Compressive sensing (CS) has received much attention in several fields such as digital
image processing, wireless channel estimation, radar imaging, and cognitive radio (CR) …

Compressed sensing deals with the reconstruction of signals from sub-Nyquist samples by
exploiting the sparsity of their projections onto known subspaces. In contrast, this article is …

The radio spectrum is the radio-frequency (RF) portion of the electromagnetic spectrum.
These spectral resources are traditionally allocated to licensed or primary users (PUs) by …

The goal of this letter is to propose an adaptive and distributed approach to cooperative
sensing for wireless small cell networks. The method uses a basis expansion model of the …

A novel power spectrum blind sampling (PSBS) approach is proposed supporting low-power
wireless sensor networks for Operational Modal Analysis (OMA) applications. The …

This article assesses numerically the potential of two different spectral estimation
approaches supporting non-uniform-in-time data sampling at sub-Nyquist average rates (ie …

Cognitive Radio (CR) challenges the traditional task of spectrum sensing with requirements
of reliability, efficiency and real-time. Sub-Nyquist sampling has been considered for this …

We examine power spectrum estimation from wide-sense stationary signals received at
different wireless sensors. We organize multiple sensors into several groups, where each …

Motivated by a need to reduce energy consumption in wireless sensors for vibration-based
structural health monitoring (SHM) associated with data acquisition and transmission, this …

Wideband spectrum sensing is one of the most challenging components of cognitive radio
networks. It should be performed as fast and accurately as possible. Traditional wideband …