Reconfigurable Intelligent Surface Assisted Massive MIMO with Antenna Selection
Jinglian He, Kaiqiang Yu, Yuanming Shi, Yong Zhou, Wei Chen, and, Khaled B. Letaief

TL;DR
This paper proposes a novel RIS-assisted massive MIMO architecture with antenna selection, combining passive beamforming and antenna optimization to improve spectral efficiency and reduce hardware costs, using advanced algorithms for complex joint optimization.
Contribution
It introduces a new RIS-assisted massive MIMO system with antenna selection, addressing non-convex optimization challenges with efficient algorithms for enhanced performance and low hardware complexity.
Findings
Algorithms outperform existing methods in capacity maximization
Joint optimization improves spectral efficiency significantly
Proposed methods are computationally efficient and scalable
Abstract
Antenna selection is capable of reducing the hardware complexity of massive multiple-input multiple-output (MIMO) networks at the cost of certain performance degradation. Reconfigurable intelligent surface (RIS) has emerged as a cost-effective technique that can enhance the spectrum-efficiency of wireless networks by reconfiguring the propagation environment. By employing RIS to compensate the performance loss due to antenna selection, in this paper we propose a new network architecture, i.e., RIS-assisted massive MIMO system with antenna selection, to enhance the system performance while enjoying a low hardware cost. This is achieved by maximizing the channel capacity via joint antenna selection and passive beamforming while taking into account the cardinality constraint of active antennas and the unit-modulus constraints of all RIS elements. However, the formulated problem turns out…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Antenna Design and Analysis · Advanced Antenna and Metasurface Technologies
