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ALLOCATION OF DYNAMIC CHANNELS FOR TDMA- BASED
MULTI-HOP CELLULAR NETWORKS Mohammed Imtiaz Ali Ahsan
Dept. of ECE, Muffakham Jah College of Engg & Tech, Hyd, AP. India, [email protected]
ABSTRACT - In this paper, I proposed a multihop
dynamic channel assignment (MDCA) scheme fortime division multiple access (TDMA) - based
multihop cellular networks. The proposed MDCAassigns channels to calls based on interference
information in surrounding cells, provided by theinterference information table (IIT) in the network.
Two different channel searching strategies,sequential channel searching (SCS) and packing
based channel searching (PCS), for use in MDCA isproposed and implemented. The channel - searchingalgorithm can be formulated as an optimization
problem and it can be proved that the proposedscheme can result in a sub-optimal solution.
Furthermore, the MDCA can efficiently alleviate thecall blocking in larger areas, this analysis compares
the feature of fixed channel assignment scheme anddynamic channel assignment scheme, hence proves
that dynamic channel allocation is more optimal.There is also an implementation of dynamic channel
allocation based on the service request.
Key Words — Multihop Cellular Networks, Channelassignment, MANET clustering
INTRODUCTION
In order to achieve efficient resourceutilization in all sorts of deployment scenarios and
QoS requirements in the future wireless cellularsystems, new resource allocation methods must be
developed. However, optimum point has to be foundbefore considering the implementation practicality.
Importance of resource scheduling was appreciatedwith the support of high data rate services in the
evolution of UMTS standard to High SpeedDownlink Packet Access (HSDPA) [1] and
Enhanced Uplink [2]. A variety of resourceallocation strategies and schemes, mainly for
downlink, can be found in references [3]-[8]. In [3] asystem with multiple traffic classes was considered
and resource allocations were based on the specific
characteristics of traffic flows resulting inminimization of power consumption or
maximization of system capacity.Under mixed service traffic including both
real-time and non-real time services, efficientresource allocation from a shared resource pool is a
challenging task due to varied and stringent QoSrequirements. In [4] authors proposed a fixed
resource partitioning method in which total resourcepool was partitioned between different serviceclasses and independent resource schedulers were
responsible for each resource partition whereas in[5], scheduling was more unified and partitioning
was dynamic to enhance spectral efficiency. Anotherapproach towards resource allocation, called utility
based approach, tries to maximize the total networkutility and thereby enhancing resource allocation.
For example, pricing is a well-known utilityfunction used in [6] for resource allocation. In [7]
authors used user’s QoS as utility function and thenconvert the resource allocation problem into a non-
cooperative game where each user tries to maximizeits own utility. A downlink resource allocation
method based on dynamic pricing was proposed in[6] aiming to maximize the summation of users’
utility. On the link level, adaptive transmission isone of the most recent technologies being
investigated for enhancing the spectral efficiency infuture cellular systems [7]. Fast scheduling together
with adaptive modulation-coding, facilitatesexploitation of channel variations resulting in multi-
user diversity gains [6].
PROBLEM OUTLINE
In an interference-limited system such asUMTS, the uplink cell capacity is basically limited
by the total received uplink power at the base stationdue to the transmit power limitation of user
terminals [6]. In decentralized scheduling, each base
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station assigns radio resources to its users on apriority basis until the estimated Rise over Thermal
noise (RoT) level reaches a pre-defined target.Recent studies in Enhanced Uplink UTRA, also
called High Speed Uplink Packet Access (HSUPA),show that the decentralized scheduling has better
performance compared with centralized one [2]. Thesubject of centralized versus decentralized
scheduling has been studied extensively in recentyears both in 3rd Generation Project Partnership
(3GPP) standard body for HSUPA and in theliterature [2]. The performance of centralized packet
scheduler of the UMTS system is evaluated in [2]the performance of a decentralized scheduling is
evaluated and compared with the centralized one in[5].
