Comparison of two optimization techniques for channel assignment in cellular radio network

Abstract

The channel assignment problem has become increasingly important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal assignment problem of channels has become increasingly important. Two optimization methods, the neural networks and the genetic algorithms are applied to the channel assignment problem. To avoid falling into the local minima in the neural networks, certain techniques such as forced assignment and changing the cell list order, are used. In the genetic algorithms approach, the proper genetic operators are developed. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. As simulation results, the average iteration (or generation) numbers, the convergence rates and the CPU times according to the various techniques for the two approaches are presented and compared.