gsm capacity load

7/23/2019 GSM capacity load

http://slidepdf.com/reader/full/gsm-capacity-load 1/5

CAPACITY OF

A

GSM NETWORK W ITH FRACTIONAL LOADING AND

RANDOM FREQUENCY

HOPPING

Jeroen Wigard, Preben Mo gensen, Jesper Johansen and Benny Vejlgaard

Center for Personkommunikation

Fredrik Bajers Vej 7A, DK-9220

Aalborg

@st,Denmark

e-mail: jw@ cpk.auc.dk

so

Abstract: The need for more capacity in

GSM

networks is increasing. Using random frequency

hopping and fractional loading is a potential way to

obtain more capacity. In this paper the optimal reuse

scheme for a

GSM

system with random frequency

hopping is presented along with some methods to

increase the capacity and to improve the link quality,

like using DTX and fractional loading. The 113 reuse

scheme appears to be best if the capacity is

determined by looking at the distribution of signal to

interference (CIR) values, while the 3/9 reuse scheme

seems best if the focus is at the percentage of

dropped calls with the used dropped call, power

control and handover algorithm). The 1/3 reuse

scheme has the advantage over the 3/9 reuse scheme

that it is able to profit from fractional loading, which

gives better quality to the individual user.

132 4

I Introduction

The GSM standard is a huge success: more than 60

zountries have implemented the system and the number

of subscribers increases quickly. This leads to a demand

for more capacity in the existing GSM networks. There

are several methods to achieve more capacity, but most

of them , like for exam ple cell splitting, are quite

zxpensive, because more base stations have to be used.

By making the reuse distance smaller by changing the

Frequency planning, more capacity is achieved with

relatively low costs. However the quality of the

individual connection decreases, due to the increased

interference. By using random frequency hopping and

Fractional loading this decrease in quality can be

:ompensated, because it gives a quality gain to every

mobile station.

The GSM standard is described shortly in section

II

Followed by a description of the simulation setup in

section III Section I V discusses the optimal frequency

:euse scheme together with the influence of some

system parameters. Section

V

presents

the

gain from

Fractional loading and synchronization.

1-7803-3692-5/96 996 IEEE

11.

GSM

The GSM standard is based

on

Multi Carrier, Time

Division Multiple Access and Frequency Division

Duplex, MC/TDMA/FDD

[11.

Two frequency bands are

defined for GSM: the band from 890 MH z to 915 MHz

is used for the uplink and the band from 935 MHz to

960 MH z is used fo r the downlink. These bands are in

most countries divided among

2

or

3

operators. Beside

these 900 MHz bands there are two bands in the 1800

Mhz from

1710

MH z to 1785 MHz and from 1805 MH z

to 1880 MHz. The C arrier spacing is 200 kHz allowing

for 124 (900 Mhz) or 374 (1800 Mhz) radio frequency

channels, thus leaving a guard band of 200 kHz at each

end of the subbands.

Each radio frequency channel is time divided into

TDMA frames of 4.615 ms. Each TDMA frame is

subdivided into 8 full slots. Each of these slots can be

given to a full rate traffic channel, two half rate traffic

channels or one of the control channels.

Class l a

Class

l b

Class 2

1 5 0

I 1 3 2 I 78

CRC

check

..

. . ....

onvolutional code

r=1/2, K=S

I 378 I 78 I

Figure I

Channel

coding of

the

TCH/FS

In GSM the databits are coded. The channel coding

introduces redundancy into the data flow, by increasing

the bit rate. For the TCW FS mo de, a 3 bit CRC is at first

applied to the Class l a bits, and secondly all class

1

bits

are encoded by a convolution code. The class 2 bits

remain unprotected. The reordering and interleaving

process mixes the encoded data block

of 456

bits,

and

groups the bits into 8 sub-blocks (half bursts). The 8

sub-blocks are transmitted on 8 successive bursts

723



(interleaving depth equals 8). The channel coding can b e

seen in Figure

1,

while the reordering and interleaving

can be seen in Figure 2.

...........................................

23 4 455

..........................................

2 3 455

Reordering

A0 AI

A2 A3

A4 A5 A6

A7 O 81 82 83

84

85

66 87

A0 - AI ~

A2

- A3

wv uv

Burst

0 1 2 3

4

5

8 7

- 80 A4 81

A5 E2

A0 83 A7

Figure

2

Reordering and Interleaving

of

the

TCH/FS

Due to multipath propagation, the erroneous receive(

bits tend to appear in “bursts”. The convolutional code

gives the best performance for random positioned bit

errors, and therefore reordering and interleaving is

introduced in the GSM signal transmission flow.

