEE In

ternational Conference on Universal Personal Communications, ICUPC,

volume 2, pages 973-977, Florence, Italy.

http://P802.ll

http://P802.ll

BIBLIOGRAPHY 169

Deng, J. and Haas, Z. J. (1999). Dual Busy Tone Multiple Access (DBTMA):

Performance Results. In IEEE Wireless Communications and Networking

Conference, WCNC, volume 3, pages 1328-1332, New Orleans, LA, USA.

European Telecommunications Standards Intsitute (1998). Broadband Radio

Access Networks (BRAN): High Performance Radio Local Area Networks

(HIPERLAN).

Fischer, M. (2001). IEEE 802.11-01/110rl Hybrid Co-ordination Function

(HCF) Proposed Updates to Normative Text. IEEE 802 LAN/MAN Stan

dards Committee, P802.ll Working Group, Task Group E: M A C QoS En

hancements.

Fullmer, C. and Garcia-Luna-Aceves, J. (1995). Floor Acquisition Multiple

Access (FAMA) for packet radio networks. In SIGCOMM 95, pages 262-

273, Cambridge MA. ACM.

Fullmer, C. L. and Garcia-Luna-Aceves, J. J. (1997a). Complete Single-Channel

Solutions to Hidden Terminal Problems in Wireless LANs. In IEEE Inter

national Conference on Communications, ICC, volume 2, pages 575-579,

Montreal, Canada. IEEE.

Fullmer, C. L. and Garcia-Luna-Aceves, J. J. (1997b). Solutions to Hidden

Terminal Problems in Wireless LANs. In SIGCOMM 97, volume 1, pages

39-49, Cannes, France. ACM.

Fullmer, C. L. and Garcia-Luna-Aceves, J. J. (1998). Performance of Floor

Acquisition Multiple Access in Ad Hoc Networks. In IEEE Symposium on

Computers and Communications, volume 1, pages 63-68, Athens, Greece.

IEEE.

Garcia-Luna-Aceves, J. J. and Tzamaloukas, A. (1999). Reversing the Collision

Avoidance Handshake in Wireless Networks. In ACM/IEEE International

Conference on Mobile Computing and Networking, Mobicom, pages 120-

131. ACM/IEEE.

http://P802.ll

BIBLIOGRAPHY 170

Geraniotis, E. and Pursley, M. B. (1982). Error Probability for Direct Sequence

Spread Spectrum Multiple Access Communications - Part II: Approxima

tions. IEEE Transactions on Communications, 30(5):985-995.

Geraniotis, E. and Soroushnejad, M. (1987). Collision Resolution Algorithms

for Networks with Spread Spectrum Capture Capability. Technical report,

University of Maryland, Institute for Systems Research.

Gerla, M., Bagrodia, R., Tang, K., and Wang, L. (1999a). TCP Over Wireless

Multi-hop Protocols: Simulation and Experiments. In IEEE International

Conference on Communications, volume 1, Vancouver, Canada. IEEE.

Gerla, M., Tang, K., and Bagrodia, R. (1999b). TCP Performance in Wireless

Multihop Networks. In 2nd IEEE Workshop on Mobile Computing Systems

and Applications, volume 1, pages 41 - 50. IEEE.

Goodman, D. J. and Saleh, A. A. M. (1987). The Near/Far Effect in Local

A L O H A Radio Communications. IEEE Transactions on Vehicular Tech

nology, 36(l):19-27.

Hansen, C, Fischer, M., Gubbi, R., and Kim, J. (2001). IEEE 802.11-01/217

TPC/DFS Proposal for 802.llh. IEEE 802 LAN/MAN Standards Com

mittee, P802.ll Working Group, Task Group H: Spectrum and Transmit

Power Management in 5GHz BAND.

Holland, G. and Vaidya, N. (1999). Analysis of TCP Performance over Mobile

Ad-Hoc Networks. In Fifth Annual International Conference on Mobile

Computing and Networking, Mobicom 99, Seatle.

Institution of Electrical and Electronic Engineers (1999a). Part 11: Wireless

LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifi

cations.

Institution of Electrical and Electronic Engineers (1999b). Part 11: Wireless


cations, Higher Speed Physical Layer Extension in the 2.4 GHz Band.

http://P802.ll

BIBLIOGRAPHY 171

Institution of Electrical and Electronic Engineers (1999c). Part 11: Wireless


cations, Higher Speed Physical Layer in the 5 GHz Band.

