Secrecy rate maximization for 6G cognitive satellite-UAV networks

To cover remote areas where terrestrial cellular networks may not be available, non-terrestrialinfrastructures such as satellites and unmanned aerialvehicles (UAVs) can be utilized in the upcomingsixth-generation (6G) era. Considering the spectrumscarcity problem, satellites and UAVs need to sharethe spectrum to save costs, leading to a cognitivesatellite-UAV network. Due to the openness of bothsatellite links and UAV links, communication secu-rity has become a major concern in cognitive satellite-UAV networks. In this paper, we safeguard a cog-nitive satellite-UAV network from a physical layersecurity (PLS) perspective. Using only the slowly-varying large-scale channel state information (CSI),we jointly allocate the transmission power and sub-channels to maximize the secrecy sum rate of UAVusers. The optimization problem is a mixed integernonlinear programming (MINLP) problem with cou-pling constraints. We propose a heuristic algorithmwhich relaxes the coupling constraints by the penaltymethod and obtains a sub-optimal low-complexity so-lution by utilizing random matrix theory, the max-minoptimization tool, and the bipartite graph matching al-gorithm. The simulation results corroborate the supe-riority of our proposed scheme.