The adoption of precoding (vectoring) in VDSL2 at the central office has resulted in mitigation of the far-end crosstalk seen at the customer premises equipment (CPE). As a result, alien noise (including repetitive impulse noise) is the new dominant source of impairment for downstream VDSL. At the CPE, an additional common mode (CM) sensor can sense the electromagnetically coupled alien noise signal, which can then be used to cancel the alien noise coupling into the differential mode signal. The intermittent and repetitive nature of the noise sources necessitates that the CM sensor based noise cancellation algorithm be capable of training and adapting during data mode in the presence of the useful data signal, since the presence of alien noise cannot be guaranteed during the modem training phase. In this paper, we propose a novel two-stage frequency domain algorithm based on a per-tone cancellation model for this purpose. The proposed algorithm outperforms previously proposed time domain algorithms in terms of convergence speed in many practical scenarios due to the decision directed nature of the proposed algorithm. We also analyse the theoretical convergence of the algorithm, which is also validated by the simulation experiments.

For VDSL systems, alien noise cancellation using an additional common mode sensor at the customer premises equipment (CPE) receiver can be done by combining the differential-mode (DM) signal with the common-mode (CM) signal passed through a long linear filter. Frequency domain per-tone cancellation offers a low complexity approach to the problem but suffers from loss in cancellation performance due to approximations in the per-tone model. We analyze this loss and show that it is possible to minimize it by a post-training “delay” adjustment. We also address the problem of training such a noise canceller during data mode in the presence of a much stronger useful data signal in DM since noise events may not occur during modem train-up. We propose an algorithm based on the per-tone approach which is capable of fast convergence during data mode for intermittent alien noise sources, analyze its convergence behaviour and demonstrate the usefulness of the pertone approach and the proposed training algorithm over existing time domain methods.