Performance Analysis of Cellular Radio System Using Artificial Neural Networks

In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.