{"title":"多无人机网络中qos驱动的无人机视频传输","authors":"Kesong Wu, Pengbin Yang, Xianbin Cao, Zongyang Yu","doi":"10.1109/ICCC57788.2023.10233431","DOIUrl":null,"url":null,"abstract":"This paper is concerned with the issue of improving video subscribers’ quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing works, we characterize subscribers’ QoE by video bitrates, latency, and frame freezing and propose to improve their QoE by energy-efficiently and dynamically optimizing the multi-UAV network in terms of serving UAV selection, UAV trajectory, and UAV transmit power. The dynamic multi-UAV network optimization problem is formulated as a challenging sequential-decision problem with the goal of maximizing subscribers’ QoE while minimizing the total network power consumption, subject to some physical resource constraints. We propose a novel network optimization algorithm to solve this challenging problem, in which a Lyapunov technique is first explored to decompose the sequential-decision problem into several repeatedly optimized sub-problems to avoid the curse of dimensionality. To solve the sub-problems, iterative and approximate optimization mechanisms with provable performance guarantees are then developed. Simulation results show that the proposed algorithm can effectively improve the QoE of subscribers and is 45.69% more energy-efficient than benchmarks.","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"QoE-Driven UAV Video Transmission in a Multi-UAV Network\",\"authors\":\"Kesong Wu, Pengbin Yang, Xianbin Cao, Zongyang Yu\",\"doi\":\"10.1109/ICCC57788.2023.10233431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is concerned with the issue of improving video subscribers’ quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing works, we characterize subscribers’ QoE by video bitrates, latency, and frame freezing and propose to improve their QoE by energy-efficiently and dynamically optimizing the multi-UAV network in terms of serving UAV selection, UAV trajectory, and UAV transmit power. The dynamic multi-UAV network optimization problem is formulated as a challenging sequential-decision problem with the goal of maximizing subscribers’ QoE while minimizing the total network power consumption, subject to some physical resource constraints. We propose a novel network optimization algorithm to solve this challenging problem, in which a Lyapunov technique is first explored to decompose the sequential-decision problem into several repeatedly optimized sub-problems to avoid the curse of dimensionality. To solve the sub-problems, iterative and approximate optimization mechanisms with provable performance guarantees are then developed. Simulation results show that the proposed algorithm can effectively improve the QoE of subscribers and is 45.69% more energy-efficient than benchmarks.\",\"PeriodicalId\":191968,\"journal\":{\"name\":\"2023 IEEE/CIC International Conference on Communications in China (ICCC)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE/CIC International Conference on Communications in China (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCC57788.2023.10233431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCC57788.2023.10233431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
QoE-Driven UAV Video Transmission in a Multi-UAV Network
This paper is concerned with the issue of improving video subscribers’ quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing works, we characterize subscribers’ QoE by video bitrates, latency, and frame freezing and propose to improve their QoE by energy-efficiently and dynamically optimizing the multi-UAV network in terms of serving UAV selection, UAV trajectory, and UAV transmit power. The dynamic multi-UAV network optimization problem is formulated as a challenging sequential-decision problem with the goal of maximizing subscribers’ QoE while minimizing the total network power consumption, subject to some physical resource constraints. We propose a novel network optimization algorithm to solve this challenging problem, in which a Lyapunov technique is first explored to decompose the sequential-decision problem into several repeatedly optimized sub-problems to avoid the curse of dimensionality. To solve the sub-problems, iterative and approximate optimization mechanisms with provable performance guarantees are then developed. Simulation results show that the proposed algorithm can effectively improve the QoE of subscribers and is 45.69% more energy-efficient than benchmarks.