Joint Resource Allocation and Trajectory Design for UAV-Assisted THz-NOMA GS Network Uplink Communication System

Terahertz (THz) and nonorthogonal multiple-access (NOMA) technologies have illustrated a great potential in the use of large-scale Internet of Things (IoT) applications. However, in most applications, ground sensors (GSs) have poor energy capacity, while THz communication suffers from significant path loss, which leads to a low data transfer rate in an air-ground communication system. Fortunately, with the development of uncrewed aerial vehicle (UAV)-assisted THz-NOMA communication technology, it has become one of the promising solutions to deal with the above challenges. To conserve GSs' limited energy while enhancing the throughput of the THz-NOMA communication system, we utilize a UAV to collect and transmit data from GSs to an aerostat. Then, the energy efficiency (EE) of GSs network is maximized by leveraging GSs' communication resource allocation strategy and UAV trajectory design, while taking into account each GS's minimum throughput and each GS's transmission power constraints. The proposed design is a mixed-integer nonconvex problem, which is generally intractable. To promptly solve the original problem, we divide it into three subproblems: GSs' communication resource allocation, UAV's altitude optimization, and horizontal trajectory design. An iterative algorithm is proposed to deal with these subproblems, based on the Dinkelbach method, dual-decomposition, and convex relaxation techniques. Simulation results show that the proposed iterative algorithm can achieve a higher EE with a shorter convergence time compared with baseline algorithms.