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.

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In order to deal with the difficulty of spectrum sensing in cognitive satellite wireless networks, a large-scale cognitive network spectrum sensing algorithm based on big data analysis theory is studied, and a new algorithm using mean exponential eigenvalue is proposed. This new approach fully uses all the eigenvalues in sample covariance matrix of the sensing results to make the decision, which can effectively improve the detection performance without obtaining the prior information from licensed users. Through simulation, the performance of various large scale cognitive radio spectrum sensing algorithms based on big data analysis theory is compared, and the influence of satellite to ground channel conditions and the number of sensing nodes on the performance of the algorithm is discussed.

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.

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