Reference : A Low-complexity Resource Optimization Technique for High Throughput Satellite
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Engineering, computing & technology : Electrical & electronics engineering
Security, Reliability and Trust
http://hdl.handle.net/10993/47697
A Low-complexity Resource Optimization Technique for High Throughput Satellite
English
Abdu, Tedros Salih mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Kisseleff, Steven mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Lagunas, Eva mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
2021
Yes
International
International Symposium on Wireless Communication Systems (ISWCS 2021)
from 06-09-2021 to 09-09-2021
Berlin
Germany
[en] Bandwidth optimization ; Dinkelbach method ; Demand satisfaction ; Flexible payloads ; Low-complexity ; Power optimization ; Successive convex approximation
[en] The high throughput satellites with flexible payloads
are expected to provide a high data rate to satisfy the increasing
traffic demand. Furthermore, the reconfiguration capability of
flexible payloads opens the door to more advanced system
optimization techniques and a better utilization of satellite
resources. Consequently, we can obtain high demand satisfaction
at the user side. For this, dynamically adaptive high-performance
and low-complexity optimization algorithms are needed. In this
paper, we propose a novel low-complexity resource optimization
technique for geostationary (GEO) High Throughput Satellites.
The proposed method minimizes the transmit power and the
overall satellite bandwidth while satisfying the demand per beam.
This optimization problem turns out to be non-convex. Hence, we
convexify the problem using Dinkelbach method and Successive
Convex Approximation (SCA). The simulation result shows
that the proposed scheme provides better flexibility in resource
allocation and requires less computational time compared to the
state-of-art benchmark schemes.
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/47697
FnR ; FNR13696663 > Eva Lagunas > FlexSAT > Resource Optimization For Next Generation Of Flexible Satellite Payloads > 01/03/2020 > 28/02/2023 > 2019 and FNR14603732 > Tedros Salih Abdu > INSAT > Power And Bandwidth Allocation For Interference-limited Satellite Communication Systems > 01/03/2020 > 30/09/2023 > 2020

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