Subspace-Confined QAOA with Generalized DickeStates for Multi-Channel Allocation in 5G CBRSNetworks

Efficient spectrum sharing in the Citizens Broadband Radio Service (CBRS) band is essential for maximizing 5G networkcapacity, particularly when high-traffic base stations require simultaneous access to multiple channels. Standard formulationsof the Quantum Approximate Optimization Algorithm (QAOA) impose such multi-channel constraints using penalty terms, somost of the explored Hilbert space corresponds to invalid assignments. We propose a subspace-confined QAOA tailored toCBRS multi-channel allocation, in which each node-wise channel register is initialized in a Generalized Dicke state and evolvedunder an intra-register XY mixer. This ansatz confines the dynamics to a tensor product of Johnson graphs that exactly encodeper-node Hamming-weight constraints. For an 8-node CBRS interference graph with 24 qubits, the effective search space isreduced from the full Hilbert space of size 2^24 to 2,916 feasible configurations. Within this subspace, the algorithm convergesrapidly to low-conflict assignments without large penalty coefficients. Simulations on instances with up to eight nodes showthat the proposed ansatz achieves near-optimal conflict levels and consistently outperforms standard penalty-based QAOAand a greedy classical heuristic in terms of feasibility. Noise simulations with depolarizing channels further indicate that theconstraint-preserving structure maintains a high feasibility ratio in NISQ-relevant error regimes.