Parameter Analysis of Semi Deterministic Pathloss against Soft

Handover Performance in Mobile Communication

Maksum Pinem

, Muhammad Zulfin

, Indah Vusvita Sari

, Sri Indah Rezkika

Electrical Engineering Department, Universitas Sumatera Utara, Padang Bulan, 20155 Medan, Indonesia

Keywords: Radio Propagation Models, Propagation Parameters, Mobile Communication Performances, Simulation

Programming.

Abstract : This research focused on assessment of the parameters semi-deterministic propagation model in effort

enhancement performance soft handover in mobile communication, so obtained characteristic model

propagation parameters affecting relations with enhancement performance soft handover. The method used is

design simulation with computer programming by building a model of virtual mobile communication system

with software. The propagation model and handover model that has been applied in this research are Cost231

Walfisch-Ikegami and soft handover-hysteresis with threshold. The observed parameters were height of

building, street width and distance between buildings. While the performance parameters system wireless

moves are observed, ie : drop call rate, radio link increase rate and active set average rate. From the simulation

result obtained, ie : the increase in height of the building causes decreased radio links, increased drop call

rates and reduction of the average number of active sets. Whereas on the contrary with the width increase

between buildings and street width respectively causing the increase of radio link, decrease of drop call rate

and addition of active set average amount.

1 INTRODUCTION

The Path loss is the electromagnetic wave that

spreads through the space between the transmitter

antenna and the receiver antenna in the

communication system. It can be caused on decline

quality and the strength of radio signals due to the

effects of reflection, refraction, diffraction, scattering

and absorption. The effect are influenced by

environmental conditions, frequency of operation,

distance between transmitter and receiver (O.O. Oni

and F.E. Idachaba, 2017). Although thus, high

mobility of user movement in mobile communication

are caused by the strong fluctuations of the received

signal level as a result of propagation damping,

distance and obstacles the environment is not

irregular (Maksum Pinem, 2014). To maintain the

stability and continuity of mobile communication, a

service switching mechanism called handover is

required .

For the new generation network move needed an

innovative predictive model related with frequency .

On research previous has analyzed six predictions

model of loss different paths and as a whole is the best

choice for a new generation of networks moving

regardless of distance and type of environment

(Aymen Zreikat and Milan Dordevic, 2017).

Caused of high mobility of the MS moving from

one cell to another cause difficulty in backing

prediction signal propagation and effect on signal

strength level of reception. Strong level signals

received by MS is influenced by path loss, shadow

fading and fast fading, as a result of the propagation

and attenuation of irregular circumstances (Singh, N.

P and Singh.B, 2010).

Study on signal radio spreading is very important

in the wireless network within effort keep quality

signal communication and stability continuity

communication move between user (handover),

beside magnitude funds to prepare infrastructure from

communication system wireless. By therefore, this

study are focused on assessment of the parameters of

the semi-deterministic path loss propagation model in

effort to enhancement performance soft handover in

mobile communication, so obtained characteristic

Pinem, M., Zulﬁn, M., Sari, I. and Rezkika, S.

Parameter Analysis of Semi Deterministic Pathloss against Soft Handover Performance in Mobile Communication.

DOI: 10.5220/0010080502430247

In Proceedings of the International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches (ICOSTEERR 2018) - Research in Industry 4.0, pages

243-247

ISBN: 978-989-758-449-7

243

model propagation parameters affecting relations

with enhancement performance soft handover, so

expected this research give contribution on guarding

quality signal communication and stability continuity

communication.

2 MODEL DESIGN

In this study, the modeled BS consists of two base

stations. Each BS has the same and separate transmit

power at distance D and mobile station (MS) moves

on a straight path with a regulated speed as shown in

Figure 1 (M. Pinem and R. Fauzi, 2018). As the

mobile station moves, the signal is obtained mobile

station has decreased. This decrease caused of the

distance accreation and obstacle around the base

station to the mobile station. Large signal decrement

in this study is modeled by propagation model Cost

231 Walfisch-Ikegami.

Figure 1: Network model

Received signal strength by mobile station

initiated for soft handover algorithm. Performance of

soft handover consisting of drop call rate, radio link

increase rate, active set average size and handover

rate. Then, soft handover performance will be

observed to the change of radio wave propagation

parameter, ie : building height, street width, and

distance between building.

