Single-ended loop make-up identification-part I: a method of analyzing TDR measurements

Loop qualification consists of determining whether a loop can support digital subscriber line (DSL) services or not, and generally, the estimate of the transfer function is sufficient for such purposes. Loop qualification is one of the most important steps that service providers need to address in d...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2006-04, Vol.55 (2), p.528-537
Main Authors: Galli, S., Kerpez, K.J.
Format: Article
Language:English
Subjects:
Algorithms
Copper
Crosstalk
Digital
Digital subscriber line
Digital subscriber line (DSL)
DSL
Human
Instrumentation
loop qualification
Maintenance
maximum likelihood (ML)
Maximum likelihood estimation
Operators
Provisioning
Qualifications
Reflectometry
Reliability engineering
Studies
Subscriber line
Subscriber loops
Time domain analysis
time-domain reflectometry (TDR)
Transfer functions
twisted-pair modeling
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Summary:Loop qualification consists of determining whether a loop can support digital subscriber line (DSL) services or not, and generally, the estimate of the transfer function is sufficient for such purposes. Loop qualification is one of the most important steps that service providers need to address in deploying DSL technology. In this paper, a solution to a more ambitious problem-single-ended automatic loop make-up identification, i.e., the determination of the length and the gauge of all loop sections (including bridged taps) via single-ended testing without human intervention-is proposed. Loop make-up identification will allow operators to more accurately qualify a loop for DSL service and to update and reorder telephone-company loop records, which can be accessed to support engineering, provisioning, and maintenance operations. Despite its potential importance, the possibility of achieving loop make-up identification via single-ended measurements has seldom been addressed in the literature. The use of time-domain reflectometry (TDR) measurements, which are analyzed by a novel step-by-step maximum-likelihood (ML) algorithm, is proposed here to achieve accurate loop make-up identification. In this paper, the proposed algorithm needs no a priori information, whereas in Part II of this study, a means to reduce the computation time of the identification algorithm will be provided, and the case where a statistical characterization of the loop may be available prior to testing will also be considered.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2006.870134