Network-Load Aware Adaptive Channel Access Control for WLAN

doi:10.4236/cn.2013.53B2085

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Communications and Network, 2013, 5, 461-466

http://dx.doi.org/10.4236/cn.2013.53B2085 Published Online September 2013 (http://www.scirp.org/journal/cn)

Network-Load A ware Adaptive Channel Access

Contr ol for WLAN*

Xiaoyan Wu1, Qinghe Du1,2, Pinyi Ren1

1School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China

2National Mobile Communications Research Laboratory of Southeast University, Nanjing, China

Email: [email protected], duqinghe@mail.xjtu.edu.cn, [email protected]

Received June 2013

ABSTRACT

Wireless local area network (WLAN) brings us a low cost and high bandwidth experience and thus plays a critically

important role in current/future networks to support high-rate transmissions. To better pro vide quality-of-servic e (QoS)

for WLAN users, we in this paper propose an improved scheme called “A-EDCA” (adaptive EDCA), based on en-

hanced distributed channel access (EDCA) of IEEE 802.11e under the infrastructure mode. Our proposed scheme aims

at efficiently adapting the transmission ove r WLAN to the time-varyin g network condition s and mitigating the competi-

tion ability unfairness between access point (AP) and non-AP stations (STAs). Specifically, all non -AP STAs adaptive-

ly modify the contention window based on the network condition. Moreover, AP skips the backoff phase by setting its

backoff coun ter as zero when non-AP STA completes transmission successfully to re lieve the unfairness. At last, sim u-

lation results d emonstra t e the effectivene ss of the pro p os ed appr oa c h .

Keywords: Quality of Service (QoS); IEEE 802.11e; Enhanced Distributed Channel Access (EDCA)

1. Introduction

Due to the characteristics of the high bandwidth, low cost

and easy deployment, WLAN has surrounded us ev ery-

where. WLAN has two kinds of modes, one with AP and

the other without AP. The former mode is adopted in the

most practical deployments. Hence, we consider the mode

with AP (also called infrastructure mode). Traditional IEEE

802.11 protocol offers us two access policies, namely,

DCF (distributed coordination function) and PCF (point

coordination function) [1]. DCF is a policy based on

competition and PCF is based on polling. Both DCF and

PCF cannot provide QoS guarantees. To accommodate

QoS, IEEE 802.11e is proposed including EDCA (en-

hanced distributed channel access) mode and HCCA (HCF

controlled channel access) mode [2]. Most network de-

vices are based on EDCA due to its easy realization and

good expansibility.

Therefore, we only discuss EDCA policy in this paper.

In EDCA, some important parameters including AC (access

category), AIFS (arbitrary inter-frame space) and TXOP-

limit (transmission opportunity limit) are adopted. Differ-

ent services have different parameters for QoS support.

However, there a re sti ll some problems whe n usi ng EDCA.

Specifically, stations may suffer from performance de-

gradations and radio resources are not fully utilized due

to the fixed parameter settings. When the number of sta-

tions increases, the probability of collisions increases

leading to frequent retransmissions and a decrease of the

overall throughput [3]. In addition, there exists unfairness

of channel access competition ability between AP and

non-AP stations (STAs) which is because that AP almost

has the same channel access competition ability with one

non-AP STA while the number of non-AP STAs is far

larger than that of AP. This causes that AP cannot handle

the data in time.

For providing better QoS, many analytical approaches

are proposed. Bianchi [4] developed a simple DTMC (dis-

crete time Markov chain) and the saturation throughput

was obtained by applying regenerative analysis to a ge-

neric slot time. In [5], authors represented an analytical

model to analyze the performance of EDCA. Cali et al.

[6] employed renewal theory to analyze a p-persistent

variant of DCF with persistence factor p derived from the

C.W. Tay et al. [7] instead used an average value ma-

thematical method to model the DCF backoff procedure

The research reported in this paper was supported by the National

Natural Science Foundation

of China under Grant No. 61102078, the

National Science and Technology Major Project under Grant No.

