The Journal of Engineering Research (TJER), Vol. 15, No. 1 (2018) 73-87

DOI: 10.24200/tjer.vol15iss1pp73-87

Capture Aware Channel Access Protocol in Wireless Network

S. Mustafa*

College of Engineering, Salahaddin University, Iraq

21 January 2015; Accepted 1 May 2017

Abstract: Spatial reuse in wireless networks is limited by the SINR threshold and it might be feasible
to capture a packet in the presence of ongoing foreign transmission. This work considers a new
capture aware channel access protocol by incorporating global channel state information in the
decision making process for the channel access jointly with adaptive power framework. The protocol
employs power heterogeneous ad-hoc networks; it assigns different transmission power level to
individual nodes based on dynamic observation of the network traffic. It exploits spatial
heterogeneity of flows at a given channel allocation and sets up either symmetric or asymmetric
carrier sensing which in turn schedules the data packets transmission to maintain adequate service
quality and fairness enjoyed by a user. It stands atop capture capable PHY to leverage the channel
reuse which is of paramount importance in the design of high capacity ad-hoc networks. Through
extensive simulations, the paper demonstrates the efficacy of the new protocol. It delivers high
network utilization and also provides fair access to the media.

Keywords: DCF; Carrier sensing; MAC mechanism; Power control; Capture effect; Wireless network.

بروتوكول الدخول اىل القنوات و الدراية حبدوث التقاط االرسال يف الشبكة الالسلكية

*مساح مصطفى

)سينر(. إشارة نسبة التدخل: ان إعادة االستخدام املكاني يف الشبكات الالسلكية يكون حمدودا بسبب حاجز امللخص

وقد يكون من املمكن التقاط حزمة ما يف وجود ارسال أجنيب مستمر. ويأخذ هذا العمل يف االعتبار بروتوكوال جديدا

للوصول إىل القنوات من خالل حالة دمج املعلومات بالقناة العامة يف عملية صنع القرار من أجل الوصول إىل القناة وباالستفادة

ويستخدم الربوتوكول قدرة غري متجانسة لشبكات خمصصة , حيث أنه حيدد مستوى قدرة .فمن إطار القدرة على التكي

اإلرسال املختلفة بالنسبة إىل الُعقد الفردية على أساس مراقبة ديناميكية حلركة مرور الشبكة. فهو يستغل عدم التجانس

ماثل أو غري متماثل للموجة احلاملة وحيدد املكاني للتدفقات عند ختصيص قناة معينة ، وحيدد سواء كان االستشعار مت

بدوره إرسال رزم البيانات للحفاظ على وجود جودة خدمة كافية وعادلة يتمتع بها املستعمل. وهو يقف فوق عملية االلتقاط

. من القادرة على االستفادة من إعادة استخدام القناة اليت تعترب ذات أهمية قصوى يف تصميم شبكات خمصصة عالية السعة

خالل احملاكاة واسعة النطاق. تربهن هذه الورقة على فاعلية الربوتوكول اجلديد. وهي توفر استخدام عال للشبكة وتوفر

أيضا إمكانية الوصول العادل إىل وسائط اإلعالم.

وسائط اإلعالمالتحكم بالوصول إىل آلية ،االستشعار الناقل،) دي سي اف( وظيفة التنسيق املوزع :ة كلمات املفتاحيال

تأثري االلتقاط. شبكة السلكية.،التحكم يف الطاقة ،) ماك(

* Corresponding author’s e-mail: samah.eecs@gmail.com

mailto:samah.eecs@gmail.com

S. Mustafa

1. Introduction

A key problem in ad-hoc wireless networking is
the design of distributed media access control
(MAC) mechanism to discover and negotiate the
access to the reusable physical channels such
that the transmission can occur without
collision. A representative mechanism of MAC
is the Carrier Sense Multiple Access/Collision
Avoidance (CSMA/CA) algorithm that forms
the basis of the dominant wireless multiple
access protocol Distributed Coordination
Function (DCF) in 802.11 (Kurth and Redlich
2009). Physically a channel is sensed busy either
when the detected energy level is above a
certain threshold ζED, when a signal with the
same PHY characteristics is detected, or a
combination of both (Larroca and Rodríguez
2014).

Carrier sensing is the main interference
mitigation mechanisms used in the PHY/MAC
layers of 802.11 WLANs, and its efficacy
becomes a key factor in determining network
capacity. A station defers its transmission for a
random period upon detecting a carrier on the
channel. However, the absence of a carrier does
not mean a transmission will succeed, nor does
the presence of a carrier mean that a
transmission will interfere. Hereby carrier sense
approach can unnecessarily reduce network
throughput and strongly affect the delay
characteristics at a station (Jamieson et al. 2005;
Zhu et al. 2004; Ma et al. 2009). Many studies
have been done to illustrate that physical carrier
sense adversely limits the effective bandwidth
utilization in the network because of fixed
carrier sense threshold and inadequately chosen
carrier sense range. Extensive research efforts
advocate the tuning of carrier sense threshold
for utilization improvement (Ma et al. 2009; Zhu
et al. 2004; Zhu e et al. 2006; Haghani et al. 2010);
however, many of today’s 802.11 MAC
implementations do not allow the threshold to
be independently tunable or even accessible
(Zhu et al. 2004). Moreover, (Pelechrinis 2009)
claims that tuning carrier sense threshold opens
the door for selfish users with lower back-off
times to ignore other transmission and therefore
obtain a higher unfair share of the spectrum.

There is a clear trade-off between the
probability of interference and the utilization in
setting carrier sense range. Larger sense range
decreases both the probability of interference
and the bandwidth utilization, whereas small
carrier sense range will be more subject to

interference. Exposed node prevents a
successful transmission while hidden node
wastes a transmission opportunity due to a
collision. As has been pointed out in (Ma et al.
2009), the optimum value of carrier sense
threshold is that at which the carrier sense range
of the transmitter just covers the interference
range of the receiver.

