Recursive least-squares decision-directed tracking of doubly-selective channels using exponential basis models

Authors:
Hyosung Kim;Jitendra K. Tugnait
Affiliations:
Department of Electrical&Computer Engineering, Auburn University, AL 36849, USA;Department of Electrical&Computer Engineering, Auburn University, AL 36849, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Forgetting factor selection in RLS decision-directed tracking of doubly-selective channels

Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers

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Abstract

We present a decision-directed tracking approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (CE-BEM). The time-varying nature of the channel is well captured by the CE-BEM while the time-variations of the (unknown) BEM coefficients are likely much slower than those of the channel. We track the BEM coefficients via the exponentially-weighted recursive least-squares (RLS) algorithm, aided by symbol decisions from a decision-feedback equalizer (DFE). Simulation examples demonstrate its superior performance over an existing subblock-wise channel tracking scheme.