Monia Turki

Spectrum sensing for cognitive radio exploiting spectrum discontinuities detection

This article presents a spectrum sensing algorithm for wideband cognitive radio exploiting sensed spectrum discontinuity properties. Some work has already been investigated by wavelet approach by Giannakis et al., but in this article we investigate an algebraic framework in order to model spectrum discontinuities. The information derived at the level of these irregularities will be exploited in order to derive a spectrum sensing algorithm. The numerical simulation show satisfying results in terms of detection performance and receiver operating characteristics curves as the detector takes into account noise annihilation in its inner structure.

Voiced/unvoiced speech classification-based adaptive filtering of decomposed empirical modes for speech enhancement

This study presents a speech filtering method exploiting the combined effects of the empirical mode decomposition (EMD) and the local statistics of the speech signal using the adaptive centre weighted average (ACWA) filter. The novelty lies in incorporating the frame class (voiced/unvoiced) in the conventional filtering using the EMD and the ACWA filter. The speech signal is segmented into frames and each one is broken down by the EMD into a finite number of intrinsic mode functions (IMFs). The number of filtered IMFs depends on whether the frame is voiced or unvoiced. An energy criterion is used to identify voiced frames while a stationarity index distinguishes between unvoiced and transient sequences. Reported results obtained on signals corrupted by additive noise (white, F16, factory) show that the proposed filtering in line with the frame class is very effective in removing noise components from noisy speech signal. Compared with filtering results of the wavelet, the ACWA, and the EMD-ACWA methods, the proposed technique gives much better results in terms of average segmental signal-to-noise ratio and listening quality based on perceptual evaluation speech quality score.

Distribution discontinuities detection using algebraic technique for spectrum sensing in cognitive radio

In this paper1, we propose a new Spectrum Sensing technique for spectrum distribution discontinuities detection using algebraic detection (AD). The presented mathematical background leading to such technique is based on operational calculus and differential algebra which offers a new stand point in sensing theory. Even if this background is quite heavy, the sensing algorithm related to this technique is nevertheless very simple and remains with extremely low complexity, comparable even to the Energy Detection technique (ED). Simulations results show good performance of the proposed technique in terms of reliability and accuracy with low complexity and good robustness in noisy context.