The setting of interference range is rather
heuristic and remains an open problem. Many
studies on wireless networks have largely
considered an interference range as twice the
transmission range, and others rely on equal
interference and transmission ranges. Physically
the interference range is defined to denote the
range within which an interfering node will
lower Signal-to-Interference ratio (SIR) below
the threshold for successful decoding of a
transmission (Maheshwari et al. 2008). It has
been depicted in (Chen et al. 2007 and Lee et al.
2010), an interferer’s impact becomes serious
when its preamble is detectable such that the
intended end-user device could engage with,
even if it is not able to decode the frame
correctly. Hereby the author recommends
characterizing the interference range within
which the preamble of a frame is detectable and
the carrier sense range should be equal to this
range.

Recall that spatial channel reuse relies on the
carrier sense threshold and the transmit power
each station uses. MAC like 802.11 DCF uses the
same transmission power at all nodes regardless
the link distance between transmitter-receiver
pair as well as interference level at the receiver
(Li et al. 2009). Moreover, it always transmits at
full power which in turn potentially maximize
the link utility from the medium. However,
this selfish behavior leads to excessive mutual
interference and degrades the network
performance. In contrast, some proposed MAC
mechanisms (Gomez et al. 2001; Lim and
Yoshida 2005) transmit at minimum possible
power to leverage the spatial reuse hence
maximizing the interference probability.

The SINR threshold for successful reception
depends on the timing and the relative order of
signal and the interference at the receiver (Chen
et al. 2007; Lee et al. 2010; and Mustafa 2015).
The radio captures a new stronger frame above
a predefined preamble capture threshold γP, if it
arrives during the first frame’s preamble
reception. 802.11's PHY layer continuously
monitors the received signal strength even the
layer in data reception state. It enables a radio to
correctly receive a second frame, even after it

Capture Aware Channel Access Protocol in Wireless Network

has already synchronized with the first one, if
the ratio of powers is sufficiently high. This is
called Message in Message MIM mode which is
not exploited before in capture aware
mechanisms. A typical ratio of powers required
for body capture is γD=10dB (Chen et al. 2007
and Lee et al. 2010). Thus, the SINR at the
intended receiver and transmission order are
crucial factors for successful delivery.

This work presents an approach to leverage
ad-hoc network's capacity relying on a
distributed capture aware framework to
coordinate the transmit power and time
schedule the traffics to exploit the PHY capture
effect with ultimate goals of improving utility
and spectrum fairness. Time schedule the traffic
is done by assigning transmit power level to set
up either symmetric or asymmetric carrier sense
scenario that can potentially schedule the data
packets transmission. Asymmetric carrier sense
situation is neither actually introduced nor
applied in previous works. It is known that a
hidden link would starve in presence of sensed
link with high load traffic. The simulation study
offers a new prospective regarding the
asymmetric carrier sense scenario and
demonstrates its benefit to time schedule the
hidden traffic without an extra timing signal.

In this work, Capture Aware Multiple
Access Protocol (CAMA) is proposed. It
requires disseminating the locally measured
link gain at individual stations throughout the
network neighborhood for identifying links that
can be concurrent and allowing them to coexist,
thereby enhanceing the effectiveness of channel
reservation. It doesn’t modify the carrier sense
threshold. CAMA exploits spatial heterogeneity
of flows at a given channel allocation by means
of dynamic power control to manage the co-
channel interference and allow for higher and
fair utilization of resources.

The rest of the paper is organized as follows:
section 2 goes through works related to this
paper. Section 3 describes CAMA mechanism
that adjusts the transmission power of the nodes
to maximize the benefits of the capture effect.
Section 4 presents the simulation results that
describe the behavior of the default and CAMA
mechanisms, and demonstrate the benefits of
the proposed protocol. Finally, Section 5
concludes the paper with general observations
and suggestions for future research.

2. Related Work

Extensive works have subjected different
aspects of 802.11MAC protocol to enhance per-
flow and aggregate throughput. This section
presents an overview of some existing work that
aims to improve network capacity by spatial
diversity through tuning transmit power.

Ding et al. 2005 proposes transmit power
control protocol to adjust the transmit power for
each frame under the same decision rule as IEEE
802.11 which in turn achieves limited
improvement. Mhatre et al. 2007 claim that
different power levels at transmitters use the
same carrier sense threshold in 802.11 networks
introduces asymmetric links which in turn lead
to throughput starvation. They demonstrate that
cross layer approach by joint tuning of the clear
channel assessment CCA threshold and
transmit power ensures starvation free control
system. Furthermore, the clients use the same
transmit power and CCA threshold as their
associated access point regardless of different
channel state each sees. The current work
demonstrates that asymmetric link do not
necessarily introduce starving nodes.

The traditional access control cannot handle
multiple packets without declaring a collision.
A capture aware MAC mechanism was
proposed in (Santhapuri et al. 2007), where
primary node transmits Request-To-Send
(RTS)/Clear-To-Send (CTS) and waits for one
preamble time interval before transmitting data
while secondary node(s) that overhears RTS will
initiate its own transmission either during wait
time for the primary user or during primary's
DATA transmission depending on the
estimated SINR at its receiver and at the
primary user. However, this scheme doesn't
address the synchronization issue due to the
existence of propagation delay, and it
incorporates that receiving the preamble of the
interference frame helps to detect the frame of
interest that arrives later while in contrast has
been proved in (Lee et al. 2010).

