[IEEE 2011 4th Joint IFIP Wireless and Mobile Networking Conference (WMNC) - Toulouse, France...

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An Opportunistic IEEE 802.11 Medium AccessControl Protocol

Hend Koubaa, Asma Ben Hassouna, Farouk Kamoun

CRISTAL Lab, ENSI, Manouba, TunisiaEmail: hend.koubaa@isi.rnu.tn, asma.hassouna@topnet.tn, frk.kamoun@planet.tn

Abstract—In a wireless network, the signals transmitted be-tween a source station and different receiver users most oftenhave different channel fluctuation characteristics. This diversitythat exists between users is named multiuser diversity (MUD) andcan be exploited to improve the capacity of wireless networks.One way of exploiting MUD is by opportunistic schedulingof users,i.e. giving priority to users having the best channelconditions. To be able to take advantage of the MUD, a feedbackprotocol has to be deployed to notify the source station aboutthe Carrier to Noise Ratio (CNR) or the channel gain of themobile user with the finest channel conditions. In this paper, weare inspired from the splitting algorithm [1] to provide IEEE802.11 with an opportunistic scheduling. We describe the newopportunistic MAC protocol and we give an overview of itsimplementation in NS-2. We show that the simulation of thesplitting algorithm gives the same average feedback time as theanalysis study. We compare the native IEEE 802.11 scheduling tothe opportunistic one and prove that exploiting MUD increasesthe network capacity. We also show that this increase is higherwith increasing the number of users. Finally, we studied theinfluence of the observed number of packets in the queue andwe prove that maximizing this number does increase the networkcapacity and the medium access fairness.

Index Terms—Multiuser Diversity (MUD), Medium AccessControl (MAC), IEEE 802.11, Splitting algorithm, OpportunisticMAC, Wireless Networks, NS-2

I. INTRODUCTION

The transmission medium used by wireless data networks isinherently time varying due to many facts, e.g. user mobilityand multipath propagation. Also, the wireless resource isscarce and expensive, requiring optimized usage to maximizethe throughput and to raise the system efficiency. Conse-quently, to achieve a high data rate wireless communicationsystem, much attention is being given to multiuser diversity(MUD) [2][3]. The MUD could be exploited by deferring theaccess to the channel by a user with poor link quality until itslink hits near a certain peak and, as a result, giving priority tousers having good channels.

Exploiting MUD is a contemporary concept that takesas matter the communication over fading wireless channels.Unlike rate adaptation based schemes [4][5][6] where the datatransmission rate is adapted to the channel quality, the fluctu-ations of channel quality are exploited rather than avoided.

Opportunistic scheduling, exploiting MUD gain, was firstproposed in [7] and relies on the assumption that differentusers in a wireless multiuser system experience independentfading processes. In those circumstances, the total throughput

can be significantly increased by scheduling each time the userwith the most favorable channel conditions. Channel qualityis measured in term of carrier to noise ratio (CNR).

Different approaches are proposed to find the best user. Indistributed approaches, as the CAA (Channel Aware Aloha)protocol [8], every user transmits with a probability thatdepends on the number of users in the system. MUD isexploited, by CAA, in a distributed way by using a variationof the slotted ALOHA protocol. The main idea of this protocolis that each user randomly transmits based on its local channelknowledge. In centralized approaches, like [9][10][11], therelevant users are probed with a set of CNR thresholds. First,the highest threshold is used. If none of the users are abovethis one, consequently no feedback is received by the sender,the threshold value is sequentially lowered until one or moreusers are found. Another centralized work proposes the MAD(Medium Access Diversity) protocol [12] where each sourcehas to exploit the diversity between its receivers. The sourcetransmits by multicast a request containing the list of the po-tential receivers. Every receiver sends back its CNR accordingto the rank of its address in the address list. The source isthen able to serve the receiver with the best CNR. Admittingthat this last work handles the contention problem, the timeneeded before the convergence of the selection algorithm isstill considered important. One more centralized work calledOSAR (Opportunistic packet Scheduling and Auto Rate) pro-tocol [13] is also proposed. The basic idea of OSAR is takingadvantage of the multiuser diversity by adapting transmissionrate to the channel quality. As in MAD, a multicast RTS packetis used to request for the channel quality of the potentialreceivers. However, OSAR avoid that all receiver reply backto the source by only authorizing feedback from receiverswith channel quality better than a certain level. Furthermore,because the feedback of each receiver is sent after deferringa time period that depends on its listing order in the RTSpacket, the potential collision of receivers with a high channelquality is avoided. The main problem of this protocol is thatnumerous queues should be maintained in each node, i.e. afirst one for the network layer control packets, another onefor broadcast packets in addition to a queue for each one hopreceiver. Furthermore, the transmission rate is chosen from apredefined set according to the receiver CNR value, hence, itdoes not accurately depend on receiver quality.

