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ANT COLONY OPTIMIZATION FOR LOCATION AREA PLANNING IN CELLULAR NETWORKS

Location Area(LA) planning has critical impact on cellular network design. It is characterized by the tradeoff between the location updates overhead and the paging cost. The LA size could be made as large as the service area of main switching centre, and hence minimizing the registration overhead at the expense of maximizing the paging cost. On the other hand, if each cell is taken as an LA, the paging cost is minimized while the registration cost is maximized. Accordingly, the tradeoff between these two factors must be optimized in such a way that the total cost of paging and registration can be minimized along with the link cost. Due to the complexity of this problem, Meta-heuristic techniques are often used for analyzing and solving practical sized instances. In this paper, we propose a solution to the LA planning problem based on Ant Colony Optimization technique. The performance of the proposed approach is investigated and evaluated with respect to the solution quality on a range of problem instances. Experimental results have shown that the Ant Colony Optimization approach outperforms other approaches such as the Simulating Annealing approach for all problem instances.