As a burgeoning technique for signal processing, compressed sensing (CS) is being
increasingly applied to wireless communications. However, little work is done to apply CS to …

Energy efficiency is one of the key objectives in data gathering in wireless sensor networks
(WSNs). Recent research on energy-efficient data gathering in WSNs has explored the use …

Although compressed sensing (CS) has been envisioned as a useful technique to improve
the performance of wireless sensor networks (WSNs), it is still not very clear how exactly it …

We focus on wireless sensor networks (WSNs) that perform data collection with the objective
of obtaining the whole dataset at the sink (as opposed to a function of the dataset). In this …

This paper proposes a novel data gathering method using Compressive Sensing (CS) and
random projection to improve the lifetime of large Wireless Sensor Networks (WSNs). To …

Compressive sensing (CS) can reduce the number of data transmissions and balance the
traffic load throughout networks. However, the total number of transmissions for data …

The emerging compressed sensing (CS) theory can significantly reduce the number of
sampling points that directly corresponds to the volume of data collected, which means that …

Sensing of the application environment is the main purpose of a wireless sensor network.
Most existing energy management strategies and compression techniques assume that the …

Compressive Sensing (CS) shows high promise for fully distributed compression in wireless
sensor networks (WSNs). In theory, CS allows the approximation of the readings from a …

In this paper, we study how to reduce energy consumption in large-scale sensor networks,
which systematically sample a spatio-temporal field. We begin by formulating a distributed …