Spectrum sensing, combined or not with database information on radio-frequency (RF)
spectrum occupation, is envisaged as part of the solution to the spectrum scarcity inherited …

The radio-frequency spectrum shortage, which is primarily caused by the fixed allocation
policy, is one of the main bottlenecks to the deployment of existing wireless communication …

This work studies the problem of neighbor discovery for device-to-device (D2D)
communications of LTE user equipments (UEs) in a modern cellular network. By listening to …

This book organizes principles and methods of signal processing and machine learning into
the framework of coherence. The book contains a wealth of classical and modern methods …

Spectrum sensing for cognitive radio requires effective monitoring of wide bandwidths,
which translates into high-rate sampling. Traditional spectrum sensing methods employing …

This paper addresses adaptive detection of a range distributed target in the presence of
dominant heterogeneous clutter, which is (possibly) low-rank and lies in a known subspace …

The idea of writing this book entitled “Cognitive Networked Sensing and Big Data” started
with the plan to write a briefing book on wireless distributed computing and cognitive …

In this paper, we consider the problem of detection of sparse stochastic signals based on 1-
bit data with tree-structured sensor networks (TSNs). In the literature, distributed detection of …

In this paper, we consider distributed detection of sparse stochastic signals with quantized
measurements. Assume that both the noise and the dominant elements in sparse signals …

In this paper, we consider the problem of detection of sparse stochastic signals with
quantized measurements in sensor networks. The observed sparse signals are assumed to …