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Handbook on Array Processing and Sensor Networks by K. J. Ray Liu, Simon Haykin

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images CHAPTER 24

Spectral Estimation in Cognitive Radios

Behrouz Farhang-Boroujeny

ECE Department, University of Utah, Salt Lake City

The demand for ubiquitous wireless services has been on the rise in the past and is expected to remain the same in the future. As a result, the vast majority of the available spectral resources have already been licensed. It thus appears that there is little or no room to add any new services, unless some of the existing licenses are discontinued. On the other hand, studies have shown that vast portions of the licensed spectra are rarely used [1, 2]. This has initiated the idea of cognitive radio (CR), where secondary (i.e., unlicensed) users are allowed to transmit and receive data over portions of spectra when primary (i.e., licensed) users are inactive. This is done in a way that the secondary users (SUs) are transparent to the primary users (PUs). For this, SUs need to sense the spectrum, and this involves some sort of spectral analysis.

The term spectral analysis refers to any signal processing method that may be used to estimate the power distribution, known as power spectral density (PSD), of a signal across the frequency axis. Spectral estimation methods can be broadly divided in two classes: parametric and nonparametric [3]. In parametric spectral estimation, the input process is modeled as a cascade of a white random process and a linear time ...

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