A selective location update strategy for PCS users

A new location update strategy for personal communication services (PCS) networks and its implementation using a genetic algorithm are proposed. Most of the practical cellular mobile systems partition a geographical region into location areas (LAs) and users are made to update on entering a new LA. The main drawback of this scheme is that it does not consider the individual user mobility and call arrival patterns. Combining these factors with the LA-based approach, we propose an optimal update strategy which determines whether or not a user should update in each LA, and minimizes the average location management cost derived from a user-specific mobility model and call generation pattern. The location management cost optimization problem is also elegantly solved using a genetic algorithm. Detailed simulation experiments are conducted to capture the effects of mobility and call-arrival patterns on the location update strategy. The conclusion from this work is that skipping location updates in certain LAs leads to the minimization of the overall location management cost for a user with a specific mobility pattern and even with moderately high call arrival rate.