ChinaCom2008-Signal Processing for Communications Symposium

Research Article

A Suboptimal User Selection Algorithm for Multiuser MIMO Systems Based on Block Diagonalization

  • @INPROCEEDINGS{10.1109/CHINACOM.2008.4685164,
        author={Xiaohan Chen and Ju Liu and Rui Xing and Hongji Xu},
        title={A Suboptimal User Selection Algorithm for Multiuser MIMO Systems Based on Block Diagonalization},
        proceedings={ChinaCom2008-Signal Processing for Communications Symposium},
        publisher={IEEE},
        proceedings_a={CHINACOM2008-SPC},
        year={2008},
        month={11},
        keywords={Multiuser MIMO; user selection; capacity upper-bound; block diagonalization.},
        doi={10.1109/CHINACOM.2008.4685164}
    }
    
  • Xiaohan Chen
    Ju Liu
    Rui Xing
    Hongji Xu
    Year: 2008
    A Suboptimal User Selection Algorithm for Multiuser MIMO Systems Based on Block Diagonalization
    CHINACOM2008-SPC
    IEEE
    DOI: 10.1109/CHINACOM.2008.4685164
Xiaohan Chen1,*, Ju Liu2,*, Rui Xing2, Hongji Xu2
  • 1: Shandong University School of Information Science and Engineering Jinan, 250100, China , Southeast University 2National Mobile Communications Research Laboratory Nanjing, 210096, China
  • 2: Shandong University School of Information Science and Engineering Jinan, 250100, China
*Contact email: xhchen@sdu.edu.cn, juliu@sdu.edu.cn

Abstract

In this paper, we propose a suboptimal user selection algorithm based on block diagonalization (BD) with low complexity. An upper-bound of sum-rate capacity is deduced. And considering it as the selection criterion we get our proposed algorithm. Furthermore in simplification of the proposed algorithm it is regarded as the adaptive criterion instead of capacity formula. After that we analyze the computational complexity in detail, and then compare the proposed algorithm with optimal selection algorithm and maximum norm selection method. Simulation results show that the proposed algorithm and its simplification can achieve the same sum-rate capacity as the optimal exhaustive search method in lower SNR, and in higher SNR they are both very close to the performance of optimal method.