Data Aggregation Scheme Based on Compressed Sensing in Wireless Sensor Network

Compressive sensing (CS) is a novel approach to achieve much lower sampling rate for sparse signals. In order to reduce the number of data transmissions and save more energy, we apply CS theory to gather and reconstruct the sparse signals in energy-constrained large-scale wireless sensor network(WSN), Instead of sending full pair-wise measurement data to a sink, each sensor transmits only a small number of compressive measurements. The processes of CS aggregation in WSN are given. The relationship between Observations and reconstruct MSE are also discussed. Simulation result shows that our scheme can recovery the unknown data accurately as well as reduce global scale cost.