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Analytical analysis of applying Aggregation with fragment retransmission on IEEE 802.11e EDCA

network in saturated conditions

Emna CHARFI, Lamia CHAARI, Lotfi KAMOUN Laboratory of Electronics and Information Technologies (LETI)

University of Sfax, National School of Engineering B.P.W, 3038 Sfax, Tunisia

Abstract— Wireless local area networking has experienced tremendous growth in the last ten years with the proliferation of IEEE 802.11 devices. The first IEEE 802.11 Medium Access Control (MAC) technique of 802.11 is called Distributed Coor-dination Function (DCF. In order to enhance the throughput, new mechanism access control techniques are developed by TGn group of IEEE 802.11n. The main purpose of AFR me-chanism is to retransmit only the corrupted fragment from large frame including multiple aggregated packets that leads to overhead reduction. This paper investigates a theoretical anal-ysis of Aggregation with fragment retransmission, based on computing saturation throughput for DCF and AFR mechan-isms. We provide a simple and accurate analytical model to calculate the Maximum MAC throughput to evaluate perfor-mances of AFR. We study the application of AFR on differen-tiated IEEE 802.11EDCA services.

Keywords: WLAN, AFR, DCF, EDCA, saturation throughput

I. INTRODUCTION Recently, Wireless Local Area Network (WLAN) technolo-gies have reached a large popularity that is still growing. In the 802.11 protocol, the fundamental medium access me-chanism is called Distributed Coordination Function DCF [1]. This is a random access scheme, based on the Carrier Sense Multiple Access with Collision Avoid-ance (CSMA/CA) protocol. The retransmission of the col-lided packets is managed according to binary exponential backoff rules. Since the original 802.11 specification was completed, a number of amendments have been introduced. The 802.11e [2] amendment addressed QoS features and enhanced MAC performance with new concepts such as TXOP and block acknowledgment (BA) [3]. Although physical improvement obtains high physical bit Rate, these mechanisms (DCF, TXOP and BA) don’t enhance the effi-ciency and the throughput. Through the IEEE 802.11n amendements [3] [4] new channel access techniques have been introduced to enhance the throughput and reduce the overhead. The most key issue suggested by IEEE802.11n is the Aggregation with Fragment Retransmission [5][6], which consists of aggregation and retransmission of mul-tiple packets are aggregated and transmitted in a single large frame. If errors occur during transmission, only the cor-rupted fragments of the frame are retransmitted. Compared

to previous designs, the approach (AFR) leads to overhead reduction. In the literature there are also some works that evaluates via simulations or analytical models the AFR and DCF schemes performance. In [7], Bianchi developed a simple analytical model to com-pute the saturation throughput performance of the 802.11 Distributed Coordination Function. This model is applied for any access scheme employed, i.e. for both Basic Access and RTS/CTS Access mechanisms. Performance of the ba-sic access method strongly depends on the system parame-ters, mainly minimum contention window and number of stations in the wireless network. In [8] the authors presented an analytical model to compute the 802.11 MAC layer satu-ration throughput for the DCF mechanism in both congested and error prone wireless channels. They have computed the optimal payload sizes according to the channel conditions and the results prove that transmission errors have a signifi-cant impact on the 802.11 MAC layer throughput perfor-mances. In [5] an analytic model is developed to evaluate the throughput and delay of AFR over a noisy channel, and to compare AFR with competing schemes in the literature. Authors prove that with zero-waiting we can achieve maxi-mum throughput. They investigate by simulations the im-pact of AFR on the performance of realistic application traf-fic with diverse requirements. Among the existing models designed for IEEE 802.11n, there are some works [9,10] developed to guarantee QoS for real time applications. Lin [9] proposed an analytical model to study the performance of IEEE 802.11n supporting voice and video services, with considering the frame aggregation and bidirectional trans-mission. He proves that these enhanced MAC mechanisms improves the network capacity by reducing the protocol overheads. Haifeng [10] investigates the performance of video transmission over 802.11n with frame aggregation scheme. He demonstrates that the optimal subframe size as well as the channel conditions improve throughput but have little effect on the video quality. He shows that with re-transmission policy, the video quality is improved without increasing the end-to-end delay. In this paper, an analytic model to evaluate saturation throughput and to compare AFR with previous schemes was developed. Optimal frame and fragment sizes are calculated

