A collision detection method for multicast transmissions in CSMA/CA networks

WIRELESS COMMUNICATIONS AND MOBILE COMPUTINGWirel. Commun. Mob. Comput. 2007; 7:795–808Published online 7 July 2006 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/wcm.421

A collision detection method for multicast transmissions inCSMA/CA networks

Thomas Nilsson*,†, Greger Wikstrand and Jerry Eriksson

Department of Computing Science, Umea University, SE-901 87 Umea, Sweden

Summary

Compared to unicast traffic, multicast is not protected by any ARQ mechanism in 802.11 networks: collisions withother multicast and unicast transmissions are not detected and senders will not adapt to the contention situation bybacking off. This results in an unreliable service for multicast transmissions.

We propose early multicast collision detection (EMCD), an algorithm with the purpose of increasing the reliabilityof multicast transmissions in the MAC layer of an IEEE 802.11 network. A multicast sender using it will introducean early pause in a transmission, perform a clear channel assessment (CCA), and if a collision is detected abortthe transmission after a fixed time and schedule a retransmission. This allows for detecting collisions with bothmulticast and unicast transmissions but also adapting to the contention situation.

A probabilistic analysis is provided showing that EMCD is more efficient than ordinary multicast and can bemade even more efficient by tuning parameters.

Simulations show that EMCD leads to increased reliability for multicast transmissions. Copyright © 2006John Wiley & Sons, Ltd.

KEY WORDS: quality of service; CSMA/CA; medium access control; 802.11; collision detection; reliable multi-cast; performance evaluation

1. Introduction

It is difficult to provide the same kind of reliable servicefor multicast traffic in an IEEE 802.11 network as forunicast traffic [1, p. 29]. In an IEEE 802.11 network,unicast traffic is protected in three ways: (1) by an auto-matic repeat request protocol (ARQ), (2) by backing-off more in case of congestion, and (3) by adaptingthe link. These, or other reliability-enhancing mech-anisms, are not available for multicast traffic. ARQis problematic because of the ACK-implosion prob-lem, that is multiple stations will send an ACK. With-

*Correspondence to: Thomas Nilsson, Department of Computing Science, Umea University, SE-901 87 Umea, Sweden.†E-mail: [email protected]

out ARQ, the back-off mechanism cannot be appliedafter a collision. Link adaptation is based on frame er-ror rate, which is not available for the same reason.Thus, such packets are more likely to be lost.

One further reason for multicast packet loss is colli-sions between access points (AP) in overlapping cellson the same channel and in the same extended serviceset (ESS). Any multicast stream must be transmitted byeach access point in an ESS [1, p. 83] leading to a riskfor synchronized and therefore colliding traffic. Also,stations are explicitly forbidden to eavesdrop on accesspoints with which they are not associated [1, p. 44] thus

Copyright © 2006 John Wiley & Sons, Ltd.

796 T. NILSSON, G. WIKSTRAND AND J. ERIKSSON

making it less efficient to use channel-reservation tech-niques. A configuration like that can be conceived, forexample, in an arena or an exhibition hall with freespace propagation where a large numbers of accesspoints have been distributed to maximize coverage andassociation capacity.

This work was done in the context of the Arenaproject (http://www.cdt.luth.se/projects/arena/). At asport event, spectators were provided with an interac-tive match program in wireless terminals. Among thefeatures of the application were the ability to playbacklive video and personalized replays in the phones. Theefficient way to reach the crowds in such a contextwould be to use multicast for the multimedia informa-tion. In the case of multicast multimedia this will re-quire minimizing packet losses to provide smooth play-back and minimizing or bounding delays so that play-back does not lag too far behind the live event. In par-ticular, the system must be robust against unicast inter-ference as there will be no way to restrict such traffic onan unlicensed frequency band. We expect spectators tobring their own equipment from home, so any solutionbased on changes to their equipment is hardly feasible.

For clarity, we provide the following definition ofmedium access control (MAC)-layer multicast. It isbased on the definition given by Sun et al. [2] butadds the requirement of simultaneity. Thus, we do notconsider the process in which a station transmits thesame multicast packet to several stations by sending itrepeatedly, once for each recipient as multicast.

Definition 1. Multicast is the process in which a sta-tion simultaneously transmits the same data packetto some of its neighbors. A multicast transmission isa transmission from one sender, the AP in an IEEE802.11 infrastructured network, to a group of zero ormore recipients. Each multicast group has a specialMAC-address recognized by its members.

Improving the reliability of multicast traffic is im-portant since multicast traffic, for example streamingvideo, reaches at least as many users as unicast traf-fic. Thus, poor reliability for multicast traffic can beexpected to have a higher negative impact on user sat-isfaction than the converse case for unicast traffic.

Not all multicast traffic has the same semantics.Sometimes it is important that all recipients receiveall frames in a timely and orderly fashion and thatthe sender knows that they have done so, for exampleconfiguration and control. In our scenario, it is suffi-cient that most recipients receive most of the packets.Streaming video can tolerate and compensate for dataloss in several different ways.

