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Sparse Representation for Wireless Communications: A Compressive Sensing Approach

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Sparse Representation for Wireless Communications: A Compressive Sensing Approach. / Qin, Zhijin; Fan, Jiancun; Liu, Yuanwei et al.
In: IEEE Signal Processing Magazine, Vol. 35, No. 3, 05.2018, p. 40-58.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Qin, Z, Fan, J, Liu, Y, Gao, Y & Li, GY 2018, 'Sparse Representation for Wireless Communications: A Compressive Sensing Approach', IEEE Signal Processing Magazine, vol. 35, no. 3, pp. 40-58. https://doi.org/10.1109/MSP.2018.2789521

APA

Qin, Z., Fan, J., Liu, Y., Gao, Y., & Li, G. Y. (2018). Sparse Representation for Wireless Communications: A Compressive Sensing Approach. IEEE Signal Processing Magazine, 35(3), 40-58. https://doi.org/10.1109/MSP.2018.2789521

Vancouver

Qin Z, Fan J, Liu Y, Gao Y, Li GY. Sparse Representation for Wireless Communications: A Compressive Sensing Approach. IEEE Signal Processing Magazine. 2018 May;35(3):40-58. Epub 2018 Apr 26. doi: 10.1109/MSP.2018.2789521

Author

Qin, Zhijin ; Fan, Jiancun ; Liu, Yuanwei et al. / Sparse Representation for Wireless Communications : A Compressive Sensing Approach. In: IEEE Signal Processing Magazine. 2018 ; Vol. 35, No. 3. pp. 40-58.

Bibtex

@article{496f0251b18842a58559518d50ed5377,
title = "Sparse Representation for Wireless Communications: A Compressive Sensing Approach",
abstract = "Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches. With the help of the sparsity property, CS is able to enhance the spectrum efficiency (SE) and energy efficiency (EE) of fifth-generation (5G) and Internet of Things (IoT) networks.",
keywords = "Wireless communications, compressive sensing, sparsity property, 5G, Internet of Things",
author = "Zhijin Qin and Jiancun Fan and Yuanwei Liu and Yue Gao and Li, {Geioffrey Ye}",
note = "{\textcopyright}2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.",
year = "2018",
month = may,
doi = "10.1109/MSP.2018.2789521",
language = "English",
volume = "35",
pages = "40--58",
journal = "IEEE Signal Processing Magazine",
issn = "1053-5888",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",

}

RIS

TY - JOUR

T1 - Sparse Representation for Wireless Communications

T2 - A Compressive Sensing Approach

AU - Qin, Zhijin

AU - Fan, Jiancun

AU - Liu, Yuanwei

AU - Gao, Yue

AU - Li, Geioffrey Ye

N1 - ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2018/5

Y1 - 2018/5

N2 - Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches. With the help of the sparsity property, CS is able to enhance the spectrum efficiency (SE) and energy efficiency (EE) of fifth-generation (5G) and Internet of Things (IoT) networks.

AB - Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches. With the help of the sparsity property, CS is able to enhance the spectrum efficiency (SE) and energy efficiency (EE) of fifth-generation (5G) and Internet of Things (IoT) networks.

KW - Wireless communications

KW - compressive sensing

KW - sparsity property

KW - 5G

KW - Internet of Things

U2 - 10.1109/MSP.2018.2789521

DO - 10.1109/MSP.2018.2789521

M3 - Journal article

VL - 35

SP - 40

EP - 58

JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

SN - 1053-5888

IS - 3

ER -