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Neural network – based digital receiver for radio communications

Liodakis Georgios, Ioannis Vardiambasis , Arvanítīs, Dīmī́trīs Th., 1948-

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Περίληψη

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.

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