WCDMA Handover Optimization

8/10/2019 WCDMA Handover Optimization

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Design of O ptimum Parameters for Handover Initiation in WC DMA

Jongin Kim , Dong-hoi Kim**, Pyeong-jung Song**, Sehun Kim*

*Korea Advanced Institute of Science and Technology (KAIST)

373-1, Kusung dong, Yusung Gu, Taejon, 305-701, KOREA

**Electronics and Telecommunications Research Institute (ETRI)

161 Kajong-Dong, Yusong-Gu, Taejon, 305-350, KOREA

Email : [email protected]

Abstract

WCDMA handover algorithms employ signal

averaging, hysteresis and the Time-to-Trigger mechanism to

optimize the trade off between nu mber of unnecessary handover,

reported events(system load) and handover delay time. We

investigate optimal parameters for the WCDMA intra-.

frequency handover algorithm and the impact of each

parameter on the system performance. Number of reporting

events triggered for handover and handover delay are key

performance measures in this paper. The study shows various

tradeoffs between the parameters related to averaging,

hysteresis and Time-to-Trigger. We have also discovered that

the layer3 filter and Time-to-Trigger mechanism may cause

negative effects on each other in some cases and there are

optimum values, when used sim ultaneously.

1

INTRODUCTION

Design of handover initiation can be made to use several

measurements such as the received signal level from the

communicating and neighboring base stations, the path loss

to the base stations, and bit error rate. In general, hysteresis

and signal averaging is employed to enhance the performance

of handover(i.e. probability of unnecessary handover at the

expense of handover delay). Previous studies on handover

initiation have revered that there are trade offs between

handover delay and n umbe r of unnecessary handover.

Handover initiation criteria analyzed in literature are

mainly based on the length of averaging window, the

threshold level and the hysteresis margin. In addition,

WCDMA introduce the Time-to-Trigger mechanism to

reduce unnecessary signaling and ping pong effects. Also

averaging window is used to smooth out random signal

fluctuations and to make handover decisions to be based on

underlying trends and not instantaneous changes.

Soft handover is essential for intra frequency

in

WCDMA.

The active set i s defined as the set of base stations to which

the mobile users is simultaneously con nected. Soft hand over

involves active set update procedure which include signaling

of appropriate event triggered by the mobile based on the

measurement of the measurement quantity (i.e. Ec/Io, path

loss, etc). Frequent reporting may cause unnecessary

handover and signaling overload. On the other, if the

reporting is too seldom, it may increase the han dover delay.

WCDMA(3GPP) recommendation does not specify the

measurement and averaging interval be fixed or variable.

Actual physical layer measurement depends on the

implementation of the mobile unit. However, WCDMA

specifies the network controlled features to enhance the

performance, which include the hysteresis, Time-to-Trigger

and Layer3 filtering. A network controlled Layer3

fiItering(exponentia1 smoothing) provides same options as to

hysteresis and Time-to-Trigger to some extent, but give some

extra benefits which makes it possible to control the rate of

reporting, i.e. system loads. Therefore, it is our interest is to

investigate the impacts of each of the network controlled

elements, including Layer3 filter, hysteresis margin and

Time-to-Trigger, to handover performance after applying a

minimal physical layer measurement. Our goal is to optimize

the parameters for these handover mechanisms considering

various ttadeoff relations. By using an appropriate

combination of filter, hysteresis and Time-to-Trigger, it is

possible to fine tune the real time decisions to be optimal in

time and amplitude. Therefore, we can optimize parameters

related to hiandover decision.

3. SYSTEM DESCRIPTION

A. Meas urem ents and Signaling

In WCDMA system, the mobile station performs intra-

frequency measurement and sends measurement report to the

Radio Network Controller(RNC), where the final decision is

made about which cell to add or remove from the Active

Sets[2]. The intra frequency measurement is done on the

downlink P-CPICH [l]. Measurement quanti ty can be any

of'

the followings; Ec/Io, path loss and the Received Signal Code

Power[

11.