In (Li et al. 2009), nodes transmit RTS/CTS at
the same maximum power, and transmit
DATA/ACK at the power based on the link
distance, as well as the interference level at the
receiver. Based on the overhead RTS or CTS, the
protocol enables a concurrent transmission at a
possible highest power level as long as it does
not interfere with the ongoing ones. Although,

S. Mustafa

the protocol considers the aggregate
interference level, but it assumes equal
contribution from the neighboring nodes, no
matter how close they are as well as the transmit
power they use.

There are some limitations on these
mechanisms: hidden terminal problem still
exists with RTS/CTS, and possible loss in ACK
packets is ignored to benefit from fewer
collisions and build inaccurate results.

Various PHY layer capture aware MAC
mechanism are proposed for wireless area local
area networks WLANs. To meet fair access and
high overall throughputs, (Jeong et al. 2013)
changes either the contention window or
arbitration inter-frame space or transmission
opportunity. The technique in (Patras et al. 2014)
uses different power levels to result in packet
capture in WLANs and improve the
performance. However, an ideal channel
condition is assumed where losses are only
caused by collisions. The work in (Takahashi et
al. 2015) configures the minimum contention
window of the stations to reduce the collision in
each network. These studies considered
infrastructure mode where nodes are within
carrier sense range of one another.

Further, these mechanisms don’t exploit
MIM mode and the assignment of concurrent
links set satisfies a single SINR constraint. The
study in (Mustafa 2015) demonstrates the
inaccuracy of the well-known interference
physical model.

3. Capture Aware Multiple Access
CAMA Framework

The 802.11 DCF (Li et al. 2009) is strong transmit
power MAC design wherein all nodes transmit
with the same power no matter how close the
sender and receiver are. The current work here
claims that by moving beyond the maximum
fixed transmit power, the fairness and channel
utilization can be improved.

Further, successful unicast transmission
depends on channel condition at both the
receiver and sender due to downstream data
traffic and upstream MAC layer
acknowledgment ACK traffic. However,
suggestion of simply extending the carrier
sensing mechanism to the receiver does not
address the MAC limitations of inefficient and
unfair spectrum utilization. A capture aware
multiple access mechanism is proposed based

on broad channel observation to tune power
level of each node to successfully retrieve the
transmitted signal and make a decision to access
the channel, while carrier sense range is fixed
and set equal to interference range. In
environment with users of homogenous
technology competing for resources, the
interference range in this work is characterized
within which the preamble of a frame is
detectable.

3.1 Two Sender-receiver Pairs
Consider two sender-receiver pairs: (S1;R1)
and (S2;R2) transmitting over communication
links L1 and L2 respectively, and sharing a single

wireless channel as shown in Fig. 1. 𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅𝑖

experienced by Ri due to concurrent data
DATA-DATA transmissions from Si and Sj is
given by

𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑆𝑖

𝐺𝑗,𝑖
𝑆𝑅 𝑃𝑆𝑗 + 𝜂

(1)

Figure 1. Two flows sharing a wireless channel.
Depending on propagation paths
between the four stations, link(s) may
or may not be established between the
nodes.

Psi denotes transmit power level at Si and η is

the noise floor. 𝐺𝑖,𝑗
𝑆𝑅 denotes Si-Rj link gain where

a propagation model suited for the surrounding
environment is used to describe the fluctuation
in the received signal strength such that the
mean received power falls off as (1/d)α. α is a
path loss exponent. A receiver can engage with
a delivered packet if the received signal power
is greater than the receiver sensitivity threshold
ζS, i.e.

𝐺𝑖,𝑖
𝑆𝑅 𝑃𝑆𝑖 ≥ ζ𝑆 (2)

Whether parallel data transmissions of data

packets are successful or failure depends on the

𝐺1,1
𝑆𝑅

𝐺2,2
𝑆𝑅

𝐺1,2
𝑅𝑅

𝐺2,1
𝑆𝑅

𝐺1,2
𝑆𝑅

𝐺1,2
𝑆𝑆

Capture Aware Channel Access Protocol in Wireless Network

observed SINR basically at receivers that should
be higher or equal to γD. It enables the radio to
correctly receive an intended frame irrespective
of the timing relation between overlapped
transmissions. γD is usually set to 10 that map to
ten times the signal power over interference
power, as stated earlier in first section. This
condition holds if Ri is closer to Si than to both Sj
and Rj by a sufficient factor, and vice versa. It
may happen that this condition holds even
though CSMA/CA would prevent the second
pair from transmitting.

To illustrate this possibility, consider the
following example. The four nodes are on a line
in the order, from left-to-right R1; S1; S2; R2.
Their locations on the x-axis are 0; 1; d+1; d+2,
respectively. Assume all the nodes transmit

with a unit power and (𝐺𝑖,𝑖
𝑆𝑅 /𝐺𝑗,𝑖

𝑆𝑅 ) ≥ 10dB. A

capture-aware protocol that would let the
sender transmit even if it sense the other
transmission could potentially have a
throughput almost twice as large as the
standard DCF protocol. CAMA looks for a
minimum possible power level that guarantees
correct packet delivery and hide the sender
from other. Further, it is able to throwing out
carrier sense line by disabling randomized
backoff and allows two senders to transmit
packets continuously and simultaneously.

Now, consider the four nodes on the x-axis
in the order from left to right S1; R1; R2; S2, at
locations 0; 1; d+1; d+2, respectively. Depending
on the channel state the nodes see, DATA-ACK
and DATA-DATA packets collision are possible.

