A three-stage heuristic combined neural-network algorithm for channel assignment in cellular mobile systems

Abstract

A three-stage algorithm of combining sequential heuristic methods into a parallel neural network is presented for the channel assignment problem in cellular mobile communication systems in this paper. The goal of this NP-complete problem is to find a channel assignment to requested calls with the minimum number of channels subject to interference constraints between channels. The three-stage algorithm consists of: (1) the regular interval assignment stage; (2) the greedy assignment stage; and (3) the neural-network assignment stage. In the first stage, the calls in a cell determining the lower bound on the total number of channels are assigned channels at regular intervals. In the second stage, the calls in a cell with the largest degree and its adjacent cells are assigned channels by a greedy heuristic method. In the third stage, the calls in the remaining cells are assigned channels by a binary neural network. The performance is verified through solving well-known benchmark problems. Especially for Sivarajan's benchmark problems, our three-stage algorithm first achieves the lower bound solutions in all of the 13 instances, while the computation time is comparable with existing algorithms.