DSL system estimation and control

• US 20060268733A1
• Filed: 01/28/2006
• Published: 11/30/2006
• Est. Priority Date: 05/09/2005
• Status: Active Grant

• Current Assignee: Assia Spe LLC
• Original Assignee: Adaptive Spectrum and Signal Alignment, Incorporated
• Inventors: Ginis, Georgios, Cioffi, John M., Rhee, Wonjong, Lee, Bin, Almandoz, Iker, Sylke, C. Thomas
• Granted Patent: US 7,684,546 B2
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: H04L 41/0213 Standardised network management protocols, e.g. simple network management protocol [SNMP]
• CPC Class Codes: H04L 41/082 the condition being updates or upgrades of network functionality
• CPC Class Codes: H04L 41/0853 by actively collecting configuration information or by backing up configuration information
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 43/50 Testing arrangements
• CPC Class Codes: H04M 11/062 using different frequency bands for speech and other data

Abstract

Methods, apparatus, computer program products and other embodiments model a system'"'"'s channel and noise characteristics using one or more Hidden Markov Models (HMMs) by modeling the state dynamics for one or more lines and associated profiles and by learning from the line history. Besides channel and noise characteristics, user data activity also can be modeled using an HMM, where all channel, noise and user data activity can be modeled jointly using HMMs as long as the joint states are properly defined. In multi-line systems, multiple lines (for example, a set of lines in a DSL system binder) may be modeled jointly. After learning channel, noise, user data activity and/or other dynamics using HMM techniques and methods, system operation and/or configuration parameters can be controlled based on the estimated HMM, providing flexible solutions for virtually any channel, noise, user data activity and/or other dynamics.

Claims

1. A method of controlling a DSL system, the method comprising:

constructing an HMM to model one or more internal states of a DSL system;

collecting update operational data pertaining to the DSL system;

analyzing the collected update operational data; and

controlling operation of the DSL system based on the constructed HMM and analyzed update operational data.

2. The method of claim 1 wherein constructing an HMM to model the internal states of a DSL system comprises modeling at least one of the following:

channel characteristics;

crosstalk characteristics;

impulse noise characteristics;

non-impulse noise characteristics;

or

user data activity.

3. The method of claim 1 wherein constructing an HMM to model the internal states of a DSL system comprises:

collecting training operational data pertaining to the DSL system;

analyzing the collected training operational data pertaining to the DSL system to construct the HMM.

4. The method of claim 3 wherein analyzing the collected training operational data pertaining to the DSL system to construct the HMM comprises using the Baum-Welch algorithm.

5. The method of claim 3 wherein at least one of the collected training operational data or the collected update operational data is checked for compliance with at least one of the following:

a data timeliness rule;

or

a data sufficiency rule.

6. The method of claim 1 further comprising updating the HMM based on the collected update operational data.

7. The method of claim 1 wherein controlling operation of the DSL system based on the constructed HMM and analyzed update operational data comprises at least one of the following:

determining the internal state of the DSL system;

or

controlling at least one of the following parameters;

data rate;

target SNR margin (TSNRM);

maximum SNR margin (MAXSNRM);

minimum SNR margin (MINSNRM);

FEC parameters;

an FEC delay parameter;

an FEC INP parameter;

transmit power;

a carrier mask parameter;

a power spectral density parameter;

a bit loading parameter;

bit allocation;

PSDMASK;

CARMASK;

or

BCAP.

8. The method of claim 1 wherein controlling operation of the DSL system based on the constructed HMM and analyzed update operational data comprises forcing a retrain of the DSL system.

9. The method of claim 8 wherein forcing a retrain of the DSL system is scheduled to occur when at least one of the following conditions is satisfied:

at a predetermined time;

when user data activity is detected to be below a certain threshold.

10. The method of claim 1 wherein constructing an HMM to model the internal states of a DSL system comprises choosing one HMM from a plurality of candidate HMMs.

11. A computer program product comprising:

a machine readable medium; and

program instructions contained in the machine readable medium, the program instructions specifying a method of controlling operation of a DSL system, the method comprising;

constructing an HMM to model the internal states of a DSL system;

collecting update operational data pertaining to the DSL system;

analyzing the collected update operational data; and

controlling operation of the DSL system based on the constructed HMM and analyzed operational data.

12. A device for controlling operation of a DSL system, the device comprising:

means for collecting operational data from the DSL system;

means coupled to the collecting means for analyzing the collected operational data;

means for controlling operation of the DSL system based on;

the collected operational data;

and an HMM modeling the internal states of the DSL system.

13. The device of claim 12 wherein the HMM modeling the internal states of the DSL system pertains to modeling at least one of the following:

channel characteristics;

crosstalk characteristics;

impulse noise characteristics;

non-impulse noise characteristics;

or

user data activity.

14. The device of claim 12 wherein the device is configured to construct and update

the HMM by:

using the collecting means to collect operational data pertaining to the DSL system; and

using the analyzing means to analyze the collected operational data.

15. The device of claim 12 wherein the device updates the HMM as necessary based on the collected operational data.

16. The device of claim 12 wherein the collecting means is configured to check for compliance with at least one of the following:

a data timeliness rule;

or

a data sufficiency rule.

17. The device of claim 12 further wherein means for controlling operation of the DSL system controls at least one of the following parameters:

data rate;

target SNR margin (TSNRM);

maximum SNR margin (MAXSNRM);

minimum SNR margin (MINSNRM);

FEC parameters;

an FEC delay parameter;

an FEC INP parameter;

transmit power;

a carrier mask parameter;

a power spectral density parameter;

a bit loading parameter;

bit allocation;

PSDMASK;

CARMASK;

or

BCAP.

18. The device of claim 12 further wherein means for controlling operation of the DSL system forces a retrain of the DSL system.

19. The device of claim 18 wherein forcing a retrain of the DSL system is scheduled to occur when at least one of the following conditions is satisfied:

at a predetermined time;

when user data activity is detected to be below a certain threshold.

20. The device of claim 18 wherein the HMM modeling the internal states of the DSL system is chosen from a plurality of candidate HMMs.

21-68. -68. (canceled)