Extensive simulation results on interferenceoutage, throughput and packet delay performance of
a reference decentralized scheduling together with
the proposed IIT Matrix approach are provided andcompared. It should be noted that although HSUPAsystem is used to demonstrate the performance of
the IIT Matrix, the concept is generic for single-carrier spread spectrum based systems where cell
RoT is widely used as a good load indicationdirectly linked to cell load. In multi-carrier systems
however, the load on subcarriers can differsignificantly and therefore RoT (averaged) is no
longer a good measure for load over all subcarriers.One can think of an effective RoT, encourage by the
introduction of effective SINR in multicarriersystems to provide a better and more accurate link
system mapping.
MULTIHOP CELLULAR
COMMUNICATION
Wireless networks are characterized with
their wireless last hops within the communicationchain from any arbitrary node to any mobile
terminal. This means that the mobile terminals are
connected to the fixed network with a wireless link.This link is most of the time a radio channel. Radiochannels are frequency bands used for
communication that are separated from each otherwith guard bands. If two sources try to send data
over the same channel at the same time, then thedata sent cannot be received by the receiving end
properly. Although there are alternative ways toaccess the medium and define the channel concept
differently, this definition is enough for thediscussion of the cellular concept.
If a large area is to be included in thewireless communication system, then there are a few
possibilities to manage this. The first possibility is tohave a single big transceiver antenna. This case is
similar to the radio transmitters that service a largearea. Let this antenna with its proper equipment be
called Base Station (BS). On the other hand, ifmultiple users of the system want to use it, there
should be enough channels available for eachconnection. Otherwise, the users should wait until
the channels become available. If only one basestation is present in a certain area, then there should
be enough number of channels available in order tokeep the rejection probability at a reasonable level,
which is infeasible most of the time.Since the number of channels are scarce
most of the time and the number of users willing touse the system cannot be predetermined easily, it is
necessary to reuse the limited number of channels in
the system. If the antennas of the base stations areplaced far enough from each other such that theinterference level is below a certain level, both
communication sessions can continue over the samechannel simultaneously. Let the area in which a base
station is active as a cell. The power level of thereceived signal can be expressed as in [5]:
P Pd
d r 0
0
(2.1)
The term Pr is the power level received at a distance
of d from the antenna, P0 is the measured powerlevel at a distance of d0 and the is the path lossexponent, which is in the order of two to four in the
urban environments.In order to continue proper communication,
the signal level from the base station serving thecalls in the cell should be so large that another base
station using the same channels should be almostimperceptible. It is enough to consider only the
nearest neighboring base stations that use the samechannels because the signal power level received
from other base stations will be at most 4-
timesthat of the next such base station according toFormula of 2.1.
In order not to leave any gaps between thecells, several strategies are developed. The
frequency set is divided into subsets and each basestation is assigned a certain subset. The placement
of the base stations is one of the problems that has tobe solved and is investigated in [7].
The ideal shapes of the cells are hexagons.With hexagonal layout a certain area can be covered
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completely without leaving a gap. Furthermore, thisshape can easily be obtained if the omni-directional
antennas of the base stations are placed such that theboundaries of the cells are determined by the signal
power of corresponding base stations. Anotheradvantage of this shape is that the differences
between the closest and farthest points on theboundaries are minimal among the shapes that can
cover an area without any gap. This assures that thepower level difference on the boundaries of a cell is
minimal. In reality, though, the shapes of the cellsare anything but hexagon due to terrestrial factors.
Figure1: A Cellular Layout (Cluster Size=7)If the whole frequency set is completely used by N
cells, then these cells constitute a cluster and thecluster size in that system is N and is a very
important system parameter. It shows a typicalcellular layout with cluster size equal to seven. The
numbers in the hexagonal cells indicate the channelset used within the cell.
For hexagonal cells, the cluster size can becalculated as follows:
N i ij j i j Z 2 2, , (2.2)
The co-channel reuse factor Q is the ratio of the distance D between the cell centers that use the
same frequency set to the larger radius R of thehexagonal cell. Q and N are related to each other
with the following formula.
