In this letter, the problem of unmanned aerial vehicle (UAV) deployment, power allocation, and bandwidth allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location, user power, and bandwidth allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the total delays of the uplink and downlink transmissions between the UAV and the ground users by jointly optimizing the deployment of the UAV, the transmit power and the bandwidth of each user. The communication delay is crucial for emergency communications. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving three subproblems: location optimization subproblem, power control subproblem, and bandwidth allocation subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to 59.3%, 49.8% and 75.5% respectively compared to baseline algorithms that optimize only UAV location, bandwidth allocation or transmit power control.

中文翻译：

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太赫兹无人机通信的联合定位、带宽和功率优化

在这封信中，研究了在太赫兹 (THz) 频率下运行的无人机辅助无线系统的无人机 (UAV) 部署、功率分配和带宽分配问题。在研究的模型中，一架无人机可以使用太赫兹频段为地面用户提供服务。然而，高度不确定的太赫兹信道会给无人机定位、用户功率和带宽分配优化问题带来新的挑战。因此，有必要设计一种新颖的框架来在太赫兹无线系统中部署无人机。该问题被正式提出为一个优化问题，其目标是通过联合优化无人机的部署、发射功率和每个用户的带宽来最小化无人机与地面用户之间上下行传输的总延迟。通信延迟对于紧急通信至关重要。为了解决这个非凸延迟最小化问题，提出了一种交替算法，同时迭代解决三个子问题：位置优化子问题、功率控制子问题和带宽分配子问题。仿真结果表明，与仅优化无人机定位、带宽分配或发射功率控制的基线算法相比，所提出的算法可以分别减少高达59.3%、49.8%和75.5%的传输延迟。