Asymptotically Optimal Closed-Form Phase Configuration of $1$-bit RISs via Sign Alignment

TL;DR

This paper introduces a closed-form phase configuration for 1-bit RISs that guarantees at least half the ideal SNR, is asymptotically optimal, and outperforms iterative and continuous quantization methods.

Contribution

It proposes a novel sign alignment scheme providing a lower bound on SNR and asymptotic optimality for 1-bit RIS phase configuration.

Findings

Achieves at least 50% of the ideal SNR with closed-form configuration.

Outperforms iterative optimization and continuous quantization approaches.

Reduces hardware complexity while maintaining high performance.

Abstract

While Reconfigurable Intelligent Surfaces (RISs) constitute one of the most prominent enablers for the upcoming sixth Generation (6G) of wireless networks, the design of efficient RIS phase profiles remains a notorious challenge when large numbers of phase-quantized unit cells are involved, typically of a single bit, as implemented by a vast majority of existing metasurface prototypes. In this paper, we focus on the RIS phase configuration problem for the exemplary case of the Signal-to-Noise Ratio (SNR) maximization for an RIS-enabled single-input single-output system where the metasurface tunable elements admit a phase difference of $\pi$ radians. We present a novel closed-form configuration which serves as a lower bound guaranteeing at least half the SNR of the ideal continuous (upper bound) SNR gain, and whose mean performance is shown to be asymptotically optimal. The proposed sign alignment configuration can be further used as initialization to standard discrete optimization algorithms. A discussion on the reduced complexity hardware benefits via the presented configuration is also included. Our numerical results demonstrate the efficacy of the proposed RIS sign alignment scheme over iterative approaches as well as the commonplace continuous phase quantization treatment.