Equalization Algorithms For Two Dimensional Intersymbol Interference Channels
Yiming Chen · Research Exchange (Washington State University) · 2011
This dissertation presents several novel iterative soft decision feedback equalization algorithms for detection of binary-valued two-dimensional images corrupted by 2D intersymbol interference (ISI) and additive white Gaussian noise (AWGN).These algorithms exchange weighted soft extrinsic information between maximum-a-posteriori (MAP) detectors employing different row-column or zigzag scan directions.We first use an independent assumption on the a priori probabilities (APP) used in the computation of the BCJR algorithm, where the extrinsic information transmission (EXIT) charts are used to speed up the optimization of the weight and iteration schemes.Simulation results for the 2 × 2 averaging mask channel show that, at low signal-tonoise ratios (SNR), the new zigzag algorithm gains about 1 dB over previous iterative row-column soft decision feedback algorithm and over a separable-mask algorithm, two of the best previously published schemes.When the zigzag algorithm is serially concatenated with the row-column algorithm, the concatenated system performs better than four of the