smriti dissertation report

7/30/2019 Smriti Dissertation Report

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1. INTRODUCTION

1.1BackgroundOne main issue in cellularsystem design reduces to one of economics. Essentially we have

a limited resource transmission spectrum, which must be shared by several users. Unlike

wired communications which benefits from isolation provided by cables, wireless users

within close proximity of one another can cause significant interference to one another? To

address this issue, the concept ofcellularcommunications was introduced around in 1968

by researchers at AT&T Bell Labs. The basic concept being that a given geography is

divided into polygons called cells [2].

Fig .1 Cellular network model

Cell is allocated a portion of the total frequency spectrum, which is channel [1].

A channel is a communication medium, the path that data takes from source to

destination. A channel can be comprised of so many different things: wires, free space, and

entire networks. Signals can be routed from one type of network to another network with

completely different characteristics. In the Internet, a packet may be sent over a wireless
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Wi-Fi network to an Ethernet Lan, to a DSL modem, to a fibre-optic backbone, etc. The

many unique physical characteristics of different channels determine the three

characteristics of interest in communication: the latency, the data rate, and the reliability of

the channel.

If channel is considered as the highway, then the bandwidth is like the number of lane in

the high way. More lanes mean more traffic at a time and high speed transportation.

Bandwidth also refers to as grade, tells us the rate, or speed at which data can be

transmitted over the channel.

There are three brands for communication channel:

Narrow Band Channel--

Narrow band channel or the low speed channel is the slowest band, transmits the data from

40 bit per second to 1200 bits per seconds. Telegraph lines are the example of narrow band

channel.

Voice Band Channel--

Voice band channel or the medium speed channel is faster than narrow band channel, and

transmit data from 110 bits per second to 9600 bits per second. Telephone lines are theexample of voice band channel.

Broad Band Channel--

Broad band channel or the high speed channel is the fastest channel which transmits data

up to several million bits per second and in special cases, goes up to billions of bits per

seconds. Coaxial cable, fibre optics, and Microwave are the examples of broadband

channels.

The "capacity" of a channel is the theoretical upper-limit to the bit rate over a given

channel that will result in negligible errors. Channel capacity is measured in bits/s.

Shannon's channel capacity is an equation that determines the information capacity of a

channel from a few physical characteristics of the channel.

Channel allocation deals with the allocation of channels to cells in a cellular network.

Once the channels are allocated, cells may then allow users within the cell to communicate


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via the available channels. Channels in a wireless communication system typically consist

of time slots, frequency bands and/orCDMA pseudo noise sequences, but in an abstract

sense, they can represent any generic transmission resource.

Common Principles of Channel Allocation Schemes:

The large array of possible channel allocation systems can become cumbersome. However,

all channel allocation methods operate under simple, common principles. Throughout this

report we have touched on three points which an efficient channel allocation scheme

should address:

1. Channel allocation schemes must not violate minimum frequency reuse conditions.

2. Channel allocation schemes should adapt to changing traffic conditions.

3. Channel allocation schemes should approach (from above) the minimum frequency

reuse constraints so as to efficiently utilize available transmission resources.

Each mobile service station (MSS) is assigned a contiguous range of channel not

overlapping with those of its neighbours. Channel boundaries between adjacent MSSs are

dynamically adjustable through voluntary withdrawals. High efficiency is provided by two

important features: early boundary expansion and need-based boundary redrawing [10].

Environment consists of assigning channels to the radio interfaces in order to achieve

efficient channel utilization and minimize interference. The problem of optimally

assigning channels in an arbitrary mesh topology has been proven to be NP-hard based on

its mapping to a graph-colouring problem [6] & [7]. Therefore, channel assignment

schemes predominantly employ heuristic techniques to assign channels to nodes in the

network.

There are three major categories for assigning these channels to cells (or base-stations).

They are

Fixed Channel Allocation,

Dynamic Channel Allocation and

Hybrid Channel Allocation which is a combination of the first two methods.

In FCA, according to predetermined traffic demand and co-channel interference

constraints, a fixed number of channels are assigned to each cell. [1] FCA is very simple
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but this scheme is difficult to survive in changing traffic conditions and user distributions.

Over the whole service area if traffic varies from cell to cell, FCA could not attain a high

efficiency of total channel usage. DCA strategy has been proposed, in order to overcome

the problems of FCA.

In DCA, channels are not allocated to cells permanently [1]. For every call request base

station request channels from MSC. According to the duration of the calls, channels are

assigned temporarily for use in cells. The channel is returned back and kept in the central

pool, after the cal is over. In order to avoid co-channel interference, any channel that in use

in one cell can only be reassigned to another cell simultaneously if the distance between

those two cells is larger than the minimum reuse distance. DCA needs many transceivers

for each base station. Behave well in low load but behave worse than FCA in heavy load.

HCA strategy has been proposed, in order to overcome the problems of DCA. DCA

schemes are suggested for TDMA/FDMAbased cellular systems such as GSM, but are

currently not used in any products.

HCA, The third category of channel allocation is hybrid channel allocation; it is hybrid

of fixed and dynamic channel allocation algorithm [2]. Channels in HCA are divided into

two disjoint sets-

First is fixed set: set of channel which is assigned to each cell on FCA basis.

Second is dynamic set: set which are kept in a central pool of MSC for dynamic

assignment.

Fixed set channels are preferred for use in their respective cells, which are assigned to

cells as in the FCA schemes. When a mobile user demands for a channel for its call,

channel is assigned from fixed set, but when all the channels in its fixed set are busy, only

then a request is made from dynamic set of central pool. The ratio of the fixed channels

and dynamic channels plays a vital role in channel allocation scheme, if the ratio is 50% or

more, than FCA performs better than HCA as in [1].

1.2 Motivation

The motivation behind this project is to decrease the call drop rate in wireless

mobile communication systems; since the available frequency spectrum is limited the

channels must be reused as much as possible in order to increase the system capacity. This
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requires a proper channel allocation scheme. Channel allocation becomes complicated,

when more than one cell become hot-spot. The term hot-spot means the bandwidth

resources currently available in those cells are not sufficient to sustain any more call [3]. In

this thesis, we present a novel Hybrid channel allocation scheme in which MSC will fetch

those ideal channels, which are borrowed to requesting cell from the central pool in the

time of hot spot and become ideal for some period of time. MSC make use of these

channels in order to sustain new incoming call.

1.3 Thesis Objective

In this thesis, we have concentrated on the issues of decreasing call drops in wireless

communication system. The aim of undertaken work in this thesis includes:

a) Study of various channel allocation scheme and their performance.

b) Implementation of hybrid channel allocation with hot-spot notification.

c) Performance evaluation of the proposed scheme using various results under call

drop rate, call block rate, handover and system load.

d) Comparison of proposed method with the existing hybrid channel allocation

scheme.

