Resource Allocation Method of Cognitive Satellite Terrestrial Networks Under Non-Ideal Spectrum Sensing

Recently, the cognitive satellite communication has attracted more attention because of the high spectrum efficiency in the satellite bands. This paper investigates a distributed joint resource allocation algorithm based on the convex optimization theory in the cognitive satellite terrestrial networks under non-ideal spectrum sensing. In the cognitive satellite terrestrial network scenario, satellite users act as secondary users (SUs) who have the ability to transmit over multiple and simultaneous radio access technologies (RATs). Considering primary user activity modeling, the goal of the proposed algorithm is to minimize the end-to-end delay of the SUs in an actual propagation channel scenario. The bandwidth of different RATs and the power of different SUs are jointly allocated, and then, the data being transported by each SU are sent based on the allocated bandwidth and power. The numerical results validate the performance enhancement of the proposed algorithm and show the impact of channel condition parameters on the SUs’ delays under non-ideal spectrum sensing. The SUs transmission delays reduce by 81.31% after the resource allocation when the mean of primary user activity matrix is 0.9.