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using this model. In the same way, an analytic model is eva-luated to study the performance of AFR when the basic access mechanism is EDAC for quality of service applica-tions. The paper is outlined as follows. In section 2 we focus on the DCF scheme limitation and its similarities with other access mechanisms. We define the Saturation Throughput concept for DCF scheme, and in section 3 we provide an analytical technique to compute this performance for the AFR model and we present a comparison of throughput and efficiency between AFR and the other medium access tech-niques. In section 4 we study the possibility of using the AFR scheme with IEEE 802.11e where the basic access mechanism is EDCA. Finally we summarize our conclu-sions in section 5.

II. MOTIVATIONS AND LIMITATIONS

A. DCF limitations: The basic CSMA/CA mechanism used in the 802.11 MAC is referred to as the distributed coordination function (DCF). The access to the medium is randomly. When a frame ar-rives at the head of the transmission queue, if the channel is busy, the MAC waits until the medium becomes idle, then defers for an extra time interval, called the DCF Inter frame Space (DIFS). If the channel stays idle during the DIFS, the MAC then starts the backoff process by selecting a random backoff counter which is determined as a random integer over the interval [0,CW]. The frame is transmitted only when the random backoff timer has finished successfully. For each frame successful reception, the receiving station immediately acknowledges by sending an acknowledgement (ACK) frame. The ACK frame is transmitted after a short IFS (SIFS), which is shorter than the DIFS. If an ACK frame is not received after the data transmission, the frame is retransmitted after another random backoff. Fig.1 illu-strates the CSMA/CA principle. Based on the above de-scription we can deduce the overhead needed for each frame to guarantee a successful transmission. The frame overhead denoted p

ohT includes the time needed to transmit the PHY

headers (PCLP Preamble and PLCP Header) denoted phyhdrT ,

the MAC header (including FCS) denoted machdrT , the back-

off time cwT , and ACK transmission time denoted ackT . All parameters significations are listed in Table.1. The frame overhead is given by the following equation:

ackcwmac

hdrphy

hdrp

oh TTTTT +++=

DIFSTTSIFST pldack

phyhdrack +++= (1)

If we assume that the transmission was successful with the first attempt and no re-transmissions were needed. In this case the Efficiency denoted η is given by (2):

p

ohP

P

TTT+

=η , rate

PP Phy

LT = (2)

Figure 1. CSMA/CA mechanism

Where PL is the payload length and ratePhy is the physical rate. The CSMA/CA efficiency decreases when the physical rate increases this is due to phy

hdrT so the η → 0 when

ratePhy → ∞. Furthermore, for IEEE 802.11 DCF method, more increasing data frame length leads to enhance efficien-cy.

B. Enhanced Burst ACK and Block ACK limitations The EDCA (Enhanced Distributed Channel Access) pro-vides the ability to differentiate the time interval for which a station is authorized to hold the channel (transmission op-portunity, TXOP) [2] [3]. TXOP is a new approach to im-prove the efficiency of the protocol. This approach consists on grouping frames and sharing the access time in the chan-nel between several frames possessing the same destination. Thus, the frames are sent in a burst during the transmit op-portunity period (TXOP). Block Acknowledgement protocol was introduced with the 802.11e amendment to improve the efficiency by allowing data frame block transfer that are acknowledged with a single Block Acknowledgement (BA) frame instead of an ACK for each data frame. For Burst ACK and block ACK mechanisms, transmission requires one Backoff period for transmitting M frames (M is the Burst size). Fig.2 and Fig.3 presents respectively burst data and block ACK schemes. The average overhead per packet for Burst ACK and Block ACK mechanisms is given re-spectively by equation (3):

Burst ACK: ackcwmac

hdrphy

hdrp

oh TMTTTT +++=

Block ACM

TMT

TTT ackcwmachdr

phyhdr

poh +++= (3)

Figure 1. Burst data transmission scheme

Figure 2. Block ACK transmission scheme

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Based on these relations, we can deduce that backoff and ACK time per frame can be reduced with a reduction factor

equal to M1 . However the other overheads remain the

same as DCF mechanism. We can conclude that the effi-ciency for Burst ACK and bloc ACK mechanisms will de-crease when the physical rate increase.