Another opportunistic protocol based on a splitting algo-

rithm is proposed in [1]. The main purpose of this algorithmis to determine two thresholds such that, each time slot (i.e.the time period needed for sending a packet and receiving areply), only receivers whose channel gains are in the intervalof the thresholds are allowed to transmit back to the sourcetheir channel quality. In a distributed way, the source and thepotential receivers use one or many trials to find the bestreceiver. At the end of each trial, each receiver receives a (0, 1,e) feedback from the source, indicating if the trying period wasidle (0), contained a successful transmission (1), or containeda collision (e). If one feedback is received, only the user withthe best channel gain transmitted in the time slot. In this case,the source carries on the data transmission. If 0 or several feed-backs are received then the users will regulate their thresholdsand repeat the algorithm until either a success occurs or themaximum number of trials is achieved. The splitting algorithmhas been used in different recent works [14][15][16]. In [14],additional information about capture and power control is usedfor a faster MUD multiple access selection. [15] presents ageneralized splitting algorithm for multiple access selection.This generalization is based on introducing new parametersand has been extended for selecting the best number of usersQ ≥ 1. In [16], the authors analyse the trade-off betweenthe best user selection and the data transmission phases ofa MUD splitting based cooperative relay system. The splittingalgorithm [1] was only studied analytically and has shown agood convergence performance. For this reason, in this work,we are interested in studying how to integrate this algorithmwithin IEEE 802.11.The work in [17] studies, in the context of wireless ad-hoc networks, a distributed opportunistic scheduling (DOS).As it is the case of the splitting algorithm [1], the linksshould compete to get the channel before data transmissions.Contention is done via channel probing (limited feedback (0,1, e) is also studied) and distributed scheduling. This worknegotiate the usefulness of performing more channel probingto reduce estimation errors even for a link with successfulcontention. However, this work does not study the influence ofthe number of users on the efficiency of the multiuser diversityexploitation and on the service fairness which are some of ourwork subjects.

Our work, inspired from this splitting algorithm [1], pro-vides IEEE 802.11 with an opportunistic scheduling usingtransmission rates that depend truthfully on the receiver chan-nel quality. We refer to the modified IEEE 802.11 as the Op-portunistic MAC (OMAC) protocol. In this paper, we describethe implementation of OMAC protocol in NS-2 [18], we studyits performance and we compare it to the performance of thenative IEEE 802.11 and, especially, we study the influencethe observed number of packets in the source queue on theexploitation of the diversity between users.

The remainder of the paper is organized as follows. Thedescription of the OMAC protocol is presented in section II.In section III, we describe the NS-2 implementation of theOMAC protocol. Based on a set of measured metrics, insection IV, we study the performance of the OMAC protocol.

Fig. 1. The opportunistic MAC protocol phases

Finally, our conclusions and future perspectives are listed insection V.

II. DESCRIPTION OF THE OMAC PROTOCOL

In a system using the native IEEE 802.11 protocol, a source,having several data packets waiting in its queue, schedules thefirst receiver. However, using the OMAC protocol, the sourcehas to schedule the receiver having the best channel quality.Thus, the source needs to be informed about the best receiver.In order to get the address of this one, the source runs thesplitting algorithm proposed by [1]. The last is over when thebest receiver transmits its channel quality back to the source.Upon finding the best channel receiver, the source computesthe elected data rate Re as a function of the received channelquality, using the Shannon expression [19]. This data rate isused to schedule a number of packets belonging to the electedreceiver. The last number is equal to bRe

Rb

c where Rb is thebasic rate and b.c indicates the largest integer lower than theenclosed value.

In the following, we give more details about the OMACprotocol. Each source station (STAS) having several receivers,or candidate stations (STACs), has to accomplish three phases:(i) the phase of queue consultation for extracting the STACsaddresses, (ii) the phase of searching the STAC having thebest channel quality and (iii) the phase of data transmission(see Figure 1).