Jain, R., Chiu, D., and Hawe, W. (1984). A Quantitative Measure Of Fairness

And Discrimination For Resource Allocation In Shared Computer Systems.

Technical Report TR-301, Digital Equipment Corporation.

Karkkainen, K. H. (1992). Mean-Square Cross Correlation As A Performance

Measure for Spreading Code Families. In IEEE 2nd Int. Symp. on Spread

Spectrum Techniques and Applications, Yokohama, Japan.

Karn, P. (1990). MACA - A New Channel Access Method for Packet Radio.

In AARL/CRRL Amateur Radio 9th Computer Networking Conference,

pages 134-40.

Kim, D. I., Kim, I. K., and Scholtz, R. A. (1995). Counting Collision Free Trans

missions in Common-Code SSMA Communications. IEEE Transactions on

Communications, 43(2/3/4).

Kleinrock, L. and Tobagi, F. A. (1975). Packet Switching in Radio Channels:

Part I-Carrier Semse Multiple-Access Modes and Their Throughput-Delay

Characteristics. IEEE Transactions on Communications, 23(12):1400-

1416.

Koksal, C. E., Kassab, H., and Balakrishnan, H. (2000). An Analysis of Short

Term Fairness in Wireless Media Access Protocols: Extended Version of

short paper. In ACM Sigmetrics.

Lau, C. and Leung, C. (1992). Capture Models for Mobile Packet Radio Net

works. IEEE Transactions on Communications, 40(5):917-925.

Lawrence Berkeley Laboratories (1999). tcpdump. http://www.tcpdump.org.

Lu, S., Bharghavan, V., and Srikant, R. (1999). Fair Scheduling in Wireless

Packet Networks. IEEE/ACM Transactions on Networking, 7(4):473-489.

http://www.tcpdump.org

BIBLIOGRAPHY 172

Luo, H., Lu, S., and Bharghavan, V. (2000). A New Model for Packet Scheduling

in Multihop Wireless Networks. In ACM Mobicom.

Mud, R., Boer, J., Kamerman, A., Van Driest, H., Diepenstraten, W., Kop-

meiners, R., and Von Bokhorst, H. (1999). Wireless LAN With Enhanced

Capture Provision. US Patent No US5987033.

Muir, A. and Garcia-Luna-Aceves, J. J. (1997). Group allocation multiple access

with collision detection. In INFOCOM 97, Sixteenth Annual Joint Con

ference of the IEEE Computer and Communications Societies, volume 3,

pages 1182 -1190.

Nandagopal, T., Kim, T.-E., Gao, X., and Bharghavan, V. (2000). Achieving

M A C Layer Fairness in Wireless Packet Networks. In A CM Mobicom,

Boston, MA.

Nasipuri, A., Zhuang, J., and Das, S. R. (1999). A Multichannel CSMA M A C

Protocol for Multihop Wireless Networks. In IEEE Wireless Communica

tions and Networking Conference, WCNC, volume 3, pages 1402-1406.

Ozugur, T., Naghshineh, M., Kermani, P., and Copeland, J. A. (1999). Fair

Media Access Methods for Wireless LAN's. In Proc. of IEEE Globecom,

volume 2, pages 570-579.

Ozugur, T., Naghshineh, M., Kermani, P., Olsen, C. M., Rezvani, B., and

Copeland, J. A. (1998). Balanced Media Access Methods for Wireless

Networks. In Proc. of ACM/IEEE MobiCom, volume 1, pages 21-32.

Pagtzis, T., Kirstein, P., and Hailes, S. (2001). Operational and Fairness Issues

with Connection-less Traffic over IEEE 802.11b. In IEEE International

Conference on Communications, ICC 2001, volume 1.

Proakis, J. G. (1995). Digital Communications. McGraw Hill, third edition.

Pursley, M. B. (1977). Performance Evaluation for Phase Coded Spread Spec

trum Multiple Access Communication - Part 1: System Analysis. IEEE

Transactions on Communications, 25(8):795-799.

BIBLIOGRAPHY 173

Rappaport, T. S. (1996). Wireless Communications: Principles and Practice.

Prentice Hall.

