CS-based framework for sparse signal transmission over lossy link

In this work, compressive sensing (CS) is applied to facilitate efficient wireless information transmission over lossy communication links. Inherently sparse data packets are transmitted without compression or error protection. The packet loss during transmission is modeled as a random sampling process of the transmitted data. The original signal then is reconstructed based on correctly received data packets using CS-based reconstruction method. No computations for source, channel coding or random measurement sampling will be required at the transmitter side. Thus, this method is suitable for applications where transmitters have extreme low power constraints such as wireless sensor networks. Compared with traditional error protection technique(automatic repeat request, data interleaving and interpolation), the proposed method delivers higher quality of sparse signal while significantly reducing energy consumption at transmitter as well as transmission latency.