For example, 𝑆𝐼𝑁𝑅|𝐷−𝐴
𝑅𝑖 due to simultaneous

transmission of data and ACK packets from Si
and Rj, respectively is given by

𝑆𝐼𝑁𝑅|𝐷−𝐴
𝑅𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑆𝑖

𝐺𝑗,𝑖
𝑅𝑅 𝑃𝑅𝑗 + 𝜂

(3)

PRi denotes the transmit power of Ri. Assume

the nodes transmit with a unit power over a

single channel of state such that 𝐺𝑖,𝑖
𝑆𝑅 /𝐺𝑗,𝑖

𝑅𝑅 is less

than a sufficient factor ζD. ζD=5dB is the SINR
threshold to guarantee a successful packet
delivery if the receiver is not engaged with
another packet (IEEE Std. 2007, Chen et al. 2007,
Lee et al. 2010). It may happen that the senders
are hidden and don't preclude data
transmission if any. Failed transmission not
only wastes energy but also has the potential to
corrupt other transmissions. The proposed
approach evaluates the state and makes an
efficient decision to access the channel. It

assigns a transmit power to set up mutual
carrier sensing and dependently schedule the
transmission opportunity.

Homogenous links in terms of channel gain
are assumed in previous examples, nevertheless
they are not usually. CAMA exploits spatial
heterogeneity of flows and assigns different
power level at each station. Recall that link S2-
R2 has higher quality than link S1-R1. While the
default solution for sender(s) out of the capture
range of the intended receipt is to preclude the
concurrent transmissions, a more efficient
solution is addressed by achieving asymmetric
carrier sensing through heterogeneous power to
schedule the transmission time. High power
node S2 does not sense the transmissions of low
power node S1. CAMA looks for possible
minimum and different power levels at each
sender to set [𝐏𝐒𝟐𝐆𝟐,𝟐

𝐒𝐑 /(𝐏𝐒𝟏 𝐆𝟏,𝟐
𝐒𝐑 + 𝜼)] ≥ 𝟏𝟎𝐝𝐁 and

[𝐏𝐒𝟏𝐆𝟏,𝟏
𝐒𝐑 /(𝐏𝐒𝟐𝐆𝟐,𝟏

𝐒𝐑 + 𝜼)] ≥ 𝟓𝐝𝐁, and lets the senders

achieve high throughput. Transmit power plays
a vital role in our mechanism to enable either
the MIM or capture effect at the nodes and set
possible concurrent transmissions on a single
wireless channel.

S1 (being hidden from S2) transmits only if
the channel is idle and commences a data
transmission prior to S2 which doesn’t block any
transmission request from an upper layer on
sensing a clear channel. It can potentially initiate
transmission that overlap with lower power
transmission. Thereby, R1 captures the first
coming packet if there is an overlapping
transmission on the channel and R2 will begin
receiving S1’s packets first, and later re-lock onto
S2’s new packet which is much stronger than
S1’s. The senders can successfully and fairly
utilize the channel if the following conditions
hold:

 𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅1 and 𝑆𝐼𝑁𝑅|𝐷−𝐴

𝑅1 exceed a threshold

guarantees a successful packet detection
threshold ζD.

 𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅2 and 𝑆𝐼𝑁𝑅|𝐷−𝐴

𝑅2 exceed γD and ζD,

respectively.

Further constraint should be followed since it
is also possible that a data packet is received
correctly, but the ACK packet is lost

𝑆𝐼𝑁𝑅|𝐴−𝐷
𝑆𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑅𝑖

𝐺𝑗,𝑖
𝑆𝑆 𝑃𝑆𝑗 + 𝜂

≥ ζ𝐷 (4)

Briefly, the channel is utilized efficiently

only if S1 commence transmission before S2.

S. Mustafa

Flow of higher transmit power can afford to
start later. It is important to highlight that we
are not using a special timing signal to schedule
the data transmission; we only depend on
carrier sense scenario to time order the traffic.

It is well understood that asymmetric links
in power heterogeneous network unfairly
degrades the utility experienced by low power
links (Mhatre et al. 2007, Shah et al. 2007).
However, our simulation study confirms that
diversity in transmit power does not necessarily
starve low power users if some constraints are
followed.

3.2 N Sender-receiver Pairs
The intended stations are responsible for

estimating and disseminating the channel
quality around to make a joint prediction about
whether more than a flow can transmit
simultaneously through minimum possible
transmit power at each station to mitigate the
interference and optimize the per-flow and
overall network throughput on a collision free
channel. If the prediction result is positive, the
stations should not block their own
transmissions, if any. Otherwise, an approach
that considers tuning of transmit power as a
PHY parameter, should be applied to set a
suitable sense interaction and subsequently
schedule the access to a shared medium.

Simulation results in section 4 illustrate that
such an access scheme performs better than the
CSMA/CA even at high traffic loads, and
applying it has the benefit of improving per-
flow and aggregate utility in wireless networks.

To estimate the complexity of such a
protocol, assume there are N sender/receiver
pairs willing to access the media. The nodes in
pair i should estimate the channel gain over

link(s) that may establish; 𝐺𝑖,𝑗
𝑆𝑅 , 𝐺𝑖,𝑗

𝑆𝑆 and 𝐺𝑖,𝑗
𝑅𝑅 ∀

neighbor pair j, either periodically or whenever
it has data to transmit and/or node(s) observes
degradation in the performance. They then post
these values to a distributed control system to
coordinate the channel access and transmit
power of the nodes according to the specified
policy. The stations may exchange simple
control signaling to initiate the process and run
the optimization algorithm. Despite that the
optimal algorithm provides optimal utility of
the channel, it is rather computationally
expensive for a large network.

To guarantee successful concurrent
transmissions that would not change the result

of the capture effect, SINR constraints should
consider joint and maximum interference
strength at a station.

