TY - GEN
T1 - Decoding Convolutional Hadamard Codes and Turbo Hadamard Codes using Recurrent Neural Networks
AU - Jiang, Sheng
AU - Lau, Francis C.M.
N1 - Publisher Copyright:
© 2024 Global IT Research Institute - GIRI.
PY - 2024/3
Y1 - 2024/3
N2 - In this paper, a Recurrent Neural Network (RNN) based decoder is proposed for the decoding of convolutional Hadamard codes (CHC) and Turbo Hadamard Codes (THC). Moreover, a long short-term memory (LSTM) network is adopted to realize the RNN decoder, forming the LSTM-CHC decoder and LSTM-THC decoder. Also, the proposed LSTM-THC decoder consists of several serial-concatenated LSTM-CHC decoders, which are pre-trained separately. The end-to-end LSTM-THC decoder is then trained based on the pre-trained weights. Simulations are performed on the LSTM-CHC/LSTM-THC decoders and their error performances are compared with those of the conventional decoders.
AB - In this paper, a Recurrent Neural Network (RNN) based decoder is proposed for the decoding of convolutional Hadamard codes (CHC) and Turbo Hadamard Codes (THC). Moreover, a long short-term memory (LSTM) network is adopted to realize the RNN decoder, forming the LSTM-CHC decoder and LSTM-THC decoder. Also, the proposed LSTM-THC decoder consists of several serial-concatenated LSTM-CHC decoders, which are pre-trained separately. The end-to-end LSTM-THC decoder is then trained based on the pre-trained weights. Simulations are performed on the LSTM-CHC/LSTM-THC decoders and their error performances are compared with those of the conventional decoders.
KW - convolutional Hadamard code
KW - Recurrent Neural Networks
KW - turbo Hadamard code
UR - http://www.scopus.com/inward/record.url?scp=85189516673&partnerID=8YFLogxK
U2 - 10.23919/ICACT60172.2024.10472004
DO - 10.23919/ICACT60172.2024.10472004
M3 - Conference article published in proceeding or book
AN - SCOPUS:85189516673
T3 - International Conference on Advanced Communication Technology, ICACT
SP - 89
EP - 93
BT - 26th International Conference on Advanced Communications Technology
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th International Conference on Advanced Communications Technology, ICACT 2024
Y2 - 4 February 2024 through 7 February 2024
ER -