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An Asynchronous Collision-Tolerant ACRDA Scheme Based on Satellite-Selection Collaboration-Beamforming for LEO Satellite IoT Networks.
Hong, Tao; Liu, Rui; Liu, Ziwei; Ding, Xiaojin; Zhang, Gengxin.
Afiliación
  • Hong T; School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Liu R; School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Liu Z; School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Ding X; School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Zhang G; School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
Sensors (Basel) ; 23(7)2023 Mar 28.
Article en En | MEDLINE | ID: mdl-37050606
ABSTRACT
In this paper, an asynchronous collision-tolerant ACRDA scheme based on satellite-selection collaboration-beamforming (SC-ACRDA) is proposed to solve the avalanche effect caused by packet collision under random access (RA) high load in the low earth orbit (LEO) satellite Internet of Things (IoT) networks. A non-convex optimization problem is formulated to realize the satellite selection problem in multi-satellite collaboration-beamforming. To solve this problem, we employ the Charnes-Cooper transformation to transform a convex optimization problem. In addition, an iterative binary search algorithm is also designed to obtain the optimization parameter. Furthermore, we present a signal processing flow combined with ACRDA protocol and serial interference cancellation (SIC) to solve the packet collision problem effectively in the gateway station. Simulation results show that the proposed SC-ACRDA scheme can effectively solve the avalanche effect and improve the performance of the RA protocol in LEO satellite IoT networks compared with benchmark problems.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China