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Interference management for spectral coexistence in a heterogeneous satellite network
Author(s) -
Hajipour Pedram,
Shahzadi Ali,
GhaziMaghrebi Saeed
Publication year - 2020
Publication title -
international journal of satellite communications and networking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 39
eISSN - 1542-0981
pISSN - 1542-0973
DOI - 10.1002/sat.1321
Subject(s) - computer science , satellite constellation , constellation , satellite , interference (communication) , transmission (telecommunications) , computer network , communications satellite , telecommunications , power control , throughput , distributed computing , power (physics) , wireless , channel (broadcasting) , physics , quantum mechanics , astronomy , engineering , aerospace engineering
Summary With the advent of the fifth generation of mobile radio communication by 2020, there will be many challenges such as increasing service demand with low delay in providing billions of end users called the satellite mobile users. It is expected that terrestrial communication systems will be faced with a dense network having many small cells anywhere and anytime. Therefore, there are some remote regions in the world where terrestrial systems cannot provide any services to end users. Furthermore, because of lack of spectral resources, it is very important that the spectrum is shared between satellite systems and terrestrial equipment by a suitable solution to interference management. In this paper, a heterogeneous satellite network that includes low earth orbit (LEO) satellite constellation and terrestrial equipment is proposed to provide low delay services. In this type of structure, interference management based on transmission power control between LEO satellite systems and mobile users is very important for obtaining high throughput. Moreover, in order to mitigate interference, transmission power control is shown based on noncooperative Stackelberg game under many subgames through pricing‐based algorithm and convex optimization method. Finally, the simulation results show that the performance of this study's system model will be improved through the proposed algorithm.