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Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond最新文献

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Non-position-based UAV trajectory optimization for coverage maximization 覆盖最大化的非基于位置的无人机轨迹优化
Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond Pub Date : 2022-10-17 DOI: 10.1145/3555661.3560866
Ye Jiang, D. Zhai, Mengke Yang, Zheng Lin, Yuanzhan Li
{"title":"Non-position-based UAV trajectory optimization for coverage maximization","authors":"Ye Jiang, D. Zhai, Mengke Yang, Zheng Lin, Yuanzhan Li","doi":"10.1145/3555661.3560866","DOIUrl":"https://doi.org/10.1145/3555661.3560866","url":null,"abstract":"In modern communication network, terrestrial base stations (TBSs) are difficult to achieve full coverage of the users in remote areas. As a potential solution, unmanned aerial vehicle (UAV) can assist TBSs to enhance coverage, owing to its mobility and flexibility. In this paper, we concentrate on the UAV trajectory optimization problem for further upgrading network coverage ratio. The scenarios of static and mobile users are considered respectively, where UAV trajectory needs to be optimized to achieve maximum coverage of users. In view of the complexity of user movement, we cannot find users' positions easily with traditional convex optimization ways. Therefore, we propose a DQN-based trajectory optimization algorithm, which can obtain the optimized UAV trajectory, and then achieve maximize the coverage of users. According to the simulation results, we find that the proposed algorithm improves the coverage ratio and is better than the random method in both static and mobile scenarios.","PeriodicalId":151188,"journal":{"name":"Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131556206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
When digital twin meets deep reinforcement learning in multi-UAV path planning 数字孪生结合深度强化学习在多无人机路径规划中的应用
Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond Pub Date : 2022-10-17 DOI: 10.1145/3555661.3560865
Siyuan Li, Xi Lin, Jun Wu, A. Bashir, R. Nawaz
{"title":"When digital twin meets deep reinforcement learning in multi-UAV path planning","authors":"Siyuan Li, Xi Lin, Jun Wu, A. Bashir, R. Nawaz","doi":"10.1145/3555661.3560865","DOIUrl":"https://doi.org/10.1145/3555661.3560865","url":null,"abstract":"Unmanned aerial vehicles (UAVs) path planning is one of the promising technologies in the fifth-generation wireless communications. The gap between simulation and reality limits the application of deep reinforcement learning (DRL) in UAV path planning. Therefore, we propose a digital twin-based deep reinforcement learning training framework. With the help of digital twin, DRL model can be trained more effectively deployed to real UAVs. In this training framework, we propose a deep deterministic policy gradient (DDPG) based multi-UAV path planning algorithm. Based on decomposed actor structure in DRL, we design a pooling-based combined LSTM network to better understand different state information in a multi-UAV path planning task. Moreover, we also establish a digital twin platform for multi-UAV system, which has a high degree of simulation and visualization. The simulation result shows that the proposed algorithm can achieve higher mean rewards, and outperforms DDPG in average arrival rate by more than 30%.","PeriodicalId":151188,"journal":{"name":"Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125017318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond 第五届国际ACM移动通信研讨会论文集:无人机辅助无线通信5G及以后
Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond Pub Date : 1900-01-01 DOI: 10.1145/3555661
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引用次数: 0
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