RIS Selection and Design Over Computable Channels in Massive MIMO mmWave Systems

As an attractive technology in multiple input multiple output (MIMO) systems, reconfigurable intelligent surface (RIS) can improve spectrum efficiency by reshaping the wireless propagation environment. In this article, we consider a RIS-assisted single-user (SU) massive MIMO millimeter wave (mmWave)...

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Published inIEEE transactions on communications Vol. 72; no. 12; pp. 8024 - 8034
Main Authors Li, Wengang, Wang, Mengyao, Zhu, Hongyu, Tian, Yiheng
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN0090-6778
1558-0857
DOI10.1109/TCOMM.2024.3420785

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Summary:As an attractive technology in multiple input multiple output (MIMO) systems, reconfigurable intelligent surface (RIS) can improve spectrum efficiency by reshaping the wireless propagation environment. In this article, we consider a RIS-assisted single-user (SU) massive MIMO millimeter wave (mmWave) downlink communication system. Our goal is to maximize spectral efficiency by selecting the optimal RIS, optimizing reflection coefficients of the RIS, and designing hybrid beamforming (HBF) at the base station (BS) and user equipment (UE) through a decoupling strategy. To be more precise, we first suggest a novel approach for computable channels (CC) based on location data and select the optimal RIS reflection path based on CC. we then propose a CC-based method to select the array response vectors and their corresponding path gains and angle information of the mmWave channels between the BS (RIS) and RIS (UE) required to formulate a passive beamforming vector, which is also solved via the manifold optimization (MO)-based algorithm. Lastly, the optimal problem of traditional HBF is decoupled into two stages. In the analog beamforming (ABF) stage, the selected path gains and angle information enable the simultaneous determination of ABF weight vectors. Based on the ABF matrix, in the digital beamforming (DBF) stage, the DBF matrix is designed to maximize spectral efficiency. Simulation results show that spectrum efficiency can be improved by selecting the optimal RIS and the computational complexity can be reduced by designing the RIS phase shifts.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2024.3420785