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Boosting Predictions by Calibration of Traffic Model and Learning of Indicators' Distributions

Autor: W. Tabbara, Benoit Fourestie, F. Brouaye, B. Sayrac, Z. Nouir

Publikováno v: IEEE Transactions on Vehicular Technology. 57:2489-2497

In this paper, we discuss a two-step scheme using measurements that are taken on a real network. The two steps are complementary and aim to enhance the precision and the quality of a radio network planning tool. We have, in a first step, calibrated t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4b4049b9685515b3ea1bcc4a8f5445ba
https://doi.org/10.1109/tvt.2007.912151

Spectogram Reconstruction from Random Sampling: Application to the GSM Band Sensing

Autor: B. Sayrac, D. Depierre, L. Gueguen

Publikováno v: ICC

In the context of cognitive radios, we present a method to sense wideband radio spectra from randomly distributed samples with an average sampling rate smaller than the Nyquist sampling rate. The method finds its roots in the compressed sensing parad

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d603778d1940533df5d36d2a911c0245
https://doi.org/10.1109/icc.2009.5199475

Reliability Enhancement of 3G Radio Network Prediction by a Conditional Distribution Discrimination Tree

Autor: Z. Nouir, A. Petrowski, B. Sayrac, Benoit Fourestie

Publikováno v: VTC Spring
Proceedings VTC Spring 2008 : IEEE 67th Vehicular Technology Conference
VTC Spring 2008 : IEEE 67th Vehicular Technology Conference
VTC Spring 2008 : IEEE 67th Vehicular Technology Conference, May 2008, Marina Bay, Singapore. pp.1985-1989, ⟨10.1109/VETECS.2008.448⟩

International audience; This paper presents a constructive learning system that enhances the reliability and precision of radio network predictions. This task is achieved by finding a correspondence between the probability density distributions of si

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83c7c7c7211f34e26545eade3ef2928c
https://doi.org/10.1109/vetecs.2008.448

Measurement Aided 3G Radio Network Prediction: Fuzzy Bayesian Framework

Autor: F. Brouaye, B. Sayrac, Benoit Fourestie, W. Tabbara, Z. Nouir

Publikováno v: VTC Spring

We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize this challenged task. To ensure better generalization capabilities of the learning

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4f8d7a3466c1365787d0c04780becb1d
https://doi.org/10.1109/vetecs.2007.157