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RESEARCH OF CELLULAR WIRELESS COMMUNATION

SYSTEM

Cellular communication systems allow a large number of mobile users to seamlessly

and simultaneously communicate to wireless modems at fixed base stations using a limited

amount

of

radio

frequency

(RF)

spectrum.

The

RF

transmissions

received

at

the

base

stations from each mobile are translated to baseband, or to a wideband microwave link, and

relayed to mobile switching centers (MSC), which connect the mobile transmissions with

the

Public

Switched

Telephone

Network

(PSTN).

Similarly,

communications

from

the

PSTN

are

sent

to

the

base

station,

where

they

are

transmitted

to

the

mobile.

Cellular

systems employ either frequency division multiple access (FDMA), time division multiple

access

(TDMA),

code

division

multiple

access

(CDMA),

or

spatial

division

multiple

access (SDMA).

1

Introduction

A wide variety of wireless communication systems have been developed to provide

access

to

the

communications

infrastructure

for

mobile

or

fixed

users

in

a

myriad

of

opera

ting environments. Most of today’s wireless systems are based on the

cellular radio

concept.

Cellular

communication

systems

allow

a

large

number

of

mobile

users

to

seamlessly

and

simultaneously

communicate

to

wireless

modems

at

fixed

base

stations

using a limited amount of radio frequency (RF) spectrum. The RF transmissions received

at

the

base

stations

from

each

mobile

are

translated

to

baseband,

or

to

a

wideband

microwave link, and relayed to mobile switching centers (MSC), which connect the mobile

transmissions

with

the

Public

Switched

Telephone

Network

(PSTN).

Similarly,

communications from the PSTN are sent to the base station, where they are transmitted to

the

mobile.

Cellular

systems

employ

either

frequency

division

multiple

access

(FDMA),

time division multiple access (TDMA), code division multiple access (CDMA), or spatial

division multiple access (SDMA) .

Wireless communication links experience hostile physical channel characteristics, such as

time-varying multipath and shadowing due to large objects in the propagation path.

In

addition,

the

performance

of

wireless

cellular

systems

tends

to

be

limited

by

interference

from

other

users,

and

for

that

reason,

it

is

important

to

have

accurate

techniques

for

modeling

interference.

These

complex

channel

conditions

are

difficult

to

describe

with

a

simple

analytical

model,

although

several

models

do

provide

analytical

tractability with reasonable agreement to measured channel data . However, even when the

channel is modeled in an analytically elegant manner, in the vast majority of situations it is

still

difficult

or

impossible

to

construct

analytical

solutions

for

link

performance

when

error control coding, equalization, diversity, and network models are factored into the link

model.

Simulation

approaches,

therefore,

are

usually

required

when

analyzing

the

performance of cellular communication links.

Like

wireless

links,

the

system

performance

of

a

cellular

radio

system

is

most

effectively modeled using simulation, due to the difficulty in modeling a large number of

random events over time and space. These random events, such as the location of users, the

number of simultaneous users in the system, the propagation conditions, interference and

power level settings of each user, and the traffic demands of each user,combine together to

impact

the

overall

performance

seen

by

a

typical

user

in

the

cellular

system.

The

aforementioned variables are just a small sampling of the many key physical mechanisms

that

dictate

the

instantaneous

performance

of

a

particular

user

at

any

time

within

the

system. The term cellular radio system,therefore, refers to the entire population of mobile

users and base stations throughout the geographic service area, as opposed to a single link

that

connects

a

single

mobile

user

to

a

single

base

station.

To

design

for

a

particular

system-level

performance,

such

as

the

likelihood

of

a

particular

user

having

acceptable

service throughout the system, it is necessary to consider the complexity of multiple users

that are simultaneously using the system throughout the coverage area. Thus, simulation is

needed

to

consider

the

multi-user

effects

upon

any

of

the

individual

links

between

the

mobile and the base station.

The

link

performance

is

a

small-scale

phenomenon,

which

deals

with

the

instantaneous changes in the channel over a small local area, or small time duration, over

which the average received power is assumed constant . Such assumptions are sensible in

the design of error control codes, equalizers, and other components that serve to mitigate

the

transient

effects

created

by

the

channel.

However,

in

order

to

determine

the

overall

system performance of a large number of users spread over a wide geographic area, it is

necessary to incorporate large-scale effects such as the statistical behavior of interference

and signal levels experienced by individual users over large distances, while ignoring the

transient channel characteristics. One may think of link-level simulation as being a vernier

adjustment

on

the

performance

of

a

communication

system,

and

the

system- level

simulation as being a coarse, yet important, approximation of the overall level of quality

that any user could expect at any time.

Cellular

systems

achieve

high

capacity

(e.g.,

serve

a

large

number

of

users)

by

allowing

the

mobile

stations

to

share,

or

reuse

a

communication

channel

in

different

regions

of

the

geographic

service

area.

Channel

reuse

leads

to

co-channel

interference

among users sharing the same channel, which is recognized as one of the major limiting

factors of performance and capacity of a cellular system. An appropriate understanding of

the effects of co-channel interference on the capacity and performance is therefore required

when deploying cellular systems, or when analyzing and designing system methodologies

that

mitigate

the

undesired

effects

of

co- channel

interference.

These

effects

are

strongly

dependent on system

aspects of the communication system, such as the number of users

sharing

the

channel

and

their

locations.

Other

aspects,

more

related

to

the

propagation

channel, such as path loss, shadow fading (or shadowing), and antenna radiation patterns

are also important in the context of system performance, since these effects also vary with

the

locations

of

particular

users.

