TY - GEN
T1 - Efficient MIMO Detection with Imperfect Channel Knowledge - A Deep Learning Approach
AU - Chen, Qian
AU - Zhang, Shunqing
AU - Xu, Shugong
AU - Cao, Shan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Multiple-input multiple-output (MIMO) system is the key technology for long term evolution (LTE) and 5G. The information detection problem at the receiver side is in general difficult due to the imbalance of decoding complexity and decoding accuracy within conventional methods. Hence, a deep learning based efficient MIMO detection approach is proposed in this paper. In our work, we use a neural network to directly get a mapping function of received signals, channel matrix and transmitted bit streams. Then, we compare the end-to-end approach using deep learning with the conventional methods in possession of perfect channel knowledge and imperfect channel knowledge. Simulation results show that our method presents a better trade-off in the performance for accuracy versus decoding complexity. At the same time, better robustness can be achieved in condition of imperfect channel knowledge compared with conventional algorithms.
AB - Multiple-input multiple-output (MIMO) system is the key technology for long term evolution (LTE) and 5G. The information detection problem at the receiver side is in general difficult due to the imbalance of decoding complexity and decoding accuracy within conventional methods. Hence, a deep learning based efficient MIMO detection approach is proposed in this paper. In our work, we use a neural network to directly get a mapping function of received signals, channel matrix and transmitted bit streams. Then, we compare the end-to-end approach using deep learning with the conventional methods in possession of perfect channel knowledge and imperfect channel knowledge. Simulation results show that our method presents a better trade-off in the performance for accuracy versus decoding complexity. At the same time, better robustness can be achieved in condition of imperfect channel knowledge compared with conventional algorithms.
KW - deep learning
KW - imperfect channel estimation
KW - MIMO detection
UR - http://www.scopus.com/inward/record.url?scp=85074747597&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2019.8885582
DO - 10.1109/WCNC.2019.8885582
M3 - Conference Proceeding
AN - SCOPUS:85074747597
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Y2 - 15 April 2019 through 19 April 2019
ER -