Methods and Apparatus to Combine Data from Multiple Sources to Characterize Communication Systems

• US 20090161741A1
• Filed: 04/27/2007
• Published: 06/25/2009
• Est. Priority Date: 05/01/2006
• Status: Active Grant

• Current Assignee: Assia Spe LLC
• Original Assignee: Adaptive Spectrum and Signal Alignment, Incorporated, AT&T Knowledge Ventures, L.P. (AT&T, Inc.)
• Inventors: Brady, Mark H., Ginis, George
• Granted Patent: US 8,902,958 B2
• Time in Patent Office: Days
• US Class Current: 375/224
• CPC Class Codes: H04B 3/46 Monitoring; Testing
• CPC Class Codes: H04L 12/6418 Hybrid transport
• CPC Class Codes: H04L 2012/6478 Digital subscriber line, e.g. DSL, ADSL, HDSL, XDSL, VDSL
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 65/80 Responding to QoS
• CPC Class Codes: H04L 69/323 in the physical layer [OSI layer 1]
• CPC Class Codes: H04M 11/062 using different frequency bands for speech and other data
• CPC Class Codes: H04M 3/304 and using xDSL modems xDSL line qualification H04M3/306

Abstract

A data collector combiner, a network management system, a DSL Optimizer (DSLO), or any combination thereof collects data, parameter(s), characteristic(s), information, or any combination thereof from two or more data sources. The data collector probabilistically combines at least the first and second data to estimate at least one DSL characterizing parameter.

Claims

1. An apparatus comprising:

a data collector combiner operative to;

receive first data indicative of at least one digital subscriber line (DSL) characteristic from a first data source;

receive second data indicative of at least one DSL characteristic from a second data source; and

probabilistically combine at least the first and second data to estimate at least one DSL characterizing parameter.

2. An apparatus as in claim 1, wherein the data collector combiner comprises:

a data collector operative to collect the first and the second data; and

a data combiner operative to probabilistically combine the first and second data to estimate the at least one characterizing parameter.

3. An apparatus as in claim 2, further wherein the data collector is operative to perform at least one of the following:

check the integrity of the first and the second data; and

check the consistency of the first and the second data.

4. An apparatus as in claim 1, wherein Bayes'"'"' theorem is operative to be applied to probabilistically combine the first and second data.

5. An apparatus as in claim 2, wherein the data collector comprises:

a data acquirer operative to collect the first and the second data;

a data integrity checker operative to check the integrity of the first and the second data;

a data preprocessor operative to preprocess an output of the data integrity checker; and

a data consistency checker operative to check the consistency of an output of the data preprocessor.

6. An apparatus as in claim 1, further comprising a database operative to store the estimated at least one DSL characterizing parameter, wherein the data collector combiner further comprises a data store operative to store the first and the second data.

7. An apparatus as in claim 1, further comprising a network management system operative to receive the at least one estimated DSL characterizing parameter and in response thereto perform at least one of:

diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter.

8. An apparatus as in claim 1, wherein the data collector combiner is operative to probabilistically combine the first and second indicative data to estimate the DSL characteristic by applying Bayes'"'"' theorem to estimate the DSL characteristic given the first and the second data and at least one conditional probability.

9. An apparatus as in claim 1, wherein at least one of:

the first data and the second data is received from at least one of;

an auto-configuration server, a line tester system, an element management system, a service assurance system, a DSL access multiplexer, loop test equipment and a service delivery system.

10. An apparatus as in claim 1, wherein at least one of:

the first data and the second data is at least one of;

a time-domain reflectometry (TDR) signal, a loop attenuation, a signal attenuation, a signal-to-noise ratio, a loop insertion loss, a bridged tap presence, a bridged tap location, a bridged tap parameter, a quiet line noise, a crosstalk noise, a data rate, an error rate, a count of code violations, a count of errored seconds, a margin, a delay, a coding parameter and a loop transfer function.

11. An apparatus as in claim 1, wherein at least one of:

the estimated DSL characterizing parameter, is at least one of;

a loop length, a loop impedance, a segment length, a cable gauge, a noise parameter, a short fault location, an open fault location, a cross fault location, a loop fault location, a bridged-tap presence, a bridged-tap location, a bridged-tap parameter, a loop attenuation, a signal-to-noise ratio, a loop insertion loss, a data rate, an error rate, a margin, a delay, a coding parameter, a loop transfer function, an impulse noise parameter, a network congestion, a spectrum management parameter, and a home distribution quality.

