On the application of compressed sensing in communication networks

Compressed sensing (CS) is an emerging theory based on the fact that the salient information of a signal can be preserved in a relatively small number of linear projections. Compressed sensing has been well used in the area of image compression and signal processing in the past few years. Recently, compressed sensing has been earning ever-increasing interests in the area of wireless communication networks. According to its advantageous characteristics, compressed sensing is able to play significant role in the fields like wireless channel estimation, signal detection, data gathering, network monitoring, and so on. This study describes current researches on the applications of compressed sensing in wireless communication networks, and then enumerates burning questions and the master keys of their corresponding solutions in these fields. Accordingly, we first introduce the basic approach of compressed sensing, and then summarize recent technical advancements of compressed sensing schemes and their applications in wireless communication networks. We assort these techniques according to the general OSI (Interconnection Reference Model) network model. In the end, we analyze problems and potential applications of compressed sensing, including novel methods for efficient data gathering by executing compressed sensing with random routing in wireless sensor networking environment.