摘要
无人机的灵活移动性在移动边缘计算系统中引起了广泛的关注。然而,空中窃听者的存在使它的安全传输仍然面对巨大的挑战。为了解决高安全通信速率与低能耗之间的矛盾,引入安全通信能效这一概念,即无人机安全通信传输速率与无人机能耗之间的比值。首先,在满足给定任务时延、无人机的CPU计算频率以及任务卸载率的约束下,提出一种最大化安全通信能效的卸载策略,即联合优化合法无人机悬停位置、CPU计算频率分配以及区分计算任务复杂度的卸载策略;同时从物理层安全角度提升了无人机-移动边缘计算场景下的安全通信。其次,由于该策略是一个复杂的非凸问题,将其解耦为3个子问题,通过块坐标下降法与连续凸逼近(SCA)相结合的全局优化算法来求解该非凸问题。仿真结果表明,针对不同任务复杂度的系统,所提策略都能在满足地面终端卸载需求的同时,平衡整体的通信安全性能和能耗之间的关系,并提高安全通信能效。
The flexible mobility of the unmanned aerial vehicle(UAV)has attracted widespread attention in the mobile edge computing(MEC)system.However,the existence of eavesdroppers in the air makes it a huge challenge for its secure transmission.In order to solve the contradiction between high safe communication rate and low energy consumption,the concept of security communication energy efficiency was introduced,that was,the ratio between UAV safe communication transmission rate and UAV energy consumption.Firstly,to subject the task delay constraint,limited UAV CPU frequency and task offloading rate constraint,an offloading strategy was proposed to maximize the energy efficiency of secure communication by jointly optimizing the legal UAV hover location,CPU frequency allocation and distinguishing the complexity of computing tasks,while improving the security communication in the UAV-MEC scenario from the perspective of physical layer security.Secondly,to address the non-convex optimization problem,it was decomposed into three sub-problems that were solved with block coordinate descent and the successive convex approximation(SCA)methods respectively.The simulation results show that,with different task complexity,the proposed strategy can balance the relationship between the overall secure communication performance and energy consumption,while meeting the offloading requirements of ground terminals.And then it improves secrecy energy efficiency.
作者
余雪勇
邱礼翔
宋家宁
朱洪波
YU Xueyong;QIU Lixiang;SONG Jianing;ZHU Hongbo(College of Telecommunications and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;Jiangsu Key Laboratory of Wireless Communications,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)
出处
《通信学报》
EI
CSCD
北大核心
2023年第3期45-54,共10页
Journal on Communications
基金
国家自然科学基金资助项目(No.92067201)
江苏省重点研发计划基金资助项目(No.BE2020084-4)。
关键词
移动边缘计算
无人机安全通信
能耗优化
资源分配
位置优化
mobile edge computing
UAV secure communication
energy consumption optimization
resource allocation
location optimizing