12. A method comprising:

collecting first data indicative of at least one DSL characteristic from a first data source;

collecting second data indicative of at least one DSL characteristic from a second data source; and

probabilistically combining at least the first and second data to estimate at least one DSL characterizing parameter.

13. A method as in claim 12, wherein the first data is collected at a customer premises and the second data is collected at a service provider location.

14. A method as in claim 12, further comprising:

checking the integrity of the first and the second data; and

checking the consistency of the first and the second data.

16. A method as in claim 12, wherein probabilistically combining comprises applying Bayes'"'"' theorem to estimate the at least one estimated DSL characterizing parameter given at least the first data, the second data and a conditional probability.

17. A method as in claim 12, wherein:

the first data is an upstream attenuation;

the second data is a downstream attenuation; and

the at least one estimated DSL characterizing parameter is a presence of a bridged tap.

18. A method as in claim 12, wherein:

the first data is a bit allocation of a first system;

the second data is a bit allocation of a second system; and

the at least one estimated DSL characterizing parameter is a bit allocation of a third system.

19. A method as in claim 12, wherein:

the first data is a first channel transfer function from an element management system;

the second data is a second channel transfer function from an auto-configuration server; and

the at least one estimated DSL characterizing parameter is an estimated channel transfer function.

20. A method as in claim 12, further comprising:

collecting third data indicative of a status of the first data; and

collecting fourth data indicative of a status of the second data, wherein the first data is a first signal-to-noise ratio from an element management system, the second data is a second signal-to-noise ratio from an auto-configuration server, and the at least one estimated DSL characterizing parameter is an estimated signal-to-noise ratio.

21. A method as in claim 12, further comprising:

third data indicative of a status of the first data; and

fourth data indicative of a status of the second data, wherein the first data is a first channel transfer function from an element management system, the second data is a line test response, and the at least one estimated DSL characterizing parameter is a length of a bridged tap.

22. A method as in claim 12, further comprising:

third data indicative of a status of the first data;

fourth data indicative of a status of the second data; and

fifth data indicative of a time of data, wherein the first data is a number of code violations function from an element management system, the second data is moving picture experts group (MPEG) statistics, and the at least one estimated DSL characterizing parameter is a packet loss rate.

23. A method as in claim 12, further comprising:

developing a Bayesian network representation, wherein probabilistically combining further comprises using the Bayesian network representation for combining.

24. A method as in claim 12 wherein developing a Bayesian network representation comprises:

choosing a set of parameters of a communication system that includes at least the first data, the second data and the at least one characterizing parameter;

determining dependency relationships amongst the selected parameters; and

determining models of the dependency relationships.

25. A method as defined in claim 12, further comprising:

assigning each parameter to a node of a graph; and

drawing edges of the graph based upon the dependency relationships.

15. A method as in 12, further comprising using the at least one estimated DSL characterizing parameter to at least one of:

diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter.

26. An article of manufacture storing machine accessible instructions which, when executed, cause one or more machines to:

collect first data indicative of at least one DSL characteristic from a first data source;

collect second data indicative of at least one DSL characteristic from a second data source; and

probabilistically combine at least the first and second data to estimate at least one DSL characterizing parameter.

27. An article of manufacture as in claim 26, wherein the machine accessible instructions, when executed, cause the one or more machines to:

check the integrity of the first and the second data; and

check the consistency of the first and the second data.

28. An article of manufacture as in claim 26, wherein the machine accessible instructions, when executed, cause the one or more machines to use the at least one estimated DSL characterizing parameter to at least one of:

diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter.

29. An article of manufacture as in claim 26, wherein probabilistically combining comprises applying Bayes'"'"' theorem to statistically estimate the at least one DSL characterizing parameter given at least the first data, the second data and a conditional probability.

30. An apparatus comprising:

a data collector combiner operative to;

receive first data indicative of at least one digital subscriber line (DSL) characteristic from a first data source;

receive second data indicative of at least one DSL characteristic from a second data source; and

probabilistically combine at least the first and second data to estimate at least one DSL characterizing parameter in response to a data integrity check (New) of the first data and the second data.

31. An apparatus as defined in claim 30, further comprising a network management system operative to receive the at least one estimated DSL characterizing parameter and in response thereto perform at least one of:

diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter.

32. An apparatus as defined in claim 30, wherein the data collector combiner probabilistically combines the first and second data to estimate the at least one DSL characterizing parameter by applying Bayes'"'"' theorem to estimate the characteristic given at least the first data, the second data and a conditional probability.