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Optimal UAV-aided RFET System Design in Presence of Hovering Inaccuracy
IEEE Transactions on Communications ( IF 8.3 ) Pub Date : 2021-01-01 , DOI: 10.1109/tcomm.2020.3025568
Suraj Suman , Swades De

In this paper, performance of unmanned aerial vehicle (UAV)-aided RF energy transfer (RFET) in presence of hovering inaccuracy is investigated. Hovering inaccuracy of UAV comprises of two types of mismatches: Localization mismatch (LM) and Orientation mismatch (OM). Thus, a total of four combinations arise. Their impact on received power at ground deployed sensor node is characterized. For this purpose, a generalized radiation pattern of UAV-mounted transmitter antenna is considered. A closed-form expression of received power at the sensor node is obtained for each of these four cases. An optimization problem is formulated with the objective of optimizing the system parameters, such as transmit power, hovering altitude, and antenna exponent. This problem contains mixed nature of variables, i.e., continuous as well as discrete. To solve this problem, an algorithm, called Hovering Inaccuracy-aware Optimal Charging System Design (HI-OCSD), is proposed to find the optimal system parameters. Through system simulations it is demonstrated that, hovering inaccuracy has notable impact on the performance, as received power at the sensor node reduces significantly in presence of hovering inaccuracy compared to ideal scenario. The effect of LM is more severe than that of OM. Further, a scenario with different level of hovering inaccuracy accounting for different deployment scenarios is considered, and the optimal system parameters are also evaluated. This study reveals that, UAV needs to hover at a relatively higher altitude to overcome the severity of hovering inaccuracy.

中文翻译:

存在悬停不准确性的最佳无人机辅助 RFET 系统设计

在本文中,研究了无人机 (UAV) 辅助射频能量传输 (RFET) 在悬停不准确的情况下的性能。无人机的悬停不准确包括两种类型的不匹配:定位不匹配(LM)和方向不匹配(OM)。因此,总共出现四种组合。它们对地面部署的传感器节点接收功率的影响进行了表征。为此,考虑了无人机安装的发射器天线的广义辐射模式。对于这四种情况中的每一种,都可以获得传感器节点处接收功率的闭合表达式。优化问题的制定目标是优化系统参数,例如发射功率、悬停高度和天线指数。这个问题包含变量的混合性质,即连续和离散。为了解决这个问题,提出了一种称为悬停不准确感知最优充电系统设计(HI-OCSD)的算法来寻找最优系统参数。通过系统仿真表明,悬停不准确性对性能有显着影响,因为与理想情况相比,在存在悬停不准确性的情况下,传感器节点的接收功率显着降低。LM的影响比OM更严重。此外,考虑了不同部署场景下悬停不准确度不同的场景,并评估了最佳系统参数。该研究表明,无人机需要在相对较高的高度悬停,以克服悬停不准确的严重性。建议寻找最优系统参数。通过系统仿真表明,悬停不准确性对性能有显着影响,因为与理想情况相比,在存在悬停不准确性的情况下,传感器节点的接收功率显着降低。LM的影响比OM更严重。此外,考虑了不同部署场景下悬停不准确度不同的场景,并评估了最佳系统参数。该研究表明,无人机需要在相对较高的高度悬停,以克服悬停不准确的严重性。建议寻找最优系统参数。通过系统仿真表明,悬停不准确性对性能有显着影响,因为与理想情况相比,在存在悬停不准确性的情况下,传感器节点的接收功率显着降低。LM的影响比OM更严重。此外,考虑了不同部署场景下悬停不准确度不同的场景,并评估了最佳系统参数。该研究表明,无人机需要在相对较高的高度悬停,以克服悬停不准确的严重性。因为与理想情况相比,在悬停不准确的情况下,传感器节点的接收功率显着降低。LM的影响比OM更严重。此外,考虑了不同部署场景下悬停不准确度不同的场景,并评估了最佳系统参数。该研究表明,无人机需要在相对较高的高度悬停,以克服悬停不准确的严重性。因为与理想情况相比,在悬停不准确的情况下,传感器节点的接收功率显着降低。LM的影响比OM更严重。此外,考虑了不同部署场景下悬停不准确度不同的场景,并评估了最佳系统参数。该研究表明,无人机需要在相对较高的高度悬停,以克服悬停不准确的严重性。
更新日期:2021-01-01
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