Co-operative Alien Noise Cancellation in Upstream VDSL: A New Decision Directed Approach

Abstract

Alien noise in the vectored very-high-speed digital subscriber line (VDSL) system is part of the additive noise at the receiver and exhibits strong correlation among users. We present a per-tone co-operative alien noise cancellation (CoMAC) algorithm for the upstream (US) VDSL that can be applied subsequent to any self far-end-crosstalk (FEXT) mitigation strategy. CoMAC operates by predicting the noise seen by a given user based on the error samples from the remaining users. These errors are conveniently obtained after slicing the self-FEXT canceled signal of all the vectored users. We show that if the estimation of these errors is accurate, the proposed alien canceler achieves the Cramer-Rao lower bound (CRLB). In practice, the seamless rate adaptation (SRA) operation, which enables increased bit rate by increasing the bit-loading per-tone, can cause decision errors in any decision directed strategy. We also analyze the impact of these decision errors - an issue not addressed in the literature. We propose a strategy for bit-loading during the SRA operation by formulating a max-min optimization problem and demonstrate a possibility of a guaranteed (minimum) improvement in the per-user rate. Simulations indicate that performance of the algorithm can exceed the minimum value significantly in practical situations.