Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Geometrical fuzzy clustering algorithms
Fuzzy Sets and Systems
Static and dynamic channel assignment using neural networks
IEEE Journal on Selected Areas in Communications
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In this paper, the fuzzy Hopfield neural network (FHNN) is proposed for channel assignment in wireless cellular system. Each channel is regarded as a data sample and every cell is taken as a cluster. Channels are adequately distributed to the dedicated cells while satisfying the interference constraints such as co-site constraints, adjacent channel constraints, and co-channel constraints. The goal is to avoid the interference and serve the expected traffic, which is to minimize used spectrum. Moreover, interference prediction is a delicate task; it depends on the details of the traffic assumptions. The FHNN guarantees that the neural network will skip local minima, and in all cases will converge to the optimum arrangement of the channels. Simulation results show that the FHNN can provide an alternative approach of solving this class of channel assignment problems.