Sherman, M. (2001). IEEE 802.11-01/130r5 Proposed Normative Text for ERTS

and ECTS. IEEE 802 LAN/MAN Standards Committee, 802.11 Working

Group, Task Group E: M A C QoS Enhancements.

Sobrinho, J. and Krishnakumar, A. S. (1999). Quality of Service in Ad Hoc Car

rier Sense Multiple Access Wireless Networks. IEEE Journal on Selected

Areas in Communications, 17(8):1353-1368.

Soroushnejad, M. and Geraniotis, E. (1991). Probability of Capture and Rejec

tion of Primary Multiple Access Interference in Spread Spectrum Networks.

IEEE Transactions on Communications, 39(6):986-994.

Swan, A. and Raman, S. (2000). A Study of Short Term Fairness in Wireless

M A C Protocols. In Technical Report.

Talucci, F. and Gerla, M. (1997). MACA-BI (MACA By Invitation) A Wireless

M A C Protocol for High Speed Ad-Hoc Networking. In 6th Annual Con

ference on Universal Personal Communications, volume 2, pages 913-917.

IEEE.

Talucci, F., Gerla, M., and Fratta, L. (1997). MACA-BI (MACA By Invitation)

A Receiver Oriented Access Protocol for Wireless Multihop Networks. In

Personal, Indoor & Mobile Radio Communications - Waves of the Year

2000, volume 2, pages 435-439. IEEE.

Tang, K., Correa, M., and Gerla, M. (2001). Effects of Ad Hoc MAC Layer

Medium Access Mechanisms Under TCP. To Appear: ACM/Baltzer Mobile

Networks and Applications, MONET.

Tang, K. and Gerla, M. (1999). Fair Sharing of MAC under TCP in Wire

less Adhoc Networks. In Multimedia, Mobility and Teletraffic for Wireless

Networks (MMT'99), Venice, Italy. IEEE.

BIBLIOGRAPHY 174

Tang, Z. and Garcia-Luna-Aceves, J. J. (2000). Collision Avoidance Transmis

sion Scheduling for Ad Hoc Networks. In IEEE International Conference

on Communications, volume 2, pages 183-190.

TGe (2001). DRAFT: Medium Access Control (MAC) Enhancements for Qual

ity of Service. IEEE 802 LAN/MAN Standards Committee, 802.11 Working

Group, Task Group E: M A C QoS Enhancements.

TGh (2001). DRAFT: Medium Access Control (MAC) and Physical Layer

(PHY) Spectrum and Transmit Power Management Extensions on the

5GHz Band in Europe. IEEE 802 LAN/MAN Standards Committee, 802.11

Working Group, Task Group H: Spectrum and Transmit Power Manage

ment in 5GHz BAND.

Tobagi, F. A. and Kleinrock, L. (1975). Packet Switching in Radio Channels:

Part II-The Hidden Terminal Problem in Carrier Sense Multiple-Access

and the Busy Tone Solution. IEEE Transactions on Communications,

23(12):1417-1433.

Tobagi, F. A. and Kleinrock, L. (1976). Packet Switching in Radio Channels:

Part III- Polling and (Dynamic) Split-Channel reservation Multiple Access.

IEEE Transactions on Communications, 24(8):832-844.

Tzamaloukas, A. and Garcia-Luna-Aceves, J. (1999). Poll-Before-Data Multiple

Access. In International Conference on Communications, ICC, volume 2,

pages 1207-1211. IEEE.

Tzamaloukas, A. and Garcia-Luna-Aceves, J. J. (2001). A Receiver-Initiated

Collision-Avoidance Protocol for Multi-Channel Networks. In INFOCOM,

pages 189-198, Anchorage, AK, USA. IEEE.

Tzamaloukas, A. E. (December 2000). Sender and Receiver Initiated Multiple

Access Protocols For Ad Hoc Networks. PhD thesis, University of Califor

nia, Santa Cruz.

BIBLIOGRAPHY 175

UCB/LBNL/VINT (1999). ns - Network Simuator. UCB/LBNL/VINT,

http://www-mash.cs.berkeley.edu/ns/.

Ware, C. and Dutkiewicz, E. (2001). IEEE 802.11-01/232 Packet Capture UDP

Experiments. IEEE 802 LAN/MAN Standards Committee, P802.ll Work

ing Group, Task Group E: M A C QoS Enhancements.

