Performance of Matrix Decomposition Algorithms in 5G NR MIMO Precoding

Simona Sibio, Paul Newson, Souheil Ben Smida, Yuan Ding, Tom Offer, David Ramsay, Bill Wilkie, George Goussetis

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents a trade-off analysis associated with different matrix decomposition algorithms in the application of MIMO precoding. A scenario of 5G New Radio (NR) Multi-User MIMO (MU-MIMO) downlink involving one base station (BS) equipped with 64 antennas which serves multiple users simultaneously is studied. The channel model follows the 3GPP TDL-C with various levels of antenna correlation. Six different matrix decomposition algorithms are studied, namely QR Modified Gram-Schmidt (QR-MGS), QR householder, Cholesky, LDL, SVD Bidiagonalization, and SVD. An evaluation of the computational complexity of the algorithms is presented and the system performance compared. These analyses allow us to make an informed trade-off between performance and hardware complexity.
Original languageEnglish
Publication statusAccepted/In press - 19 Jul 2022
Event2022 IEEE Vehicular Technology Society Asia Pacific Wireless Communications Symposium - Seoul, Korea, Democratic People's Republic of
Duration: 24 Aug 202226 Aug 2022
http://www.apwcs2022.org/

Conference

Conference2022 IEEE Vehicular Technology Society Asia Pacific Wireless Communications Symposium
Abbreviated titleIEEE VTS APWCS 2022
Country/TerritoryKorea, Democratic People's Republic of
CitySeoul
Period24/08/2226/08/22
Internet address

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