Consider a model for a network controlled handover

filtering (Signal averaging) shown in Figure 1 This model is

as recommended in 3CPP specification[ 11. Parameter 1 is

related to :shape of Layer3 filter provided by the network and

0-7803-7005-8/01/ 10.00

0

2001

IEEE

2768

parameter 2 is related to types of handover, i.e.

frequency, inter-frequen cy, etc and reporting criteria.

I

Paramters

2

P a m t e r s

1

Layer Layer 3

filtering iltering

-b

valuation

_

ofreporting

Figure 1. Model for handover measurements

intra

D


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Uu lub

Physical layer implementation (inputs A and Layer 1

filtering) is not constrained by the standard i.e. the model

does not state a specific samp ling rate or even if the sampling

is periodic or not. What the standard specifies is the

performance objectives and reporting rate at point B in the

model. Th e reporting rate is equal to the measuremen t period,

which is 200ms for intra-frequency measurement. The

performance objectives for the physical layer measurements

are specified in [3].

In addition , the Layer3 filtering

is

performed according to

the following exponential averaging formula to give more

accuracy.

The variables in the formula are defined as follows;

F,,

s the

updated filtered measurement result. F,+,

is

the old filtered

measurement result. M,, is the latest received measurement

result from physical layer measurements. If

a

is

set to

1

that

will mean no layer 3 filtering. Also, smaller will mean that

it

is

giving more weights to past samp les.

Hysteresis and Time-to-Trigger mechanism on the other

hand is important for reducing unnecessary signaling or

handover and they complement to averaging mechanism.

Evaluation of reporting criteria

is

based on the measurement

results (after appropriate filtering) using the hysteresis and

Time-to-Trigger mechanism. The reporting event 1A and

1

B

is

defined as;

-Meas_Sign>Best-Ss-Hyst-Add for AT: Event A

-Meas-Sign


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2:

Propagation Model

Channel Model

Standard Deviation of

I

-

0

1000

2 3 4

Distance

traveled by mobile

m)

Figure4. Model for handover measurements

128.1+37.6log (R)

ITU-Vehicular A

1OdB

As it can be seen, the basic Layerl filtering of 200ms in

our model does not completely average out the signal

fluctuation. Relationship between the accuracy and the

measurement distance is described in [5]. Our interest i s to

investigate the effects of the network controlled elements,

such as Layer3 filter, hysteresis margin and Time-to-Trigger,

on the handover performance after applying a minimal

Layerl filtering. The simulation parameters are listed below

and the channel model

i s

described in the following

subsection.

CPICH Power

Parameter Value

47dBm

Log-Normal fading

Decorrelation des tance 20m

I

H

yst -ADD lSdB,3dB,4SdB,6dB

I

Hyst -Drop 2SdB,5dB,7SdB,lOdB

Ti me-to-Tri gge r Oms,200ms,400ms

Measurement Pen od 200m s

Sampling interval

Layer3 filter coefficient

0.1-1

I

Table 1. Simulation parameters

A.

Propagation Model

Th e received signal at a mobile consists of three parts; path

loss, slow fading and fast fading (Rayleigh distributed).

Therefore, the received signal (in dB) as a function of m obile

distance

i s

given by,

r d ) =

K ,

-

K , log,, d) + v d ) + 201og,,[e d)]

The parameters K1 and K2 accounts for path loss, v(d) i s

the shadow fading process; zero mean, variance lOdB,

stationary Gaussian process. The shadowing process is

assumed to have the exponential correlation function

proposed by Gudmundson[6]. Decorrelation distance is

assumed tci be 20m in vehicular environments [4].

For the fast fading, we use ITU Vech icular A m odel[4].

Received s,ignal after filtering is then given by

~

d )

= K,

-

K,

l o g , , ( d ) +

V d )+

2010g l , [ e ( d ) ]

B. Performance Measures

Optimal handover is the trade off between the number of

unnecessai-y handover and the h andover d elay. Many

previous literatures have studied the properties of this trade

off for various parameters such as the hysteresis margin and

the length of averaging distance[8]

In W CDM A, the standards specify the measurem ent model

and the range of parameters like Layer3 filter coefficient,

hysteresis and Time-to-Trigger. But, the impacts of these

parameter:: and different choices for the values remain to be

clarified.

