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On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation
dc.contributor.author | Antón Haro, Carles |
dc.contributor.author | Rodríguez Fonollosa, José Adrián |
dc.contributor.author | Faulí Prats, Claudio |
dc.contributor.author | Rodríguez Fonollosa, Javier |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2008-01-29T11:17:29Z |
dc.date.available | 2008-01-29T11:17:29Z |
dc.date.created | 1998-12-01 |
dc.date.issued | 2001-05-31 |
dc.identifier.citation | Antón Haro, C.; Rodríguez Fonollosa, J. A.; Fauli, C.; Rodríguez Fonollosa, J. On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation. IEEE Transactions on Vehicular Technology, 2001, vol. 50, núm. 3, p. 867-873. |
dc.identifier.issn | 0018-9545 |
dc.identifier.uri | http://hdl.handle.net/2117/1542 |
dc.description.abstract | In this paper, the theory of hidden Markov models (HMM) is applied to the problem of blind (without training sequences) channel estimation and data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedure assumes the model (i.e., the channel response) to be static throughout the observation sequence. By means of introducing a parametric model for time-varying channel responses, a version of the algorithm, which is more appropriate for mobile channels [time-dependent Baum-Welch (TDBW)] is derived. Aiming to compare algorithm behavior, a set of computer simulations for a GSM scenario is provided. Results indicate that, in comparison to other Baum–Welch (BW) versions of the algorithm, the TDBW approach attains a remarkable enhancement in performance. For that purpose, only a moderate increase in computational complexity is needed. |
dc.format.extent | 867-873 |
dc.language.iso | eng |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal |
dc.subject.lcsh | Mobile communication systems |
dc.subject.lcsh | Markov processes |
dc.subject.other | Blind channel estimation |
dc.subject.other | Blind data detection |
dc.subject.other | Hidden Markov models |
dc.subject.other | Mobile channels |
dc.subject.other | Cellular radio |
dc.subject.other | Computational complexity |
dc.subject.other | Fading channels |
dc.subject.other | Maximum likelihood estimation |
dc.subject.other | Parameter estimation |
dc.subject.other | Signal detection |
dc.subject.other | Channel time dependence |
dc.subject.other | Baum-Welch algorithm |
dc.subject.other | Observation sequence |
dc.subject.other | Parametric model |
dc.subject.other | Time-varying channel response |
dc.subject.other | Computer simulations |
dc.subject.other | Equalisers |
dc.subject.other | GSM |
dc.subject.other | GMSK |
dc.subject.other | HMM |
dc.subject.other | MLE |
dc.subject.other | TDBW |
dc.title | On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation |
dc.type | Article |
dc.subject.lemac | Comunicacions mòbils |
dc.subject.lemac | Processos de Markov |
dc.contributor.group | Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Open Access |
dc.relation.projectidctt | TIC96-0500-C10-01 |
dc.relation.projectidctt | TIC98-08412 |
dc.relation.projectidctt | TIC98-0703 |
local.personalitzacitacio | true |
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