Communications and Network, 2013, 5, 671-677
http://dx.doi.org/10.4236/cn.2013.53B2120 Published Online September 2013 (http://www.scirp.org/journal/cn)
Capacity Based Multicast Channel Assignment in Wireless
Mesh Network
Anju Singh*, Karan Singh, Sandeep Sharma
School of Information and Communication Technology, Gautam Buddha University, Greater Noida, India
Received May 2013
ABSTRACT
Wireless mesh networking (WMN) is an emerging technology that enables multihop wireless connectivity to areas
where wiring o r installing cables is difficult or exp ensive. Multicast is a form of communicatio n that delivers informa-
tion from a source to a group of destinations. In a single-channel WMN, all nodes share and communicate with each
other via the same channel. In such a network, the throughput capacity of multicast degrades significantly as the net-
work size increases. A critical factor that contributes to this rapid degradation is the co-channel interference in sin-
gle-channel WMNs. The major advantage of WMN is that power is not the major issue as compare to other wireless
network like MANET, Sensor etc. Hence Power can be optimally utilized in WMN to increase throughput and total
network efficiency. In this paper, we propose a channel assignment algorithm for multicast based on high channel ca-
pacity with minimum interference. This scheme uses all overlapping and non overlapping channel for the channel as-
signment. By this scheme we provide better performance in terms of average packet delivery ratio, average throughput
and average end to end delay with respect to multichannel multicast channel assignment schemes.
Keywords: WMN; Multicast; Multi Interface; Non Overlapping Channels; Partially Overlapping Channels; SNR
1. Introduction
Wireless mesh network is also known as community
wireless networks. It is an emerging technology that sup-
ports many important applications such as Internet access
provisioning in rural areas, ad hoc networking for emer-
gency and disaster recovery, security surveillance, and
information services in public transportation systems. Due
to its promising technology it is becoming the major ave-
nue for the next generation of wireless mobility [7]. The
technology enables networking capability where wiring
or installing cables are difficult or expensive. Wireless
mesh network (WMN) is a new cost effective technology
which constructs a resilient, locally networked access to
communication infrastructure. This is due to its desirable
characteristics multi-hop routing, auto configuration, band-
width fairness, low cost, easy deployment, self healing
and self organized.
In the recent years, the demand for multicast TV, vid-
eo confer ence and online multicas t based games are huge-
ly increased. More online programs that could be live
soccer match or live performance made the multicast
communication more important research topic in WMNs
[8]. Some commercial deployments are already working
to provide low-cost connectivity to residents and local
businesses. Multicast is a form of communication that
delivers information from a source to a group of destina-
tions simultaneously in an efficient manner. Important
applications of multicast include distribution of financial
data, billing records, software, and newspapers; audio/
video conferencing; distance education; IP television; and
distributed interactive games. Research on multicast in
WMNs has considered mostly networks with a single
channel, i.e., all nodes in the network share and commu-
nicate with each other via one single channel [4]. The
study shows that the throughput capacity of a single-
channel WMN degrades significantly as the network size
increases.
Traditionally, WMN were equipped with node having
a single radio. They were faced with number of limita-
tions such as lower throughput and limited use of availa-
ble wireless channels [5]. Major issue of wireless net-
work is its deployment so WMN are preferred over other
wireless network due to its random assignment node and
capacity enhanced feature. But, using single channel creates
interference like hidden terminal problem and exposed
terminal problem. So, this problem can be improved by
using multi channel in wireless mesh network.
Multiple channels with multi radio are one of the most
*Corresponding a uthor.

A. SINGH ET AL.
672
effective approaches to achieve higher throughput. The
network throughput in these multichannel systems can be
increased multiplicatively at the cost of additional inter-
face equipment. The tremendous popularity of wireless
networking in recent years has led to the commoditiza-
tion of wireless radios whose prices have fallen dramati-
cally thanks to technology advances and mass production
[6]. Therefore, the idea of multi-interface multi-channel
wireless networking is very promising, allowing us to use
two or more radios on the same device. The network has
n channels, which may either overlap, such that a channel
partially shares its frequency spectrum with the adjacent
channels, or may be completely separated (non-overlap-
ping or orthogonal). Orthogonal channels do not interfere
with each other.