An algorithm, which would enable collision detec-tion for multicast frames, was introduced in 1984 byLo and Mouftah [3,4] under the name time split col-lision detection or CSMA/TCD and again in 1986 byRom [5]. We call it the ‘the Rom Algorithm’. It is thepurpose of this paper to reevaluate their algorithm(s)in terms of their suitability for solving the problemsoutlined above. We investigate the efficiency of themodified algorithm and the possibility of using it inan IEEE 802.11 network.

The rest of this paper is organized as follows. InSection 2 some other collision detection and avoidancetechniques are described and categorized. In Section 3our modified Rom Algorithm, called early multicastcollision detection (EMCD), is described along withthe modifications required for applying it to an IEEE802.11a network. We argue for relevant parameters touse and describe various collision scenarios. EMCDwas evaluated through probabilistic analysis and sim-ulations. The analysis is presented in Section 4 and thesimulation results are presented in Section 5. Section 6contains our conclusions.

2. Related Work

Much work has been done in the area of channel reser-vation and collision resolution in MAC protocols forunicast traffic, for example, References [6–8]. Thesesolutions are not directly applicable to multicast traf-fic where multiple receivers are addressed and normalARQ is not feasible. Below, we review some that havebeen developed for multicast. Basically, the problemwith lost multicast traffic can be resolved in two ways:avoiding or detecting packet loss.

2.1. Channel Reservation and CollisionDetection in IEEE 802.11

The MAC scheme used in the IEEE 802.11 standard iscalled the distributed coordination function (DCF). It isa distributed contention-based access method based onthe carrier sense multiple access with collision avoid-ance (CSMA/CA) algorithm. Carrier sensing, knownas clear channel assessment (CCA) in IEEE 802.11,is used to determine the status of the medium prior toattempting to access the channel. If the channel is de-termined to be busy or after a collision a station choosesa back-off counter (time to wait until retransmission)randomly from a contention window (CW), which isdoubled after each unsuccessful attempt. The back-offcounter is decremented by one for each time slot themedium is idle, and as soon as the medium becomes

Copyright © 2006 John Wiley & Sons, Ltd. Wirel. Commun. Mob. Comput. 2007; 7:795–808

A COLLISION DETECTION METHOD FOR MULTICAST IN CSMA/CA 797

busy the countdown is postponed until the medium hasbeen idle during a DIFS.

Subsequent frame transmissions are separated byshort time gaps on the channel called inter frame spaces(IFS), used to differentiate control and data frames. TheShort IFS (SIFS) is used when a station have seizedthe medium and need to keep it for the completion ofa frame exchange sequence, for example between thedata frame and the corresponding ACK frame. Dataframes are separated by a DCF IFS (DIFS) which islonger than a SIFS.

There is an additional inter frame space called ex-tended inter frame space (EIFS) used by a receivingstation to defer access to the channel after an unsuc-cessful reception of a packet. The EIFS is intended toprovide sufficient time for another station, that did ex-perience a correct reception of the frame, to transmitan ACK to the sender. As a result of this, the lengthof the EIFS is much longer than other inter framespaces.

An optional way of accessing the channel, by anexchange of control frames prior to the data transmis-sion, is included in DCF. The sender starts by sendinga request to send (RTS) and the receiver responds witha clear to send (CTS), after first waiting a SIFS. Thechannel is then reserved and the pending data framemay be sent free of collisions. These control framescontain the duration of the complete frame exchangesequence which allows other stations, in range of thesender or the receiver or both, to defer access duringthe completion of the frame exchange sequence. Thestations only in range of the receiver are referred to ashidden terminals (hidden from the sender).

2.2. Collision Avoidance Techniques

With the exception of Blackburst [9], channel reserva-tion techniques for wireless MAC-layer multicast inIEEE 802.11 or other CSMA/CA protocols that wehave found in the literature are based on variations onthe RTS/CTS scheme described above. The main dif-ference between the proposed methods is the numberof stations which respond with a CTS, one station orall stations.

In the techniques with one CTS responder, it caneither be a fixed and designated responder as in RobustMulticast [10], or the stations can take turns in a round-robin fashion as in BMW [11]. In the latter method,the CTS station will also piggy-back information onwhich frames it has received earlier. The first methodsuffers from the fact that the designated station mightnot be representative. The second solution might lead

to frames being retransmitted after a long time if theround-robin queue is long.

In the techniques where all stations respond in turnthe responses can either be sequential or simultaneous.In one method, all recipients send a CTS in an orderdetermined by the multicast sender and announced inthe RTS packet [2]. This method obviously has a largeoverhead and will scale poorly. In another scheme, eachstation waits a random interval in case someone elseresponds before sending their own CTS [12]. If theinterval is too long (≥DIFS) the stations will not havetime to respond before other transmissions start. If it istoo short it becomes very probable that several stationstransmit at once.

