TY - GEN
T1 - 4-QAM gray coding for deep neural network based decoder training
AU - Kim, Minhoe
AU - Cho, Dong Ho
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/12
Y1 - 2017/12/12
N2 - We propose a gray coding method for deep neural network (DNN) based decoder. With multiple resources considered together, DNN can be used to decode corrupted signals. In deep learning training, stochastic gradient descent (SGD) algorithm is used, which means that the cost function must be differentiable. Then, allocating the discrete bits for each symbol is difficult. To solve this problem, the basic gray coding for 4-quadrature amplitude modulation (QAM) is investigated for deep learning training. The performance of the proposed scheme is evaluated by simulation result compared with non-gray coding scheme. The symbol error rate (SER) performance is shown to be equivalent, but the bit error rate (BER) performance of the proposed scheme is shown to be better, which implies the gray coding is successfully done.
AB - We propose a gray coding method for deep neural network (DNN) based decoder. With multiple resources considered together, DNN can be used to decode corrupted signals. In deep learning training, stochastic gradient descent (SGD) algorithm is used, which means that the cost function must be differentiable. Then, allocating the discrete bits for each symbol is difficult. To solve this problem, the basic gray coding for 4-quadrature amplitude modulation (QAM) is investigated for deep learning training. The performance of the proposed scheme is evaluated by simulation result compared with non-gray coding scheme. The symbol error rate (SER) performance is shown to be equivalent, but the bit error rate (BER) performance of the proposed scheme is shown to be better, which implies the gray coding is successfully done.
UR - http://www.scopus.com/inward/record.url?scp=85046905665&partnerID=8YFLogxK
U2 - 10.1109/ICTC.2017.8190979
DO - 10.1109/ICTC.2017.8190979
M3 - Conference contribution
AN - SCOPUS:85046905665
T3 - International Conference on Information and Communication Technology Convergence: ICT Convergence Technologies Leading the Fourth Industrial Revolution, ICTC 2017
SP - 247
EP - 249
BT - International Conference on Information and Communication Technology Convergence
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Information and Communication Technology Convergence, ICTC 2017
Y2 - 18 October 2017 through 20 October 2017
ER -