𝑆𝐼𝑁𝑅1|𝐷−𝐷
𝑅𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑆𝑖

∑ 𝐺𝑗,𝑖
𝑆𝑅 𝑃𝑆𝑗

𝑁
𝑗=1,𝑗≠𝑖 + 𝜂

≥ ζD (5)

𝑆𝐼𝑁𝑅2|𝐷−𝐷
𝑅𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑆𝑖

𝑚𝑎𝑥𝑗≠𝑖 (𝐺𝑗,𝑖
𝑆𝑅 𝑃𝑆𝑗) + 𝜂

≥ γD (6)

If the simultaneous transmissions could ban

the capture on a subset of M links, higher
transmit power should be assigned at the
senders of these links that being oblivious of
lower power flows within their sensing range.
SINR constraints should satisfy the earlier
inequalities at the receivers of the M links. SINR
experienced at the receivers of the remaining N-
M links should exceed ζD as given by

𝑆𝐼𝑁𝑅|𝐷−𝐴
𝑅𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑆𝑖

∑ 𝐺𝑗,𝑖
𝑅𝑅 𝑃𝑅𝑗

𝑁
𝑗=1,𝑗≠𝑖 + 𝜂

≥ ζD (7)

Further, SINR experienced at the senders

should exceed ζD for successful delivery of ACK
packets, as given by

𝑆𝐼𝑁𝑅|𝐴−𝐷
𝑆𝑖 =

𝐺𝑖,𝑖
𝑆𝑅

𝑃𝑅𝑖

∑ 𝐺𝑗,𝑖
𝑆𝑆 𝑃𝑆𝑗

𝑁
𝑗=1,𝑗≠𝑖 + 𝜂

≥ ζ𝐷 (8)

CAMA determines the appropriate

minimum transmit power that ensures that the
sender can sustain a data rate to reach the
intended receipt and the interference level
perceived at other nodes can be mitigated
thereby higher number of concurrent
transmissions can be achieved.

4. Simulation Results

In this section, we present simulation-based
studies using NS-2.34 which incorporates the
modeling details of the IEEE 802.11 MAC and
PHY modules (Chen et al. 2007). The PHY
module includes cumulative SINR computation,
preamble and PLCP header processing and
capture, and frame body capture. The MAC
accurately models transmission and reception
coordination, back off management and channel
state monitoring in a structured and modular
manner to presents the CSMA/CA mechanism.

All nodes implement the 802.11g technology.
The senders and receivers are placed in an
indoor environment, and the radio propagation
reflects shadowing model with path loss
exponent of 4 over the distance (Srinivasan and

Capture Aware Channel Access Protocol in Wireless Network

(a)

R1 S2 S1

(b) (c)

Haenggi 2009). Parameters as antenna gain and
system loss are assumed to be fixed. The default
values of configuration parameters are used.

Compared to preamble detection threshold ζP
where preamble detection starts to work, energy
detection threshold ζED in terms of SNR is
higher (Lee et al. 2010).

Table I lists the main parameters in our
simulation study. The minimum PHY bit rate
δ=6Mbps is considered in the simulation. Hence
the minimum SINR which guarantees a reliable
packet communication ζD=ζP=5dB, as a
hardware defined threshold (IEEE Std. 2007;
Chen et al. 2007; and Lee et al. 2010). The
simulation is restricted to one-hop unicast UDP
traffic. Each link carries constant bit rate (CBR)
traffic. Each simulation runs for 60 seconds with
disabled RTS/CTS virtual carrier sensing. The
nodes are configured to be always backlogged
with packets to send and each MAC data frame
to be 1028 bytes long.

During the simulation we consider utility in
terms of MAC layer goodput at the receiver and
Channel Usage Efficiency CUE in terms of the
ratio of MAC layer goodput at the receiver to
PHY layer throughput at the transmitter over a
given channel as two distinct metrics. We first
have activated one link to find the maximum
achievable throughput, goodput and CUE of
unicast traffic that are approximately 5.19 Mbps,
5.05 Mbps and 0.973 respectively due to
MAC/PHY layers overhead. Low CUE indicates
that a node has gained access with failed
transmission which consumes energy and may
cause interference to neighbors over the same
channel.

Fairly Shared Spectrum Efficiency (FSSE)
index is considered to measure the portion of
System Spectral Efficiency SSE that is shared
equally among all active users. In case of
scheduling starvation, FSSE would be zero
during certain time intervals. In case of equally

shared resources, FS SE would be equal to SSE.
If FSSE is maximized, the max-min fairness can
be achieved (Eriksson 2001).

4.1 Performance Evaluation of Default DCF
Determining how well carrier sense works in

wireless networks is the focus of the simulation
studies in this section. We show few examples
where the default bandwidth utilization by the
802.11MAC is far from optimal setting. Carrier
sense may sometimes make incorrect access
decisions thereby leading to inefficient channel
usage, as explained before when exposed
and/or hidden terminals are present. Utility in
terms of goodput and CUE are our basic metrics
for comparison of link performance across
various carrier sensing settings and for
measuring the efficiency of default channel
access scheme.

Consider a scenario of a simple four nodes
topology in a 100x100m2 indoor environment to
compose two wireless links, with symmetric
incomplete view of channel state in Fig. 2a. The
senders are within sense range of each other and
within the capture range of their intended
receiver. Hence, if S1 commences a data
transmission, S2 should not block its own
transmissions, if any, and vice-versa despite the
presence of the ongoing data delivery. They
could simultaneously transmit without causing
excessive interference at the receivers to disrupt

Table 1. Configuration parameters in the

simulation study.

parameters
Configuration

value

γP 4dB

γD 10dB
ζED 10dB
ζP= ζD 5dB
δ 6Mbps
η -96dBm

Figure 2. Three scenarios of two flows sharing a wireless channel. In scenario (a) the intended links could always

present, given that senders are in capture range of their respective receiver. Scenario (b) portrays hidden terminal

case where the intended links could not present simultaneously. Scenario (c) shows a topology of two

heterogeneous wireless links in terms of channel gain, given that the senders are hidden terminals and S1-R1 link

only is always present.

http://en.wikipedia.org/wiki/Scheduling_starvation

S. Mustafa

successful communication. However, the
default MAC mechanism based on local channel
assessment may mispredict the channel state
and consequently waste the transmission
opportunity.

