Abstract
In this paper, a new adaptive method is proposed to estimate blind minimum mean-square error equalizer with arbitrary delay of single-input-multiple-output channel. By using a recursive least-square-similar algorithm to recursively update a correlation matrix and its pseudo-inverse, the proposed algorithm ensures convergence and is not sensitive to the initialization of its parameters. Compared with other batch-type approaches, the new adaptive method does not require to compute the pseudo-inverse or singular value decomposition directly, consequently does not need rank estimation nor channel order estimation. Furthermore, the fast convergence enables the proposed method to be used in real time communication applications. Simulation results are provided to demonstrate the performance of the proposed method.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahn KS, Cho J, Baik HK (2004) Blind adaptive channel equalization using multichannel linear prediction-based cross-correlation vector estimation. IEEE Trans Consum Electron 50(4):1026–1032
Chen Y, Lin C (2008) Blind-channel identification for mimo single-carrier zero-padding block-transmission systems. IEEE Trans Circuits Syst-I Regul Pap 55(6):1571–1579
Giannakis GB, Halford SD (1997) Blind fractionally spaced equalization of noisy fir channels: direct and adaptive solutions. IEEE Trans Signal Process 45:2277–2292
Haykin S (1996) Adaptive filter theory, 4th edn. Prentice-Hall, Englewood Cliffs
Li J, Kim K (2012) Hidden attribute-based signatures without anonymity revocation. Inf Sci 180(9):1681–1689
Li J, Wang Y (2006) Universal designated verifier ring signature (proof) without random oracles, lecture notes in computer science. In: Zhou X, Sokolsky O, Yan L, Jung E-S, Shao Z, Mu Y, Lee DC, Kim DY, Jeong Y-S, Xu C-Z (eds) Emerging directions in embedded and ubiquitous computing, vol 4097. Springer, Heidelberg, pp 332–341
Li X, Fan H (2000a) Direct estimation of blind zero-forcing equalizers based on second-order statistics. IEEE Trans Signal Process 48:2211–2218
Li X, Fan H (2000b) Linear prediction methods for blind fractionally spaced equalization. IEEE Trans Signal Process 48:1667–1675
Pan YC, Phoong SM (2012) An improved subspace-based algorithm for blind channel identification using few received blocks. IEEE Trans Commun 61(9):3710–3720
Proakis J (1995) Digital communications, 3rd edn. McGraw-Hill, New York
Shen J, Ding Z (2000) Direct blind MMSE channel equalization based on second-order statistics. IEEE Trans Signal Process 48(4):1015–1022
Tong L, Xu G, Kailath T (1994) Blind identification and equalization based on second-order statistics: a time domain approach. IEEE Trans Inf Theory 40:340–349
Xie S, He ZS, Gao Y (2006) Adaptive theory of signal processing, 1st edn. Chinese Science Press, Beijing
Yu C, Zhang C, Xie L (2012) Blind identification of multi-channel ARMA models based on second-order statistics. IEEE Trans Signal Process 60(8):4415–4420
Zhang JK, Huang F (2010) Blind unique identification of mimo channels using signal designs and high-order moments. IEEE Trans Signal Process Lett 17(6):539–542
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, C., Yu, J. An adaptive algorithm for blind MMSE equalization of SIMO channels. J Ambient Intell Human Comput 6, 597–602 (2015). https://doi.org/10.1007/s12652-014-0229-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-014-0229-8