Compressive sensing (CS)-based in-network data processing is a promising approach to
reduce packet transmission in wireless sensor networks. Existing CS-based data gathering …

Compressive Sensing (CS) has been recognized as a promising technique to reduce and
balance the transmission cost in wireless sensor networks (WSNs). Existing efforts mainly …

Data gathering in sensor networks is required to be efficient, adaptable and robust.
Recently, compressive sensing (CS) based data gathering shows promise in meeting these …

Compressive data gathering, which is based on the recent breakthroughs in compressive
sensing theory, has been proposed as a viable approach for sensor network data collection …

Compressive sensing (CS) provides a new paradigm for efficient data gathering in wireless
sensor networks (WSNs). In this paper, with the assumption that sensor data is sparse we …

Compressive sensing (CS) has been widely used in wireless sensor networks for the
purpose of reducing the data gathering communication overhead in recent years. In this …

Compressive Sensing (CS) can use fewer samples to recover a great number of original
data, which have a sparse representation in a proper basis. For energy-constrained …

The recent advances of compressive sensing (CS) have witnessed a great potential of
efficient compressive data gathering (CDG) in wireless sensor network systems (WSNSs) …

In this paper, we study the problem of data gathering with compressive sensing (CS) in
wireless sensor networks (WSNs). Unlike the conventional approaches, which require …

The data transmission process in Wireless Sensor Networks (WSNs) often experiences
errors and packet losses due to the environmental interference. In order to address this …