I. J. Communications, Network and System Sciences, 2008, 4, 285-385
Published Online November 2008 in SciRes (http://www.SciRP.org/journal/ijcns/).
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
Improving Throughput in Wireless Local Area Networks
Imam AL-WAZEDI, Anjali AGARWAL, Ahmed K. ELHAKEEM
Department of Electrical and Computer Engineering,
Concordia University, Montreal, Quebec, Canada
Received September 6, 2008; revised October 16, 2008; accepted October 21, 2008
Abstract
The medium access control (MAC) technique of standard WLANs, called the distributed coordination function
(DCF), is carrier sense multiple access based on collision avoidance (CSMA/CA) scheme with binary slotted
exponential backoff. It has a two way handshaking technique for packet transmission and also defines an
additional four way handshaking technique called RTS/CTS mechanism, which is used to reduce the hidden
terminal problem. The RTS/CTS frames carry the information of the packet length to be transmitted which can
be read by any listening stations, to update a network allocation vector (NAV) about the information of the
period of time in which the channel is busy. In this paper a method is proposed called the table driven technique
(which has two parts called table driven DCF and table driven RTS/CTS) which is similar to the standard DCF
(IEEE802.11) and RTS/CTS (IEEE802.11) system without having the exponential backoff. In this technique
users use the optimum transmission probability by estimating the number of stations from the traffic conditions
in a sliding window fashion one period at a time, thereby increasing the throughput compared to the standard
DCF (IEEE802.11) and RTS/CTS (IEEE802.11) mechanism while maintaining the same fairness and the
delay performance.
Keywords: Standard DCF (IEEE802.11), Standard RTS/CTS (IEEE802.11), Table Driven DCF, Table
Driven RTS/CTS
1. Introduction
Wireless local area networks (WLANs) have been widely
deployed for the past decade. Their performance has been
the subject of intensive research. In [1] an improvement of
throughput and fairness is shown by optimizing the
backoff without estimating the number of active nodes in
the network. In [2], the authors proposed a MAC layer
based WLAN technique in which they gave higher
priority to access points so as to improve the throughput
and the channel utilization. A technique is proposed
where the backoff is tuned based on collision avoidance
and fairness to improve the channel utilization [3]. In [5] a
DCF model is proposed where the arrival and the service
of the packets in the queue are controlled to improve the
throughput and delay performance.
Cali in [6] pointed out that depending on the network
configuration, DCF may deliver a much lower throughput
compared to the theoretical limit. Cali derived a
distributed algorithm that enables the stations to tune its
backoff at run time where a considerable improvement in
the throughput is shown. In [7] a contention based MAC
protocol named fast collision resolution is presented
where the backoff is also utilized. A model named DCF+
in [8] is proposed which uses the backoff to improve the
fairness.
It is evident that the throughput, delay, fairness
performances are improved by tuning the backoff in
different scenarios considered by the authors in [1–8].
RTS/CTS mechanism with (NAV) is used solve the
hidden terminal problem. In [9] Khurana proposed a
concept of Hearing graph to model the hidden terminals
in static environment and analyzed the performance. Also
in [11] Fullmer, proposed a three way handshaking
technique to solve the hidden terminal problems of single
channel WLANs. However our paper does not
concentrate on the hidden terminals but contributes on a
modification of the standard DCF and standard RTS/CTS
mechanisms.
In this paper table driven DCF and table driven
RTS/CTS systems are proposed, which are similar to
IEEE 802.11 (Both DCF and RTS/CTS) standards without,