Two methods where all stations send their CTS atthe same time have been proposed to enable the mul-ticast sender to decode the transmissions. In one case,the strongest (closest) sender is assumed to be suffi-ciently stronger than all other senders together so thatthe multicast sender can decode the CTS [13]. Othersargue that this is highly unlikely and instead proposeusing linearly independent codes for each sender lettingthe recipient decode all of them simultaneously [14].This solution might require extensive changes in thephysical layer.

A hybrid method has been proposed where a desig-nated station sends the CTS but where stations who donot ‘agree’ will send a ‘negative’ CTS (NCTS) in orderto cancel out the CTS [12]. This solution requires thatall stations agree.

2.3. Collision Detection Techniques

Collision detection techniques can be further subdi-vided into intransmission carrier sensing and ARQ ap-proaches.

Kuri and Kasera [12] also proposed an analog hybridscheme for ARQ. In it, a designated station transmitsan ACK and any station which has not received themulticast frame but detects the ACK will transmit a‘negative’ ACK (NAK) to collide with the ACK. Thisapproach requires all stations to receive a given multi-cast packet correctly or not at all, that is, this approachdoes not tolerate any packet degradation in marginalstations. A large number of multicast receivers withvarying channel qualities will deteriorate the perfor-mance of this approach since it is enough that one re-ceiver experiences a packet loss for a retransmission tobe triggered.

Sheu et al. [15] proposed a highly reliable broad-cast scheme for ad hoc networks [15]. They mod-ify the 802.11 MAC scheme to incorporate broadcast



acknowledgments by dividing the DIFS time, follow-ing a broadcast transmission, into several mini-slotsand require each station to contend for transmittingshort acknowledgment frames. This ARQ approachdoes not scale to the number of multicast receivers andis limited by DIFS.

3. Early Multicast Collision Detection

We have adopted the algorithm proposed by Rom [5]for the purpose of detecting collisions experienced bymulticast senders in an IEEE 802.11 network and thusenabling retransmissions of lost packets. This will in-crease the reliability for the otherwise unprotected mul-ticast traffic but also minimize the overhead associatedwith collisions.

The Rom algorithm differs from non-persistentCSMA in its ability to detect collisions during the trans-mission. The main difference from CSMA is that asender transmitting a packet pauses during the trans-mission and performs an additional carrier sense op-eration to detect other potential transmitters. A senderdetecting a collision does not abort the transmissionimmediately but continues for a predetermined period,referred to as the collision detection interval (CDI), toassure that a later scheduled pause does not miss thecollision. If the channel is sensed idle during the CDIthe transmission continues as normal.

Lo and Mouftah [4] and Rom [5] have proposed sim-ilar algorithms for collision detection for the CSMAfamily of protocols. Using the categories in Section 2,these algorithms and EMCD are collision detectiontechniques. The work presented by Rom [5] is a moreelaborate algorithm in the sense that the pausing subinterval is chosen from a uniform distribution, whereasLo and Mouftah assume a non-slotted CSMA with thesame pausing sub interval for all senders.

Algorithm 1 Early Multicast Collision Detectionsuccess = false, bo = 0, retries = 0while ¬ success AND retries≤ Rmax do

Perform backoff/collision avoidancePerform Vanguard Transmission Tv, duration from (3.1.2)if CCA() = busy then

retries=retries+1jam until end of CDIbo ∈ U {0, CWmin}

elsePerform main transmission Tmsuccess=true

end ifend while

Table I. Glossary.

ρ channel utilizationl contention window sizek number of stationsn number of slotsτ probability for a station to have bo = 0bo current back-off of a stationp(i, k, l) probability that i stations finish back-off simultaneouslyw(r, i) probability that i stations back-off simultaneously in the

r:th attemptP(r, i) probability of i contending stations in the r:th attemptE[U] expected useful timeE[B] expected busy timeE[I] expected idle timeCWmin minimum back-off window sizeTCDI duration of the collission detection intervalTm duration of main transmissionTmin duration of shortest possible transmissionTs duration of a successful transmissionTCND duration of an unsuccesful transmissionTv duration of vanguard transmissionT� smallest detectable time differenceCCA clear channel assessmentCIFS collision inter frame spaceSIFS short inter frame spaceDIFS DCF inter frame spaceEIFS extended inter frame space

3.1. Protocol Description

EMCD operates in three phases, see Algorithm 1. (Aglossary of our notation is provided in Table I.) Thefirst phase is the vanguard transmission, the secondphase is the carrier sensing phase, and the third phase isthe main or jamming transmission. Since stations cantransmit data at varying rates, frames of the same sizemay require different transmission durations. For thisreason, EMCD is based on timing intervals rather thanpacket size. This is different from the Rom algorithmwhich implicitly assumes a fixed transmission rate forall transmitters [5].

