Location Management Techniques in PCS Environment

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 with moderately
high call arrival rate.