C. Aggregation scheme limitations Two techniques were adopted in high throughput standard IEEE 802.11n. The first one is the Aggregated MAC Ser-vice Data Unit (A-MSDU), and the second one is Aggre-gated MAC Protocol Data Unit (AMPDU). Transmission through aggregated data is shown in Fig.4. With A-MSDU, MAC service data units (MSDUs) received from the LLC and destined for the same receiver and with the same service category (same traffic identifier or TID) may be accumulated and encapsulated in a single MAC pro-tocol data unit (MPDU).With A-MPDU, fully formed MAC PDUs are logically aggregated at the bottom of the MAC. A short MPDU delimiter is pretended to each MPDU and the aggregate presented to the PHY as the PSDU for transmis-sion in a single PPDU [4] [11] [12]. The aggregation ap-proach is enhancing the efficiency due to the reduction of the physical overheads. However, other question should be resolved which is the optimal frame size. In order to eva-luate the frame size effect in DCF mode we will compute the saturation throughput denoted DCF

AggS [7][8]. The”Saturation Throughput” is a fundamental performance metric defined as the limit reached by the system throughput as the offered load increases, and represents the maximum load that the system can carry in stable conditions. It is well known that several random access schemes exhibit an unst-able behavior. In particular, as the offered load increases, the throughput grows up to a maximum value, referred to as ”Maximum Throughput” given by (4):

acke

acke

datae

dataeccssII

fsDCFAgg

TPTPTPTPTP

LPS

++++= (4)

The transmission flow of a packet is explained by Fig.5. Where IT is the idle slot duration; sT is the duration in which the channel is sensed busy because of a successful transmission; cT is the duration in which the channel is sensed busy because of a collision. Since hidden terminal is not considered in this paper, only the data frames can get collided, and there are no collisions for ACK frames; data

eT , is the duration that the channel is sensed busy because of a data frame transmission error; ack

eT is the duration in which

Figure 3. Aggregated data transmission

),( II PT),( ss PT

),( cc PT

Figure 4. Flow of transmitting a packet

the channel is sensed busy because of an ACK frame trans-mission error. In summary, the five different time slots are given by (5):

σ=IT

DIFSSIFSTTTT ackpphy

hdrs +++++= δ2

δ+++= EIFSTTT pphy

hdrc

=dataeT cT

=ackeT sT (5)

IP , sP , cP , dataeP , and ack

eP can be calculated from the following Expression (6):

nIP )1( τ−=

)1)(1()1( 1 acke

datae

ns PPnP −−−= −ττ

nnc nP )1()1(1 τττ −−−−=

datae

ndatae pnP 1)1( −−= ττ

acke

datae

nacke ppnP )1()1( 1 −−= −ττ (6)

dataeP stands for the probability that a transmission error

occurs on a data frame in a time slot; this occurs when only one STA transmits in a time slot and the data frame is cor-rupted because of transmission errors. ack

eP refers the prob-ability that a data frame transmission is successful but the corresponding ACK frame is corrupted due to transmission errors. Thus, data

ep and ackep can be expressed using the

following two expressions, where bp represents the BER (Bit error rate). They are given by (7):

fLb

datae pP )1(1 −−=

ackLb

datae pP )1(1 −−= (7)

Fig.6 shows that the throughput attends peak values for a specific frame size. However, transmitting large frames in wireless networks over noisy channel leads to throughput decreasing when larger frames are used [13][14]. The big-gest aggregation scheme limitation resides in the necessity of retransmitting the whole frame even if only one bit is lost. Retransmission of only the erroneous part(s) of a frame could be expected to improve performance. This is a key motivation of this work.

