Nortel Networks Corporation

Northern Telecom Limited

Richard Buz

Edgar Velez

Ian Dublin

Sisay Yirga

A blind convergence process for an adaptive decision feedback equalizer that includes an quadrature amplitude modulation (QAM) slicer having a index n, a forward filter defined by a plurality of forward tap coefficients and a feedback filter defined by a plurality of feedback tap coefficients. The blind convergence process includes initializing the forward tap coefficients of the forward filter and the feedback tap coefficients of the feedback filters with predetermined values. The slicer operates in two modes: a clustering mode and a decision directed mode. In the clustering mode the following steps are performed: (1) update the forward tap coefficients of the forward filter using an error estimate (e.g. Sato error), and (2) update the feedback tap coefficients of the feedback filter using an error estimate (e.g. Sato error). In the decision directed mode the following steps are performed: (1) update the forward tap coefficients of the forward filter for a prescribed QAM index n using actual error, and (2) update the feedback tap coefficients of the feedback filter for a prescribe QAM index n using actual error. This process enables blind convergence of an equalizer for a wide range of QAM indexes (e.g. 4-256).

Clustering blind convergence process in an adaptive decision feedback equalizer

A method of detecting misconvergence in an equalizer having a quadrature amplitude modulation (QAM) slicer having an index n. The method includes the steps of initializing a plurality of signal counters then processing random symbols (for example between 500 and 20000 symbols) through the equalizer where the symbols are quantized into an appropriate constellation point in an n-QAM constellation map, where each signal counter corresponds to a respective one of the constellation points in the constellation map. The signal counters are incremented when one of the symbols is quantized to the corresponding constellation point. After the signals have been processed into the constellation map the number of non-zero counters are detected. If the number of non-zero counters is less than a prescribed number (for example between approximately 0.5n and approximately 0.9n), then the equalizer has not converged and if the number of non-zero counters is equal to or greater than the prescribed number than the equalizer has converged.

Method of detection of misconvergence using constellation scanning in an equalizer

A method of estimating signal-to-noise ratio at an output of an adaptive decision feedback equalizer receiving an input signal. The method of SNR estimation includes (a) calculating an average output error of the equalizer; and (b) estimating the signal-to-noise ratio (SNRest&equals;k,&minus;20 log,(Eavg)) where k,is a constant based on a QAM index n and Eavg is the average output error of the equalizer. The estimated SNR can be used to detect proper equalizer convergence by comparing the estimated SNR to an SNR threshold (e.g. lowest SNR for a 4QAM signal), wherein the equalizer is not properly converged when the estimated SNR is lower than the SNR threshold. The estimated SNR can also be used to adjust the operating QAM index of the equalizer by comparing the estimated SNR to an ideal SNR based on an objective bit error rate for a prescribed QAM index, and reconverging the equalizer at a QAM index lower than the prescribed QAM index when the estimated SNR is lower than the ideal SNR.

Method and apparatus for operating an adaptive decision feedback equalizer

A blind convergence process for an adaptive decision feedback equalizer having an quadrature amplitude modulation (QAM) slicer, a forward filter defined by a plurality of forward tap coefficients and a feedback filter defined by a plurality of feedback tap coefficients. The blind convergence process includes the step of initializing the forward tap coefficients of the forward filter and the feedback tap coefficients of the feedback filters with predetermined values. The QAM slicer operates in two modes: a clustering mode and a decision directed mode. The clustering mode includes the step of updating only the forward tap coefficients of the forward filter for a prescribed start-up QAM index (such a 4 QAM). The decision directed mode is predefined for set of QAM indexes having values n,, n,, . . . n,, and includes: updating the forward tap coefficients of the forward filter for a QAM index n,selected from the predefined set of QAM indexes, and updating the feedback tap coefficients of the feedback filter for the QAM index n,selected from the predefined set of QAM indexes. The decision directed processing steps are repeating the next QAM index n,of the predefined set of QAM indexes until the equalizer has converged to its highest available QAM index or until the equalizer has converged to the highest operable QAM index (constellation). The QAM index set can be &lcub;4,16,64,256&rcub;.

Sequential blind convergence process in an adaptive decision feedback equalizer

A method of reducing leakage noise introduced to an equalizer in a modem during steady state operation. The equalizer includes forward and feedback filters represented by tap coefficients. The tap coefficients of the filters are updated using least mean squares adaptation equations at a symbol rate during steady state operation. The method of the invention includes the steps of: (a) reducing the absolute value of the updated tap coefficients of the filters at a prescribed rate that is less than the symbol rate. Long term convergence stability is improved and leakage noise is reduced by leaking the filter coefficients less frequently than the symbol rate.

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Rohnert Park, CA, United States of America

Richard Buz