Iterative Sparse Channel Estimator Based on SpaRSA Approach

Xiaolin Shi; Honglei Wang; Shu-Hung Leung

doi:10.1109/ICCSNT.2017.8343718

Iterative Sparse Channel Estimator Based on SpaRSA Approach

Xiaolin Shi, Honglei Wang, Shu-Hung Leung

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l₂-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.

Original language	English
Title of host publication	Proceedings of 2017 6^th International Conference on Computer Science and Network Technology - ICCSNT 2017
Publisher	IEEE
Pages	356-360
ISBN (Electronic)	9781538604939
ISBN (Print)	9781538604922
DOIs	https://doi.org/10.1109/ICCSNT.2017.8343718
Publication status	Published - Oct 2017
Event	6th International Conference on Computer Science and Network Technology (ICCSNT 2017) - Dalian, China Duration: 21 Oct 2017 → 22 Oct 2017

Conference

Conference	6th International Conference on Computer Science and Network Technology (ICCSNT 2017)
Place	China
City	Dalian
Period	21/10/17 → 22/10/17

Research Keywords

OFDM
sparse channel estimator
sparse reconstruction by separable approximation

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10.1109/ICCSNT.2017.8343718

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@inproceedings{94186309b5864c5683f20df20a91647f,

title = "Iterative Sparse Channel Estimator Based on SpaRSA Approach",

abstract = "In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l2-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.",

keywords = "OFDM, sparse channel estimator, sparse reconstruction by separable approximation",

author = "Xiaolin Shi and Honglei Wang and Shu-Hung Leung",

year = "2017",

month = oct,

doi = "10.1109/ICCSNT.2017.8343718",

language = "English",

isbn = "9781538604922",

pages = "356--360",

booktitle = "Proceedings of 2017 6th International Conference on Computer Science and Network Technology - ICCSNT 2017",

publisher = "IEEE",

address = "United States",

note = "6th International Conference on Computer Science and Network Technology (ICCSNT 2017) ; Conference date: 21-10-2017 Through 22-10-2017",

}

Shi, X, Wang, H & Leung, S-H 2017, Iterative Sparse Channel Estimator Based on SpaRSA Approach. in Proceedings of 2017 6^th International Conference on Computer Science and Network Technology - ICCSNT 2017. IEEE, pp. 356-360, 6th International Conference on Computer Science and Network Technology (ICCSNT 2017), Dalian, China, 21/10/17. https://doi.org/10.1109/ICCSNT.2017.8343718

Iterative Sparse Channel Estimator Based on SpaRSA Approach. / Shi, Xiaolin; Wang, Honglei; Leung, Shu-Hung.
Proceedings of 2017 6^th International Conference on Computer Science and Network Technology - ICCSNT 2017. IEEE, 2017. p. 356-360.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Iterative Sparse Channel Estimator Based on SpaRSA Approach

AU - Shi, Xiaolin

AU - Wang, Honglei

AU - Leung, Shu-Hung

PY - 2017/10

Y1 - 2017/10

N2 - In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l2-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.

AB - In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l2-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.

KW - OFDM

KW - sparse channel estimator

KW - sparse reconstruction by separable approximation

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U2 - 10.1109/ICCSNT.2017.8343718

DO - 10.1109/ICCSNT.2017.8343718

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781538604922

SP - 356

EP - 360

BT - Proceedings of 2017 6th International Conference on Computer Science and Network Technology - ICCSNT 2017

PB - IEEE

T2 - 6th International Conference on Computer Science and Network Technology (ICCSNT 2017)

Y2 - 21 October 2017 through 22 October 2017

ER -

Iterative Sparse Channel Estimator Based on SpaRSA Approach

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