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A blind detection-guided approach for normalised multi-modulus crosstalk estimator in sparse multi-user DSL channels

机译:稀疏多用户DSL信道中归一化多模串扰估计器的盲检测指导方法

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In high-speed digital subscriber lines (DSL), far-end crosstalk is the main limiting factor on data rates. However, most of the crosstalk is due to the neighbouring twisted pairs in the binder. Therefore, the crosstalk channel matrix is sparse. Using Level 3 of Dynamic Spectrum Management, users are co-ordinated at the central office to cancel the crosstalk. Means for estimating the crosstalk canceller matrix are of critical importance for the cancellation to prove effective. Preferably, the estimation procedure should have low overhead both in computation and bandwidth. Normalised least mean squares (NLMS) based adaptive crosstalk cancellers (Gujrathi et al. (2009) [1]) have a low computational overhead but use a training sequence to ensure they converge adequately. However, using a training sequence consumes some amount of bandwidth which can be avoided if an unsupervised or blind algorithm like a normalised multi-modulus algorithm (NMMA) is used instead. A limitation of NMMA is that its convergence time is often longer than that of the NLMS algorithm. Furthermore, this is made worse as the number of canceller coefficients is made larger. In application to adaptive crosstalk cancellation within the multi-user DSL binder-channel, we argue that the convergence time can be significantly decreased by using an activity detector to exclude canceller coefficients below an appropriate minimum. In this paper, we present an activity detector design using a thresholding criterion based on the least squares technique, Akaike's information criterion (Homer et al. (1998) [2]) and Donoho's universal thresholding principle (Donoho (1995) [3]). This enables us to identify the significant crosstalkers within a DSL binder for each user. We further incorporate this strategy within the blind estimation NMMA and propose an enhanced crosstalk canceller. Our simulations indicate this multi-modulus detection-guided crosstalk canceller demonstrates improved convergence speed and has a steady state error close to that of the standard (non-detection-guided) canceller.
机译:在高速数字用户线(DSL)中,远端串扰是数据速率的主要限制因素。但是,大多数串扰是由于粘合剂中相邻的双绞线引起的。因此,串扰信道矩阵是稀疏的。使用动态频谱管理的3级,可以在中心局协调用户以消除串扰。估计串扰抵消器矩阵的方法对于抵消证明有效至关重要。优选地,估计过程应该在计算和带宽上都具有低开销。基于归一化最小均方(NLMS)的自适应串扰消除器(Gujrathi et al。(2009)[1])具有较低的计算开销,但使用训练序列来确保它们充分收敛。但是,使用训练序列会消耗一定数量的带宽,如果改为使用无监督或盲算法(如归一化多模算法(NMMA))则可以避免。 NMMA的局限性在于它的收敛时间通常比NLMS算法的收敛时间长。此外,随着抵消系数的数量变大,这变得更糟。在应用于多用户DSL绑定信道内的自适应串扰消除中,我们认为可以通过使用活动检测器排除低于适当最小值的抵消器系数来显着缩短收敛时间。在本文中,我们提出一种基于最小二乘技术的阈值准则,Akaike的信息准则(Homer等人(1998)[2])和Donoho的通用阈值准则(Donoho(1995)[3])来设计活动检测器。 。这使我们能够为每个用户识别DSL绑定器中的重要串扰者。我们将这种策略进一步纳入了盲估计NMMA中,并提出了一种增强的串扰消除器。我们的仿真表明,该多模检测引导串扰消除器显示出提高的收敛速度,并且稳态误差接近于标准(非检测引导)消除器。

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