A Modiied Hoppeld Network Approach for Cellular Radio Channel Assignment

A new channel assignment algorithm using a modiied Hoppeld neural network is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by a modiied discrete Hoppeld network. Also a new technique to escape local minima is introduced. The interconnection weights between the neu-rons are designed in such a way that each neuron receives inhibitory support from neurons that violate the constraint conditions and receives excitatory support from external input. Various initialization techniques which use the speciic characteristics of frequency assignment problems in cellular radio networks such as co-site constraint, adjacent channel constraint, and co-channel constraint and updating methods are investigated. Other than the already proposed neural network algorithms, this new algorithm xes no frequencies of the cells before the frequency assignment procedure. This new algorithm, together with the proposed initialization and updating techniques and with no xed frequencies in certain cells, has better performance results than the results reported previously utilizing xed cells.