308 I. AL-WAZEDI ET AL.
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
the use of the exponential backoff. In table driven DCF
and table driven RTS/CTS the users estimate the number
of active stations and transmit with an optimum
probability measured from the traffic conditions (by
sensing the channel) in a sliding window fashion, which is
described elaborately later on. Simulation results show
that our systems out perform the standard in terms of
throughput while maintaining same delay and fairness.
2. The IEEE 802.11 MAC Protocol
Figure 1 shows one of many transmission scenarios
possible with the IEEE 802.11 DCF mode. In this mode a
node with a packet to transmit initializes a backoff timer
with a random value selected uniformly from the range [0,
CW-1], where CW is the contention window in terms of
time slots. After a node senses that the channel is idle for
an interval called DIFS (DCF interframe space), it begins
to decrease the backoff timer by one for each idle time slot
observed on the channel. When the channel becomes busy
due to other nodes transmission ativity the node freezes its
backoff timer until the channel is sensed idle for another
DIFS. When the backoff timer reaches zero, the node
begins to transmit. If the transmission is successful, the
receiver sends back an acknowledgement (ACK) an
interval called the SIFS. Then, the transmitter resets its
CW to CW
min
. In case of collisions the transmitter fails to
receive the ACK from its intended receiver within the
specified period, it doubles its CW subject to maximum
value CW
max
, chooses a new backoff timer, and starts the
above processes again.
In 802.11, DCF also provides a more efficient way of
transmitting data frames that involves transmission of special
Figure 1. IEEE 802.11 MAC mechanism.
Figure 2. Standard RTS/CTS access mechanism in IEEE
802.11.
short RTS and CTS frames prior to the transmission of
actual data frame. As shown in Figure 2, an RTS frame is
transmitted by a node, which needs to transmit a packet.
When the destination receives the RTS frame, it will
transmit a CTS frame after SIFS interval immediately
following the reception of the RTS frame. The source
station is allowed to transmit its packet only if it receives
the CTS correctly. Note that all the other stations are
capable of updating their knowledge about other nodes
transmission duration by receiving a certain field in RTS,
CTS, ACK, and packets transmission called network
allocation vector (NAV). This helps to combat the hidden
terminal problem. In fact, a node that is able to receive the
CTS frames correctly, can avoid collisions even when it is
unable to sense the data transmissions directly from the
source station. If a collision occurs with two or more RTS
frames, much less bandwidth is wasted when compared
with the situations where larger data frames in collision,
thus justifying the case for RTS, CTS mode of operation [4].
3. Analysis of Table Driven DCF and Table
Driven RTS/CTS
Let p be the transmission probability of each node and M
be the number of active stations. Assuming each user tries
to transmit randomly in each slot following the DIFS
period. According to table driven DCF (Figure 3) the
probability of successful transmission, is thus given by
Equation (1).
1
)1(
−
−=
M
s
pMpP (1)
The probability of an idle slot in table driven DCF is
M
o
pP )1( −= (2)
and the probability of unsuccessful transmission for table
driven DCF is
osc
PPP −−=1 (3)
Let
i
be the number of idle periods (cycles) before a
successful transmission as shown in Figure 3 and j be the
number of idle slots in each idle period lengths
(W
1
,W
2
,…). The throughput (
1
η ) is given by Equation (7)
for table driven DCF.
It is easily seen that the average length of each idle
period except the last one before packet success in table
driven DCF is given by
( )
∑
∞
=
−
====
1
121
)(......
jc
j
oL
PPjjEWWW
( )
2
1
o
co
P
PP
−
=
slots (4)
which means Equation (4) determines the number of idle
slots before a collision.
The last idle period before a success, has an average of
( )
2
1
o
so
L
P
PP
W− =slots (5)
RTS
DIFS
DATA
SIFS
Source
Destination
Other
SIFS
CTS
SIFS
ACK
DIFS
NAV (DATA)
NAV (RTS)
NAV (CTS)
Defer Access
CW
Backoff
Starts
P ACKET
T RANSMISSION
SIFS
ACK
DIFS
W IRELESS C HANNEL I DLE B ACKOFF S LOT
I DLE B ACKOFF S LOT
C
OLLISION
DIFS
P ACKET
T RANSMISSION
…
…
.

IMPROVING THROUGHPUT IN WIRELESS LOCAL AREA NETWORKS 309
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
The average number of cycles (I) is given by,
∑
∞
=
=
1ii
iPI
(
)
0
2
001
1
.......1.
P
P
PPPPPcyclesofNoPwhere
s
sss
−
=
+++==
( )
( )
2
0
0
2
0
0
0
0
2
1
.......
111
2.
P
PP
P
P
PP
P
P
PP
P
P
PcyclesofNoP
sc
s
c
s
c
s
c
−
=






