Linear-Quadratic Detectors for Spectrum Sensing

Ezio Biglieri and Marco Lops

Abstract : Spectrum sensing for cognitive-radio applications may use a matched-filter detector (in the presence of full knowledge of the signal that may be transmitted by the primary user) or an energy detector (when that knowledge is missing). An intermediate situation occurs when the primary signal is imperfectly known, in which case we advocate the use of a linear-quadratic detector. We show how this detector can be designed by maximizing its deflection, and, using moment-bound theory, we examine its robustness to the variations of the actual probability distribution of the inaccurately known primary signal.​

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