The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07)
AN ADAPTIVE MECHANISM FOR HIGH EFFICIENCY AND FAIRNESS IN IEEE
802.11 WIRELESS LANS
Orestis Tsigkas∗
Aristotle University of Thessaloniki
Thessaloniki, Greece
A BSTRACT
Wireless Local Area networks own their popularity mainly
to the robust characteristics of distributed medium access
schemes. However, as new user applications diverge from the
traditional data-centric model, the introduction of distributed
medium access methods that achieve high efficiency in terms
of both throughput and fairness becomes of utmost importance.
IEEE 802.11 is the most widely used access scheme for wireless networks. In this paper, we address a shortcoming of IEEE
802.11 as indicated by previous studies, namely the inability
of the protocol to adapt to different working conditions. We
study and evaluate a low complexity mechanism that allows a
network employing the IEEE 802.11 protocol to adapt its operating parameters according to the offered load. Simulation
studies further document and confirm the high throughput and
fairness performance of the proposed scheme.
I
I NTRODUCTION
Wireless Local Area Networks have known an increasing popularity during the past few years. Medium access represents
one of the most critical building blocks regarding the performance of a distributed wireless LAN. By arbitrating access to
the shared channel, medium access schemes have a direct impact on the efficient usage of the available raw bandwidth. According to distributed Medium Access Control (MAC) protocols, packet transmissions take place in a completely stochastic
way, with minimal or totally absent coordination between the
stations participating in the network. Consequently, there exists
a probability that multiple transmissions take place simultaneously, resulting in erroneous reception. In order to ensure that
the scarce wireless resources are not wasted, medium access
protocols should possess a number of desirable characteristics;
low collision rates, low overhead, fairness and robustness. Recently, another attribute has been added to this list, namely that
of service differentiation.
The IEEE 802.11 protocol [1] is the dominant medium access scheme used for channel access in wireless local area networks (WLANs). The IEEE 802.11 MAC protocol adopts the
Distributed Coordination Function (DCF) with a binary exponential backoff as a medium access control mechanism. DCF
employs the concept of carrier sensing to prevent network stations from transmitting, when they sense that a transmission is
already in progress. Previous studies have indicated that DCF,
the medium access scheme of IEEE 802.11, is sensitive to different working conditions. The parameters of DCF are fixed
and determined by the standard. While those parameters were
∗ Partially supported by the Hellenic State Scholarships Foundation (I.K.Y.).
c
1-4244-1144-0/07/$25.002007
IEEE
Fotini-Niovi Pavlidou
Aristotle University of Thessaloniki
Thessaloniki, Greece
chosen to provide a good protocol performance, they fail to
provide an optimum utilization of the channel, in particular under heavy load scenarios. Since the performance of DCF is
largely dependant on its backoff mechanism, several mechanisms have been proposed to adapt the working parameters of
DCF to the number of contending stations.
In this paper, we propose a dynamic adaptation of the DCF
access scheme that allows it to achieve high medium utilization under both low and high traffic conditions. Extensive simulation results demonstrate that the proposed scheme significantly improves the performance of 802.11 DCF, and outperforms other proposed schemes, with respect to both throughput
and fairness.
The rest of the paper is structured as follows. In Section II,
we provide an overview of DCF and existing schemes that allow it to adapt to traffic conditions. Section III provides the
motivation of our work and describes the design of the proposed protocol. Section IV presents the performance evaluation of the proposed scheme through simulation experiments,
while Section V concludes the paper.
II
BACKGROUND WORK
This section reviews the medium access scheme of the IEEE
802.11 protocol, as well as the mechanisms that have been proposed to enhance its performance.
A IEEE 802.11 DCF
The fundamental access method of the IEEE 802.11 MAC is
the Distributed Coordination Function (DCF) known as carrier
sense multiple access with collision avoidance (CSMA/CA).
DCF allows for automatic medium sharing through the use
of CSMA/CA and a random backoff time following a busy
medium condition. Carrier sense is performed through both
physical and virtual mechanisms. A node which intends to
transmit a packet invokes the carrier-sense mechanism to determine if the medium is idle for a minimum specified duration
before attempting to transmit. If the medium is determined to
be idle, the transmission may proceed. Otherwise, the node
defers access until the end of the current transmission. After deferral, or prior to attempting to transmit again immediately after a successful transmission, the node defers until the
medium is determined to be idle without interruption for a period of time equal to Distributed InterFrame Spacing (DIFS).
After this DIFS medium idle time, the node generates a random
backoff period for an additional deferral time before transmitting, unless the backoff timer already contains a nonzero value,
in which case the selection of a random number is not needed
and not performed.
The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07)
Backoff Window
DIFS
SIFS
SIFS
SIFS
DATA
Busy
medium
A
C
K
R
T
S
Slot Time
SIFS
C
T
S
A
C
K
SIFS
Figure 1: An access cycle of IEEE 802.11 DCF
The backoff interval is uniformly distributed over the interval [0,CW], where CW is an integer within the range of values
aCW min and aCW max. The Contention Window (CW) parameter takes an initial value of aCW min, and is doubled at
