Signal processing for single-ended loop make-up identification

Abstract

Broadband digital subscriber line (DSL) access for small business and residential customers is one of the most important new services currently being offered by network and service providers. To date, DSL service providers are still in need of an advanced loop qualification system that can minimize qualification errors. Loop qualification consists of determining whether a loop can support DSL services or not and, generally, the estimate of the loop transfer function is sufficient for such purposes. We propose here to solve a more ambitious problem: single ended automatic loop make-up identification (LMID), i.e. the determination of the length and the gauge of all loop sections (including bridged taps) via single-ended testing without human intervention. It is proposed here to use time domain reflectometry (TDR) measurements, which are analyzed by a novel step-by-step ML algorithm, to achieve accurate LMID. This problem is equivalent to resolving via a single sensor experiment an unknown number of closely spaced echoes, some overlapping some not, which exhibit unknown amplitudes, unknown times of arrival and unknown shapes.