Generalized training based channel identification

In this paper, we address the general problem of identifying convolutive channels when several training sequences are inserted in the transmitted data symbols stream. We analyze the general situation where the training sequences differ from each other. We consider quasi-static channels (i.e. the sampling period is several orders of magnitude below the coherence time of the channel). There are no requirements on the length of the training sequence and all the received symbols that contain contributions from the training symbols are used for the identification. We first propose an iterative method that quickly converges to the maximum likelihood (ML) channel estimate. We also derive a simple closed form expression that approximates the ML channel estimate.

[1]  Marc Moonen,et al.  Training based maximum likelihood channel identification , 2003, 2003 4th IEEE Workshop on Signal Processing Advances in Wireless Communications - SPAWC 2003 (IEEE Cat. No.03EX689).

[2]  Luc Deneire,et al.  Training sequence versus cyclic prefix-a new look on single carrier communication , 2001, IEEE Communications Letters.

[3]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[4]  M. Moonen,et al.  Semi-blind channel estimation for block transmissions with non-zero padding , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[5]  J. Cavers.  An analysis of pilot symbol assisted modulation for Rayleigh fading channels (mobile radio) , 1991 .

[6]  Thomas Kailath,et al.  Optimal training for frequency-selective fading channels , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[7]  Luc Deneire,et al.  Training sequence vs. cyclic prefix a new look on single carrier communication , 2000, Globecom '00 - IEEE. Global Telecommunications Conference. Conference Record (Cat. No.00CH37137).

[8]  Marc Moonen,et al.  A stochastic method for training based channel identification , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..