Nonlinear frequency domain MMSE turbo equalization using probabilistic data association

This letter proposes a new frequency domain turbo equalization algorithm based on nonlinear minimum-mean- squared-error (MMSE) estimation. The conceptual basis of the proposed equalizer is the probabilistic data association (PDA) filtering. It is shown that by performing internal equalizer iteration...

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Bibliographic Details
Published in:IEEE communications letters 2008-04, Vol.12 (4), p.295-297
Main Authors: Grossmann, M., Matsumoto, T.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Analytical models
Applied sciences
Computer simulation
Convergence
Covariance matrix
Detection, estimation, filtering, equalization, prediction
Equalization
Equalizers
Exact sciences and technology
Filtering
Frequency domain analysis
Frequency domains
Information, signal and communications theory
Iterative algorithms
Nonlinearity
Personal digital assistants
Probabilistic methods
Probability theory
Signal and communications theory
Signal processing algorithms
Signal, noise
Telecommunications and information theory
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Summary:This letter proposes a new frequency domain turbo equalization algorithm based on nonlinear minimum-mean- squared-error (MMSE) estimation. The conceptual basis of the proposed equalizer is the probabilistic data association (PDA) filtering. It is shown that by performing internal equalizer iterations, of which structure is resulted from the algorithm derivation according to the PDA concept, the convergence properties, analytical and verified by simulations, can be significantly improved over conventional MMSE turbo equalization techniques. Results of the simulations conducted to demonstrate the superiority of the proposed algorithm and to verify the accuracy of the analysis are presented in this letter.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2008.071600.