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

The massive growth in mobile users and wireless technologies has resulted in increased
data traffic and created demand for additional radio spectrum. This growing demand for …

The compressive sensing (CS) framework aims to ease the burden on analog-to-digital
converters (ADCs) by reducing the sampling rate required to acquire and stably recover …

We give the first computationally tractable and almost optimal solution to the problem of one‐
bit compressed sensing, showing how to accurately recover an s‐sparse vector\input …

Consider the recovery of an unknown signal x from quantized linear measurements. In the
one-bit compressive sensing setting, one typically assumes that x is sparse, and that the …

The recently emerged compressive sensing (CS) framework aims to acquire signals at
reduced sample rates compared to the classical Shannon-Nyquist rate. To date, the CS …

In compressive sensing (CS), the goal is to recover signals at reduced sample rate
compared to the classic Shannon-Nyquist rate. However, the classic CS theory assumes the …

Binary measurements arise naturally in a variety of statistics and engineering applications.
They may be inherent to the problem-for example, in determining the relationship between …

The recently introduced compressive sensing (CS) framework enables digital signal
acquisition systems to take advantage of signal structures beyond bandlimitedness. Indeed …

We investigate the one-bit MIMO (1b-MIMO) radar that performs one-bit sampling with a time-
varying threshold in the temporal domain and employs compressive sensing in the spatial …