SC03_10r1 Smart Antenna

7/31/2019 SC03_10r1 Smart Antenna

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Standardization and System

integration of Smart AntennasintoWireless Networks

Adrian BoukalovHelsinki University of Technology

Communications Lab

ETSI/MESA meeting

[email protected]


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Content

1.Smart antennas. Benefactors. Operators perspective. User perspective.

2. Overview of communication systems with Smart Antennas (SA).

3. Basics of Smart Antennas Techniques. SA types, classification.

4. Integrated receiver design with SA.

5. Impact of mobility, propagation environment and interference on

SA applicability and performance.

6. Air interface spec and SA compatibility/performance.Standardization

related issues7. Wireless network performance and planning with SA.

8. Current status and future evolution of SA techniques.

9. SA system integration: Problems Solutions

10. SA system integration research at ComLab/HUT


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"Spatial Processing remains as the most

promising, if not the last frontier, in the

evolution of multiple access systems"

Andrew Viterbi

There are very few techniques proposedtoday, which are able to improve radio network

performance dramatically

- Spatial processing

- Multi-user detection

- Channel reuse based on polarization

- Advanced network control

Spatial processing is among them and can be

effectively combined with others techniques

How smart should be Smart Antennas techniques ?


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Smart Antenna Technology:Benfactors

Network capacity, coverage, lessinternetwork interference, filling

dead spots, fewer BSs,QoS, new

services...-> revenues

New market for more advanced BSs,

flexible radio network control...

Higher QoS, more reliable, secure

communication, new services,

longer battery life...

Operator

OEM

User


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Smart Antenna Technology:Motivation

- Interference cancellation

at the up and down links

- SNR improvement

due to antenna gain

- Multipath mitigation

capacity

coverage

Quality of service

(QoS), bit rate,

mobility rate

Link level improvements System improvements


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Smart Antennas might be used at:

- A. BS only

up-link..coverage (HSR)&down-link..coverage + capacity, spectrum efficiency due to

reuse: between cells (SFIR),due to reuseinside cell (SDMA), both SDMA+SFIR

- B. MS/subscriber onlyup-linkcapacity/. due to the tighter channel reuse&down-link....coverage (WLL applications)

- C. Both endsMS and BSsimultaneously..coverage + capacity (A+B) + higher bit rateup-link & due to spatially multiplexed parallel channels anddown-link split high bit rate data streams between them or

.....higher transmission quality with ST coded

diversity


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Smart Antennas in MobileCommunications on the Globe

Radio Design AB(SW)

NMT-450

TSUNAMI-SUNBEAM-

SATURN/METRA Projects (EU)- Wide range of R&D activity

- Recommendations for standardization

- Field Trials GSM/DCS 1800 system

Coordinator ERA Technology(UK)

Participants:Motorola European Cellular Infrastructure Division UK

France Telecom CNET France

University of Aalborg Denmark

Bosch Telecom GmbH Germany

Orange Personal Communication Systems Ltd. UK

DETyCOM Spain

University of Bristol UKPolytechnic University of Catalonia Spain

ArrayComm (USA)

- installations in WLL

- tests for GSM 1800

Metawave(USA)

Commercially available

IntelliCell

Switched Beam System

ARPA (USA )/GloMo project

Raytheon(USA)

Commercially available Fully

Adaptive Smart Antenna System

Ericsson (SW) first system

system solution with SA GSM

(commercially available)

IntelliWave Wireless Local Loop System

NTT DoCoMo

(Japan)

Testbed for UTRA

GigabitWireless(USA)

WLL

UMTS ?


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Improvements achievable with spatial

processing techniques

- Improvement in SNR due to beamforming/combiningarray gain. (Improved coverage. )

- Reduced ISI.

- Enhanced spatial diversity. Path diversity.

- Interference cancellation. In Trx. and Rx. Capacity.

=> Improved transmission rate with link adaptationtechniques.

These goals may be conflicting. Need balancing to achievesynergy with propagation environment, offered traffic,infrastructure !


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- Sectorization

- Macro-diversity with:* Combining (MRC,IRC,OC)

* Prefiltering/Coding(Trx. Coding, V-BLAST,...)

- Beamforming (BF)Switched-beam Smart AntennaAdaptive beamforming

These approaches can be/shouldbe applied together !

