Capacity and Delay Analysis for Data Gathering with Compressive Sensing in Wireless Sensor Networks
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 the authors apply the theory of CS to data gathering for a WSN where n nodes are randomly deployed. They investigate the fundamental limitation of data gathering with CS for both single-sink and multi-sink random networks under protocol interference model, in terms of capacity and delay. For the single-sink case, they present a simple scheme for data gathering with CS and derive the bounds of the data gathering capacity.