Low-Complexity Quantum Annealing based Beamforming for Distributed-RIS-Assisted Communication System

Reconfigurable intelligent surface (RIS) is increasingly recognized as a pivotal technology for the sixth-generation communication networks, offering a unique ability to customize the communication environment by programming the passive surface. To fully exploit RISs' potential in improving the coverage and spectral efficiency, we focus on the beamforming design for a distributed-RIS-assisted communication system. However, it usually has the high computational complexity and difficulty to obtain the feasible solution due to non-linear constraints of distributed RISs. To solve this highly non-convex optimization problem of multiple variables, we propose a quantum annealing based method in this paper. Specifically, we firstly transform the original sum-of-log problem into a sub-problem in the form of Ising model by using the fractional programming. Then, we present an adiabatic theorem based algorithm for finding the ground state of the Ising model, and implement it on a Dwave's quantum annealing machine. Numerical results validate the effectiveness of our proposed method, demonstrating that the deployment of quantum annealing can significantly reduce the computational complexity from ON2 to O(N), and obtain an 8% performance gain compared with the typical baselines.