−
+






−
+






−
==
() ( )
3
0
2
2
1
3. P
PP
cyclesofNoP
sc
−
==
( )
i
s
i
c
i
P
PP
P
0
1
1−
=
−
Therefore
(
)
s
o
P
P
I− =1
(6)
Let the number of collisions be C= I–1. This C and W
L
are calculated from different values of M and p which are
stored in two different tables (not shown for space con-
sideration). So for particular values of M and P there is a
particular value of C and W
L
. The throughput for table
driven DCF
(
)
1
η and table driven RTS/CTS
(
)
2
η are
given in Equations (7) and (8) respectively based on the
transmission activity on the wireless channel as shown in
Figure 3.
(a)
(b)
Figure 3. Transmission Activity on the Wireless Channel for (a) table driven DCF and (b) table driven RTS/CTS.
(){ }
SlotLPayloadSIFSACKDIFSDIFSSlotL
Payload
TWTTTTTITWWW
T
+++++−+++
=
−
)1(..
121
1
η
(7)
() {}
SlotLPayloadSIFSACKCTSRTSDIFSSIFSDIFSRTSSlotL
Payload
TWTTTTTTTTTITWWW
T
+++++++++−+++
=
−
3)1(..
121
2
η
(8)
(From DIFS start to end of packet success)
Packet
transmission
SIFS
ACK
DIFS
Idle Slots
RTS
Collision
.............
.............
DIFS
Idle Slots
Packet
transmission
.......................
...
Current Transmission Period
SIFS
Previous Transmission Period
Next T
ransmission Period
First Idle Period
W
1
=3
RTS
CTS
Last Idle period
before success
W
L
Packet
transmission
SIFS
ACK
DIFS
Idle Slots
Collision
.............
.............
DIFS
Idle Slots
Packet
transmission
.......................
...
Current Transmission Period
SIFS
P
revious Transmission Period
Next Transmission Period
First Idle Period
W
1
=3
Last Idle period
before success
W
L

310 I. AL-WAZEDI ET AL.
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
The throughput
1
η (for table driven DCF) is calculated
for different values of M and p as in Figure 4. Table 1
depicts the probabilities at which the maximum
throughput occurs for different values of M.
Similarly for the table driven RTS/CTS, to calculate
the C and W
L
, Equations (1)–(6) are used. However the
throughput is calculated from Equation (8) which includes
the RTS/CTS frames (Figure 3).
For the case of table driven RTS/CTS all cycles
leading to no success (RTS heard but no CTS) will each
have a cost of T
RTS
+T
DIFS
+T
Slot
seconds.
4. Operation of Table Driven Technique
In the proposed protocol, if the nodes sense that the
channel is idle for an interval called DIFS (DCF
interframe space), they try to send a packet with a proba-
bility p, which is dependent on the traffic condition i.e. the
number and activities of the nodes, as follows.
A user continuously monitors the channel in each idle
slot following the DIFS idle period. If the previous slot is
idle, it calls a uniform random generator (0,1). If the value
0.1 0.2 0.3 0.4 0.50.6 0.70.8 0.9
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
Probability of each transmitting station
Throughput(
η
1
)
M=1
M=2
M=3
M=4
M=5
M=6
M=7
M=8
M=9
M=10
Figure 4. Throughput for different probabilities and
different number of stations for table driven DCF.
Table 1. Optimum throughput for different probabilities
and different number of stations for table driven DCF.
No of
Stations Probability Optimum throughput
1 0.9000 0.9532
2 0.3400 0.9458
3 0.2200 0.9444
4 0.1600 0.9437
5 0.1300 0.9434
6 0.1000 0.9431
7 0.1000 0.9428
8 0.1000 0.9420
9 0.1000 0.9410
10 0.1000 0.9397
of this generator is less than or equal to p, it tries to start its
packet transmission in the given next slot. If the value is
larger than p, the user persist on listening and repeats trials
as stated. However if the channel is sensed busy the user
defers his transmission till the next DIFS idle period heard.
The users measure the number of collisions C= I–1 and
the length W
L
by monitoring the channel over a large
enough window (which is explained latter on). With the
help of these values the users can use the tables formulated
in Section 3 to obtain the corresponding p and M.
Users having a non-empty queue start by monitoring
the channel for the first n transmission periods. This
active user will average the length of the idle period
preceding the correct packet transmission over n
transmission periods, i.e.
L
W and C , the average number
of collisions over the same period. Aided with these
values the users obtain the operating values of p and M
and uses p to control their activities for the head of line
packet in their queue. Active users continuously monitor
the channel and use a sliding window technique to
estimate W
L
and I and hence obtain (M, p). For example
the first sliding window averages W
L
and C of the first n
transmission periods. The second window averages W
L
and C of the l=2,3,...,n+1 transmission periods. The
sliding window averaging process reflects the changing
traffic, so transmission activity of active users are dependent
only on the current traffic and not on past history.
It is possible that the tables relating (M, p) to (W
L
, I)
yield more than one possibility for (M, p) for certain (W
L
, I)
measurement values from the sliding window. In this case,
the user averages the obtained values of M and use Table
1 to find the optimum p at this averaged value of M. This
Table 1 is obtained from Figure 4 in an evident manner.
The operation of this table driven technique is similar to
the DCF standard (IEEE 802.11) [4] except for using this
optimized transmission probability p. The active users
just estimate (M, p) from the traffic conditions (by sensing
the channel) in a sliding window fashion one period after
another.
We note that old and new users both measure the
traffic and adapt to the same traffic conditions fairly and
obtain the same p. However having same p does not mean
all users will repeatedly collide in the same slot because of
feeding a random number generator with p.
The above procedure is followed for both table driven
DCF and table driven RTS/CTS shown in Figure 3.
5. Simulation Results
For numerical calculations the following parameters are
taken from “Bianchi” in [4].
In the table driven DCF, as per the standards, following
the observance of each DIFS, users try to transmit with
probability p obtained from
L
W
and
C
. If two or more
stations try to transmit at the same time, collisions occur.
If no stations transmit (Figure 3), the number of idle slots
will increase. If one station is successful after certain