This paper focuses on the channel allocation scheme
which efficiently utilizes multiple wireless interfaces to
achieve better throughput thereby increasing the network
capacity. We are using the capacity based channel as-
signment in which channel are assigned on the basis of
the link which has high capacity and have some channel
difference to al read y ass igned chan nel. On av erag e, a mul-
tichannel wireless network at least doubles the through-
put, since each node is now in full-duplex mode, being
able to transmit and receive simultaneously. Multi-in-
terface networks, in return, require efficient channel as-
signment (CA) and routing algorithms that can take ad-
vantage of multiple channels and multiple interfa ce s .
2. Related Work
Guokai et al. [1] proposed the channel assignment scheme
through Ascending and Heuristic approach. In which in-
itially construct the multicast tree using level channel as-
signment (LCM) and multichannel multicast (MCM) ap-
proach then assign the channels to it. Mesh network in-
itially needs to convert in a spanning structure and Tree
structure is the least complex structure. So by LCA and
MCM form the tree. Level Channel Assignment (LCA) is
a method to build a multicast tree. Initially, the nodes
obtain their level information [2]. The BFS is used to
traverse the whole network. All the nodes are portioned
into different levels according to the hop count distances
between the source and the nodes. If node a (in level i)
and b (in level i + 1) are within each other “s” communi-
cation range, then “a” is called the parent of “b”, and “b”
is called the child of “a”. Then build a multicast tree
based on the node level information. Initially, the source
and all the receivers are included in the tree.
Then, for each multireceiver v, if on e of its paren ts is a
tree node then connect it with that parent, and stop. Oth-
erwise randomly choose one of its parents, say fv, as
relay node on the tree, and connect v and fv. Afterwards,
we try to find out the relay node for fv recursively. The
process repeats until the entire multireceiver is included
in the multicast tree.
The tree nodes decide their channel assignment with
the level information.
• The source node (level 0) only uses one interface,
which is assigned channel 0. This interf ace is respon-
sible for sending packets to the tree nodes in level 1.
• The internal tree node in level i (i ≥ 1) uses two inter-
faces: one is assigned channel i − 1, which is used to
receive packets from the upper level; the other is as-
signed channel 1, which is used to forward the pack-
ets to the tree nodes at level i + 1.
• The leaf in the level i (i ≥ 1) uses two interfaces: one
uses channel i − 1 to receive the packets from level i
− 1, the other uses channel i to forward the packets to
the mesh clients within the communication range that
desire to receive the packets.
For example in Figure 1, the node s is the source and
nodes f, g, e are the multireceiver. In Figure 1 {s, f, g,
and e} are included in the multicast tree. Since nodes of
g’s parents are tree nodes, it randomly selects d as a par-
ent node and connects node g with d. Then choose d’s
parent b as a tree node and connect d with b. Since b’s
parent s is a tree node connect b with s. Next, we start
from multireceiver e. Connect e with its parent node b
and stop because b is alr eady connected with tree node s.
Similarly the third multireceiver f, connect f with c, c
with a and then a with s. Thus the tree construction is
completed by connecting all the receivers with the tree.
Multichannel Multicast ( MCM) is another approach to
construct multicast tree in which the throughput increases
effectively [3]. Here the main aim is to minimize the
number of relay nodes and hop count distance between
source and destination. When all the Nodes are multire-
ceiver, the multicast problem becomes the broadcast prob-
lem. Broadcast is a special case of multicast. The broad-
cast structure in the mesh netw ork is built by the follow-
ing steps:
• After the BFS traversal, all the nodes are divided into
different levels.
Figure 1. LCA mesh tree mesh.

A. SINGH ET AL.
673
• Delete the edges between any two nodes of the same
level, with which we get the elementary communica-
tion structure “tree mesh”.
• Identify the minimal number of relay nodes that form
the broadcast tree.
Using more relay node means more transmissions in
the network. Because the number of available channel is
limited, more transmissions would result in more inter-
ference and result in more bandwidth cost. Hence, mini-
mizing the multicast tree size helps to improve the
throughput. The purpose of this step is to identify the
relay node for a node that has more than one parent
nodes so that the number of relay node is minimal. In
broadcast structure unnecessary branches are present if
the destinations do not involve all the nodes. Hence, we
propose to construct a structure using the MCM Tree
Construction algorithm. The goal of the algorithm is to
discover the minimal number of relay nodes needed to
construct a multicast tree. The search process starts from
the bottom to the top.