WCDMA use soft handover mechanism to enhance the

coverage and capacity of the network. Soft handover

mechanisrn involves active set update and removal as

described in the previous section. To many reporting events

will cause unnecessary active set updates and increase the

signaling load. On the other hand, infrequent reporting may

cause delay in handover. Optimal size

of

soft handover

depends on loading conditions and, etc. The size of soft

handover area can be also controlled by the system

parameters.

Number of reporting events triggered for handover and

handover delay are key performance measures in this paper.

In our simulation, the tradeoff between the number of

reporting events and average distance of active set

additioniremaval, averaged over 1000 runs, are investigated

with different hysteresis margins, Layer 3 filter coefficients

and Time-to-Trigger. Average distance

of

reporting event

1

A

i s the mean distance at which the active set addition for BS2

takes place.

5. SIMULATION RESULTS

Figure

5 .

shows the expected number of report ing e ventlA

for mobile traveling at speeds 50km/h and 120km/h with

various hysteresis, not using Time-to-Trigger. Number of

reporting events

i s

quite large when Time-to Trigger is not

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used. It can be observed that the layer3 filter can reduce the

number of reporting events significantly. Especially at low

mobile speed, it shows significant improvements. The effect

of the hysteresis is also shown in this figure. Figures

9.

and

IO show the mean distance at which the mobile sends the

reporting Even tIA for BS2 and eve ntlB for BS1,respectively.

It can be interpreted as the expected point where the mobile is

enterindleaving the

soft

handover area. This position

depends on the setting of hysteresis levels, but Layer3

filtering also has effects of delaying the distance of

enterindle aving the area. Similarly, as show in Figures

1 1

and 12, the Time-to-Trigger mechanism also delays the

reporting even ts. Th e gain of soft handover and optimum size

depends on many factors including the system loads and the

capacity.

Figure 6. represents the expected number of reporting

event

1A

with Time-to-Trigger of 200ms. It is interesting to

observe that the rate of increase of the number of reporting

event starts to slow down at some point as alpha is increased.

Further, in Figures 7 and 8, with 4 00ms Time-to-Trigger, the

number of reporting actually begin to decrease at some point

along alpha. This characteristic is explained as fo llows. First,

with no Time to Trigger, the smoother curve will obviously

give less reporting events since it has smaller variations. If

the Time-to-Trigger of 200ms and 400ms is used, two and

three adjacent samples are subsequently evaluated,

respectively. Exponential averaging induces correlations

between these samples. Correlated samples will be

undesirable than independent samples in extracting the

average value. Therefore, there exists a tradeoff between

obtaining the stable measurement results and getting

independent samples. Consequently, in setting Time-to-

Trigger and Layer3 filter constant, we may consider this to be

compromised.

.+

c

3 -

0

r

a

[r

c

-

2 1 2 -

1 1 -

n

1 0 -

60

I

50

t

5

40

0

3

0

g

20

a

10

Z

0

yst-Add=B, Hyst-D

rop= lO,

V=l20

krnh

0 . H yst-Pd d=3, Hyst-D rop=5, V=l2Okrn/h

yst-Ad

d=6,

Hyst-0

r o p=lO , V=SOkrn/h

Hys t_Nd=3 . Hyst_Drop=5,

V Okrn/h

I I

0 0 0 2 0 4 0 6 0 8 1 0 1 2

Layer3 Filter Coefficient(a)

Figure

5.

Average number

of

reporting eventlA

Time-to-Trigger = Oms)

5

4

-0 /J

0 0

0 2

0 4 0 6

0 8

1 0

Layer3 Filter Coefficient(a)

Figure

6.

