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Data-Driven Wireless Networks: A Compressive Spectrum Approach
Paperback
Series: Springerbriefs in Electrical and Computer Engineering
ISBN13: 9783030002893
Publisher: Springer Nature
Published: Nov 7 2018
Pages: 93
Weight: 0.38
Height: 0.24 Width: 6.14 Depth: 9.21
Language: English
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.
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