This article proposes a cooperative friendly jamming framework for swarm unmanned aerial vehicle (UAV)-assisted amplify-and-forward (AF) relaying networks with wireless energy harvesting. Due to the limited energy of the UAVs, we develop a collaborative time-switching relaying protocol which allows the UAVs to collaborate to harvest wireless energy, relay information, and jam the eavesdropper. To evaluate the secrecy rate, we derive the secrecy outage probability (SOP) for two popular detection techniques at the eavesdropper, i.e., selection combining and maximum-ratio combining. Monte Carlo simulations are then used to validate the theoretical SOP derivation and to show the effectiveness of the proposed framework in terms of SOP as compared with the conventional amplify-and-forward relaying system. Using the derived SOP, one can obtain engineering insights to optimize the energy harvesting time and the number of UAVs in the swarm to achieve a given secrecy protection level. The analytical SOP derived in this work can also be helpful in future UAV secure-communications optimizations (e.g., trajectory, locations of UAVs). As an example, we present a case study to find the optimal corridor to locate the swarm so as to minimize the system SOP.
翻译:本文建议为使用无线能源收集的无人驾驶飞行器(UAV)辅助扩频和前向式转发网络建立一个合作友好干扰框架。由于无人驾驶飞行器的能量有限,我们开发了一个协作时间转换转发协议,使无人驾驶飞行器能够合作获取无线能源、中继信息并干扰窃听器。为了评估保密率,我们为窃听器中两种流行的探测技术(即混合和最大拉比组合)得出保密性中断概率(SOP ) 。随后,Monte Carlo模拟用于验证理论性SOP衍生结果,并显示拟议框架在SOP方面与常规的超前继电器系统相比的有效性。利用衍生的SOP,人们可以获取工程洞察力,以优化节能采集时间和暖中无人驾驶飞行器的数量,以达到保密保护水平。这项工作中的分析SOP结果还有助于未来的UAV安全通信(e.g.Carlo 模拟) 优化SOP系统,作为目前最佳轨道,我们找到最佳轨道。