However, the reorderinginterleaving only improves the

coding performance, if the

8

successive bursts carrying

the data information of one speech block are exposed to

uncorrelated fading. This can be ensured by either a

spatial movement (high user speed) or frequency

hopping.

111.

Network Simulation setup

A GSM network simulation tool, ‘CAPACITY’, has

been developed in order to measure both the

performance and the capacity of a FH-GSM system.

This simulation tool is able to simulate the factors that

affect the performance of the GSM system, like

frequency hopping, DTX , and power control and

returns the quality of the GSM system

at

a given system

load. This quality is measured in terms of CJR and

percentage of dropped calls.

The cell radius is

2 km

and the base station grid is

regularly with 48 base stations. With a transmitting

power

of 34 dBm

and a path loss slope of 3.5 this leads

to a received power median at the cell edge

of -81 dBm.

Hence, the interference will be the limiting factor on the

cell size.

In

the simulations Rayleigh and shadow fading are

simulated. The log-normal fading is correlated over 110

m.

A standard deviation of

6

dB (for urban area)

[2]

is

used as the reference in the capacity simulations. For

each SAC CH multi frame, measurements

are

performed

on 104 bursts. For burst measurements the time

resolution is set to 4.615 ms, corresponding to

TDM A frame.

In

the simulations the handover algorithm is based

distance and a simple power control algorit

described in

[ 3 ]

s used. Since the handover and po

control have quite an influence on the number

dropped calls, the capacity based on the percentag

dropped calls might be improved by using ano

power contro l and handover algorithm.

The GS M network operators have only a limited num

of channels at their disposal. This means that

capacity of the system must be optimized with a f

number of channels. The capacity is limited by eithe

number of traffic channels

(Hard blocking)

or

interference from the neighbor cells

(Soft

blocking).

soft blocking is determined by setting a threshol

percentage of dropped calls or to the percentage of

values, which are worse than

9

dB.

When the percentage of dropped calls is used,

maximum capacity is determined by finding

maximum load for which the percentage of drop

calls is less than

5 .

If the percentage of CIR<9d

used, like in

[ 3 ]

and the soft blocking threshold is l

the maximum capacity is found by determining the

for which

10

percent of all CIR values is worse th

dB

With a small reuse factor there is a large numbe

frequencies available in each cell but the system

limited by interference due to the low reuse factor.

system with a high reuse factor, the number of user

the system are limited by the number of avail

channels. This gives a high blocking probability wh

call is attempted. The maximum capacity should

reached somewhere between an extremely low r

factor and a fairly high reuse factor. In the simulatio

hard blocking of

2

is used.

In the simulations the following call drop algorith

used: each mobile station has a counter. When

RX-QUAL of a superframe is worse than the call d

RX-QUAL threshold (which is set to 5 in

simulations, i.e. has a raw BER worse than 6.4%),

the counter is increased by 1.

If

the

RX-QUAL is b

or equal to the call drop RX-QUAL threshold, then

counter is decreased by 2, if that does not make

counter negative (in that case the counter is set to

When the counter becomes greater than the call

threshold

(equal to 9 in the simulations), the mo

connection is dropped.

In

most cases this leads to a

drop, when the mobile station has 10 follow

superframes with a RX-QUAL>S.

In

Figure 3

exam ple can be seen of the call drop algorithm.

724



RX-QUAI,

Counter. 0 1 2 3 4 S 6 7 8 6 7 8 9 1 0

J

Call

Drop

Figure 3: Example of the call drop algorithm with Call Drop

RX-QUAL threshold=5 and Call Drop threshold=9.

3 6 6 6 6 7 7 6 5 6 7 7 6

The following table summarizes the parameters in the

GSM

network simulation tool.

1/1

313

414

Path

loss

Shadow fading standard deviation

Shadow fading correlation distance

Call mean hold time

Mo bile velocity

Time slo ts used

Cell radius

Max. effective BS output power

Min. effective BS output power

Antennas

Frequency hopping algorithm

Handover

Power control

DTX factor

Call Drop

RX-QUAL

threshold

Call

drop threshold

20.2 20.2 Soft

61.4 61.4 Soft

60.5 60.5 Hard

Lp=

35

log

d

6

dB

l/e at 110

m

100

s

(exponential distribution)

50kmh

1 (due to sim ulation time)

2km

34 dBm

4 dBm

90

O

sectorized and omnidirectional

random hopping

based

on

distance

both level and quality

0.5

5

9

113

28.8

86.4

Table :

Summary

of the simulation parameters in the dynamic

simulations

Soft

IV. esults

The following conclusions were taken after the initial

network simulations

[2]:

319

In an interference limited environment random

hopping has better performance than sequential

hopping, because

w

random hopping not only

frequency diversity, but also interference diversity is

obtained.