2013ZX03002003-

004, the Specialized Res earch Fu nd f or the Doctoral

Program of Higher Education under Grant No. 20110201120014, the

Open Research Fund of N

ational Mobile Communications Research

Laboratory, Southeast Universit y (No.

2011D10), and the Fundamental

Research Funds for the Central University.

X. Y. WU ET AL.

462

and to calculate the average number of interruptions that

the backoff timer experienced. The throughput and delay

for EDCA were derived based on Markov Chain [8,9]. In

order to realize QoS guarantees, researchers have pro-

posed many approaches. A large proportion of these ap-

proaches are based on EDCA [10-15].

In this paper, we propose an improved scheme “A-

EDCA” based on EDCA with a low computation com-

plexity. Firstly, we adjust the contention window (CW)

adaptively according to the current network load condi-

tion so as to make full use of the wireless channel re-

source. Secondly, we adjust channel access policy of AP.

The remainder of this paper is organized as follows: in

Section 2, we present the system model and the brief

summary of EDCA policy. The design and detailed pro-

cedures of our proposed scheme are given in Section 3.

The performance analysis is given in Section 4. We show

and analyze the simulation results in Section 5. Finally,

we conclude our work in Section 6.

2. System Model

2.1. System Model

We consider the infrastructure mode of WLAN. There

are N non-AP STAs distributed randomly and one AP in

WLAN. Each non-AP STA transmits/receives packets

through AP and there are no packet transmissions be-

tween non-AP STAs. We assume that the channel is ideal

and that all STAs (including AP and non-AP STAs) are

still for simplicity. The scenario is depicted in Figu re 1.

Without loss of generality, we consider two kinds of trafﬁcs:

voice trafﬁc and background trafﬁc. As we know, voice

trafﬁc is delay-sensitive and has higher priority than back-

ground trafﬁc. Because some problems exist when ED-

CA policy is used directly, we propose an improved chan-

nel access scheme called “A-EDCA”.

2.2. Enhanced Distributed Channel Access

This subsection brieﬂy summarizes the operations of IEEE

Figure 1. Scenario with N non-AP STAs and one AP.

802.11e EDCA. For detailed description, readers may

refer to [1,2]. EDCA is an enhanced policy of DCF.

There are some important notions, as depicted by Table

1. The packets from upper layer are classified into four

ACs. Each AC is corresponding to one queue. Each STA

has four queues and each queue has a backoff counter.

The mapping from upper layer to medium access control

(MAC) layer is shown as Figure 2 (refer to [2]). In EDCA,

the channel acces s process is described as following. STA

which has packets to send senses the channel. If the

channel is idle for AIFS period, th e STA transmits pack-

ets immediately. If the channel is busy, the backoff coun-

ter is initialized and set as a value based on the backoff

mechanism. The STA enters the backoff phase after it

senses the channel idle for AIFS period. In the backoff

phase, the backoff counter decreases by one if the chan-

nel is idle for one time slot (TS) consecutively. If the

channel becomes busy, the backoff counter is suspended.

The counter resumes when the STA senses the channel

idle for AIFS period again. The STA transmits packets if

the backoff counter decreases to zero. The node can tr ans-

mit multiple packets during TXOP. When the STA suc-

cessfully transmits data, its CW is set as CWmin and its

backoff counter is set as a value from [0, CW − 1] ran-

domly. The channel access process is illustrated as Fig-

ure 3 (refer to [2] ).

There exist two kinds of collisions in EDCA, namely,

virtual collisions and inter-STA collisions. The former

occurs when more than two queues (including two queues)

in a STA simultaneously attempt to transmit packets.

Table 1. Notions and Comments.

Notion Comment

TS time slot

SIFS short inter-frame space

DIFS distributed inter-frame space

AIFS arbitrary inter-frame space

CW contention window

CWmin minimum contention window

AC access category

TXOP transmission opportunity

retrylim maximum retransmission time

Figure 2. The mapping from upper layer to medium access

control (MAC) layer.

