Spread Spectrum Signal Detection in Overlay Systems using Maximum Entropy PDF Estimation Based on Fractional Moments

In this paper we introduce a new nonlinear detector to improve the performance of spread spectrum receiver in the presence of narrow-band interference. The new detector is blind in the sense that no training data is required. In our scheme we use maximum likelihood (ML) detection rule in conjunction with maximum entropy method (MEM) for probability density function (PDF) estimation of the observation noise. We use MEM with a new approach based on fractional moments instead of integer moments. The estimated PDF based on fractional moments is quite close to the true PDF. The results indicate that the new nonlinear detector outperforms conventional matched filter, and well known locally optimal (LO) detector.