Average number

of

reporting event 1A

Time-to-Trigger

=

200ms )

2

1 5

0

-e Hyst_Pdd=3, Hyst_Drop=5

0 Hysl-Pdd=l 5, Hyst_Orop=25

0 9

0 0 0 2 0 4 0 6

0 8

1 0 1 2

Layer3 Filter Coefficient(0)

Figure 7. Average number of reporting event 1A

V=120km/h, Time-to-Trigger = 400ms)

U

f

v

/

0

0

.- 0

Hyst_Pdd=3,

Hysl_Drop=5

yst-Add=l 5. Hyst_Drop=25

/

0 0

0 2 0 4 0 6 0 8

1 0 1 2

Layer3 Filter Coefftcient(0)

Figure8. Average number

of

reporting event 1A

V=50km/h, Time-to-Trigger

=

400ms)

277 1


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1600

\

1750

700

650

-

E

J 1600

1550

s

0

-c H yst -A d d 4 d B , Hy st-D rop=5dB

0

Hyst_Pdd=6dB, Hyat-Drap=lOdB

0.

2600

2500

-

E

8 2400

E

P

2300

-

...

i

2200

21 00

0

* 0 0 0 0 0 0

Hyst_Pdd=3, Hyst_Drop=5

0 Hyst_Pdd=6, Hyst-Drop=lO

0 0 0 2

0 4

0 6 0 8 1 0 1 2

Layer3 ilter soefficient(0)

Figure

I O .

M e a n d i s t a n c e

of

r e p or ti n g e v e n t l B(50km/h)

1820

1800

-

E

-

8

1780

E

0

1760

...

d

1740

1720

T

-4- Time-to-Trigger=Oms

0 Time-to-Tr igge~200ms

ime-to-Tr igge~400ms

\O

0 0

0 2

0 4 0 6

0 8

1 0 1 2

Layer3 ilter coefficient(a)

Figure 11. Mean distance

of

reporting eventlA

Hyst_Add=3,Hyst_Drop=5,

50krn/h)

2300

r I

2280

.-.

E

2269

E

2240

A

Ln

22zD

Time_to_Trigger=2SOms

o\

\

\

2200

0 0

0 2

0 4

0 6 O B

1 0 1 2

Layer3 filter coefficient(a)

Figure 12. Mean distance of reporting eventl B 50km/h)

Hyst-Add=3, Hyst_Drop=5, 50km/h)

6.

CONCLUSIONS

This study investigates the impacts of each of the network

controlled features (including Layer3 filter, hysteresis margin

and Tim e to Trigger) in handover initiation mechanism. The

study shows various tradeoffs between the parameters. It was

investigated in terms of the number of event reporting and

handover delay distance. The performances are also shown to

depend on the velocity of the mobile. We have also

discovered that the layer3 filter and Time-to-Trigger

mechanism may cause negative effects on each other in some

cases anti there is an optimum combination, when used

simultaneously. The results presented in this study may help

in understanding the behavior of the features related to

triggering of handover measurement reports and in extracting

optimum parameter values. Further, these results can be used

for developing more efficient handover algorithms.

REFEREN E

[I ] 3GPP T S 25.302 Ver 3.3.0 Services prvided by physical

layer, March, 2000

[2] 3GPP T S 25.331 V er 3.6.0 RRC protocol specification,

March,

2000.

[3] 3GPP T S 25.133 Ver 3.5.0 Requirements for Support of

Radi o Resource Management ,December, 2000

[4] ETSI TR 101 112 V3.2.0, Selection procedures for the

choice of radio transmission technologies of the UMTS,

April , 1998

McGrawHill , 1981

[ ]

C.Y.Lee, Mobile Communications Engineering

[6] M.Gudmunson, Correlation Model for Shadow Fading in

Mobile Radio Systems, Electronics Letter, Vol 27, no23,

pp 2145-2146, NOV 1991.

[7] R.Vijayan and J.M.Holtzman, A Model for Analyzing

Handoff Algorithms, IEEE Trans. On Vehicular

Technology, August 1993.

Cominunications M agazine, March 1996

[8]

Gregory P. Pollini, Trends in Handover Design, IEEE

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WCDMA Handover Optimization

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