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Efficient Hybrid Linear Massive MIMO Detector Using Gauss–Seidel And Successive Over-Relaxation

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Abstract

The initial solution of a massive multiple-input multiple-output (M-MIMO) detector for uplink (UL) is greatly influence the balance between the bit error rate (BER) performance and the computational complexity. Although the maximum likelihood (ML) detector obtains the best BER performance, it has an extremely high computational complexity. Iterative linear minimum mean square error (MMSE) detector based on the Gauss–Seidel (GS), the successive over-relaxation (SOR), and the Jacobi (JA), obtains a good performance-complexity profile when the base station (BS)-to-user-antenna-ratio (BUAR) is large. However, when the BUAR is small, the system suffers from a considerable performance loss. In this paper, a hybrid detector based on the joint GS and SOR methods is proposed where the initial solution is determined by the first iteration of GS method. Numerical results show a considerable complexity reduction and performance enhancement using the proposed GS-SOR method over all methods when the BUAR is small.

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Acknowledgements

This research is supported by the Research Council (TRC) of the Sultanate of Oman (agreement No. TRC/BFP/ASU/01/2018).

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, College of Engineering, A’Sharqiyah University, Ibra, 400, Oman

    Mahmoud A. M. Albreem

  2. IIT, Kanpur, India

    K. Vasudevan

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  1. Mahmoud A. M. Albreem
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  2. K. Vasudevan
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Correspondence to Mahmoud A. M. Albreem.

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Albreem, M.A.M., Vasudevan, K. Efficient Hybrid Linear Massive MIMO Detector Using Gauss–Seidel And Successive Over-Relaxation. Int J Wireless Inf Networks 27, 551–557 (2020). https://doi.org/10.1007/s10776-020-00493-5

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