5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings

Research Article

Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems

  • @INPROCEEDINGS{10.1007/978-3-319-72823-0_36,
        author={Zhenyu Zhang and Yuanyuan Dong and Zhongshan Zhang and Xiyuan Wang and Xiaoming Dai and Linglong Dai and Haijun Zhang},
        title={Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems},
        proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings},
        proceedings_a={5GWN},
        year={2018},
        month={1},
        keywords={Accelerated overrelaxation (AOR) Iterative algorithm Minimum mean square error (MMSE) Convergence Complexity},
        doi={10.1007/978-3-319-72823-0_36}
    }
    
  • Zhenyu Zhang
    Yuanyuan Dong
    Zhongshan Zhang
    Xiyuan Wang
    Xiaoming Dai
    Linglong Dai
    Haijun Zhang
    Year: 2018
    Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems
    5GWN
    Springer
    DOI: 10.1007/978-3-319-72823-0_36
Zhenyu Zhang1, Yuanyuan Dong1, Zhongshan Zhang1, Xiyuan Wang1, Xiaoming Dai1,*, Linglong Dai2, Haijun Zhang1
  • 1: University of Science and Technology Beijing
  • 2: Tsinghua University
*Contact email: daixiaoming@ustb.edu.cn

Abstract

Massive multiple-input multiple-output (MIMO) systems can substantially improve the spectral efficiency and system capacity by equipping a large number of antennas at the base station and it is envisaged to be one of the critical technologies in the next generation of wireless communication systems. However, the computational complexity of the signal detection in massive MIMO systems presents a significant challenge for practical hardware implementations. This work proposed a novel minimum mean square error (MMSE) signal detection method based on the accelerated overrelaxation (AOR) iterative algorithm. The proposed AOR-based method can reduce the overall complexity of the classical MMSE signal detection by an order of magnitude from to , where is the number of users. Numerical results illustrate that the proposed AOR-based algorithm can outperform the performance of the recently proposed Neumann series approximation-based algorithm and approach the conventional MMSE signal detection involving exact matrix inversion with significantly reduced complexity.