In emergency situations, existing Internet of Things (IoT) infrastructure is vulnerable to natural disasters and unable to provide reliable services to users in disaster areas. Due to flexible maneuverability and fast deployment, unmanned aerial vehicle (UAV) plays an important role in the IoT deployment in emergency since it can be fast deployed as aerial relay to significantly enhance the communication capacity in disaster areas by designing efficient UAV trajectory. In this paper, a UAV relay communication model for multi-user data transmission is designed. When the communication between the user area and base station (BS) is interrupted, BS first sends information to the UAV, and then the UAV acts as a relay to forward the information to the users. According to the model, a joint UAV trajectory and power allocation scheme is proposed. The goal is to maximize the downlink achievable sum rate of all users by jointly optimizing UAV trajectory and BS/UAV power subject to the UAV mobility and information causality constraints. In view of the non-convexity of the formulated problem, an efficient iterative algorithm is proposed which optimizes the UAV trajectory and the BS/UAV transmit power alternately to obtain the approximately optimal solution to the original problem. Simulation results show that the proposed iterative algorithm can not only optimize the UAV trajectory, but also effectively improve the downlink achievable sum rate compared with the benchmark schemes.

在紧急情况下，现有的物联网（IoT）基础架构易受自然灾害的影响，无法为灾区用户提供可靠的服务。由于灵活的机动性和快速部署，无人飞行器（UAV）在紧急情况下的IoT部署中起着重要作用，因为它可以通过设计有效的UAV轨迹快速部署为空中中继，从而显着增强灾区的通信能力。本文设计了一种用于多用户数据传输的无人机中继通信模型。当用户区域和基站（BS）之间的通信中断时，BS首先将信息发送到UAV，然后UAV充当中继器将信息转发给用户。根据该模型，提出了联合无人机航迹和动力分配方案。目标是通过联合优化无人机轨迹和BS / UAV功率（受无人机移动性和信息因果关系约束），最大化所有用户的下行链路可实现总速率。鉴于提出问题的非凸性，提出了一种有效的迭代算法，该算法优化了无人机的航迹和BS / UAV的发射功率，以获得对原始问题的近似最优解。仿真结果表明，与基准方案相比，该迭代算法不仅可以优化无人机航迹，而且可以有效地提高下行链路可实现的总速率。鉴于提出问题的非凸性，提出了一种有效的迭代算法，该算法优化了无人机的航迹和BS / UAV的发射功率，以获得对原始问题的近似最优解。仿真结果表明，与基准方案相比，所提出的迭代算法不仅可以优化无人机航迹，而且可以有效地提高下行链路可达到的总速率。鉴于提出问题的非凸性，提出了一种有效的迭代算法，该算法优化了无人机的航迹和BS / UAV的发射功率，以获得对原始问题的近似最优解。仿真结果表明，与基准方案相比，该迭代算法不仅可以优化无人机航迹，而且可以有效地提高下行链路可实现的总速率。