We have chosen not to double the contention windowfor EMCD stations in order to prioritize the multicasttraffic carried in the downlink. This is motivated bythe unbalanced contention between up and downlinkreported by Pilsof et al. [16]. The access point, alonecontends for all the downlink traffic, whereas each sta-tion individually contends for its uplink traffic. Thisresults in an unbalanced contention since the accesspoint have no higher priority than a normal station inaccessing the channel. Hence, unicast stations contend-ing for the uplink can easily starve the downlink trafficunder high load. Under saturated conditions with a totalof N contending senders including the access point, theaccess point will only recieve 1/N of the total capacity,that is, the same as all the other stations.



The retransmission mechanism used in IEEE 802.11uses a short and long retry limit for short control pack-ets (CTS and RTS) and longer data packets, respec-tively. Recommended values are four for data packetsand seven for control packets [1]. The retransmissionstrategy is important to multimedia applications, thatare more sensitive to delay and jitter. Retransmitting adata packet carrying video information may not makesense if the play out deadline has passed. There is aclear trade-off between tolerance to packet losses anddelay. We are assuming a lower retransmission limit(Rmax) for multicast packet to minimize delays, seeSection 5. Furthermore, as mentioned earlier EMCDis not doubling the contention window to prioritize themulticast traffic, this will give the multicast sendershigher capacity and lower delays.

3.1.1. Collision detection interval

The length of the CDI, that is TCDI, affects the perfor-mance of EMCD in three ways. First, TCDI determinesthe maximum number of unique transmission timesthat are selectable by the multicast senders. If the CDIis very short there will only be a few unique trans-mission times and hence the probability for derivingthe same transmission time will be greater. Second,TCDI has an effect on the detection probability forcollisions with unicast senders. If the derived vanguardtransmission is longer than the unicast transmission,the multicast sender will not detect the collision. Third,a long detection period will add additional delay andmore overhead to the retransmission, mainly becausethe collision is detected later.

So the CDI should be as short as possible to detecta majority of the unicast transmissions, but still largeenough to yield several unique transmission times.

A static solution might be envisaged where everymulticast sender would be assigned a Tv,i �= Tv,j forany stations i �= j to be used for every vanguard trans-mission; no collisions would go undetected. However, astatic solution would require configuration of the mul-ticast senders, which is contrary to the basic idea ofdecentralization in IEEE 802.11. It will not be consid-ered in this paper.

3.1.2. Duration of the vanguard transmission

The duration of the vanguard transmission is derivedfrom the expressions below:

Tv = Tmin + XT�

X ∈ U{

0,TCDI−Tmin

T�

}(1)

Fig. 1. Different Tv generated by three senders.

Tmin is the minimum allowed or possible transmissiontime. T� is the smallest time difference that can bedetected between two vanguard transmission from dif-ferent senders by the CCA and TCDI is the maximumduration of the vanguard transmission plus CIFS (seebelow). Figure 1 illustrates how three senders have se-lected different Tv. All EMCD stations in an ESS, thatis, stations including access points that implement anduse EMCD, should use the same value for TCDI.

3.1.3. Duration of the carrier sensing phase

After the vanguard transmission, the station performsa CCA to detect other transmissions, see Algorithm 1.We refer to the interval in which the CCA is performedas the collision inter frame space (CIFS). Selecting ashort CIFS minimizes overhead.

A lower bound on the CIFS is defined by the timerequired to perform a correct CCA (ordinarily < 4 �s[17, pp. 27 & 40]) the signal propagation time, and thetime required to switch from transmitting to receivingand back again, that is the receive/transmit turnaroundtime. The first term is partially hardware dependent,the second term depends of the physical configurationof the arena, and the third term is hardware dependent.

An upper bound on the CIFS is defined by the SIFS,PIFS, and DIFS timing intervals (16, 25, and 34, re-spectively in IEEE 802.11 [1, p. 85] [17, p. 40]). Itmust be shorter than PIFS and DIFS of them to preventother stations from detecting the channel idle, and con-sequently begin their transmissions in between Tv andTm. So, in an 802.11a WLAN the CIFS can be in therange 11 ≤ CIFS ≤ 25.

3.2. Collision Scenarios

Figure 2 illustrates a collision between two multicastsenders (1 and 2) starting their transmissions at thesame time. Sender 2 will detect the collision beforeSender 1, and continue by jamming the medium untilthe end of the CDI to assure that Sender 1 also detectsthe collision. At the end of the CDI they will end theirtransmissions and reschedule the collided packets



Fig. 2. Collision between two multicast senders is detected by EMCD. Retransmissions are scheduled.

according to Algorithm 1. The access point generatingthe shortest back-off time will win the next contentionphase (Sender 2 in Figure 2).

In Figure 3 a multicast sender (1) and a unicast sender(2) start their transmissions simultaneously resultingin a collision. The carrier sense operation performedby station 1 will detect the collision. Station 2 willdetect the collision when it does not receive an ACK.Both stations will back-off before retransmitting theircollided packets. If the packet had been shorter thanTmin the collision would not have been detected.

