University of Oulu

Markus Leinonen, Marian Codreanu and Georgios B. Giannakis (2019), "Compressed Sensing with Applications in Wireless Networks", Foundations and Trends® in Signal Processing: Vol. 13: No. 1-2, pp 1-282.

Compressed sensing with applications in wireless networks

Saved in:
Author: Leinonen, Markus1; Codreanu, Marian2; Giannakis, Georgios3
Organizations: 1Centre for Wireless Communications, University of Oulu
2Department of Science and Technology, Linköping University
3Department of Electrical and Computer Engineering, University of Minnesota
Format: ebook
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 7.7 MB)
Persistent link:
Language: English
Published: Now Publishers, 2019
Publish Date: 2020-06-01


Sparsity is an attribute present in a myriad of natural signals and systems, occurring either inherently or after a suitable projection. Such signals with lots of zeros possess minimal degrees of freedom and are thus attractive from an implementation perspective in wireless networks. While sparsity has appeared for decades in various mathematical fields, the emergence of compressed sensing (CS) — the joint sampling and compression paradigm — in 2006 gave rise to plethora of novel communication designs that can efficiently exploit sparsity. In this monograph, we review several CS frameworks where sparsity is exploited to improve the quality of signal reconstruction/detection while reducing the use of radio and energy resources by decreasing, e.g., the sampling rate, transmission rate, and number of computations. The first part focuses on several advanced CS signal reconstruction techniques along with wireless applications. The second part deals with efficient data gathering and lossy compression techniques in wireless sensor networks. Finally, the third part addresses CS-driven designs for spectrum sensing and multi-user detection for cognitive and wireless communications.

see all

Series: Foundations and Trends® in Signal Processing
ISSN: 1932-8346
ISSN-E: 1932-8354
ISSN-L: 1932-8346
ISBN: 978-1-68083-647-9
ISBN Print: 978-1-68083-646-2
Volume: 13
Issue: 1-2
Pages: 1 - 282
DOI: 10.1561/2000000107
Type of Publication: C1 Scientific book
Field of Science: 213 Electronic, automation and communications engineering, electronics
Copyright information: © 2019 M. Leinonen, M. Codreanu and G. B. Giannakis. The final publication is available from now publishers via