During the phase (i) the STAS selects the first N RA

STACs in its queue. The number of these selected candidatesrespects the condition that the maximum number of observedpackets in the queue is MAXpack. The last is a parameterthat has to be chosen to optimise the network capacity andto avoid unfairness problems. The phase (ii) is divided intoseveral time slots. The length of a slot, T , is sufficient forsending a packet and receiving another. The channel qualityis expressed in terms of channel gain. Let gi be the gain of thechannel between the STAS and the STAC i. The expressionof gi is given by expression (1) where P i

r is the power of thesignal received by STAC i and P is the transmission power.

gi =P i

r

P(1)

The expression (2) is used to calculate the elected data rateRe used to send packets to STAC i, where ξ0 is the channelnoise considered as an additive white Gaussian noise and Ωis the channel bandwidth.

Re = Ω log(1 +giP

Ω ξ0

) (2)

The phase (ii) starts when the STAS multicasts an ORTS(as Opportunistic RTS) packet to the N RA chosen STACsto get their channel gains. The ORTS packet carries the list ofthe STACs. After the reception of the ORTS, the STAS andthe STACs start, simultaneously, the splitting algorithm. Theyset three variable gain thresholds Gll, Gl and Gh accordingto [1]. The interval [Gl, Gh] represents the channel gain range.During a time slot T , only the STACs i : gi ∈ [Gl, Gh] areallowed to transmit back their gains to the STAS. Actually, thegain is transmitted in an OCTS (as Opportunistic CTS) packet.Gll is a temporary variable that contains the highest value ofGl used in previous time slots such as exists a number of userswith channel gain larger than Gll. Gl initial value is chosenso that the probability that one user’s channel gain is aboveGl is 1

N(N is the number of STACs) and consequently the

probability of a collision is reduced. Gh threshold is initiallyset to a vary large gain value.

After transmitting the ORTS, the STAS has to wait for atime T needed for the reception of one or several OCTSs.Three cases are possible. (1) If the number of received OCTSis 0, no station has the channel gain in the threshold interval[Gl, Gh]. (2) If the number of the received OCTSs is exactly1, only one STAC has its channel gain within the thresholdinterval. (3) Finally, if a collision occurs at the STAS, severalSTACs have their channel gain within [Gl, Gh]. To inform theSTACs about what happened, the STAS broadcasts a feedbackpacket, noted FBK, containing a field which is set to one ofthe values 0, 1 or e (to indicate 0, 1 or several feedbacks).These various values correspond to the three cases explainedabove.

In the second case, only the STAC having transmitted anOCTS gets access to the wireless medium. In this case, thesplitting algorithm is over. In the first and third cases, thethresholds Gll, Gl and Gh are, in a similar way, modifiedby the STAS and the different STACs. This modificationoptimises the time necessary for the splitting algorithm to beover. After receiving a single OCTS packet, the STAS sendsa final FBK packet, waits for a final OCTS packet from theelected STAC. By sending this final OCTS, the elected STACconfirms the reservation of the channel to all its neighbors.Then, the phase (iii) begins and the STAS starts transmittingdata packets.

After the transmission of n data packets, the STAS runs thesame splitting algorithm and the STACs are chosen among theremaining MAXpack - n first packets in the queue. The valueof n is computed by the source as a function of the electeddata rate (Re) as described in section II. When the MAXpack

packets are served, another group of MAXpack packets ischosen for a new opportunistic access scheduling period.

Gl = F−1G

( 1n

), Gh = 1, Gll = 0while feed 6= 1 and slot≤slotmax do

feed = get 0, 1 or many (e) feedbacks from previous slotif feed = e then

Gll = Gl

Gl = split(Gl ,Gh)else

if feed = 0 thenGh = Gl if Gll = 0 then

Gl = split(Gll,Gh)else

Gl = lower(Gl)

slot = slot + 1

Alg. 1: Description of the splitting algorithm

The thresholds Gll, Gl and Gh are computed accordingto the splitting algorithm described by Algorithm 1 [1]. Thenumber of feedbacks is noted feed. slot is the current numberof time slots already used for different threshold intervals.slotmax is the maximum number of time slots to take intoaccount the case the splitting algorithm does not converge. FG

denotes the channel gain’s complimentary distribution functionof a single user. In the following, we present the expressionsof lower() and split() functions.

split(Gl , Gl) = F−1G

(FG(Gl)+FG(Gh)

2)

lower(Gl) = F−1G

(FG(Gl)(1 − 1n

) + 1n

) , if Gl> 0lower(Gl) = 0 , if Gl≤ 0

This exchange between the STAS and the STACs as well asthe application of the splitting algorithm will continue until asuccessful transmission takes place or the maximum number oftimeslots, slotmax, is achieved. In this last case, all variablesare set to their initial values and the first enqueued user isserved. Then, a new search interval starts.

