摘要:
A generalized form of a multimodulus algorithm (GMMA) is described for use in blind equalization. A receiver uses a signal point constellation representing 256 levels. This signal space is divided into sample, or data, subsets. Cost function minimization is done with respect to each sample subset.
摘要:
A blind convergence technique is restricted to using a subset of equalizer output samples. Illustratively, a receiver implements a windowed MMA approach. In this windowed MMA approach, a sample window overlays the two-dimensional plane representing the set of equalizer output samples. Only those equalizer output samples appearing within the sample window are used during filter adaptation.
摘要:
A blind equalization technique uses both the "constant modulus algorithm" (CMA) and the "multimodulus algorithm" (MMA) during blind start-up. This approach provides the basis for a "transition algorithm." One example of a transition algorithm is the CMA-MMA transition algorithm in which an adaptive filter simply switches from CMA to MMA. Other examples are variations of the CMA-MMA transition algorithm and are illustrated by the "Constant Rotation CMA-MMA" transition algorithm and the "Dynamic Rotation CMA-MMA" transition algorithm.
摘要:
A blind equalization technique - the multimodulus algorithm (MMA) - adapts coefficients of an equalizer so as to minimize dispersion of the output samples, of the equalizer, around piecewise linear contours of a signal space. The MMA technique is illustrated in the context of both square and non-square signal point constellations.
摘要:
A blind convergence technique is restricted to using a subset of equalizer output samples. Illustratively, a receiver implements a windowed MMA approach. In this windowed MMA approach, a sample window overlays the two-dimensional plane representing the set of equalizer output samples. Only those equalizer output samples appearing within the sample window are used during filter adaptation.
摘要:
A blind equalization technique - the multimodulus algorithm (MMA) - adapts coefficients of an equalizer so as to minimize dispersion of the output samples, of the equalizer, around piecewise linear contours of a signal space. The MMA technique is illustrated in the context of both square and non-square signal point constellations.