Abstract
Outside the coverage of terrestrial cellular networks, non-terrestrial infrastructures, e.g., satellites and unmanned aerial vehicles (UAVs), should be utilized, to efficiently cover the remote areas. This requires a cognitive satellite-UAV network, where satellites and UAVs share the spectrum to save cost, and the network resources are orchestrated in an on-demand manner. In this paper, we focus on the physical layer security issue of the cognitive satellite-UAV networks, which is important due to the openness of both satellite links and UAV links. We formulate a joint power and channel allocation problem, using only the slowly-varying large-scale channel state information (CSI), to maximize the sum secrecy rate of UAV users. By resorting to the random matrix theory, the max-min optimization tool, as well as the bipartite graph matching algorithm, we propose a sub-optimal low-complexity solution, the superiority of which is verified by simulation results.
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