Ware, C. G., Judge, J., Chicharo, J. F., and Dutkiewicz, E. (2000). Unfair

ness and Capture Behaviour in 802.11 Adhoc Networks. In International

Conference on Communications, volume 1, New Orleans. IEEE Press.

Ware, C. G., Wysocki, T., and Chicharo, J. (2001a). Hidden Terminal Jam

ming Problems in IEEE 802.11 Mobile Ad Hoc Networks. In International

Conference on Communications, Helsinki. CRDOM.

Ware, C. G., Wysocki, T., and Chicharo, J. (2001b). On The Hidden Terminal

Jamming Problem in IEEE 802.11 Ad Hoc Networks, submitted to: IEEE

Transactions on Vehicular Technology.

Ware, C. G., Wysocki, T., and Chicharo, J. (2001c). Simulating Capture Be

haviour in IEEE 802.11 Radio Modems. Journal of Telecommunications

and Information Technology.

Ware, C. G., Wysocki, T., and Chicharo, J. (2001d). Simulation of Capture

Behaviour In IEEE 802.11 Radio Modems. In Vehicular Technology Con

ference, Fall 2001, New Jersey. IEEE.

Ware, C. G., Wysocki, T., and Chicharo, J. F. (2001e). Modelling Capture

Behaviour In IEEE 802.11 Radio Modems. In International Conference on

Telecommunications, Bucharest. IEE / IEEE. CDROM.

Webster, M. and Halford, S. (2000). IEEE 802.11-00/389rl Overview of OFDM

for High Rate Extension. IEEE 802 LAN/MAN Standards Committee,

P802.ll Working Group, Task Group G: High Rate Extensions in 2.4 GHz

Band.

http://www-mash.cs.berkeley.edu/ns/

http://P802.ll

http://P802.ll

BIBLIOGRAPHY 176

Wu, S., Tseng, Y., and Sheu, J. (2000). Intelligent Medium Access for Mobile

Ad Hoc Networks with Busy Tones and Power Control. IEEE Journal on

Selected Areas in Communications, 18(9).

Appendix A

Hidden Node Detection Mechanisms

As mentioned in Section 6.3.1, identification of hidden nodes is a key issue

for the performance of any technique designed to control unfair behaviour as a

result of hidden terminals. In this appendix, we outline proposed mechanisms to

identify potential hidden node pairs within the 802.11 framework. This can then

be employed to instigate the fairness control algorithms under development.

Within the context of a C S M A / C A M A C , a potential mechanism to identify

hidden nodes exists through observation of message exchange semantics within

either the R T S / C T S / D A T A / A C K or D A T A / A C K handshake. Figure A.l below

outlines the scenario for the identification of a hidden node. In this context,

nodes 1 and 3 are hidden nodes, with node 1 referred to as the hidden node for

node 3, via node 2.

An STA is able to identify a potential hidden STA if it receives a significant

number of C T S frames addressed to another STA, without observing the cor

responding R T S or D A T A frames. If such a case is observed, the intended

recipient of the C T S frame is the potential hidden STA, and the transmitter of

the C T S frame the node via which the hidden STA is present. Referring to Fig

ure A.l, STA 3 is able to identify STA 1 as hidden when C T S and A C K frames

addressed to STA 1 are observed without having observed the corresponding

177

Hidden Node Detection Mechanisms 178

^^-- Hidden Nodes ____

® © ®

i RTS TA=1

; CTS RA = I

! DATA TA=1

! ACK RA = 1

C T S RA = I ;

A C K RA=1 !

I I I

Figure A.l Hidden Terminal Message Exchange Semantics. Node 3 observes node 1 as hidden via CTS and A C K frames

RTS or DATA frames from STA 1.

In the case where no RTS/CTS handshake is employed, the messaging exchange

involves D A T A and A C K frames only. Each STA will be required to observe

A C K frames, then having observed no corresponding D A T A frames the intended

recipient of the A C K can be identified as a hidden node. Figure A.l provides

an overview of the message exchange observations required to identify a hidden

node.

Observation of messaging exchange sequences can be implemented using either

timing flags, or through a table of known neighbours. 802.11 places tight tim

ing constraints on the transmission of C T S and A C K messages (Institution of

Electrical and Electronic Engineers, 1999a). A n RTS must be followed by a

C T S after a single SIFS period. Likewise, an A C K frame must be returned a

single SIFS period after the completion of the D A T A frame. These constraints

may be exploited to identify a potential hidden node. If a node observes a C T S

frame without having observed the immediately previous RTS, followed by an

A C K without having observed the preceding D A T A frame, the Receiving Ad-

<u


dress (RA) of the C T S and A C K frame is a potential hidden node. This can be

achieved by recording the SA of the R T S or D A T A frame and the Duration/ID

field.

