Adaptive Channel Prediction Based on Polynomial Phase Signals
Paper in proceedings, 2008

Motivated by recently published physics based scattering SISO and MIMO channel models, a new adaptive channel prediction using Kalman filter based on non-stationary polynomial phase signals with time-varying amplitudes is proposed. To mitigate the influence of the time-varying amplitudes on parameter estimation, an iterative estimation using the Non-linear instantaneous LS criterion is proposed, where the number of signal components and model orders are known. The new predictor outperforms the classical Linear Prediction and stationary sinusoidal modeling based prediction in Monte Carlo simulations.

Adaptive Kalman filtering

Rayleigh channels

Nonlinear estimation

Radio propagation

Prediction methods

Author

Ming Chen

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Mats Viberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Stefan Felter

Telefonaktiebolaget LM Ericsson

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP; Las Vegas, NV; United States; 31 March 2008 through 4 April 2008

1520-6149 (ISSN)

2881-2884

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/ICASSP.2008.4518251

ISBN

978-142441484-0

More information

Created

10/8/2017