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Trajectory and Resource Optimization in OFDM-Based UAV-Powered IoT Network

机译:基于OFDM的UV供电的IOT网络轨迹和资源优化

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The Internet of Things (IoT) is playing an increasingly vital role in multiple industries and our everyday life. A pressing practical problem of IoT devices (IoT-Ds) is their explosive growth of connectivity which leads to large energy consumption. One of the most promising solutions to achieve a sustainable green IoT network is unmanned aerial vehicle (UAV) enabled wireless power transfer (WPT) due to its flexibility, mobility and cost advantage. In this paper, we propose an UAV-powered IoT network based on Orthogonal Frequency Division Multiplexing (OFDM). In the proposed network, two ground nodes (GNs) are powered by two UAVs through down link WPT. In the uplink, the data collected by GNs are transmitted to the corresponding UAVs with the harvested energy by utilizing orthogonal subcarriers, which can effectively avoid the interference. UAVs' trajectories and resource allocation are optimized to maximize the sum average transmission rate of two GNs while ensuring the minimum average transmission rate of each GN. In this paper, we utilize successive convex programming (SCP) technique to solve the proposed optimization problem. Simulation results show that our proposed scheme achieves larger sum average transmission rate than the benchmark schemes.
机译:事情互联网(物联网)在多个行业和日常生活中发挥着越来越重要的作用。 IOT设备(IOT-DS)的压制实际问题是它们的连接性爆炸性增长,导致大量的能耗。实现可持续绿色物联网网络的最有希望的解决方案之一是无人驾驶飞行器(UAV),由于其灵活性,移动性和成本优势,使无线电力传输(WPT)能够。在本文中,我们提出了一种基于正交频分复用(OFDM)的UV供电的物联网网络。在所提出的网络中,两个地点节点(GNS)通过两个无人机通电通过Down Link WPT。在上行链路中,通过利用正交的子载波,由GNS收集的数据与收获的能量一起发送到相应的UV,这可以有效地避免干扰。优化了无人机的轨迹和资源分配,以最大化两个GNS的总和平均传输速率,同时确保每个GN的最小平均传输速率。在本文中,我们利用连续凸编程(SCP)技术来解决所提出的优化问题。仿真结果表明,我们的建议方案实现了比基准计划更大的总和平均传输速率。

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