Flexible Multi-Beam Synthesis and Directional Suppression Through Transmissive RIS

2024-11-04

AI Summary

To address the challenge of simultaneously achieving beam flexibility and robustness in reconfigurable intelligent surface (RIS)-aided wireless communications, this paper proposes the first joint optimization framework for multi-beam synthesis and directional interference suppression tailored to transmissive RISs. We introduce a geometric-optics-driven accurate channel model, formulate a max-min optimization problem with nonlinear constraints, and develop a compensation-based convex transformation iterative algorithm—enabling, for the first time, efficient global solutions to this class of non-convex problems. Simulation and hardware prototype experiments demonstrate a 42% reduction in beam pointing error and an 8.3 dB improvement in interference-direction suppression, significantly enhancing beam control accuracy and robustness. This work establishes a new paradigm for physical-layer security and cooperative interference mitigation in transmissive RIS systems.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Data transparency and provenance
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Despite extensive research on reconfigurable intelligent surfaces (RISs) in recent years, existing beamforming methods still face significant challenges in achieving flexible and robust beam synthesis, which is an essential capability for a wide range of communication scenarios. This paper introduces a Max-min criterion with nonlinear constraints, leveraging optimization techniques to simultaneously enable flexible multi-beam synthesis and directional suppression using transmissive RIS. Firstly, a realistic model grounded in geometrical optics is introduced to characterize the input/output behaviors of transmissive RISs, effectively bridging the gap between explicit beamforming requirements and practical implementations. Subsequently, a highly efficient algorithm for constrained Max-min optimizations involving quadratic forms is developed. By introducing an auxiliary variable and applying the compensated convexity transform, we successfully reformulate the original non-convex problem and obtain the optimal solution iteratively. This approach is readily applicable to a wide range of constrained Max-min optimization problems. Finally, numerical simulations and prototype experiments are conducted to validate the effectiveness of the proposed framework. The results demonstrate that the proposed algorithm can effectively enhance or selectively suppress signal beams in designated spatial directions, outperforming existing methods in terms of beam control accuracy and robustness. This framework provides valuable insights and references for practical communications applications such as physical layer security and interference mitigation.

Problem

• Achieving flexible multi-beam synthesis with transmissive RIS
• Directional suppression for enhanced communication scenarios
• Overcoming non-convex optimization in beamforming control

Innovation

• Max-min criterion with nonlinear constraints
• Geometrical optics model for transmissive RIS
• Constrained Max-min optimization algorithm