A general framework for the design and analysis of sparse FIR linear equalizers

Abubakr O. Al-Abbasi, Ridha Hamila, Waheed Uz Zaman Bajwa, Naofal Al-Dhahir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Complexity of linear finite-impulse-response (FIR) equalizers is proportional to the square of the number of nonzero taps in the filter. This makes equalization of channels with long impulse responses using either zero-forcing or minimum mean square error (MMSE) filters computationally expensive. Sparse equalization is a widely-used technique to solve this problem. In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries. In addition, some possible choices of sparsifying dictionaries in this framework are discussed. Furthermore, the worst-case coherence of some of these dictionaries, which determines their sparsifying strength, are analytically and/or numerically evaluated. Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.

Original languageEnglish (US)
Title of host publication2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages834-838
Number of pages5
ISBN (Electronic)9781479975914
DOIs
StatePublished - Feb 23 2016
EventIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States
Duration: Dec 13 2015Dec 16 2015

Publication series

Name2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Other

OtherIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
CountryUnited States
CityOrlando
Period12/13/1512/16/15

Fingerprint

Equalizers
Glossaries
Impulse response
Mean square error
Experiments

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Signal Processing

Cite this

Al-Abbasi, A. O., Hamila, R., Bajwa, W. U. Z., & Al-Dhahir, N. (2016). A general framework for the design and analysis of sparse FIR linear equalizers. In 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 (pp. 834-838). [7418314] (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2015.7418314
Al-Abbasi, Abubakr O. ; Hamila, Ridha ; Bajwa, Waheed Uz Zaman ; Al-Dhahir, Naofal. / A general framework for the design and analysis of sparse FIR linear equalizers. 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 834-838 (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015).
@inproceedings{88b07cab240043d5aff77d8b515b6fbb,
title = "A general framework for the design and analysis of sparse FIR linear equalizers",
abstract = "Complexity of linear finite-impulse-response (FIR) equalizers is proportional to the square of the number of nonzero taps in the filter. This makes equalization of channels with long impulse responses using either zero-forcing or minimum mean square error (MMSE) filters computationally expensive. Sparse equalization is a widely-used technique to solve this problem. In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries. In addition, some possible choices of sparsifying dictionaries in this framework are discussed. Furthermore, the worst-case coherence of some of these dictionaries, which determines their sparsifying strength, are analytically and/or numerically evaluated. Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.",
author = "Al-Abbasi, {Abubakr O.} and Ridha Hamila and Bajwa, {Waheed Uz Zaman} and Naofal Al-Dhahir",
year = "2016",
month = "2",
day = "23",
doi = "10.1109/GlobalSIP.2015.7418314",
language = "English (US)",
series = "2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "834--838",
booktitle = "2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015",
address = "United States",

}

Al-Abbasi, AO, Hamila, R, Bajwa, WUZ & Al-Dhahir, N 2016, A general framework for the design and analysis of sparse FIR linear equalizers. in 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015., 7418314, 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015, Institute of Electrical and Electronics Engineers Inc., pp. 834-838, IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015, Orlando, United States, 12/13/15. https://doi.org/10.1109/GlobalSIP.2015.7418314

A general framework for the design and analysis of sparse FIR linear equalizers. / Al-Abbasi, Abubakr O.; Hamila, Ridha; Bajwa, Waheed Uz Zaman; Al-Dhahir, Naofal.

2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 834-838 7418314 (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A general framework for the design and analysis of sparse FIR linear equalizers

AU - Al-Abbasi, Abubakr O.

AU - Hamila, Ridha

AU - Bajwa, Waheed Uz Zaman

AU - Al-Dhahir, Naofal

PY - 2016/2/23

Y1 - 2016/2/23

N2 - Complexity of linear finite-impulse-response (FIR) equalizers is proportional to the square of the number of nonzero taps in the filter. This makes equalization of channels with long impulse responses using either zero-forcing or minimum mean square error (MMSE) filters computationally expensive. Sparse equalization is a widely-used technique to solve this problem. In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries. In addition, some possible choices of sparsifying dictionaries in this framework are discussed. Furthermore, the worst-case coherence of some of these dictionaries, which determines their sparsifying strength, are analytically and/or numerically evaluated. Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.

AB - Complexity of linear finite-impulse-response (FIR) equalizers is proportional to the square of the number of nonzero taps in the filter. This makes equalization of channels with long impulse responses using either zero-forcing or minimum mean square error (MMSE) filters computationally expensive. Sparse equalization is a widely-used technique to solve this problem. In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries. In addition, some possible choices of sparsifying dictionaries in this framework are discussed. Furthermore, the worst-case coherence of some of these dictionaries, which determines their sparsifying strength, are analytically and/or numerically evaluated. Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.

UR - http://www.scopus.com/inward/record.url?scp=84964778069&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964778069&partnerID=8YFLogxK

U2 - 10.1109/GlobalSIP.2015.7418314

DO - 10.1109/GlobalSIP.2015.7418314

M3 - Conference contribution

AN - SCOPUS:84964778069

T3 - 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

SP - 834

EP - 838

BT - 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Al-Abbasi AO, Hamila R, Bajwa WUZ, Al-Dhahir N. A general framework for the design and analysis of sparse FIR linear equalizers. In 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 834-838. 7418314. (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015). https://doi.org/10.1109/GlobalSIP.2015.7418314