X. Y. WU ET AL.

463

Figure 3. Channel Access Process in Enhanced Distributed

Channel Access (EDCA) .

The queue with the highest priority wins and attempts to

transmit data while the others do not send data but upd ate

their CWs according to the backoff mechanism depicted

in Equations (1)-(2) and continue to sense the channel.

(1)

(2)

The latter collision happens when there are more than

two STAs (including two STAs) simultaneously transmit

data. The STAs participating in the collision all update

their CWs according to the backoff mechanism depicted

in Equations (1)-(2), and increase retry number (denoted

by retrynum) by one. Then all stations sense the channel

for the next attempt again.

3. A-EDCA Channel Access Policy

In this section, we present A-EDCA channel access pol-

icy. To begin with, we present the general idea of

A-EDCA. Then the detailed description is given.

3.1. Proposed A-EDCA Channel Access Policy

There exist problems when EDCA policy is used directly.

It cannot indicate how crowded the channel becomes that

a certain station either succeeds to transmit packets or

collides with others. In order to adapt to the network load

condition, we have to find a metric that can reflect what

the current load condition is like. From the backoff me-

chanism we know that the more crowded the WLAN is,

the bigger the retrynum becomes. Therefore, we adopt the

average value of retrynum (denoted by E[retrynum]) as the

metric. In order to provide AP with the bigger channel

access opportunity to relieve th e un fair ness, we adjust the

channel access policy of AP. After a certain non-AP STA

transmits packets successfully we set the backoff counter

of AP as zero so as to make AP skip the backoff phase

and attempt to transmit data in the next time.

3.2. Detailed Description of A-EDCA

3.2.1. CW Value Adjustment

When a certain STA (including AP) succeeds to transmit

packets we calculate E[retrynum] using Equation (3).

(3)

Here, M is the number of stations whose retrynum > 0.

The channel is not busy if E[retrynum] and the

channel becomes crowded if E[retrynum] . We com-

pare E[retrynum] with the threshold (denoted by ) and

update CW according to Equation (4).

(4)

When collision occurs, we compute E[retrynum] using

Equation (3) and update the CW of the stations partici-

pating in the collision using Equations (1) (2) and (5).

(5)

3.2.2. Channel Access Policy Adjustment for AP

When a non-AP STA succeeds to transmit packets, AP

sets its backoff counter as zero which makes AP skip the

backoff phase. Then AP can attempt to transmit data af-

ter AIFS period during which the channel is continuously

idle. This adjustment relieves the unfairness between the

channel access competition ability of non-AP STAs and

that of AP, depicted in Figure 4. We emphasize that the

policy that we set backoff counter of AP as zero is

adopted only when non-AP STA completes transmission

successfully, which is for the sake of avoiding AP occu-

pying the channel all the time.

The algorithm is presented in pseudo-code in Table 2.

4. Performance Analysis

The section is based on [8]. For simplicity, we only con-

sider two ACs without loss of generality, namely, AC0

which prese nt s bac kground traffic a nd AC3 which presents

voice traffic. We assume that each station only includes

one AC. In order to obtain the expressions of perfor-

mance metrics, some equations are given as follows. The

probability that a station of ACi transmits data in a

slot is shown by

Figure 4. Channel Access Policy Adjustment of AP in A-EDCA.

X. Y. WU ET AL.

464

Table 2. A-EDCA Algorithm.

Algorithm 1. A-EDCA

01. Initialization

02. if Transmission completes successfully for nodei then

03. Calculate E[retrynum] using equation (3);

04. if nodei is AP then

05. if E[retrynum]

then

06. CW(i)

←

CWmin

07. else

08. CW(i) does not change;

09. end if

10. else

11. Set backoff counter of AP as zero;

12. Do steps 5-9;

13. end if

14. end if

15. if Collision occurs in which nodei,j,k,… (denoted by A) partici-

pate then

16. Calculate E[retrynum] using equation (3);

17. if E[retrynum]

≥

18. Update CWs of STAs according to (1) and (2)

19. else

20. CWs do not change;

21. end if

22. end if

0,0,0

0,0

(1 )0,

(1 )

13.

