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20 results

Robust Statistics for Signal Processing
  • Abdelhak M. Zoubir, Visa Koivunen, Esa Ollila, Michael Muma
  • Published online:
    26 October 2018
    Print publication:
    08 November 2018
  • Understand the benefits of robust statistics for signal processing with this authoritative yet accessible text. The first ever book on the subject, it provides a comprehensive overview of the field, moving from fundamental theory through to important new results and recent advances. Topics covered include advanced robust methods for complex-valued data, robust covariance estimation, penalized regression models, dependent data, robust bootstrap, and tensors. Robustness issues are illustrated throughout using real-world examples and key algorithms are included in a MATLAB Robust Signal Processing Toolbox accompanying the book online, allowing the methods discussed to be easily applied and adapted to multiple practical situations. This unique resource provides a powerful tool for researchers and practitioners working in the field of signal processing.

  • 5 - Spectrum exploration and exploitation

  • Ezio Biglieri, Universitat Pompeu Fabra, Barcelona, Andrea J. Goldsmith, Stanford University, California, Larry J. Greenstein, Rutgers University, New Jersey, Narayan B. Mandayam, Rutgers University, New Jersey, H. Vincent Poor, Princeton University, New Jersey
  • Book:
    Principles of Cognitive Radio
    Published online:
    05 December 2012
    Print publication:
    15 November 2012, pp 184-258

  • Summary

    Introduction

    Chapter motivation

    Chapter 4 introduced the basic spectrum sensing framework for detecting the presence of primary users in a cognitive radio system. In this chapter, we develop this framework further by taking a look at how a cognitive radio system or a cognitive radio network can optimize its spectrum sensing and access functions in order to explore and exploit the spectrum in the most efficient and effective manner. Chapters 1 and 2 described three cognitive radio network paradigms, i.e., the underlay, overlay, and interweave paradigms. In this chapter, we focus almost exclusively on the interweave paradigm in which the secondary users try to exploit the spatio-temporal spectral opportunities (i.e., spectrum holes) resulting from intermittent and uneven spatial and temporal use of the spectrum by the primary users. As described in Chapter 4, these spectrum holes are typically considered to be white spaces, i.e., completely empty of any signals, except for noise. In addition, we will consider a few approaches suitable also for the underlay paradigm. In particular, we will consider game-theoretic techniques and algorithms for spectrum access and sharing in cognitive radio networks that operate under interference temperature constraints, as described in Chapter 4. The remaining third paradigm, the overlay paradigm, is not explicitly considered in this chapter.