British Telecommunications Public Limited Company

Philip M Bull

Stephen A Cassidy

David M Rohlfing

Paul Benyon

Richard Gedge

Beum Seuk Lee

Daniel Gilks

Botond Virginas

David Rohlfing

Interference on DSL (Digital Subscriber Lines) systems can be identified by collecting modem data and determining, for a plurality of time intervals, whether the line is carrying traffic and/or whether there are errors on the line. The presence of interference can be inferred from the correlation of the traffic data and the error data.

Digital subscriber line interference identification

The invention describes a method of performing re-synchronizations on a DSL line to optimize the synchronization rate of the line. The line is monitored over a period of time, and a stable SNR margin is determined, below which the line is observed to lose synchronization. Historical synchronization rates and associated SNR margins for the line are recorded, and the highest stable synchronization rate is determined as the historical synchronization rate that does not have any associated SNR margins below the stable SNR margin. The method attempts to optimize the synchronization rate of the line towards this highest stable synchronization rate. To do this, the current target SNR margin imposed by DLM is identified, for example, by interrogating the DLM system or by noting the SNR margin on the line immediately after the most recent synchronizations. Assuming the current synchronization rate on the line is less than the highest stable rate, then the synchronization rate is optimized by triggering a synchronization of the line when the SNR margin is greater than the target SNR margin plus an additional predetermined amount. The result should be an increase in the synchronization rate, and can be repeated until the synchronization rate reaches the highest stable synchronization rate.

Smart dynamic line management

The present invention presents a method of identifying faults in a DSL line using upstream and downstream attenuation measurements, which can be obtained directly from the DSLAM or CPE, thus requiring no specialist test equipment nor disrupting service. A downstream over upstream attenuation ratio is calculated for a line, with calculations repeated over a population of lines. The distribution of ratios, as well as upper and lower thresholds, is determined based on the population. A line is identified as being potentially faulty if it has an attenuation ratio above the upper threshold or below the lower threshold. Specifically, an attenuation ratio below the lower threshold is identified as having a high resistance joint fault (caused by an imperfect connection or corrosion at a joint in at least one of the pairs of a line), and a ratio above the upper threshold as a shunt (caused by degradation of the insulation between the pairs of a line, and often coupled with water ingress).

Fault identification using line attenuations

The invention presents a method of identifying faults on a DSL line, typically intermittent faults arising from unstable joints in the DSL line. The method collects errored seconds data at the DSLAM and at the customer's premises equipment (CPE, typically a home hub or router). The error data collected at the DSLAM are termed near-end errors, and the error data collected at the CPE are termed far-end errors. The near-end and far-end data is then analyzed by applying regression analysis to determine if there is a correlation or match between the two sets of data. Matching data patterns are indicative of unstable or bad joints in the DSL line, and are typically intermittent and located near the customer's premises.

Identifying line faults using regression analysis on near and far end errors

Proposed is an improved method of determining the location of a common fault on a line in a telecommunications network. An overall performance measure is generated for each of the lines in the network based on various electrical measurements, highlighting potentially faulty lines. Nodes within the network also have a performance measure calculated based on the performance measures of the lines passing through the node. Examples of nodes include cross connection points, junction boxes, cabinets, and sections of cabling. A common faulty node is identified from all nodes along a line, based on the overall performance measures associated with those nodes. Then, all other faulty lines running through that node are identified. A distance to fault measurement is estimated for each of the identified faulty lines, using capacitance measurements for each line. A common fault location is determined based on aggregating the estimated distances to fault calculated for each of the identified faulty lines.

Fault localisation

A method of measuring the performance of a DSL line provides an indication of potential faults in the line. Analysis of broadband DSL is less straightforward than for other technologies, since 'normal' behavior depends on a number of factors, including line length and line quality, where normal behavior for a long line could be regarded as poor for a short line. The data transmission characteristics of a DSL line under test are measured with reference to its upstream line attenuation, then the results are compared with the model for the corresponding data transmission characteristic. A performance measure is calculated for each characteristic indicative of the difference between the measured characteristic and the observed 'average' for other lines having the same upstream line attenuation. A final line performance indicator is calculated based on the combination of all the individual performance measures, which provides a quantitative measure of a line's performance.

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Ipswich, United Kingdom

Philip M Bull