Blind channel estimation and data detection using hidden Markov models theory
| Contribuinte(s) |
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
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| Data(s) |
10/05/2012
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| Resumo |
In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver. Peer reviewed |
| Identificador | |
| Idioma(s) |
eng |
| Publicador |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Direitos |
Consulteu les condicions d'ús d'aquest document en el repositori original:<a href="http://hdl.handle.net/2117/1566">http://hdl.handle.net/2117/1566</a> |
| Palavras-Chave | #Àrees temàtiques de la UPC::Enginyeria electrònica i telecomunicacions::Processament del senyal #Telecommunication systems #Signal processing #Blind channel estimation #Baum-Welch algorithm #Cellular radio #Data detection #Equalisers #GSM environment #Hidden Markov models #HMM theory #Linear constraints #Linear FIR hypothesis #Nonblind receiver #Parameter estimation #Signal detection #Standard test channels #Time-varying channels #Performance analysis #Sistemes de comunicació de banda ampla #Processament del senyal |
| Tipo |
info:eu-repo/semantics/article |