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Figure 5. DCF with large packets

III. PERFORMANCE OF AGGREGATION WITH FRAGMENT RETRANSMISSION

The basic idea of the AFR (aggregation with fragment re-transmission scheme) is to aggregate packets from the upper layer into large frames. Packets that exceed the fragmenta-tion threshold are segmented into fragments. Then the MAC layer transmits the large frames and retransmits only frag-ments when errors are detected by their Frame Check Se-quence (FCSs). An example of the AFR scheme is shown in Fig. 4 [5] [6]. At the sender, every outgoing packet is seg-mented according to a fragmentation threshold. Before transmission, all the fragments are marked as ’undelivered’ and kept temporarily in a MAC layer sending-queue (Sq). MAC constructs a frame in the following way: It searches the Sq from head to tail for fragments marked as ’undeli-vered’ and aggregates them into the sending frame until either no ’undelivered’ fragments available or the frame size is large enough. Then, MAC transmits this frame according to the DCF procedure. AFR principle is given by Fig.7.

A. Saturation throughput In the AFR scheme [5], a MAC frame consists of a frame header and a frame body. In the new MAC header, all the fields of the DCF MAC header remain unchanged, and three fields are added fragment size, fragment number and a spare field. The spare field is left for future extension and main-taining alignment. The frame body consists of fragment-headers, fragment bodies and the corresponding FCSs. The fragment-headers in the frame body has a variable size.

Figure 6. AFR scheme

The fragment header consists of six fields: packet The frag-ment header consists of six fields: packet ID (pID), packet length (pLEN ), startPos, offset, spare and FCS. For the AFR mechanisms, the saturation throughput [5] is given by equation (8):

AFRc

AFRc

AFRs

AFRs

AFRI

AFRI

fragef

AFRsDCF

AFRTPTPTP

PLPS

++

−=

)1( (8)

Where AFRIT is the idle duration, AFR

sT is the duration of

successful or corrupted transmission, and AFRcT is the colli-

sion duration. These timing parameters are given by (9):

σ=AFRIT

ackphy

hdrfphy

hdrAFR

s TDIFSTSIFSTTT +++++=

DIFSTTT fphy

hdrAFR

c ++= (9)

frageP represents the fragment error rate, and it is expressed

by (10):

FCSfrag LLb

frage pP +−−= )1(1 (10)

AFRIP , AFR

sP , AFRcP are the probabilities of Idle, a success-

ful or an erroneous transmission and Collision events re-spectively. They are given by (11):

nAFRIP )1( τ−=

1)1( −−= nAFRs nP ττ

AFRI

AFRs

AFRc PPP −−= 1 (11)

Where τ the transmission probability in a virtual slot is is computed based on Bianchi model [7] by resolving the sys-tem of equation (12) below:

)21()1)(21()21(2

mppWWpp

−++−−=τ (12)

1)1(1 −−−= np τ

We have evaluated the saturation throughput for different fragment length and results are illustrated by Fig.8 and Fig.9. Since we don’t use a noisy channel (BER <10-2), the saturation throughput can achieve lower value when the fragment size is incremented, this is illustrated by Fig.8. The AFR scheme can achieve higher values of saturation throughput when using higher ratePhy , this is illustrated by Fig.9. In section2 we have demonstrate that the throughput attends peak values for a specific frame size. We have done the same study for the AFR model. It can be seen from Fig.8 that AFR fundamentally changes the throughput scaling behavior in a noisy channel and DCF

AFRS reaches maximum throughput under different BER conditions. In the AFR scheme, under all channel states, the throughput increases

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with frame sizes. This is because we reduce the physical header duration effect across more fragments, while the per-fragment error probability remains constant. Increasing packet size when using AFR mechanism leads to enhancing the throughput, contrary to DCF where the throughput exhi-bits a maximum value as frame size is varied with the max-imum depending on the BER.

