This regular paper was presented as part of the main technical program at IFIP WMNC'2011

978-1-4577-1193-0/11/$26.00 ©2011 IEEE

Abstract— B3G or 4G systems present different Radio Access

Technologies (RAT). These networks are interconnected to

improve spectral efficiency, extend service ranges and provide

seamless mobility for multi-RAT mobile users. The seamless

mobility refers to the network capability of providing continuous

services when a mobile user is crossing different RATs.

Heterogeneous networks will be seamlessly integrated in one

“common” access network, enabling users’ mobility with

continuous services. This paper analyzes the performance of a

new solution of radio resource management for vertical handover

UMTS /WiMAX. Our solution is based on load balancing

strategy The proposed policy is based on a decision criterion

related to call service quality in order to calculate a load factor.

The performance analysis, compared to existing approaches for

such VHO vision, show that our proposed solution presents lower

packet loss rate, lower handover latency and a reduced call

blocking probability.

Index Terms— Heterogeneous networks, UMTS, WiMAX,

vertical handover, Load Balancing, load factor.

I.INTRODUCTION

The recent evolutions in telecommunications have been

influenced by the crescent need of users to access their

subscribed services in mobile environments. This demand has

determined two complementary research axes in this area.

First, multi mode terminals have been developed being able to

access different network technologies, such as Universal

Mobile Telecommunication System (UMTS) and World

Interoperability for Microwave Access (WiMAX). On the

other hand, the interoperability between different access

networks has been triggered to seamlessly call change from

one interface to another.

Both access technologies, WiMAX and UMTS are considered

complementary to each other. UMTS offers a broad coverage

but with lower rates compared to WiMAX offered rates within

a relative limited geographical coverage.

Considering UMTS and WiMAX interoperability, this paper

analysis the performance of a new proposed radio resources

management strategy that we compared to the Mtend strategy

proposed in [4]. Our new approach is based on load balancing

policy between these two networks.

In the next section, we present the vertical handover and its

different phases. The section three details some related works

like the Mtend strategy. The section four describes our

proposed policy for radio resource management for vertical

handover UMTS WiMAX based on the load balancing. The

section five presents the simulation scenario used to analyze

and compare the performance of our proposed algorithm with

the Mtend strategy. The section six analysis in detail the

simulation results. Finally, last one concludes the present work

and depicts our future work.

II.VERTICAL HANDOVER

The principal challenge of heterogeneous radio access

technologies is to provide a highly mobility process to mobile

subscribers anywhere and anytime. To insure seamless

mobility across these heterogeneous technologies, Vertical

Handover algorithms have been developed. Such mechanism

occurs to provide connection switching from one access

network to another, for example from WIFI or WiMAX

networks to a cellular network. Vertical handover procedure

[1-3] encompasses three main phases: system discovery phase,

the decision phase and handover execution phase.

1. System discovery phase

During this phase, the mobile terminal determines which

networks can be used and what services are available in each

one. Measurements are made for certain parameters in order to

analyze the status of the existing connection between the

terminal and the serving cell and the quality status of neighbor

cells.

All these measurements are collected in a measurement report

and sent to the handover decision entity.

1. 2. Decision phase

Depending on the measurement report, the mobile determines

if the connections should continue using the existing network

selected or connect to another network.

The handover decision may come from a decision entity of the

terminal (user controlled terminal) or the network decision

entity (user-controlled network).

3. Handover execution phase

During this phase, the connections are routed from the existing

network to another one in a transparent manner. In UMTS, the

handover execution is made by the network, while in the

802.16e network; the handover is made by the mobile

terminal.

III.RELATED WORK

The majority of researches are interested to the ability to

integrate wireless terrestrial networks such as WLAN

(Wireless Local Area Network) and 3G networks in order to

share services. This integration raises many problems because

each network has different features such as bandwidth,

Load Balancing Policy for Vertical handover between

3G/WiMAX

Ben Hassine Rym, Mériem Afif

Mediatron, Ecole Supérieure des Communications de Tunis (Sup'Com), Route Raoued, Km3.5, 2083

Cité El Ghazala – TUNISIA. Carthage University Email: benhassinerima@gmail.com , Mariem.afif@supcom.rnu.tn

technology access, coverage area, power, standard, etc... One

of these problems is about the implementation of a seamless

handover without data loosing. These different researches

offer today a set of solutions that contribute to the

technologies convergence evolution by improving various

aspects of vertical handover. Among these solutions, we quote

the Mtend solution proposed in [4]. This solution aims to

maximize radio resources, while satisfying the QoS

requirements posed by the applications.

