Syed Safwan Khalid

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Statistical spectrum sensing is a promising method which can reliably detect the primary users while requiring little prior information in cognitive radio networks. In this paper, we present an overview of sensing methods based on Goodness-of-Fit tests. We discuss the performance of Energy Detector (ED) sensing, Anderson Darling (AD) sensing, Cram'er(More)
Envelop-based (EVB) SNR estimators are robust to carrier offset and phase jitter. The performance of such estimators however, degrades with increasing SNR for nonconstant modulus constellations. In this work, we consider the SNR estimation as an optimum scale-invariant rank discrimination testing problem and propose an EVB algorithm that does not fail at(More)
Modulation classification is a signal processing technique which can estimate the modulation format of the received signals using multiple hypotheses test In this paper, we have presented an overview of modulation classification techniques based on Goodness-of-Fit tests. We have discussed the classification performance of modulation classification method(More)
A modulation classification method based on modified Kolmogorov-Smirnov (K-S) test is proposed. Unlike modulation classification based on K-S test, the proposed method evaluates the sum of the difference between the empirical distribution obtained from the features extracted from received signals and the hypothesized distribution for each modulation(More)
We obtain a class of higher-degree stochastic integration filters (SIF) for nonlinear filtering applications. SIF are based on stochastic spherical-radial integration rules that achieve asymptotically exact evaluations of Gaussian weighted multivariate integrals found in nonlinear Bayesian filtering. The superiority of the proposed scheme is demonstrated by(More)
The area under the Receiver-Operating-Characteristic (ROC) curve of a detector is a simple and suitable figure-of-merit of its detection capability. However the problem of determining the Area-Under-the-Curve (AUC) of an ROC is a non-trivial exercise and hence it has gone usually unnoticed in literature. In this report we analyze the AUC of the recently(More)
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