A Novel Blind Channel Estimation for a 2x2 MIMO System

Xia LIU, Marek E. BIALKOWSKI, Feng WANG

The University of Queensland, Brisbane, Australia.

DOI: 10.4236/ijcns.2009.25037                

Abstract

A novel blind channel estimation method based on a simple coding scheme for a 2 by 2 multiple input multiple output (MIMO) system is described. The proposed algorithm is easy to implement in comparison with conventional blind estimation algorithms, as it is able to recover the channel matrix without performing singular value decomposition (SVD) or eigenvalue decomposition (EVD). The block coding scheme accompanying the proposed estimation approach requires only a block encoder at the transmitter without the need of using the decoder at the receiver. The proposed block coding scheme offers the full coding rate and reduces the noise power to half of its original value. It eliminates the phase ambiguity using only one additional pilot sequence.

Keywords

MIMO, Channel Estimation, Semi-Blind Channel Estimation, Phase Ambiguity

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Telatar, “Capacity of multiple antenna Gaussian channels,” European Transactions on Telecommunications, Vol. 10, No. 6, pp. 585-595, November/December 1999.
[2]	G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas,” Wireless Personal Communications, Vol. 6, pp. 311-335, 1998.
[3]	S. Zhou, B. Muquet, and G. B. Giannakis, “Sub-space-based (semi-) blind channel estimation for block precoded space-time OFDM,” IEEE Transactions on Signal Processing, Vol. 50, No. 5, pp. 1215-1228, May 2002.
[4]	R. Zhang, “Blind OFDM channel estimation through linear Precoding: A subspace approach,” in Proceedings Asilomar’02, Pacific Grove, CA, November 2002.
[5]	E. Moulines, P. Duhamel, J. F. Cardoso, and S. Mayrargue, “Subspace methods for the blind identification of multichannel FIR filters,” IEEE Transactions on Signal Processing, Vol. 43, pp. 516-525, February 1995.
[6]	A. K. Jagannatham and B. D. Rao, “Whitening-rotation- based semi-blind MIMO channel estimation,” IEEE Transactions on Signal Processing, Vol. 54, No. 3, March 2006.
[7]	A. Jagannatham and B. D. Rao, “Constrained ML algorithms for semi-blind MIMO channel estimation,” Pro-ceedings of IEEE Communication Society Globecom, 2004.
[8]	X. Liu and M. E. Bialkowski, “SVD-Based blind channel estimation for a MIMO OFDM system employing a simple block precoding scheme,” Proceedings of IEEE Eurocon, Poland, 2007.
[9]	S. Shahbazpanahi, A. B. Gershman, and J. H. Manton, “Closed-form blind MIMO channel estimation for orthogonal space-time block codes,” IEEE Transactions on Signal Processing, Vol. 53, No. 12, December 2005.
[10]	S. M. Kay, “Fundamentals of statistic signal processing: Estimation theory,” Prentice-Hall, Incorporation, 1993.
[11]	M. Biguesh and A. B. Gershman, “MIMO channel estimation: Optimal training and tradeoffs between estimation techniques,” Proceedings ICC’04, Paris, France, June 2004.
[12]	M. Biguesh and A. B. Gershman, “Training-based MIMO channel estimation: A study of estimator tradeoffs and optimal training signals,” IEEE Transactions on Signal Processing, Vol. 54, No. 3, March 2000.
[13]	A. K. Jagannatham and B. D. Rao, “A semi-blind technique for MIMO channel matrix estimation,” Proceedings IEEE Workshop on SPAWC, Roma, Italy, 2003.