MAP BASED INTRA-CELL METHOD FOR LOCATION PREDICTION OVER UMTS NETWORK PLATFORM | ||||
| JES. Journal of Engineering Sciences | ||||
| Article 10, Volume 39, No 5, September and October 2011, Page 1069-1094 PDF (504.13 K) | ||||
| Document Type: Research Paper | ||||
| DOI: 10.21608/jesaun.2011.129386 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Mohammed Abo-Zahhad1; Sabah M. Ahmed2; M. Mourad2 | ||||
| 1Electrical and Electronics Department, Faculty of Engineering, Assiut University, Egypt | ||||
| 2Electrical and Electronics Eng. Department, Faculty of Engineering, Assiut University, Assiut, Egypt | ||||
| Abstract | ||||
| Location based services (LBS) and their applications are regarded as the most growing services applied on communication systems. According to the great enhancement in the mobile network platform and its related database servers, we are not only able to develop LBS applications but also to enhance the performance of mobile networks. Future location prediction of mobile user results in great enhancement in LBS applications and mobile network performance. Many researches were introduced to predict location of mobile user. In [7] User Mobility Pattern (UMP) algorithm based on sequential mining prediction has been developed to deal with future location prediction in mobile networks. The main limitations of this pattern are: map based intra cell prediction cannot be extracted and the timestamps aren't associated with rules. In [8], another method has been introduced using All frequent Movement Pattern (ALLMOP) algorithm for extracting all frequent movement patterns within movement Rule based Location Prediction method (RLP). RLP method works on GPS network map based platform without manipulating cell to cell movement. So, it can't be used to enhance mobile network's resource allocation and mobility management. In this paper we proposed a new method, Intra Cell Movement Prediction (ICMP), for mobile user's future location prediction on Universal Mobile Telecommunication System (UMTS) environments to benefit from both intra and inter cell based techniques for both network and services enhancement. The proposed method depends on map based intra-cell prediction and utilizes the network database and positioning techniques in extracting user trajectories and movement rules. As a result, the user position can be predicted for the next movement step. The performance of the proposed algorithm is evaluated through computer simulation and compared with that of [7] and [8]. The simulation results indicate that the proposed method is highly efficient for both network and services' improvements as it is used to enhance location based services with satisfactory accuracy, network's resource utilization, reduce the latency in accessing resources and mobility management. | ||||
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