location management cost strategies in cellular networks · rizal munadi,mahamod ismail,mardina...

Location Management Cost Strategies in Cellular Networks

Rizal Munadi

Electrical Engineering Department, Engineering

Faculty

Syiah Kuala University

[email protected]

Mahamod Ismail, Mardina Abdullah, Norbahiah

Misran

Electrical, Electronics and System Department -

Engineering Faculty

Universiti Kebangsaan Malaysia

{mahamod, mardina, bahiah} @vlsi.eng.ukm.my

Abstract-The growth of cellular users using to

communicate at any place and any time increases the

signaling activities among the cellular networks. To

reduce the network costs and better usage of radio

resources, an efficient location management scheme:

location updating and paging strategies are essential to

improve the network performance. This paper presents

a mixed location management strategy that combines

some strategies of location update and paging schemes

to minimize the overall cost. Simulation results

indicates that the location management performance of

using larger memory system, shows better result in

reducing the location management costs.

Keyword: Location Management, Cellular user,

Location Update, Paging, Cost

1. Introduction

The growth of cellular users and the intense of

communication activities will increase signaling traffic

in which the available spectrum for radio resources is

limited. Increasing the number of active users in service

area have influenced the grade of service of the

network, which is dependent on the size of the cell

employed. On the other hand, increasing the user

mobilities will increase uncertainty of user locations in

a network with respect to the size of the cell employed.

Increased signaling incurs additional cost to operators

by consuming network resources that effected to

revenue-generating traffic.

The cost of mobility tracking depends primarily on

the costs of location update (LU) and paging.

Intuitively, the location accuracy depends in the LU

frequency. The more frequent the LU, the more

accurate the location information of cellular user . In

other word, this frequent LU activity will increase the

cost of signaling and on the other hand the paging cost

may decrease. If the cellular user performs the lower

LU activities, it will increase the task of the system to

page cellular user when it delivers the incoming call.

This situation will decrease the LU cost but increase the

paging cost. This cost problem is the main interest of

this study and a mixed strategy using a combination of

different LU and paging schemes is implemented to

obtain the minimal signaling cost.

The rest of the paper is organized as follows. In

Section 2, the concept of location management is briefly

introduced and followed the review of the current

research in this area. In Section 3, the procedure for

mixed strategy LU and paging schemes developed is

described. Section 4 gives the simulation results and

finally Section 5 concluded the paper.

2. Location Management Concepts and

Review of Previous Works

In order to provide fast and smooth mobile services

to users, Location Management (LM) becomes a

primary issue in cellular communication system. The

location management system resides in Mobile

Switching Center (MSC) that contains two databases to

facilitate the tracking of cellular user: Home Location

Register (HLR) and Visitor Location Register (VLR).

The HLR contains the user permanent data (e.g.,

directory number, profile information, current location,

and validation period) of the cellular user whose

primary subscription is within the area. The VLR is

associated with an MSC in the networks. The VLR

retrieve information for handling calls to or from a

visiting cellular user.

Location management is concerned with the

procedures required to enable the network to maintain

location information for each active cellular user and to

efficiently handle the establishment of incoming calls.

There are two basic procedures in LM: LU and Paging.

These two-stage process in LM enables the network to

discover the current attachment point of the mobile user

for call delivery [1]. LU is initiated by the mobile

terminal, and informed the network of the subscriber’s

current location. The network initiates paging when an

incoming call arrives. It means that the paging process

always performs after the completion of the LU

transaction. Paging messages are broadcast in one or

more paging areas, contained within the current

location, and inform the target user of the incoming call.

Rizal Munadi,Mahamod Ismail,Mardina Abdullah,Norbahiah Misran, Int. J. Comp. Tech. Appl., Vol 2 (1), 188-192

188

ISSN : 2229-6093

mailto:mahamod%[email protected]

There are two tracking strategies to maintain user

location, static and dynamic strategy. Static strategy is

defined that the network decides when and where the

mobile user or mobile terminal should report to the

network of their location, and in dynamic strategy the

cellular user informed the network of its location when

and where it could be. The cellular user transmits

update message according to their movement and not in

predetermined cells. The location tracking strategy

currently used by most PCS is fixed paging area

strategy [2, 3]. In this strategy, all cells of the network

are partitioned into service area that called registration

areas (RA) or location area (LA). A cellular user in this

system is required to update its new location when it

entered to a new LA. Whenever a call arrives, the exact

location of the called is queried by paging all cells of

the LA the active cellular user lastly updated. Designing

appropriate LAs could reduce the location tracking cost

of the PCS effectively [4]. Although the fixed paging

area (PA) strategy could be easily implemented but the

drawback it could not reach the optimal location

tracking cost since the PA defined in this approach may

be large (for low mobility mobiles) or small (for high

mobility mobiles) to make unnecessary updates. There

should be a complicated work in designing the optimal

paging size.