Q D
R N 3 (2.3)
The signal to interference ratio S/I is themeasure of requested signal to co-channel
interference ratio. Furthermore, if there are i0 immediate neighbors using the same co-channel set,
S/I can be approximated as:
S
I
D R
i
N
i0 0
3(2.4)
If the value of Q is small, the system
capacity increases since the value of N is also smalland the channels can more frequently be used over a
given area. On the other hand, if the value of Q is
large, this leads to better transmission quality sincethe S/I ratio increases. At the same time systemcapacity decreases [5]. The choice of N depends on
the quality of the transceivers used and the terrestrialfactors. It should be chosen as small as possible and
as large as necessary. When the necessary S/I isdetermined, the cluster size is also determined and
vice versa.It is very interesting to note that calculation
of the required signal to interference ratio isindependent of actual radii and distances. Once the
cluster size is determined, the designer is free tochoose any radius for the cells. Hence, the cell
radius is an engineering parameter in the cellularnetwork design problems.
All the wireless communication networksbased on the cellular concept are called cellular
networks.
RESOURCE ALLOCATION STRATEGY
The key idea of CMCN is to achieve thecharacteristics of the macrocell/microcellhierarchical overlaid system [7] by applying
MANET clustering [4] to TCNs. As shown in Fig. 1,a BS in TCNs covers the entire macrocell with a
radius rM. The transmission ranges of traffic andcontrol channels are the same and equal to rM forboth the BSs and MSs. In CMCN, a macrocell is
divided into seven microcells with a radius of rm.Each virtual microcell can be divided into two
regions: inner half and outer half. The inner half is
near the central microcell. The transmission range ofthe traffic channels in CMCN for both the BSs andMSs is equal to rm. The transmission range of the
control channels for the BSs and MSs is equal to rMso that the BS can communicate with all the MSs
within its macrocell area for control informationexchange. In this study, the microcells are virtually
formed by the BSs based on the geographicinformation using IIT, e.g. global positioning system
(GPS).
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1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
30
35
40
communication time
S y t e m T h r o u g h p u t
Throughput plot for the syst em
Non-Monitored
Monitored-IIT
Figure 5: obtained throughput of the developedsystem for both monitored and non-monitored
communication.
CONCLUSION & FUTURE SCOPE
Due to the multiple requesting of channels,
they are getting blocked at the link points and thisresults in very high network overhead. In this work
an allocation strategy for channel is developed basedon requesting micro-cell of IIT. The required
channels are monitored and allocated at theswitching terminals based on the channel searching
strategy developed. The feasibility of applyingallocation scheme for multihop cellular
communication system is developed. A multihopdynamic channel allocation scheme with two
channel searching strategies is developed.
For clustered network, results show thatMCN with adaptive allocation can improve the
system capacity greatly as compared to FCA andDCA communication system.
The suggested approach is developed formultihop traffics in cellular architecture. The work could be further improved by improving the
allocation strategies incorporating allocation withavailability and resource allocation such as required
power; data rate etc. For further improvement, thechannel allocation at micro cell level could also be
developed as sub channel access strategy forresource utilization.
REFERENCES
[1] Xue Jun Li, and Peter Han Joo Chong, IEEETransactions on Wireless Communications, Vol.7,
NO.6, June 2008.
[2] The Portio Research Limited, Worldwide MobileMarket Forecasts 2006-2011, Market Study, UK,
2006.
[3] H. Wu, S. De, C. Qiao, E. Yanmaz, and O.Tonguz, “Managed mobility:
a novel concept in integrated wireless systems,” in Proc. IEEE MASS’04,
pp. 537-539, Fort Lauderdale, FL, Oct. 2004.
[4] H. Luo, R. Ramjee, P. Sinha, L. E. Li, and S. Lu,in Proc. ACM MOBICOM’03, pp.353-367,CA, Sept.
2003.
[5]Rose,C.and R.Yate, Location Uncertainty inMobile Networks: IEEE Communications
Magazine, pp.94-101, February 1997.
[6] Special Issue on Mobile Computing, InternalReport Number MPG-94-18, 1996
[7] Pollini,P.P, “Trends in Handover Design,1996,http://www.ieee.org/comsoc/pollini.ht
[8] Çayırcı, E. and C. Ersoy, “Cell Grouping in PCS
Networks,” Proceedings of the Second Symposiumon Computer Networks, pp. 14-41, Ankara, Turkey,
1997.
ACKNOWLEDGEMENTS
The Author is thankful to Prof. Dr. Kaleem Fatima,Head Dept. of ECE, MJCET for her encouragement
and is also highly thankful to the management ofMuffakham Jah College of Engineering and
Technology for their financial support.