sis 15(4): e3

Research Article

Effective user selection algorithm for quantized precoding in massive MIMO

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  • @ARTICLE{10.4108/sis.2.4.e3,
    author={Nayan fang and Jie Zeng and Xin Su and Yujun Kuang},
    title={Effective user selection algorithm for quantized precoding in massive MIMO},
    journal={EAI Endorsed Transactions on Scalable Information Systems},
    volume={2},
    number={4},
    publisher={ICST},
    journal_a={SIS},
    year={2015},
    month={2},
    keywords={massive MIMO, user selection, quantized precoding},
    doi={10.4108/sis.2.4.e3}
}
  • Nayan fang
    Jie Zeng
    Xin Su
    Yujun Kuang
    Year: 2015
    Effective user selection algorithm for quantized precoding in massive MIMO
    SIS
    ICST
    DOI: 10.4108/sis.2.4.e3
Nayan fang1, Jie Zeng1,2,*, Xin Su2, Yujun Kuang1
  • 1: School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China
  • 2: Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China
*Contact email: zengjie@tsinghua.edu.cn

Abstract

The downlink of a multi-user massive MIMO wireless system is considered, where the base station equipped with a large number of antennas simultaneously servesmultiple users. In this paper, an effective user selection algorithm is proposed for quantized precoding in massive MIMO systems. The algorithm aims at minimizing the correlation of precoders among users by relaxing the optimal problem to be convex and solving it using the Primal Newton’s Barrier Method. The complexity of the proposed algorithm is relatively low and the performance shown by the numerical results is close to the exhaustive search method. The advantage of the proposed algorithm increasingly shows up as the transmit antennas increase significantly.

Keywords
massive MIMO, user selection, quantized precoding
Received
2014-03-04
Accepted
2014-05-28
Published
2015-02-17
Publisher
ICST
http://dx.doi.org/10.4108/sis.2.4.e3

Copyright © 2015 Nayan fan et al., licensed to ICST. 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.