Figure 3 illustrates the normalized utility on
two communication links L1 and L2 when the
senders depend on local channel observation
only or extend the observation to the intended
receiver. Having a single exposed node
potentially drops the overall throughput to 50%
of the optimal setting.

Further complications arise in cases where
hidden nodes are likely, scenario (b). Suppose S1
is oblivious of ongoing flow from S2 and vice-
versa. The receivers are in close proximity such
that S1 (S2) data transmission and/or R1 (R2)
ACK transmission could corrupt R2 (R1)
reception. The incomplete view of channel state
possessed by the sender causes hidden terminal
where the absence of a carrier at the sender does
not mean a transmission will not collide. Both
links experience packet loss due to the
concurrent transmissions from the hidden
terminals. The senders double their contention
window size for each failure of data
transmission; hereby an obvious drop in the
channel utilization is illustrated in Fig. 3.
Misprediction of channel state can drop the
utility significantly than if an access decision is
extended to the intended receiver.

It is obvious that exposed and hidden
terminals in the previous scenarios affect the
two flows equally. The third scenario in Fig. 2
considers a topology of hidden terminals with
heterogeneous link quality. S1 and S2 are out of
each other’s sensing range, and S2 cannot
corrupt R1 reception. However, S1 may initiate a
transmission while S2 is transmitting, and

disrupt the reception at R2. If S1 occupies the
channel for a long time, S2 will starve.

The simulation in Fig. 3 shows extreme
unfairness due to asymmetric interference and
diverse transmission opportunity the senders
have, which cannot be addressed in this
scenario with extending the channel observation
to the intended receiver. The unfairness in
access opportunity which is undesirable as it
can adversely affect delay sensitive applications
cannot be addressed without coordination with
the surrounding nodes.

Next, we have evaluated the performance of
hidden terminals in the topology of Fig. 2c with
different traffic load on the wireless links and
default MAC mechanism. S1 is located within
the capture range of its intended receiver while
S2 is not always depending on the traffic rate on
the interfering link L1.

Regarding the simulation results in Fig. 4 in
terms of normalized utility on L2, R2's default
MAC layer has recorded nothing at traffic load
of 3Mbps. It could work better at low traffic
load wherein the target utility of 1Mbps is
attained. However, CUE metric considered here
is not satisfying even with low traffic load.
Failed transmissions not only alleviate CUE and
waste energy but also have the potential to
corrupt other transmissions.

Generally, the overall performance claim
that the default mechanism doesn't work
efficiently even with low traffic load, and
simply extending the observation to the
intended receiver don't address the limitation.
An intuition to maximize the utility and channel
usage efficiency is to set up capture aware MAC
scheme jointly with adaptive transmit power as
has been described in section 3.

Figure 3. Normalized utility for the scenarios in Fig. 2, in terms of MAC's layer good put with

default channel assessment at the senders and extended assessment to the intended
receiver.

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Capture Aware Channel Access Protocol in Wireless Network

4.2 Performance Evaluation of CAMA
In this section we assess the performance of

our proposed framework to mitigate the
interference and leverage the spatial reuse via a
broad picture of the channel state. In this paper,
we assume that information exchange works
perfectly as well as the coordination. We
conducted three different sets of simulations
using different number of sender-receiver pairs
use CBR applications on the same channel.

4.3.1 First Scenario

First, we have conducted a number of
simulations using two links for illustrative
purpose. The position of nodes is sampled from
a two-dimensional distribution in 100x100 m2
indoor environment, as shown in Fig. 5. The
receivers are deployed in overlapping area of
the senders and each tolerates a certain level of
interference depending on channel gain and the

transmit power. The unicast traffic considered is
generated and flowed at a rate sufficient to
saturate the medium. The link gain is assumed
as being fixed for the duration at which power
updates are performed in CAMA framework.

Fig. 6a shows the normalized utility
experienced by users to illustrate the
performance improvement compared to the
default DCF at different power levels. The
default MAC mechanism depends on local
channel assessment to decide whether to
commence a transmission or to defer it. With
default DCF and transmit power level of 19dBm
(Case1), the senders are hidden and transmit
independently. L2 hits the maximum utility with
sender in capture range of the intended receiver,
whereas L1 is seriously affected by co-channel
interference. Fig. 6b shows inefficient channel
usage by S1, in contrast to S2 that being oblivious
of the collisions experienced by R1.

Figure 4. Performance evaluation in terms of normalized utility and channel usage efficiency on L2

for the scenario (c) in Fig. 2 at different traffic loads. In case1, traffic loads Ʈ1= Ʈ2 = 3Mbps.
Case2 considers Ʈ1=2Mbps and Ʈ2=1Mbps, while in case3, Ʈ1 = Ʈ2 = 1Mbps.

Figure 5. Network model and topology as used in the simulation. The nodes disseminate the
estimated link gain to get broader view and perform joint optimization.

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Normalized Utility

S. Mustafa

Higher transmit power can be used to set
symmetric carrier sensing between the senders,
for example 27dBm (Case2). The goal is to
silence a sender when the other initiates a
transmission. Slight different performance: 0.48
and 0.59 of the maximum utility is hit,
respectively over the transmission links.
Collisions occur at R1 when two senders choose
the same slot in the contention window to
transmit their frames since L1 observes less
degree of channel quality; however, this case
doesn’t happen as often compared to the case
when the senders are hidden from each other.