1.4 Thesis Outline

The thesis is organised as follows:

The thesis is organized as follows: chapter 2 contains literature survey of various channel

allocation technique and topics related to problem domain. The approaches used by

different researchers differ in the type of channel allocation. Chapter 3 covers background

theory which includes description of all the channel allocation technique, comparison

between them, and hot-spot condition. In Chapter 4, the proposed method for decreasing

call drop rate in hybrid channel allocation with hot-spot notification in detail. Chapter 5

includes implementation of our proposed system. Chapter 6 presents the experimental

results for hybrid channel allocation with proposed techniques. Finally chapter 7 includes

the conclusion and future scope.


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2. LITERATURE REVIEW

The radio spectrum allocated to wireless cellular mobile communication system is fixed

one. Efficient use of available spectrum will produce an increased number of users [4].

The fundamental operational principle of wireless cellular mobile communication system

is the reuse of frequencies at different places within the areas of service. The channel

allocation strategy is the technique used to make the most efficient and intelligent way of

utilizing the available radio spectrum by the way in which channels are allocated to mobile

multimedia calls. The channel allocation strategy is the soul of all portable communication

systems. It affects not only the quality and availability of connections but also the traffic

distribution which, in turn, affects the capacity of the system.

The work presented in this thesis is focused on optimal hybrid channel allocation

algorithm with hot-spot to decrease the call drop rate. In this chapter, Vigorous research

has been pursued in channel allocation technique for a number of years. In the area of

channel allocation different techniques have been used and still the area is being explored.

In this section we review some of the papers on channel allocation techniques.

The outline of the chapter is as follows: In section 2.1 we review the comparison between

different channel allocation schemes. Section 2.2 covers code channel assignment.

Channel assignment with different algorithm is presented in section 2.3. Hybrid channel

allocation is proposed in section 2.4. Section 2.5 explores the hybrid channel allocation

algorithm using hot-spot technique. In section 2.6 Game theoretical approaches for

channel allocation is proposed. Performance of different channel allocation schemes is

covered in section 2.7.

2.1. Comparison between different Channel allocation schemes

In 1996, Chi Chung Lam,presents [21] a distributed channel allocation algorithm based on

the concept of dynamic channel boundaries. Under this scheme, each mobile service

station (MSS) is assigned a contiguous range of channel not overlapping with those of its

neighbours. Channel boundaries between adjacent MSSs are dynamically adjustable

through voluntary withdrawals. High efficiency is provided by two important features:

early boundary expansion and need-based boundary redrawing. This algorithm imposes a

low message volume on the fixed network, has short response times to connection requests
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and achieves high channel utilization under both evenly and unevenly distributed loads.

Channel utilization is further improved if a MSS may borrow channels from its

neighbours.

In 1997, Zukerman, M. provides [22] simple models for efficiency evaluation of various

channel allocation schemes in digital mobile telecommunications networks. The analysis is

based on known queuing network results and standard Markovian queuing models.Queues

can be chained to form queuing networks where the departures from one queue enter the

next queue. Queuing networks can be: open & closed. Open queuing networks have an

external input and an external final destination. Closed queuing networks are completely

contained and the customers circulate continually never leaving the network.

2.2. Code channel assignment

In 2003, Hasan Cam, proposed [14] a Non blocking OVSF Codes and Enhancing

Network Capacity for 3G Wireless and Beyond Systems in which he explained orthogonal

variable spreading factor (OVSF) codes which are employed as channelization codes in

WCDMA. Any two OVSF codes are orthogonal if and only if one of them is not a parent

code of the other. Therefore, when an OVSF code is assigned, it blocks its entire ancestor

and descendant codes from assignment because they are not orthogonal to each other.Unfortunately, this code blocking problem of OVSF codes can cause a substantial spectral

efficiency loss of up to 25%. This paper presents non blocking OVSF (NOVSF) codes to

increase substantially the utilization of channelization codes without having the overhead

of code reassignments.

Fig.2.1 OVSF Code Tree
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2.3 Channel assignment using different algorithm

In 2005, Wei Wang and Xin Liu proposed [17], a List-colouring Based Channel Allocation

for Open-Spectrum Wireless Networks, in this paper he studied the dynamics in the

available channels caused by the location and traffic load of the primary users and

proposed several distributed algorithms to exploit the available channels for secondary

users. The performance of different algorithms is evaluated in networks with static and

time-varying channel availability.

Fig.2.2 A Colour Graph

In 2006, Jun Sun develop a novel auction-based algorithm [20] to allow users to fairly

compete for a wireless fading channel. We use the second-price auction mechanism

whereby user bids for the channel, during each time slot, based on the fade state of the

channel, and the user that makes the highest bid wins use of the channel by paying the

second highest bid. Under the assumption that each user has a limited budget for bidding,

we show the existence of a Nash equilibrium strategy, and the Nash equilibrium leads to a

unique allocation for certain channel state distribution, such as the exponential distributionand the uniform distribution Based on the Nash equilibrium strategies of the second-price

auction with money constraint, he further propose a centralized opportunistic scheduler

that does not suffer the shortcomings associated with the proportional fair scheduler.

2.4 Hybrid channel allocation algorithm

In 2005, Geetali Vidyarthi proposed an algorithm for Hybrid Channel Assignment

Approach Using an Efficient Evolutionary Strategy [16]. In this paper; she had developed

an evolutionary strategy (ES) which optimizes the channel assignment. The proposed ES


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approach uses an efficient problem representation as well as an appropriate fitness

function. This paper deals with a novel hybrid channel assignment based scheme called D-

ring. D-ring method yields a faster running time and simpler objective function. she also

proposed a novel way of generating the initial population which reduces the number of

channels reassignments and therefore yields a faster running time and may generate a

possibly better initial parent.

The basic steps of an ES algorithm can be summarized as follows.

1) Generate an initial population of individuals.

2) Evaluate each individual according to a fitness function.

3) Selectbest individuals called the parent population and discard the rest.

4) Apply genetic operator to create off springs fromparents.

5) Go to step 2 until a desired solution has been found or predetermined number

generations have been produced and evaluated.