every unsuccessful attempt to transmit a packet, until it reaches
the value of aCW max. Once it reaches aCW max, the CW
remains at the value of aCW max until it is reset. This improves the stability of the access protocol under high-load conditions. The CW is reset to aCW min after every successful transmission. The backoff interval counter is decremented
while the medium is idle, and when it is zero the node is allowed to transmit. This process minimizes collisions during
contention between multiple nodes that have been deferring to
the same event.
B
Existing Work
The mechanisms that have been proposed in order to enhance
the performance of DCF can be broadly classified into three
categories: 1) mechanisms that change the contention resolution algorithm based on locally experienced traffic conditions,
2) mechanisms that adapt the parameters of the protocol to a
rough or an accurate estimate of the number of contending stations and 3) mechanisms that sense the common channel and
share information with other contending stations to adapt the
parameters of the protocol to the optimum values.
Medium access schemes belonging to the first category,
make modifications to the contention resolution algorithm and
the backoff parameters based on the number of successful
transmissions and packet collisions that they experience locally. The Fast Collision Resolution (FCR) algorithm [2],
changes the contention window size upon both successful
packet transmissions and collisions for all active stations in order to actively avoid potential future collisions. However, in
this way the existing unfairness of IEEE 802.11 is exacerbated,
as FCR gives more priority to stations that have transmitted recently. To cope with this shortcoming, the authors propose to
modify the self-clocked fair queueing (SCFQ) algorithm and
incorporate it into the FCR. Nevertheless, the complexity of the
scheme is greatly increased. The authors in [3] take a more conservative measure than decreasing the contention window to the
initial value after each success transmission. GDCF halves the
contention window size after a certain number of consecutive
successful transmissions. This ”gentle” decrease is shown to
reduce the collision probability, especially when the number
of competing nodes is large. A similar approach called Probabilistic DCF (PDCF) [4] resets the window size to its minimum
value with fixed probability.
MAC protocols belonging to the second category adapt the
parameters of DCF to a rough or an accurate estimate of the
number of competing terminals and the load of the network. In
[5], an adaptive contention window mechanism that dynamically selects the optimal backoff window by estimating the
current number of contending stations is proposed. For a small
number of contending stations, a smaller CW min value is selected, while a larger CW min value is selected when there are
many contending stations. In [6], the authors estimate the number of competing terminals based on sequential Monte Carlo
methods. The algorithm uses a Bayesian approach, optimizing the backoff parameters of the DCF based on the predictive distribution of the number of competing terminals. The
p-persistent protocol is proposed in [7]. At the beginning of an
empty slot, a station transmits with a probability p, while the
transmission defers with a probability 1 − p , and then repeats
the procedure at the next empty slot. Hence, in this protocol
the average backoff time is identified by the value p. The ppersistent IEEE 802.11 protocol is tuned, by observing the network status, so that for a given congestion level, the appropriate
size of the contention window is selected. Results obtained indicate that under stationary traffic and network configurations
(i.e., constant average message length and fixed number of active stations), the capacity of the enhanced protocol approaches
the theoretical limits. However, this protocol may not be suitable for realistic wireless networks, where the number of stations frequently changes and the bursty nature of traffic renders
only a fraction of the stations active. In [8], a simple adaptive optimization mechanism, DOOR (Dynamic Optimization
on Range), is proposed. By replacing the accurate measurement of system parameters with the measurement and estimation of the subrange of competing station number, DOOR has
lower algorithm complexity and lower system cost than previous schemes. A methodology to estimate the number of contending stations, based on an extended Kalman filter coupled
with a change detection mechanism is presented in [9]. By
independently monitoring the transmissions eventually occurring within each slot-time, each station is in the condition to
estimate, the number of competing terminals.
Protocols belonging to the second category suffer from their
high complexity, while their efficiency depends significantly
on their ability to track the number of active stations. On the
other hand, protocols, belonging to the third category, sense the
channel and share information in order to select the optimum
value for the contention window. To address the problem of
unfairness in the DCF scheme, the multiplicative increase linear decrease (MILD) algorithm was introduced in the MACAW
protocol [10]. In the MILD scheme, a collided node increases
its backoff interval by multiplying it by 1.5. The MACAW
protocol assumes that a successful node has a backoff interval that is somehow related to the contention level of the local
area. Therefore, the current backoff interval is included in each
transmitted packet. A backoff interval copy mechanism is implemented in each node, to copy the backoff intervals of the
overheard successful transmitters. The contention window in
the MILD scheme can be summarized by the following set of
The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07)
equations:

