Detection of Digital Amplitude-Phase Modulated Signals in Symmetric Alpha-Stable Noise

In this paper, we propose a scheme for the detection of digital amplitude-phase modulated signals in flat fading channels with non-Gaussian noise. The additive noise is modeled by a symmetric alpha-stable distribution, a well-known model of man-made and natural noise that appears in various environments. A major challenge in the design of signal detection schemes is that detectors typically operate without knowledge of the transmitted data, channel state, and noise statistics. The design becomes especially difficult for the considered noise model since conventional signal processing approaches are not applicable. For this reason, we propose a five-stage signal detection scheme that is based on the use of a matched myriad filter. An important contribution of this paper is the development of new algorithms for the estimation of noise distribution parameters in the presence of an unknown signal. Results are presented which show that the proposed detector outperforms a zero-memory non-linearity-based scheme.