When a CTS or ACK frame is observed on the WM, the RA and Duration/ID

are compared against the address and duration recorded previously. Inconsis

tencies between the address or the duration fields indicate that the C T S may

have origininated from a hidden node. This is outlined in Figure A.2. Upon

receipt of a C T S frame, the Duration field should match the duration from the

corresponding R T S frame, less the time required to transmit the C T S frame and

a single SIFS period. If the observed Duration is inconsistent with the cached

value, the C T S frame is directed towards a potentially hidden host. A similar

process can be followed to determine if the Duration field within the A C K frame

is consistent with the value cached from a corresponding D A T A frame.

Alternatively, the cache of known neighbours introduced in Section 6.3, can be

utilised to identify potential hidden nodes. Upon reception of a C T S or A C K

frame the R A is checked against the cache of known neighbours. If the address

is unknown, then a potential hidden node has been identified. The algorithm

required to implement this technique is outlined graphically in Figure A.3.

Both the address based, and the timing method will require a threshold number

of observations to prevent 'false alarm' hidden node indications in a practical

implementation. Once a node has identified a hidden node, the address of the

hidden node must be communicated to the common node, via which the hidden

node is present. This can be achieved using a hidden station identification

management frame proposed in (TGh, 2001). Unfortunately, within the 802.11

standard an SA field is not included within a C T S or A C K frame. Without

the S A a node cannot identify the common node via which the hidden node is

observed. Referring to Figure A.l for example, node 3 is unable to identify node

2 as the common node via which node 1 is hidden. To overcome this limitation, a

node will be required to broadcast the hidden station identification notification

to all neighbours. A node receiving the hidden station management notification


(a) Nodes 1, 2, 3 Not Hidden

® RTS SA = l

CTS RA = !

DATAS A = 1

ACK R A = j

" R T S SA = 1 !

;CTSRA=I i

JDATASA=J

;ACKRA = 1 I

& co

,f to

n co

CTS/ACK immediately

preceeded by RTS/DATA

Consistent SA/Duration

(b) Nodes 1 and 3 hidden

® © ® ! RTS S A = 1 \

i i /

| C T S R A = 1 j

: DATAS A = 1 : ; 1 I ;

! ACK R A = 1 , ,

,6 CTSRA-J I

I C O " j

t 6

M 1

r & A C K R A _ j |

1

CTS or A C K not immediately

preceeded by RTS or D A T A

. Inconsistent SA/Duration

Figure A.2 STA 3 observes STA 1 as hidden through the timing constraints places

on CTS and A C K frames. In (a) STA 3 is not hidden from STA 1, hence Duration

and SA fields are consistent. In case (b) where STA 3 is hidden from STA 1, the

cached Duration and SA fields will be inconsistent with the values observed in the

CTS or A C K frames


® (a) Nodes 1, 2, 3 Not Hidden

Known STA List

~4

1

R T S SA = 1

CTS RA _ j

DATAS A = 1

ACK R A _ i

' R T S S A = 1 i

iCTS*A = > i JDATASA = 1

|ACKRA=1 i

Node 3 Action

STA 1 updated in Known STA List

_ STA 1 matched in known STA list

- STA 1 updated in known STA list

- STA 1 matched in known STA list

(b) Nodes 1 and 3 hidden

® ! R TS S A = I

| CTSRA=1

1 1

! \

! DATAS A = 1 J J

! ACKR A = 1 ji

l CO

co

I CO

' 55

tl

CTSRA=1 |

ACKR^S^ = j \

1

Node 3 Action

STA 1 not added to known STA list

STA 1 not matched in known STA list

STA 1 not added to known STA list STA 1 not matched in known STA list

STA 1 identified by STA 3 as hidden STA

Figure A.3 STA 3 observes STA 1 as hidden as no RTS or DATA frames have been

received to update known neighbour list in STA 3. In (a) STA 3 is not hidden from

STA 1, hence STA 3 is able to identify and maintain STA 1 in the known neighbours

list. In case (b) where STA 3 is hidden from STA 1, the R A within CTS and A C K

frames will not be found in the known neighbours list


which also contains both the SA and hidden node address within the notification

in the cache of known neighbours, is therefore the common node between the

hidden node pair. The common node is then able to apply a fairness control

mechanism as outlined in Sections 6.4.1, 6.4.2, and 6.4.3.

