Wireless communication highly depends on the cellular ground base station (GBS). A failure of the cellular GBS, fully or partially, during natural or man-made disasters creates a communication gap in the disaster-affected areas. In such situations, public safety communication (PSC) can significantly save the national infrastructure, property, and lives. Throughout emergencies, the PSC can provide mission-critical communication and video transmission services in the affected area. Unmanned aerial vehicles (UAVs) as flying base stations (UAV-BSs) are particularly suitable for PSC services as they are flexible, mobile, and easily deployable. This manuscript considers a multi-UAV-assisted PSC network with an observational UAV receiving videos from the affected area's ground users (AGUs) and transmitting them to the nearby GBS via a relay UAV. The objective of the proposed study is to maximize the average utility of the video streams generated by the AGUs upon reaching the GBS. This is achieved by optimizing the positions of the observational and relay UAVs, as well as the distribution of communication resources, such as bandwidth, and transmit power, while satisfying the system-designed constraints, such as transmission rate, rate outage probability, transmit power budget, and available bandwidth. To this end, a joint UAVs placement and resource allocation problem is mathematically formulated. The proposed problem poses a significant challenge for a solution. Considering the block coordinate descent and successive convex approximation techniques, an efficient iterative algorithm is proposed. Finally, simulation results are provided which show that our proposed approach outperforms the existing methods.

翻译：无线通信高度依赖于蜂窝地面基站（GBS）。在自然或人为灾害期间，蜂窝GBS完全或部分失效会在受灾区域造成通信中断。在此类情况下，公共安全通信（PSC）可显著保护国家基础设施、财产和生命安全。在紧急事件中，PSC能在受灾区域提供关键任务通信和视频传输服务。作为飞行基站（UAV-BS）的无人机（UAV）因其灵活性、机动性和易于部署性，特别适用于PSC服务。本文考虑了一个多无人机辅助PSC网络，其中观测无人机接收受灾区域地面用户（AGU）的视频并通过中继无人机传输至邻近GBS。本研究的目标是最大化AGU生成的视频流到达GBS时的平均效用。通过优化观测无人机与中继无人机的位置，以及带宽和发射功率等通信资源的分配，同时满足传输速率、速率中断概率、发射功率预算和可用带宽等系统设计约束，实现上述目标。为此，本文数学建模了一个联合无人机部署与资源分配问题。该问题的求解具有显著挑战性。基于块坐标下降法和逐次凸逼近技术，提出了一种高效迭代算法。最后，仿真结果表明，所提出的方法优于现有方案。