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Rotatable IRS Aided Wireless Communication

Qiaoyan Peng, Qingqing Wu, Guangji Chen, Wen Chen, Shaodan Ma, Shanpu Shen, Rui Zhang

TL;DR

An angle-dependent channel model is proposed that accurately characterizes the reception and reflection of each IRS element, including the effective reception area and reflection efficiency, and significant SNR improvement is achieved by the proposed rotatable IRS design over various benchmark schemes under different system setups.

Abstract

Rotatable intelligent reflecting surface (IRS) introduces a new spatial degree of freedom (DoF) by dynamically adjusting orientations without the need of changing its elements' positions in real time. To unleash the full potential of rotatable IRSs for wireless communications, this paper investigates the joint optimization of IRS rotation angles to maximize the minimum expected signal-to-noise ratio (SNR) over all locations within a given target area. We first propose an angle-dependent channel model that accurately characterizes the reception and reflection of each IRS element. Different from the conventional cosine-law assumption, the proposed model captures the practical electromagnetic characteristics of the IRS, including the effective reception area and reflection efficiency. For the single target location case, a particle swarm optimization (PSO)-based algorithm is developed to solve the SNR maximization problem, and a closed-form expression for a near-optimal solution is derived to provide useful insights. For the general area coverage enhancement case, the optimal rotation is obtained through a two-loop PSO-based iterative algorithm with null-point detection. In this algorithm, the outer loop updates the global rotation angles to maximize the minimum SNR over the target area, whereas the inner loop evaluates the SNR distribution within the area to identify the location corresponding to the minimum SNR through null-point detection. Numerical results demonstrate significant SNR improvement achieved by the proposed rotatable IRS design over various benchmark schemes under different system setups.

Rotatable IRS Aided Wireless Communication

TL;DR

An angle-dependent channel model is proposed that accurately characterizes the reception and reflection of each IRS element, including the effective reception area and reflection efficiency, and significant SNR improvement is achieved by the proposed rotatable IRS design over various benchmark schemes under different system setups.

Abstract

Rotatable intelligent reflecting surface (IRS) introduces a new spatial degree of freedom (DoF) by dynamically adjusting orientations without the need of changing its elements' positions in real time. To unleash the full potential of rotatable IRSs for wireless communications, this paper investigates the joint optimization of IRS rotation angles to maximize the minimum expected signal-to-noise ratio (SNR) over all locations within a given target area. We first propose an angle-dependent channel model that accurately characterizes the reception and reflection of each IRS element. Different from the conventional cosine-law assumption, the proposed model captures the practical electromagnetic characteristics of the IRS, including the effective reception area and reflection efficiency. For the single target location case, a particle swarm optimization (PSO)-based algorithm is developed to solve the SNR maximization problem, and a closed-form expression for a near-optimal solution is derived to provide useful insights. For the general area coverage enhancement case, the optimal rotation is obtained through a two-loop PSO-based iterative algorithm with null-point detection. In this algorithm, the outer loop updates the global rotation angles to maximize the minimum SNR over the target area, whereas the inner loop evaluates the SNR distribution within the area to identify the location corresponding to the minimum SNR through null-point detection. Numerical results demonstrate significant SNR improvement achieved by the proposed rotatable IRS design over various benchmark schemes under different system setups.

Paper Structure

This paper contains 13 sections, 3 theorems, 55 equations, 13 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Single Target Location SNR Maximization
  4. Area Coverage Enhancement
  5. Simulation Results
  6. Single Target Location SNR Enhancement
  7. Evaluation of the Proposed Schemes
  8. Performance Comparison for Rotatable IRS and Fixed Rotation IRS
  9. Performance Comparison for Rotatable IRS and M-IRS
  10. Area Coverage Enhancement
  11. Performance Evaluation Under Locations within the Target Area
  12. Impact of the IRS's Altitude
  13. Conclusion

Key Result

Proposition 1

Under the assumption that $t_{1,1} \ge \sqrt{N}l^2/\lambda$, the BS-IRS channel entry can be approximated as where ${{{{\bar{g}}}}_m} = M_m^{\mathrm{c}}\tilde{l}\cos \varpi _{\mathrm{B}}^{\mathrm{c}} + M_m^{\mathrm{r}}\tilde{l}\cos \varpi _{\mathrm{B}}^{\mathrm{r}},m \in \mathcal{M}$ and ${{{{\tilde{g}}}}_n} = - N_n^{\mathrm{c}}l\cos {\varpi _{\mathrm{c}}} - N_n^{\mathrm{r}}l\cos {\varpi _{\mathr

Figures (13)

  • Figure 1: A rotatable IRS-aided wireless communication system.
  • Figure 2: An example of a rectangular IRS with 6 elements, where each reflecting element in a specific row and a specific column is labeled with a unique index.
  • Figure 3: Illustration of the two-timescale design.
  • Figure 4: Values of $\delta_1$, $\delta_2$, and $\delta_1 \times \delta_2$ versus the rotation $\bm{\Omega}$ when $\bar{L} = 0.25$.
  • Figure 5: Values of $\delta_1$, $\delta_2$, and $\delta_1 \times \delta_2$ versus the rotation $\bm{\Omega}$ when $\bar{L} = 0.1$.
  • ...and 8 more figures

Theorems & Definitions (3)

  • Proposition 1
  • Proposition 2
  • Proposition 3