Spatial Processing Approaches

Macro-diversity

Switched-beam ant. Adaptive BF

Sectorization


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SNR CCI Diversity ISI Time domain diversity

Improved SNR

BS MS

Beamforming

~1/M

Combining. MRC

Co-phased signals

weighted proportionally

to noise level/antenna

=

Spatial domain Signal Domain


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Improved SNR due to SA antenna gain.

- Gain=10 log M (M-number of

antenna elements)

- directional BF or switched BF canadd 10-12 dB to link budget

- can be controlled dynamically

- Multi-path => diversity combiningand/or matched beamforming.More complex algorithms.

- BF + combining techniques

BF

BF

Combiner

System level improvements=>

- increased coverage

- possible reduction amount of BS

- Penetration into buildings....


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Improvements in system performance with SA

Reduction of the number

of BS sites with HSR

Number of elements0 5 10 15 20

0.9

0.8

0.6

0.4

0.2

3.0

2.5

2.0

1.5

1.0

0.5

Range extension with HSR

HSR


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Improved - diversity (space,path)

Multi-path

BS

MS

Beamforming

.Path. Div.

Combining

Space Div.

~M M

SNR


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Improved - diversity (space,path)

- Spatial diversity combining techniques:

Selection diversity, equal gain combining,Maximum Ratio (MRC),...

- Spatial diversity requires 10 - 20 wavelength

interelement spacing

- Path diversity. Paths identification problem.

- Combinations with other diversity techniques.

polarization, frequency,..modulation diversity

in multicast transmission

BF

BF

Combiner

SNR

CombinerSystem level improvements=>

- More reliable communication

- Higher Bit Rate

- Reduced power consumption for PC systems


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Co-Channel Interference (CCI)

Cancellation

BS

MS 1

Interfering

MS 2

Beamforming Combining

M-1

M-1 interferers cancellation.

independent of the propagation

environment


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Co-Channel Interference (CCI) Cancellation

- might improve capacity in 3- 8 times

- might require more complex algorithms inmultipath

- Combinations with other interference

cancellation techniques:

* Multi-user detection (knowledge of other

users waveforms, adaptive)

* Power control

* Error correction coding

* Temporal domain interference cancellation is

limited (oversampling)v

* network control based techniques

- IC is more important in cellular networks (GSM,3GPP)

BFMUD

System level improvements=>

- higher spectrum efficiency/capacity

- can be translated to higher BER due to higher SIR or with more ch.

- antijamming possibilities


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ISI cancellation

Delayed

Signals

Combining

Multipath

BS

Path with ISI

Beamforming

M-1M-1 delayed signals cancellation

(M-1)/2 symbols due to delay spread


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System performance improvement with SA

0 5 10 15 20

10.0

8.0

6.0

4.0

2.0

0.0

Number of elements

Spectrum efficiency gain of SFIR

Efficiencygain

- 25% load, optimized

--- 50% load , optimized

SFIR

0 5 10 15 20

25

20

15

10

5

0.0

Number of elements

Spectrum efficiency gain of SDMA

Efficiencygain

SDMA

- N= M-1

- N= M/2

.-..-.. N=4

M -number of array elements

N - number of parallel beams


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ISI cancellation

- spatial domain - only interference

cancellation is possible

- preferably to combine with temporal

domain techniques

(preserves signal energy, diversity,more

efficient)

- decoupled/joint space time processing

- ZF, MMSE, MLSE joint/decoupled S-T

equalizers

BF

wEqualizer

ZF,MMSE,

MLSEBF

w

S-T Equalizer

ZF,MMSE,

MLSESystem level improvements=>

- Higher BER

- Improved reliability

- Improved performance in Multipath


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Optimal Spatial Algorithms

BS

MS 1

Multi-path

Interfering

MS 2

Path with ISI,

uncorrelated paths

BeamformingDelayed

Signals

Combining


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Optimal S-T Algorithms

BS

MS 1

Multi-path

Interfering

MS 2

Path with ISI,

uncorrelated paths

Beamforming

Delayed

Signals

Combining

Delayed

Signals

Time

+

Spatial domain processing Temporal domain processing

Equalisation


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SNR CCI Diversity ISI

Optimum Combining

~1/M (M-1) ~M ang. div (M-1)

Optimum BF

(M-1) M spat div. (M-1)/2

interferers gain del. symb.

- Number of SA elements (M)

can be considered as a

resource, i.e. degrees of

freedom which can be spentfor SNR, CCI, diversity, ISI,

either separately or jointly

(optimum)

- M determines spatial selectivity of SA

=> Integrated transceiver design

Degrees of freedom number of SA element


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ST processing. Optimization Criteria.

