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Efficient Iterative Massive MIMO Detectors Based on Iterative Matrix Inversion Methods

Efficient Iterative Massive MIMO Detectors Based on Iterative Matrix Inversion Methods

Mahmoud Albreem
Copyright: © 2021 |Pages: 21
ISBN13: 9781799846109|ISBN10: 1799846105|EISBN13: 9781799846116
DOI: 10.4018/978-1-7998-4610-9.ch009
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MLA

Albreem, Mahmoud. "Efficient Iterative Massive MIMO Detectors Based on Iterative Matrix Inversion Methods." Design Methodologies and Tools for 5G Network Development and Application, edited by P. Suresh, et al., IGI Global, 2021, pp. 175-195. https://doi.org/10.4018/978-1-7998-4610-9.ch009

APA

Albreem, M. (2021). Efficient Iterative Massive MIMO Detectors Based on Iterative Matrix Inversion Methods. In P. Suresh, G. Vairavel, & U. Saravanakumar (Eds.), Design Methodologies and Tools for 5G Network Development and Application (pp. 175-195). IGI Global. https://doi.org/10.4018/978-1-7998-4610-9.ch009

Chicago

Albreem, Mahmoud. "Efficient Iterative Massive MIMO Detectors Based on Iterative Matrix Inversion Methods." In Design Methodologies and Tools for 5G Network Development and Application, edited by P. Suresh, G. Vairavel, and U. Saravanakumar, 175-195. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-4610-9.ch009

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Abstract

Massive multiple-input multiple-output (MIMO) is a key technology in fifth generation (5G) communication systems. Although the maximum likelihood (ML) obtains an optimal performance, it is prohibited in realization because of its high computational complexity. Linear detectors are an alternative solution, but they contain a matrix inversion which is not hardware friendly. Several methods have been proposed to approximate or to avoid the computation of exact matrix inversion. This chapter garners those methods and study their applicability in massive MIMO system so that a generalist in communication systems can differentiate between different algorithms from a wide range of solutions. This chapter presents the performance-complexity profile of a detector based on the Neuamnn-series (NS), Newton iteration (NI), successive over relaxation (SOR), Gauss-Seidel (GS), Jacobi (JA), Richardson (RI), optimized coordinate descent (OCD), and conjugate-gradient (CG) methods in 8×64, 16×64, and 32×64 MIMO sizes, and modulation scheme is 64QAM.

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