School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China.
Sensors (Basel). 2020 Apr 19;20(8):2332. doi: 10.3390/s20082332.
In recent years, unmanned aerial vehicles (UAVs) have been considered an ideal relay platform for enhancing the communication between ground agents, because they fly at high altitudes and are easy to deploy with strong adaptabilities. Their maneuvering allows them to adjust their location to optimize the performance of links, which brings out the relay UAV autonomous mobility control problem. This work addressed the problem in a novel scene with mobile agents and completely unknown wireless channel properties, using only online measured information of received signal strength (RSS) and agent positions. The problem is challenging because of the unknown and dynamic radio frequency (RF) environment cause by agents and UAV maneuvering. We present a framework for both end-to-end communication and multi-agent-inter communication applications, and focus on proposing: (1) least square estimation-based channel approximation with consideration of environment effects and, (2) gradient-based optimal relay position seeking. Simulation results show that considering the environmental effects on channel parameters is meaningful and beneficial in using UAV as relays for the communication of multiple ground agents, and validate that the proposed algorithms optimizes the network performance by controlling the heading of the UAV.
近年来，无人机（UAV）被认为是增强地面代理之间通信的理想中继平台，因为它们在高空飞行，并且易于部署，具有很强的适应性。它们的机动能力使它们能够调整位置，以优化链路的性能，这就提出了中继无人机自主移动性控制问题。这项工作在一个具有移动代理和完全未知无线信道特性的新场景中解决了这个问题，只使用接收到的信号强度（RSS）和代理位置的在线测量信息。由于代理和无人机机动引起的未知和动态射频（RF）环境，这个问题具有挑战性。我们提出了一种适用于端到端通信和多代理间通信应用的框架，并重点提出了：（1）考虑环境影响的基于最小二乘估计的信道近似，以及（2）基于梯度的最优中继位置搜索。仿真结果表明，考虑信道参数对环境的影响对于利用无人机作为多个地面代理通信的中继是有意义和有益的，并验证了所提出的算法通过控制无人机的航向来优化网络性能。
