Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for Ofdm Systems

dc.authorscopusid 6603245438
dc.authorscopusid 35620998700
dc.authorscopusid 56989358100
dc.contributor.author Ciflikli, Cebrail
dc.contributor.author Ozsahin, A. Tuncay
dc.contributor.author Yapici, A. Cagri
dc.date.accessioned 2024-07-05T15:11:55Z
dc.date.available 2024-07-05T15:11:55Z
dc.date.issued 2009
dc.department Atılım University en_US
dc.department-temp [Ciflikli, Cebrail; Ozsahin, A. Tuncay] Erciyes Univ, Kayseri Vocat Coll, TR-38039 Kayseri, Turkey; [Yapici, A. Cagri] Atilim Univ, Fac Engn, Dept Elect & Elect Engn, TR-06836 Ankara, Turkey en_US
dc.description.abstract The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel. en_US
dc.identifier.citationcount 11
dc.identifier.doi 10.1007/s11277-008-9639-2
dc.identifier.endpage 229 en_US
dc.identifier.issn 0929-6212
dc.identifier.issn 1572-834X
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-77549085291
dc.identifier.startpage 221 en_US
dc.identifier.uri https://doi.org/10.1007/s11277-008-9639-2
dc.identifier.uri https://hdl.handle.net/20.500.14411/1513
dc.identifier.volume 51 en_US
dc.identifier.wos WOS:000270195400001
dc.identifier.wosquality Q3
dc.language.iso en en_US
dc.publisher Springer en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 20
dc.subject OFDM en_US
dc.subject Channel estimation en_US
dc.subject Artificial neural network en_US
dc.subject Cosimulation en_US
dc.title Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for Ofdm Systems en_US
dc.type Article en_US
dc.wos.citedbyCount 12
dspace.entity.type Publication

Files

Collections