Optimizing FBS 3D positions for sum rate maximization in downlink NOMA 6G network

The explosive growth of internet of everything (IoE) devices and the increasing demand for ultra-reliable, high-capacity wireless connectivity pose significant challenges to next-generation networks. Flying base stations (FBSs) make a significant contribution to the physical layer of vehicular communication by improving connectivity among different transportation systems. However, the mobility of FBSs and the IoE devices frequently disrupt communication links, impairing the performance of wireless communication. This issue can be addressed through strategic FBS positioning. In this paper, we propose a transmission structure based on multi-FBS with non-orthogonal multiple access (NOMA) in downlink 6G networks, where NOMA is employed at each FBS to provide services for IoE devices. Our objective is to maximize the total sum rate (TSR) by minimizing the inter/intra-cluster interference. To this end, the three-dimensional (3D) positions of the FBS are optimized in such a way that the FBS consistently remains at the center of the IoE devices' locations even when their locations change within the network. The optimization problem is non-convex optimization problem due to the optimization of FBSs' 3D positions. To address this issue, a genetic algorithm-based evolutionary algorithm is developed. Moreover, a perfect successive interference cancellation (SIC) strategy is introduced to address NOMA-SIC among IoE devices. The simulation results state that our proposed algorithm outperforms the other state-of-the-art in terms of TSR, achieving up to 21.03% higher TSR compared to Annealing, block coordinate descent, modified gray wolf optimization, and the center-of-cluster approach, thus demonstrating the advantages of optimizing the 3D positions of FBSs in this manner.