While the default solution for sender out of
the capture range of the intended receiver, is to
preclude the concurrent transmissions, CAMA
framework shows the existence of optimal
transmit power for each node in this scenario to
set up asymmetric carrier sense and satisfy
SINR constraints, where an obvious
improvement in per-flow and aggregate utility
is resulted (Case 3). By switching for example
to transmit power 27dBm at S1 and 19dBm at S2,
R1 and R2; S2 is able to carrier sense data
transmissions from S1 but not vice-versa.

The sender S2 can access the channel during
time interval between successive transmitted
frames of high power sender within its sensing
range. S1 doesn’t block any transmission request
from an upper layer that could overlap with
existing flow. Moreover, if S1’s frame arrives
when S2 is in transmission state, S2 will not be
able to hear this frame even if its transmission
would end very soon after, since the received
energy from S1 is below energy detection
threshold and S2 would have missed the
preamble and PLCP header. We confirmed the
above argument by tracing the transmission
order and inter-transmission time NS-2.34 trace
file.

Albeit the transmission time of the terminals
could overlap and eventually the frames based
on the traffic size, the concurrent transmissions
with the new setting of transmit power don't
introduce enough interference to deprive the
reception. Low power data flow survives the
collision with the early interference frame from

S2 with 𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅1 ≥10dB and hits the maximum

utility. Higher power flow attains that utility

with 𝑆𝐼𝑁𝑅|𝐷−𝐷
𝑅2 ≥5dB that guarantees data

packet delivery: the first captured frame from S2
tends to survive the collision with a later
interference packet from S1. Other SINR

constraints: 𝑆𝐼𝑁𝑅|𝐷−𝐴
𝑅𝑖 ≥5dB and 𝑆𝐼𝑁𝑅|𝐴−𝐷

𝑆𝑖 ≥5dB

are also met to preclude data and ACK packets
collision.

The senders successfully and fairly utilize
the channel wherein normalized utility and
CUE results in Fig. 6 are almost one. The results
demonstrate no starving with asymmetric links
in power heterogeneous network, and confirm
the efficacy of CAMA framework to provide
collision free channel. Our simulation results
with unicast traffic in contrast to the results
have been observed in (Rao and Stoica 2005)
with broadcast traffic over asymmetric sensing
links. Extended Inter Frame Space (EIFS) is
supposed to be the main reason for the
unfairness in the transmission opportunity.
Figure 7 shows FSSE and SSE results
wherein CAMA mechanism obviously has
much better spectral efficiency and fairness
since it gets off hidden and exposed node
scenarios, which are the well known sources for
the limitation of the default mechanism. The
results shows that coordinated and
collaborative framework enables efficient use of
the wireless resource and achieves potential
improvement over DCF.

Figure 6. Performance evaluation in terms of a) Normalized utility, and b) CUE of possible scenarios

with default DCF and CAMA.

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(a) (b)

S. Mustafa

4.3.2 Second Scenario
We substantiated the proposed CAMA

mechanism on larger networks of sender-
receiver pairs distributed in three-dimensional
distribution in 100x100x100m3 indoor
environment with disparity in link quality. The
probability with which a given frame could be
captured by intended receipt is a function of the
number of ongoing transmission. The energy
received from the intended packet should be
higher than total accumulated energy received
from the remainder parallel transmission over
the capture interval, as defined in the equations
(5)-(8). The optimal solution consists of defining
a set of willing end-users to transmit, and apply
CAMA mechanism to enable possible
concurrent transmissions over the channel.

To portray the impact of the aggregate
interference, consider a set of four sender-
receiver pairs (Fig. 8). The distance between the
senders S1, S2, S3 and S4 is roughly 40m except
the distance between S3 and S4 is 70m. The
position of the receivers is sampled such that R3

is within the interference range of S1 and S2, i.e.
either R3 is able to decode the foreign frame
correctly or not, it could engage with overheard
S1 or S2's preamble. R4 is also within the
interference range of S1. Each flow is sending
separate CBR flows to the corresponding
receiver on the same channel.

In a scenario where the nodes have no
knowledge of ongoing hidden transmission
(Case1), S1 and S2 monopolize the channel and
achieve the maximum utility at the expense of
the starving nodes S3 and S4, as simulation
results in terms of utility and FSSE demonstrate
in Figs. 9 and 10, respectively. Average CUE in
terms of the ratio of the aggregate MAC layer
good put at the receivers to the aggregate PHY
layer throughput at the corresponding
transmitters, is also presented in Fig. 10. We
have recorded 10.4Mbps an aggregate utility. In
the next case (Case2), mutual sensing leverages
FSSE and drops SSE with an aggregate utility
reaches roughly 7.2Mbps.

Figure 7. Performance evaluation in terms of fairness and overall spectral efficiency of the scenarios in
Fig. 6.

Figure 8. Four sender-receiver pairs distributed in three-dimensional distribution in 100x100x100m3
indoor environments with disparity in link quality.

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0.2

0.3

0.4

0.5

Case1 Case2 Case3

FSSE (bps/Hz)

SSE (bps/Hz)

Capture Aware Channel Access Protocol in Wireless Network

S. Mustafa

Later, we have applied CAMA mechanism in
Case 3 to find the appropriate transmit power
for each node depending on the interfering
environment it sees, such that parallel uplink
and downlink transmissions cannot introduce
enough interference to corrupt the reception at
neighbor send-receive pairs.

Higher transmit power of 23dBm and 21dBm
are set at S3 and S4, respectively due to the link
quality each sees. Lower power level 13dBm is
set at the remaining nodes such that:

 S1 and S2 are sensing S3 and S4's traffic but not
vice versa.

 S1 and S2 transmit independently as well as S3
and S4 since they don't experience peer
interference.

