Simplified Kalman Estimation of Fading Mobile Radio Channels:
High Performance at LMS Computational Loads.

Lars Lindbom

NUTEK Workshop on Digital Communications, Uppsala, Sweden, May 25-26, 1992.

In Pdf

Outline:

Parameters of time-varying systems are often estimated by adaptive algorithms with sliding time-windows, which discount old data. We may then face a dilemma: the use of a short data window (or, equivalently, a large adaptation gain) results in noisy estimates. With a long data window (small gain), time varying parameters are tracked with a considerable delay. To improve the accuracy, the present paper suggests a low-complexity algorithm which takes a priori information about the properties of the time-variations into account, in the form of stochastic models.

Abstract:

A low complexity algorithm for channel estimation in Rayleigh fading environments is presented. The channel estimators are presumed to operate in conjunction with a Viterbi detector. The algorithms are based on simplified internal modelling of time-variant channel coefficients and approximation of a Kalman estimator.

A novel averaging approach is used to replace the on-line update of the Riccati equation. Compared to RLS tracking, both a significantly lower bit error rate and a much lower computational complexity is attained.

Related publications:

Conference paper in IEEE ICASSP'93, on the above theme.
Licentiate thesis by L Lindbom, with more details on the algorithm.
Sinusoid modelling of time-varying channel coefficients in D-AMPS systems.
PhD Thesis by L Lindbom 1995, presenting an improved general design methodology.