An Adaptive DFE Using Light-Pattern-Protection Algorithm in 12 NM CMOS Technology

Abstract

The sign-sign least-mean-squares (SSLMS) algorithm has been widely used in decision feedback equalizer (DFE) adaptation. However, the convergence direction of DFE tap coefficients in the training process is closely related to the data flow. In the case of extreme data flow, the coefficients may converge to inaccurate values, resulting in DFE sampling errors. This article proposes a novel light-pattern-protection (LPP) algorithm to achieve robustness. The LPP guarantees the convergence direction in extreme data flow and brings no loss of convergence rate in a balanced situation. Another advantage of LPP is good scalability, which can be demonstrated in two points. One point is that the convergence time does not increase as the number of DFE taps. The other is that extending the algorithm to the traditional SSLMS scheme requires insignificant hardware and power consumption.