Papers › Flexible Intelligent Metasurface-Aided Wireless Communications: Architecture and Performance
Flexible Intelligent Metasurface-Aided Wireless Communications: Architecture and Performance
Songjie Yang, Zihang Wan, Boyu Ning, Weidong Mei, Jiancheng An, Yonina C. Eldar, Chau Yuen
Typical reconfigurable intelligent surface (RIS) implementations include metasurfaces with almost passive unit elements capable of reflecting their incident waves in controllable ways, enhancing wireless communications in a cost-effective manner. In this paper, we advance the concept of intelligent metasurfaces by introducing a flexible array geometry, termed flexible intelligent metasurface (FIM), which supports both element movement (EM) and passive beamforming (PBF). In particular, based on the single-input single-output (SISO) system setup, we first compare three modes of FIM, namely, EM-only, PBF-only, and EM-PBF, in terms of received signal power under different FIM and channel setups. The PBF-only mode, which only adjusts the reflect phase, is shown to be less effective than the EM-only mode in enhancing received signal strength. In a multi-element, multi-path scenario, the EM-only mode improves the received signal power by 125% compared to the PBF-only mode. The EM-PBF mode, which optimizes both element positions and phases, further enhances performance. Additionally, we investigate the channel estimation problem for FIM systems by designing a protocol that gathers EM and PBF measurements, enabling the formulation of a compressive sensing problem for joint cascaded and direct channel estimation. We then propose a sparse recovery algorithm called clustering mean-field variational sparse Bayesian learning, which enhances estimation performance while maintaining low complexity.
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