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LIU Rui, GUO Kefeng, ZHU Shibing, LI Changqing, LI Keying. Performance Analysis of Satellite-Aerial-Terrestrial Multiple Primary Users Cognitive Networks Based on NOMA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230212
Citation: LIU Rui, GUO Kefeng, ZHU Shibing, LI Changqing, LI Keying. Performance Analysis of Satellite-Aerial-Terrestrial Multiple Primary Users Cognitive Networks Based on NOMA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230212

Performance Analysis of Satellite-Aerial-Terrestrial Multiple Primary Users Cognitive Networks Based on NOMA

doi: 10.11999/JEIT230212
Funds:  The National Natural Science Foundation of China (6201517)
  • Received Date: 2023-04-03
  • Rev Recd Date: 2023-07-03
  • Available Online: 2023-07-14
  • Due to its unique advantages of strong survivability and seamless coverage, Satellite Communication (SatCom) can make up for the shortcomings of ground communication such as terrain limitations and small coverage, and has become increasingly important in current and future communication systems. In addition, aerial-assisted communication is considered a valuable research direction due to its flexibility and scalability in satellite ground networks. To overcome the problems of spectrum shortage and low spectrum utilization in Integrated Satellite-Aerial-Terrestrial Network (ISATN), Cognitive Radio (CR) and Non-Orthogonal Multiple Access (NOMA) are used in wireless communication networks to improve spectrum utilization and transmission performance. In this regard, the performance of a NOMA-based Cognitive Integrated Satellite-Aerial-Terrestrial Network(CISATN) with multiple primary users is studied, and accurate expressions for Outage Probability (OP) and ergodic capacity of the primary and secondary networks are derived. Asymptotic expressions for the OP and diversity order of these two networks are provided to obtain further insights. Finally, the correctness of the theoretical derivation is verified through numerical simulation, and the impact of key variables on system indicators is analyzed.
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