基于改进蚁群算法的量子无线通信网络多跳传输研究

Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition Pub Date : 2022-09-23 DOI:10.1145/3573942.3573985

Xinyuan Mao, Min Nie, Guang Yang

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引用次数: 0

摘要

首先，提出了一种改进的蚁群算法来优化量子连通性，并对量子无线多跳网络中的纠缠样例分布节点部署进行了研究和分析。在此基础上，本文将遗传算法与改进蚁群算法(ga - qcan)相结合，可以有效缓解蚁群算法由于缺乏初始信息素而导致效率低下的问题。仿真结果表明，qcan和ga - qcan均显著提高了量子连通性，ga - qcan比qcan平均提高了32.1%。

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Research on Multi-hop Transmission in Quantum Wireless Communication Networks Based on Improved Ant Colony Algorithm

Firstly, an improved ant colony algorithm (QCANT) is proposed to optimize quantum connectivity, and the entanglement example distribution node deployment in quantum wireless multi-hop networks is studied and analyzed. On this basis, this paper combined genetic algorithm with improved ant colony algorithm (GA-QCANT), which can effectively alleviate the problem of low efficiency of ant colony algorithm due to the lack of initial pheromone. Simulation results show that both QCANT and GA-QCANT improves quantum connectivity significantly, and GA-QCANT improves quantum connectivity by an average of 32.1% compared to QCANT.

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Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition

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