Description

Book Synopsis
Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and

Table of Contents
1. Introduction; 2. Overview of wireless networks; Part I. Compressive Sensing Techniques: 3. Compressive sensing framework; 4. Sparse optimization algorithms; Part II. Compressive Sensing-Based Wireless Communication: 5. Analog to digital converter; 6. Channel estimation; 7. Ultra wide band; 8. Positioning; 9. Multiple access; 10. Cognitive radio networks and sensor networks.

Compressive Sensing for Wireless Networks

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    £82.64

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    Order before 4pm tomorrow for delivery by Tue 16 Jun 2026.

    A Hardback by Zhu Han, Husheng Li, Wotao Yin

    3 in stock


      View other formats and editions of Compressive Sensing for Wireless Networks by Zhu Han

      Publisher: Cambridge University Press
      Publication Date: 06/06/2013
      ISBN13: 9781107018839, 978-1107018839
      ISBN10:

      Description

      Book Synopsis
      Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and

      Table of Contents
      1. Introduction; 2. Overview of wireless networks; Part I. Compressive Sensing Techniques: 3. Compressive sensing framework; 4. Sparse optimization algorithms; Part II. Compressive Sensing-Based Wireless Communication: 5. Analog to digital converter; 6. Channel estimation; 7. Ultra wide band; 8. Positioning; 9. Multiple access; 10. Cognitive radio networks and sensor networks.

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