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Linear State Space Model Based Channel Estimation for High Mobility OFDM Systems

P. Saimadhuri, Chukka Rajasekhar


Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high data rate transmission in wireless communication and the channel estimation is very important for implementation of OFDM. Channel modeling and channel estimation in time varying channels become more challenging in high mobility communication channels. In this paper, cyclic prefix (CP) can be used as a source of channel information which is originally used to reduce inter symbol interference (ISI). The time varying channel is modeled as Complex Exponential Basis Expansion Model (CE-BEM). Based on the CP observation, we propose Linear State Space Model which reduces the complexity of Channel implementation. The proposed technique is evaluated on the basis of traditional channel model, tapped delay line model (TDL) and proposed channel model, complex exponential basis expansion model (CE-BEM).Channel estimation error MSEE is evaluated under different Doppler spreads using Cyclic Prefix (CP) and Conventional Training (CT) methods for previous and proposed channel models.


OFDM, Time Varying Channels, CE-BEM, TDL, Linear State Space Model, Cyclic Prefix, Conventional Training, Channel Estimation Error, MSEE

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Herman Rohling, “OFDM: Concepts for Future Communication Systems”, Springer link Publications

Wang X Liu, K.J.R, “Adaptive Channel estimation using Cyclic Prefix in multicarrier modulation systems”, IEEE Communication Letters

Bernard Sklar, “Digital Communication”, 2nd Edition, Prentice Hall Publications

Choi, Y. S., Voltz, P. J., &Cassara, F. A, “On channel estimation and detection for multicarrier signals in fast and selective Rayleigh fading channels”, IEEE Transactions on Communications, 2001

P.V. Naganjaneyulu, K.Satya Prasad, “Adaptive Channel Estimation in OFDM using Cyclic Prefix”, IJCNS December 2009

Ma, X., Giannakis, G. B., &Ohno, S, “Optimal training for block transmissions over doubly selective wireless fading channels”, IEEE Transactions on Signal Processing 2003

Andrea Goldsmith, “Wireless Communication”, Cambridge University Press

Georgios B. Giannakis, CihanTepedelenliogˇ lu,”Basis Expansion Models and Diversity Techniques for Blind Identification and Equalization of Time-varying Channels”, proceedings of the IEEE.

Ming-Xian Chang and Yu. T. Su “Model-Based Channel Estimation for OFDM Signals in Rayleigh Fading”, IEEE Transactions on Communications.

Tsatsanis, M. K., &Giannakis, G. B. (1996). Modeling and equalization of rapidly fading channels.Intl.Jnl. Of Adaptive Contr. Signal Processing, John Wiley and Sons

Gerald Matz, “A Method for Estimating Basis Expansion Model Coefficients of an OFDM Transmission Channel”, International paper 2011

S.Haykin, “Adaptive Filter Theory”, Pearson Publications

van de Beek, J. J., Edfors, O., Sandell, M.,Wilson, S. K.,&Borjesson, P. O. (1995).On channel estimation in OFDM systems. InProc.IEEE 45th Veh. Tech. Conf.

Steven M Kay, “Fundamentals of statistical Signal Processing – Estimation Theory”, Prentice Hall Publications.

Chen, S., & Yao, T. (2004). Intercarrier interference suppression and channel estimation for OFDM systems in time-varying frequency-selective fading channels. IEEE Transactions on Consumer Electronics


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