Fading Channel Estimation Based on Noisy Autoregressive Model and Kalman Filter

Document Type : Original Article

Authors

Electrical Engineering Department, Shahid Chamran University of Ahvaz

Abstract

In this paper, a new method for estimation of flat fading is proposed. First, the channel is modeled by a noisy autoregressive (AR) model and then Zheng method is used to estimate the AR model parameters. After the model is determined, the channel is estimated using Kalman filter. Using simulations the performance of the proposed method is evaluated and compared with the other existing methods in terms of estimation accuracy and bit error rate (BER). Simulation results show that the proposed method outperforms the other existing methods.

Keywords


[1] Kalofonos, D. N., Stojanovic, M., Proakis, J. G., “Performance of adaptive MC- CDMA detectors in rapidly fading Rayleigh channels”, IEEE Trans. On Wireless Communications, vol. 2, pp. 229–239, March 2003.
[2] Baddour, K. E., Beaulieu, N. C., “Autoregressive modeling for fading channel simulation. IEEE Trans. on Wireless Communications”, vol. 4, pp.1650–1662, July 2005.
[3] Komninakis, C., Fragouli, C., Sayed, A. H. and Wesel, R. D., “Multi-input multi- output fading channel tracking and equalization using Kalman estimation”, IEEE Trans. On Signal Processing, vol. 50, pp. 1065-1076, May 2002.
[4] Cai, J., Shen, X. Mark, J., “Robust channel estimation for OFDM wireless communication systems - an H∞ approach”, IEEE Trans. on Wireless Communications, vol. 3, pp. 2060–2071, November 2004.
[5] Labarre, D., Grivel, E., Najim, M., “Dual H∞ algorithms for signal processing, application to speech enhancement”, IEEE Trans. on Signal Processing, vol. 55, no. 11, pp. 5195-5208, Nov. 2007.
[6] Jamoos, Ali, Abdo, Ahmad and Abdel Nour, Hanna. “Estimation of OFDM Time- Varying Fading Channels Based on Two-Cross-Coupled Kalman Filters”, Proc. Spring Science, 2008.
[7] Jakes, W. C., Microwave Mobile Communications, Wiley, New York, 1974.
[8] Zheng, W. X., “Autoregressive parameter estimation from noisy data”, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, vol. 47, no. 1, pp. 71–75, 2000.
[9] MN Ali, MA Zohdy, “Interactive Kalman Filtering for Differential and Gaussian Frequency Shift Keying Modulation with Application in Bluetooth”, Journal of Signal and Information Processing, 2012.
[10] Aldababseh, Mahmoud, Jamoos, Ali. “Estimation of FBMC/OQAM fading channels using dual Kalman filters”, The Scientific World Journal, 2014.