A neural network for predicting decoder error in turbo decoders

It is shown that a neural network can be trained to predict the presence of errors in turbo-decoded data. The inputs to the network are samples of the cross entropy of the component decoder outputs at two or more time instants. Such a neural network can be used as a trigger for retransmission requests at either the beginning or at the conclusion of the decoding process, providing improved reliability performance and lower average decoding complexity than turbo decoding with CRC error detection.