Power heterogeneous network is required
here to schedule the possible largest number of
successful concurrent transmissions in a single
time slot on a single wireless channel. Various
power levels are set at the nodes to drive a
sender in or out of sensing range of others herby
schedule the time to transmit, and to satisfy the
SINR constraints in equation (5-8). An obvious
improvement is portrayed in the simulation
based results.

Energy detection threshold here is set at the
default value. Individual transmission of S3 and
S4 results in SNR higher than ζED and ζP,
respectively at S1 and S2 that enables either S3's
preamble or energy detection, and S4's energy
detection if S1 or S2 are listening. It is obvious
that their concurrent transmission is also
detectable. As for individual links, we observe
that power adaptation according to CAMA
maximizes S3 and S4’s utility only, and their
saturated traffic especially of S3 reduces
obviously other's opportunity to access the
channel. Nevertheless, obvious improvement in
FSSE and SSE is attained.

Later in Case4, higher ζED is configured such
that S1 and S2 do not sense a delivered energy of
ongoing transmission when the corresponding
preamble is missed. Preamble detection only is
required to schedule the instantaneous
transmissions of senders with homogenous
technology. S1 and S2 knock the channel
frequently to achieve the maximum utility and
subsequently lead to the maximum fairness,
though the power levels are not changed. Fairly
and efficiently channel utilization demonstrates
the efficacy of CAMA framework.

Figure 9. Performance evaluation of different scenarios of four heterogeneous wireless links in terms

of channel gain, and distributed in 3D indoor environment.

Figure 10. Performance evaluation in terms of fairness, overall spectral efficiency and average channel

usage efficiency.

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Capture Aware Channel Access Protocol in Wireless Network

4.3.3 Third Scenario
We next randomly distribute 20 and 50

nodes in a 100x100 m2 indoor environment,
respectively. Each sender has its own receiver
chosen randomly from the set of immediate
neighbors. A random traffic model at each
sender is used with a sufficiently high load such
that a sender to be always backlogged with
packets to send. A high ζED is configured at each
node such that they do not sense a delivered
energy of ongoing transmission when the
corresponding preamble is missed. In this case
study, CAMA uses a genetic algorithm GA
approach for optimal power distribution in a
network. The GA is applied to find the optimal
power level for each user under different
operating conditions based on the constraints
defined earlier. The problem is formulated as a
multi-objective optimization problem which
aims at maximizing the utilization and fairness.
GA can work even when the objective function
is not exactly known since it relies only on an
objective function’s evaluation. It is well-known
for their remarkable generality and versatility,

and has been applied in a wide variety of
settings in wireless networks. The author
skipped the details of GA since it is not in the
scope of the work rather than for applying an
optimization algorithm in CAMA framework.
For details on GA, the author recommends
(Sivanandam and Deepa 2007).

Figure 11 illustrates the aggregate one-hope
utility achieved using 20 and 50 nodes in a
random topology using the default DCF and
CAMA as a channel access mechanism. The
aggregate utility is found as the aggregate
throughput of concurrent one hop
communication in the network. The results are
averaged over three independent simulation
runs. Our approach offers clear improvement
against DCF.

Figure 12 illustrates the average value of the
FSSE and CUE using the default DCF and
CAMA in random topology of 50 nodes.
Performance evaluation in terms of fairness and
the channel usage demonstrates the significant
improvement using CAMA based on a broad
observation of the channel state.

Figure 11. The average of the aggregate one-hope utility in random topology of 20 and 50 nodes.

The results are achieved using default DCF and CAMA mechanism.

Figure 12. Performance evaluation of 50 nodes in a random topology in terms of fairness FSSE and
average channel usage efficiency CUE, using the default DCF and CAMA mechanism.

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20 nodes 50 nodes

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Avg. CUE

S. Mustafa

Through the investigated use cases,
asymmetric carrier sense is introduced and
applied in CAMA. The simulation results
portray the benefit of asymmetric sense
scenario to time schedule the overlapped
traffic without an extra timing signal.
CAMA employs power heterogeneous ad-
hoc network to optimize criteria involving
throughput and fairness. This requires
obtaining effective spatial reuse while
satisfying the interference constraints.

5. Conclusion and Future Work

Based on local channel assessment, the
default DCF mispredicts transmission
failures and wastes potential transmission
opportunities when they exist. It ignores the
possibility of parallel transmissions that
make use of the capture effect. It can be
ineffective even at low traffic load.

This paper proposes a new capture-
aware mechanism for ad-hoc networks
while their benefit is amplified by properly
adjusting the transmission power of the
nodes based on broad observation of the
channel. Through simulations, such a
mechanism is shown to deliver high
network utilization and provide fair access
to the media than the standard DCF that
these networks use. Using the simulator
trace files, we have found that tuning
transmit power is helpful in setting specific
sense scenario and subsequently schedule
the access to a shared medium without
modifying carrier sense threshold, as has
been exploited in CAMA framework in an
interference-free fashion.

The nodes cooperate in power updating
process via exchanging simple control
signaling in power heterogeneous network.
Further, based on the simulation results, we
have found that throwing energy detection
carrier sense line offers higher network
utility.

In environment with heterogeneous
technologies, foreign preambles are
undetectable and energy detection may
results in lower per-flow utility. However,
the target SINR by CAMA at the
corresponding heterogeneous nodes is
expected to be lower since a receiver would
not engage to a first coming foreign
preamble, which in turn enables more
concurrent transmissions and records

higher aggregate utility and overall spectral
efficiency. Our future work will
demonstrate it. We also propose to explore
how a similar mechanism can be used to
adjust more PHY parameters like the PHY
rate or/and contention window size as
MAC parameter.

Conflict of Interest

The author declares no conflicts of
interest.

Funding

No funding was received for this
research.

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