Impulsive noise estimation and cancellation in DSL using compressive sampling

T. Y. Al-Naffouri; F. F. Al-Shaalan; A. A. Quadeer; H. Hmida

doi:10.1109/ISCAS.2011.5938020

Impulsive noise estimation and cancellation in DSL using compressive sampling

T. Y. Al-Naffouri^*, F. F. Al-Shaalan, A. A. Quadeer, H. Hmida

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

24 Scopus citations

Abstract

Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and results in dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling for a coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We also present a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.

Original language	English (US)
Title of host publication	2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011
Pages	2133-2136
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2011.5938020
State	Published - 2011
Externally published	Yes
Event	2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011 - Rio de Janeiro, Brazil Duration: May 15 2011 → May 18 2011

Other

Other	2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011
Country/Territory	Brazil
City	Rio de Janeiro
Period	05/15/11 → 05/18/11

Keywords

Compressive sampling
DSL
Impulsive noise
Sparse signal reconstruction

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/ISCAS.2011.5938020

Cite this

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title = "Impulsive noise estimation and cancellation in DSL using compressive sampling",

abstract = "Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and results in dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling for a coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We also present a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.",

keywords = "Compressive sampling, DSL, Impulsive noise, Sparse signal reconstruction",

author = "Al-Naffouri, {T. Y.} and Al-Shaalan, {F. F.} and Quadeer, {A. A.} and H. Hmida",

year = "2011",

doi = "10.1109/ISCAS.2011.5938020",

language = "English (US)",

isbn = "9781424494736",

pages = "2133--2136",

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note = "2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011 ; Conference date: 15-05-2011 Through 18-05-2011",

}

Al-Naffouri, TY, Al-Shaalan, FF, Quadeer, AA & Hmida, H 2011, Impulsive noise estimation and cancellation in DSL using compressive sampling. in 2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011., 5938020, pp. 2133-2136, 2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011, Rio de Janeiro, Brazil, 05/15/11. https://doi.org/10.1109/ISCAS.2011.5938020

TY - GEN

T1 - Impulsive noise estimation and cancellation in DSL using compressive sampling

AU - Al-Naffouri, T. Y.

AU - Al-Shaalan, F. F.

AU - Quadeer, A. A.

AU - Hmida, H.

PY - 2011

Y1 - 2011

N2 - Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and results in dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling for a coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We also present a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.

AB - Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and results in dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling for a coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We also present a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.

KW - Compressive sampling

KW - DSL

KW - Impulsive noise

KW - Sparse signal reconstruction

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EP - 2136

BT - 2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011

T2 - 2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011

Y2 - 15 May 2011 through 18 May 2011

ER -

Impulsive noise estimation and cancellation in DSL using compressive sampling

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Keywords

ASJC Scopus subject areas

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