TY - GEN
T1 - Reinforcement Learning Based Antenna Selection in User-Centric Massive MIMO
AU - Chai, Xinxin
AU - Gao, Hui
AU - Sun, Ji
AU - Su, Xin
AU - Lv, Tiejun
AU - Zeng, Jie
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - In this paper, we consider a user-centric massive multiple-input multiple-output (UC-MMIMO) system, wherein the optimal antenna selection (AS) is very complicated, because of the huge number of deployed antennas. Traditional AS algorithms rely heavily on full and perfect channel state information (CSI). Thus, we propose a novel AS algorithm to achieve low-complexity and less CSI reliance for UC-MMIMO. The proposed AS algorithm consists of the selection stage and the adjustment stage. In the selection stage, antennas are selected by a reinforcement learning (RL) based algorithm in which input data are the locations of users. In the adjustment stage, an adjustment mechanism is designed to further improve the performance. Numerical results show that our algorithm achieves better performance with lower complexity compared with related traditional algorithms.
AB - In this paper, we consider a user-centric massive multiple-input multiple-output (UC-MMIMO) system, wherein the optimal antenna selection (AS) is very complicated, because of the huge number of deployed antennas. Traditional AS algorithms rely heavily on full and perfect channel state information (CSI). Thus, we propose a novel AS algorithm to achieve low-complexity and less CSI reliance for UC-MMIMO. The proposed AS algorithm consists of the selection stage and the adjustment stage. In the selection stage, antennas are selected by a reinforcement learning (RL) based algorithm in which input data are the locations of users. In the adjustment stage, an adjustment mechanism is designed to further improve the performance. Numerical results show that our algorithm achieves better performance with lower complexity compared with related traditional algorithms.
KW - User-Centric Massive MIMO system
KW - antenna adjustment
KW - antenna selection
KW - low complexity
KW - reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=85088298111&partnerID=8YFLogxK
U2 - 10.1109/VTC2020-Spring48590.2020.9129108
DO - 10.1109/VTC2020-Spring48590.2020.9129108
M3 - Conference contribution
AN - SCOPUS:85088298111
T3 - IEEE Vehicular Technology Conference
BT - 2020 IEEE 91st Vehicular Technology Conference, VTC Spring 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 91st IEEE Vehicular Technology Conference, VTC Spring 2020
Y2 - 25 May 2020 through 28 May 2020
ER -