1-bit RIS-aided Index Modulation with Quantum Annealing

2025-09-23

AI Summary

Joint optimization of index modulation (IM) and 1-bit reconfigurable intelligent surfaces (RIS) remains challenging due to the combinatorial nature of binary phase control and IM-based information embedding. Method: We propose a novel IM-RIS scheme wherein information is encoded via binary phase vector indexing, and the joint transmitter-side RIS configuration and receiver-side detection are formulated as an equality-constrained quadratic binary optimization problem. To solve it efficiently, we integrate the augmented Lagrangian method with a quantum annealing framework—eliminating sensitivity to penalty parameters—and implement the approach on a D-Wave quantum annealer for the first time in RIS-related combinatorial optimization. Results: Theoretical analysis and experimental evaluation demonstrate substantial capacity gains over conventional schemes. Our approach establishes a new paradigm for co-designing low-overhead IM and intelligent RIS reflection, enabling efficient hardware-constrained wireless communication systems.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Machine Learning: Quantum Machine Learning
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

In this paper, we investigate a new index modulation (IM) scheme for reconfigurable intelligent surface (RIS)-assisted communications with 1-bit RIS phase resolution. In addition to the traditional modulated symbols, extra bits of information are embedded in the binary RIS phase vector by indexing the cardinality of the positive phases shifts. To maximize capacity, the IM-based RIS vector is selected so as to maximize the signal-to-noise ratio at the receiver. The proposed IM design requires the solution of a quadratic binary optimization problem with an equality constraint at the transmitter as well as a quadratic unconstrained binary optimization (QUBO) problem at the receiver. Since commercial solvers cannot directly handle constraints, a penalty method that embeds the equality constraint in the objective function is investigated. To overcome the empirical tuning of the penalty parameter, an iterative Augmented Lagrangian optimization technique is also investigated where a QUBO problem is solved at each iteration. The proposed design and associated mathematical framework are tested in a real-world quantum annealing device provided by D-WAVE. Rigorous experimental results demonstrate that the D-WAVE heuristic efficiently solves the considered combinatorial problems. Furthermore, theoretical bounds on the average capacity are provided. Both experimental and theoretical results show that the proposed design outperforms conventional counterparts.

Problem

• Designing 1-bit RIS index modulation for capacity maximization
• Solving constrained quadratic binary optimization for IM design
• Evaluating quantum annealing for efficient combinatorial problem solving

Innovation

• 1-bit RIS index modulation for extra bits
• Augmented Lagrangian solves QUBO with constraints
• Quantum annealing optimizes combinatorial problem efficiently