Is Channel Estimation Necessary to Select Phase-Shifts for RIS-Assisted Massive MIMO?

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Publication date: 17 June 2021

Abstract: Reconfigurable intelligent surfaces (RISs) have attracted great attention as a potential beyond 5G technology. These surfaces consist of many passive elements of metamaterials whose impedance can be controllable to change the characteristics of wireless signals impinging on them. Channel estimation is a critical task when it comes to the control of a large RIS when having a channel with a large number of multipath components. In this paper, we propose novel channel estimation schemes for different RIS-assisted massive multiple-input multiple-output (MIMO) configurations. The proposed methods exploit spatial correlation characteristics at both the base station and the planar RISs, and other statistical characteristics of multi-specular fading in a mobile environment. Moreover, a novel heuristic for phase-shift selection at the RISs is developed. For the RIS-assisted massive MIMO, a new receive combining method and a fixed-point algorithm, which solves the max-min fairness power control optimally, are proposed. Simulation results demonstrate that the proposed uplink RIS-aided framework improves the spectral efficiency of the cell-edge mobile user equipments substantially in comparison to a conventional single-cell massive MIMO system. The impact of several channel effects are studied to gain insight about which RIS configuration is preferable and when the channel estimation is necessary to boost the spectral efficiency.

Has companion code repository: https://github.com/emilbjornson/ris-massive-mimo

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