Line Topology Identification Using Multiobjective Evolutionary Computation

The broadband capacity of the twisted-pair lines strongly varies within the copper access network. It is therefore important to assess the ability of a digital subscriber line (DSL) to support the DSL services prior to deployment. This task is handled by the line qualification procedures, where the identification of the line topology is an important part. This paper presents a new method, denoted topology identification via model-based evolutionary computation (TIMEC), for line topology identification, where either one-port measurements or both one-and two-port measurements are utilized. The measurements are input to a model-based multiobjective criterion that is minimized by a genetic algorithm to provide an estimate of the line topology. The inherent flexibility of TIMEC enables the incorporation of a priori information, e. g., the total line length. The performance of TIMEC is evaluated by computer simulations with varying degrees of information. Comparison with a state-of-art method indicates that TIMEC achieves better results for all the tested lines when only one-port measurements are used. The results are improved when employing both one-and two-port measurements. If a rough estimate of the total length is also used, near-perfect estimation is obtained for all the tested lines.