Appendix B

Additional Fairness Algorithm Results

B.l 3 Node TCP Results

The results presented here are the result of additional trials investigating the

performance of each fairness control mechanism with T C P traffic streams. Both

the static and dynamic scenarios of Sections 6.5.3 and 6.5.5 employed.

B.l.l Static topology Results

Additional TCP based results for the 3 node static hidden terminal topology of

Section 6.5.3.

Figure B.l p-Persistence on Backoff Countdown

Figure B.2 Probabilistic Discard

Figure B.3 Enhanced CTS Suppression

183

Additional Fairness Algorithm Results 184

(a) Data Trace - Evolution p = 0

1800

^ 1600

§• 1400

§ 1200

8 1000 co Q T3

>

'8 <D

OC

(b) Data Trace - Access Times (5 = 0

800

600

400

200

0

1400

•vr 1200 CD

m 1000

w 800 a ° 600

I 400 o CD

tt 200

1.1 1

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0


5 10 15 20 25 30

Time (sec)



10 15 20 25 30

Time (sec)


r.vifl9^.ffiv^py^M^--^"!xv4y!^-ft-!

Jam's Index: Average 0.96

10 15 20

Time (sec)


25 30

0.35

•o

o Z

3 n sz o> 3 p -C

•n

<» <a a E o Z

0.4

0.35

OH

0.2b

0.2

0.15

0.1

0.05

0

Q. J= D> 3

P CD CO

ra E o z

0.3

0.25

0.2

0.15

0.1

0.05

0


5 10 15 20 25

Time (sec)



10 15 20 25

Time (sec)



10 15 20

Time (sec)


Connection A Connection B *

30

30

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Figure B.l 3 node topology, static scenario for p-Persistence on Backoff Countdown

algorithm using TCP - optimal 0 = 0.25


(a) Data Trace - Evolution (3 = 0 1800

_ 1600

J[ 1400 § 1200

8 1000 CO

° 800 § 600 CD

8 400 = 200


1200

« 1000 S. m CO

c3 Q T3 CD

> CD U CD

CE

800

600

400

200


5 10 15 20 25 30 Time (sec)



A • r

< > • ' '

•

•

10 15 20 25 Time (sec)


30

CD n

E 2

z 1

13 O

z

X CO 13

CO CO CD

CO LL

1.1 1

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 C

r-

-AA

•

) 5

1 1 1 1

\ /us j A^IM n w « u n i i Nrv**rnr\!$

\ U v \Z V j

Jam's Index: Average 0.96 t *

10 15 20 25

Time (sec)


3

3 Q. SI O) 3 H 13

"co E o z

0

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

o sz O)

s sz CD CO CO

F o

0.5 0,45

0.4 0.3b 0.3

0.25

0.2 0.15

0.1 0.05

0



10 15 20 25 Time (sec)


5 10 15 20 25 30 Time (sec)


30


5 10 15 20 25 30 Time (sec)



_3_ 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

P

Figure B.2 3 node topology, static scenario for Probabilistic Discard algorithm using TCP - optimal 0 = 0.40



3000

« 2500 % * 2000 co ™ 1500 t> CD

>

8 CD

DC

1000

500

CD

%. m CO

ra D ID

§ CD

o CD

DC

1000

900

800

700

600

500

400

300

200

100

1.1 1

0.9 x 0.8 CD

S 0.7 • 0.6 8 0.5

co LL

0.4 • 0.3 0.2

0.1 r 0


5 10 15 20 25 30

Time (sec)



-•

./ y f

,,y jy

. *

/

L

'

/

J'" f

'

1

/ " •

y y-y •

s ^

-

-

,

10 15 20

Time (sec)


25 30

f. A f\ ,*\A », r\ n n^M A

Jam's Index: Average 0.89

10 15 20

Time (sec)


25 30

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1 •

3 r> sz O)

o s:

<i> CO CO b o Z

0.4

0.35

OH 0.25

0.2

0.15

0.1

0.05

0

0.5

0.45

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0



5 10 15 20 25 30

Time (sec)



