Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6961
Title: Kalman Prediction Based Proportional Fair Resource Allocation for a Solar Powered Base Station
Authors: Ersoy, Neyre Tekbıyık
Bıyıkoğlu, Elif Uysal
Leblebicioğlu, Kemal
Girici, Tolga
Keywords: Energy harvesting
proportional fair
wireless sensor networks
solar energy
Kalman filter
prediction
Issue Date: 2013
Publisher: IEEE
Source: 21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS
Series/Report no.: Signal Processing and Communications Applications Conference
Abstract: This paper considers optimising transmissions of base station (BS) equipped with a solar panel. The BS is assumed to serve a distributed wireless network of nodes or gateways on orthogonal channels. Considering the daily periodicity as well as short term variations of solar energy, and the differences in channel gain from the BS to the nodes, a scheduling method for efficient delivery of maintenance messages from the BS to the wireless nodes that it serves to (such as wireless sensor network gateways) is investigated. The proposed solution is an online resource allocation algorithm, called PTF-On, that can predict the base station's energy arrival profile, and then, act upon this profile to determine the best power and time allocation that will maximize the throughput in a proportionally fair way.
URI: https://hdl.handle.net/20.500.11851/6961
ISBN: 978-1-4673-5563-6; 978-1-4673-5562-9
ISSN: 2165-0608
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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