2.5 Hybrid channel allocation using hot-spot technique

In 2006, Rana Ejaz Ahmed proposed [2] a hybrid channel allocation algorithm using hot-

spot notification.This paper presents a new hybrid channel allocation algorithm in which

the base station sends a multi-level hotspot notification to the central pool located at

Mobile Switching Station (MSC) on each channel request that cannot be satisfied locally

at the base station. This notification will request more than one channel be assigned to the

requesting cell, proportional to the current hot-spot level of the cell. When a call using

such a borrowed channel terminates, the cell may retain the channel depending upon its

current hot-spot level. The simulation study of the protocol indicates that the protocol has

low overhead, and it behaves similar to the Fixed Channel Allocation (FCA) scheme at

high traffic and to the Dynamic Channel Allocation (DCA) scheme at low traffic loads.The proposed algorithm also offers low-overhead in terms of the number of control

messages exchanged between a base station and the MSC on channel acquisition and

release phases.

In 2008, Yuhong Zhang and Ezzatollah Salari investigated and proposed [23] a novel

analytical model of a hybrid channel allocation algorithm in which each cell of the

network consists of a predefined fixed number of channels and the network may approve


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the request for extra channel for both new and handoff calls if all predesigned channel are

occupied. This approval depends on the type of new and handoff calls, as well as the

number of approved channels in the cell. If the request id denied for an arriving new call,

this call will not be blocked immediately but rather put on hold in buffer with finite space.

The implication behind this is to give priority to hand off calls.

In 2010, Joshi, J. proposed [13] a hybrid channel allocation algorithm to reduce call

blocking probability using hot-spot notification. In this paper attempts are made to reduce

call-blocking probability by designing hybrid channel allocation (HCA) which is the

combination of fixed channel allocation (FCA) and dynamic channel allocation (DCA). A

cell becomes hot-spot when the bandwidth available in that cell is not enough to sustain

the users demand and call will be blocked or dropped. A simulation result shows that HCA

scheme significantly reduces call-blocking probability in hotspot scenario and compared

with cold-spot cell. This hot-spot notification will request more than one channel be

assigned to the requesting cell, proportional to the current hot-spot level of the cell.

Furthermore, all channels will be placed in a central pool and on demand will be assigned

to the base station. That will be helpful to reduce call-blocking probability when cell

becomes hot-spot. When a call using such a borrowed channel terminates, the cell may

retain the channel depending upon its current hot-spot level therefore HCA hascomparatively much smaller number of reallocations than other schemes. It also shows

that it behaves similar to the FCA at high traffic and to the DCA at low traffic loads as it is

designed to meet the advantages of both.

2.6 Game theoretical approach for channel allocation

In 2011, Jiming Chen proposed [5] a Game Theoretical Approach for Channel Allocation

in Wireless Sensor and Actuator Networks, in which multi-channel allocation in wireless

sensor and actuator networks is formulated as an optimization problem which is NP-hard.

In order to efficiently solve this problem, a distributed game based channel allocation

(GBCA) Algorithm is proposed by taking into account both network topology and routing

information. For both tree/forest routing and non-tree/forest routing scenarios, it is proved

that there exists at least one Nash Equilibrium for the problem. Furthermore, the sub

optimality of Nash Equilibrium and the convergence of the Best Response dynamics are

also analyzed. Simulation results demonstrate that GBCA significantly reduces the
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interference and dramatically improves the network performance in terms of delivery ratio,

throughput, channel access delay, and energy consumption.

Main contribution of this paper is-

1. Analyze the relationship between the numbers of links and define interference metric.

2. For the tree/forest routing, we show that the game is an exact potential game and there

exists at least one NE in the game.

3. We introduce several virtual nodes and add interfering links for each crossing node to

facilitate the construction of parent-children sets in general routing.

4. In order to solve the channel allocation problem in a suboptimal way but in polynomial

time, we propose a distributed algorithm, GBCA.

2.7 Performance of different channel allocation schemes.

In 2012, M.L.S.N.S. Lakshmiproposed [1] an insight to call blocking probabilities of

channel assignment schemes In this paper, the performance of three different channel

allocation schemes FCA, DCA and HCA will be analytically compared and the results are

presented. Different channel allocation schemes are in use for mobile communication

systems, of which the Hybrid channel allocation (HCA) a combination of Fixed and

Dynamic channel allocation schemes (FCA and DCA respectively) was effective by the

experimental and simulated evaluations of all channel assignment schemes we proposed

that HCA will give the appropriate results in reducing call blocking probability. The main

advantage of this algorithm is that it can adapt to dynamic strategy at low traffic load and

to fixed strategy at higher traffic intensity load and to fixed strategy at higher traffic

intensity. If we increase the value of hot-spot level (L), the system performance in both

regions of the low and high traffic intensity. From the above discussion it can be deemed

that hybrid channel allocation algorithm sends a multi-level hot-spot notification to the

central pool on each channel request which cannot be satisfied locally at the base station.

This notification will request more than one channel be assigned to the requesting cell,

proportional to the current hot-spot level (L) of the cell. This also reduce control message

overhead needed to acquire each channels individually.


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3. BACKGROUND THEORY

3.1 COMMUNICATION CHANNELS

3.1.1. Introduction

In telecommunications and computer networking, a communication channel, or channel,

refers either to a physical transmission medium such as a wire, or to a logical connection

over a multiplexed medium such as a radio channel. A channel is used to convey an

information signal, for example a digital bit stream, from one or several senders (or

transmitters) to one or several receivers. A channel has a certain capacity for transmitting

information, often measured by its bandwidth in Hz or its data rate in bits per second.

Communicating data from one location to another requires some form of pathway or

medium. These pathways, called communication channels, use two types of media: cable

(twisted-pair wire, cable, and fibre-optic cable) and broadcast (microwave, satellite, radio,

and infrared). Cable or wire line media use physical wires of cables to transmit data and

information. Twisted-pair wire and coaxial cables are made of copper, and fibre-optic

cable is made of glass. In the Internet, a packet may be sent over a wireless Wi-Fi network

to an Ethernet Lan, to a DSL modem, to a fibre-optic backbone, etc. The many unique

physical characteristics of different channels determine the three characteristics of interest

in communication: the latency, the data rate, and the reliability of the channel.

If channel is considered as the highway, then the bandwidth is like the number of lane in

the high way. More lanes mean more traffic at a time and high speed transportation.

Bandwidth also refers to as grade, tells us the rate, or speed at which data can betransmitted over the channel.

3.1.2 There are three bands for communication channel:

1. Narrow Band Channel--

Narrow band channel or the low speed channel is the slowest band, transmits the data from

40 bit per second to 1200 bits per seconds. Telegraph lines are the example of narrow band

channel.
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1. Space division multiplexing:In wireless transmission, SDM implies a separate sender for each communication channel

with a wide enough distance between the senders [10]. This multiplexing is used, for

example, at FM radio stations where the transmission range is limited to a certain region.