In the last few years some strategies have been

proposed related to LU and paging. For LU, the

proposed strategies that frequently appear in literatures

can be summed up into time-based [5], movement-

based [6], distance-based [7] and zone-based scheme [8,

9].

In the time-based strategy, the cellular user

updates its location periodically every certain time

interval as a threshold. In the distance-based update

strategy, a cellular user updates its location whenever

the distance between the current cell and the last

registered cell exceeds a predefined threshold value. In

the movement-based update strategy, a cellular user

updates its location if the number of cells it has traveled

since the last LU exceeds a pre-defined threshold value.

Finally, in zone-based strategy, the entire cellular

network is partitioned into LA and the user updates

whenever a LA boundary is crossed. In case of an

incoming call, the current LA of the user (where the last

updated) is paged.

Another scheme, Profile Based Strategy (PBS) was

proposed in [10] and [11] as a technique to reduce the

cost of LU. In the PBS, the system maintains a record of

each user’s most likely itinerary. This technique

considers that the user location is known in advance.

A number of authors have proposed paging

strategies. In [12], a sequential paging strategy has

investigated with given an assumed probability

distribution on the user location. In this strategy, when

there is an incoming call to a target cellular user, the

PAs are sequentially paged for the cellular user

following a pre-defined paging strategy, which defines

the order for paging the PAs. To improve the

probability of finding the cellular user and reduce the

paging cost, in [13], based on the velocity and direction

information of a cellular user, the system estimates the

most possible cell that the cellular user is residing.

It is difficult to compare various mobility

management strategies since as yet there exist no

absolute bounds on optimum performance can be

applied to any procedure regardless of assumptions

about mobility, network structure, and the like [14]. On

the other hand, it has been shown that the distance-

based LU with sequential paging would be the most

efficient strategy in the case of saving radio resource

and reducing the network signaling [2]. Among various

method in LU and paging schemes, in this paper a

combination of distance and zone-based method is

analyzed to achieve the minimal cost.

3. Mixed LU and Paging Schemes

The distance-based LU [15, 16] was selected among

the schemes in this work. The basic idea of this

algorithm is as follows. Each cell having a base station

and having its own id (identifier), with cellular user

resides in each cell for some time interval before

moving on the next cell. It is assumed that when cellular

user leaves a cell, there is an equal probability that any

one of the immediate neighboring cells is selected as the

destination. The distance-based scheme is determined

by measuring the cell-to-cell distance. The updating

cost will be processed only if the information about the

cell is changed or in another word the cellular user

moves to a different cell. For paging, a cluster of seven

cells called PA is defined. When the cellular user moves

to another cell, the system will check whether the new

cell belongs to the same PA profile or not.

The mixed strategy LU and paging scheme to reduce

the cost of signaling is described as follows:

A. Location update procedures

Four different LU strategies are proposed and

implemented in this paper. There are 49 cells. Denoting

the base station in every cell as BS1 up to BS49 and

suppose that the initial location of the cellular user is in

cell 1, the system will register the cellular user as BS1

data. Every time cellular user moves to a different cell,

the system will count as a cost. Figure 1 shows a sketch

of a sample path, showing cellular user travels from cell

47 38 6 5 4 1. The strategies are as follows:

1. If the current cell id (n) is different to (n-1) the cost

is LUA. This strategy is similar to Lin [17] and

Abutaleb [18].

2. If the current cell id (n) is different to (n-1) and

(n+1), the cost is LUB.

3. If the current cell id (n) is different to (n-1) and (n-

2), the cost is LUC.

4. If the system can record larger data set for each user

state (ni), where i = 1 to m and m is the maximum of


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length of the data set. The difference in cell id in the

data set gives the cost, LUD.

Figure 1. Cellular coverage using 49 cells

B. Paging procedures

For paging scheme, an analysis using single PA and

zone-based strategy are employed in this work. In zone-

based, the system is divided into equal size (weight)

area, among MSCs to keep the network overhead

minimal. For this purpose, seven symmetrically PAs of

equal size, in which each cluster consists of seven cells

is defined, as shown in Table 1. The paging schemes

will process any incoming signal by identifying the cell

id of each active cellular user. The system will count as

a cost if the current cell id is different to the previous

one. The mechanisms are as follow:

1. Based on zone area, the system will check whether

cellular user belongs to a certain PA. If it is

different, the system will count as a paging cost,

PgA.

