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Erschienen in: Wireless Personal Communications 4/2021

07.05.2021

Low-Complexity Joint Weighted Neumann Series and Gauss–Seidel Soft-Output Detection for Massive MIMO Systems

verfasst von: Xiaoming Dai, Tiantian Yan, Yuanyuan Dong, Yuquan Luo, Hua Li

Erschienen in: Wireless Personal Communications | Ausgabe 4/2021

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Abstract

We introduce a joint weighted Neumann series (WNS) and Gauss–Seidel (GS) approach to implement an approximated linear minimum mean-squared error (LMMSE) detector for uplink massive multiple-input multiple-output (M-MIMO) systems. We first propose to initialize the GS iteration by a WNS method, which produces a closer-to-LMMSE initial solution than the conventional zero vector and diagonal-matrix based scheme. Then the GS algorithm is applied to implement an approximated LMMSE detection iteratively. Furthermore, based on the WNS, we devise a low-complexity approximate log-likelihood ratios (LLRs) computation method whose performance loss is negligible compared with the exact method. Numerical results illustrate that the proposed joint WNS-GS approach outperforms the conventional method and achieves near-LMMSE performance with significantly lower computational complexity.

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Metadaten
Titel
Low-Complexity Joint Weighted Neumann Series and Gauss–Seidel Soft-Output Detection for Massive MIMO Systems
verfasst von
Xiaoming Dai
Tiantian Yan
Yuanyuan Dong
Yuquan Luo
Hua Li
Publikationsdatum
07.05.2021
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-021-08557-2

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