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UAV-assisted wireless powered Internet of Things: Joint trajectory optimization and resource allocation

机译:无人机辅助的无线物联网:联合轨迹优化和资源分配

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摘要

Due to affordable price, high mobility and flexible maneuverability, Unmanned Aerial Vehicle (UAV)assisted communication can play an important role in the deployment of the Internet of Things (IoT) in emergency. Since UAV network performance is highly dependent on UAV deployment location, trajectory design becomes the research hotspot in UAV-assisted communication. To this end, a UAV-assisted multi carrier wireless powered communication model is proposed for IoT scenarios in this paper. Specifically, as an aerial base station, the UAV transmits Orthogonal Frequency Division Multiplexing (OFDM) signals to IoT nodes, while IoT nodes decode information and harvest energy from the signals. Afterwards, IoT nodes transmit information to the UAV by using the harvested energy. A joint UAV trajectory optimization and resource allocation scheme based on OFDM is proposed. The aim is to maximize the minimum achievable rate in the uplink among all IoT nodes by jointly optimizing UAV trajectory, subcarrier, power and subsloT allocation, subject to the achievable sum rate of all IoT nodes in the downlink. Due to the non-convexity and complexity of the formulated optimization problem, an alternative iteration algorithm is proposed to deal with the problem. Simulation results that the proposed algorithm can optimize the UAV trajectory and adapt to the node movement. Compared with conventional resource allocation schemes, the proposed scheme not only significantly enhances the minimum achievable rate, but also works well for two flight modes. (C) 2019 Elsevier B.V. All rights reserved.
机译:由于价格合理,机动性高,机动性强,无人机在紧急情况下的物联网(IoT)部署中可以发挥重要作用。由于无人机的网络性能高度依赖于无人机的部署位置,因此轨迹设计成为无人机辅助通信中的研究热点。为此,本文针对物联网场景提出了无人机辅助的多载波无线供电通信模型。具体来说,作为空中基站,无人机将正交频分复用(OFDM)信号发送到IoT节点,而IoT节点则对信息进行解码并从信号中获取能量。之后,物联网节点利用所收集的能量将信息传输到无人机。提出了一种基于OFDM的联合无人机航迹优化与资源分配方案。目的是通过联合优化UAV轨迹,子载波,功率和subsloT分配来最大化所有IoT节点之间的上行链路中的最小可实现速率,具体取决于下行链路中所有IoT节点可实现的总速率。由于所提出的优化问题的非凸性和复杂性,提出了一种替代迭代算法来解决该问题。仿真结果表明,该算法可以优化无人机航迹并适应节点运动。与传统的资源分配方案相比,该方案不仅显着提高了最低可实现率,而且在两种飞行模式下均能很好地工作。 (C)2019 Elsevier B.V.保留所有权利。

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