Efficient Quantum Algorithm for Phase Optimization of 1-Bit RIS-Assisted MIMO Communication System

We propose a Quantum Approximate Optimization Algorithm with a deterministic linear ramp schedule (QAOA-LR) for phase optimization of a 1-bit RIS-assisted MIMO communication system. Each RIS element is restricted to a binary phase shift of 0 or {\pi}, turning the passive beamforming design problem with N elements into a combinatorial optimization problem over 2^N configurations. Instead of running a classical optimizer, QAOA-LR uses a fixed linear ramp to set the variational parameters across p layers and finds the best scale via a simple one-dimensional grid search over a single parameter. Monte Carlo simulations over Rayleigh-fading MIMO channels confirm that QAOA-LR closely tracks the optimum maximum-likelihood (ML) solution. Furthermore, the proposed algorithm reduces the computational complexity compared with classical optimization, and real hardware experiments on the IBM Quantum processor confirm near-ML capacity performance with polynomial scaling of quantum processing unit execution time as the number of RIS elements increases.