FFT/IFFT Based Blind SIMO Channel Identification

Article Sidebar

PDF
Published: Nov 22, 2007
DOI: https://doi.org/10.37936/ecti-eec.200862.171784

Main Article Content

Song Wang
Department of Electronic Engineering, La Trobe University
Jonathan H. Manton
Department of Information Engineering, Australian National University

Abstract

This paper presents an FFT/IFFT based blind identification method for estimating the finite impulse response of single-input multiple-output channels driven by an unknown deterministic signal. The proposed algorithm successfully handles a very small size of received data, for which the existing blind channel estimation methods, including the subspace, cross-relation and shifted correlation algorithms, are known to be ineffective. Moreover, with no assumption of the precise knowledge of channel order, the proposed algorithm is capable of estimating channel parameters as well as detecting channel order. Simulations show that the proposed algorithm outper forms the existing methods in small sample size situations.

Article Details

How to Cite
Wang, S., & Manton, J. H. (2007). FFT/IFFT Based Blind SIMO Channel Identification. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 6(2), 158–163. https://doi.org/10.37936/ecti-eec.200862.171784
Issue
Vol. 6 No. 2 (2008): Regular Issue
Section
Research Article

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

- Creative Commons Copyright License

The journal allows readers to download and share all published articles as long as they properly cite such articles; however, they cannot change them or use them commercially. This is classified as CC BY-NC-ND for the creative commons license. 

- Retention of Copyright and Publishing Rights

The journal allows the authors of the published articles to hold copyrights and publishing rights without restrictions.

References

[1] W. A. Gardner, editor. Cyclostationarity in Communications and Signal Processing. IEEE Press, 1994.

[2] G. B. Giannakis, Y. Hua, P. Stoica and L. Tong, editors. Signal Processing Advances in Wireless and Mobile Communications. Vol. 1: Trends in Channel Estimation and Equalization. Prentice Hall PTR, 2001.

[3] E. Moulines, P. Duhamel, J.F. Cardoso and S. Mayrargue, "Subspace methods for the blind identification of multichannel FIR filters," IEEE Trans. Signal Processing, vol. 43, no. 2, pp. 516-525, 1995.

[4] G. Xu, H. Liu, L. Tong and T. Kailath, "A least squares approach to blind channel identification," IEEE Trans. Signal Processing, vol. 43, no. 12, pp. 2982-2993, 1995.

[5] S. Chen and T. Yao, "An eigenanalysis-based method for blind channel identification and equalisation," European Trans. Telecommunications, vol. 16, pp. 349-355, 2005.

[6] H. Gazzah, P.A. Regalia, J-P. Delmas and K. Abed-Meraim, "A blind multichannel identification algorithm robust to order overestimation," IEEE Trans. Signal Processing, vol. 50, no. 6, pp. 1449-1458, 2002.

[7] L. Tong and S. Perreau, "Multichannel blind identification: from subspace to maximum likelihood methods," Proc. of IEEE, vol. 86, no. 10, pp. 1951-1968, 1998.

[8] C.-Y. Chi, C.-Y. Chen, C.-H.Chen, C.-C. Feng and C.-H. Peng, "Blind identification of SIMO systems and simultaneous estimation of multiple time delays from HOS-based inverse filter criteria," IEEE Trans. Signal Processing, vol. 52, no. 10, pp. 2749-2761, 2004.

[9] Y. Hua and M.Wax, "Strict identifiability of multiple FIR channels driven by an unknown arbitrary sequence," IEEE Trans. Signal Processing, vol. 44, no. 3, pp. 756-759, 1996.

[10] A. Scaglione, G.B. Giannakis and S. Barbarossa, "Redundant filterbanks precoders and equalizers, Part I & Part II," IEEE Trans. Signal Processing, vol. 47, no. 7, pp. 1988-2022, 1999.