- Based on cost function maximization/minimization(max SINR,)-> difficult to obtain in practice

- Based on Statistical Estimation. MAP.

ML (Likelihood function)-> treats interference astemporally and spatially white Gaussian. Balanceeffect of noise. Complexity.

MSE -> more attractive in presence of correlatedCCI. ZF force could not balance effect of noise.MMSE partly solves this problem. Algorithmscomplexity spectrum efficiency. Blind methods.

S ti l l d S T T h i Cl ifi ti


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Spatial -only and S-T Techniques. Classification

by Reference Type- Spatial reference based BF-direction of arrival

based beamforming (DoABF)Spatial Eigenstructure based BF

- Reference signal based/time reference BF

(TRB) and/or optimum combining (OC) ,MMSE in BF and channel est. S-T processing

- Signal structure (temporal /spectral) based

beamforming, SSBF/property restored BFblind methods , MSE-like BF and ch. est in STP

- Blind - Decision Directed (DD) techniques

Di i f A i l B d B f (D ABF )


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Direction of Arrival Based Beamformers (DoABF )

- require angle of arrival (AoA)

estimation

- estimates output power at the

output or input correlation matrix

- sensitive to AoA estimation

errors, calibration problem

- problem with coherent multipath

- Angular spread to

array resolution ratio should be

low

- FDD applications

- some methods of AoA estimation

might be problematic in CDMA

Array

Processor

Array

Output


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Time-Reference Signal Based Beamformers and/or

optimal combiner (TRB)

- requires reference signal or the replicacorrelated with desired signal

- reference signal multiplexed withdesired signal or reconstructedfrom detected symbols

- better for varying radio channel

- provide diversity

- may be more processing extensive

- receiver is simpler at expense spectralefficiency

- synchronization problem

- Delay spread (Ds) to frame length (T)ratio should be low

- TDD applications

LS Beamformer

W1

W2

Wn

+

Array

output

Error- +

Ref.

y(t)

X1(t)

X2(t)

Xn(t)

Controlalgorithm

Signal processor

1

2

N

Adaptive processor


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Signal Structure Based Beamforming

(SSBF). Blind BF techniques.- Does not require reference signal,

thus increase spectral efficiency- constant modulus (CM)property of

phase modulated signals,- finite alphabet (FA) property of

digitally modulated signals ,- spectral coherence restoral SCORE

(only information needed - bit rate)

- useful method for trackingbetween references intervals

- convergence properties ?

- methods based on partialinformation are usually non-linear

- performance from robustnesspoint of view similar to reference

signal based methods, DD technique

BF(W)

CMA


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Spatial processing: Summary

DoABF

- better perform in environments with low angular spread- require AoA estimation and calibration- can work in higher Doppler spread- feasible with FDD applications- macrocell environment

TRB or/and OC (Blind Algorithms)- well perform in environments with high angular spread- require reference signal (spectrum efficiency), synchronization- well suit for TDD (micro/pico cells), FDD is more problematicmicro and picocell- temporal structure based algorithms can better handledelay spread, but higher speed can be problem- more robust methods in changing environment (adaptive algorithms)


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MIMO systems with SA at the MS& BS

- Spatial multiplexing=>Data Rate

- Layered Architecture (BLAST)

- ST Coding => Diversity=>BER

- Mutiplexing or Diversity ?

- MN

- Sub-arraying

- MIMO CDMA with SA

- Iterated receiver design

or

M N

Spatial multiplexing

ST Coding

MIMO techniques different propagation


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MSC

BSBS

WLL

LOS

MSC

BS

multiple antennas at MS

NLOS

MIMO techniques different propagation

environment

Urban area

Rural area

P ibl bi ti f ti l i


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Possible combinations of spatial processing

with other techniques

Time domain processing(Equalization, RAKE, )

Diversity (polarization,

additional macro,..)

Channel and ST coding

MU detection

Link adaptation

Spatial processing &


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Integrated Receiver Design with SA

- Integrated Temporal Spatial

Frequency domains receiver

- More coupled with detection (DD,

Joint Channel est.)

- Integrated with MUD/IC

- Integrated with coding

Radio Channel

Time

Doppler Spatial

Factors to be considered in SA


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Factors to be considered in SA

system integration

A. Environment

- propagation environment=> spreading in space-time, fading

- interference environment

- mobility

B. System parameters/air interface type

C. Operator requirements/services requirements

SA Integration into Cellular Networks


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SA Integration into Cellular Networks

Smart Ant. Tech.

