Application of hidden markov models to blind channel estimation and data detection in a gsm environment
Document typeConference report
Rights accessOpen Access
In this paper, we present an algorithm based on the Hidden Markov Models (HMM) theory to solve the problem of blind channel estimation and sequence detection in mobile digital communications. The environment in which the algorithm is tested is the Paneuropean Mobile Radio System, also known as GSM. In this system, a large part in each burst is devoted to allocate a training sequence used to obtain a channel estimate. The algorithm presented would not require this sequence, and that would imply an increase of the system capacity. Performance, evaluated for standard test channels, is close to that of non-blind algorithms.
CitationAnton, C., Fonollosa, José A. R., R. Fonollosa, J. Application of hidden markov models to blind channel estimation and data detection in a gsm environment. A: European Signal Processing Conference. "EUSIPCO 1996: Signal processing VIII: theories and applications; proceedings of EUSIPCO-96, Eighth European Signal Processing Conference: Trieste, Italy: 10-13 September 1996". Trieste: 1996, p. 811-814.