Cellular Radio Channel Assignment Using a Modiied Hoppeld Network

The channel assignment problem is important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal channel assignment problem has become increasingly important. In this paper, 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. In this algorithm, an energy function is derived and the appropriate interconnection weights between the neurons are speciied. The interconnection weights between the neurons are designed in such a way that each neu-ron receives inhibitory support if the constrain conditions are violated and receives excitatory support if the constraint conditions are satissed. To escape the local minima, if the number of assigned channels are less than the required channel numbers, one or more channel is assigned in addition to already assigned channels such that the total number of assigned channels are the same as the required number of channels in the cell even though energy is increased. 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. In the previously proposed neural network approach, some frequencies are xed to accelerate the convergence time. In our algorithms, no frequency is xed before the frequency assignment procedure. This new algorithm, together with the proposed initialization and updating techniques and without xing frequencies in any cells, has better performance results than the results reported previously utilizing xed frequencies in certain cells.