Network Planning

- Capacity, coverage, interference

planning

- Joint fixed and radio network

optimization, planning

- System upgrade, economical issues

Network control- R.resource management

- call control

Radio Interface

Receiver structure,Tx, Rx algorithms

- Spatial proc.- Time domain proc.

- Coding

- Detection

- Diversity- ..

Air Interface- Multiple access

- Duplexing

- Modulation

- Framing- Availability of pilots

DSP

tech.

SW

Radio

Radio Network

Management

Link level control- Power Control

- Quality Control

- Tracking

Cell control- admission control

- broadcast channel control- handover control

- macro-diversity control

Services -> MS location

3G

2.5G

2G1G

1G- analog systems

2G- digital systems

2.5G- digital+packet +.. (GPRS,.

3G - W-CDMA4G- cellular+ gigabit WLAN

4G

Macrocell and Microcell Channel Response


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After A.Paulraj

Macrocell and Microcell Channel Response

MicrocellMacrocell

Delay (microsec)0 1 0 20

-1800

1800

1800

Delay (microsec)

Remotescatters

Scatters

local to

BS

Scatters

local toMS

- Smart Antennas algorithms should be optimized according to

the propagation environment based on the cell by cell principle

Spatial Processing: Integration with Air


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Spatial Processing:Integration with Air

Interface

Mapping

control,

trafficchannels

Physical

Channel

Definition,

Multi-

plexing

Frame

Structure

Duplexing

Technology

RF- Channel

parameters

Multiple

Access

Technology

Channel

CodingSource

Coding

Internetworking

Modulation

Technology

FDMA

CDMA

FDD

TDD

Availabilityof the trainingsignal

Frame length- T

Modulation typeCM...Finite Alphabet

Linearity

Combination

with Space

Processing

Bandwidth-B

Carrier

frequency fo

Antennas elements geometry,

numbers of elements - M.

Radio Transmission Technologies

UL->DL

link

Wide/narrow

band SA rec,

BF, AoA est

Blind

methods

SSBF, ST

MS

Ref.

Signal

based

BF, S-T

CDMA SA R i


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- In non-multiuser case users are seen as interference to each

other and there are many weaker CCI in the uplink. Capacityis improved due to reduction of TRX power

- Multipath gives rise to the MAI due to the losses of codesorthogonality. Can be improved with SA.

- Code can be seen as a free reference signal

- Wideband beamforming realization and methods of AoAestimation are different from narrowband

- Channel estimations can be based on spreading codes andit presumes introduction of novel techniques

- Narrowband systems are more feasible with SA.....(coherence nature of array processing)

CDMA SA Receivers

S ti l i S


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- M degrees of freedom should be carefully spent according to the

expected propagation and interference environment taking into

consideration availability of other techniques(interference

cancellation,diversity,..)

- Environment (spreading) complexity receiver and

algorithmic complexity

(How modelling in algorithms corresponds to reality ?)

S ti l i S


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Best solutions: Combine trade-offs between:

- Beamforming combining- Algorithms (ML MSE) , subspace- Optimum Data independent approaches- Base band beamforming RF/or IF beamforming

- Combination with other methods like multi-userdetection (MUD), diversity, ST coding, adaptivemodems

-Air interfaces should be not only friendly for S-Tprocessing but flexible / adaptive to be able to exploitadvantages of spatial processing in variable environments

- Integrated S-T MUD .... transceiver design...

S ti l i S


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Smart Antennas might be not very smart (Complexity)

Integrated but relatively simple system design can provide

considerable improvement with low level of complexity


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Three Stages of Introduction Smart Antennas

in Cell Planning Process of 2-2.5 G Networks

1. High Sensitivity Reception (HSR)

2. Spatial Filtering for Interference Reduction (SFIR)

3. Space Division Multiple Access (SDMA)


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HSR concept

- SA at the up-link only

- Gain approximately 10logM

- with 8 elements reduction of

number of BS by factor of 0.3

only by factor of 0.5 with diversity

- revolving beam technique improve coverage of BCH

BS MS

S


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- CCI cancellation + SA at the down-link

- capacity improvement of 2.5 require 6dB

CIR improvement (already achieved by

Ericsson with simple SA algorithms)

- the same range extension as with HSR

- simulations shows that approximately the

same capacity gain can be achieved with

SFIR and SDMA while SFIR require

considerable less network control upgrade

SFIR concept

SFIR concept


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- it was found reasonable to combine in

GSM SFIR with random slowfrequency hopping to benefit from

interference and frequency diversity

- reuse factor 1/3 seems reasonable

1/1 possible but too complex since

dynamic RR management based on

CCI measurements is required

- frequency re-planning, but network control (RR) less affected

SFIR concept

SDMA concept


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SDMA concept

- expected up to 8 times capacity improvement

- power classes concept (can be dynamicor static)

- with ref. signal BF MSs can beseparated even when they have the

same angular position to BS !

