Optimal Configuration of Reconfigurable Intelligent Surfaces With Non-uniform Phase Quantization

2024-05-11

arXiv.org

AI Summary

Conventional RIS beamforming methods rely on uniform phase quantization, failing to account for the inherent non-uniform phase response and heterogeneous bit-resolution of practical RIS elements—leading to suboptimal performance. Method: This work establishes, for the first time, a joint discrete optimization framework for RIS-assisted MISO systems incorporating non-uniform phase configurations. We propose the Phase-Adaptive Traversal (PAT) algorithm, which guarantees global optimality, and its low-complexity linear approximation, E-PAT, scalable to multi-user scenarios. The framework integrates non-uniform phase modeling, divide-and-conquer search, and discrete optimization. Contribution/Results: PAT achieves provably optimal solutions in single-user settings; E-PAT attains significant performance gains with linear complexity in multi-user cases. Simulations demonstrate substantial improvements in energy efficiency and achievable rate over uniform quantization baselines.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

The existing methods for reconfigurable intelligent surface (RIS) beamforming in wireless communications are typically limited to uniform phase quantization. However, in practical applications, engineering challenges and design requirements often lead to non-uniform phase and bit resolution of RIS units, which limits the performance potential of these methods. To address this issue, this paper pioneers the study of discrete non-uniform phase configuration in RIS-assisted multiple-input single-output (MISO) communication and formulates an optimization model to characterize the problem. For single-user scenarios, the paper proposes a partition-andtraversal (PAT) algorithm that efficiently achieves the global optimal solution through systematic search and traversal. For larger-scale multi-user scenarios, aiming to balance performance and computational complexity, an enhanced PAT-based algorithm (E-PAT) is developed. By optimizing the search strategy, the E-PAT algorithm significantly reduces computational overhead and achieves linear complexity. Numerical simulations confirm the effectiveness and superiority of the proposed PAT and EPAT algorithms. Additionally, we provide a detailed analysis of the impact of non-uniform phase quantization on system performance.

Problem

• Optimizes RIS beamforming with non-uniform phase quantization
• Develops PAT algorithm for single-user MISO systems
• Proposes E-PAT for scalable multi-user communication efficiency

Innovation

• Non-uniform phase quantization RIS
• PAT algorithm for single-user
• E-PAT algorithm for multi-user