FollowSpot: Enhancing Wireless Communications via Movable Ceiling-Mounted Metasurfaces

2025-07-05

AI Summary

This paper addresses the beam focusing problem for ceiling-mounted reconfigurable intelligent surfaces (RISs), aiming to maximize the signal-to-noise ratio (SNR) at a target receiver. Due to strong inter-surface positional coupling and the inherent non-convexity and discreteness of the optimization, conventional methods struggle to achieve both global optimality and computational efficiency. To overcome this, we introduce continuous auxiliary variables to decouple positional constraints, thereby equivalently reformulating the original NP-hard nonlinear discrete optimization problem as a discrete search over a finite candidate set. We then propose a globally optimal algorithm with time complexity O(ML² log(ML)). Simulation results demonstrate that our approach significantly improves beam focusing accuracy and SNR, achieving faster convergence and superior performance compared to baseline schemes.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

This paper studies the optimal placement of ceiling-mounted metasurfaces (MTSs) to help focus the wireless signal beam onto the target receiver, as inspired by the theatre spotlight. We assume that a total of $M$ MTSs are deployed, and that there are $L$ possible positions for each MTS. The resulting signal-to-noise (SNR) maximization problem is difficult to tackle directly because of the coupling between the placement decisions of the different MTSs. Mathematically, we are faced with a nonlinear discrete optimization problem with $L^M$ possible solutions. A remarkable result shown in this paper is that the above challenging problem can be efficiently solved within $O(ML^2log(ML))$ time. There are two key steps in developing the proposed algorithm. First, we successfully decouple the placement variables of different MTSs by introducing a continuous auxiliary variable $μ$; the discrete primal variables are now easy to optimize when $μ$ is held fixed, but the optimization problem of $μ$ is nonconvex. Second, we show that the optimization of continuous $μ$ can be recast into a discrete optimization problem with only $LM$ possible solutions, so the optimal $μ$ can now be readily obtained. Numerical results show that the proposed algorithm can not only guarantee a global optimum but also reach the optimal solution efficiently.

Problem

• Optimizing ceiling-mounted metasurfaces placement for signal focus
• Solving nonlinear discrete SNR maximization efficiently
• Decoupling MTS placement variables via auxiliary variable

Innovation

• Ceiling-mounted metasurfaces optimize signal focus
• Efficient algorithm solves nonlinear discrete optimization
• Decouples placement variables with auxiliary variable