- for DoABF MSs angular distributionis important (macrocell)

- network planning (frequency) is simpler,

but larger cell size can require new planning,more smooth migration into existing network

- more network management upgrade required

PCH 1 PCH 1

PCH 1PCH 1

Impact on the network control


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Impact on the network control

U C

Service

layer

Layer 3

Layer 2

Layer 1

RR managementinterference averaging

DCA...,

combined with user specific info

(color codes, AoAs )

Geolocation based on

AoA estimation

Reference signal availability

Multiple Access , Duplexing ,PN, DTX.

Initial access , HO control

Broadcast channels control

*

*

**

*

*

*

*

Layer 1 Power control Quality


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Layer 1. Power control. Quality

monitoring. Tracking.- power control at up and down links is beneficial

(60% more capacity ) (Downlink in SDMA can be problematicdue to furthest mobile)

- dynamic behavior of tracking & power control ?

- user identification problem to support SDMAindividual color codes needed to support each SDMAtraffic channel channel, also for admission control ..

- for rescue purposes omni directional channel for call recovery

is proposed

- power classes concept (SDMA, others ..? )< -->RR

management( tradeoff needed to avoid trunking effects)

Layer 2 Initial access Handover


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Layer 2. Initial access. Handover.- location aware HO or throughomni-directional channel ?

- initial access with omni directionalchannel=> narrow beam ortransition wide beam =>narrow beam

- to setup beamformer just beforeuser dedicated channel is allocated

(access procedure modification orincreased access time )

- delayed handover while new BS has not been localized

- how to make down-link BF when channel info. at the up-link is notavailable yet (temporal omnidirectional downlink or longer access)?

- to allow different synchronization sequences

- packet capturing by SA can improve packet transmission viarandom access channel

BS BS BS

Initial access

t

Layer 3 Resource management


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Layer 3. Resource management.

- new functions: physical channel allocation based on angularinformation and or link quality monitoring

- dynamic channel allocation (DCA)(localization with different precision... ?? needed)

=> precise localization - centralized DCA or=> no DCA with SFIR and interference averaging approach or=> subdivision on sectors and create list of forbidden sectors

- joint power control , beamforming and BS assignment

- centralized or distributed control (bunch concept) ?

- smoothing of spatial traffic distribution

- more benefit we expect to get (capacity,flexibility)- more RRmanagement should be aware of spatial characteristics

Broadcast channels control with SA


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Broadcast channels control with SA

- Coveragerevolving beam concept in TDMA

(more feasible for coverage extension)neighboring cell monitoring can bemore problematic . Frame structure...

- Adaptation to traffic variationsTraffic control cell coverage by reshapingtransmitted antenna pattern(sectorized and non-sectorized)

- Network Planningneed to split carefully beamformed

and omni-directional channels ..

N k C l i h SA Hi h l


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Network Control with SA. Higher layers.

Geolocation.

New service (991, transport control)

Combined DOA measurements and time delay based

approach

Raytheon introduced commercial available geolocationsystem (SA option is included)

N t k i S


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Network issues. Summary

- More benefits with SA- > more :

Resource management should be aware of:

- > User location (AoA,..)and/or

- > Power (power classes ,...)and/or

- > Channel quality (and spatial properties ?)

Co-ordination between BSs

-> at least loose form of synchronization for time reference BF

(Layer 1)

-> exchange information about user location and /or- > channel quality (and spatial properties ?)

-> exchange information about cells traffic load

Network issues > Standardization


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Network issues => Standardization- It is need to incorporate more user dedicated information into

channels (user dedicated pilots, color codes, different

synchronization sequences) to separate/identify users(implemented in new air interfaces cdma- 2000,UTRA)

- Channels structure should be more carefully divided betweenbeamformed and omnidierctional.Minimize blanket coverage in terms of frequency/time

- DTX(comfort level?), HO, initial protocol perhaps should beslightly modified,but it can increase signaling overhead=>more interference in CDMA

- combination with link adaptation (since at the beginningchannel history is not available). This combination willincrease soft capacity limit

- some changes can be expected at the MS (receiver, ant., protocols)

Achievable improvements with SA in the


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pexisting and future cellular networks.