Figure 7. AFR saturation throughput via BER

Figure 8. AFR saturation throughput via PHYrate

Figure 9. AFR via DCF

B. Comparative study between AFR and others transmission schemes

The AFR scheme is the most recent technique used for transmitting data in high throughput. Before the apparition of this method, there was several access mechanisms pro-posed to ameliorate performance of data transmitting. Our goal is to compare AFR with these previous access methods [5] shown in Fig.11. We suppose that the acknowledgment of succeeded transmission is accomplished by ACK frame in all the mechanisms. In the PAC, Aggregation and AFR scheme, data are accumulated and transmitted in one frame. However, in the Burst ACK and Block ACK scheme, mul-tiple frames are transmitted at each transmission opportuni-ty. The general expression of the maximum throughput is defined by (13):

total

packetep

T

PLMT = (13)

where totalT refers to the total duration of transmitting a packet assuming in this part that one frame includes some packets depending on the transmission scheme. For Aggre-gation scheme [11][12][15], a special delimiter is used for each packet in a frame, and all aggregated packet are trans-mitted using a single header. Since one frame contains a number of aggregated packets equal to k, maximum throughput is given by (14):

ψχ kPL

MTpacket

epAgg +

−=

)1(

cwackphy

hdr TTSIFST +++=χ

p

f

LL

k =

rate

PADpMD

PhyLLL ++

=ψ (14)

In the PAC scheme [16], each packet in a frame is preceded by a sub-physical-header, which is of 12¹s duration with an IEEE 802.11a PHY. Since one frame contains a number of

Figure 10. IEEE 802.11 access mechanisms

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aggregated packets equal to k, maximum throughput is giv-en by (15):

ψχ kPL

MTpacket

epPAC +

−=

)1(

cwacksubphy

hdrphy

hdr TTSIFSTkT +++−+= )1(χ

p

f

LL

k =

rate

PADpMD

PhyLLL ++

=ψ (15)

With Block ACK scheme [2] [17], a block of data frames is transmitted in a transmit opportunity period, and the whole is acknowledged with a single Block Acknowledgement (BA), and a PHY header is transmitted before each packet. Since K packets are transmitted with SIFS time between them, and the length of the frame obtained by these k pack-ets is known, then maximum throughput is given by (16):

rate

p

packetep

BA

PhyL

PLMT

+

−=

χ

)1(

cwBABARphy

hdr TTSIFSTSIFSTk +++++= )(χ

p

f

LL

k = (16)

For Data Burst scheme [2] [3], frames are sent in a burst during the period of TXOP. Each frame is acknowledged by an ACK frame, SIFS after the transmission of the data. A PHY header is transmitted before each packet, thus Maxi-mum throughput is given by (17):

ψχ kPL

MTpacket

epBA +

−=

)1(

cwTDIFS +=χ

p

f

LL

k =

+++= ackphy

hdr TSIFSTψrate

p

PhyL

(17)

Results are shown in Fig.12 and Fig.13, and they illustrate respectively the throughput and efficiency of all theses me-chanisms. From this figure, it can be seen that the schemes based on aggregation as AFR, Aggregation and PAC, con-sistently outperform the Burst and Block ACK schemes. On the other hand, it can also be seen that the PAC scheme has the lowest throughput against schemes which use aggre-gation. This is caused by the introduction of sub-physical-header which causes long duration of transmitting. AFR achieves the highest throughput over all others access me-thods. In fact, AFR is the only scheme that uses both frag-mentation and aggregation.

Figure 11. Schemes’s throughput performance

Figure 12. Scheme’s efficiency performance

IV. PERFORMANCE OF AFR BASED ON IEEE 802.11E EDCA

Contrarily to the previous sections where we have supposed that all stations send the same type of traffic, we propose in this section that we have two type of traffic: voice and best-effort data.

