Performance evaluation for underlay cognitive satellite-terrestrial cooperative networks

  • Yuhan Ruan
  • Yongzhao LiEmail author
  • Cheng-Xiang Wang
  • Rui Zhang
  • Hailin Zhang
Research Paper


With the continuously increasing demand for broadband applications and services, underlay cognitive satellite-terrestrial networks, enabling to accommodate better wireless services within the scarce spectrum, have attracted tremendous attentions recently. In this network, satellite communications are allowed to operate in the frequency bands allocated to terrestrial networks under the interference constraints imposed by terrestrial network, which may lead to a performance degradation of the satellite network. To guarantee the performance of the primary terrestrial network as well as the secondary satellite network, we introduce the cooperation into cognitive satellite-terrestrial networks and investigate the performance of the new framework, i.e., cognitive satellite-terrestrial cooperative network (CSTCN). Specifically, by restricting the transmit power of satellite communications with interference power constraints imposed by terrestrial communications, we firstly obtain the received signal-to-interference-plus-noise ratio (SINR) of the considered network. Moreover, by employing the moment generating function (MGF) approach, closed-form expressions for symbol error rate (SER) and outage probability (OP) of the considered cognitive network are derived. The analytical results obtained in this paper can provide theoretical support for optimizing the performance of satellite-terrestrial networks.


cognitive satellite-terrestrial cooperative network interference constraints moment generating function symbol error rate outage probability 



This work was supported by National Key R&D Program of China (Grant No. 2016YFB1200202), National Natural Science Foundation of China (Grant No. 61771365), Natural Science Foundation of Shaanxi Province (Grant No. 2017JZ022), Programme of Introducing Talents of Discipline to Universities (111 Project) (Grant No. B08038), EU H2020 RISE TESTBED Project (Grant No. 734325), and EPSRC TOUCAN Project (Grant No. EP/L020009/1).


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Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yuhan Ruan
    • 1
  • Yongzhao Li
    • 1
    Email author
  • Cheng-Xiang Wang
    • 2
  • Rui Zhang
    • 1
  • Hailin Zhang
    • 1
  1. 1.State Key Laboratory of Integrated Service NetworkXidian UniversityXi’anChina
  2. 2.School of Engineering and Physical SciencesHeriot-Watt UniversityEdinburghUK

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