Here space is represented via circles indicating the interference range. The channel k1 to k3

can be mapped onto the three spaces s1 to s3 which clearly separate the channel and prevent

the interference range from overlapping.

fig.3.1 Space Division Multiplexing

2. Frequency division multiplexingSeparation of the whole spectrum into smaller frequency bands channel gets a certain band

of the spectrum for the whole time [10]. Each channel k, is now allocated its own

frequency band as indicated senders using a certain frequency band can use this band

continuously.

Advantages: no dynamic coordination necessary, works also for analog signals.

Disadvantages: waste of bandwidth if the traffic is distributed unevenly inflexible guard

spaces


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Fig. 3.2 Frequency Division Multiplexing

3. Time division multiplexing:A more flexible multiplexing scheme for typical mobile communication is time division

multiplexing (TDM) [10]. Here a channel k1 is given the whole bandwidth for a certain

amount of time, i.e., all senders use the same frequency but at different point of time.

Advantages: only one carrier in the medium at any time, throughput high even for many

users. Disadvantages: precise synchronization necessary.

Fig. 3.3 Time Division Multiplexing


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4. Frequency and time multiplexing:

Combination of both methods: A channel gets a certain frequency band for a certain

amount of time [10]. Example: GSM Advantages: Better protection against tapping,

protection against frequency selective interference & higher data rates compared to code

multiplex. but: precise coordination required.

Fig. 3.4 Frequency and Time division multiplexing combined

5. Code division multiplexingCode division multiplexing is a relatively new scheme in commercial communication

systems [10].fig 3.5 shows all channels k1 use the same frequency at the same time for

transmission. Separation is now achieved by assigning each channel its own code, guardspaces are realized by using codes with the necessary distance in code space, e.g.,

orthogonal codes.

Fig.3.5 Code Division Multiplexing


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3.2 Channel Allocation

3.2.1 Introduction

A given radio spectrum (or bandwidth) can be divided into a set of disjoint or noninterfering radio channels [19]. All such channels can be used simultaneously while

maintaining an acceptable received radio signal. In order to divide a given radio spectrum

into such channels many techniques such as frequency division (FD), time division (TD),

or code division (CD) can be used. In FD, the spectrum is divided into disjoint frequency

bands, whereas in TD the channel separation is achieved by dividing the usage of the

channel into disjoint time periods called time slots. In CD, the channel separation is

achieved by using different modulation codes. Furthermore, more elaborate techniques can

be designed to divide a radio spectrum into a set of disjoint channels based on combining

the above techniques. For example, a combination of TD and FD can be used by dividing

each frequency band of an FD scheme into time slots. The major driving factor in

determining the number of channels with certain quality that can be used for a given

wireless spectrum is the level of received signal quality that can be achieved in each

channel. The distance between two cells is defined as the Euclidean distance between the

centres of the two cells. Let Si(k) be denoted as the set ( i ) of wireless terminals that

communicate with each other using the same channel k. By taking advantage of physical

characteristics of the radio environment, the same channel k can be reused simultaneously

by another set j if the members of sets i and j are spaced sufficiently apart. All such sets

which use the same channel are referred to as co-channel sets or simply co-channels. The

minimum distance at which co-channels can be reused with acceptable interference is

called the "co-channel reuse distance, as shown in [19].

This is possible because due to propagation path loss in the radio environment, the averagepower received from a transmitter at distance d is proportional to PT d a, where a is a

number in the range of 3-5 depending on the physical environment, and PT is the average

transmitter power. For example, for an indoor environment with a = 3.5, the average

power at a distance 2d is about 9 percent of the average power received at distance d.

Thus, by adjusting the transmitter power level and/or the distance between co-channels, a

channel can be reused by a number of co-channels if the Carrier-to- Interference ratio

(CIR) in each co-channel is above the minimum CIR value. Here the carrier power


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represents the received signal power in a channel, and the interference represents the sum

of received signal powers of all co-channels.

As an example, consider Fig. 1 where a wireless station labelled R is at distances dt from

a transmitter station labelled T using a narrowband radio channel. We refer to the radio

channel used by T to communicate to R as the reference channel. In this figure, we have

also shown five other stations labelled 1, 2. . . 5, which use the same channel as the

reference channel to communicate with some other stations. Denoting the transmitted

power of station i by Pi and the distance of station i from R by di, the average CIR at the

reference station R is given by Eq. (1).

.eq.(1)

Where, No represents the environmental noise; to achieve a certain level of CIR at

the reference station R, different methods can be used.

3.2.2 Common Principles of Channel Allocation Schemes:

The large array of possible channel allocation systems can become cumbersome. However,

all channel allocation methods operate under simple, common principles. Throughout this

report we have touched on three points which an efficient channel allocation scheme

should address:

1. Channel allocation schemes must not violate minimum frequency reuse conditions.

2. Channel allocation schemes should adapt to changing traffic conditions.

3. Channel allocation schemes should approach (from above) the minimum frequency

reuse constraints so as to efficiently utilize available transmission resources.


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3.2.3 Call blocking probability

Several metrics can be used to evaluate and compare the performance of the proposed

algorithm. The call blocking probability is defined as the ratio of the number of new calls

initiated by a mobile host which cannot be supported by existing channel arrangement to

the total number of new calls initiated. Call blocking probability (Pb) is given by the ratio

of number of calls lost by the system to the total number of new calls initiated.

3.2.4 Fixed channel allocation

In the FCA strategy a set of nominal channels is permanently allocated to each cell for its

exclusive use [4]. Here a definite relationship is assumed between each channel and each

cell, in accordance to co channel reuse constraints. The total number of available channels

in the system C is divided into sets, and the minimum number of channel sets N required

to serve the entire coverage area is related to the reuse distance s.

N = (1/3) ^2, for hexagonal cells.

Here is defined as D/Ra, where Ra is the radius of the cell and D is the physical distance

between the two cell centres [5]. N can assume only the integer values 3, 4, 7, 9... as

generally presented by the series, (i + j)2 i, j, with i and j being integers [5, 7]. Figures

4(a) and 4(b) give the allocation of channel sets to cells for N = 3 (0 = 3) and N = 7 (0 =

4.45), respectively.

In the simple FCA strategy, the same number of nominal channels is allocated to each

cell. This uniform channel distribution is efficient if the traffic distribution of the system is

also uniform. In that case, the overall average blocking probability of the mobile system is

the same as the call blocking probability in a cell. Because traffic in cellular systems can

be non uniform with temporal and spatial Fluctuations, a uniform allocation of channels to

cells may result in high blocking in some cells, while others might have a sizeable number

of spare channels. This could result in poor channel utilization. It is therefore appropriate

to tailor the number of channels in a cell to match the load in it by non uniform channel

allocation or static borrowing. In non uniform channel allocation the number of nominal

channels allocated to each cell depends on the expected traffic profile in that cell.