3.3. Compatibility

It is sufficient to implement EMCD in the multicastsenders. Multicast recipients need no further infor-mation than what is required to reassemble the twoparts of the packet. The multicast senders could makethat process entirely transparent by refragmenting thepacket at a higher protocol level. That would also cir-cumvent the injunctions in the 802.11 standard againstfragmenting multicast packets [1, p. 71] and mak-ing earlier fragments of a packet shorter than laterfragments [1, p. 93].

3.4. Protocol Overhead

The extra carrier sense operation in EMCD imposesan additional overhead on transmissions. In Table IIthe protocol overhead is shown for unicast, multicast,and multicast using EMCD, under the assumption thatthe data payload is 1496 bytes and the rate is 6 Mbps.Note that only the packet overhead is considered in thetable and not the back-off time, DIFS, etc. Multicast

Table II. Protocol overhead in �s for multicast using EMCD,multicast, and unicast. The payload length is 1496 bytes and therate is 6 Mbps.

EMCD Multicast Unicast

Preamble 40 20 20ACK — — 44SIFS — — 16CIFS 11 — —Data 1996 1996 1996Mac header 104 52 52Total �s 2151 2068 2128% 7.2 3.55 6.22

packets are split into two transmissions by the EMCDalgorithm and the overhead per packet is doubled. Theoverhead for EMCD is slightly larger than for unicast.

4. Analytical Evaluation

The Rom algorithm was evaluated analytically in theoriginal paper [5]. The analysis uses an infinite popu-lation of users which as an aggregate form a Poissonarrival process. In general the time to transmit a packetis shorter than the arrival rate so the channel is far fromsaturation [18].

Here it is assumed that there is a finite populationof k stations. Each station operates under saturationconditions, that is, it always has a packet ready fortransmission. We further assume that there are onlyEMCD stations. We also assume that no packets arelost because of noise and that the EIFS mechanismworks perfectly.

Fig. 3. Collision between a multicast and a unicast transmission. Both stations detect it and schedule retransmissions.



The first two assumptions are fairly standard in thistype of analysis, cf. [19]. The following three assump-tions are made for simplicity of analysis, the impact ofbreaking them are considered in the simulation sectionlater.

4.1. Channel Utilization

Consider a transmission cycle consisting of zero ormore unsuccessful transmission attempts followed by asuccessful transmission. The channel utilization ρ willbe the time required for the transmission of useful datain a cycle divided by the length of the cycle. (A glossaryof our notation is provided in Table I.) Let E[U], E[I],and E[B] be the expected useful, idle and busy timesof a cycle then [4,18,19]

ρ = E[U]

E[I] + E[B](2)

E[U] is easily obtained from the average packet lengthm in units of time. The expected idle and busy timesare given in Equations (13) and (11), respectively. Let ndenote the number of slots in the CDI and k the numberof stations.

4.1.1. Single station back-off

Under the assumption of independent back-off betweenstations the back-off of a single station can be describedusing a Markov-chain. By solving for the stationaryprobability distribution it is possible to obtain the prob-ability that a single station has a back-off counter ofzero and will transmit. It was given as τ = 2/(W + 1)by Bianchi [20, Eq. 8], where W is CW+1. We shalluse a slightly different notation l = W − 1, and write

τ(l) = 2

l + 2(3)

4.1.2. Multiple stations back-off

For Bianchi, it was sufficient to determine the proba-bilities that there was a transmission from one stationand if so, if that station was the only one transmitting.In our case we must know how many stations collideto be able to derive the probability that a collision willbe detected.

The probability that i out of k stations have finishedbacking-off at the same time will be given by the bi-nomial distribution with τ(l) as the success probability

and we write

p(i, k, l) ={(

ki

)τ(l)i(1 − τ(l))k−i i ≤ k

0 i > k(4)

4.1.3. Winners' in each step

Recall that the EIFS affects what happens after a colli-sion. Non-colliding stations will defer until a successfultransmission occurs or to the end of the EIFS. Let e bethe length of the EIFS in slots and P(r, i) be the prob-ability that i stations are left before contention phaser begins. First, consider the case where the EIFS islonger than the contention window, that is, e ≥ l, thenthe probability w(r, i) for i ‘winning’ stations is givenby

w(r, i) =k∑

j=1

p(i, j, l)P(r, j)

1 − p(0, j, l)(5)

Under our assumptions we start with k stations in thefirst step. The number of stations left is basically thesame as the number of winning stations in the preced-ing steps except for the following: if there is a singlewinning station in the earlier step then there will be nostations left in the following step and we can write

P(r, 1, . . . , k) ={(0, . . . , 0, 1) r = 1

(0, w(r − 1, 2), . . . , w(r − 1, k)) r > 1(6)

If e < l two cases can occur, either at least one stationfinishes backing-off before the end of the EIFS or theEIFS ends with no stations having finished backing-off. The probability that a station i will have a back-offcounter boi higher than the EIFS timeout is

