601. Blind channel estimation and data detection using hidden Markov models theory
- Author
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Antón Haro, Carles, Rodríguez Fonollosa, José Adrián, Rodríguez Fonollosa, Javier, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, and Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
- Subjects
Signal processing ,Linear constraints ,Data detection ,Performance analysis ,Telecommunication systems ,Time-varying channels ,Linear FIR hypothesis ,Enginyeria de la telecomunicació::Processament del senyal [Àrees temàtiques de la UPC] ,Nonblind receiver ,Processament del senyal ,HMM theory ,Standard test channels ,Blind channel estimation ,Parameter estimation ,Sistemes de comunicació de banda ampla ,GSM environment ,Hidden Markov models ,Equalisers ,Cellular radio ,Baum-Welch algorithm ,Computer Science::Information Theory ,Signal detection - Abstract
In this correspondence, we propose applying the hidden Markov models (HMM) theory to the problem of blind channel estimation and data detection. The Baum–Welch (BW) algorithm, which is able to estimate all the parameters of the model, is enriched by introducing some linear constraints emerging from a linear FIR hypothesis on the channel. Additionally, a version of the algorithm that is suitable for timevarying channels is also presented. Performance is analyzed in a GSM environment using standard test channels and is found to be close to that obtained with a nonblind receiver.