Compressed Sensing Based Protocol for Efficient Reconstruction of Sparse Superimposed Data in a Multi-Hop Wireless Sensor Network
The authors consider a multi-hop wireless sensor network that measures sparse events and propose a simple forwarding protocol based on Compressed Sensing (CS) which does not need any sophisticated Media Access Control (MAC) scheduling, neither a routing protocol, thereby making significant overhead and energy savings. By means of flooding, multiple packets with different superimposed measurements are received simultaneously at any node. Thanks to their protocol, each node is able to recover each measurement and forward it while avoiding cycles. Numerical results show that their protocol achieves close to zero reconstruction errors at the sink, while greatly reducing overhead.