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Fig. 3.9 FCA for pattern k=7

3.2.5 Channel borrowing scheme

In a channel borrowing scheme, an acceptor cell that has used all its nominal channels can

borrow free channels from its neighbouring cells (donors) to accommodate new calls [19] .

A channel can be borrowed by a cell if the borrowed channel does not interfere with

existing calls. When a channel is borrowed, several other cells are prohibited from using it.

This is called channel locking. For example, for a hexagonal planar layout with reuse

distance of one cell ( = 3), a borrowed channel is locked in three additional neighbouring

cells, as is shown in Fig. 5, while for a one dimensional layout or a hexagonal planar grid

layout with two-cell reuse distance, it is locked in two additional neighbouring cells. The

channel borrowing schemes can be divided into simple and hybrid. In simple channel

borrowing schemes, any nominal channel in a cell can be borrowed by a neighbouring cell

for temporary use. In hybrid channel borrowing strategies, the set of channels assigned to

each cell is divided into two subsets, A (standard or local channels) and B (nonstandard or

borrowable channels). Subset A is for use only in the nominally assigned cell, while subset

B is allowed to be lent to neighbouring cells.


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2. Borrow from the richest (SBR)

3. Basic algorithm (BA)

4. Basic algorithm with reassignment (BAR)

5. Borrow first available (BFA)

Hybrid channel borrowing scheme

The different schemes of hybrid channel borrowing are,

1. Simple hybrid borrowing scheme (SHCB)

2. Borrowing with channel ordering (BCO)

3. Borrowing with directional channel locking (BOCL)

4. Sharing with bias (S H B) Channel assignment with borrowing and reassignment

(CABR)

5. Ordered dynamic channel assignment with Re arrangement

Table 3.1 summarizes the channel borrowing scheme


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3.2.6 Dynamic channel allocation

Due to short-term temporal and spatial variations of traffic in cellular systems, FCA

schemes are not able to attain high channel efficiency [14]. To overcome this, DCA

schemes have been studied during the past 20 years. In contrast to FCA, there is no fixed

relationship between channels and cells in DCA. All channels are kept in a central pool

and are assigned dynamically to radio cells as new calls arrive in the system. After a call is

completed, its channel is returned to the central pool. In DCA, a channel is eligible for use

in any cell provided that signal interference constraints are satisfied. Because, in general,

more than one channel might be available in the central pool to be assigned to a cell that

requires a channel, some strategy must be applied to select the assigned channel. Based on

information used for channel assignment, DCA strategies could be classified either as call

-by- call DCA or adaptive DCA schemes [27]. In the call-by-call DCA, the channel

assignment is based only on current channel usage conditions in the service area, while in

adaptive DCA the channel assignment is adaptively carried out using information on the

previous as well as present channel usage conditions. Finally, DCA schemes can be also

divided into centralized and distributed schemes with respect to the type of control they

employ.

1. Centralized DCA Schemes

In centralized DCA schemes, a channel from the central pool is assigned to a call for

temporary use by a centralized controller. The difference between these schemes is the

specific cost function used for selecting one of the candidate channels for assignment.

2. First Available (FA)

The simplest of the DCA schemes is the FA strategy. In FA the first available channel

within the re use distance encountered during a channel search is assigned to the call. The

FA strategy minimizes the system computational time; and, as shown by simulation. For a

linear cellular mobile system, it provides an increase of 20 percent in the total handled

traffic compared to FCA for low and moderate traffic loads.

3. Locally Optimized Dynamic Assignment (LODA)


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In the LODA strategy, the selected cost function is based on the future blocking

probability in the vicinity of the cell in which a call is initiated.

4. Channel Reuse Optimization Schemes

The objective of any mobile system is to maximize the efficiency of the system. Maximum

efficiency is equivalent to maximum utilization of every channel in the system. It is

obvious that the shorter the channel reuse distance, the greater the channel reuse over the

whole service area. The cost functions selected in the following schemes attempt to

maximize the efficiency of the system by optimizing the reuse of a channel in the system

area.

5. Selection with Maximum Usage on the Reuse Ring (RING)

In the RING strategy, a candidate channel is selected which is in use in the most cells in

the co channel set. If more than one channel has this maximum usage, an arbitrary

selection among such channels is made to serve the call. If none is available, the selection

is made based on the FA scheme.

Comparison between FCA & DCA

In general, there is a trade-off between quality of service, the implementation complexity

of the channel allocation algorithms, and spectrum utilization efficiency [1]. Under low

traffic intensity, DCA strategies perform better. However, FCA schemes become superior

at high offered traffic, especially in the case of uniform traffic. In the case of non uniform

traffic and light to moderate loads, it is believed that the DCA scheme will perform better

due to the fact that under low traffic intensity, DCA uses channels more efficiently than

FCA. In the FCA case channels are pre assigned to cells, so there are occasions when, due

to fluctuation in traffic, calls are blocked, even though there are channels available in

adjacent cells. In addition, a basic fact of telephone traffic engineering is that a server with

capacity C is more efficient than a number of small ones with the same total aggregate

capacity. That is, for the same average blocking probability a system with high capacity

has higher utilization. FCA schemes behave like a number of small groups of servers,

while DCA provides a way of making these small groups of servers behave like a larger

server. Then It is observed that in Fig. 6, with low traffic intensity DCA uses channels


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more efficiently than FCA because of flexible channel assignment and shows good

performance. But with high traffic intensity, DCA does not show better performance than

FCA.

Fig.3.11 Traffic intensity and blocking rate.

3.2.7 Hybrid channel allocation

Hybrid channel assignment schemes are a mixture of the FCA and DCA techniques [4]. In

HCA, the total number of channels available for service is divided into fixed and dynamic

sets. The fixed set contains a number of nominal channels that are assigned to cells as in

the FCA schemes and, in all cases, are to be preferred for use in their respective cells. The

second set of channels is shared by all users in the system to increase flexibility.

Fig 3.12 Hybrid Channel Allocation

When a call requires service from a cell and all of its nominal channels are busy, a channel

from the dynamic set is assigned to the call. The channel assignment procedure from the

dynamic set follows any of the DCA strategies described in the previous section.

Variations of the main HCA schemes include HCA with channel reordering and HCA


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If no channel from the fixed list for the cell is available, then the base station updates the

value ofL as follows:

L = L +1;

The base station estimates the current level of hot-spot, hin the cell.