IMPROVING THROUGHPUT IN WIRELESS LOCAL AREA NETWORKS 311
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
T
Payload
10msec
PHYheader 128bits
ACK 112bits+PHY header
RTS 160bits+PHY header
CTS 112bits+PHY header
Channel bit rate 1 Mbits/s
Slot time (T
Slot
) 50 µs
T
SIFS
28 µs
T
DIFS
128 µs
service rate
1
payload
T
µ =
offered traffic
λ
packets/sec
M
λ µ
≤
No of stations M
number of idle and collision periods, the transmission
period ends. As a result the total time for one successful
packet transmission include T
DIFS
, T
SIFS
T
Idle
, T
Payload
. The
throughput is calculated at the end of the simulation at
certain values of M,
λ
and p i.e. ,
( ) n
Payload
Time
simulationwholetheinPeriodsonTransmissiofNoT
×
= η
where
(
)
n
Time is the total simulation time that depends on
T
DIFS
, T
SIFS
, T
Slot
, T
Payload
. Initially
(
)
DIFS
n
TTime = and is
subsequently increased based on the user’s activity, e.g.,
(
)
(
)
( )( )
( )( )
packetsuccessfuleachfor
TTTTimeTime
collisioneachforTTimeTime
periodslotidleeachforTTimeTime
PayloadSIFSDIFS
nn
DIFS
nn
Slot
nn
;
;
;
+++=
+=
+=
For the Table driven RTS/CTS the total simulation
time is calculated by the following equations,
(
)
(
)
( )( )
( )( )
packetsuccessfuleachfor
TTTTTTimeTime
collisioneachforTTTimeTime
periodslotidleeachforTTimeTime
PayloadSIFSDIFSCTSRTS
nn
DIFSRTS
nn
Slot
nn
;3
;
;
+++++=
++=
+=
Figure 5 shows a comparison of the throughput
between the table driven DCF and the standard DCF
(IEEE 802.11) for 10 stations. The values of standard
DCF are taken from [5] which uses the same parameters
as in [4]. It is evident the table driven DCF performs better
than the standard DCF (IEEE 802.11).
Figure 6 shows a comparison of average delay between
the table driven DCF and the standard DCF (IEEE
802.11). The values of standard DCF are again taken from
[5]. It is noticeable that the delay performances are the
same.
Figure 7 shows the throughput curve for different
offered loads for the table driven RTS/CTS technique. It
shows that the throughput rises and becomes saturated at
higher values of the load. The maximum throughput
calculated by “Bianchi” in [4] for the standard RTS/CTS
(IEEE 802.11) mechanism is 0.837281 when M=10.
Figure 5. Throughput comparison between the table driven
DCF and the standard DCF (IEEE 802.11).
Figure 6. Average Delay Comparison between the table
driven DCF and standard DCF (IEEE 802.11).
Figure 7. Throughput corresponding to different offered
traffic for table driven RTS/CTS.
1 2 34 5 67 8
9
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Offered Traffic Packets/sec
Standard DCF with M=10
table driven DCF with M=10
Throughput
Offered Traffic Packets/sec
1 2 3 4 5 67 89
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Standard DCF with M=10
table driven DCF with M=10
Offered Traffic Packets/sec
Average Delay in Seconds
123 45678 9
0.8
0.82
0.84
0.86
0.88
0.9
0.92
table driven RTS/CTS
Offered Traffic λ packets/sec
Throughput

