Online Mobile User Speed Estimation: Performance and Tradeoff Considerations

Majed Haddad 1 Dalia-Georgiana Herculea 2, 3, 4, 5 Chung Shue Chen 2, 3 Eitan Altman 6 Veronique Capdevielle 7
1 LIA - Laboratoire Informatique d'Avignon
2 LINCS - Laboratory of Information, Network and Communication Sciences
3 Alcatel-Lucent Bell Labs France [Nozay]
4 DYOGENE - Dynamics of Geometric Networks
DI-ENS - Département d'informatique de l'École normale supérieure, CNRS - Centre National de la Recherche Scientifique : UMR 8548, Inria de Paris
5 DI-ENS - Département d'informatique de l'École normale supérieure
6 NEO - Network Engineering and Operations
CRISAM - Inria Sophia Antipolis - Méditerranée
7 Nokia Bell Labs [Paris-Saclay]
Abstract : This paper presents an online algorithm for mobile user speed estimation in 3GPP Long Term Evolution (LTE)/LTE-Advanced (LTE-A) networks. The proposed method leverages on uplink (UL) sounding reference signal (SRS) power measurements performed at the base station, also known as eNodeB (eNB), and remains effective even under large sampling period. Extensive performance evaluation of the proposed algorithm is carried out using field traces from realistic environment. The on-line solution is proven highly efficient in terms of computational requirement, estimation delay, and accuracy. In particular, we show that the proposed algorithm can allow for the first speed estimation to be obtained after 10 seconds and with an average speed underestimation error of 14 kmph. After the first speed acquisition, subsequent speed estimations can be obtained much faster (e.g., each second) with limited implementation cost and still provide high accuracy.
Keywords : estimation delay complexity mobility state estimation LTE Cellular networks shadowing memory consumption
Type de document :
Communication dans un congrès
IEEE Consumer Communications and Networking Conference (CCNC), Jan 2017, Las Vegas, United States. 2017
Liste complète des métadonnées

Littérature citée [17 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01380734
Contributeur : Chung Shue Chen <>
Soumis le : jeudi 13 octobre 2016 - 14:00:37
Dernière modification le : jeudi 26 avril 2018 - 10:29:10
Document(s) archivé(s) le : samedi 4 février 2017 - 21:11:37

Fichier

t13_CR_M.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01380734, version 1

Collections

UPMC | INRIA | INRIA2017 | PSL | UNIV-COTEDAZUR

Citation

Majed Haddad, Dalia-Georgiana Herculea, Chung Shue Chen, Eitan Altman, Veronique Capdevielle. Online Mobile User Speed Estimation: Performance and Tradeoff Considerations. IEEE Consumer Communications and Networking Conference (CCNC), Jan 2017, Las Vegas, United States. 2017. 〈hal-01380734〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

373

Téléchargements de fichiers

194

Contact


archive-ouverte@inria.fr