2. The system will detect individually to the paged

cellular user in a single cell, the paging cost PgB.

3. Based on the zone concept, but assuming the system

can store previous information and detect if cellular

user stays in different PA, the paging cost is PgC.

Table 1. Symmetrical Cell Clustering

Cell Cluster Cell Number

1 1, 2, 3, 4, 5, 6, 7

2 8, 9, 10, 11, 12, 13, 14

3 15, 16, 17, 18, 19, 20, 21

4 22, 23, 24, 25, 26, 27, 28

5 29, 30, 31, 32, 33, 34, 35

6 36, 37, 38, 39, 40, 41, 42

7 43, 44, 45, 46, 47, 48, 49

4. Results

The simulation generates a hundred cellular users

randomly with starting at different points. Eight

possible directions of cellular user positions are

implemented in the simulation and cellular user

movement depends on system processing as shown in

Figure 2. Each position of the cellular user has been

investigated using the strategies described in Section 3.

Figure 2. Mobile Terminal Activities

4.1. Location update performance

Four different LU strategies as describe in Section 3

are investigated and compared. The performance of

these strategies is analyzed to obtain the lower signaling

activities using the cumulative distribution function

(cdf) as shown in Figure 3. The LU abbreviation

followed by alphabet A, B, C, and D respectively are

the initial of each LU strategy. With LU_A as the

benchmark, the results show that LU_D is superior with

respect to LU_B and to LU_C in this order, with each

cdf values of 76%, 52%, and 30% respectively.

Figure 3. Location Update Performance

4.2. Paging performance

As mentioned in Section 3, only three procedures in

Paging strategy are evaluated in this simulation. Figure

4 shows cdf of the average number of paging for the

three paging strategies described. The result shows that

using only a single cell will waste the network resources

and increase the paging cost. With this single cell

paging strategy, PG_A as the benchmark, the cdf for

PG_C is 93% and the cdf for PG_B is 65%. PG_C is

shown to be superior to PG_B and PG_A respectively.


190

Figure 4. Paging Performance

4.3. Mixed LU-Paging performance

From the LU and paging strategies that have been

investigated in the previous section, twelve possible

combinations can be employed for the mixed LU-

paging strategies. Figure 5 shows performance of this

scheme, where each LU and Paging combination is

mixed as pair in term of signaling activities. As shown

in this figure, the PG_A and LU_A pair is the worst pair

and the PG_C and LU_D is the best pair in terms of

paging and updating cost reductions.

Figure 5. A Mixed LU and Paging Signaling

Activities

Another way to examine the performance of the

mixed LU-paging strategy is by looking at the cdf plot

as shown in Figure 6. For simplicity, only the best four

combined strategies as given in Table 2 are plotted and

evaluated, these are:

Table 2. Strategy for Mixed LU-Paging pair

Strategy Mixed LU-paging pair

A LU_D and PG_C

B LU_B and PG_C

C LU_D and PG_B

D LU_C and PG_C.

With strategy D as the benchmark, the cdf of strategy A,

B, and C are 84%, 33%, and 32% respectively. Again,

the result shows that the mixed strategy A is superior to

others that will give the lower signaling activities and

the best choice to implement.

Figure 6. Mixed LU-Paging Strategies

Performance

5. Conclusion

In this paper, we have studied a practical mixed

strategy of LU and Paging. The cost function of the

analysis is counted as a number of signaling activities in

LU and paging strategies in cumulative distribution

function. Simulation results showed the performance of

LU case: Strategy LU_D gives superior performance

(76%) with respect to the other three (LU_B, LU_C and

LU_A) respectively. In the Paging case: Strategy PG_C

gives the best result (93%) with respect to Paging

strategy PG_A and PG_B. Both of these LU and Paging

strategy employed larger data set. The strength of these

strategies is that it minimizes the cost of calculating the

redundant data. The mixed strategy results show that

strategy A, a combination of LU_D and PG_C, give the

lower signaling activities with cumulative distribution

function (cdf) value of 84 % with respect to the worst

case combination of strategy D.

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location management cost strategies in cellular networks · rizal munadi,mahamod ismail,mardina...

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