TY - GEN
T1 - Deep Learning Based Signal Detection in Dual Mode Generalized Spatial Modulation
AU - Yang, Kaiyue
AU - Bai, Zhiquan
AU - Zhang, Jinmei
AU - Pang, Ke
AU - Hao, Xinhong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper proposes a kind of deep learning (DL) based signal detection in dual mode generalized spatial modulation (DM-GSM) system, which aims to balance the detection performance and the complexity. Specifically, two neural networks, deep neural network (DNN) and convolutional neural network (CNN), are utilized to gain the mapping relationship among the received symbols, the channel matrix, and the transmitted bits. After offline training, the trained network is deployed for the online signal detection according to the input feature vector. Simulation results illustrate that the proposed DL detection can obtain the approximate performance of maximum likelihood (ML) detection at lower complexity and can provide better robustness compared with the conventional detection algorithms in the presence of various noise deviating from the standard Gaussian distribution.
AB - This paper proposes a kind of deep learning (DL) based signal detection in dual mode generalized spatial modulation (DM-GSM) system, which aims to balance the detection performance and the complexity. Specifically, two neural networks, deep neural network (DNN) and convolutional neural network (CNN), are utilized to gain the mapping relationship among the received symbols, the channel matrix, and the transmitted bits. After offline training, the trained network is deployed for the online signal detection according to the input feature vector. Simulation results illustrate that the proposed DL detection can obtain the approximate performance of maximum likelihood (ML) detection at lower complexity and can provide better robustness compared with the conventional detection algorithms in the presence of various noise deviating from the standard Gaussian distribution.
KW - Dual mode generalized spatial modulation (DMGSM)
KW - convolutional neural network (CNN)
KW - deep neural network (DNN)
KW - signal detection
UR - https://www.scopus.com/pages/publications/85135220423
U2 - 10.1109/ICUFN55119.2022.9829706
DO - 10.1109/ICUFN55119.2022.9829706
M3 - Conference contribution
AN - SCOPUS:85135220423
T3 - International Conference on Ubiquitous and Future Networks, ICUFN
SP - 140
EP - 144
BT - ICUFN 2022 - 13th International Conference on Ubiquitous and Future Networks
PB - IEEE Computer Society
T2 - 13th International Conference on Ubiquitous and Future Networks, ICUFN 2022
Y2 - 5 July 2022 through 8 July 2022
ER -