K « *XM X

10 15 20 25

Time (sec)


30


10 15 20

Time (sec)



0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

P

Figure B.3 3 node topology, static scenario for Enhanced CTS Suppression algorithm

using T C P - optimal 0 = 0.55


B.l.2 Dynamic Topology Results

Additional TCP based results for the dynamic 3 node topology of Section 6.5.5

Figure B.4 p-Persistence on Backoff Countdown

Figure B.5 Probabilistic Discard

Figure B.6 Enhanced CTS Suppression



1600

~ 1400 CD

S. 1200 m * 1000 CO

g 800 "§ 600

'8 400 CD

*• 200


1600

~ 1400 £ •5. 1200 m * 1000 co ™ 800 •a

I 8 400 CD 01 200

600 •

CD T3

Connection A * Connection B »

5 10 15 20 25

Time (sec)


Connection Connection


30

•a

o Z

XX .. .

_ ™ ™ ™


13 O

z

0

1.1 1

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2

0.1 0 C )

'

I

5

5 10 15 20 25 30

Time (sec)


, rr "Ti! \ t | \ j:; .* a ,=1 .'

Jain's Index: Average 0.96 , *

10 15 20 25 3

Time (sec)

3 Q. SZ CD 3

8 s: 1-

•a CD CO

n E o Z 0

0.3

0.25

0.2

0.15 r

0.1

0.05 r

0

CO 3

s SZ

^-T3 CD CO

ro E b z

0.3

0.25

0.2

0.15

0.1

0.05 I-

0

5 10 15 20 25

Time (sec)




10 15 20

Time (sec)



0.1 0.2 0.3

P 0.4 0.5

30

10 15 20 25 30

Time (sec)


0.6

Figure B.4 3 node topology, static scenario for p-Persistence on Backoff Countdown

algorithm using TCP - optimal 0 = 0.05



CO CO Q 13

§ CD O CD

DC

1800 ^ 1600 CO

§, 1400 § 1200

1000 800

600

400

200

0

1400

IS 1200 CD

§• 1000 *: co 0! Q

CD O CD

DC

800

600

400

200

2.

1.1 i

0.9 0.8 0.7 I-0.6 0.5 0.4 0.3 0.2 0.1 0

1

x 0.9 S - 0.8 r

CD

S 0.6 CD

* 0.5

0.4


25 5 10 15 20 Time (sec)


30


5 10 15 20 Time (sec)


"JA rf "> ft.

Jajn's Index: Average 0.90

10 15 20 Time (sec)


25 30

100 Frame Window

0.1 0.2 0.3 0.4 0.5 0.6

P

T3 O

z

0.3

3 C) SZ n> 3 n sz T) CD (0 ffl h Z

0 25

0.2

0.15

0.1

0.05

0



5 10 15 20 25 Time (sec)



10 15 20 25 Time (sec)

(f) Normalised Throughput p - 0.30


30

30

5 10 15 20 25 30 Time (sec)



0.1 0.2 0.3 0.4 0.5 0.6

P

Figure B.5 3 node topology, dynamic scenario for Probabilistic Discard algorithm

using T C P - optimal 0 = 0.30



1800

^ 1600 • CO

£ 1400 • §_ 1200 • 8 1000 •

800 •

600

400 I-

200

0

•a

I '<u o CD

DC


1400

•S? 1200 CD

§ 1000

«T 800 co ° 600 2 5 400 o CD

C 200

1.1 1

0.9 x 0.8 CU

f 0.7 • « 0.6 • 8 0.5

I 0.4 "- 0.3

0.2 0.1 0

25 5 10 15 20

Time (sec)



10 15 20 25

Time (sec)


( (I ft/W M

Jain's Index: Average 0.96

10 15 20 25

Time (sec)


30

30

O

z

3 O

T3 CD .CO

« E h_

o z

0.3

0.2

0.1




_j i_


\ / \

5 10 15 20 25 30 Time (sec)


0 5 10 15 20 25 30

Time (sec)


5 10 15 20 25 30

Time (sec)



0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

P 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Figure B.6 3 node topology, dynamic scenario for Enhanced C T S Suppression algo

rithm using T C P - optimal 0 = 0.25

2001 An investigation of capture effects in IEEE 802.11 ...

Documents

Transcript of 2001 An investigation of capture effects in IEEE 802.11 ...