[Paper Review] Aerial Intelligent Reflecting Surface: Joint Placement and Passive Beamforming Design with 3D Beam Flattening

Haiquan Lu, Yong Zeng+2 more|arXiv (Cornell University)|Jul 27, 2020

Advanced Wireless Communication Technologies38 references15 citations

TL;DR

This paper proposes a joint optimization framework for aerial intelligent reflecting surfaces (AIRS) to maximize worst-case signal-to-noise ratio (SNR) over a target area by jointly designing transmit beamforming, AIRS placement, and 3D passive beamforming. It introduces a novel 3D beam broadening and flattening technique using sub-arrays to achieve uniform array gain across the coverage area, resulting in up to 30 dB SNR gain over benchmark schemes.

ABSTRACT

This paper proposes a new three-dimensional (3D) wireless passive relaying system enabled by aerial IRS (AIRS). Compared to the conventional terrestrial IRS, AIRS enjoys more deployment flexibility as well as wider-range signal reflection, thanks to its high altitude and thus more likelihood of establishing line-of-sight (LoS) links with ground source/destination nodes. Specifically, we aim to maximize the worst-case signal-to-noise ratio (SNR) over all locations in a target area by jointly optimizing the transmit beamforming for the source node and the placement as well as 3D passive beamforming for the AIRS. The formulated problem is non-convex and thus difficult to solve. To gain useful insights, we first consider the special case of maximizing the SNR at a given target location, for which the optimal solution is obtained in closed-form. The result shows that the optimal horizontal AIRS placement only depends on the ratio between the source-destination distance and the AIRS altitude. Then for the general case of AIRS-enabled area coverage, we propose an efficient solution by decoupling the AIRS passive beamforming design to maximize the worst-case array gain, from its placement optimization by balancing the resulting angular span and the cascaded channel path loss. Our proposed solution is based on a novel 3D beam broadening and flattening technique, where the passive array of the AIRS is divided into sub-arrays of appropriate size, and their phase shifts are designed to form a flattened beam pattern with adjustable beamwidth catering to the size of the coverage area. Both the uniform linear array (ULA)-based and uniform planar array (UPA)-based AIRSs are considered in our design, which enable two-dimensional (2D) and 3D passive beamforming, respectively. Numerical results show that the proposed designs achieve significant performance gains over the benchmark schemes.

Motivation & Objective

• To address the limitations of terrestrial IRS in deployment flexibility and coverage range by proposing an aerial IRS (AIRS) system.
• To maximize the worst-case SNR across a target area in 3D space, considering both signal strength and deployment constraints.
• To jointly optimize transmit beamforming, AIRS placement, and 3D passive beamforming for enhanced area coverage.
• To develop a beam broadening and flattening technique that enables uniform array gain across the target area.
• To demonstrate the superiority of the proposed design over conventional 1D beamforming and fixed-placement schemes.

Proposed method

• Formulates a non-convex optimization problem to maximize worst-case SNR over a 3D target area using joint transmit beamforming, AIRS placement, and 3D passive beamforming.
• Introduces a 3D beam broadening and flattening technique by dividing the AIRS into sub-arrays with optimized phase shifts to create a uniform, adjustable beamwidth.
• Decouples the optimization into two stages: maximizing worst-case array gain via beam design, and balancing angular span and path loss for optimal AIRS placement.
• Applies the technique to both uniform linear array (ULA) and uniform planar array (UPA) configurations for 2D and 3D beamforming, respectively.
• Derives a closed-form solution for the special case of single-location SNR maximization, showing that optimal horizontal placement depends only on the source-destination distance-to-altitude ratio.
• Employs numerical optimization and simulation to validate the performance gains of the proposed joint design.

Experimental results

Research questions

• RQ1 How does the optimal horizontal placement of an aerial IRS depend on the geometric relationship between the source, destination, and IRS altitude?
• RQ2 What beamforming strategy enables uniform signal strength across a 3D target area, minimizing worst-case SNR degradation?
• RQ3 How does 3D beam broadening and flattening compare to conventional 1D beamforming in terms of array gain and coverage uniformity?
• RQ4 What is the performance gain of joint placement and beamforming optimization over fixed or benchmark placement schemes?
• RQ5 Can the proposed beamforming technique achieve near-uniform array gain across large coverage areas using sub-array phase control?

Key findings

• The optimal horizontal AIRS placement depends only on the ratio of source-destination distance to IRS altitude, derived in closed-form for single-location SNR maximization.
• The proposed 3D beam broadening and flattening technique achieves approximately equal array gain across all locations in the target area, enabling uniform performance.
• The proposed scheme outperforms benchmark 1D beamforming by up to 30 dB in worst-case SNR for UPA-based AIRS, especially in large coverage areas.
• Optimized AIRS placement achieves significant performance gains over the benchmark center-located placement, highlighting the importance of joint optimization.
• UPA-based AIRS with the proposed beamforming achieves similar performance to ULA-based AIRS, while the deactivation-based benchmark scheme performs worse and is more sensitive to array aperture.
• The proposed method maintains high array gain across the entire coverage area, reducing SNR variation and improving reliability in dynamic or complex environments.