An Intelligent Paging Strategy Using Rule-Based AI Technique for Locating Mobile Terminals in Cellular Wireless Networks

This paper proposes an efficient rule-based paging strategy (RBPS) using a well-known concept of artificial intelligence, namely, rule base. The novelty of the scheme lies in devising ldquorulesrdquo that offer a potential mapping from seemingly disparate input data items (yet having some statistical relations) to an almost exact position of mobile terminals (MTs). Considering the conventional models of call arrival, cell residence, and mobility, we have developed a stochastic model to analyze the performance of the scheme. Interestingly, RBPS requires no additional processing at MTs and involves a nominal overhead at mobile switching centers. Simulation results reveal that RBPS significantly outperforms the blanket paging scheme adopted in global system for mobile (GSM) communications. In addition, results are very much encouraging when compared with the popular shortest-distance-first scheme. Finally, RBPS is generic enough to be potentially used in next-generation wireless networks, irrespective of any standards, with only minor adaptations to conform to the respective standards.