Abstract
The predictor coefficients of a mobile radio channel predictor have to be adapted to the changes in the radio environment. A direct adaptive predictor for the taps of a mobile radio channel is proposed. The coefficients of the predictor are assumed to change according to a filtered random walk model and are tracked using a Kalman filter. The filtered random walk is the simplest linear model that describes smooth changes of the coefficients and that includes integration. The proper choice of tuning parameters is discussed.
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© 2003 Springer-Verlag Berlin Heidelberg
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Ekman, T. (2003). Adaptive Prediction of Mobile Radio Channels Utilizing a Filtered Random Walk Model for the Coefficients. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_179
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DOI: https://doi.org/10.1007/978-3-540-45224-9_179
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40803-1
Online ISBN: 978-3-540-45224-9
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