The design of High Throughput Satellite (HTS) systems builds on the concept of Smart Gateway Diversity (SGD) to exploit the spatial diversity of gateways in case of feeder link outage, occurring because of atmospheric impairments introduced in Extremely High Frequency (EHF) frequency bands. The gateway handover procedure requires precise prediction algorithms and coordination among different network elements. This paper presents novel outage prediction algorithms based on machine learning concepts, integrated in the framework of SDN architectures, to efficiently orchestrate the gateway handover operations. Simulation campaigns prove the validity of the proposed concept and shed light on the potentials of the SDN architecture in future HTS systems.

Feeder-link outage prediction algorithms for SDN-based high-throughput satellite systems

Mongelli Maurizio;
2016

Abstract

The design of High Throughput Satellite (HTS) systems builds on the concept of Smart Gateway Diversity (SGD) to exploit the spatial diversity of gateways in case of feeder link outage, occurring because of atmospheric impairments introduced in Extremely High Frequency (EHF) frequency bands. The gateway handover procedure requires precise prediction algorithms and coordination among different network elements. This paper presents novel outage prediction algorithms based on machine learning concepts, integrated in the framework of SDN architectures, to efficiently orchestrate the gateway handover operations. Simulation campaigns prove the validity of the proposed concept and shed light on the potentials of the SDN architecture in future HTS systems.
2016
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
9781479966646
gateway handover
machine learning
prediction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/325200
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