Title :
Nonlinear frequency domain MMSE turbo equalization using probabilistic data association
Author :
Grossmann, Marcus ; Matsumoto, Tad
Author_Institution :
Ilmenau Tech. Univ., Ilmenau
fDate :
4/1/2008 12:00:00 AM
Abstract :
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.
Keywords :
equalisers; filtering theory; least mean squares methods; nonlinear estimation; turbo codes; convergence properties; frequency domain turbo equalization algorithm; internal equalizer iterations; nonlinear minimum-mean- squared-error estimation; probabilistic data association; Algorithm design and analysis; Analytical models; Convergence; Covariance matrix; Equalizers; Filtering; Frequency domain analysis; Iterative algorithms; Personal digital assistants; Signal processing algorithms;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2008.071600.