Smart Grid NOMA Resource Allocation Optimization Using Quantum Approximate Techniques

For the first time, we transplant the Quantum Approximate Optimization Algorithm (QAOA) from quantum computing labs to the radio links that connect smart meters inside power grids, reframing Non-Orthogonal Multiple Access (NOMA) resource allocation as a combinatorial task within a multi-carrier downlink. The search for optimal pairs is then delegated to QAOA, whose superposition and entanglement resources explore the solution space far more compactly than any classical heuristic. An Improved-QAOA (I-QAOA) algorithm is also proposed, which dynamically adjusts user grouping based on channel state information, significantly enhancing spectral efficiency. Simulation results demonstrate that I-QAOA achieves higher spectral efficiency compared to traditional channel-based and random pairing methods, even at low transmission power, and maintains superior performance at high power levels, offering a promising approach for optimizing smart grid communication networks.