The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 14, 1999

Filed:

Oct. 22, 1997
Applicant:
Inventors:

Yuri Goldstein, Southbury, CT (US);

Val Maizenberg, Danbury, CT (US);

William Hanna, Wolcott, CT (US);

Assignee:

PC Tel, Inc., Waterbury, CT (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04B / ; H04L / ;
U.S. Cl.
CPC ...
375222 ; 375232 ; 375233 ; 708323 ;
Abstract

A PCM modem equalizer includes an RBS estimator and decision modulator in conjunction with an adaptive equalizer such as a conventional decision feedback equalizer (DFE). The RBS estimator and decision modulator receives error signals from the second summer in the equalizer, receives the estimated R signals from the first summer of the equalizer, and outputs a gain correction signal which is applied to the output of the reference generator before the reference generator output is applied to the feedback equalizer and the second summer. The methods of the invention are based on the recognition that the effects of RBS can be detected in the amplitude modulation of the main training sequence stream. The modulation will occur in a periodic repetitive pattern of length 6*T where T is the symbol interval. Therefore, the invention applies a corrective gain to the decision in each time slot in a periodic manner having the same period 6*T. For each time interval T.sub.k over a period of 6*T, the symbol present at the time interval is sampled and a respective corrective gain g(6k-j) is applied to it, where j has the values 0 through 5. The gain applied to each of the six time slots is adaptively updated over a training period until each of the six gain coefficients is optimized.


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