Heuristics for optimizing minimum interference channel allocation problem in cellular networks

Abstract

The channel allocation problem (CAP) requires cellular communication services to meet electromagnetic constraints, such as having the least bandwidth, satisfy customer demand/capacity, less call-blocking probability, and the least level of interference. With a limited bandwidth and cumulative growth in non-uniform dynamic demand which varies depending on the times of day, the problem of channel allocation becomes more crucial. Artificial intelligence Technique for heuristic optimization can be used to minimize the overall interference level (MICAP) and satisfy the channel demand. The MICAP is solved using the Genetic Algorithm and Simulated Annealing. When designing the cost or fitness function, co-channel, and co-site channel constraints are taken into account. The channel allocation matrix is observed, the cost function value is measured for the number of iterations or generations needed to satisfy the demand with constraints imposed. When the simulated observations are compared to previously reported results, the cost function value is found to be reduced for the benchmarks EX1, HEX1, HEX2, HEX3, HEX4, P1, P2, and P3, each of which indicates a distinct number of cells, frequency, and traffic demand.

URN:NBN:sciencein.jist.2024.v12.789