Data-driven wireless networks : a compressive spectrum approach /
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| Author / Creator: | Gao, Yue, author. |
|---|---|
| Imprint: | London : Springer, [2019] |
| Description: | 1 online resource |
| Language: | English |
| Series: | SpringerBriefs in electrical and computer engineering SpringerBriefs in electrical and computer engineering. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11746050 |
MARC
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| 245 | 1 | 0 | |a Data-driven wireless networks : |b a compressive spectrum approach / |c Yue Gao, Zhijin Qin. |
| 264 | 1 | |a London : |b Springer, |c [2019] | |
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| 505 | 0 | |a Part I : Background -- Introduction -- Sparse representation in wireless networks -- Part II : Compressive spectrum sensing algorithms -- Data-driven compressive spectrum sensing -- Robust compressive spectrum sensing -- Secure compressive spectrum sensing -- Part III : Conclusions -- Conclusions and future work. | |
| 520 | |a This SpringerBrief discusses the applications of spare representation in wireless communications, with a particular focus on the most recent developed compressive sensing (CS) enabled approaches. With the help of sparsity property, sub-Nyquist sampling can be achieved in wideband cognitive radio networks by adopting compressive sensing, which is illustrated in this brief, and it starts with a comprehensive overview of compressive sensing principles. Subsequently, the authors present a complete framework for data-driven compressive spectrum sensing in cognitive radio networks, which guarantees robustness, low-complexity, and security. Particularly, robust compressive spectrum sensing, low-complexity compressive spectrum sensing, and secure compressive sensing based malicious user detection are proposed to address the various issues in wideband cognitive radio networks. Correspondingly, the real-world signals and data collected by experiments carried out during TV white space pilot trial enables data-driven compressive spectrum sensing. The collected data are analysed and used to verify our designs and provide significant insights on the potential of applying compressive sensing to wideband spectrum sensing. | ||
| 588 | 0 | |a Print version record. | |
| 650 | 0 | |a Wireless sensor networks. |0 http://id.loc.gov/authorities/subjects/sh2008004547 | |
| 650 | 0 | |a Internet of things. |0 http://id.loc.gov/authorities/subjects/sh2013000266 | |
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| 650 | 7 | |a Wireless sensor networks. |2 fast |0 (OCoLC)fst01746575 | |
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| 700 | 1 | |a Qin, Zhijin, |e author. | |
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