 min(1.5 · CW, Bmax ),
CW = CWpacket ,

max(CW − 1, Bmin ),
CW value on their transmitted data. Second, high medium utilization can be achieved only if all stations select a Contention
upon collision
Window that balances the collision rate and the number of idle
upon overhearing a success slots. To select the appropriate size of the contention window
upon success
without paying the collision costs, all active stations should react to both successful transmissions and collisions.
where CWpacket is the backoff interval value included in the
The proposed Sensing with CW Copy (SCC) mechanism
overheard packet.
requires all nodes that successfully transmit a packet to pigA sensing backoff algorithm, SBA, is proposed in [11] that gyback the value of their current CW on their data. All staprovides much better fairness performance than DCF. In the tions, overhearing the successful transmission, calculate the
SBA scheme, every node that experiences packet collisions mean value CWC of the CW of the packets that were transmultiplies its backoff interval by α, α > 1. The transmit- mitted successfully in the C preceding cycles. Then, their CW
ter and the receiver of each successful transmission multiply value is set equal to CWC multiplied by θ, θ < 1. Contrary to
their backoff intervals by θ, θ < 1. All active nodes over- MACAW, our proposed scheme calculates the mean CW value
hearing (sensing) a successful transmission are required to de- of the C last transmitted packets. This feature protects the efficrease their backoff intervals by β slots. This sensing feature is ciency of our scheme under low traffic conditions, since it preresponsible for the improvement of the fairness performance. vents nodes from copying and using a high value for their CW.
The SBA operation can be summarized by the following set of Even in the case that a transmitting station has a high value of
equations:
CW, the mean value is only slightly increased. Moreover, upon

the successful transmission of a packet, all stations reduce their
upon collision
 min(α · CW, Bmax ),
contention window by the same amount. This is not the case
CW = max(CW − β, Bmin ), upon overhearing a success with SBA, where the transmitter of a successful packet and the

upon success
max(θ · CW, Bmin ),
stations overhearing the successful transmission decrease their
CW by a different number of slots. In the SCC scheme, every
III P ROPOSED SCHEME
node that experiences packet collisions multiplies its backoff
In this section, we propose a mechanism that allows DCF to ef- interval by 2, as in the legacy DCF. Furthermore, all stations
ficiently use the available raw bandwidth, while achieving fair- sensing the collisions multiply their CW by α, 1 < α < 2. Staness and low complexity. To achieve high medium efficiency, tions that experience packet collisions increase their contention
the length of the backoff interval should balance two different window by a larger amount of slots than stations overhearing
qualities that are both desirable - low collision rates and short them, since their collisions may be due to their low value of
access cycles. Arbitrarily low collision rates may be achieved CW and not due to an increase in the offered load. The SCC
at the cost of long access cycles and vice versa. The efficiency operation can be summarized by the following set of equations:
of DCF is governed on a great degree by the equilibrium of

upon collision
min(2 · CW, Bmax ),

these two conflicting qualities. In the legacy 802.11 DCF, each

upon overhearing collision
min(α · CW, Bmax ),
station selects independently its contention window at the cost CW =
CW
,
B
),
upon
success
max(θ
·