312 I. AL-WAZEDI ET AL.
Copyright © 2008 SciRes. I. J. Communications, Network and System Sciences, 2008, 4, 285-385
5001000 1500 2000 2500 3000 3500
1
2
3
4
5
6
7
8
9
10
11
No of Transmission Periods
Throughput and Traffic (
λ
)
Input Traffic
λ
Throughput
Figure 8. Throughput and input traffic corresponding to the
number of transmission periods (table driven RTS/CTS).
From the Figure 7 it is evident that table driven
RTS/CTS performs better than the standard RTS/CTS in
terms of throughput.
The table driven RTS/CTS technique has an extra
advantage as it is a load adaptive system. It means that it
has the capability to adapt to the input traffic as quickly as
possible. Figure 8 shows a case where the input traffic
suddenly increases from 5 packets/sec to 10 packets/sec.
In this case the throughput
(
)
( )
Input traffic rate
η λ
× is
shown to follow the offered traffic
λ
.
Fairness (FI) is another important issue considered in
this paper. To express this, we take the fairness index
defined in [10] and [2] to measure the fair packet capacity
allocation. In [10] fairness index is represented as
1
1
1
1
r
n
i
i
nr
i
i
x
n
x
n
=
=
 
 
 
 
 
 
∑
∑
. For example if m dollars are to be
distributed among n people and we favor k people by
giving them m/k dollars each and discriminate against n-k
people, then the above function becomes
1
r
k
FI n
−
 
=
 
 
.
Favoring 10% would result in a fairness index of
1
0.1
r
FI
−
=and discriminate index of
1
1 0.1
r
−
−. Therefore
r should be equal to 2. That is,
(
)
( )
2
1
2
1
n
i
i
n
i
i
x
FI
n x
=
=
=
∑
∑
, where
FI is the fairness index,
n
is the number of stations,
i
x is
the packets transmitted by the
th
i active station during the
simulation time (current traffic in which the offered traffic
λ
is same for all stations).
Figure 9 shows the comparison of the fairness index
performance of table driven DCF, table driven RTS/CTS
and standard DCF (IEEE 802.11). It can be observed that,
for the three cases up to 15 active stations the performance
is fair.
Figure 9. Fairness index for different number of stations for
table driven DCF, table driven RTS/CTS and standard DCF
(IEEE 802.11).
6. Conclusions and Future Work
In this paper a new approach that is based on the table
driven technique is proposed for DCF and RTS/CTS
mechanism in WLANs. While maintaining the same
delay the table driven DCF outperforms the standard DCF
(IEEE 802.11) in terms of throughput. The table driven
RTS/CTS also demonstrates that its throughput is more
than the standard RTS/CTS mechanism. Moreover the
table driven DCF and table driven RTS/CTS gives very
good fairness performance. In the table driven technique
(for both DCF and the RTS) a simple search mechanism is
used to find the values of M and p from
L
W and C .
However an efficient lookup mechanism is required for
this purpose.
The subnet technique presented in this paper is
amenable to implementation with two hops or more from
the SS (subscriber stations) of the IEEE802.16. This SS is
typically aware of the number of the nodes of the subnet
of the IEEE802.11 standard and will broadcast such
number to the nodes of the IEEE802.11 subnet. The nodes
may use this value as rule of thumb against the actual
estimated value of M obtained by the new table driven
technique. This current paper estimates p and M from the
nodes activities on the channel. Further, the value of M
from SS and its favorable consequences are for future
research. Our table based technique shall hence improve
the performance of such subnet.
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0.8
0.85
0.9
0.95
1
1.05
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Table driven RTS
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Number of Mobile station
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