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Reconfigurable Intelligent Surface-Assisted Cell-Free Massive MIMO Systems Over Spatially-Correlated Channels
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2021 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, p. 1-1Article in journal (Refereed) Published
Abstract [en]

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an aggregated channel estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. p. 1-1
Keywords [en]
Cell-free Massive MIMO, Channel estimation, Computer architecture, ergodic net throughput, Finite element analysis, Massive MIMO, maximum ratio processing, reconfigurable intelligent surface, Scattering, Throughput, Uplink
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-312604DOI: 10.1109/TWC.2021.3136925ISI: 000838503800036Scopus ID: 2-s2.0-85122288245OAI: oai:DiVA.org:kth-312604DiVA, id: diva2:1660756
Note

QC 20220525

Available from: 2022-05-24 Created: 2022-05-24 Last updated: 2024-03-15Bibliographically approved

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Ottersten, Björn

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