IfHis less than or equal to the old value of level L ,

H L

Meaning that the congestion in the cell is the same or easing,

IfHis greater than the old value of level L

H > L

Meaning that the congestion in the cell is getting worse,

Multilevel notification has low overhead as compared to one-by-one notification on its

current hot-spot level. Low-overhead in terms of the number of control messages

exchanged between a base station and the MSC on channel acquisition and release phases.


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3.4Hybrid channel assignment schemesHybrid channel assignment strategies combine both static and dynamic assignment

properties by applying a fixed assignment for some interfaces and a dynamic assignment

for other interfaces [15, 16, 13]. Hybrid strategies can be further classified based on

whether the fixed interfaces use a common channel [13] or varying channel [15, 16]

approach. The fixed interfaces can be assigned a dedicated control channel or a data and

control channel [13], while the other interfaces can be switched dynamically among

channels. Hybrid assignment strategies are attractive because, as with fixed assignment,

they allow for simple coordination algorithms, while still retaining the flexibility of

dynamic channel assignment. In the next two subsections we describe two hybrid schemesfor CA.

Fig.3.13 Hybrid channel allocation

3.4.1 Link Layer Protocols for Interface Assignment

Innovative link layer interface assignment algorithm (LLP) [15] categorizes available

interfaces into fixed and switchable interfaces. Fixed interfaces are assigned, for long time

intervals, specific fixed channels, which can be different for different nodes. On the other

hand, switchable interfaces can be switched over short timescales among non-fixed

channels based on the amount of data traffic. By distributing fixed interfaces of different

nodes on different channels, all channels can be used, while the switchable interface can

be used to maintain connectivity. Two coordination protocols based on hash functions and

the exchange of Hello packets are proposed in [15] to decide which channels should be

assigned to the fixed interface and manage communication between nodes. In [16] the


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its level by 1 & sends a channel request to the central pool in order to borrow channels

from MSC. Channel request include base station current level and maximum level. On

receiving channel request from base station MSC will assign channels from the central

pool to base station up to the requesting level at the same time base station add the same

number of channel to its temporary pool. As the traffic increases, base station maintains its

level on each channel request. When a call terminates base station check the type of

channel the call belonged to. If the channel belonged to fixed set then it remain in base

station but if channel belonged to dynamic pool, now base station is required to estimate or

check its level, if its level is below hot-spot level than channels are retained to MSC from

its temporary pool otherwise remain in base station itself.

If the base station level is greater or equal to hot-spot level, meaning that the congestion in

the cell is same or getting worse, now the channels remain in the cell itself in the

temporary pool of base station in order to sustain more calls. Condition becomes critical

when MSC has no channel available in its central pool and channel request arrives from

any cell. In this case, call starts dropping or blocking.


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4. PROPOSED METHODOLOGY

In this thesis, an optimal method for hybrid channel allocation with hot-spot is proposed.

A review of various method and techniques of channel allocation was presented in the

chapter 2. The technique proposed by Rana Ejaz Ahmed [2], is inspiring us for the

development of hybrid channel allocation. In this thesis, hot-spot technique is used for

hybrid channel allocation in order to decrease call drop rate in the cellular network.

The system uses a hybrid channel allocation scheme where as in [3,] the total number ofC

channels is divided into two disjoint sets, Fand D. The set Fcontains the channels for

fixed (or static) assignment, while the set Dcontains the channels for dynamic assignment,i.e., C = FUD. Moreover, each base station maintains a temporary pool (called T)to

retain a channel that was originally transferred from the dynamic assignment pool at MSC.

The system uses a frequency reuse factor N. The fixed channels are assigned to a cell

statically as in FCA; while dynamic channels are kept in a centralized pool at MSC. Let r

be the ratio of the number of dynamic channels to the total number of channels available in

the system, [13] i.e.,

r= |D| / |C|.

The value of r depends upon the traffic condition as well as on designers view.

The hot-spot notification level is a multiple of 2, such that 2 i

Where i is an integer i.e. 0, 1, 2, 3..&

H={1, 2, 4, 8.... M}

Where M=pre-defined maximum level supported by the system.

& H=represents the fact that up to Hborrowed channels can be retained by the base

station after a call on the borrowed channel from that cell terminates.

The work which is presented here is for efficient management of unused channels. The

unused channels are returned back to MSC on cell request, if there is non- availability of

channels. The request is implemented by rending the whole process in two phases [3].


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This can be posed as a limitation to the approach which can be overcome if the MSC on

certain interval of time sends notification to BS for requirement of unused and extra

channels provided by the MSC during Channel acquisition phase in step 3. The only

reason for allocating H+ 1 channel to BS instead of H is a proactive measure, because

request is generated by hot-spot cell which is dealing with heavy load and it is assumed

that in near future it will require more communication bandwidth, so as to reduce overhead

up to some extent, this particular fashion is adopted. But, as seen in step 4 of Channel

acquisition phase, the situation of call dropping can be avoided if unused channels with

any cell can be retrieved. So, here to manage channel allocation scheme in a better way,

step 4 can be modified as-

5. If MSC cannot allocate even one channel, then Channel retrieval phase will be initiated.

Now suppose in Channel retrieval phase, dynamic pool gets exhausted then

a). MSC notifies all BS which borrowed a channel from dynamic pool to return unused

channel, if any.

Fig.4.1 Flowchart for Channel acquisition phase


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b). On receiving such request (notification), those BS, having the same will return the

unused bandwidth to MSC.

c). On retrieving bandwidth Channel retrieval phase terminates, and request of any hot-

spot BS is served.

4.3 Channel release phase

Lastly, the issue of channel emancipation, if a call gets terminated at any MH. So,

algorithmically,

1. On termination of any call at MH, a channel, let us suppose ki gets free and is to be

returned back either to local pool at BS site or dynamic pool at MSCs site.

2. On analyzing that the released channel belongs to dynamic pool, before returning, the

BS estimates the current value of hot-spot level (let us say, H), in the cell.

IfHis less than or equal to the old value of level L ,

H L

Meaning that the congestion in the cell is the same or easing, in this case after checking its

temporary pool, channel is returned back to MSC. Else IfHis greater than the old value of

level L

H > L

Meaning that the congestion in the cell is getting worse, in this case Channel ki is retained

in its temporary pool as condition got worse, and cell is in urgent need of communication

bandwidth.


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Fig 4.2 Flowchart for Channel release phase

From the flowcharts channel acquisition phase and release phase can be easily understand.