Fig.1 represents the decision algorithm used for the joint

management of interconnected UMTS and WLAN radio

resources controlled by the same

operator.

Fig. 1.Joint multi-Radio resource management algorithm for Mtend

When a new requested call arrives, the algorithm decides to

which interface should be directed, based on the required QoS

and available resources available.

If both networks have available resources, the strategy is

based on the users Mobility Tendency, differentiating

applications according to their mobility tendency.

In scenarios of insufficient resources, this strategy proposes

two complementary mechanisms. The first one consists of

renegotiating the new call requested resources. The second

mechanism considers the possibility of reallocating an

accepted call from one network to the other.

The selected network interface to serve the new call is chosen

according to Eq. (1), where tend represents the decision

tendency.

(1)

PU M T S and PW LAN are the eligibility degrees given to an

arriving session, respectively to be transported over the UMTS

and WLAN interfaces. The 1 aU M T S and 1BwW LAN variables

are, respectively, the available UMTS load factor and the

available bandwidth over WLAN interface.

Thus, the Mtend strategy gives priority to mobile applications

in the UMTS network, in order to avoid vertical handoffs

between different network technologies. Applications usually

used in static contexts (e.g., web browsing and video

streaming) are served by a WLAN network.

IV.AN INTER-RAT LOAD BALANCING PROPOSED SOLUTION

Our solution addresses the problem of mobile networks

heterogeneity and seems to solve some problems of the

vertical handover by proposing a new Load Balancing

mechanism between the two technologies UMTS and

WiMAX.

The main objectives of our solution are:

Offer best radio resources management in UMTS and

WiMAX networks.

Minimize the handover latency between UMTS and

WiMAX.

Minimize the Call Blocking Probability (CBP).

Minimize the Packet loss Ratio during the handover

UMTS/WiMAX.

The proposed mechanism is based primarily on the incoming

call priority. Generally, we consider that real time applications

such as video applications, video conference… have the

highest priority in the UMTS network.

Our solution allows also calculating a new load factor LF for

each network (LFUMTS and LFWiMAX). This factor depends on

other network characteristics such as the available bandwidth

in each network, the calls percentage, accepted in a network,

reserved resources for each type of traffic, the number of

traffic in each network...

The new load factor LF is calculated as it is given by Eq (2):

LFservice=Dnetw-(Nbcall*DTrf) (2)

Where:

Dnetw=(Dservice*Rnetw)/100 (3)

Dservice: Theoretical flow of each network UMTS or WiMAX.

Nbcall: Call number for one type of traffic.

DTrf : Flow required by each traffic.

Dnetw: Allocated flow by a network for one type of traffic.

Rnetw : Percentage of resources reserved by a network for a

traffic.

According to this factor values, our algorithm selects the

network to serve the incoming calls. If this factor takes a

negative value, it means that the available resources in this

network are not sufficient to transmit the traffic and, at this

time, this traffic will be switched to the other network. The

same steps must be done on the other network.

This load balancing policy optimizes the use of available

resources in each network to enhance the quality of service of

the applications in progress.

To succeed our approach, we consider other QoS parameters

to evaluate our solution such as the call blocking probability

CBP and the signal to noise and interference ratio SINR

(Signal to Interference and Noise Ratio). These two

parameters can evaluate the QoS of the established connection

between mobile and the network.

The SINR parameter represents the quality of the link between

a base station and a mobile. The Call blocking probability

CBP, given by eq (4), represents the probability that a new call

will be rejected due to insufficient available resources in a

network. To guaranty a better quality of service, the CBP

probability must be reduced [5].

(4)

Cacept : Accepted calls number

Coff : Total number of calls offered to the system

The Fig.2 represents the decision algorithm structure used to

perform a load balancing for the UMTS/WiMAX vertical

handover.

Fig. 2 Inter-RAT load-balancing based QoS Algorithm

As is mentioned by the flow chart given by figure 2, our

proposed mechanism “Inter-RAT load-balancing” takes several

steps as below:

Step 1: Calculating the Call blocking probability CBP

2. If CBP varies between 0 and 1 (0<=CBP<1) this means

that this call is in progress.

3. If CBP=1, this means that Cacept=0 and the call is

terminated.

Step 2: Calculating the load factor LF and SINR

When the CBP varies between 0 and 1, our algorithm proceeds

to the next step to calculate the load factor and the SINR

parameter.

If the load factor LF is null (=0) or positive and the SINR is

above a fixed SINR threshold fixed for each service type, the

call is accepted. Otherwise, the considered call will switch

automatically to the other available network.

Step 3: The load balancing

At this step, some traffic will be switched to the other network

according to it’s the available resources.