−=

−



=−

=

−



(6)

where r is retrylim, p is the collision probability that a

frame encounters,

0,0,0

and

0,0

are steady prob abili-

ties referred to [8], and PI is the probability that the

channel is idle in a time slot, given by PI = q1/(1+q1 − q2).

Here, q1 and q2 is the probability that there are no trans-

missions in a slot during an AIFS period and during oth er

period respectively, depicted as follows:

203

(1 )

(1) (1)

ττ

= −

=−−

(7)

where ni is the number of stations of ACi. The probability

PB that a slot is busy is given by PB = 1 − PI. The proba-

bility Psi that a station of ACi succeeds to transmit data in

a slot time is shown by

(1) (1)0,

(1 )

(1) (1)3.

ii in

SiiiiB

ii i

Pn P

ττ τ

ττ

ττ τ

−

−− =



= −



+− −=



(8)

The probability PC that collisions happen in a slot time

is given by

C IS

P PP=−−

According to [8], throughput (denoted by S) is pre-

sented as follows:

[ ][]

SPEPE TS= ∗

(9 )

where PS is the probability that a successful transmission

occurs in a slot time depicted by

03Ss s

PPP= +

[]EP

is the average size of frame, and E[TS] is the average

length of a time slot given by E[TS] = PI

+ PSTS +

PCTC. Here,

is the length of a time slot, TS is the av-

erage time of successful transmission, and TC is the av-

erage time of collision. The TS and TC in the basic mode

are presented by

[ ]

C timeout

THE PSIFSACK

THE PSIFSACKAIFS

=+++

=++++

(10)

where H is the size including both MAC head and PHY

head, E[P] is the size of frame. From (9) we know that S

is a decrea s i ng functi on of collision pr obabili t y p.

The mean access delay (denoted by E[D]) is shown as

follows:

()

[][ ]

ir i

EDE TS



−



= ⋅



−





∑

(11)

We can derive that E[D] is an increasing function of

collision probability p.

By using A-EDCA policy without considering AP pol-

icy the collision probability can be decreased efficiently

especially when the number of stations becomes large.

From (9) (11) we can know that the throughput is im-

proved and that delay is decreased by using A-EDCA

policy. Taking AP policy adjustment into account, we can

know that the downlin k throughput can be improved and

that the unfairness can be relieved.

5. Simulation Results

We adopt throughput, mean end-to-end delay and fair-

ness of throughput to compare the performance between

A-EDCA policy and EDCA policy. The fairness of

throughput (denoted by I) is defined as the ratio of the

difference between uplink throughput and downlink

throughput to the throughput of uplink, depicted as Equ-

ation (12).

( )

up down up

ITT T= −

(12)

where Tup and Tdown denote uplink throughput and down-

link throughput, respectively.

We make some assumptions in our simulation. The

channel is ideal and packet loss ratio (PLR) is only in-

troduced by the event that the retransmission time is up

to retrylim. Only two kinds of traffic are considered which

are voice traffic (denoted by AC3) and background traffic

(denoted by AC0). TXOP is set as zero for all nodes,

which means that the node occupying the channel suc-

cessfully can o nly tr ans mit on e p acket. We adopt the basic

access mode. Simulation parameters are listed in Ta ble 3.

Due to the dynamic adjustment of CW and AP channel

access policy adjustment, the probability of collisions can

X. Y. WU ET AL.

465

be decreased and AP can get more opportunity to access

the shared channel, which improves the performance of

throughput, end-to-end delay and relieves the unfairness

between AP a nd non-AP STAs.

Figure 5 shows the performance comparison between

Table 3. Simulation Parameters.

