Deep-LMS for gigabit transmission over unshielded twisted pair cables

In this paper we propose a rapidly converging LMS algorithm for crosstalk cancellation. The architecture is similar to deep neural networks, where multiple layers are adapted sequentially. The application motivating this approach is gigabit rate transmission over unshielded twisted pairs using a vectored system. The crosstalk cancellation algorithm uses an adaptive non-diagonal preprocessing matrix prior to a conventional LMS crosstalk canceler. The update of the preprocessing matrix is inspired by deep neural networks. However, since most the operations in the Deep-LMS algorithm are linear, we are capable of providing an exact convergence speed analysis. The role of the preprocessing matrix is to speed up the convergence of the conventional LMS crosstalk canceler and hence the convergence of the overall system. The Deep-LMS is important for crosstalk cancellation in the novel G.fast standard, where traditional LMS converges very slowly due to the ill-conditioned covariance matrix of the received signal at the extended bandwidth. Simulation results support our analysis and show significant reduction in convergence time compared to existing LMS variants

Signal Processing for Gigabit-Rate Wireline Communications

Signal processing played an important role in improving the quality of communications over copper cables in earlier DSL technologies. Even more powerful signal processing techniques are required to enable a gigabit per second data rate in the upcoming G.fast standard. This new standard is different from its predecessors in many respects. In particular, G.fast will use a significantly higher bandwidth. At such a high bandwidth, crosstalk between different lines in a binder will reach unprecedented levels, which are beyond the capabilities of most efficient techniques for interference mitigation. In this article, we survey the state of the art and research challenges in the design of signal processing algorithms for the G.fast system, with a focus on novel research approaches and design considerations for efficient interference mitigation in G.fast systems. We also detail relevant VDSL techniques and points out their strengths and limitations for the G.fast system.Comment: 20 pages, Accepted for publication in the IEEE Signal Processing Magazine, May 201