Design and Analyses of a Fast Feed-forward Blind Equalizer with Two-Stage Generalized Multilevel Modulus and Soft Decision-Directed Scheme for High-Order QAM Cable Downstream Receivers

In the present study, a fast feed-forward blind equalizer with a two-stage generalized multilevel modulus algorithm (GMMA) and soft decision-directed (SDD) scheme was developed for high-order QAM cable receivers on broadcasting downstream wired cable channels. The proposed fast blind equalization algorithm uses a two-stage convergence strategy, and the modified SDD part applies an adaptively selected decision region. At the first convergence stage, joint GMMA and modified SDD equalization was applied for fast convergence. When the convergence process reached the steady state, the convergence detector changed the first equalization stage to the second stage. At the second stage, the modified SDD scheme reduced the mean square error (MSE) further. To prove the convergence, MSE analyses of two-stage GMMA+SDD/SDD blind equalization in the steady state were conducted. On the wired cable channel at 64, 256, and 1024QAM modes, the proposed blind algorithm had a faster convergence speed than previous blind methods. The proposed algorithm also achieved a smaller MSE than the other methods at the same signal-to-noise ratio (SNR). When the proposed method used the architecture of the decision-feedback equalizer (DFE) with a SDD-based feedback FIR filter (FBF), the steady-state MSE and bit-error-rate (BER) decreased further

Design and Analyses of a Fast Feed-forward Blind Equalizer with Two-Stage Generalized Multilevel Modulus and Soft Decision-Directed Scheme for High-Order QAM Cable Downstream Receivers

In the present study, a fast feed-forward blind equalizer with a two-stage generalized multilevel modulus algorithm (GMMA) and soft decision-directed (SDD) scheme was developed for high-order QAM cable receivers on broadcasting downstream wired cable channels. The proposed fast blind equalization algorithm uses a two-stage convergence strategy, and the modified SDD part applies an adaptively selected decision region. At the first convergence stage, joint GMMA and modified SDD equalization was applied for fast convergence. When the convergence process reached the steady state, the convergence detector changed the first equalization stage to the second stage. At the second stage, the modified SDD scheme reduced the mean square error (MSE) further. To prove the convergence, MSE analyses of two-stage GMMA+SDD/SDD blind equalization in the steady state were conducted. On the wired cable channel at 64, 256, and 1024QAM modes, the proposed blind algorithm had a faster convergence speed than previous blind methods. The proposed algorithm also achieved a smaller MSE than the other methods at the same signal-to-noise ratio (SNR). When the proposed method used the architecture of the decision-feedback equalizer (DFE) with a SDD-based feedback FIR filter (FBF), the steady-state MSE and bit-error-rate (BER) decreased further