Line qualification with neural networks

Details Line qualification with neural networks Line qualification with neural networks

1999-09-30

2004-02-03

Tieu, Binh (Department: 2643)

Telephonic communications

Diagnostic testing, malfunction indication, or electrical...

Of data transmission

C379S024000, C379S027010

Reexamination Certificate

active

06687336

ABSTRACT:

BACKGROUND OF THE INVENTION
This application relates generally to communications networks, and more particularly, to testing communication lines.
Recently, there has been an increased demand for plain old telephone systems (POTS's) to carry high-speed digital signals. The demand has been stimulated by home access to both the Internet and distant office computers. Both types of access typically employ a POTS line as part of the path for carrying digital signals.
POTS's lines were built to carry voice signals at audible frequencies and can also carry digital signals as tones in the near audible frequency range. Modern digital services such as ISDN and ADSL transmit data at frequencies well above the audible range. At these higher frequencies, POTS's lines that transmit voice signals well may transmit digital signals poorly. Nevertheless, many telephone operating companies (TELCO's) would like to offer ISDN and/or ADSL data services to their subscribers.
Telephone lines between a TELCO switch and a subscriber's premises are frequent sources of poor performance at the high frequencies characteristic of ISDN and ADSL transmissions. Nevertheless, high cost has made widespread replacement of these subscriber lines an undesirable solution for providing subscribers with lines capable of supporting ISDN and ADSL. A less expensive alternative would be to remove only those subscriber lines that are inadequate for transmitting high-speed digital data.
To enable limited replacement of inadequate lines, TELCO's have placed some emphasis on developing methods for predicting which subscriber lines will support data services, such as ISDN and ADSL. Some emphasis has been also placed on predicting frequency ranges at which such data services will be supported. Some methods have also been developed for finding faults in subscriber lines already supporting data services so that such faults can be repaired.
Current methods for predicting the ability of subscriber lines to support high-speed digital transmissions are typically not automated and labor intensive. Often, these methods entail using skilled interpretations of high frequency measurements of line parameters to determine data transmission abilities. At a network scale, such tests are very expensive to implement.
The present invention is directed to overcoming or, at least, reducing the affects of one or more of the problems set forth above.
SUMMARY OF THE INVENTION
In a first aspect, the invention provides a method of testing a subscriber line. The method includes determining values of electrical line features from electrical measurements on the subscriber line and processing a portion of the values of the electrical features with a neural network. The neural network predicts whether the line qualifies to support one or more preselected data services from the portion of the values.
In a second aspect, the invention provides a method of constructing a test for qualifying subscriber lines for data transmissions. The method includes obtaining electrical feature and qualification data for sample lines of a training set and determining parameters defining a neural network from the data of the training set. The network is configured to use values of electrical properties of a subscriber line to predict whether the subscriber line qualifies for one or more preselected data services.
In a third aspect, the invention provides a method of testing a subscriber line. The method includes determining values of electrical features of the line from electrical measurements on the subscriber line and forming a vector having the values as components. The method also includes determining whether the vector is a member of a cluster of feature vectors and predicting whether the line qualifies for a data service based in part on the determination of cluster membership. Feature vectors of the cluster are associated with sample lines of a training set.
In a fourth aspect, the invention provides a data storage medium storing a computer executable program of instructions for performing one or more of the above-described methods.


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