Research Article
Transmit Antenna Selection Aided Linear Group Precoding for Massive MIMO Systems
@ARTICLE{10.4108/eai.24-10-2019.160982, author={Van Khoi Dinh and Minh Tuan Le and Vu Duc Ngo and Xuan Nam Tran and Chi Hieu Ta}, title={Transmit Antenna Selection Aided Linear Group Precoding for Massive MIMO Systems}, journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}, volume={6}, number={21}, publisher={EAI}, journal_a={INIS}, year={2019}, month={10}, keywords={MU-MIMO system, Massive MIMO system, linear precoder, lattice reduction algorithm}, doi={10.4108/eai.24-10-2019.160982} }- Van Khoi Dinh
Minh Tuan Le
Vu Duc Ngo
Xuan Nam Tran
Chi Hieu Ta
Year: 2019
Transmit Antenna Selection Aided Linear Group Precoding for Massive MIMO Systems
INIS
EAI
DOI: 10.4108/eai.24-10-2019.160982
Abstract
In this paper, we investigate the combination of linear group precoding with a transmit antenna group selection (TA-GS) algorithm based on the channel capacity analysis for Massive MIMO systems. Simultaneously, we propose a low complexity linear precoding algorithm that works on the selected antennas. The proposed precoder is developed based on the conventional linear precoders in combination with the element-base lattice reduction shortest longest vector technique having low complexity. Numerical and simulation results show that the system performance significantly improves when the transmit selection technique is applied. Besides, the proposed precoder has remarkably lower computational complexity than its LC-RBD-LR-ZF counterpart. The bit error rate (BER) performance of the proposed precoder can approach that of the LC-RBD-LR-ZF precoder as the number of groups increases, yet at the cost of higher detection complexity.
Copyright © 2019 Van Khoi Dinh et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
