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 instant s. Such a neural network can be used as a trigger for retransmission reques ts at either the beginning or at the conclusion of the decoding process, pr oviding improved reliability performance and lower average decoding complex ity than turbo decoding with CRC error detection.