The quality increase from power control and DTX

can be translated into a capacity increase when

using random frequency hopping since the quality

increase is averaged among all the mobiles.

In

the

case w here no frequency hopping is used this quality

increase can not completely be translated into a

capacity increase since only some mobiles benefit

from the increase in quality.

23.7 71.0

I Hard

In order to illustrate the capacity of the various reuse

schemes when frequency hopping is utilized the

maximum capacity of each reuse schem e was simulated.

The maximum capacity is defined as the limit where

either hard blocking, or soft blocking (dropped calls or

CIR limited) is reached.

4112 I 16.6

First the results, based on CIR limited soft blocking, are

presented. To make these results comparable with what

is obtainable for a single operator, a fixed number of

36

TCH

frequencies has been simulated in the system.

I.e.

there are more frequen cies available per cell in a system

with a reuse factor of 3 than in a system with a reuse

factor

4.

The results from the simulations of the

maximum capacity for a hard blocking threshold of 2%

and a soft blocking threshold of

10

s given in Table

2.

49.7 Hard

Random frequency hopping

Reuse I Erlanglcell Erlanglsite I Blocking

4/12

16.6 49.7

Hard

T

/

\

/9

,

/

\4/12

l 2 4

6

10

12 14

Fraction of

total

frequencies per cell

[36k

req /cell]

Figure 4: Illustration of the maximum capacity obtainable

with various reuse factors and a

90

coverage with a

CIR

limit of 9 dB. indicates reuse schemes with omn i directional

antennas. indicates sectorized reuse schemes. o indicates

calculated points fo r hard blocking in omni systems, these are

not simulated.

The maximum capacity per site is reached for the

sectorized reuse schemes with the 1/3 reuse scheme as

the maximum. T his was also found by [3], although they

725



used a slightly different system, with a simplified

averaging method. The 1/3 reuse scheme along with 36

frequencies available gave a maximum capacity of 86.4

Erlang/site (30% load) as opposed to the static 4/12 with

a capacity of 49.7 Erlanghite. The capacity

of

the 1/3

reuse scheme is a 74% increase compared to the static

4/12 reuse scheme.

The capacity curves shown in Figure 4 are calculated

from the received CIR values and is thus completely

independent of the receiver structure and its

performance. When the percentage of dropped calls is

used as measure for the soft blocking, then the results

are receiver dep endent.

When we use the percentage of dropped calls as

measure for the soft blochng, then we find some

different results. The results are more negative.

Simulations have shown that the 1/3 reuse scheme with

30% load, which was found to be optimal, when soft

blocking based on CIR is used, gives a dropped call

percentage of 16% with the used call drop algorithm

The capacity when a limit of maximal

5

dropped calls

is used, w e find the results as depicted in Figure 5 . The

capacity for 3 different bandwidths can be seen.

100

E

t

r

c

a0

6

S

.- 40

U

p

20

m

B

0

0 2 4

6

a

10 12

Frequency reuse

F i gure

5:

T he c apac i t y f o r d i f f e re n t bandwi d t hs and

re use s c he m e s , ac h i e v e d

with

a soft b l oc k i ng base d

on

m ax i m al 5 blocked cal l s .

It can be seen that the capacity decrease in the case of 36

TCH

channels

(9.6

Mhz)

is

about

20

and that the

1/3

reuse scheme is no longer preferable above the 3 /9 reuse

scheme. We think the method of determining the

capacity with the percentage of dropped calls is more

realistic than the method based on the C IR values, since

dropped calls is something, which is really being

experienced in a mobile network by the individual user,

while the CIR values method does not look at the

individual user at all. However the power control and

handover algorithm, which are used, might not be

optimal, and these algorithms have a great influenc

the dropped calls. So the capacity, based on

percentage of dropped calls might be improved, by u

another power control and handover algorithm.

result might even be that the 1/3 reuse scheme beco

better than the 3/9.

From the figure also can be seen that the capacity ca

increased quite a lot by getting more bandwidth.

V. Fractional loading

The

GSM

link simulation tool, developed at Aal

University (AUC), has been used for the analysis of

of fractional loading. The w hole program is describ

[4]. Each of the operations in the GSM transmi

path including a fading radio chan nel and thermal n

(white Gaussian) a re included.

