摘要
Satellite-assisted quantum network (SQN) is emerging as a promising solution to overcome the distance limitations of ground-based fiber quantum network (QN). However, each satellite and ground station has a limited number of transmitters and receivers, respectively, and the Entanglement Distribution Rate (EDR) decreases with the distance between satellites and ground stations, highlighting the need for effective resource allocation to serve requests in the SQN. In this paper, we present a novel optimization problem, termed ESOP, which aims to maximize the total EDR in the network while simultaneously considering the resource capacities of both satellites and ground stations, as well as the fidelity requirements of individual requests. To solve ESOP, we propose a (2 + epsilon)-approximation algorithm, AESOP, which combines a greedy approach with a tailored local search. Simulation results show that AESOP achieves up to 64% improvement in total EDR compared to the existing method.