A. Definitions and hypothesis

In IEEE 802.11e, EDCA (Enhanced Distributed Channel Access) is the basic MAC access mechanism, we propose in this section to extend it for the aggregation with fragment retransmission scheme AFR. EDCA [18] considers two ba-sic priority mechanisms for accessing the channel: different per-class setting of the CW backoff parameters (CWmin and CWmax), and different per-class setting of the AIFS (arbi-tration inter frame space) after which a transmission may occur. Packets arriving at the MAC layer are divided into four different access categories (ACs), which represent four different AIFSs for monitoring idle channel and different values of CWs for the backoff time extraction. For this work, we consider voice and best-effort data which are dif-ferentiated by AIFS. We consider: • The inter frame space is given by (18):

slotTiAIFSNSIFSiAIFS *][][ += (18)

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• Let C denotes the difference between AIFSs of two access categories:

][][ AAIFSBAIFSC −= (19)

• The EIFS time is defined by (20):

][][ iAIFSNTSIFSiEIFS ack ++= (20)

• Let AC[A] and AC[B] denote the voice and best effort respectively, thus AC[A] has the higher priority, and AC[B] has the lower one.

• We suppose that the fragment size is equal to the size of the data of AC. When AC[A] or AC[B] gains access to the channel, it transmits data with the AFR scheme me-thod.

• Let An and Bn denote the number of stations of

AC[A] and AC[B] respectively. • The probability that a station transmits in a slot time is

constant. • The fragment size is equal to (21):

bytesACL Afrag 160)( =

bytesACL Afrag 1500)( = (21)

Let Aτ and Bτ denote the probability that AC[A] and

AC[B] transmit respectively, they are given by (22):

)21())2(1]([min

A

mAA

A pppACW

−−−

=τ

)21())2(1)(.1]([min

B

mBBB

B ppppCBCW

−−−−

=τ

BA nB

nAAp )1()1(1 1 ττ −−−= −

AB nA

nBBp )1()1(1 1 ττ −−−= − (22)

The transmission scheme of AC[A] and AC[B] is detailed in fig.14. In the zone1, )1(:zonetrP is the probability that at least one station of AC[A] transmits. In zone2, AC[A] and AC[B] can transmit, that’s why we define by )2(:zonetrP the probability that at least one station transmits [18] [19]. They are given by (23):

AnAzonetrP )1(1)1(: τ−−=

BA nB

nAzonetrP )1()1(1)2(: ττ −−−= (23)

Figure 13. EDCA transmission zones

Let )1(:zoneidleP and )2(:zoneidleP denote the probabilities that a

station from AC[A] or AC[B] is idle in zone1 and zone2 respectively. They are given by (24):

)1(:)1(: 1 zonetrzoneidle PP −=

)2(:)2(: 1 zonetrzoneidle PP −= (24)

The probabilities that stations from AC[A] or AC[B] suc-cessfully transmit data in zone1 and zone 2 are given by (25):

1)1(: )1( −−= An

AAAzonesuccA nP ττ BA n

Bn

AAAzonesuccA nP )1()1( 1)2(: τττ −−= −

0)1(: =zonesuccBP AB n

An

BBBzonesuccB nP )1()1( 1)2(: τττ −−= − (25)

The collision probabilities in both zones are given by (26):

)1(:)1(:)1(:)1(: zonesuccBzonesuccAzonetrzonecol PPPP −−=

)2(:)2(:)2(:)2(: zonesuccBzonesuccAzonetrzonecol PPPP −−= (26)

Let EDCAIT , EDCA

sT and EDCAcT denote the idle, success, and

collision duration respectively. In the EDCA scheme, they are given by (27):

σ=EDCAIT

minAIFSSIFSTTTT ackpphy

hdrEDCA

s ++++=

EIFSTTT pphy

hdrEDCA

c ++= (27)

Let EDCAAS and EDCA

BS denote the saturation throughput of AC[A] and AC[B] respectively.

