A Cost Function for Joint Blind Equalization and Phase Recovery
Commenced in January 2007
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A Cost Function for Joint Blind Equalization and Phase Recovery

Authors: Reza Berangi, Morteza Babaee, Majid Soleimanipour

Abstract:

In this paper a new cost function for blind equalization is proposed. The proposed cost function, referred to as the modified maximum normalized cumulant criterion (MMNC), is an extension of the previously proposed maximum normalized cumulant criterion (MNC). While the MNC requires a separate phase recovery system after blind equalization, the MMNC performs joint blind equalization and phase recovery. To achieve this, the proposed algorithm maximizes a cost function that considers both amplitude and phase of the equalizer output. The simulation results show that the proposed algorithm has an improved channel equalization effect than the MNC algorithm and simultaneously can correct the phase error that the MNC algorithm is unable to do. The simulation results also show that the MMNC algorithm has lower complexity than the MNC algorithm. Moreover, the MMNC algorithm outperforms the MNC algorithm particularly when the symbols block size is small.

Keywords: Blind equalization, maximum normalized cumulant criterion (MNC), intersymbol interference (ISI), modified MNC criterion (MMNC), phase recovery.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076720

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References:


[1] J.A. Cadzow, "Blind deconvolution via cumulant extrema," IEEE Signal Processing Magazine, vol. 13, no. 3, pp. 24 - 42, May 1996.
[2] C.-Y. Chi and M.-C. Wu, "Inverse filter criteria for blind deconvolution and equalization using two cumulants," Signal Processing, vol. 43, no. 1, pp. 55 - 63, Apr. 1995.
[3] C.-C. Feng and C.-Y. Chi, "Performance of cumulant based inverse filters for blind deconvolution, " IEEE Trans. Signal Processing, vol. 47, no. 7, July 1999.
[4] C.-C. Feng and C.-Y. Chi, C.-H. Chen, "Blind Equalization and System Identification: Batch Processing Algorithms, Performance and Applications, " Springer Publications , 2006.
[5] C.-Y. Chi, C.-Y. Chen, C.-H. Chen, C.-C. Feng, "Batch Processing Algorithm for Blind Equalization Using Higher-Order Statistics," IEEE Signal Processing Magazine, January 2003.
[6] M. Babaee, "Design, Simulation and Improvement of a Blind Equalization Algorithm," Master-s thesis, Imam Hossein University, Tehran, Iran, July 2007.
[7] 0. Shalvi and E. Weinstein, "Super-exponential methods for blind deconvolution," IEEE Trans. Information Theory, vol. 39, no. 2, pp. 504-519, March 1993.