Throughput Maximization for UAV-RIS NOMA Cognitive Systems in Disaster Communications

This paper examines a cognitive radio (CR) non-orthogonal multiple access (NOMA) system, which deploys an unmanned aerial vehicle (UAV) with a reconfigurable intelligent surface (RIS) in a disaster area. In particular, in the primary network, a base station (BS) communicates with a primary receiver (PR), while a secondary transmitter (ST) simultaneously sends superimposed signals to the two sensor destinations (SDs) via NOMA with the help of the UAV-RIS. Furthermore, a UAV eavesdropper (UE) wiretaps the signals from the UAV-RIS. To improve system performance, we then employ bat algorithm optimization (BAO) to maximize secondary network throughput under outage probability and security constraints.