Research Article
Optimal ZF Precoder for MU massive MIMO Systems over Ricean Channel with per Antenna Power Allocation
@ARTICLE{10.4108/eai.13-7-2018.156088, author={James Kweku Nkrumah Nyarko and Christian Ango Mbom}, title={Optimal ZF Precoder for MU massive MIMO Systems over Ricean Channel with per Antenna Power Allocation}, journal={EAI Endorsed Transactions on Mobile Communications and Applications}, volume={4}, number={15}, publisher={EAI}, journal_a={MCA}, year={2018}, month={12}, keywords={MU massive MIMO, Ricean Fading, Zero Forcing, Lattice Reduction, Beamforming, Precoding, Per-antenna power Allocation}, doi={10.4108/eai.13-7-2018.156088} }
- James Kweku Nkrumah Nyarko
Christian Ango Mbom
Year: 2018
Optimal ZF Precoder for MU massive MIMO Systems over Ricean Channel with per Antenna Power Allocation
MCA
EAI
DOI: 10.4108/eai.13-7-2018.156088
Abstract
Multiuser massive multiple-input multiple-output systems have the potential to increase the data rate. However, with a large base station (BS) antenna, the non-square channel matrix restricts the zero-forcing (ZF) precoder rotations to obtain the best optimal solution with the per-antenna power allocation. In this paper, we propose the beamforming and lattice reduction (LR) approach to restrain the channel matrix and transform the lattice of the channel vectors to be near orthogonal. Numerical results show that the LR-based ZF precoder outperforms other ZF precoder schemes, such as, the norm approximation of the beamforming matrix. In particular, the sum rate of the proposed optimal ZF precoder requires a small number of BS antenna. Subsequently, with the strong line of sight (LoS) channel, the optimal power allocations in the subchannels depend on the dominance of the users in order to achieve substantial multiplexing and diversity gains. Specifically, the Ricean channel gain with the water-filling allocation at high SNR is non-negligible.
Copyright © 2019 James K. N. Nyarko and Christian A. Mbom, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (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.