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The problem of optimal channel assignment has become increasingly important because of available frequency spectrum and increasing demand for cellular communication services. This has been shown to be an Np complete optimization problem. Many heuristic approaches including neural network, simulated annealing and genetic algorithm have been used to solve it. In this paper we propose a novel and efficient...
With limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel allocation becomes increasingly important. However, finding a conflict-free channel allocation with minimum interference and minimum channel span is NP hard. Genetic algorithm (GA) is one of the heuristic optimization tools that can be used to solve this problem efficiently. In this...
In this paper, we propose a quasi-static approach which, using a powerful Linux/PC cluster, combines the merits of both traditional static and dynamic schemes for the channel assignment problem. The static component of our approach uses a parallel genetic algorithm to generate a suite of representative assignments based on a set of different estimated traffic scenarios. At on-line time, the dynamic...
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