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Location based power control for mobile devices in a cellular network
This paper provides location estimation based power control strategy for cellular radio systems via a location based interference management scheme. Our approach considers the carrier-to-interference as dependent on the transmitter and receiver separation distance and therefore an accurate estimation of the precise locations can provide the power critical mobile user to control the transition power accordingly. In this fully
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.
History
Title of proceedings
Tencon 2005 - 2005 IEEE region 10 conference : Melbourne, Australia, 21-24 November 2005.Event
TENCON (2005 : Melbourne, Australia)Pagination
1 - 6Publisher
IEEELocation
Melbourne, Vic.Place of publication
Piscataway, NJStart date
2005-11-21End date
2005-11-24ISBN-13
9780780393110ISBN-10
0780393112Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2005, IEEEEditor/Contributor(s)
R Harris, H BradlowUsage metrics
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No categories selectedKeywords
CarNetpower controllocation trackingmobility modellingrobust extended kalman filterwireless networksScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Software EngineeringComputer Science, Theory & MethodsEngineering, Electrical & ElectronicImaging Science & Photographic TechnologyTelecommunicationsComputer ScienceEngineeringRADIO SYSTEMSALGORITHMTRACKINGUPDATE
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