Nonlinear prediction of mobile radio channels: measurements and MARS model designs

The rapid time variation of mobile radio channels is often modeled as a random process with second order moments reflecting vehicle speed, bandwidth and the scattering environment. These statistics typically show that there is little room for prediction of channel properties such as received power o...

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Published in1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258) Vol. 5; pp. 2667 - 2670 vol.5
Main Authors Ekman, T., Kubin, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Adaptive systems
Bandwidth
Land mobile radio
Mars
Mutual information
Random processes
Scattering
Statistics
Vehicles
Wideband
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Summary:The rapid time variation of mobile radio channels is often modeled as a random process with second order moments reflecting vehicle speed, bandwidth and the scattering environment. These statistics typically show that there is little room for prediction of channel properties such as received power or complex taps of the impulse response coefficients, at least when linear predictor structures are considered. We use mutual information estimation to measure statistical dependencies in sequences of wideband mobile radio channel data and find significant nonlinear dependencies, far exceeding the linear component. Based on these upper limits for the predictability of channel evolution over time intervals up to 30 ms ahead, we develop practical nonlinear predictor systems using multivariate adaptive regression splines (MARS). We demonstrate computationally efficient schemes that increase the prediction horizon beyond 10 ms, compared to less than 4 ms with linear predictors at comparable prediction gains.
ISBN:0780350413
9780780350410
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1999.761246