Environment-Aware Codebook Design for RIS-Assisted MU-MISO Communications: Implementation and Performance Analysis

doi:10.1109/TCOMM.2024.3415619

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Environment-Aware Codebook Design for RIS-Assisted MU-MISO Communications: Implementation and Performance Analysis

2024-12-01

DOI：10.1109/TCOMM.2024.3415619

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Abstract

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Reconfigurable intelligent surface (RIS) provides a new electromagnetic response control solution, which can proactively reshape the characteristics of wireless channel environments. In RIS-assisted communication systems, the acquisition of channel state information (CSI) and the optimization of reflecting coefficients constitute major design challenges. To address these issues, codebook-based solutions have been developed recently, which, however, are mostly environment-agnostic. In this paper, a novel environment-aware codebook protocol is proposed, which can significantly reduce both pilot overhead and computational complexity, while maintaining expected communication performance. Specifically, first of all, a channel training framework is introduced to divide the training phase into several blocks. In each block, we directly estimate the composite end-to-end channel and focus only on the transmit beamforming. Second, we propose an environment-aware codebook generation scheme, which first generates a group of channels based on statistical CSI, and then obtains their corresponding RIS configuration by utilizing the alternating optimization (AO) method offline. In each online training block, the RIS is configured based on the corresponding codeword in the environment-aware codebook, and the optimal codeword resulting in the highest sum rate is adopted for assisting in the downlink data transmission. Third, we analyze the theoretical performance of the environment-aware codebook-based protocol taking into account the channel estimation errors. Finally, numerical simulations are provided to verify our theoretical analysis and the performance of the proposed scheme. In particular, the simulation results demonstrate that our protocol is more competitive than conventional environment-agnostic codebooks.

Keywords:

Channel estimation

MIMO communication

Reconfigurable intelligent surfaces

Array signal processing

Protocols

Training

Optimization

Reconfigurable intelligent surface (RIS)

channel training

environment-aware codebook

multiuser downlink beamforming