P(boi > EIFS) = l − e

l= 1 − e

l

The probability that none of the stations have fin-ished backing-off before the end of the EIFS is

P

(k′

mini=1

boi ≥ EIFS

)=(

l − e

l

)k′

(7)

where k′ is the number of initially participating stations,1 ≤ k′ ≤ k. So the probability that at least one stationfinishes backing-off is

P(k′

mini=1

boi < EIFS) = 1 −(

l − e

l

)k′

(8)



Considering the two cases, the probability that therewill be i ‘winning’ stations in step r is given by com-bining Equations (5), (7), and (8). After some trivialsimplifications we have

w(r, i) =k∑

j=1

[p(i, j, l)

1 − p(0, j, l)P(r, j)

(1 −

(l − e

l

)j)]

+ p(i, k, l)

1 − p(0, k, l)

k∑j=1

[P(r, j)

(l − e

l

)j]

(9)

4.1.4. Busy times

In each transmission attempt, there are three possibleoutcomes: Only one station transmits and the transmis-sion is considered to be successful (s). Two or more sta-tions transmits and either the collision is detected (CD)or it is not detected (CND). The busy times are derivedfrom Algorithm 1 and the IEEE 802.11a standard [17].

The busy time will be the same if the transmissionis successful or not, and will be given by Ts = TCND =m + 155, see Table II. If the collision is detected thebusy time will be TCDI.

The probability of not detecting a collision is theprobability that all stations will choose the same slotto pause in and is

P(detect) = n1−k

if there are k transmitting stations. The risk of notdetecting a collision will decrease with increasing n

and k. The expected busy time for a single transmissionattempt is

E[busy] = n1−kTCND + (1 − n1−k)TCDI (10)

The expected busy time for all attempts in a cycle is

E[B] =∞∑

r=1

k∑i=1

w(r, i)(n1−iTCND + (1 − n1−i)TCDI)

(11)

If n = 0, that is ordinary multicast, then the right-hand factor will reduce to TCND which is obviouslylarger than n1−iTCND + (1 − n1−i)TCDI for any posi-tive n and i.

4.1.5. Idle time

Remember that the expected value of a discrete stochas-tic variable is the sum of the probabilities of each out-come times its numerical value. The channel will beidle until at least one station has finished backing off.The probability that at least one station has finishedbacking off is 1 − p(0, k, l) from Equation (5). The ex-pected number of back-off steps before that happens isgiven by the geometric distribution

E[back-off] = p(0, i, l)

1 − p(0, i, l)(12)

Each transmission attempt will be proceded by aDIFS and with a certain probability an EIFS. Hencethe expected idle time in a cycle is

E[I] =∞∑

r=1

k∑i=1

q(r, i)

(DIFS + etslot

(l − e

l

)i

+ p(0, i, l)tslot

1 − p(0, i, l)

)(13)

The channel utilization is easily found by substitut-ing Equations (11) and (13) in Equation (2).

4.2. Results

The analysis was validated by comparison to simula-tions in GloMoSim see Section 5 for details. Figure 4shows that the analytical results are a good match forthe simulated results as long as the number of stationsis small.

The lowest curves, for n = 1, show what perfor-mance could be expected from normal multicast butwith some additional overhead. Channel utilizationdecreases assymptotically towards a value around 0.35.The upper two pairs of curves show an interesting be-havior in that they first decrease then increase slightly.The effect is more pronounced in the simulated curves.This is an effect of the back-off no longer being inde-pendent for each station when there are a large numberof stations as explained in Subsection 4.3.

The optimal number of steps nopt as a function of thenumber of stations and the effect on channel utilizationis presented in Figure 5. The figure shows two things:first, the optimal number of slots decreases with thenumber of stations and second, the choice of n hassmaller impact for lower numbers of stations.



0 10 20 30 40 500.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

Number of stations

Cha

nnel

util

izat

ion

ρ

Simulated, n=1Simulated, n=3Simulated, n=5Analytical, n=1Analytical, n=3Analytical, n=5

Fig. 4. Channel utilization ρ as a function of the number of stations k with CW l = 15, simulated and analytical. The relativemean square error is ≈ 2.1%.

4.3. A Note on Asymptotic Behavior

As the number of stations k grow in relation to the num-ber of available back-off slots l + 1 the preceding anal-ysis will become increasingly inaccurate. It is based on

the assumption that almost all channel allocations willstart with a competition for the medium during at leastone back-off time slot.

What will happen instead is that we will end up with1 ≤ k′ ≤ k stations with bo = 0. All of them will try

5

10

15

20

Number of stations

n opt

nopt

0 10 20 30 40 500.6

0.7

0.8

0.9C

hann

el u

tiliz

atio

n ρ

n=n

opt

n=2n=4

Fig. 5. Selecting the optimal number of slots n.



to transmit (and fail). After that they will choose a newbackoff value so that on average k′/(l + 1) stations willremain with bo = 0. This will reoccur until zero or onestations are left. In the first case, all stations will back-off once. In the second case a successful transmissionwill occur.