EDCAc

EDCAc

EDCAs

EDCAs

EDCAI

EDCAI

ApsuccEDCA

ATPTPTP

LPS A

++=

EDCAc

EDCAc

EDCAs

EDCAs

EDCAI

EDCAI

BpsuccEDCA

BTPTPTP

LPS B

++= (28)

AsuccP ,BsuccP EDCA

IP , EDCAsP , and EDCA

cP are given by (29):

)2(:)1(: zonesuccAzonesuccAsucc PPPA

+=

)2(:)1(: zonesuccBzonesuccBsucc PPPB

+=

)2(:)1(: zoneidlezoneidleEDCA

I PPP +=

BA succsuccEDCA

s PPP +=

)2(:)1(: zonecolzonecolEDCA

c PPP += (29)

B. Comparative study between DCF and EDCA We have shown previously that the achievable throughput of DCF scheme reaches maximum values for a given packet size, and that was the major motivation of this section. We

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aim to study the impact of increasing packet size for both voice and best effort flows under IEEE 802.11e differen-tiated mechanism EDCA. Contrarily to DCF, Fig.15 proves that achievable throughput increases as well as packet size increases too. Moreover, it becomes saturated for large transmitted packets. Perversely to DCF where AFR was needed to solve the decreased throughput for large packets, EDCA seems to be efficient even for important packet sizes. However, AFR is required to reduce overheads since we are under very high throughput networks IEEE 802.11n. Then, AFR may be based on EDCA medium access rather than DCF.

C. Comparative study between EDCA and AFR based on EDCA

The goal of this part is to compare the performance of the AFR scheme studied in the previous section under IEEE 802.11e EDCA scheme. We suppose that in the AFR/EDCA scheme, when an AC gains access to the medium, the first AC which gains access to the medium start to transmit ag-gregated data with fragment retransmission, and the latter transmits in the same manner when it reaches its backoff period. For AFR/EDCA scheme, for a given size of one

Figure 14. EDCA saturation throughput

Figure 15. AFR/EDCA saturation throughput

frame (16384 bytes), the fragment size for voice and best effort flows is:

Voice: 186 fragments Best effort: 104 fragments

Results are illustrated in Fig.16; achievable throughput reaches higher values when AFR is included. Although EDCA guarantees stability of throughput for large transmit-ted packet sizes, but it is disable to provide maximum reached throughput as AFR/EDCA does. For example, for voice traffics, achievable throughput is equal to 350 Mbps for AFR/EDCA but it is limited to 30 Mbps for EDCA. Therefore, AFR scheme is efficient effect on differentiated medium access such as EDCA especially when packets siz-es are so large.

V. CCONCLUSIONS In this paper we have presented an analytical model for AFR scheme under both IEEE 802.11 DCF and IEEE 802.11e EDCA medium access mechanisms. We considered a WLAN with large size transmitted packets to presume the efficiency of AFR scheme for next WLANs generations comparing to others IEEE 802.11 schemes. Our analysis proves that AFR/DCF solves the DCF limitation, which resides on the decreased throughput for large packet sizes. AFR/DCF provides stability for achievable throughput in the case that packets are so large. Contrarily to DCF, EDCA access mechanism, throughput stabilizes for important packet sizes. However, simulation results prove that with AFR scheme, throughput reaches higher values for IEEE 802.11e EDCA.

Table I CSMA /CA parameters Parameter Signification

pohT Overhead for transmitting one packet

phyhdrT Time to transmit the PHY headers of one

frame MAC

hdrT Time to transmit the MAC headers of one frame

fraghdrT Time to transmit the fragment headers of

one frame

cwT Contention backoff period

ackT Overhead of transmitting an ACK frame

pT Time duration to transmit one packet

δ Propagation delay (1µs) σ Time slot (9µs) n Number of stations m Retransmission limit

fL Payload size in one frame (byte)

pL Packet size (bytes)

fragL Fragment size (bytes)

An Number of stations AC[A] (10)

Bn Number of stations AC[B] (10)

References

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[3] Eldad perahia, Robert Stacey,”Next Generation Wireless LANs Throughput, robustness, and reliability in 802.11n”, Cambridge Uni-versity Press 2008, ISBN-13 978-0-521-88584-3 , eBook (EBL)

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