Demodulation with a Multichannel Estimation Method Using a Reduced Rank Constraint

Authors:
H. Kassem;P. Forster
Affiliations:
64, Bd. J.-J. Rousseau, 72100 Le Mans, France;64, Bd. J.-J. Rousseau, 72100 Le Mans, France
Venue:
Analog Integrated Circuits and Signal Processing
Year:
2003

Citing 2
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Maximum likelihood array processing in spatially correlated noisefields using parameterized signals

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Maximum likelihood parameter and rank estimation in reduced-rankmultivariate linear regressions

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Abstract

This paper deals with the Maximum Likelihood Estimation of the multichannel impulse response in a mobile communication system whose base stations are equipped with antennas arrays. The following problem is solved: using the training sequence, find the maximum likelihood multichannel impulse response from one mobile to the base station under a reduced rank constraint in the presence of gaussian noise and jammers with unknown covariance matrix. This method finds applications in demodulation (the reduced rank channel estimate can be used in a Viterbi Algorithm), and experimental results using real signals demonstrate its high performance compared with the standard Minimum Mean Square Error (MMSE) multichannel estimate.