Pattern Design and Power Management for Cognitive LEO Beaming Hopping Satellite-Terrestrial Networks

Abstract

The number of base stations (BSs) in remote areas is poor, and seamless coverage cannot be achieved. This paper investigates a cognitive satellite-terrestrial network, including the low earth orbit-beam hopping (BH) satellite and terrestrial systems. Besides, the weighted capacity-request ratio is regarded as the quality of service (QoS) in the satellite system, and the weight indicates channel quality and service priority. Similarly, the capacity-request ratio is introduced as the QoS in the terrestrial system. By establishing a relationship between beams and terminals, the solution space of the BH pattern and beam power is shrunk, and the power allocation competition algorithm is proposed. The proposed algorithm promptly obtains a better solution than the particle swarm optimization and genetic algorithms. As the secondary system, the terrestrial system should obtain an accurate sense of the satellite system. We design a dynamic-ratio threshold spectrum detection mechanism, which causes less miss detection than energy detection under co-channel interference (CCI). Moreover, based on CCI suppression and quick selection of greedy thought, an adaptive resource adjustment algorithm is determined for the BS pattern and transmit power. Finally, the efficiency of the proposed algorithms and spectrum detection mechanism is demonstrated in simulations.