Walfisch Ikegami COST231 restricted to :

a. Frequency (f

) : 800MHz-2000MHz

b. High antenna BS (h

) : 4 m - 50 m

c. High MS ( h

) : 1 m - 3 m

d. Distance BS and MS (d) : 0.02 km - 5 km.

The COST231 WI model is a suitable model used

for predict unfortunate- loss trajectory in the area city.

This model applied for area where transmitter no

visible on directly by receiver caused the number

object barrier in between transmitter and receiver as

seen on Figure 2 (Maksum Pinem, 2018).

Figure 2: Illustration COST231 models Walfisch -Ikegami

There are four factors that are included in

calculation of path loss for this model , ie (COST

Action 231, 1999) :

a. High building ( h )

b. Wide street ( w )

c. Distance between building ( b )

d. Orientation related street with LOS path (φ) .

This model distinguish between propagation of

LOS and non-LOS. For propagation of LOS, this

model use Equation 1 .

𝐿



 42,6  26 log



𝑑



 20 log



𝑓





for d  20 meter (1)

For non-LOS propagation , this model use Equation

𝐿



 42,6  26 log



𝑑



 20 log



𝑓





(2)

where L FSPL is loss room free (free space loss), L

rts is losses resulting by diffraction " rooftop to street

" and L msd is loss estimated effect existence

influence diffraction from the number object barrier

between base station and The nearest building with

mobile station.

The Walfisch-Ikegami COST231 model has be

accepted by body standardization international ITU-

R and could applied for high antenna BS above

rooftop . Mean error allowed is of ± 3 dB and standard

deviation of 4 - 8 dB (Nining Triana, 2015).

3 METHOD

Implementation of this research is done with literature

study, propagation parameter verification Cost231

Walfisch-Ikegami, designing signal transition

generating virtual base station, system model design

virtual communication, Application of soft handoff

algorithm hysteresis threshold for two base station,

determining simulation parameter input data, design

of simulation coding (programming) on overall,

testing the simulation by varying the observed

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

244

variables from radio wave propagation model and

analyze the simulation result. The block diagram of

the system shown at Figure 3.

Figure 3: Design of System Model

The parameters used in the simulation are shown

on Table 1. The program simulation in this study uses

MATLAB software and data of research results

obtained based on the data results of running

simulation program that runs repeatedly.

Furthermore, the analysis is done by statistical

methods to see the relationship between input

parameters with system performance parameters

using Microsoft Excel.

Table 1: Simulation Parameters

4. RESULT AND DISCUSSION

Performance analyzed in this study is based on

building height, street width, distance between

building and orientation streets that affect

performance drop cal rate, radio link increase rate,

active set avarage rate and handover rate

3.1 Effect of Building Height on Soft

Handover Performance

The relationship between the height increase of the

building on the rate of decreasing the radio link, the

Drop Call rate and the average of the active size is

presented in Table 2.

Table 2: Influence of Building Height on Soft Handover

Performance

It can be observed that with the increasing height of

the building the decrease of Radio Link is higher,

since the height of the building blocks the signal from

BS, as shown at Figure 4. This will impact the

weakening of the signal received by MS. So when the

height of the building is at 29 meters then began to

occur drop call. Drop call more frequent when the

height of the building is set 30 meters. Conversely,

when viewed from the parameter set active, the

increase in the height of the building impact on the

reduction of the number of active sets that serve the

MS.

Figure 4: Link Degradation Rate

3.2 Effect of Street Width on Soft

Handover Performance

The relationship between the increase of the street

width against of the radio link degradation rate, the

Drop Call rate and the average of the active size are

presented in Table 3.

