Joint resource scheduling and trajectory design for multi-UAV-assisted uplink NOMA networks

The combination of unmanned aerial vehicle (UAV) communication and non-orthogonal multiple access (NOMA) is of great significance to support massive connections in the Internet of things (IoT). This paper studies a multi-UAV-assisted communication network, where the UAVs are employed as aerial access points to receive data from IoT nodes with NOMA adopted for uplink transmission. The aim is to maximize the average sum rate of the network, with the requirements of the individual upload of each node. To handle the node clustering problem, the spectral clustering and maximum weight matching algorithm are first integrated to divide the IoT nodes. Then, the time-varying NOMA user grouping scheme is implemented accordingly. Furthermore, by considering the trajectory decomposition and successive hover-and-fly structure, the complex UAV trajectory problem is transformed into a linear programming and the optimal time-continuous trajectory is achieved. Extensive simulations validate the effectiveness of the proposed algorithms for the UAV-assisted NOMA network.

Automated summary

This paper studies a multi-UAV-assisted communication network, where UAVs serve as aerial access points for IoT nodes using non-orthogonal multiple access (NOMA) for uplink transmission. The research aims to maximize the average sum rate of the network while satisfying individual upload requirements for each node. The paper proposes algorithms combining spectral clustering and maximum weight matching for node clustering, and implements a time-varying NOMA user grouping scheme. Additionally, it solves the complex UAV trajectory problem through trajectory decomposition and a linear programming approach. Extensive simulations validate the effectiveness of the proposed algorithms.