Neural Network – based Digital Receiver for Radio Communications

This paper proposes a novel digital receiver, based on a multilayer perceptron neural network architecture, which works in a radio communications environment. Training is carried out by the variable learning rate back-propagation algorithm with momentum in a supervised manner and a batch training mode. We present computer simulation results comparing the performance of this receiver against the classical correlation receiver, for various modulation methods. The results show that the neural network – based receiver achieves better performance in terms of bit error rate for various o b N / E values, especially in the case of a Rayleigh multipath channel. Key-Words: Neural networks, digital receiver, correlation receiver, radio channel, signal detection, backpropagation learning algorithm, wireless communications.