MAP BASED INTRA-CELL METHOD FOR LOCATION PREDICTION OVER UMTS NETWORK PLATFORM

Abstract

Location based services (LBS) and their applications are regarded as the mostgrowing services applied on communication systems. According to the greatenhancement in the mobile network platform and its related database servers,we are not only able to develop LBS applications but also to enhance theperformance of mobile networks. Future location prediction of mobile userresults in great enhancement in LBS applications and mobile networkperformance. Many researches were introduced to predict location of mobileuser. In [7] User Mobility Pattern (UMP) algorithm based on sequentialmining prediction has been developed to deal with future location prediction inmobile networks. The main limitations of this pattern are: map based intra cellprediction cannot be extracted and the timestamps aren't associated with rules.In [8], another method has been introduced using All frequent MovementPattern (ALLMOP) algorithm for extracting all frequent movement patternswithin movement Rule based Location Prediction method (RLP). RLP methodworks on GPS network map based platform without manipulating cell to cellmovement. So, it can't be used to enhance mobile network's resource allocationand mobility management. In this paper we proposed a new method, Intra CellMovement Prediction (ICMP), for mobile user's future location prediction onUniversal Mobile Telecommunication System (UMTS) environments to benefitfrom both intra and inter cell based techniques for both network and servicesenhancement. The proposed method depends on map based intra-cellprediction and utilizes the network database and positioning techniques inextracting user trajectories and movement rules. As a result, the user positioncan be predicted for the next movement step. The performance of the proposedalgorithm is evaluated through computer simulation and compared with that of[7] and [8]. The simulation results indicate that the proposed method is highlyefficient for both network and services' improvements as it is used to enhancelocation based services with satisfactory accuracy, network's resourceutilization, reduce the latency in accessing resources and mobilitymanagement.