TY - GEN
T1 - Concatenated Classic and Neural (CCN) Codes
T2 - 2023 IEEE Wireless Communications and Networking Conference, WCNC 2023
AU - Günlü, Onur
AU - Fritschek, Rick
AU - Schaefer, Rafael F.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Small neural networks (NNs) used for error correction were shown to improve on classic channel codes and to address channel model changes. We extend the code dimension of any such structure by using the same NN under one-hot encoding multiple times, then serially-concatenated with an outer classic code. We design NNs with the same network parameters, where each Reed-Solomon codeword symbol is an input to a different NN. Significant improvements in block error probabilities for an additive Gaussian noise channel as compared to the small neural code are illustrated, as well as robustness to channel model changes.
AB - Small neural networks (NNs) used for error correction were shown to improve on classic channel codes and to address channel model changes. We extend the code dimension of any such structure by using the same NN under one-hot encoding multiple times, then serially-concatenated with an outer classic code. We design NNs with the same network parameters, where each Reed-Solomon codeword symbol is an input to a different NN. Significant improvements in block error probabilities for an additive Gaussian noise channel as compared to the small neural code are illustrated, as well as robustness to channel model changes.
UR - http://www.scopus.com/inward/record.url?scp=85159777458&partnerID=8YFLogxK
U2 - 10.1109/WCNC55385.2023.10118867
DO - 10.1109/WCNC55385.2023.10118867
M3 - Conference contribution
AN - SCOPUS:85159777458
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2023 IEEE Wireless Communications and Networking Conference, WCNC 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 March 2023 through 29 March 2023
ER -