The results are obtained by simulations for diffe

loads with multiple interferers. The simulations are

with 6 interferers and one background interferer w

C I level of 7.5 dB lower than the other 6 interferer

Figure 6 the locations of the different interferers ca

seen. The background interferer is always on, becau

represents all the interference from outside the first

The other six interferes are sometimes on sometime

depending on the load of the system. Shadow

Rayleigh fading are included.

\ /

.BACKGROUNDMTERFERU

Figure 6: Assumed network set-up fo r the simulations. Ea

hexago n is a cluster, not a cell.

I1

to I6 are the

6

interfer

of the f irst tier whilst BS is the base station from which

desired signal is received. A background Interfe

represents the interfering signals from the second tier.

The Figures 7 and 8 show the gain of fractional loa

In Figure 7 the FER of a TU3 link with frequ

hopping, power control and no synchronization.

power control compensates completely for the sh

fading

of

the desired user. The results without p

control show the same gain from fractional loading

random frequency hopping.

In

Figure 8 the relative

in BER (class

1

or protected bits) of fractional lo

726



with and without synchronization can be seen with as

reference a 100 loaded network without DTX, where

no gain is achieved by fractional loading and

synchronization.

1

0.1

K

w

LL

0.01

0.001

. - - . - .

.

.

- - - . - - - - .

5 load

A 25 load

-C50 load

.

.

- - .

.

. . . . .

Figure 7: The FER in a TU3 u l l hopping link with 6

interferers and one background interferer fo r different loads

in the case o pow er control and

no

synchronization

0

0 5

1 1.5 2 2.5 3 3.5 4 4.5

Relative gain [dBl

Figure 8: The relative gain

of

the BER class 1 in dB of

fractional loading and synchronization in a GSM network.

From these

2

Figures the following observations can be

made:

The gain from fractional loading is between the

3

and

4

dB, when going from a

10

load to a

100

load.

By synchronization a gain is achieved. This gain

depends very much

on

the load.

10

load leads to a

gain of about 1 dB, while in the case of 100 load

the gain has disappeared.

If a 1/3 reuse scheme is used with 25-30% load, which

corresponds in the case of a DTX factor of 0.5 to

15

load in the Figures, approximately 3 dB is gained by

fractional loading, while synchronization gives a further

gain

of 0.5 dB.

It should be noted how ever that this kind

of synchronization is ideal synchronization,

so

the gain

will be even less in reality. When a 319 reuse scheme is

used no ex tra gain is achieved from fractional loading or

synchronization, because the system is loaded m ore than

75

due to the high soft blocking limit.

VI. Conclusions

For getting the maximum capacity out of a

GSM

network, random frequency hopping with fractional

loading has to be applied. The optimal reuse pattern has

been found to be either 1/3 or 3/9 depending on whether

the CIR distribution or the percentage of dropped calls is

used as parameter. We think the percentage of dropped

calls is a better measure than the CIR distribution, since

it says something about what the individual user

experiences in the network. With the dropped call

algorithm, which we have used, the 3/9 reuse scheme is

better in terms

of

capacity than the 1/3 reuse scheme.

However this might change by using another handover

and power control algorithm, since these two algorithm

have a great influence on the number of dropped calls.

In the simulations a very simple power control and

handover algorithm was used. The 3/9 reuse scheme is

limited by the hard blocking (number of available

channels), so no fractional loading gain can be achieved.

The advantage of the

1/3

reuse scheme is that soft

blocking is the limiting factor, because there are enough

channels per sector. This means that a gain can be

achieved by using fractional loading. This gain can

however not be translated direct into capacity, it gives

only a better quality.

Acknowledgment

We would like to thank Nokia telecommunications

Finland for co-sponsoring the project.

Literature

[13

GSM

Recommendations

[2] Johansen Jesper and Vejlgaard Benny, Capacity analysis

of

a Frequency Hopping GSM System Master Thesis Report,

Aalborg

University , June 1995

[3] Carenheim

Caisa

Jonsson

Svend-Olof,

Ljungberg Malin,

Madsfors

Magnus

and Naslund Jonas,

FH-GSM Frequency

Hopping GSM

IEEE

Proc. of VTC'94, Stockholm,pp. 1155-

1159.

[4] Jeroen

Wigard, GSM

Link Simh ation

Tool

version

2.0

Aalborg university, October 1995.

gsm capacity load

Documents