Sparse Representation for Wireless Communications:A Compressive Sensing Approach

Qin, Zhijin and Fan, Jiancun and Liu, Yuanwei and Gao, Yue and Li, Geioffrey Ye (2018) Sparse Representation for Wireless Communications:A Compressive Sensing Approach. IEEE Signal Processing Magazine, 35 (3). pp. 40-58. ISSN 1053-5888

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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.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Signal Processing Magazine
Additional Information:
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Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2208
Subjects:
ID Code:
89465
Deposited By:
Deposited On:
05 Jan 2018 13:40
Refereed?:
Yes
Published?:
Published
Last Modified:
28 Oct 2020 06:07