Channel Allocation in Mobile Cellular System using Hybrid Genetic Algorithm and Simulated Annealing

Radio spectrum is limited resource in wireless mobile communication system. Cellular system has to serve the maximum possible number of users while the number of channels available is limited. An effective channel assignment technique is important to improve the system capacity while maintaining a desirable level of electromagnetic compatibility (EMC) constraint. Solution to dynamic channel allocation is NP-hard. Heuristic search techniques are widely used for solving such kind of problems. In this paper a hybrid technique of Genetic Algorithm and Simulated Annealing (HGASA) is applied for dynamic channel allocation. With this hybrid algorithm effort is made to reduce the search complexity of channel allocation while satisfying constraints of interference. Hybridization of two algorithms is done so that the advantages and disadvantages of both are compensated by each other. The concept of Simulated Annealing (SA) is incorporated into Genetic Algorithm (GA) in order to avoid pre-mature convergence of the strings. The simulation for non-uniform traffic distribution on a 64 cell network model can show that the average new incoming call blocking probability for the proposed hybrid channel optimization method is lower than the previous methods.