A Modified Immune Genetic Algorithm for Channel Assignment Problems in Cellular Radio Networks

In order to use the frequencies more efficiently, a modified immune genetic algorithm to solve the problem of channel assignment in cellular radio networks is presented. Three constraints were considered for the channel assignment: the co-channel constraint, the adjacent constraint and the co-site constraint. Our objective is to obtain a conflict-free channel assignment scheme among the cells, which satisfies both the electromagnetic compatibility (EMC) constraints and traffic demand requirements. The minimum-separation encoding scheme was introduced to meet the co-site constraint. The genetic operators(crossover and mutation) was proposed to ensure the traffic demand throughout the iterative process. In order to increase the efficiency and velocity of convergence, immune operators are given, such as immune clone, vaccination, immune selection etc. To void local optima, the elite strategy was used. Some well-known benchmark problems were simulated. The significant results indicate that the proposed algorithm is a better approach for solving the channel assignment problem.