In order to reduce the risk of authorized users being interrupted in the cognitive satellite wireless network, a multi-step prediction approach based on a cascaded forward artificial neural network is proposed to predict user behavior in the designed scenario. This approach uses the powerful learning ability of the cascaded forward network to analyze the historical spectrum occupancy records of licensed users, and then predict the user behavior in the next few time slots. The prediction result can help the base station in the cognitive network to schedule the dynamic access process of the cognitive users, and reduce the interference caused by the cognitive user to the authorized users. Finally, compared with traditional prediction algorithms, it is verified that the proposed multi-step prediction algorithm can effectively reduce the probability of spectrum conflicts.
The integrated satellite and terrestrial network has become one of the frontier technologies of the next generation mobile communication system. The satellite network is used as an extension and supplement of the ground network to achieve seamless coverage of wireless mobile communications. The spectrum sharing of the integrated satellite and terrestrial network is realized from the perspective of spectrum planning, considering the number of co-frequency terminals and the distance between the terminal and the center of the satellite beam. The existing spectrum sharing schemes use the concept of geographic isolation, which will limit the available bandwidth of the terrestrial network. Therefore, the concept of time domain isolation is proposed, and a soft frequency reuse based spectrum sharing scheme in the integrated satellite and terrestrial network is designed. The allocation of time slots increases the degree of spectrum isolation and improves the signal to interference ratio of the network. In addition, due to the increase in the utilization rate of the satellite spectrum, the capacity of the satellite system is improved.
In this paper, we mainly research on the QoS (Quality of Service) routing algorithms for MEO/LEO (medium Earth orbit/low Earth orbit) double-layered satellite networks. In this type of networks, the rapidly changing network topology due to relative motion of satellites is one of the main challenges when designing an efficient routing algorithm. Specifically, the issues of high rerouting overhead and traffic routing with diverse QoS requirements remain to be resolved. This paper proposed a M-BMDP (modified bandwidth constrained minimum delay path) routing algorithm based on swarm and location for MEO/LEO double-layered satellite networks. This algorithm forms a set of LEO groups according to the footprint of MEO satellites and chooses the relative MEO satellites as its group manager. For delay sensitive traffic, the algorithm can improve the QoS as the cost of packet loss based on hop limit. And for users located in reversed crevice zone, the traffic can route through one MEO satellite to reduce the time delay. The simulation results show that the M-BMDP algorithm performs better in rerouting delay, overhead and pack loss rate compared with existing solutions.
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