Data and channel estimators: a systematic classification

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

Abstract

A taxonomy of algorithms in digital receivers is presented, including data, channel and joint estimators. The receiver is seen as an elaborate estimator, whose primary purpose is to estimate (or "detect") the data. In communications, the impulse response of the linear channel is normally seen as a nuisance parameter set. The optimal receiver is defined to be a MAP detector where the channel is either assumed to be perfectly known or, if statistically known, be removed by averaging. On the other hand, in channel estimation data are assumed to be known or removed by averaging. Finally, joint estimators, which are generally optimal data detectors only asymptotically, can be defined. All the estimators are initially defined to be of the block-type, but they can be approximated with recursive versions. The estimators are based on some statistical knowledge on the channel, for example on the first- or second-order statistics of the impulse response and noise. Adaptive estimators do not necessarily rely on this a priori knowledge, but they are approximations of the optimal estimators and explicitly or implicitly estimate also the statistics.
Original languageEnglish
Title of host publicationProceedings of the X National Symposium of Radio Science, URSI 2002
Pages13-25
Publication statusPublished - 2002
MoE publication typeB3 Non-refereed article in conference proceedings
EventNational Symposium of Radio Science, URSI 2002 - Poxnan, Poland
Duration: 14 Mar 200215 Mar 2002

Seminar

SeminarNational Symposium of Radio Science, URSI 2002
Abbreviated titleURSI 2002
CountryPoland
CityPoxnan
Period14/03/0215/03/02

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communication
detector
statistics
nuisance
parameter

Cite this

Mämmelä, A., Polydoros, A., & Järvensivu, P. (2002). Data and channel estimators: a systematic classification. In Proceedings of the X National Symposium of Radio Science, URSI 2002 (pp. 13-25)
Mämmelä, Aarne ; Polydoros, Andreas ; Järvensivu, Pertti. / Data and channel estimators: a systematic classification. Proceedings of the X National Symposium of Radio Science, URSI 2002. 2002. pp. 13-25
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Mämmelä, A, Polydoros, A & Järvensivu, P 2002, Data and channel estimators: a systematic classification. in Proceedings of the X National Symposium of Radio Science, URSI 2002. pp. 13-25, National Symposium of Radio Science, URSI 2002, Poxnan, Poland, 14/03/02.

Data and channel estimators: a systematic classification. / Mämmelä, Aarne; Polydoros, Andreas; Järvensivu, Pertti.

Proceedings of the X National Symposium of Radio Science, URSI 2002. 2002. p. 13-25.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

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AB - A taxonomy of algorithms in digital receivers is presented, including data, channel and joint estimators. The receiver is seen as an elaborate estimator, whose primary purpose is to estimate (or "detect") the data. In communications, the impulse response of the linear channel is normally seen as a nuisance parameter set. The optimal receiver is defined to be a MAP detector where the channel is either assumed to be perfectly known or, if statistically known, be removed by averaging. On the other hand, in channel estimation data are assumed to be known or removed by averaging. Finally, joint estimators, which are generally optimal data detectors only asymptotically, can be defined. All the estimators are initially defined to be of the block-type, but they can be approximated with recursive versions. The estimators are based on some statistical knowledge on the channel, for example on the first- or second-order statistics of the impulse response and noise. Adaptive estimators do not necessarily rely on this a priori knowledge, but they are approximations of the optimal estimators and explicitly or implicitly estimate also the statistics.

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Mämmelä A, Polydoros A, Järvensivu P. Data and channel estimators: a systematic classification. In Proceedings of the X National Symposium of Radio Science, URSI 2002. 2002. p. 13-25