Local Call Admission Policies for Cellular Networks Using Genetic Algorithms

It is well known that if a stochastic service system (such as a cellular network) is shared by users with different characteristics (such as differing handoff rates or call holding times), the overall system performance can be improved by denial of service requests even when the excess capacity exists. Such selective denial of service based on system state is defined as call admission. A recent paper suggested the use of Genetic Algorithms to find near-optimal call admission policies for cellular networks. In this paper, we define local call admission policies that make admission decisions based on partial state information. We search for the best local call admission policies for one dimensional cellular networks using Genetic Algorithms and show that the performance of the best local policies is comparable to optima for small systems. We also test our algorithm on larger systems and show that the local policies found outperform the maximum packing and best handoff reservation policie..