Performance of Two Neural Receiver Structures in the Presence of Co-Channel Interference

Real communication channels with multipath propagation, interference and possible nonlinearities pose a difficult problem to the detecting receiver. This paper deals with neural approaches to solve those difficulties. Two types of neural networks, self-organizing map and radial basis functions have been studied. The results show that, while there are no actual benefits in using neural receivers in simple white noise Gaussian channels, the performance in nonlinear channels is much better with these new approaches than with the traditional ones.