Decentralized detection for B5G massive MIMO: When local computation meets iterative algorithm

Massive multiple-input multiple-output (MIMO) is a key enabler for 5G and beyond. For signal detection of massive MIMO, computing resources available at the network edge were underexplored in most existing algorithms. For this reason, the paper proposes a new detection algorithm, termed inner-loopin...

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Vydáno v:Physical communication Ročník 51; s. 101554
Hlavní autoři: Yang, Qiyu, Yan, Jiayi, Zhang, Xia, Zhang, Hekun
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.04.2022
Témata:
Decentralized algorithm
Massive MIMO
Mean square error
Message passing
Message passing
Decentralized algorithm
Massive MIMO
Mean square error
ISSN:1874-4907, 1876-3219
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Shrnutí:Massive multiple-input multiple-output (MIMO) is a key enabler for 5G and beyond. For signal detection of massive MIMO, computing resources available at the network edge were underexplored in most existing algorithms. For this reason, the paper proposes a new detection algorithm, termed inner-looping decentralized generalized expectation consistent for signal recovery (iDeGEC-SR), which leverages an extra (inner) loop of message passing added to the DeGEC-SR and makes better exploration of the local computing resources. As demonstrated by theoretical analysis and Monte Carlo simulations, the algorithm outperforms state-of-the-art techniques like GEC-SR (in terms of computational complexity), GAMP and DeGEC-SR (in terms of estimation accuracy), considerably.
ISSN:1874-4907
1876-3219
DOI:10.1016/j.phycom.2021.101554