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Dynamic Divide Grouping Non-Orthogonal Multiple Access in Terrestrial-Satellite Integrated Network.
Yan, Yanjun; Xu, Huihui; Zhang, Ning; Han, Guangjie; Liu, Mingliu.
Afiliação
  • Yan Y; The 91892 Troops, Sanya 572000, China.
  • Xu H; School of Weaponry Engineering, Naval University of Engineering, Wuhan 430072, China.
  • Zhang N; School of Weaponry Engineering, Naval University of Engineering, Wuhan 430072, China.
  • Han G; Department of Information and Communication Systems, Hohai University, Changzhou 213000, China.
  • Liu M; Electronic Information School, Wuhan University, Wuhan 430072, China.
Sensors (Basel) ; 21(18)2021 Sep 16.
Article em En | MEDLINE | ID: mdl-34577407
ABSTRACT
Non-orthogonal multiple access (NOMA) has been extensively studied to improve the performance of the Terrestrial-Satellite Integrated Network (TSIN) on account of the shortage of frequency band resources. In this paper, the terrestrial network and satellite network synergistically provide complete coverage for ground users, and based on the architecture, we first formulate a constrained optimization problem to maximize the sum rate of the TSIN under the limited spectrum resources. As the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, in which the optimal power control factor expression is derived. Then, by constructing the relationship model between user elevation angle, beam angle and distance, we develop a dynamic group pairing schemes to ensure the effective pairing of NOMA users. Based on the user pairing, to obtain the optimal resource allocation, a joint optimization algorithm of power allocation, beam channel and base station channel resource is proposed. Finally, simulation results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with the existing works.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article