1-bit RIS-aided Index Modulation with Quantum Annealing Maximizes Capacity Using Quadratic Unconstrained Binary Optimization

Reconfigurable intelligent surfaces offer exciting possibilities for enhancing wireless communication, and researchers are now exploring how to maximise their potential through innovative signal encoding techniques. Ioannis Krikidis from the University of Cyprus, Constantinos Psomas from the European University Cyprus, and Gan Zheng from the University of Warwick, along with their colleagues, investigate a new approach called index modulation, which embeds extra information within the surface’s configuration. This work introduces a system where the surface’s phase shifts not only direct the signal, but also carry additional data, significantly increasing communication capacity. By formulating the problem as a complex optimisation challenge and utilising quantum annealing, the team demonstrates a practical method for selecting the optimal surface configuration, achieving superior performance compared to conventional techniques and paving the way for more efficient wireless networks.

A central focus is solving complex optimization problems related to beamforming, channel estimation, and resource allocation within these systems, with a particular interest in developing computationally efficient algorithms for real-world implementation. The research highlights RIS as a promising technology for enhancing wireless communication coverage, capacity, and energy efficiency. Scientists are investigating quantum annealing to solve challenging optimization problems inherent in wireless communication and RIS design, employing hybrid approaches that combine classical algorithms with quantum annealing to leverage the strengths of both computational methods.

Researchers are developing techniques to mitigate limitations of current quantum annealers, such as limited qubit connectivity and noise, through careful problem formulation and embedding techniques. Specific techniques under investigation include converting optimization problems into a format suitable for quantum annealers, employing augmented Lagrangian methods, and utilizing random rotation-based schemes for RIS configuration. Variational inference is also being explored for channel estimation, bridging the gap between theoretical advancements and practical implementation for more efficient and reliable wireless networks.

RIS Index Modulation and Optimization Techniques

Scientists have developed a novel communication scheme for RIS-assisted systems, employing index modulation (IM) to embed additional information within the reflected signal by utilizing RIS elements to modify the phase. By carefully selecting the RIS configuration, researchers maximize the signal-to-noise ratio at the receiver, requiring the solution of complex optimization problems formulated as quadratic binary optimization problems and equivalent QUBO formulations. Recognizing the limitations of standard solvers when dealing with constrained optimization, the team investigated a penalty method, embedding the equality constraint directly into the objective function, and further refined this using an iterative Augmented Lagrangian optimization technique. To validate their theoretical framework, researchers tested the design using a real-world quantum annealing device, demonstrating the efficiency of the D-WAVE heuristic in solving the combinatorial problems inherent in the optimization process. This study pioneers a method for conveying information not just through traditional signal modulation, but also through the indexing of RIS phase shifts, effectively increasing spectral efficiency. Experimental results confirm that the proposed IM design outperforms conventional communication schemes, and the team established theoretical bounds on the average capacity achievable with this approach, paving the way for more efficient and reliable wireless communication systems by leveraging low-resolution phase shifters and quantum annealing techniques.

Index Modulation with Reconfigurable Intelligent Surfaces

Scientists have developed a new communication scheme integrating index modulation (IM) with reconfigurable intelligent surfaces (RIS), utilizing 1-bit phase resolution to embed extra information within the binary RIS phase vector by indexing the cardinality of positive phase shifts. The proposed design requires solving a quadratic binary optimization problem at the transmitter and a quadratic unconstrained binary optimization (QUBO) problem at the receiver to maximize signal-to-noise ratio. To overcome limitations of commercial solvers handling constraints, researchers investigated a penalty method embedding the equality constraint within the objective function, and further refined this using an iterative Augmented Lagrangian optimization technique, solving a QUBO problem at each iteration to improve performance. The entire system and associated mathematical framework were rigorously tested using a real-world quantum annealing device, demonstrating the efficiency of the D-WAVE heuristic in solving the complex combinatorial problems inherent in this design. Measurements confirm that this IM-based RIS design outperforms conventional communication schemes, and theoretical bounds on average capacity were also established, supporting the experimental findings. This research addresses a gap in the literature by exploring low-bit resolution RIS communications with IM techniques, highlighting the potential of integrating quantum computing architectures, specifically quantum annealing, to address the computational demands of advanced wireless technologies and unlock new capabilities in communication systems.

RIS Modulation via Quantum Annealing

This research presents a new index modulation scheme for reconfigurable intelligent surface (RIS)-assisted communication systems, designed to enhance signal capacity through innovative use of RIS phase shifts. By embedding additional information within the binary RIS phase vector, the team has developed a method that surpasses conventional approaches to maximizing signal-to-noise ratio at the receiver, formulating the optimization problems as both quadratic binary optimization problems and equivalent QUBO formulations suitable for implementation on quantum annealing hardware. Experimental validation using a real-world annealing device demonstrates the efficiency of the proposed heuristic in solving these complex combinatorial problems, with both theoretical analysis and practical results confirming that this design outperforms existing methods for RIS-assisted communication. The team successfully implemented and tested their scheme, demonstrating a tangible improvement in communication system performance. The authors acknowledge that the requirement for global channel state information at both the transmitter and receiver represents a practical limitation, and that the complexity of the optimization problems increases with the number of RIS elements, potentially limiting scalability. Future research directions include exploring methods to reduce the reliance on perfect channel state information and investigating techniques to simplify the optimization process for larger RIS deployments.