Title
Optimized Power Control Scheme for Global Throughput of Cognitive Satellite-Terrestrial Networks Based on Non-Cooperative Game.
Abstract
In this paper, we investigate the power control problem for spectrum sharing in the cognitive satellite-terrestrial networks (CSTNs), aiming to maximize the throughput of global networks while meeting the requirements of signal to interference plus noise ratio (SINR) in the satellite links. Since the power control problem for global networks involves a mass of information collection or exchange, it is not conducive to centralized control in CSTNs. So we solve it by constructing a non-cooperative game with limited information exchange. First, we theoretically prove that the Nash equilibrium (NE) of the proposed game is consistent with the stationary point of the global throughput maximization problem. Then, we design a distributed power control (DPC) algorithm to obtain the NE of the game with guaranteeing the SINR demand of the satellite links. Considering that the precise channel state information (CSI) is often difficult to be obtained in actual communication scenarios, we propose a modified scheme of the DPC algorithm for the case of imperfect CSI. The modified scheme not only ensures that the SINR requirements of the satellite links can be met but also approximately converges to an NE of the problem with a little performance loss. Finally, the numerical results demonstrate that our scheme outperforms the existing typical algorithms in terms of the throughput of the global networks as well as the number of iterations.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2920428
IEEE ACCESS
Keywords
Field
DocType
Cognitive satellite-terrestrial networks,power control,game theory,global optimization
Satellite,Computer science,Power control,Computer network,Throughput,Cognition,Non-cooperative game,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Zhuyun Chen121.72
Daoxing Guo26927.71
Guoru Ding364957.39
Xinhai Tong400.68
Heng Wang541.74
Xiao-kai Zhang6226.38