摘要:

In this work, we address joint optimization of unmanned aerial vehicle (UAV) trajectories and user communication scheduling for a dual-UAV enabled secure communication system, where one UAV moves around to communicate with multiple users on the ground in a time division multiple access (TDMA) mode while the other UAV in the area flies to jam the eavesdroppers on the ground to protect communications of the desired users. Specifically, we maximize the minimum worst case secrecy rate among the users within each period by jointly adjusting UAV trajectories and user scheduling under the maximum UAV speed constraints, the UAV return constraints, the UAV collision avoidance constraints, and the discrete binary constraints on user scheduling variables. Since the resulting optimization problem is very challenging due to its highly nonlinear objective function and nonconvex constraints, we first transform this problem into a more tractable form. In particular, the discrete binary constraints are equivalently converted to a number of equality constraints. We then develop a novel joint optimization algorithm based on the penalty concave-convex procedure (P-CCCP) technique to solve the resultant problem. The simulation results show that the proposed joint optimization algorithm achieves significantly better performance than the conventional algorithms.

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附主讲人简介：

蔡云龙，浙江大学信电学院副教授，IEEE高级会员，于 2004 年 7 月在北京交通大学获学士学位，2006 年 3 月在英国萨里大学获硕士学位，2010年 1 月在英国约克大学获电子工程博士学位。2010 年 2 月至2011 年 1 月在法国国立工艺学院信号处理实验室任博士后研究员。 2016 年 8 月至 2017 年 1 月在美国佐治亚理工学院电子与计算机系做访问学者。2011 年 2 月起加入浙江大学信电学院任讲师，于 2013 年 12 月晋升副教授。长期从事基本通信理论，通信信号处理，以及优化理论等方面的研究。当前主要研究方向为毫米波大规模天线混合A/D波束赋形优化设计，无人机通信系统优化设计，人工智能技术在下一代无线通信中应用等。至今已发表SCI期刊论文40余篇，其中包括IEEE期刊（TSP, JSAC,TCOM, TWC,JSTSP等）近30篇，国际会议论文60余篇。长期担任各类 IEEE期刊的审稿人。自 2018年起受邀担任信号处理与通信领域国际知名期刊IEEE Signal Processing Letters编委。