First-Orded Non-Gaussian Class C Interference Models and Their Associated Threshold Detection Algorithms

摘要

A useful approximate first-order characteristic function for Class C interference is obtained, for arbitrary combinations of the additive Class A and Class B nongaussian components which define Class C noise. From this, in turn, the associated first-order probability density, (w sub 1)(x sub c+g), is derived, including an independent gaussian component. The corresponding optimum threshold detection algorithms (for coherent, incoherent, and composite reception) are described, including the associated bias terms. The specific role of (w sub 1)(x sub c+g) in these threshold algorithms is noted, as well, also for the Class C statistics (L sup 2, L sup 4) governing detector performance. Various topics for subsequent investigation are briefly indicated.