Cognitive radio technology has the potential to address the shortage of available radio
spectrum by enabling dynamic spectrum access. Since its introduction, researchers have …

Sparse signals are characterized by a few nonzero coefficients in one of their transformation
domains. This was the main premise in designing signal compression algorithms …

Compressed sensing (CS) is an emerging field that has attracted considerable research
interest over the past few years. Previous review articles in CS limit their scope to standard …

Random projection (RP) is a classical technique for reducing storage and computational
costs. We analyze RP-based approximations of convex programs, in which the original …

Compressive sensing (CS) exploits the sparsity present in many signals to reduce the
number of measurements needed for digital acquisition. With this reduction would come, in …

Intelligent Reflecting Surface (IRS) represents a significant breakthrough in wireless
communications, allowing the reconstruction of wireless channels even for occluded users …

In light of the ever-increasing demand for new spectral bands and the underutilization of
those already allocated, the concept of Cognitive Radio (CR) has emerged. Opportunistic …

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 …

With the adoption of arbitrary and increasingly wideband signals, the design of modern
radar systems continues to be limited by analog-to-digital converter technology and data …

Cognitive radio requires efficient and reliable spectrum sensing of wideband signals. In
order to cope with the sampling rate bottleneck, new sampling methods have been …