III. IMPLEMENTATION OF THE OMAC PROTOCOL IN NS2We have implemented the OMAC protocol in NS-2. We

present in this section an overview of this implementation.

A. The OMAC protocol framesSimilar to several defined opportunistic MAC proto-

cols, [5][12][13] for example, new control frames are requiredto deploy the OMAC protocol. Inspired from the native IEEE802.11 control frames, we define the ORTS, the OCTS and theFBK frames. The ACK and the DATA packets are the sameas in the native IEEE 802.11. In this section, we describe thenew frames.

1) The ORTS frame: This frame is used by the sourcestation to query the STACs and to get their gains. This frame,carrying a list of receiver addresses, is broadcasted to thesource’s neighbors. Figure 2 describes the ORTS frame whichcontains two new fields, compared with the IEEE 802.11 RTS.The RA field contains the list of candidate addresses chosenby the source and the N RA field contains the number of thesecandidates.

Fig. 2. The ORTS frame structure

Fig. 3. The OCTS frame structure

2) The OCTS frame: This frame is sent back by a STACto the STAS. The structure of the OCTS frame is presentedin Figure 3. Compared with the IEEE 802.11 CTS, the OCTScontains three new fields: TA, END and GAIN. The field TAcontains the address of the OCTS transmitter. The value ofthe END field is set to FALSE to inform neighbors that theOCTS is used to send the receiver’s gain. The value of the ENDfield is set to TRUE after the splitting algorithm convergenceand is necessary to inform neighbors that data transmissionwill begin. The GAIN field is used by the OCTS transmitterto indicate its channel gain. The OCTS frame is thus used tofind the best candidate station and also to reserve the mediumas does the IEEE 802.11 CTS.

3) The FBK frame: This frame is broadcasted by the STASand is intercepted by all the STACs, i.e., users having alreadyreceived an ORTS packet. This frame is presented in Figure 4.The field VAL carries the number of the OCTS packets receivedby the STAS (0, 1, e if a collision occurs). Its value iseventually used by each STAC to compute the new thresholdinterval [Gl, Gh].

B. The OMAC protocol states

The MAC layer can be in a transmission, a reception oran idle state. The transmission MAC layer states, defined bythe OMAC protocol, depend on the type of the packet tosend. These states are MAC RTS, MAC CTS, MAC FBK,MAC ACK and MAC SEND, which correspond respectivelyto transmitting an ORTS, an OCTS, a FBK, an ACK or aDATA packet. During a packet reception, the OMAC layerstate is MAC RECV which means that MAC layer is receiving

Fig. 4. The FBK frame structure

Fig. 5. The possible transitions between the OMAC layer states

a packet, or MAC COLL which indicates that a collisionoccurs. The OMAC layer, which is neither in a transmissionstate, nor in a reception state, is in a MAC IDLE state.Figure 5 illustrates the different OMAC states.

C. Functions used to deploy the OMAC protocol

To implement the OMAC protocol in NS-2, we first imple-mented an extension based on a general model used to deployopportunistic MAC protocols [20]. This model is composedof a set of general functions that can be used to implementany opportunistic MAC protocol based on the IEEE 802.11standard. We used our NS-2 extension to deploy the OMACprotocol. Figure 6 underlines different functions used to deploythe OMAC protocol. Some of these functions belong to thegeneral model and others are specific to the splitting algorithm.Table 1 describes some functions that belong to our NS-2extension and that we use to deploy the OMAC protocol.Table 2 describes some functions used in the OMAC protocolimplementation. These functions are specific to the splittingalgorithm.

