Weighted fair precoding based on traffic demands for multibeam satellite systems

Zhengwei Luo; Dewei Yang; Hua Wang; Jingming Kuang

doi:10.1109/VTCFall.2019.8891259

Weighted fair precoding based on traffic demands for multibeam satellite systems

Zhengwei Luo, Dewei Yang^*, Hua Wang, Jingming Kuang

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

In this paper, a linear precoding scheme is proposed to maximize the total throughput of a broadband geostationary earth orbit (GEO) satellite system based on traffic demands. The weighted max-min fair (WMMF) problem under the per-antenna power constraints and the traffic demands constraints is investigated to achieve this purpose. Semidefinite relaxation (SDR) approach and bisection search method are jointly adopted to solve the corresponding related problem, and then Gaussian randomization and a power control problem are proposed to get a suboptimal solution of the WMMF problem. Different traffic demands scenarios and weighted values selection schemes are considered to analyze the impact of them on the precoding design. Simulation results demonstrate that the total performance of the proposed scheme has been improved significantly over the traditional schemes and is better than the rate balance scheme.

Original language	English
Title of host publication	2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728112206
DOIs	https://doi.org/10.1109/VTCFall.2019.8891259
Publication status	Published - Sept 2019
Event	90th IEEE Vehicular Technology Conference, VTC 2019 Fall - Honolulu, United States Duration: 22 Sept 2019 → 25 Sept 2019

Publication series

Name	IEEE Vehicular Technology Conference
Volume	2019-September
ISSN (Print)	1550-2252

Conference

Conference	90th IEEE Vehicular Technology Conference, VTC 2019 Fall
Country/Territory	United States
City	Honolulu
Period	22/09/19 → 25/09/19

Keywords

GEO satellite system
Gaussian randomization
Semidefinite relaxation
Weighted max-min fairness
Weighted values selection

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10.1109/VTCFall.2019.8891259

Cite this

Luo, Z., Yang, D., Wang, H., & Kuang, J. (2019). Weighted fair precoding based on traffic demands for multibeam satellite systems. In 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings Article 8891259 (IEEE Vehicular Technology Conference; Vol. 2019-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2019.8891259

@inproceedings{4291fb50bd494e83873354e0f9aacb40,

title = "Weighted fair precoding based on traffic demands for multibeam satellite systems",

abstract = "In this paper, a linear precoding scheme is proposed to maximize the total throughput of a broadband geostationary earth orbit (GEO) satellite system based on traffic demands. The weighted max-min fair (WMMF) problem under the per-antenna power constraints and the traffic demands constraints is investigated to achieve this purpose. Semidefinite relaxation (SDR) approach and bisection search method are jointly adopted to solve the corresponding related problem, and then Gaussian randomization and a power control problem are proposed to get a suboptimal solution of the WMMF problem. Different traffic demands scenarios and weighted values selection schemes are considered to analyze the impact of them on the precoding design. Simulation results demonstrate that the total performance of the proposed scheme has been improved significantly over the traditional schemes and is better than the rate balance scheme.",

keywords = "GEO satellite system, Gaussian randomization, Semidefinite relaxation, Weighted max-min fairness, Weighted values selection",

author = "Zhengwei Luo and Dewei Yang and Hua Wang and Jingming Kuang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 90th IEEE Vehicular Technology Conference, VTC 2019 Fall ; Conference date: 22-09-2019 Through 25-09-2019",

year = "2019",

month = sep,

doi = "10.1109/VTCFall.2019.8891259",

language = "English",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings",

address = "United States",

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Luo, Z, Yang, D, Wang, H & Kuang, J 2019, Weighted fair precoding based on traffic demands for multibeam satellite systems. in 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings., 8891259, IEEE Vehicular Technology Conference, vol. 2019-September, Institute of Electrical and Electronics Engineers Inc., 90th IEEE Vehicular Technology Conference, VTC 2019 Fall, Honolulu, United States, 22/09/19. https://doi.org/10.1109/VTCFall.2019.8891259

Weighted fair precoding based on traffic demands for multibeam satellite systems. / Luo, Zhengwei; Yang, Dewei; Wang, Hua et al.
2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8891259 (IEEE Vehicular Technology Conference; Vol. 2019-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Weighted fair precoding based on traffic demands for multibeam satellite systems

AU - Luo, Zhengwei

AU - Yang, Dewei

AU - Wang, Hua

AU - Kuang, Jingming

PY - 2019/9

Y1 - 2019/9

N2 - In this paper, a linear precoding scheme is proposed to maximize the total throughput of a broadband geostationary earth orbit (GEO) satellite system based on traffic demands. The weighted max-min fair (WMMF) problem under the per-antenna power constraints and the traffic demands constraints is investigated to achieve this purpose. Semidefinite relaxation (SDR) approach and bisection search method are jointly adopted to solve the corresponding related problem, and then Gaussian randomization and a power control problem are proposed to get a suboptimal solution of the WMMF problem. Different traffic demands scenarios and weighted values selection schemes are considered to analyze the impact of them on the precoding design. Simulation results demonstrate that the total performance of the proposed scheme has been improved significantly over the traditional schemes and is better than the rate balance scheme.

AB - In this paper, a linear precoding scheme is proposed to maximize the total throughput of a broadband geostationary earth orbit (GEO) satellite system based on traffic demands. The weighted max-min fair (WMMF) problem under the per-antenna power constraints and the traffic demands constraints is investigated to achieve this purpose. Semidefinite relaxation (SDR) approach and bisection search method are jointly adopted to solve the corresponding related problem, and then Gaussian randomization and a power control problem are proposed to get a suboptimal solution of the WMMF problem. Different traffic demands scenarios and weighted values selection schemes are considered to analyze the impact of them on the precoding design. Simulation results demonstrate that the total performance of the proposed scheme has been improved significantly over the traditional schemes and is better than the rate balance scheme.

KW - GEO satellite system

KW - Gaussian randomization

KW - Semidefinite relaxation

KW - Weighted max-min fairness

KW - Weighted values selection

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M3 - Conference contribution

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BT - 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings

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Weighted fair precoding based on traffic demands for multibeam satellite systems

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