5. Simulation Results

We extended the analytical evaluation from the previ-ous section with simulations in order to examine factorswhich are beyond the scope of the analysis. The simu-lations were performed in the discrete event simulatorGloMoSim [21].

We are mainly interested in reliability and efficiency.Efficiency is often measured as throughput which ishard to define. The aggregated throughput for multicastcan not be easily calculated because there are multiplerecipients and some of them may receive the packetwhile other do not. Consequently, it is difficult to knowif a multicast packet should be included in the aggre-gated throughput or not. For instance, Tourhilles [10]considered only a single broadcast receiver. Anotherway is to consider the average reception. We considerthe average packet delivery ratio which is more a mea-sure of reliability than efficiency.

The following metrics are used: delay and ratio ofassumed success to measure efficiency and packet de-livery ratio to measure reliability. The delay is the timefrom when a packet arrives at the MAC layer in thesender until it is successfully received. The averagepacket delivery ratio is defined as the average ratioof multicast packets received by the multicast groupto the unique packets offered for transmission. Ra-tio of assumed success is defined as (#main transmis-sions)/(#vanguard transmissions). When a main trans-mission begins the transmission is assumed successful.More than one vanguard transmission per main trans-mission will result in a ratio of assumed success smallerthan one.

5.1. Traffic and Radio Model

In each simulated scenario a specific number of accesspoints are evenly distributed onto a quadratic area withsides 200 m long. The specific number of stations arevaried for the different simulation scenarios and theposition of each station is randomly set within the sim-ulation area.

We assume that there is no mobility. Each station isassociated with the closest access point. The associa-

tion is kept during the whole simulation. All stations ina BSS are members of a single multicast group.

Both the multicast and unicast traffic assumes a con-stant bit rate model with a packet size of 1496 bytes.

Two different scenarios are simulated. In the firstscenario the multicast senders have a fixed bit rate of500 kbps and the aggregated load from unicast sendersis gradually increased by introducing more senders un-til the saturated condition is achieved. In this scenario,each unicast sender adds a packet rate of four packetsper second to the aggregated load. In the second sce-nario with saturated conditions each sender constantlyhas a new packet to send.

For the modeling the path loss we have used a noiseaccumulating two-ray path loss model, and for fadingwe assume a Rician distribution with K = 5. This rep-resents a strong line of sight path between the trans-mitter and receiver, resembling an open arena environ-ment. The output power is set to 15 dBm. All accesspoints are assumed to use the same frequency channelresulting in overlapping basic service sets. The datarate for all transmissions is set to 6 Mbps.

5.2. Variable Load Scenario

In the first simulation scenario EMCD is evaluated un-der variable load. In the simulation there are four andnine overlapping cells (access points) with both multi-cast and unicast senders.

In Figure 6, the average packet delivery ratio is plot-ted against the number of unicast senders. For standardmulticast (802.11) the packet delivery ratio decreasesrapidly as the offered load increases, when moreunicast senders join the network. When the mediumbecomes saturated, for around 70 stations, the rate ofdecrease becomes smaller mainly as a result of muchhigher CW values for the unicast senders. EMCD is ca-pable of maintaining a relatively high packet deliveryratio for an increasing load. The upper curves are forfour and nine access points, and two values of n. Theeffect of increasing n is more evident in the caseof nine access points where more collisions arebetween the access points and more slots will increasethe detection probability. Moreover, the saturationpoints is reached more quickly for EMCD sinceretransmissions are performed that increase theload.

In Figure 7 the ratio of assumed success is shown foran increasing number of unicast senders. Increasing thenumber of unicast senders and/or access points requiremore vanguard transmissions per main transmissiondue to collisions. The fraction of collisions experienced



10 20 30 40 50 60 70 80 90 1000.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Number of stations

Ave

rage

pac

ket d

eliv

ery

ratio

802.11, 4 AP802.11, 9 APEMCD, 4 AP, n = 2EMCD, 4 AP, n = 13EMCD, 9 AP, n = 2EMCD, 9 AP, n = 12

Fig. 6. The average packet delivery ratio for EMCD and standard 802.11 for four and nine access points.

between multicast senders are higher for low and highloads. For lower loads, few unicast senders are presentand a majority of the collisions are between multicastsenders. For high loads, the unicast senders have muchhigher values of CW then the multicast senders (hav-ing CWmin) resulting in more collisions between themulticast senders. This is why the effect of increasingn is more distinct for these two load levels.

5.3. Saturated Load Scenario

In the second scenario, a fully saturated network withfour access points, the aim is to illustrate the trade-offbetween packet losses and delay when changing someof the parameters.