C
min

of collisions. Small backoff intervals result in a high probamax(θ · CWC , Bmin ), upon overhearing success
bility of collisions, lowering the channel throughput. On the
other hand, large backoff intervals introduce unnecessary idle
IV P ERFORMANCE EVALUATION
time on the channel and increase the average packet delay, also
degrading the scheme’s efficiency. Fairness among competing We used event-driven stochastic simulations to assess the efnodes should also be considered, as it is an important issue ficiency of our medium access scheme in maximizing the efin MAC protocol design for wireless local area networks. As fective use of the wireless bandwidth while providing fairness
shown in [10], DCF exhibits inherent unfairness characteris- to contending stations. The proposed scheme was compared
tics.
with legacy DCF, MILD with backoff interval copy and SBA.
The proposed mechanism achieves both high throughput and The triplet (α, β, θ) of SBA was set to (1.9, 1, 0.93), which was
high degree of fairness performance, by dynamically calculat- found to achieve the highest efficiency. The slight difference
ing the contention window based on shared and sensed infor- from the optimal values (1.2, 0.8, 0.93) proposed by its authors
mation. Therefore, our scheme makes use of both the copy stems from the fact that we considered a larger packet size. The
mechanism of MACAW and the sensing feature of SBA. As in parameters α and θ of SCC were set to 1.65 and 0.96 respecthe case of the two schemes, the knowledge of the number of tively, and the mean value CWC was computed over the last
active nodes in a network is not required. This preserves the 100 successful access cycles.
The working parameters of the four schemes were set to
simplicity of our implementation in real WLANs. The algorithm is developed based on two observations. First, fairness those of IEEE 802.11b and the RTS/CTS handshake was not
is achieved only if all contending stations have the same prob- used. The physical channel was considered to be ideal; that
ability of getting access to the common medium. Therefore, is, the only reason behind erroneous reception was the simulthey should share the same value for the Contention Window. taneous transmission of more than one station (packet colThis can be accomplished if stations piggyback their current lision). Furthermore, all network stations were within one
The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07)
(a) Medium utilization vs number of contending stations
(b) Collision probability vs number of contending stations
Figure 2: (a) Medium utilization and (b) Collision probability vs number of contending stations
hop from each other, thus, eliminating the appearance of hidden/exposed terminals. The performance metrics of interest
were the achieved medium utilization, the fairness and the
packet loss ratio and were examined for different node populations (1–200 stations).
Each station was assumed to initiate a video stream with a
maximum allowable delay that was uniformly distributed in the
range [20, 200ms]. To better approximate compressed video
traffic, real frame sizes of H.263 encoded video were used. The
video frame traces were taken from a video conference available at [12]. The bitrate of the encoder output, for this video
sequence, is 64 kb/s and its peak to mean bitrate ratio is equal
to 6.2. The maximum packet size was set to 2048 bytes. Upon
their arrival, packets were assigned a lifetime which was equal
to the delay budget associated with the flow that they belonged
to. Packets that could not be delivered within the allocated lifetime were discarded.
A
Simulation results
In Fig. 2(a), the mean medium utilization achieved by each
scheme is presented. All four schemes exhibit the same
throughput under low and medium load conditions. However,
as the number of contending stations increases the medium
utilization curves of DCF and SBA show a decreasing trend.
The major deficiency of the DCF scheme comes from the slow
collision resolution as the number of active stations increases.
After each successful transmission, DCF sets the contention
window to its minimum value resulting in an excess collision
probability, as shown in Fig. 2(b). SBA achieves better performance than DCF, as it reduces the contention window only
by a certain amount, and consequently, does not suffer from
such a high collision probability. For high traffic load, the reduced efficiency of SBA is accounted to the lack of cooperation
when packet collisions are detected. In the SBA scheme, stations react only to successful packet transmissions and take no
action when packet collisions are detected. Therefore, stations
increase their contention window only when their own packets collide. The collision probability of MILD is the lowest of
all schemes. However, this comes at the expense of increased
overhead. The increased number of idle slots has an adverse
impact on the efficiency of MILD, even for a low number of
contending stations. The best balance between collision probability and overhead is achieved by the proposed scheme. The
