Genetic inspired channel assignment schemes for cellular systems

Channel allocation schemes in a cellular network can be modeled as combinatorial optimization problems. Genetic algorithms (GAs) have been shown to be effective and robust tools in providing adequate solutions of such problems. This paper investigates the application of GAs to two common assignment strategies from the field of cellular communications: the dynamic (DCA) and the borrowing channel assignment (BCA). In both schemes, channel allocation is formulated as a discrete energy minimization problem and can be put in proper genetic representation. A computer simulation model examines the performance of the proposed GA-DCA and GA-BCA schemes for uniform and non-uniform traffic distributions under the effect of cochannel and adjacent channel interference constraints.