基于NOMA的无人机数据采集网络剩余能量最大化算法：轨迹优化和资源分配

朱浩; 郝建军; 郭一珺

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Residual Energy Maximization for NOMA-Enabled UAV Data Collection Network: Trajectory Optimization and Resource Allocation

首发时间：2022-03-17

Zhu Hao ¹
Zhu Hao (1996-), male, major research direction: UAV communication.
Hao Jianjun ¹
Hao Jianjun (1969-), male, associate professor, major research direction: articial intelligence and mobile communication, E-mail: jjhao@bupt.edu.cn.
Guo Yijun ¹

1、School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876

Abstract：This paper concentrates on a non-orthogonal multiple access (NOMA) enabled UAV data collection network for Internet of Things devices (IoTDs), where a unmanned aerial vehicle (UAV) is deployed as an aerial base station. During its flight period, the UAV can collect data from IoTDs and take advantage of the simultaneous wireless information and power transfer (SWIPT) technology to charge the batteries of IoTDs. With the aid of NOMA, spectrum efficiency has been improved. This paper aims to prolong the lifetime of the Internet of Things (IoT) network, via jointly optimizing the UAV trajectory, the time allocation for information communication and wireless power transfer, the IoTDs' transmit power, as well as the IoTDs' group scheduling for NOMA. Then this paper uses the block coordinate decent (BCD) and successive convex approximation (SCA) techniques to tackle the non-convexity of the formulated problem. Numerical results show that the proposed solution increases the residual energy of the IoTDs, thus prolonging the lifetime of the network.

keywords： Communication and Information System, IoT, UAV Trajectory Designing, NOMA Transmission Scheduling

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基于NOMA的无人机数据采集网络剩余能量最大化算法：轨迹优化和资源分配

朱浩 ¹
Zhu Hao (1996-), male, major research direction: UAV communication.
郝建军 ¹
Hao Jianjun (1969-), male, associate professor, major research direction: articial intelligence and mobile communication, E-mail: jjhao@bupt.edu.cn.
郭一珺 ¹

1、北京邮电大学信息与通信工程学院，北京　100876

摘要：本文主要研究一个基于非正交多址接入技术（Non-orthogonal Multiple Access, NOMA）的部署物联网设备（Internet of Things Devices, IoTDs）无人机数据收集网络,其中无人机（Unmanned Aerial Vehicle, UAV）被部署为空中基站。在飞行期间,无人机可以从IoTDs处收集数据,并利用无线携能通信技术（Simultaneous Wireless Information and Power Transfer, SWIPT）为物联网设备的电池充电。本文通过应用NOMA技术提高了频谱效率。本文的目标是通过联合优化无人机轨迹、SWIPT的时间分配、IoTDs的发射功率以及NOMA分组策略,延长物联网（Internet of Things, IoT）的生存时间。然后,本文通过块坐标下降法（Block Coordinate Decent, BCD）和连续凸逼近技术（Successive Convex Approximation, SCA）来求解非凸问题。数值结果表明,该方案增加了IoTDs的剩余能量,从而延长网络的生存时间。

关键词：通信与信息系统\quad 物联网\quad 无人机轨迹规划\quad NOMA传输策略

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Zhu Hao,Hao Jianjun,Guo Yijun. Residual Energy Maximization for NOMA-Enabled UAV Data Collection Network: Trajectory Optimization and Resource Allocation[EB/OL]. Beijing:Sciencepaper Online[2022-03-17]. https://www.paper.edu.cn/releasepaper/content/202203-229.

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论文编号	202203-229
论文题目	基于NOMA的无人机数据采集网络剩余能量最大化算法：轨迹优化和资源分配
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