Parameters value

PHY Header 192 bits

MAC Header 272 bits

SIFS 1 Time Slot

DIFS 3 Time Slot

AIFSN[AC0] 7

AIFSN[AC3] 2

ACK Frame PHY Header + 112 bits

ACKtimeout ACK Frame + DIFS

Data Rate 11 Mbps

Time Slot 20 μs

retrylim 7

AC0 1500 bytes

AC3 200 bytes

CW[AC0] {31, 63, 127, 255, 511, 1023}

CW[AC3] {7, 15, 31, 63, 127, 255}

(a)

(b)

Figure 5. (a) Comparison of Throughput When No. of STAs

Changes; (b) Comparison of Mean End-to-End Delay When

No. of STAs Changes.

A-EDC A a nd EDCA whe n t he num be r of stations changes.

Figure 5(a) illustrates that throughput under A-ED CA is

larger than that under EDCA. Figure 5(b) shows that

mean end-to-end delay becomes smaller under A-EDCA.

From Fig u res 6(a) and (b) we can see that our A-EDCA

brings performance improvements when the packet ar-

rival rate changes. The cumulative distribution function

of mean end-to-end delay is shown in Figure 7(a). We

can see that about 90 percent of delay is under 400 ms

under A-EDCA policy while it is 500 ms under EDCA

policy. Figure 7(b) shows us that the unfairness is re-

lieved under A-EDCA especially when the number of

stations is large.

6. Conclusion

This paper has considered the problem of IEEE 802.11e

EDCA policy which includes not adapting to the time-

varying network condition due to the fixed parameter

settings and the channel competition ability unfairness

between AP and non-AP STAs. In order to solve the

problem, we proposed an improved scheme “A-EDCA”.

(a)

(b)

Figure 6. ( a) C omp arison of Thr oughput When Packet Arrival

Rate Changes; (b) Comparison of Mean End-to-End Delay

When Packet Arrival Rate Changes.

50 55 60 65 70 75 80

16 x 10

Number of St aion s

Thr o ug hp ut (bit/s )

v oice under EDCA

v oice under A-EDCA

data und e r EDCA

data under A-EDCA

tot al under EDCA

tot al under A- EDCA

50 55 6065 70 75 80

100

150

200

250

300

350

Number of St aion s

Me an End -to-End Delay (ms)

v oice under EDCA

v oice under A-EDCA

data und e r EDCA

data under A-EDCA

12345678

0.2

0.4

0.6

0.8

1.2

1.4

1.6

1.8

2.2 x 105

Packet Ar r iv al Rate

Thr o ug hp ut (bit/s )

voice under EDCA

voice under A-EDCA

data un de r EDCA

data under A- EDCA

total under EDCA

total under A-EDCA

12345678

100

150

200

250

300

350

400

Packet Ar r iv al Rate

Me an End-to -End Delay (ms )

voice under EDCA

voice under A-EDCA

data un de r EDCA

data under A- EDCA

X. Y. WU ET AL.

466

(a)

(b)

Figure 7. (a) Comparison for Delay CDF; (b) Comparison

for Fairness.

In the scheme CW of the node is adjusted dynamically

for the sake of adapting to the current network condition,

and AP skips the backoff phase by setting its backoff

counter as zero when non-AP STA completes transmis-

sion successfully to relieve the unfairness between chan-

nel access competition ability of AP and that of non-AP

STAs. Through the simulations, we verify the effective-

ness of our approach. The performances of both through-

put and mean end-to-end delay are improved effectively.

The unfairness is relieved to a large extent. Future re-

search will focus on how to satisfy hard QoS require-

ments and how different kinds of access networks such

as WLAN, LTE-A provide better services for users to-

gether.

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100 200 300400500 600

100

Mean End-to- End Del ay (ms)

Cumulative Fract ion (% )

EDCA

AEDCA

50 55 6065 70 7580

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

N um ber of St aions

Fairn es s be twee n Uplink a nd Downlink

EDCA

A-EDCA