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Robust Beamforming Design and Antenna Selection for Dynamic HRIS-aided MISO System

Jintao Wang, Binggui Zhou, Chengzhi Ma, Shiqi Gong, Guanghua Yang, Shaodan Ma

TL;DR

A penalty-based exact block coordinate descent (PEBCD) algorithm is proposed to address the mean-square-error (MSE) minimization problem for the dynamic HRIS-aided MISO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS.

Abstract

In this paper, we propose a dynamic hybrid active-passive reconfigurable intelligent surface (HRIS) to enhance multiple-input-single-output (MISO) communications, leveraging the property of dynamically placing active elements. Specifically, considering the impact of hardware impairments (HWIs), we investigate channel-aware configurations of the receive antennas at the base station (BS) and the active/passive elements at the HRIS to improve transmission reliability. To this end, we address the average mean-square-error (MSE) minimization problem for the HRIS-aided MISO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS. To overcome the non-convexity and intractability of this problem, we first transform the binary and discrete variables into continuous ones, and then propose a penalty-based exact block coordinate descent (PEBCD) algorithm to alternately solve these subproblems. Numerical simulations demonstrate the significant superiority of our proposed scheme over conventional benchmark schemes.

Robust Beamforming Design and Antenna Selection for Dynamic HRIS-aided MISO System

TL;DR

A penalty-based exact block coordinate descent (PEBCD) algorithm is proposed to address the mean-square-error (MSE) minimization problem for the dynamic HRIS-aided MISO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS.

Abstract

In this paper, we propose a dynamic hybrid active-passive reconfigurable intelligent surface (HRIS) to enhance multiple-input-single-output (MISO) communications, leveraging the property of dynamically placing active elements. Specifically, considering the impact of hardware impairments (HWIs), we investigate channel-aware configurations of the receive antennas at the base station (BS) and the active/passive elements at the HRIS to improve transmission reliability. To this end, we address the average mean-square-error (MSE) minimization problem for the HRIS-aided MISO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS. To overcome the non-convexity and intractability of this problem, we first transform the binary and discrete variables into continuous ones, and then propose a penalty-based exact block coordinate descent (PEBCD) algorithm to alternately solve these subproblems. Numerical simulations demonstrate the significant superiority of our proposed scheme over conventional benchmark schemes.
Paper Structure (15 sections, 4 theorems, 23 equations, 3 figures, 1 algorithm)

This paper contains 15 sections, 4 theorems, 23 equations, 3 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Problem formulation
  5. Proposed PEBCD algorithm
  6. Problem Transformation
  7. Receive Beamforming
  8. Amplification Factor
  9. Auxiliary Variables
  10. Selection Variables
  11. Dynamic mode selection
  12. Receive antenna selection
  13. Reflection phase selection
  14. Simulation
  15. Conclusion

Key Result

Lemma 1

Assume ${\bf{x}} \in \mathbb{R}^N,{\bf{y}} \in \mathbb{R}^N$ and define $\chi \triangleq \{ ({\bf{x}},{\bf{y}}) | {\bf{-1}} \leq {\bf{x}} \leq {\bf{1}}, ||{\bf{y}}||_2^2 \leq N, {\bf{x}}^T{\bf{y}}=N, \forall {\bf{y}} \}$. Assume that ${\bf{x}},{\bf{y}} \in \chi$, then we have ${\bf{x}} \in \{-1,1\}^

Figures (3)

  • Figure 1: A dynamic HRIS-assisted uplink MISO communication system.
  • Figure 2: MSE versus the transmit power of HRIS for different algorithm comparisons.
  • Figure 3: Robust versus nonrobust design under the transmit power of HRIS.

Theorems & Definitions (6)

  • Lemma 1
  • proof
  • Proposition 1
  • proof
  • Corollary 1
  • Corollary 2