In Figure 8 the average packet delivery ratio is shownfor three different retransmission limits Rmax and two

10 20 30 40 50 60 70 80 90 1000.4

0.5

0.6

0.7

0.8

0.9

1

Number of stations

Rat

io o

f ass

umed

suc

cess

EMCD, 4 AP, n = 13EMCD, 4 AP, n = 2EMCD, 9 AP, n = 12EMCD, 9 AP, n = 2

Fig. 7. The ratio of assumed success versus an increasing number of unicast sender for four and nine access points.



10 20 30 40 50 60 70 80 90 1000.75

0.8

0.85

0.9

0.95

Number of stations

Ave

rage

pac

ket d

eliv

ery

ratio

Rmax

=2, n = 2

Rmax

=2, n = 13

Rmax

=3, n = 2

Rmax

=3, n = 13

Rmax

=4, n = 2

Rmax

=4, n = 13

Fig. 8. The average delivery ratio for three different values of Rmax and two values of n.

sizes of n. The delivery ratio is increasing for highervalues of Rmax. The effect of changing the number ofslots n depends on the fraction of unicast senders in thesystem. When the fraction of unicast senders are low,the majority of collisions will be between multicastsenders and if n is increased some gain in performanceis achieved. However, this effect is less significant whenthe fraction of unicast senders are higher. Only a small

percentage of the collisions will be between multicastsenders and increasing n has smaller effect.

When Rmax = 4 and only a few slots exists thepacket delivery ratio may actually increase when moreunicast senders enters the network. This is because allcollisions with unicast senders will be detected, lead-ing to more retries and so the success probability willincrease.

10 20 30 40 50 60 70 80 90 1000.014

0.016

0.018

0.02

0.022

0.024

0.026

0.028

Number of stations

Ave

rage

del

ay (

s)

Rmax

= 2, n = 2

Rmax

= 2, n = 13

Rmax

= 2, n = 2

Rmax

= 2, n = 13

Rmax

= 4, n = 2

Rmax

= 4, n = 13

Fig. 9. The average delay for three different values of Rmax and two values of n.



The average delay is shown in Figure 9. The delay isevidently increasing for higher values of Rmax. Chang-ing n has much smaller impact on the delay, especiallyfor smaller values of Rmax. The two curves at the bot-tom are almost indistinguishable while there is moredifference in the two upper curves.

Clearly, there is a trade-off between delay and packetdelivery ratio which is determined by Rmax. In the caseof a streaming application the choice of Rmax may beimportant to maximize the utility of the service.

6. Conclusion

We have adapted the Rom algorithm to an IEEE 802.11network with the purpose of detecting and recoveringfrom multicast packet losses caused by collisions. Wecall the algorithm EMCD. We have used probabilisticanalysis and simulations to study the performance ofEMCD.

The main contributions of this paper are (a) thatwe have adapted the Rom algorithm to contemporaryCSMA/CA networks and MAC layer multicast, (b) thatwe have provided a probabilistic analysis of its perfor-mance under saturated load conditions, and (c) that wehave provided simulation results for the algorithm un-der both saturated and unsaturated conditions in mixednetworks.

Some of the key findings are that EMCD signif-icantly reduces undetected packet losses caused bycollisions and reduces the time wasted on collisions(see Eq. (11)). The net effect is higher efficiency andreliability.

Only a relatively low number of slots are needed toachieve optimal channel utilization. With a large num-ber of stations, n = 7 is optimal. With fewer stations n

is higher but the system is also less sensitive to changesin n. Adding unicast to the mix changes the situationslightly, on one hand fewer slots are needed to detect acollision as long as there is at least one unicast stationinvolved, on the other hand ending the transmission atTCDI has less effect as the unicast transmission will con-tinue anyway. An acceptable choice in many situationscould be n = 7.

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Authors’ Biographies

Thomas Nilsson is a Ph.D. student atUmea University, Sweden. He focuseson resource optimization and Quality ofService in wireless networks. Thomasreceived his Master of Science degreein computing science in 2002 and hislicenicate degree in 2005, both fromUmea University. He was born in Umea,Sweden in 1978. Thomas Nilsson is a

student member of the IEEE.

Greger Wikstrand is a doctoral studentat Umea University. He was born inUppsala, Sweden in 1972. He obtainedthe Master of Science in EngineeringPhysics degree from Uppsala Universityin 1998, and the Licenciate of Engi-neering degree in Computing Sciencefrom Umea University in 2003. He was

a doctoral student at Linkoping University during 1998 and1999. In 2000, he was with Procter & Gamble in Stockholm,Sweden. During 2001–2002, he worked as a research projectmanager at Ericsson AB. Greger Wikstrand is a student mem-ber of the ACM and the IEEE.

Jerry Eriksson is a senior lecturer atUmea university. He obtained the Masterof Science in Computing Science fromUmea University in 1990 and the Ph.D.from the same university in 1995. Hisdoctoral dissertation (1995) treats the op-timization and regularization of nonlin-ear least squares problems. He worked atEricsson from 1997 to 2000. His current

research interests involves telecommunication and resourceoptimization.


A collision detection method for multicast transmissions in CSMA/CA networks

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