Due to the limitation of bandwidth, it is required to use the bandwidth efficiently. Our

proposed algorithm is also tends to use the bandwidth efficiently and decrease rate of call

drop. In communication system the foremost requirement is to decrease call drop and call

block.


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5. IMPLEMENTATION

In the previous chapter, we have seen the details of overall communication system. Hybrid

channel allocation and hot-spot condition also shown in [1,2, and 3] which is essential for

proposed optimal hybrid channel allocation technique with hot-spot notification. We have

given thorough description of all the three channel allocation, namely fixed channel

allocation, dynamic channel allocation and the hybrid channel allocation.

To evaluate the effectiveness of our approach, a cellular network is simulated over

OMNeT++ simulation environment which is an Integrated Development Environment and

is based on the Eclipse platform, and extends it with new editors, views, wizards, andadditional functionality. OMNeT++ adds functionality for creating and configuring models

(NED and ini files), performing batch executions, and analyzing simulation results, while

Eclipse provides C++ editing, SVN/GIT integration, and other optional features (UML

modelling, bug tracker integration, database access, etc.) via various open-source and

commercial plug-ins [10]and results are expounded in various scenarios viz. Fixedchannel

allocation scheme, and hybrid channel allocation scheme by varying the number of

dynamic channels used, and the behaviour is studied in terms of Call drop rate and

Blocked call rate versus System load.

In this chapter we have reported database which is described in section 5.1 and section 5.2

covers experimental setup for the proposed system.

5.1 Database

The parameters and scenarios used in this simulation are illustrated in this section in which

we have simulated the approach on over environment with total available channels i.e.

K=300 over a BS grid of 66 over a area of 50,00050,000 meteres2 with one Mobile

switching Centre. Now, the approach has been evaluated for four different scenarios.

Firstly, with fixed channel allocation Scheme for all available channels, and secondly, by

varying the number of dynamic channels used by 30, 150 and 240 channels which in turn

will vary the ratio of the number of dynamic channels to the total number of channels

available in the system.


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5.2 Experimental Setup

Here we are describing every step of establishing communication system.

First of all BSC is located in the network. The Basic switching centre basically manages

the BTSs. It reserves radio frequencies, handles the hand over, and performs the paging ofthe MS. The BSC also multiplexes the radio channels onto the fixed network connection at

the air interface. Air is interface through which signals can be transmitted. Any messages

which are transferred between BSC, BTS and ms are transferred through this air.

Fig. 5.1 BSC is located in the network

Air is interface through which signals can be transmitted. Any messages which are

transferred between BSC, BTS and ms are transferred through this air.

Message which are transferred from mobile station to BTS are like connection request,disconnect request, check BTS, mobile station data, check line etc. Similarly message

which are transferred from BTS to ms are like connection acknowledgement, disconnect

acknowledgement, force disconnect, handover ms, check ms, BTS data etc.


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As shown in the fig. after MS, BTS is located in the network. BTS is Base Transceiver

System. Each BTS is connected to the BSC. A BTS comprises all radio equipment i.e.

antennas, signal processing, amplifiers necessary for radio transmission. A BTS can form a

radio cell or, using sectorized antennas, several cells and is connected to MS via interface.

Now when mobile user wants to initiate the call, it request BTS for the channel available

in the local pool. As shown in the fig. MS sends the connection request message to BTS.

BTS has two pool first is local pool and another is temporary pool. Channels with are fixed

allocated is stored in local pool while the channels which are borrowed from the dynamic

pool of BSC is stored in temporary pool. Channels are returned back to BSC from

temporary pool after the requirement is over. Since our proposed method is through hot-

spot notification, thats why more channels get stored in the temporary pool in the high

traffic.

Fig. 5.4 Message from MS to BTS

As shown in the fig. connection acknowledgement is given by BTS to MS. Now BTS will

provide the channel to MS from local pool, if channels in local pool are available. In this

way channel acquisition phase completed. Now the condition become complicated when

there are no channels available in the local pool, in this situation


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6. EXPERIMENTAL RESULTS

6.1 Performance EvaluationThe parameters and scenarios used in this simulation are illustrated in this section in which

we have simulated the approach on over environment with total available channels i.e.

K=300 over a BS grid of 66 over a area of 50,00050,000 meteres2 with one Mobile

switching Centre, the approach has been evaluated for four different scenarios. Firstly,

with fixed channel allocation Scheme for all available channels, and secondly, by varying

the number of

dynamic channels used by 30, 150 and 240 channels which in turn will vary the ratio ofthe number of dynamic channels to the total number of channels available in the

system(i.e. h=number of dynamic channel/total number of channels) and the results are

tabulated below.

Parameters evaluated from Hybrid Channel Allocation using hot-spot notifications are as

follows:

(1) Successful call percentage

(2) Call drop rate

(3) Call block rate

(4) Handover rate

The above parameters can be calculated as follows:

Successful call percentage =

Call drop rate =

Call block rate =

The main objective of the proposed system is to obtain decrease no. of call drop rate, call

block rate and handover. Here we present our simulation result in the form if table.


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6.1.1 Call Block Evaluation:

Systemload

Call blocked rate

fca h=0.1 h=0.5 h=0.8

0.25 0 0 0 00.5 2.00 2.45 1.26 0.46

0.75 6.04 5.02 4.39 3.65

1 15.34 9.56 10.48 10.23

1.25 20.65 18.98 15.66 14.87

Table 6.1 Call block rate in traditional system

System

load

Call blocked rate

fca h=0.1 h=0.5 h=0.80.25 0 0 0 0

0.5 1.48 1.59 0.26 0.22

0.75 5.20 4.99 4.39 3.21

1 13.53 10.28 8.48 6.59

1.25 18.41 16.09 15.66 10.88

Table 6.2 Call block rate in our proposed system

The obtained results, illustrates the expound effectiveness of work in terms of call dropped

and call blocked compared against system load in both cases in different scenarios

mentioned above and compared with and without employing Hybrid Channel allocation

scheme. In the case of HCA, three different cases of different ratio of the number of

dynamic channels to the total number of channels available in the system i.e. D has been

considered as 30, 150 and 240 channels (i.e. h=0.1, 0.5, 0.8). In implementation, number

of MSC is 1 in all cases for the sake of simplification. The results are illustrated

graphically to show the behaviour of network with above defined approach.


