Energy-Efficiency Computation Offloading Strategy in UAV Aided V2X Network With Integrated Sensing and Communication

作     者：Liu, Qian Liang, Hairong Luo, Rui Liu, Qilie 

作者机构：Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Mobile Commun Technol Chongqing 400065 Peoples R China Nanchang Inst Technol Coll Elect & Informat Engn Nanchang 330000 Jiangxi Peoples R China 

出 版 物：《IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY》 (IEEE open J. Commun. Soc.)

年 卷 期：2022年第3卷

页      面：1337-1346页

核心收录：

基　　金：Basic and Advanced Research Projects of CSTC [cstc2019jcyj-zdxmX0008] Science and Technology Research Program of Chongqing Municipal Education Commission [KJZD-K201900605] Doctoral Initial Funding of Chongqing University of Posts and Telecommunications [A2021-195(E012A2021195)] 

主　　题：Task analysis Data integration Intelligent sensors Energy consumption Computational modeling Autonomous aerial vehicles Vehicle-to-everything Unmanned aerial vehicles vehicular-to-everything mobile computing integrated sensing and communication successive convex approximation 

摘      要：Integrated Sensing and Communications (ISAC) technology can jointly design radio sensing and communication functionalities, which enable 6G Ere to have the ability to see the physical world rather than communication-only. Benefitting from ISAC, vehicular-to-everything (V2X) networks may efficiently complete high-precision traffic environment perception. Furthermore, with the assistance of flexibly deployed Unmanned Aerial Vehicles (UAVs), the V2X networks overcome the limited sensing range of sensors equipped on a vehicle and guarantee safe driving. This paper proposes an energy-efficient computation offloading strategy for multiple sensor data fusion in UAV Aided V2X Network supported by Integrated Sensing and Communication. Firstly, a vehicle-UAV cooperative perception architecture is proposed to perceive a wide range of traffic environments. Secondly, we introduce a computation offloading strategy jointly considering offloading decisions and dynamic computing resource allocation. Finally, a successive convex approximation (SCA) algorithm transforms a non-convex formulation problem into a tractable convex approximation problem. The simulation results show that the strategy proposed in this paper reduces the UAV energy consumption and data fusion task processing delay.