University of British Columbia, Vancouver, Distinguished Lecture, Feb. 27, 2006. Crosstalk and Loop Make-Up Identification for DSL Systems. Dr. Stefano Galli Senior Scientist, Telcordia Technologies [email protected] http://www.argreenhouse.com/bios/sgalli. Talk Outline.
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University of British Columbia, Vancouver, Distinguished Lecture, Feb. 27, 2006
Dr. Stefano GalliSenior Scientist, Telcordia Technologies [email protected]://www.argreenhouse.com/bios/sgalli
Loop loss Lecture, Feb. 27, 2006
and inside wire
EMI radio ingress
Impulse noiseCopper Impairments
CO-based ADSL Lecture, Feb. 27, 2006
Really BAD FEXT
FrequencyDynamic Spectrum Management (DSM)
Today – equal transmit spectra
really bad Crosstalk
DSL #1 Lecture, Feb. 27, 2006
ADSL Discrete multi-tone (DMT) modem data:
- 255 tones
- Nearly as good as continuous spectra!
Crosstalk Identification Lecture, Feb. 27, 2006
Power-Sum Models !
Dark black line = 99% worst-case model
: set of N frequency samples of the measured crosstalk PSD
caused by un unknown DSL disturber
: set of N frequency samples of the k-th basis crosstalk PSD
profile, with 1 k P
Find the single disturber that generates crosstalk Y given the set of all the
crosstalk PSD profiles X, i.e. find relationship between Y and X
Classical regression problem:
The regression coefficients 300a(k) and b(k) are determined by the condition
that the sum of the squared residuals S(k) is minimum:
It is possible to show that the sum of squared residuals can be expressed
in terms of the correlation coefficient:
Minimizing sum of squared
residuals is equivalent to
finding the maximum
disturbers across all N frequencies
full rank NxP matrix containing all the PSD profiles
vector of weighting coefficients
vector containing the residuals over all the frequency points
Problem: find an optimal sparse representation of a
vector from an overcomplete set of vectors.
No SVD 300
(P = 800)
( = 8)
4) ADSL Dn
5) SDSL 400
6) SDSL 1040
7) SDSL 1552
8) HDSL2 Up
ID rate (%)
SVD allows to drastically reduce computational complexity.
22 Gauge 300
1400 ftLoop Response Estimation
Detailed loop characterization is difficult to obtain because:
1) information kept for POTS service was not detailed
2) loop records are often on paper
3) records are often wrong
It is necessary to perform measurements
Telco DSL CO
Estimate loop make-up stick diagram from single-ended CO-based TDR measurement
Echo Modeling 300
(Test signal: 200 ns Square Pulse, 1 V amplitude)
Echo Modeling 300
Echo Modeling 300
Echo Modeling 300
The reflection coefficient for the spurious echoes:
Problem: Here we have only one sensor!!!
Let’s try to turn our single sensor case into a multi-sensor one and use MUSIC, ESPRIT, or WSF.
Similar to the multi-sensor problem but now the array manifold depends on the shape of the echo
Not much literature on Loop Make-Up identification. 300First papers are recent:
The identification process is based on analyzing TDR measurements in such a way that the measurements are successively mapped to gradually augmented loop make-up topologies until the error between the measured TDR trace and the simulated TDR waveform of a set of hypothesized loop topologies becomes sufficiently small.
S. Galli, K. Kerpez, "Single-Ended Loop Make-Up Identification - Part 1 and 2," IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 2, April 2006.
1) Hypothesize all “sensible” topologies and generate corresponding waveform according to echo model
2) Choose topology whose waveform best matches measured data, and identify discontinuity
3) Augment chosen topology using auxiliary topologies (infinite length), generate corresponding waveform, and subtract it from measured data to obtain a de-embedded TDR trace
4) Identify the next discontinuity
5) Go to 2 using de-embedded trace as measured data until last echo is found
Current loop estimate
Enhancement: Multiple Estimate Path Search
19 loops representing the variety at a CO. Loops picked so that 5%, 10%, ..., 95% of all loops at the wire center were shorter. Loops include bridged tap, gauge change, etc.
Different actual 300
Static spectrum managementSimulation results
Presented at the IEEE ICC 2005 conference
Back-Up Slides 300
The probability histogram of working lengths measured in the 1983 loop survey.
The probability histogram of total bridged tap lengths, measured in the 1983 loop survey (excluding zero lengths)
Cable gauge statistics from the 1983 and the 1987-90 Bellcore loop surveys. In the 1987-90 Bellcore loop surveys, only 0.1% of cabling overall was 19 gauge, so 19 gauge is omitted from the table
Broadband Test Head prototype architecture Bellcore loop surveys. In the 1987-90 Bellcore loop surveys, only 0.1% of cabling overall was 19 gauge, so 19 gauge is omitted from the table
Schematic diagram of our differential TDR Bellcore loop surveys. In the 1987-90 Bellcore loop surveys, only 0.1% of cabling overall was 19 gauge, so 19 gauge is omitted from the table