A simple example is shown to explain the process in a
tree mesh in Figure 2, where nodes 6, 7, and 8 are the
multireceiver. First select node 4 at level 2 because it
covers all the multireceiver at level 3. Next select node 2
at level 1, which covers all the multi receivers and the
relay node at level 2. By doing these steps finally we get
the multicast tree in Figure 2 because it covers all the
multireceiver at level 3. Next select node 2 at level 1,
which covers all the multi receivers and the relay node at
level 2. By doing th ese steps finally we ge t the multicast
tree in Figure 2.
Ascending Approach: In ascending approach from
top to down in the tree, the channels are assigned to the
Interfaces in the ascending order until the maximum chan-
nel Number is reached, then start from channel 0 again.
Each child node of a parent gets the same channel alloca-
tion. This approach avoids the situation that the same
Channel is assigned to two nearby links that interfere
with each other. The number above the node represents
the channel number used for its RI, while the number
below the node represents the channel number for its SI.
In the algorithm, only the limited orthogonal Channels
Figure 2. Multichannel multicast tree construction.
are used. 802:11b provides 11 channels in American do-
main which are 5 MHz apart in frequency. To be totally
orthogonal, the frequency should be at least 30 MHz, so
802:11b can offer only three non-overlapping channels.
Thus, although the Ascending Ch annel Allocatio n is easy
to implement, its performance is still constrained by the
limit e d number of orthogonal c ha n ne ls.
Heuristic Approach: In this, utilize all the channels
available in ban d. Interference range decreases with chan-
nel separation. If physical distance is short b/w two wire-
less links then channel separation should be large. Here,
main objective is to minimize the sum of interference
area of all transmission. Bigger interference area means
bigger chance two transmissions may interfere. When al-
locating a channel for relay node u, the channel assign-
ment should take a channel that minimizes the sum of the
square of the IRs between u and us neighbouring relay
nodes, that is, minimize IR 2(uv) where N(u) represents
the set of the neighbouring relay nodes of u. This is be-
cause the bigger interference area means the bigger chance
two transmissions may interfere.
3. Proposed Work
The existing schemes of channel assignment in WMN
used the non overlapping channels only and provide im-
provement in system performance characteristics like
throughput, delay but wasted the limited resource. In the
proposed work we will show the use of all available
channels.
3.1. System Model
We model a WMN as a graph G (V, E), with nodes V
and links E. Assume T ⊆ V is the set of gateways. Each
gateway has a high-bandwidth connection to the Internet,
and can be viewed as a data source. Let S be the set of
data transmission sessions. We define five vectors of
variables. The first four are: the vector of data flows f;
the vector of multicast throughput r; the vector of link
capacities c; and the power assignment vector P. The last
one is on channel assignment. We assume that each node
is equipped with radio of capacity c. Here Γ represents
the set of pre-defined channels in the IEEE 802.11b/g
standard.
There are many chann el assignment schemes for WMN
that are basically based on the channel separation con-
cept. On the basis of channel separation, authors mainly
defined that if channel separation between two adjacent
channels is 4 or more than 4 then channel correlation
coefficient is minimum. We know th at interfer ence facto r
between channels is direc tly proportion al to channel cor-
relation coefficient. So if channel correlation coefficient
value is zero then interference factor will be zero. On the
basis of this concept only some specific channels mostly

A. SINGH ET AL.
674
near about 3 channels amongst 11 available channels of
IEEE 802.11 standards are used. But, in our proposed
scheme for each transmission we use one of the 11 chan-
nels of IEE E 802.11 standard. Now w e proposed a chan-
nel scheme that is based on channel capacity and channel
separation both. We know that channel correlation coef-
ficient is inversely proportional to chann el separation and
channel interference is directly related to channel corre-
lation coefficient. We analyse that if channel capacity is
high then it can tolerate some amount of interference. We
find that channel capacity not only depends upon the
channel separation but also depends on some other fac-
tors. So, channel capacity of channel defined by the fol-
lowing equation
Where b bandwidth, Gee = Gain, Pe = Power of chan-
nel e, Ile = Channel correlation coefficient, Pl = pow er of
channel l, Gle = Interference coefficient between channel
e and l, σ2 = Noise associated with a link.