sensing feature of SCC, along with the copy of the contention
window value, allows it to effectively adapt to traffic conditions.
The second performance metric of interest was the packet
loss ratio witnessed by each scheme, which is illustrated in
Fig. 3(a). When the number of contending stations is less
than 40, each scheme exhibits approximately zero packet loss.
However, for medium and large contending populations, all
schemes, other than SCC, experience an increased portion of
lost packets. For medium traffic load, the number of discarded
packets is much higher in the case of MILD. For high traffic
load, the low collision rate of MILD and SBA results in a lower
number of lost packets compared to both DCF and SBA. The
packet loss ratio is a significant metric of the ability of each
scheme to provide service assurances, since the QoS requirements of most applications are expressed in terms of both maximum allowable delay and packet loss probability. With respect
to video applications, 3GPP defines that their performance will
not be harmed as long as their packet loss ratio remains below
2%. In this case, SCC could admit 132 sessions, SBA 112 sessions, MILD 61 sessions and DCF 114 sessions, while ensuring
that the packet loss requirement of flows is not violated.
Fig. 3(b) presents the fairness exhibited by each scheme. The
fairness index (FI) indicates the instantaneous domination in
the channel sharing. The FI is calculated as the probability
that the previous successful node becomes the next successful transmitter multiplied by the number of contending stations. Therefore, medium access schemes that distribute the
bandwidth fairly among the competing stations should have an
The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07)
(a) Packet loss probability vs number of contending stations
(b) Fairness index vs number of contending stations
Figure 3: (a) Packet loss probability and (b) Fairness index vs number of contending stations
FI value equal to one. The unfair characteristics of DCF become evident as the traffic load increases. On the other hand,
the FI values of the SCC and SBA scheme stay at almost the
same level as the number of contending station increases from
1 to 100. This shows the good fairness performance of these
schemes when the offered load is below the MAC Capacity.
However, when the offered load is high, SBA tends to favour
the last transmitting station. This is attributed to the fact that
only the stations that experience collisions increase their contention window. On the other hand, the FI value of MILD is
lower when the traffic load is higher than the channel capacity, allowing stations that were previously deferring access to
transmit their packet.
V
C ONCLUSION
In this work, we have proposed and evaluated the performance
of a medium access scheme that allows DCF to adapt to traffic
conditions. The mechanisms behind the proposed protocol that
allow it to achieve better performance rely on the sensing feature of the proposed scheme and the cooperation of contending
stations by sharing information about their current contention
window. The good characteristics of the proposed scheme were
confirmed via simulations, where significant gains in performance were witnessed for all scenarios examined.
R EFERENCES
[1] IEEE, ”802.11: Wireless LAN medium access control (MAC) and physical layer specification”, 1997.
[2] Y. Kwon, Y. Fang and H. Latchman, ”Design of MAC Protocols With
Fast Collision Resolution for Wireless Local Area Networks”, IEEE
Transactions on Wireless Communications, vol. 3, no. 3, 2004
[3] C. Wang, B. Li and L. Li, ”A New Collision Resolution Mechanism to
Enhance the Performance of IEEE 802.11 DCF”, IEEE Transactions on
Vehicular Technology, vol. 53, no. 4, 2004
[4] C. Wang and W. Tang, ”A Probability-Based Algorithm to Adjust Contention Window in IEEE 802.11 DCF”, ICCCAS, vol. 1, pp. 418–422,
2004
[5] M.-S. Kim et al., ”Adaptive Window Mechanism for the IEEE 802.11
MAC in Wireless Ad Hoc Networks”, Lecture Notes in Computer Science, pp. 31–40, 2005
[6] A. Toledo, T. Vercauteren and X. Wang, ”Adaptive Optimization of
IEEE 802.11 DCF Based on Bayesian Estimation of the Number of
Competing Terminals”, IEEE Transactions on Mobile Computing, vol.
5, no. 9, pp. 1283- 1296, 2006
[7] F. Cali, M. Conti and E. Gregori, ”IEEE 802.11 Protocol: Design and
Performance Evaluation of an Adaptive Backoff Mechanism”, IEEE
Journal on Selected Areas in Communications, vol. 18, no. 9, 2000
[8] H. Ma et al., ”Dynamic Optimization of IEEE 802.11 CSMA/CA Based
on the Number of Competing Stations,” In Proc. IEEE ICC 04, 2004
[9] G. Bianchi and I. Tinnirello, ”Kalman Filter Estimation of the Number
of Competing Terminals in an IEEE 802.11 Network”, In Proc. Infocom
2003, vol. 2, pp. 844–852, 2003
[10] Vaduvur Bharghavan et al., ”MACAW: A Medium Access Protocol for
Wireless LANs”, In the Proc. SIGCOMM ’94, pp. 212–225, 1994
[11] Z. J. Haas and J. Deng, ”On Optimizing the Backoff Interval for Random Access Schemes”, IEEE Transactions on Communications, vol. 51,
no. 12, 2003
[12] http://trace.eas.asu.edu