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Article: Sparse Representation for Wireless Communications: A Compressive Sensing Approach

TitleSparse Representation for Wireless Communications: A Compressive Sensing Approach
Authors
Qin, ZhijinFan, JiancunLiu, YuanweiGao, YueLi, Geoffrey Ye
Issue Date2018
Citation
IEEE Signal Processing Magazine, 2018, v. 35, n. 3, p. 40-58 How to Cite?
DOI: http://dx.doi.org/10.1109/MSP.2018.2789521
AbstractSparse 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.
Persistent Identifierhttp://hdl.handle.net/10722/349241
ISSN
1053-5888
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 4.896

 

DC FieldValueLanguage
dc.contributor.authorQin, Zhijin-
dc.contributor.authorFan, Jiancun-
dc.contributor.authorLiu, Yuanwei-
dc.contributor.authorGao, Yue-
dc.contributor.authorLi, Geoffrey Ye-
dc.date.accessioned2024-10-17T06:57:13Z-
dc.date.available2024-10-17T06:57:13Z-
dc.date.issued2018-
dc.identifier.citationIEEE Signal Processing Magazine, 2018, v. 35, n. 3, p. 40-58-
dc.identifier.issn1053-5888-
dc.identifier.urihttp://hdl.handle.net/10722/349241-
dc.description.abstractSparse 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.-
dc.languageeng-
dc.relation.ispartofIEEE Signal Processing Magazine-
dc.titleSparse Representation for Wireless Communications: A Compressive Sensing Approach-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/MSP.2018.2789521-
dc.identifier.scopuseid_2-s2.0-85044521828-
dc.identifier.volume35-
dc.identifier.issue3-
dc.identifier.spage40-
dc.identifier.epage58-

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