Open Access Open Access  Restricted Access Subscription or Fee Access

Novel Semi-blind Channel Estimation Schemes for Rayleigh Flat Fading MIMO Channels

Jaymin Bhalani, Dharmendra Chauhan, Y.P. Kosta, A.I. Trivedi

Abstract


In this paper, we propose two novel semi-blind channel estimation techniques based on QR decomposition for Rayleigh flat fading Multiple Input Multiple output (MIMO) channel using different receiver antenna combinations and various pilot symbols. In the first technique, the flat-fading MIMO channel matrix H can be decomposed as a upper triangular matrix R and a unitary rotation matrix Q as H=RQ. The matrix R is estimated blindly from only received data by using orthogonal matrix triangularization based house holder QR decomposition, while the optimum rotation matrix Q is estimated exclusively from pilot based Orthogonal Pilot Maximum Likelihood Estimator (OPML) algorithm. In the second technique, joint semi-blind channel and data estimation is performed using QR decomposition based Least Square (LS) algorithm. Simulations have taken under 4-PSK data modulation scheme for two transmitters and different combinations of receiver antennas as well as various training symbols. Finally, these two new techniques compare with Whitening Rotation (WR) based semi-blind channel estimation technique and results shows that those new techniques achieve very nearby performance with low complexity compare to Whitening rotation based technique. Also first technique with perfect R outperforms Whitening Rotation based technique.

Keywords


Multiple Input Multiple Output, Orthogonal Pilot ML Estimator, QR Decomposition, Semi Blind Channel Estimation

Full Text:

PDF

References


J.G.Proakis, Digital Communications, McGraw-Hill Higher Education, New York, 2001.

D Pal, “Fractionally spaced semi-blind equalization of wireless channels,” The Twenty-Sixth Asilomar Conference, 1992, vol. 2, pp. 642–645.

E. De Carvalho and D. T. M. Slock, “Asymptotic performance of ML methods for semi-blind channel estimation,” Thirty-First Asilomar Conf., 1998, pp. 1624–1628.

A.Medles, D.T.M. Slock, and E.D.Carvalho, “Linear prediction based semi-blind estimation of MIMO FIR channels,” Third IEEE SPAWC, Taiwan, pp.58-61, 2001.

A. K. Jagannatham and B. D. Rao, “A semi-blind technique for MIMO Channel matrix estimation,” in Proc. of IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2003), Rome, Italy, pp no. 304-308.

Xia Liu, Feng Wang and Marek E. Bialkowski “Investigation into a Whitening-Rotation-Based Semi-blind MIMO Channel Estimation for Correlated” International Conference on Signal Processing and Communication Systems, ICSPCS 2008. pp no-1-4.

Qingwu Zhang, Wei-Ping Zhu, Qingmin Meng, „Whitening-rotation-based semi-blind estimation of MIMO FIR channels‟ .International Conference on Wireless Communications & Signal Processing, WCSP 2009, pp. 1-4.

Feng Wan, Wei-Ping Zhu and M.N.S. Swamy „Perturbation Analysis of Whitening-Rotation-based Semi-Blind MIMO Channel Estimation‟ IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09,2009 pp 240-243.

F. Wan, W.-P. Zhu, and M. N. S. Swamy, “A semi-blind channel estimation approach for MIMO-OFDM systems”, IEEE Trans. on Signal Processing, vol. 56, no. 7, pp. 2821–2834, 2008.

A. K. Jagannatham and B. D. Rao, “Whitening-rotation-based semiblind MIMO channel estimation,” IEEE Trans. on Signal Processing, vol. 54, no. 3, pp. 861–869, 2006.

M Kiessling, J Speidel and Y Chen, “MIMO Channel estimation in correlated fading environments,”: in proceeding of 58th IEEE vehicular technology conference (VTC‟03), Orlando, pp. 1187-91, OCT 2003.

G Xie, X Fang, A Yang and Y Liu, “Channel estimation with pilot symbol and spatial correlation information,”: in proceeding of IEEE international Symposium on communication and information Technologies (ISCIT‟07), Sydney, pp.1003-6, OCT 2007.

S M Kay, Fundamentals of statistical signal processing: Estimation Theory. Prentice – Hall, Upper saddle River, NJ 07458, 1993.

G K Krishnan and V U Reddy, “MIMO Communication – motivation and a practical realization,” IETE Tech Rev, Vol.24,No.4,pp.203-13, jul-aug 2007.

Two and P A Hoeher, “Semi – Blind Channel estimation for frequency selective MIMO system,” in IST Mobile Summit, Dresden, jun 2005.

T Cui and C Tellambura, “Semiblind Channel estimation and data detection for OFDM System with optimal pilot design, “ IEEE Trans. Commun, Vol.55,No.5,pp. 1053-62, may 2007.

Two, P A Hoeher, A Scherb and K D Kammeyer,”Performance analysis of maximum – likelihood semi blind estimation of MIMO Channel,” in Proceedings of 63rd IEEE vehicular Technology Conference (VCT), Melbourne,pp. 1738-42, may 2006.

S Chen, X C Yang, L Chen and L hanzo, “ Blind joint maximum likelihood channel estimation and data detection for SIMO System,” int. J.Auto.Comput., Vol.4, no.1,pp.47-51, jan 2007.

K Sabri, M El Badaoui, F Guillet, A Adib and D Aboutajdine, “A Frequency domain based apporch for blind MIMO System identification using second order cyclic statistics,” Elsevier signal Processing, vol.89, No.1,pp.77-86,jan 2009.

I M Panahi and venket, “Blind identification of multi-channel system with single input and unknown order,” Elsevier signal processing, vol.89, No.7,pp.1288-310,jul 2009.

M Abuthinien, S Chen, A Wolfgang, and L Hanzo, “jont maximum likelihood channel estimation and data detection for MIMO system,”: in proceeding of IEEE international conference on Communication (ICC‟07),Glasgow,pp.5354-8,jun 2007.

M A Khalighi and s Bourennane, “Semiblind single – carrier MIMO Channel estimation using overlay pilots, “IEEE Trans. Vehicular Tech., Vol.57,no.3,pp.1951-6, May 2008.

B Chen and A P Petropulu, “ Frequency Domain blind Mimo System identification based on second and higher order statistics,” IEEE Trans. Signal Process., Vol.49, No.8,pp.1677-88, Aug 2001.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.