Autonomous Spectrum Balancing Using Multiple Reference Lines for Digital Subscriber Lines

Leung, Christopher; Huberman, Sean; Le‐Ngoc, Tho

doi:10.1109/glocom.2010.5683960

Cited by 12 publications

(18 citation statements)

References 6 publications

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“…However, both update formulas are derived in a fundamentally different way, where IASB1 gives some important additional insights. More specifically, it shows that (11) is the solution of a convex problem satisfying conditions (3)(4)(5), which proves that this per-user iterative update is nondecreasing and converges to a (univariate) local optimum, properties which were not known previously for DSB.…”

Section: A Design Approachmentioning

confidence: 97%

“…The CA-DSB and SCALE algorithms are two effective ICA procedures that, respectively, use the convex approximations f k ,s k ) are constants that depend on the approximation points k , and which are computed in closed-form such that conditions (3)(4)(5) are satisfied, see [2], [5].…”

Section: Algorithmmentioning

confidence: 99%

“…and (ii) the computational cost of solving the corresponding approximation. Such ICA algorithms (for distributed or centralized computation) are typically implemented in a per-user iterative approach, as this is demonstrated to be highly efficient [3], [2], [9], [4], [5], [6]. For instance, it is shown that these iterative implementations can solve small-to medium-scale DSL scenarios, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…The DSM spectrum optimization problem corresponds to a challenging nonconvex problem, for which many DSM algorithms have been proposed in the literature, ranging from fully autonomous [1], [2], [3], and distributed [2], [4], [5], [6], to centralized algorithms [7], [8]. In particular, the approach of iterative convex approximation (ICA) has been recognized to be very efficient, such as the CA-DSB [2] and SCALE [5] algorithms.…”

Section: Introductionmentioning

confidence: 99%

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A novel class of iterative approximation methods for DSL spectrum optimization

Tsiaflakis

Glineur

2012

2012 IEEE International Conference on Communications (ICC)

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Abstract-Spectrum optimization is a promising means to tackle the crosstalk problem in DSL systems, and corresponds to a challenging nonconvex optimization problem. Iterative convex approximation (ICA) methods have been proposed in the literature to deal with this optimization problem. These methods consist in solving a series of improving convex approximations and are typically implemented in a per-user iterative approach. In this paper we develop a novel class of iterative methods that focus explicitly on per-user iterative implementations, and which consist of improved per-user approximations that are tighter and simpler to solve (in closed-form) than state-of-theart ICA methods. As a result, the proposed methods improve the convergence speed as fewer approximations are required to converge, and display a significantly lower computational cost. Furthermore, three of the proposed methods can tackle the issue of getting stuck in bad locally optimal solutions, and hence improve solution quality with respect to existing ICA methods.

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Section: A Design Approachmentioning

confidence: 97%

Section: Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel class of iterative approximation methods for DSL spectrum optimization

Tsiaflakis

Glineur

2012

2012 IEEE International Conference on Communications (ICC)

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“…The optimal scheme of this section is only applicable to problems with a few users. However, simplifications as the introduction of "virtual disturber lines" [5,20] reduce the number of lines which are jointly optimized and therefore make such an optimal scheme also relevant for the performance evaluation in large networks. Similarly, in Sect.…”

Section: Discussionmentioning

confidence: 99%

Enabling greener DSL access networks by their stabilization with artificial noise and SNR margin

2012

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Low-power modes (LPM) are a standardized means in asymmetric digital subscriber lines (ADSL) 2 for reducing the power consumption at the central office. However, the activation of LPMs is hampered by the operators' concern for instability introduced by frequent transmit power changes. The injection of artificial noise (AN) has been proposed as a standard-compliant stabilization technique. We develop an analytical solution for setting the AN power spectrum. Based on this solution we jointly optimize the AN power spectrum and the signal-to-noise ratio (SNR) margin. Simulation results show the performance gain in terms of rate and energy compared to heuristic rules for setting the AN power spectrum. We propose and demonstrate three approaches for evaluating the performance of AN-enabled DSL systems, including (a) joint spectrum balancing, AN, and margin optimization, (b) single-user worstcase-stable optimization, and (c) worst-case-stable optimization based on sequential initialization. Simulation results confirm a strong dependency of the performance under AN on the selected SNR margins, and highlight the total AN power consumption as well as the residual energy savings under low-power modes stabilized by AN.

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Reducing Near–Far Problem in a VDSL Network with Modified IWF Algorithm by Using Fixed Spectral Mask Yielding Improved Data Rate of Near End User

Sharma

Sahu

2019

Wireless Pers Commun

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Autonomous Spectrum Balancing Using Multiple Reference Lines for Digital Subscriber Lines

Cited by 12 publications

References 6 publications

A novel class of iterative approximation methods for DSL spectrum optimization

A novel class of iterative approximation methods for DSL spectrum optimization

Enabling greener DSL access networks by their stabilization with artificial noise and SNR margin

Reducing Near–Far Problem in a VDSL Network with Modified IWF Algorithm by Using Fixed Spectral Mask Yielding Improved Data Rate of Near End User

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