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Weighted Codebook Scheme for RIS-Assisted Point-to-Point MIMO Communications

Zhiheng Yu, Jiancheng An, Lu Gan, Hongbin Li, Symeon Chatzinotas

TL;DR

The paper tackles optimizing RIS-assisted point-to-point MIMO performance under finite codebooks by introducing a weighted DFT codebook approach. It jointly designs online RIS RC weights and transmit precoding using uplink training observations, an iterative KKT-based weight update, and SVD-based downlink precoding, yielding an RC vector as a weighted sum of DFT codewords. A key novelty is the Codeword Configuration Order, including environment-aware ordering that leverages statistical CSI to prioritize codewords aligned with the LoS components. Simulations show that the proposed weighted scheme outperforms conventional codebook and passive beamforming schemes, is robust to channel estimation noise, and scales favorably with larger RIS sizes, reducing the performance gap imposed by finite codebooks.

Abstract

Reconfigurable intelligent surfaces (RIS) can reshape the characteristics of wireless channels by intelligently regulating the phase shifts of reflecting elements. Recently, various codebook schemes have been utilized to optimize the reflection coefficients (RCs); however, the selection of the optimal codeword is usually obtained by evaluating a metric of interest. In this letter, we propose a novel weighted design on the discrete Fourier transform (DFT) codebook to obtain the optimal RCs for RIS-assisted point-to-point multiple-input multiple-output (MIMO) systems. Specifically, we first introduce a channel training protocol where we configure the RIS RCs using the DFT codebook to obtain a set of observations through the uplink training process. Secondly, based on these observed samples, the Lagrange multiplier method is utilized to optimize the weights in an iterative manner, which could result in a higher channel capacity for assisting in the downlink data transmission. Thirdly, we investigate the effect of different codeword configuration orders on system performance and design an efficient codeword configuration method based on statistical channel state information (CSI). Finally, numerical simulations are provided to demonstrate the performance of the proposed scheme.

Weighted Codebook Scheme for RIS-Assisted Point-to-Point MIMO Communications

TL;DR

The paper tackles optimizing RIS-assisted point-to-point MIMO performance under finite codebooks by introducing a weighted DFT codebook approach. It jointly designs online RIS RC weights and transmit precoding using uplink training observations, an iterative KKT-based weight update, and SVD-based downlink precoding, yielding an RC vector as a weighted sum of DFT codewords. A key novelty is the Codeword Configuration Order, including environment-aware ordering that leverages statistical CSI to prioritize codewords aligned with the LoS components. Simulations show that the proposed weighted scheme outperforms conventional codebook and passive beamforming schemes, is robust to channel estimation noise, and scales favorably with larger RIS sizes, reducing the performance gap imposed by finite codebooks.

Abstract

Reconfigurable intelligent surfaces (RIS) can reshape the characteristics of wireless channels by intelligently regulating the phase shifts of reflecting elements. Recently, various codebook schemes have been utilized to optimize the reflection coefficients (RCs); however, the selection of the optimal codeword is usually obtained by evaluating a metric of interest. In this letter, we propose a novel weighted design on the discrete Fourier transform (DFT) codebook to obtain the optimal RCs for RIS-assisted point-to-point multiple-input multiple-output (MIMO) systems. Specifically, we first introduce a channel training protocol where we configure the RIS RCs using the DFT codebook to obtain a set of observations through the uplink training process. Secondly, based on these observed samples, the Lagrange multiplier method is utilized to optimize the weights in an iterative manner, which could result in a higher channel capacity for assisting in the downlink data transmission. Thirdly, we investigate the effect of different codeword configuration orders on system performance and design an efficient codeword configuration method based on statistical channel state information (CSI). Finally, numerical simulations are provided to demonstrate the performance of the proposed scheme.

Paper Structure

This paper contains 10 sections, 16 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. The Proposed Codebook Weighting Scheme
  4. $Q < N+1$
  5. $Q = N+1$
  6. Weight Design
  7. Transmit Precoding Design
  8. Codeword Configuration Order
  9. Simulation Results
  10. Conclusion

Figures (4)

  • Figure 1: An RIS-assisted point-to-point MIMO communication system.
  • Figure 2: Comparison between (a) The proposed DFT codebook weighting scheme and (b) The conventional codebook scheme.
  • Figure 3: Channel capacity $C$ versus training overhead $Q$.
  • Figure 4: (a) Channel capacity $C$ versus total transmit power $p_d$. (b) Channel capacity $C$ versus the number of RIS elements $N$. (Both with training overhead $Q = 6$.)