Throughput analysis and optimization for NOMA Multi-UAV assisted disaster communication using CMA-ES

When communication infrastructure is destroyed by natural disasters, reconstructing a flexible network for search and rescue or restoring transmission channels is a necessary mission. Therefore, in this paper, we investigate the system performance for the Internet of Things (IoT) using multiple unmanned aerial vehicles (UAVs) in the disaster area. The communication protocol is separated into two phases: In the first phase, due to the resource limitation, UAV relays (URs) harvest energy from a ground power beacon (GPB) to support the communication process. In the second phase, the ground base station (GBS) sends the signal to the first UR by using non-orthogonal multiple access (NOMA) technique. It is noted that the first UR uses its energy harvested from the first phase to forward the signal to the second UR by applying the decode-and-forward (DF) approach. Similarly, the second UR uses DF to transfer the signal to two IoT sensor node (IoTS) clusters, i.e., near cluster and far cluster. Accordingly, we derive the closed-form expression of the throughput for the IoTSs under imperfect channel state information (CSI) with Nakagami- m fading and formulate a new problem of throughput optimization for multi-UAV system. For optimization problem, solutions are found using covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm. The numerical results show that system performance in terms of throughput can be improved by tuning the UAVs’ altitudes and distances from the GBS to suitable values.