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The design and performance of a neural network for predicting turbo decoding error with application to hybrid ARQ protocols

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2 Author(s)
M. E. Buckley ; Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA ; S. B. Wicker

It is shown that a neural network can be trained to observe the cross entropy of the outputs of component decoders in a turbo error control system and to accurately predict the presence of errors in the decoded data. The neural network can be used as a trigger for retransmission requests at either the beginning or the conclusion of the decoding process, providing improved reliability and throughput performance at a lower average decoding complexity than turbo decoding with cyclic redundancy check error detection

Published in:

IEEE Transactions on Communications  (Volume:48 ,  Issue: 4 )