C = blog2 (1 + SINRe) (1)
Where,
ee e
e1e 11e2
1e
GP
SINR I PGσ
≠
=+
∑
(2)
So, we observe that my proposed work which is based
on channel capacity show that when channel capacity is
high, it can tolerate up to a threshold limit of channel
interference factor.
3.2. Procedure for Channel Assignment
We are prov iding the procedure of proposed work in fol-
lowing way:
STEP 1 Create mesh network with the help of adja-
cency matrix. Set stack of all channels.
STEP 2 Given total no. of channels C that is defined
in IEEE 802.11 standards.
STEP 3 Now set the parameter for all channels, ac-
cording to equation number 1.
STEP 4 Use BFS algorithm for traversing node from
source node to all destination nodes.
STEP 5 Assign any channel to source node S.
STEP 6 Now, calculate the current link capacity using
Equation (1) for next all intermediate nodes between
source to all destination and calcula te the chann el sepa-
ration between assumed and already used channel.
STEP 7 Check the assignment requ irement:
1) If calculated channel capacity is m ore than thre-
shold capacity.
2) If channel separation is more than threshold.
STEP 8 Select channel e for which Ce is maximum
and channel separation is more.
STEP 9 Assign that channel Ce to current Node.
STEP 10 Repeat these steps 4 to 8 until all stacks are
empty.
4. Result Analysis
4.1. Simulation Environment
The proposed work is simulated in QualNet in which a
simulation environment is created for demonstrating the
channel Assignment schemes for wireless mesh network.
4.2. Performance Matrices
Packet delivery, throughput and delay are major perfor-
mance criteria for channel assignment schemes for wire-
less mesh network.
4.3. Simulation Parameters
We simulated a small network of 50 nodes uniformly
distributed over a 1000 m × 1000 m area shown in Fig-
ure 3. The transmission power and transmission range of
each node were varying. We adapt the uniform distribu-
tion to distribute loads evenly and to minimize interfe-
rence among routers. The number of nodes and the cor-
responding network size were chosen in such a way that
there were no disjoint nodes or network pa rtitions through-
out the simulation. The uniform distribution of nodes, the
network size was computed such that any one-hop neigh-
boring nodes were within the transmission range of each
other. We used the IEEE 802.11b standard at the physical
layer with a transmission rate of 11 Mbits/s. The IEEE
802.11 Carrier Sense Multiple Access with Collision
Avoidance (CS-MA/CA) is chosen as the medium access
control (MAC) for multicast transmissions.
Each multicast group has one source. The source of a
multicast group transmits at a constant bit rate properly
set for each experiment. The numbers of multicast desti-
nations (the group size) are also specified for each scena-
rio. The source and the destinations of a multicast group
were selected randomly. All destinations joined a multi-
cast group at the beginning and stayed until the whole
group terminated. In each experiment, the source sent
data for 300 seconds of simulated time, at a constant bit
rate specified for each experiment. After the source fi-
nished sending, the simulation continued to run for 100
seconds of simulated ti me to give the last packets time to
be processed and routed, for a total of 400 seconds. This
400-second duration does not include the time needed for
constructing the routing tree at the beginning.
4.4. Experiment Scenario
We measured the average packet delivery ratio, end to
end delay and throughput as functions of Multicast Source
Rate, Multicast Group Size, Number of Channels
The source rate was varied from 10 to 100 packet s/s.
The total number of channels, including overlapping and
non-overlapping channels, was 11.

A. SINGH ET AL.
675
Figure 3. Network topology.
The number of multicast destinations in the multicast
group ranged from 1 to 30 nodes in the 50-node network.
The multicast source rates were set at 60 packets/s and
40 packets/s in the small and medium-size networks,
respectively. Number of channels: The total number of
overlapping and non-overlapping channels was varied
from 1 to 20. In the small network of 50 nodes, there
were 20 multicast destinations, and the multicast source
rate was set at 60 packet s/s.
