An efficient technique for dynamic channel allocation (DCA) in mobile cellular networks

The scarcity of radio channels is the main bottleneck in the enhancement of system capacity while maintaining quality of service (QoS) in mobile cellular networks. A channel allocation scheme, which can adapt the varying load of a network, may help to overcome that bottleneck to some extent. Thus, dynamic channel allocation (DCA) is an important problem in mobile cellular networks. In this paper, we have formulated the DCA problem as a state space search problem and solved it by using a heuristic search technique, which is a variant of the well-known depth first branch and bound (DFBB) search technique. We have compared the performance of this technique with two other existing meta-heuristic techniques, namely simulated annealing (SA), and tabu search (TS) with respect to the call blocking probability for varying load in a network. From experimental results, it is found that the proposed technique performs better than TS and SA in this problem domain.