Channel States Information based Spectrum Sensing Algorithm in Satellite Cognitive Communication Networks

This paper proposes a spectrum sensing algorithm based on channel states information to solve the problem of the instantaneous power drop of the signal in the satellite cognitive network. The proposed algorithm adds an update mechanism in the traditional energy detection process and maps the current channel state statistic by using the channel statistics of the previous detections. This algorithm is studied in the satellite cognitive network scenario, in which GEO satellite network is primary user, LEO satellite network is secondary user. Moreover, a spectrum sensing model is built to help study this algorithm. Simulation results show that the proposed algorithm significantly improves the efficiency of spectrum sensing and solves the problem that the power of the signal to be detected is constantly changing due to shadow effect.