4.5. Function of Multicast Source Rate
The sender’s rate varies from 10 to 100 packets/sec.
Multicast group is of 20 receivers in the network of 50
node. When traffic load is light (10 - 20 packets/sec)
there is less contention and usage of channel, the multi-
cast group did not take advantage of MCMR. A single
channel is adequate for this case. When traffic load is
moderate (above 40 packets/sec) the advantage of multi-
channel can be seen.
The Figure 4 shows that when the load of the traffic
increases, packet delivery ration decreases. For both
schemes MCM and CBM-CA we observe that as traffic
load increases packet delivery ratio decreases. But we see
that our CBM-CA based schemes give the better result as
compare to MCM schemes because in our scheme,
channel capacity is high at all link and also find that in-
terference b/w channel also very low so the ratio of no.
Figure 4. Average PDR.
of packet send and no. of packet receive is high means no.
of packet deliver at each link. In the figure we see when
traffic load is 10 packet/s then the packet delivery ratio
for CBM-CA schemes near about 90% and when the
traffic load is 100 packet/s the PDR is above 70% that is
good in compar ison to MCM.
The F igure 5 shows the average throughtput for the
different traffic loads. We observe that that no. of packet
received in given time interval increases as traffic load

A. SINGH ET AL.
676
Figure 5. Average Throughput.
increases. In both schemes CBM-CA and MCM it hap-
pened that average throughput increases as traffic load
increases. But in the case of CBM-CA provide better
throughput as compare to MCM because no. of packet
delivery rate of each channel in the multicast tree is high
as compare to assign the channel in MCM schemes.
In the Figure 6 we observe that as the traffic load in-
creases the average end to end delay some times increas-
es and some time decreases. We observe that for the
CBM-CA based schemes the end to end delay is near
about 42 ms for the traffic load 10 to 100 packet/s and
for MCM 44 ms so we find the end to end delay in case
of CBM-CA gives better result due to high capacity. For
all three cases, as the sender’s rate increas es, the through-
put increases as expected; the PDR decreases because
higher loads cause more congestion and collisions, re-
sulting more packets dropped or damaged.
4.6. Function of Number of Channels
The number of channels in this set of experiments is va-
ried from 1 to 20. The multicast group in the 50-node
network has 20 receivers, and its source sends at a rate of
60 pkts/s. This rate yields a moderate load for the given
group size in this netw ork.
Figure 7 shows that as the no. of channel increases the
packet delivery rate ratio will increase. In the figure we
observe that the CBM-CA based schemes show the better
result as compare to MCM based channel assignment
scheme, as the no. of channel increases the no. of non
overlapping channel increases and interference decreases
so that PDR increases. In the case of CBM-CA capacity
of each link also high with minimum interference so that
gives the better result as compare to MCM.
The performance of CBM-CA is only slightly better
than of MCM in this set of experiments. In the Figure 8
Figure 6. Average End to End Delay.
Figure 7. Packet delivery ratio.
Figure 8. Average throughput.

A. SINGH ET AL.
677
shows the average Throughput for different channels. We
observe that average throughput increases as no. of chan-
nel increases and see that CBM-CA gives the better re-
sult as compare to MCM.
5. Conclusion
In this paper, we proposed the capacity based multicast
channel assignment (CBM-CA) algorith m. The o ptimiza-
tion function of the CBM-CA algorithm uses channel se-
paration and channel capacity and thus does not rely on
the computation of the interference factors. Advantages
of our proposed algorithm include its simple implemen-
tation and high performance. The effectiveness of the
CBM-CA algorithm is maximized in a network where
the multicast group (tree) is dense. In such environment,
the number of neighbouring nodes around a node is high
and thus, without a carefully designed channel assign-
ment (CA) algorithm like CBM-CA, the probability of
channel conflicts among nodes would be very high. Our
simulation results showed that the CBM-CA algorithm
outperforms MCM in terms of average PDR, throughput,
and end-to-end delay under various traffic loads, group
sizes and different number of channels. We introduced an
approach based on channel capacity to address the CA
problem in multicast WMN to maximize throughput. Our
simulation results showed that the CBM-CA algorithm
outperforms MCM in terms of average PDR, throughput,
and end-to-end delay under various traffic loads, group
sizes and different number of channels.
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