Transmit Antenna Selection Aided Linear Group Precoding for Massive MIMO Systems

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.

Design of Group Precoding for MU-MIMO Systems with Exponential Spatial Correlation Channel

“…However, their computational complexity is still very high due to the adoptions of QR decomposition and LR algorithms. In [12], the precoding algorithm is proposed based on system expansion. Besides, the precoding algorithm based on the principal component analysis technique (PCA) is proposed for Massive MIMO systems [13].…”

“…Besides, the precoding algorithm based on the principal component analysis technique (PCA) is proposed for Massive MIMO systems [13]. However, for the proposals in [12] and [13], the authors have not given the symbol error probability analysis expression of the system.…”

“…) :, 1: ( BD T N WD (7) Applying the same steps to 1 H , we are able to get the next precoding matrix 2 BD W . The precoding matrix BD W is designed to have the following form: 12 .…”