In order to identify if a subscriber loop is suitable for a certain digital subscriber line (DSL) service, the transfer function of the loop has to be estimated. Several measurement techniques exist, however single-ended line testing (SELT) is often preferred by the telecom operators because all necessary measurements can be done at the central office. The SELT data is typically interpreted in the time domain. This paper presents a new approach by doing the identification in the frequency domain. It starts by explaining the drawbacks of the time domain approach. The paper explains how these are avoided by using a frequency domain identification algorithm. Measurement results show this is a viable alternative to the classical time domain identification.

Qualifying a subscriber loop for xDSL transmission can be done in many ways. Amongst all ways, methods that don't require an expensive truck-roll to the customer are preferred. In this paper we provide a method for an intelligent automated interpretation of reflectometric 1-port measurements at the central office. First, we focus on how reflectograms can be characterised. Next, we build up intelligence in the system to deal with the uncertainty on the characteristics and to infer the topology by means of a belief network. Eventually, we combine in an artificial intelligent way, by means of a rule-based expert system all available knowledge and derive the basic loop properties i.e. the topology and the delays of the individual line sections.

In order to qualify a subscriber loop for xDSL transmission, the channel capacity has to be estimated, which depends on the transfer function of the network. A method is provided to estimate the transfer function of the subscriber loop only measuring the one-port scattering parameter at the central office. We consider three types of networks according to their topology: a single line, a homogeneous network with a bridged tap, and a cascade of two line sections. For each type of network a parametric model is derived of its one-port scattering parameter and transfer function based on the physical line model VUB0. The model for the scattering parameter is used to identify the network based on the corresponding measurements by means of a maximum-likelihood estimator. The estimated parameters are substituted in the transfer function model, which is needed for the capacity estimation. The proposed models and estimators are validated by measurements and simulations. For the measurements, which were performed with a network analyzer, three types of twisted-pair cables were used: British Telecom (BT), Deutsch Telekom (FT), and Belgacom.

This contribution proposes a new family of methods to reduce the peak-to-average power ratio (PAR) in discrete multi-tone (DMT) and orthogonal frequency division multiplexing (OFDM) systems. This method avoids the use of extra inverse fast Fourier transformations (IFFT) as were used in some previously published techniques, but instead is based on transformations in the time domain of the original sequence available at the output of the IFFT processor. The improved statistics of peak power in the optimized transmit signal are demonstrated by simulation results.