In

this

chapter,

we

will

discuss

the

application

of

system-level

simulation

in

the

analysis

of

the

performance

of

a

cellular

communication

system under the effects of co-channel interference. We will analyze a simple multiple- user

cellular system, including the antenna and propagation effects of a typical system. Despite

the simplicity of the example system considered in this chapter, the analysis presented can

easily be extended to include other features of a cellular system.

2

Cellular Radio System

System-Level Description

：

Cellular systems provide wireless coverage over a geographic service area by dividing

the

geographic

area

into

segments

called

cells

as

shown

in

Figure

2-1.

The

available

frequency

spectrum

is

also

divided

into

a

number

of

channels

with

a

group

of

channels

assigned to each cell. Base stations located in each cell are equipped with wireless modems

that

can

communicate

with

mobile

users.

Radio

frequency

channels

used

in

the

transmission

direction

from

the

base

station

to

the

mobile

are

referred

to

as

forward

channels,

while

channels

used

in

the

direction

from

the

mobile

to

the

base

station

are

referred

to

as

reverse

channels.

The

forward

and

reverse

channels

together

identify

a

duplex cellular channel. When frequency division duplex (FDD) is used, the forward and

reverse channels are split in frequency. Alternatively, when time division duplex (TDD) is

used, the forward and reverse channels are on the same frequency, but use different time

slots for transmission.

Figure 2-1 Basic architecture of a cellular communications system

High-capacity

cellular

systems

employ

frequency

reuse

among

cells.

This

requires

that co-channel cells (cells sharing the same frequency) are sufficiently far apart from each

other to

mitigate co-channel

interference. Channel

reuse is

implemented

by covering the

geographic service area with clusters of N cells, as shown in Figure 2-2, where N is known

as the cluster size.

Figure 2-2 Cell clustering:Depiction of a three-cell reuse pattern

The RF spectrum available for the geographic service area is assigned to each cluster,

such that cells within a cluster do not share any channel . If M channels make up the entire

spectrum available for the service area, and if the distribution of users is uniform over the

service area, then each cell is assigned M/N channels. As the clusters are replicated over

the

service

area,

the

reuse

of

channels

leads

to

tiers

of

co-channel

cells,

and

co- channel

interference

will

result

from

the

propagation

of

RF

energy

between

co-channel

base

stations and mobile users. Co-channel

interference

in

a

cellular system

occurs

when, for

example, a mobile simultaneously receives signals from the base station in its own cell, as

well as from co-channel base stations in nearby cells from adjacent tiers. In this instance,

one co-channel forward link (base station to mobile transmission) is the desired signal, and

the other co-channel signals received by the mobile form the total co-channel interference

at

the

receiver.

The

power

level

of

the

co-channel

interference

is

closely

related

to

the

separation distances among co-channel cells. If we model the cells with a hexagonal shape,

as in Figure 2-2, the minimum distance between the center of two co-channel cells, called

the reuse distance

D

N

, is

D

N

?

3

N

R

（

2-1

）

where R is the maximum radius of the cell (the hexagon is inscribed within the radius).

Therefore, we can immediately see from Figure 2-2 that a small cluster size (small reuse

distance

D

N

), leads to high interference among co-channel cells.

The level of co-channel interference received within a given cell is also dependent on

the

number

of

active

co-channel

cells

at

any

instant

of

time.

As

mentioned

before,

co-channel

cells

are

grouped

into

tiers

with

respect

to

a

particular

cell

of

interest.

The

number

of

co- channel

cells

in

a

given

tier

depends

on

the

tier

order

and

the

geometry

adopted

to

represent

the

shape

of

a

cell

(e.g.,

the

coverage

area

of

an

individual

base

station). For the classic hexagonal shape, the closest co-channel cells are located in the first

tier and there are six co-channel cells. The second tier consists of 12 co-channel cells, the

third,

18,

and

so

on.

The

total

co-channel

interference

is,

therefore,

the

sum

of

the

co-channel interference signals transmitted from all co-channel cells of all tiers. However,

co-channel

cells

belonging

to

the

first

tier

have

a

stronger

influence

on

the

total

interference, since they are closer to the cell where the interference is measured.

Co-channel

interference

is

recognized

as

one

of

the

major

factors

that

limits

the

capacity and link quality of a wireless communications system and plays an important role

in

the

tradeoff

between

system

capacity

(large-scale

system

issue)

and

link

quality

(small-scale issue). For example, one approach for achieving high capacity (large number

of users), without increasing the bandwidth of the RF spectrum allocated to the system, is

to reduce the channel reuse distance by reducing the cluster size N of a cellular system .

However,

reduction

in

the

cluster

sizeincreases

co-channel

interference,

which

degrades

the link quality.

The level of interference within a cellular system at any time is random and must be

simulated

by

modeling

both

the

RF

propagation

environment

between

cells

and

the

position location of the mobile users. In addition, the traffic statistics of each user and the

type

of

channel

allocation

scheme

at

the

base

stations

determine

the

instantaneous

interference level and the capacity of the system.

The

effects

of

co-channel

interference

can

be

estimated

by

the

signal- tointerference

ratio

(SIR)

of

the

communication

link,

defined

as

the

ratio

of

the

power

of

the

desired

signal S, to the power of the total interference signal, I. Since both power levels S and I are

random variables due to RF propagation effects, user mobility and traffic variation, the SIR