子空间受限的QAOA与广义Dicke态用于5G CBRS网络多通道分配
Subspace-Confined QAOA with Generalized Dicke States for Multi-Channel Allocation in 5G CBRS Networks
AI总结：
针对5G CBRS网络多通道分配问题，提出子空间受限QAOA算法，利用广义Dicke态和Johnson图约束，实现高效低冲突配置。
摘要：
在公民宽带无线电服务（CBRS）频段中实现高效的频谱共享对于最大化5G网络容量至关重要，特别是在高流量基站需要同时访问多个通道时。标准的量子近似优化算法（QAOA）通过惩罚项施加多通道约束，因此大部分探索的希尔伯特空间对应于无效分配。我们提出了一种针对CBRS多通道分配的子空间受限QAOA，其中每个节点的通道寄存器初始化在广义Dicke态中，并在寄存器内进行XY混合同步。该算法将动态限制在Johnson图的张量积中，精确编码每个节点的汉明重量约束。对于具有24个量子比特的8节点CBRS干扰图，有效搜索空间从完整的希尔伯特空间大小$2^{24}$减少到2916个可行配置。在该子空间内，算法迅速收敛到低冲突分配，而无需大惩罚系数。在最多八个节点的实例模拟中，所提出的算法实现了接近最优的冲突水平，并在可行性方面优于标准惩罚基于QAOA和贪心经典启发式方法。具有去极化通道的噪声模拟进一步表明，约束保持结构在NISQ相关误差范围内保持高可行性比率。
英文摘要：
Efficient spectrum sharing in the Citizens Broadband Radio Service (CBRS) band is essential for maximizing 5G network capacity, particularly when high-traffic base stations require simultaneous access to multiple channels. Standard formulations of the Quantum Approximate Optimization Algorithm (QAOA) impose such multi-channel constraints using penalty terms, so most of the explored Hilbert space corresponds to invalid assignments. We propose a subspace-confined QAOA tailored to CBRS multi-channel allocation, in which each node-wise channel register is initialized in a Generalized Dicke state and evolved under an intra-register XY mixer. This ansatz confines the dynamics to a tensor product of Johnson graphs that exactly encode per-node Hamming-weight constraints. For an 8-node CBRS interference graph with 24 qubits, the effective search space is reduced from the full Hilbert space of size $2^{24}$ to 2916 feasible configurations. Within this subspace, the algorithm converges rapidly to low-conflict assignments without large penalty coefficients. Simulations on instances with up to eight nodes show that the proposed ansatz achieves near-optimal conflict levels and consistently outperforms standard penalty-based QAOA and a greedy classical heuristic in terms of feasibility. Noise simulations with depolarizing channels further indicate that the constraint-preserving structure maintains a high feasibility ratio in NISQ-relevant error regimes.
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