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Fig. 6.1 Call Block versus system load in traditional system

Fig. 6.2 Call block versus system load in our proposed method

Fig 6.2 shows the blocking probability versus system load according to [3]. Here ascompared to our result in fig 6.1 we observed that blocking probability is comparatively


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Fig. 6.3 Call drop rate versus system load in traditional system

Fig. 6.4 Call drop rate versus system load in our proposed method

Similarly, if pattern of Call dropped is observed a slight improvement is seen when

hybrid approach is used as compared to its fixed counterpart. An unexpected increase in


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call drop rate is observed when the number of channels in dynamic pools was 30 i.e

h=0.1,in both the system which might be the result of abrupt network traffic pattern and

other parameters which affects the performance such as poor connectivity, interference,

and many more. In h=0.5, both system give almost same result. Here best outcome is

observed when number of dynamic channels is varied to 240 i.e. h=0.8, where call drop

rate is least for increasing load. In the traditional system it was 28 whereas in our proposed

system it decreases to 22.

6.1.3 Handover Calls Evaluation:

Systemload

Handover Calls

fca h=0.1 h=0.5 h=0.8

0.25 1300.12 1356.12 1357.28 1357.35

0.5 1288.56 1298.65 1300.19 1305.92

0.75 1198.11 1100.21 1009.5 1009.8

1 1009.98 945.21 1000.88 998.76

1.25 800.60 712.34 803.76 1000.20

Table. 6.5 Handover calls rate in traditional system

Systemload

Handover Calls

fca h=0.1 h=0.5 h=0.8

0.25 1284.64 1287.31 1287.31 1287.31

0.5 1145.52 1156.34 1212.10 1220

0.75 1000 930.68 946.83 990.27

1 615.23 645.36 1085.88 870.10

1.25 502.61 467.34 577.76 998.20

Table. 6.6 Handover calls rate in our proposed method


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Fig. 6.5 Handover versus system load in traditional system

Fig. 6.6 Handover versus system load in our proposed system

In the case of handover we observed that when the ratio of dynamic channels is low,

handover occurs more in all the three cases where it was traditional or our proposed

system. But as the dynamic channels are increases and system load increases, then

handover decreases. As compared to traditional system clearly our proposed method cause

low handover. If we focus on h=0.8 in both cases, our method gives 1000 handover


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whereas in above system it was 1200. So it is clear that proposed method performs better

in any case.

So in all the result we observed that as the ratio of dynamic channels increases, in all

aspect performance becomes good. For the better communication system, it is required to

vary the number of dynamic channels as per the traffic grows. For low traffic condition,

even FCA performs better. Proper management system should to be maintaining in the

time of high traffic and in the time of hot-spot to manage the entire mobile user.


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7. CONCLUSION

The demand in the mobile communication has remarkably grown in the last two decade.

An efficient channel allocation is essential to achieve the good performance in cellular

system. While the limited number of channels available, requires efficient reuse of

channels. To resolve this problem various channel allocation scheme developed by

researchers. The present work is carried in the general context of channel allocation issue

involved in cellular networks at heavy load situations. The simulation of this approach is

expounded and evaluated over OMNeT++ in a scenario with fixed channel allocation and

hybrid approach by varying the proportion of dynamic channels to total number of

channels available and the effectiveness is evaluated in terms of Call blocked and Call

dropped versus System load. The work presented here illustrates the efficiency and

flexibility of hybrid channel allocation algorithm along with a slight modification in

conventional algorithm by introducing the channel retrieval phase which retrieves back the

channels with BS, borrowed from MSC and are unused and allocates the same to some BS

requiring it and thus resolving the limitation of MSC of being exhausted of communication

bandwidth to serve further calls in heavy load. The call effectiveness of the work has been

illustrated in simulation where the approach performs better in almost all cases as

compared to its fixed counterparts.

If we compare the result of traditional system and proposed system then, call block rate in

h= 0.8, 240 channels are dynamic in 300 total channels, the call block rate 0.17 in our

proposed system whereas in traditional it was 0.2. Our method decreases the call block

rate but call drop is reduced even more. In the traditional system it was 28 whereas in our

proposed system it decreases to 22. Similarly hand over calls also reduces. If we focus on

h=0.8 in both cases, our method gives 1000 handover whereas in above system it was

1200. So it is clear that proposed method performs better in each and every case.

The simulation study of the protocol indicates that the protocol has low overhead, and it

behaves similar to the FCA at high traffic and to the DCA at low traffic loads. So by the

experimental and simulated evaluations of all channel assignment schemes we proposed

that HCA will give the appropriate results in reducing call blocking probability. Further

research has to be continued on HCA by increasing number of hotspot levels by

considering interference as a main parameter


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[9] Fan Wu and Nitin Vaidya, Workload-Aware Opportunistic Routing in Multi-Channel, Multi-

Radio Wireless Mesh Networks, 2012 9th Annual IEEE Communications Society Conference on

Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

[10] Prof. Dr.-Ing. Jochen Schiller, http://www.jochenschiller.de/ MC SS05, Mobile

Communications Chapter 2: Wireless Transmission

[11] Yu cheng, hongkun li, and peng-jun wan, A Theoretical framework for optimal cooperative

networking in multiradio multichannel wireless networks, IEEE Wireless Communications

April 2012

[12]Ashish Raniwala, Kartik Gopalan and Tzi-cker Chiueh, Centralized Channel Assignment and

Routing Algorithms for Multi-Channel Wi reless Mesh Networks,Mobile Computing and

Communications Review, Volume 8, Number 2

[13] J Joshi, G Mundada, A hybrid channel allocation algorithm to reduce call blocking

probability using hot-spot notification, Information and Automation for sustainability, 2010 -

ieeexplore.ieee.org

[14] Hasan C am, Nonblocking OVSF Codes and Enhancing Network Capacity for 3G Wireless

and Beyond Systems, Proc. of The 2002 International Conference on Wireless Networks, June

24-27, 2002, Las Vegas, USA

[15] Habiba Skalli, IMT Lucca Institute for Advanced Studies Samik Ghosh and Sajal K. Das, The

University of Texas at Arlington, Channel Assignment Strategies for Multi radio Wireless Mesh

Networks: Issues and Solutions.IEEE Communications Magazine November 2007

[16] Geetali Vidyarthi, Alioune Ngom, and Ivan Stojmenovic, A Hybrid Channel AssignmentApproach Using an Efficient Evolutionary Strategy in Wireless Mobile Networks, IEEE

TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 54, NO. 5, SEPTEMBER 2005

[17] Wei Wang and Xin Liu, List-coloring Based Channel Allocation for Open-Spectrum

Wireless Networks, University of California, Davis Davis, CA 95616, U. S. A.

[18] RayGuang Cheng & phone Lin, OVSF Code Channel Assignment For IMT-2000

0-7803-5718-3/00$10.00 2000 IEEE.


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smriti dissertation report

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