Iterative soft decision feedback zig-zag equalizer for 2D intersymbol interference channels

Authors:
Yiming Chen;Patrick Njeim;Taikun Cheng;Benjamin J. Belzer;Krishnamoorthy Sivakumar
Affiliations:
School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA;Boeing Commercial Airplanes, Seattle, WA;Microtune Inc., Boulder, CO;School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA;School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA
Venue:
IEEE Journal on Selected Areas in Communications
Year:
2010

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Abstract

We present a novel iterative soft decision feedback zig-zag algorithm for detection of binary images corrupted by two dimensional intersymbol interference and additive white Gaussian noise. The algorithm exchanges soft information between maximum-a-posteriori detectors employing different zigzag scan directions. Each detector exploits soft-decision feedback from the other zig-zag detectors. Simulation results for the 2×2 averaging mask channel show that, at low signal-to-noise ratios, the new algorithm gains about 1 dB over an iterative rowcolumn soft decision feedback algorithm and over a separablemask algorithm, two of the best previously published schemes. When the zig-zag algorithm is concatenated with the row-column algorithm, the concatenated system performs as well as or better than four of the best previously published algorithms, at both low and high signal-to-noise ratios, for a variety of 2 × 2 and 3 × 3 convolution masks; in several cases, the system performs within less than 0.1 dB of the maximum-likelihood performance bound.