! Adopted Architecture

Another important issue for seamless mobility is the used

interconnection architecture and the considered coupling

scenario.

Our solution is based on the “Tight coupling” architecture. In

this case, the coupling is achieved by the SGSN (Serving

GPRS Support Node) node. Fig.3 shows our adopted

architecture.

Fig.3. Adopted Architecture

V.PERFORMANCE ANALYSIS

A. Simulated Scenario

In order to demonstrate and evaluate the Inter-RAT load-

balancing strategy proposed in our work, we used Network

Simulator [6] patched with UMTS patch and WiMAX NIST

patch [7].We consider d a simulation scenario composed by 20

mobile nodes with different type of traffic. Each MN is multi

homed and is attached to an SCTP agent. Its primary interface,

MN_if0, is associated to the UMTS network and the

secondary interface, MN_if1, is associated to the WiMAX

network. The SGSN is also attached to an SCTP agent. Its

primary interface, Sgsn_if0, is connected to the RNC (Radio

Network Controller) UMTS network node and its secondary

interface, Sgsn_if1, is connected to the WiMAX base station.

Fig.4 shows our simulated scenario for each mobile node MN.

Fig.4. Simulated scenario

To evaluate our solution, we use different types of traffic in

each network as: FTP, web, voice and video. The Table.1

represents the traffic flows that we considered in our

simulations.

Traffic type Required flow

FTP between 50kb/s and 120kb/s

Pareto between 500kb/s and 1000kb/s

Video between 800kb/s and 2Mb/s

Voice between 200kb/s and 500kb/s

Table.1 Flows of Simulated traffic

B. Simulation Results and interpretation

In this section we present and discuss the obtained simulated

results of our proposed solution that we compare to the Mtend

solution [4]. The objective is to compare the behavior of our

proposed policy, identified as inter-RAT Load Balancing and

the other solution as Mtend.

To analyze the performance of our solution, which mainly

introduces the concept of load balancing between the two

heterogeneous networks UMTS and WiMAX, we will propose

as performance criteria:

The packets loss rate.

The handover latency.

The load factor LF.

The Call Blocking Probability (CBP).

! The packets loss rate

The QoS at the application level is affected by the packet loss

during the handover. To calculate packet loss ratio, we the

following expression:

The curves given by Fig.5 (a) and (b) show respectively the

variations of packets loss rates in both UMTS and WiMAX

networks for FTP traffic using the « Load Balancing » and

« Mtend » solutions during 100s.

Fig.5 (a) Packets loss rates in UMTS network for FTP traffic using the

« Load Balancing » and « Mtend » solutions

Fig.5 (b) Packets loss rates in WiMAX network for FTP traffic using the

« Load Balancing » and « Mtend » solutions

Comparing Fig.5 (a) with fig.5 (b) we can deduce that the

packet loss rate is more important in the case of the Mtend

solution either for UMTS network or WiMAX network. With

this solution, the FTP traffic has an average packet loss rate of

0.16729 in the UMTS network and about 0.25263 in the

WiMAX network. However, these values are lower with our

proposed solutions that are about 0.13565 in the WiMAX

network and 0.096889 in UMTS one.

To better evaluate the performance of our approach, we

simulate another type of traffic which is the video traffic. This

traffic has a higher flow rate than FTP traffic.

Fig.6 (a) and fig.6 (b) show respectively the packets loss rates

variations in both UMTS and WiMAX networks for video

traffic using the « Load Balancing » and « Mtend » solutions

for a simulation time 100s.

Fig.6 (a) Packets loss rates in UMTS network for video traffic using the

« Load Balancing » and « Mtend » solutions

Fig.6 (b) Packets loss rates in UMTS network for video traffic using the

« Load Balancing » and « Mtend » solutions

For video traffic, the packet loss rates have an average value

equal to 0.21509 in UMTS network and to 0.41031 in

WiMAX network using the Mtend solution. Same to FTP

traffic, these values are better with our solution and they have

averages equal to 0.10284 in UMTS and to 0.17313 in

WiMAX network. All these statistics confirm that our solution

gives better results than those given by the "Mtend" solution

in terms of packet loss rates independent to traffic type or

network type. In all these curves, there are many peaks of loss

rates. These peaks represent the handover execution instant. In

addition, the number of dropped packets increases when

executing handover. We note in both figures 5 and 6 that

packet loss variation during UMTS/WiMAX handover is

slightly lower than obtained packet loss variation during

WiMAX/ UMTS handover, for both video and FTP traffic.

