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An Improved Gauss-Seidel Algorithm for Signal Detection in Massive MIMO Systems

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Wireless and Satellite Systems (WiSATS 2019)

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Abstract

Massive multiple input multiple output (MIMO) is a promising technology that has been proposed to meet the requirement of the fifth generation wireless communications systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) shows near-optimal performance. However, due to the direct matrix inverse, the computational complexity of the MMSE detection algorithm is too high, especially when there are a large number of users. Thus, in this paper, we propose an improved Gauss-Seidel algorithm by utilizing delayed over relaxation (DOR) scheme, which is named as delayed over relaxation Gauss-Seidel (DRGS) algorithm. The basic idea of the DOR scheme is to combine the predicted iterative step (n + 1) with the iteration of step (n − 1). The scheme can provide a significant improvement of the convergence speed for iterative algorithm. The theoretical analysis of DRGS algorithm shows that the proposed algorithm can reduce the computational complexity from O (K3) to O (K2), where K is the number of users. Simulation results verify that the DRGS algorithm can achieve almost the same BER performance as that of MMSE detection with a small number of iterations.

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Acknowledgement

This work is supported in part by the Postgraduate Research & Practice Innovation Program of Jiangsu Provence (No. SJCX18_0646), the National Natural Science Foundation of China (No. 61571108 & No. 61701197 & No. 61801193), the open research fund of National Mobile Communications Research Laboratory of millimeter wave, Southeast University (No. 2018D15), the open research fund of the National Key Laboratory of millimeter wave, Southeast University (No. K201918), and the Open Foundation of Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunication (No. 2017WICOM01), and Project funded by China Postdoctoral Science Foundation (No. 2018M641354).

Author information

Authors and Affiliations

  1. Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University, Wuxi, 214122, China

    Xiaoqing Zhao, Zhengquan Li, Qiong Wu, Yang Liu, Baolong Li & Cheng Zhou

  2. National Mobile Communication Research Laboratory, Southeast University, Nanjing, 210096, China

    Zhengquan Li & Qiong Wu

  3. Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China

    Qiong Wu

  4. The National Key Laboratory of Millimeter Wave, Southeast University, Nanjing, 210096, China

    Yang Liu

  5. School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China

    Ziyan Jia

Authors
  1. Xiaoqing Zhao
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  2. Zhengquan Li
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  3. Qiong Wu
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  4. Yang Liu
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  5. Baolong Li
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  6. Ziyan Jia
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  7. Cheng Zhou
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Corresponding author

Correspondence to Zhengquan Li .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Min Jia

  2. Harbin Institute of Technology, Harbin, China

    Qing Guo

  3. Harbin Institute of Technology, Harbin, China

    Weixiao Meng

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhao, X. et al. (2019). An Improved Gauss-Seidel Algorithm for Signal Detection in Massive MIMO Systems. In: Jia, M., Guo, Q., Meng, W. (eds) Wireless and Satellite Systems. WiSATS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-030-19156-6_37

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  • DOI: https://doi.org/10.1007/978-3-030-19156-6_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19155-9

  • Online ISBN: 978-3-030-19156-6

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