1673-159X

CN 51-1686/N

无线充电无人机路径规划和通信资源管控算法

A Path Planning and Communication Resource Management Algorithm for the Wireless Charging UAV

  • 摘要: 无人机因其低成本、部署灵活等优点而被广泛应用在无线通信系统中,有望在未来6 G通信网络中扮演重要角色,但无人机受尺寸和重量的限制导致其系统安全信息容量有限。此外,无人机与地面用户之间的无线信道的广播和视距传输特性导致空地通信极易被地面非法用户窃听。因此,本文基于无线能量传输和物理层安全技术提出一种无线充电无人机路径规划和通信资源管控算法,该算法通过联合优化无人机的无线充电时间、飞行轨迹和发射功率使系统安全信息容量最大化。具体地,首先提出如何让电池容量受限的无人机在飞行周期内使系统安全信息容量最大化的问题;为了求解此非凸优化问题,将其转化为具有光滑目标函数的等价问题;然后,利用交替优化和连续凸近似技术求解此等价问题,并提出一种低复杂度的无人机路径规划和通信资源管控算法。仿真表明,与传统固定无人机路径、发射功率和充电时间的算法相比,本文所提算法能明显提高系统安全信息容量。

     

    Abstract: Unmanned aerial vehicles (UAVs) have been widely used in the wireless communications, and are expected to play an important role in the sixth-generation (6G) wireless networks. However, due to the size and weight limitation of UAV, the system safety information capacity is limited. In addition, the broadcast and line-of-sight transmission characteristics of the wireless channel between UAVs and ground users make the air-ground communication easy to be eavesdropped by illegal ground users. To address these challenges, we adopt the wireless power transfer and physical layer security technique in this paper. We maximize the total secrecy rate over a finite time horizon by jointly optimizing the wireless charging duration, the trajectory and transmit power of the UAV subject to the energy-harvesting causal, maximuming flying speed, and limiting battery size constraints. To deal with this non-convex problem, we first transform this problem into an equivalent problem with smooth objective function, and then propose an efficient trajectory design and communications resource allocation algorithm to solve this reformulated problem by leveraging the alternating optimization and successive convex programming (SCP). Extensive simulations are carried out to demonstrate the idea and the results show that proposed algorithm outperforms the benchmark strategies without the trajectory optimization and/or power control and/or battery.

     

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