Neural network-based dynamic channel assignment for cellular mobile communication systems

Conventional dynamic channel assignment schemes are both time-consuming and algorithmically complex. An alternative approach, based on cascaded multilayered feedforward neural networks, is proposed and examined on two cellular systems with different configurations. Simulation results showed that the blocking performance of our multistage neural network approach can match that of an example conventional scheme with less complexity and higher computational efficiency. The example scheme considered here is the ordered channel search, which can achieve a reasonably high spectral efficiency as compared to that of an ideal dynamic channel allocation algorithm. We conclude that our neural network approach is well-suited to the dynamic channel allocation problem of future cellular or microcellular systems with decentralized control