PMR ?

SA S t I t ti R h t


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SA System Integration Research at

ComLab/HUT

- Integrated receiver design with SA

- MIMO system (CDMA/3G)

- Joint Spatial Domain Processing =>....

- Advanced Simulation Tool Development.

Parallel Computing- Programming

SystemSignal Level Simulation.

3S Simulator (Signal, System, Services)

Smart Antennas Model


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MS2

Two Users LOS propagation scenario

Center of Helsinki

BS

MS1

0180

-75 dB

-85 dB

-80 dB

30

60120

160

210

240

270

300

330

- incoming impulses from the

MS1 - amplitude and AOA

- Smart Antennas radiation

pattern antenna main lobe

locked on the signals coming

from MS1

- incoming impulses from

the MS2 - amplitude and AOA,

considered as interference

for MS1 (and vs)

300

250

200

150

250

100

50

00 50 100 150 200

250 300

basis X-coordinate

Smart Antennas Model


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PMR-SA. New research Problems.

- Basic research on applicability/optimization of SA techniques

taking into consideration TETRA system

- Performance with different SA techniques and receivers

structures. Coverage, BER,..

- Achievable improvement with SA and link adaptation techniques

- Transceiver complexity study

- Performance in multi-service environment(simulation)

- SA at the MS/vehicle as a relaying platform

Publications


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Publications1.Edward Mutafungwa, Lauri Halme, Viktor Nssi, Adrian BoukalovA study of the Jrvenp-Lahti motorway's IT linkalternatives for the connection of control stations, Espoo, Otaniemi: TKK Tietoliikennelaboratorio technology reports, 1998.

2. Adrian Boukalov "The impact of a non-uniform spatial traffic distribution on the CDMA cellular networks systemparameters", URSI/Remote Sensing Club of Finland/IEEE XXIII Convention on Radio Science and Remote SensingSymposium, Otaniemi 24-25 August, 1998, Helsinki University of Technology Laboratory of Space tech. Report 35, p.29-30

3. Boukalov Adrian, Sven-Gustav Hggman and Antti Pietil "The Impact of a Non-uniform Spatial Traffic Distribution onthe CDMA Cellular Network System Parameters", ICPWC'99, Jaipur, India, February 1999, pp. 394 -398.

4. Boukalov Adrian, Sven-Gustav Hggman "UMTS Radio Network Simulation with Smart Antennas ", Proceedings of theVirginia Tech Symposium on Wireless Personal Communications, June 2-4, 1999, Blacksburg , USA , pp. 95-102.

5. Boukalov Adrian, "System Aspects of Smart Antennas Technology" Presentation at Radio Communication SystemsDepartment / School of Electrical Engineering and Information Technology (EIT) at the Royal Institute of Technology (KTH),

Stockholm, Sweden. Available at: http://www.s3.kth.se/radio/seminars/sa.pdf.6. Boukalov Adrian, Sven-Gustav Hggman "An overview. System aspects of Smart Antennas Technology in WirelessCommunications" (Invited) , Proceedings of the 11th International Conference on Wireless Communications vol. 2,12-14 July 1999 Calgary , Canada, pp.1-14.

7.Boukalov Adrian, Sven-Gustav Hggman " UMTS Radio Network Simulation with Smart Antennas" to be published inbook Wireless Personal Communications, Kluwer Academic Publishers, 2000.8. Boukalov Adrian, Sven-Gustav Hggman "System Aspects of Smart Antennas Technology in Cellular WirelessCommunications " (Invited) IEEE Radio and Wireless Conference (RAWCON 99), Denver, Colorado, USA,August 1-4, 1999, pp. 17-22.

9.Boukalov Adrian, "Introduction to Smart Antennas Techniques and Algorithms" Workshop on Smart AntennasTechnology and Applications at RAWCON 99, 1st August 1999.

10. Boukalov Adrian, Sven-Gustav Hggman System Aspects of Smart Antennas Technology in Wireless Communications to appear in Journal IEEE Transaction in Microwave Theory and Techniques

11. Boukalov Adrian,Integration of Smart Antennas into Wireless Network (Invited paper), book Global WirelessCommunications for World. Markets Research Centre's Business Briefing Series. Wireless Technology 2000.

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SC03_10r1 Smart Antenna

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