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Data-Driven Wireless Networks

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-3-030-00290-9

ISBN: 978-3-030-00289-3

Publisher: Springer International Publishing - Springer Journals

Oct 20, 2018

Available

Introduction

Gao, Yue; Qin, Zhijin

Pages: 3 –8

[Radio frequency (RF) spectrum is a valuable but tightly regulated resource due to its unique and important role in wireless communications. The demand for RF spectrum is increasing due to a rapidly expanding market of multimedia wireless services, while the usable spectrum is becoming scarce due...
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Sparse Representation in Wireless Networks

Gao, Yue; Qin, Zhijin

Pages: 9 –20

[This chapter provides an overview of the background knowledge of sparse representation with particular focus on compressive sensing, including basic principles of CS, reweighted CS, and distributed CS. Moreover, this chapter also introduces the basic framework of compressive spectrum sensing,...
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Data-Driven Compressive Spectrum Sensing

Gao, Yue; Qin, Zhijin

Pages: 23 –41

[In this chapter, the related work and the main contributions are firstly introduced in Sect. 3.1. In Sect. 3.2, the proposed data-driven compressive spectrum sensing framework is presented, in which geolocation database is used to provide prior information for signal recovery. Additionally,...
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Robust Compressive Spectrum Sensing

Gao, Yue; Qin, Zhijin

Pages: 43 –64

[In this chapter, the existing work on compressive spectrum sensing in CRNs and the main contributions are firstly reviewed in Sect. 4.1. In Sect. 4.2, the proposed robust compressive spectrum sensing working at a single CR user is presented. Section 4.3 gives the related simulation results....
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Secure Compressive Spectrum Sensing

Gao, Yue; Qin, Zhijin

Pages: 65 –88

[In this chapter, a malicious user detection model is proposed to improve the security of CSS networks. The low-rank MC technique is invoked in the proposed model. More specifically, Sect. 5.1 introduces the related work and main contributions of the work in this chapter. Section 5.2 describes...
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Conclusions and Future Work

Gao, Yue; Qin, Zhijin

Pages: 91 –93

[This book presented research work on the promising applications of compressive sensing (CS) technique in wideband spectrum sensing, which is regarded as one of the most challenging tasks in cognitive radio networks (CRNs). It has been demonstrated that CS is capable of enabling sub-Nyquist...

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