Loading in 2 Seconds...
Loading in 2 Seconds...
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.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
University of British Columbia, Vancouver, Distinguished Lecture, Feb. 27, 2006
Dr. Stefano GalliSenior Scientist, Telcordia Technologies [email protected]://www.argreenhouse.com/bios/sgalli
and inside wire
EMI radio ingress
Impulse noiseCopper Impairments
ADSL Discrete multi-tone (DMT) modem data:
- 255 tones
- Nearly as good as continuous spectra!
Traditional approach is in terms of power sums (sum of the pair-to-pair NEXT coupling powers of the other pairs in the binder group).
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:
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.
(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.
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
(Test signal: 200 ns Square Pulse, 1 V amplitude)
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. First 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.
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
Measured TDR traces obtained probing a 975 m (3,200 ft) of AWG26 followed by 975 m (3,200 ft) of AWG24.