The development of quantum networks (QNs) relies on efficient mechanisms for distributing entanglement among multiple quantum users (QUs) under practical system constraints. This paper investigates the problem of entanglement rate maximization in a dual-connectivity (DC) wireless quantum network comprising multiple quantum base stations (QBSs). Under the DC architecture, each QU can associate with up to two QBSs, thereby enhancing resource utilization compared to conventional single-connectivity (SC) schemes. The joint QBS-QU association and entanglement generation rate allocation problem is formulated as a mixed-integer nonlinear programming problem that incorporates practical constraints, including limited QBS entanglement generation capacity as well as heterogeneous minimum entanglement rate demands and fidelity requirements for QUs. To efficiently solve this challenging problem, an alternating optimization (AO) algorithm is developed, which decomposes the original formulation into entanglement rate allocation and association subproblems. Simulation results demonstrate that the proposed DC architecture significantly outperforms SC schemes, while the AO algorithm achieves near-optimal performance with substantially reduced computational complexity.

翻译：量子网络的发展依赖于在实际系统约束下，在多个量子用户之间高效分发纠缠的机制。本文研究了包含多个量子基站的双连接无线量子网络中纠缠速率最大化的问题。在双连接架构下，每个量子用户最多可关联两个量子基站，从而相比传统单连接方案提升了资源利用率。联合的量子基站-量子用户关联与纠缠生成速率分配问题被建模为一个混合整数非线性规划问题，其中纳入了实际约束，包括量子基站有限的纠缠生成能力，以及量子用户异构的最小纠缠速率需求和保真度要求。为高效求解这一挑战性问题，本文开发了一种交替优化算法，该算法将原始问题分解为纠缠速率分配和关联两个子问题。仿真结果表明，所提出的双连接架构显著优于单连接方案，同时交替优化算法能以大幅降低的计算复杂度实现接近最优的性能。