IV. THE OMAC PROTOCOL PERFORMANCE STUDY

In this section, we study the performance of the OMACprotocol via many simulations. The simulation area is chosensuch as users can reach each other at the basic data rate(2Mbit/s) and using the Rayleigh propagation model. Theinterface queue size is set to the default value (50 packets)and MAXpack value is 45 packets unless otherwise specified.For all simulations, we consider one source station that has aCBR traffic for each receiver (see figure 7). Each CBR traffic isset to a load of one 1024-byte packet per 0.1s. The simulation

Fig. 6. The functions used to deploy the OMAC protocol

Function DescriptiongetUsersAddresses() Takes as inputs the interface queue instance

and the MAXpack value and returns the list ofcandidate addresses

getElectedRate() Takes as input the reception power of the currenttimeslot c, Pi

r(c), and returns the elected datarate.

getNbrData() Takes as input the elected data rate (Re) andthe basic data rate (Rb). It returns the numberof data packets to be sent.

macDequeue() Takes as input the address of a packet anddequeues it from the interface queue.

getDataToSend() Takes as inputs the number of data packets thatwere sent and the total number of packets to besent. It returns the current data packet to send.

sendORTS() Takes as input the list of candidate addresses. Itprepares an ORTS packet to be sent to this listof receivers.

sendOCTS() Takes as inputs the destination address and thegain value. It prepares an OCTS packet to besent to this destination.

getBestUserAddress() Takes as input the list of candidate addresses andreturns the address of the best user.

Tab. 1. The functions of the opportunistic NS-2 extension

duration is 100s. The number of wireless mobile users variesfrom one scenario to another.

We measured the guard time, the received data rate andthe medium access percentage per user. The first measuresthe number of timeslots needed to find the best STAC. Thedata rate corresponds to the total received data bytes dividedby the total simulation time. The medium access percentageper user represents the percentage of the number of times aspecific STAC gains access to the channel, to the total numberof access done by all the STACs.

The average guard time: We study a scenario where thenumber of users is varied from 5 to 100. Figure 8 presents theaverage guard time as a function of the number of users. Theobtained result is the same as the result given from analysisin [1]: the average guard time is less than 2.5 time slots. This

Function DescriptioninitSplitting() Takes as input the number of candidate stations and

initializes the splitting algorithm. It initializes thesplitting thresholds and sets the current number oftime slots to 0.

lower() Decreases the value of the threshold Gl. It is Calledby the function splitting().

split() Computes the new values of the thresholds Gll, Gl

and Gh. It is called by the function splitting().splitting() Takes as input the number of candidate stations. It

is called until a single OCTS is sent to the sourcestation.

sendFBK() Prepares a FBK packet to be sent.recvFBK() Handles the received FBK packet. This feedback

indicates if zero, one or several OCTS packets arereceived by the source station. In case of zero orseveral feedbacks, the function splitting() is called.Then, the channel gain is computed. If it belongsto the threshold interval [Gl, Gh], the functionsendOCTS() is called. Otherwise, the access to themedium is deferred.

getCurrentData() Returns the current data packet to send.

Tab. 2. The functions of the NS-2 opportunistic extension that are specific tothe splitting algorithm

confirms that the splitting algorithm has a good convergenceperformance. Moreover, the guard time does not depend onthe number of users as proved in [1].

The network capacity: To study the OMAC enhancementof the network capacity, we simulated the data rate in IEEE802.11 and OMAC protocols. The IEEE 802.11b data rates,used for comparison, are 2, 5.5, and 11 Mbit/s. We variedthe number of receiver users. Figure 9 compares both ofthese protocols and shows that exploiting multiuser diversityimproves the network capacity. This improvement increaseswith increasing the number of users. Also, we notice that theOMAC protocol reaches data rates that exceed those given bythe IEEE 802.11 even using the maximum raw data rate of11Mbit/s. This is explained by the fact that with a highernumber of users, the gain in diversity is more significant,

Fig. 7. The simulation scenario (One CBR traffic for each receiver)

Fig. 8. The average guard time as a function of the number of users

which increases the data rates used by the source.The medium access percentage per user: Using the

OMAC protocol, the user having the best channel gain isexpected to access to the medium more often than the usershaving lower channel gains. We simulated the medium accesspercentage per user as a function of the channel gain for bothIEEE 802.11 and the OMAC protocols using a scenario of30 users. The corresponding result is presented in Figure 10.The OMAC protocol shows a medium access percentage peruser increase with increasing the gain, i.e. a user maintains thechannel only if its channel gain is relevant. Conversely, in a

Fig. 9. The received data rate as a function of the number of users

Fig. 10. The medium access percentage per user as a function of the channelgain

system deploying IEEE 802.11, a user keeps accessing to thechannel and reserving it even if its channel is poor.