Our solution will be more beneficial in the UMTS-WiMAX

handover case because WiMAX has a greater bandwidth than

UMTS network.

! Handover Latency

The impact of handover on the offered quality of service by a

network is typically characterized by its latency. We define

handover latency parameter [8] as the time between the

moments when the mobile has received the last data packet

through the serving base station and when it receives the first

packet through the new base station (new radio link). So it is

the time interval during which a mobile node cannot receive or

send traffic. To evaluate this factor, we simulated a UMTS

network with 10 mobile nodes. Among these mobiles, there

are five which were accepted by UMTS and five who have

switched to WiMAX network. Fig.7 represents latencies

values of five handover executed in the UMTS network with

our solution "Load Balancing" LB and with the Mtend

solution.

Fig.7 Handover Latency in UMTS network using Load Balancing and Mtend solutions

This chart shows that with our solution, the handover latency

value is reduced for an average of 2120 ms against an average

of 3640 ms with the Mtend solution.

The first handover presented in the Fig.7 is executed by FTP

traffic. The difference between the handover latencies using

our solution and the Mtend solution is about 600ms. However,

the fourth handover is executed by a video traffic and has a

latency difference of 2500ms. These results show that the

handover latency is more important in the case of video traffic

for both solutions. However, they are more reduced with our

Load Balancing proposed policy.

The table.2 represents the latencies of two-way of handover

UMTS-WiMAX for four different traffic.

Traffic type UMTS-WiMAX

Handover latency (ms)

WiMAX-UMTS

Handover latency (ms)

FTP 1200 1800

Video 3800 5700

Voice 2300 3600

Web (Pareto) 1800 2200

Table.2 Handover latency for four different type of traffic in UMTS and

WiMAX networks

The handover delay values are higher in the case of UMTS-

WiMAX handover especially for the video traffic that can

reach up to 5700 ms. these latencies values increase with the

suggested services bandwidth and rates current applications.

! Load factor LF

As we described in the previous section, this factor is

calculated according to available resources in each networks.

Table 3 shows the values of this factor for four mobile nodes:

Mobile

number

Traffic

type

Communi

cations

number

UMTS

Load

Factor

WiMAX

Load

Factor

MN-

UMTS BS

distance

(m)

MN-

WiMAX

BS

distance

(m)

MN1 FTP 6 100 400 170 2600

MN2 web 4 200 800 2200 3500

MN3 voice 4 80 1000 3700 2000

MN4 video 6 -4000 100 300 2400

Tab.3 LF values for four type of simulated traffic in UMTS and WiMAX

networks

According to our strategy, a mobile node that has a negative

load factor must switch to another network even if it has not

left the coverage area of its serving network. We take as an

example; the mobile MN4 which has a video traffic with a

load factor equal to -4000. This mobile will switch from

UMTS to WiMAX because the available resources in UMTS

network that are reserved to this type of traffic is not

sufficient, although it has not left the coverage area of UMTS

and is fixed in our simulation to 3Km. All these results

approve the importance of the load balancing solution in the

UMTS-WiMAX vertical handover.

! The Call Blocking probability CBP

The CBP factor represents the probability that a new call can

be rejected due to insufficient available resources in the

network.

Fig.8 (a) and (b) show respectively the CBP variation in both

UMTS and WiMAX networks using our Load Balancing

solution and the Mtend solution.

Fig.8 (a) CBP variation in UMTS network using our Load Balancing and

Mtend solutions.

As shown by these two figures, the values of CBP are

reduced in the case of our solution and have an average equal

to 0.72 in WiMAX network and to 0.58 in the UMTS network.

However, this probability is higher in the UMTS network and

reaches up to 0.65 against 0.2 in WiMAX for the same number

of users.

Fig.8 (b) CBP variation in UMTS network using our Load Balancing and Mtend solutions.

VI.CONCLUSION

In this work we have proposed a new vertical handover

mechanism based on load balancing policy. We have

presented a performance analysis of two radio resource

management strategies for the UMTS/WiMAX vertical

handover. These analyses compare the behavior of the Mtend

strategy in this context, based on user mobility and

introducing two mechanisms for call renegotiation and call

reallocation, with a new policy that we named Inter-RAT

Load balancing strategy. Our proposed solution calculates a

new load factor LF parameter according to calls quality of

service features. Simulation results elaborated in this work

show that the Load Balancing strategy reduces effectively the

packet loss and the handover latency for each network and has

a performance which is globally better than the Mtend

strategy. We have also shown from these simulations that our

solution gives a better result in the case of UMTS-WiMAX

handover. For future works we propose to study this policy

with a context awareness mechanism in order to perform an

intelligent handover.

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