Personalized Location Area Design with Genetic Algorithm for Future PCS Networks

In Personal Communication Services (PCS) networks, mobile terminals (MT) are communicating frequently using variety of services. The increasing demands for diverse services dictate a high-quality framework for location management. To accomplish this objective, it is necessary to track MTs roving in the system within the time limit to deliver the services in timely manner. The expected reduction of the cell sizes due to transmission power concerns and for better frequency reuse in future PCS networks, and increasing speeds of MTs on the other hand, would cause a considerable signaling in the always updating (AU) strategy adopted in current PCS networks. Personalized location area (PLA) is an efficient way to reduce the location management cost by considering both the movement behavior of the individual users in the networks system and the system parameters. However, the PLA design problem is found to be NP-complete with high computation complexity. In this paper, we try to solve the problem by using the genetic algorithm (GA). Simulation results show that the location management cost of the designed PLAs by GA is significantly lower than that of the AU mechanism.