Parameter Analysis of Semi Deterministic Pathloss against Soft Handover Performance in Mobile Communication

245

Table 3: Effect of Street Width on Soft Handover

Performance

It can be observed that with increasing street width

the decrease of Radio Link is lower, meaning the

signal is better because the increase of street width

gives an increase spaciousness and flexibility of

propagation of BS signal emission. This certainly

reduces the signal attenuation that reaches and

received in MS. So when the width of the street is set

at 20 meters then the radio link is in the best

condition, where at this distance there is no drop call

at all, as shown at Figure 5. Therefore, when viewed

from the active set parameter, the increase in the

width of the street has an impact on increasing the

number of active sets that serve the MS.

Figure 5: Drop Call Rate

3.3 Effect of Distance between Building

on Soft Handover Performance

The next observation is the relationship between the

increase of distance between buildings on the rate of

decrease of radio link, Drop Call rate and the average

of active size shown in Table 4.

Table 4: Effect of Distance between Building on Soft

Handover Performance

It can be observed that with increasing width of the

distance between buildings, decrease of Radio Link is

also lower. This means that the increase in signal

strength is better because of the reduced signal barrier

so that the increased freedom of propagation of the

BS signal emission. This of course also affects the

reduction of attenuation signals that reach and receive

in MS. So when the distance between buildings set to

8 to 20 meters then the radio link is in the best

condition of all, where there is no drop call at all.

Likewise, when observed from active set parameters,

the increase of distance between buildings also has an

effect on increasing the

average number of active sets

serving MS toward servant stability, as shown at

Figure 6.

Figure 6: Active Set Size Average

4 CONCLUSIONS

This study has successfully demonstrated the

relationship between semi-deterministic propagation

model parameters and the performance parameters of

soft handover in mobile communications. From the

simulation results obtained that the increase in height

of the building causes decreased radio links,

increased drop call rates and reduction of the average

number of active sets. Whereas on the contrary with

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

246

the width increase between buildings and street width

respectively causing the increase of radio link,

decrease of drop call rate and addition of active set

average amount.

ACKNOWLEDGMENT

This research was funded by Research Institute

University of North Sumatera under TALENTA grant

for Research Contract of Fiscal Year 2018.

REFERENCES

Aymen Zreikat and Milan Dordevic. (2017). Performance

Analysis of Path loss Prediction Models in Wireless

Mobile Networks in Different Propagation

Environments. Proceedings of the 3rd World Congress

on Electrical Engineering and Computer Systems and

Science (EECSS'17) Rome.

COST Action 231. (1999). Digital Mobile Radio Towards

Future Generation Systems – Final Report. European

Communities, Luxembourg.

M. Pinem and R. Fauzi. (2018). The effect of various

parameters of large scale radio propagation models on

improving performance mobile communications. IOP

Conf. Ser. Mater. Sci. Eng., vol.309, no. 135, p. IOP

Publishing.

Maksum Pinem. (2014). Optimization of Performance

parameter of CDMA System by Using Empirical

Radio Wave Propagation Channel. Disertation,

University of North Sumatera.

Maksum Pinem, et al. (2018). Characterization of Outdoor

to Indoor Propagation in Urban Area by Using A

Combination of COST231 Walfisch-Ikegami and

COST231 Multiwall Models in 1800 Mhz and 2100

Mhz. International Journal of Engineering &

Technologi (IJET), Vol 7, No 3.2, pp.: 698-702.

Nining Triana. (2015). Analysis of Semi-Deterministic

Path Loss Propagation Model For Triple Band

Applications in Metropolitan Area. Singuda Ensikom

Journal Department of Electrical Engineering.

University of North Sumatera.

O.O. Oni and F.E. Idachaba. (2017). Review of Selected

Wireless System Path loss Prediction Models and its

Adaptation to Indoor Propagation Environments.

Proceedings of the International Multi Conference of

Engineers and Computer Scientists, Vol II. Hongkong

Another reference.

Singh, N. P and Singh, B. (2010). Performance

Enhancement of Cellular Network Using Adaptive

Soft Handover Algorithm. Wireless Personal

Communications.

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