The influence of the channel quality on the data rate:To study the influence of the user channel quality on the datarate in the OMAC protocol, we consider a source station thatgenerates CBR traffics. Figure 11 represents the received datarate per user as a function of its average gain. We can observethat this rate increases with increasing the channel quality.This behavior is due to the opportunistic nature the OMACprotocol. Each time, this protocol elects the receiver havingthe best channel gain.

Fig. 11. The data rate received by a user as a function of its channel gain.

The influence of the MAXpack parameter: In order tostudy the influence of the MAXpack parameter on the systemperformance, we run a number of simulations using a scenarioof 20 users (one source and 19 receivers). For each MAXpack

value, we measured the received data rate. Simulation resultsare illustrated in Figure 12. This last shows that the measuredOMAC data rate increases with an increase of the MAXpack

parameter. This result is justified by the fact that systemdiversity is exploited further when the number of candidatescompeting for channel is higher. Actually, rising the number ofobserved packets, MAXpack, means maximizing the chance ofgetting the best channel gains and, consequently, maximizing

the probability of getting the best candidate receivers inthe system. By maintaining the channel, these receivers canguarantee a higher throughput.

To study the influence of the parameter MAXpack on theOMAC fairness performance, we have computed the receiveddata rate of each user for different values of MAXpack.Figure 13 shows the result for a simulation of 20 users (onesource and 19 receivers). For the different values of MAXpack,we have a lack of fairness among users which have unequalreceived data rates. A deeper simulation study was necessaryto justify this result. We have, indeed, computed the averagechannel gain of each user for different values of MAXpack

(see Figure 14). This average channel gain takes into accountthe instantaneous channel gain values when users are served.The result shows that for a high value of MAXpack (≥30),the received data rate follows the increase or the decrease ofthe average channel gain. This justifies why users do not havethe same received data rate: users with better channel gainsreceive data with better data transmission rates and then havebetter received data rates.To study thus the OMAC fairness performance, independentlyof the variation in the channel gain, we have simulated themedium access percentage for each user. We found, indeed,that for a high value of MAXpack (≥30), users have a fairaccess to the medium. For lower values of MAXpack, usershave an unfair medium access. This is justified by the factthat for a low value of MAXpack, some users are taken intoaccount in the best candidate research phase less than otherusers. However, for a higher value of MAXpack, all usersare taken into account which results in a fair medium accessfor all users. Figures 15 and 16, showing the medium accesspercentage per user for two values of MAXpack (5 and 50),prove our claim.

Fig. 12. The data rate as a function of the MAXpack parameter

V. CONCLUSION

In this paper, we propose and describe OMAC, which isan opportunistic IEEE 802.11 MAC protocol inspired fromthe splitting algorithm [1]. We present how to provide IEEE802.11 with an opportunistic scheduling. We give some details

Fig. 15. The medium access percentage per user for MAXpack value of 5packets

Fig. 16. The medium access percentage per user for MAXpack value of 50packets

corresponding to the NS-2 implementation of the OMACprotocol.

The deployment and simulation of the OMAC protocol is agood step toward the study of a special kind of protocols thatdepend on the user channels. Through our work, many resultsare achieved. We show that the simulation of the splittingalgorithm gives the same average guard time as the analysisstudy. We compare the native IEEE 802.11 scheduling to theOMAC scheduling and prove that exploiting MUD increasesthe network capacity. We also show that this increase is higherwith increasing the number of users. Moreover, we confirmthat the medium access percentage per user in the OMACprotocol increases with the channel gain increasing. Besides,we study the influence of the MAXpack parameter and weprove that when the number of observed packets in the queueis higher, the diversity between users is better exploited andthe medium access fairness is better.

Future work will cover a more detailed simulation to opti-mise some parameters of the OMAC protocol. In particular, tostudy the optimal value of MAXpack as a function of the num-ber of users in the system. Also, it is interesting to simulatethe OMAC protocol in a multihop network taking into accountthat multiple users have data for transmission. Simulation offading models other than the Rayleigh is also important toimprove our conclusions. Furthermore, highlighting the impact

Fig. 13. The received data rate percentage per user for different MAXpack values

Fig. 14. The channel gain per user for different MAXpack values

of collisions and packet losses on the performance of OMACprotocol is also an interesting subject of future works. Besides,it seems appealing to provide different priorities to diverseapplications and subsequently analyse the behavior of theOMAC protocol operating on a QoS (quality of service) basedsystem.

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