5th International ICST Conference on Communications and Networking in China

Research Article

On the application of compressed sensing in communication networks

Download659 downloads
  • @INPROCEEDINGS{10.4108/chinacom.2010.53,
        author={Xiao Wang and Zhifeng Zhao and Ning Zhao and Honggang Zhang},
        title={On the application of compressed sensing in communication networks},
        proceedings={5th International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2011},
        month={1},
        keywords={compressed sensing communication networks signal detection channel estimation data gathering network monitoring},
        doi={10.4108/chinacom.2010.53}
    }
    
  • Xiao Wang
    Zhifeng Zhao
    Ning Zhao
    Honggang Zhang
    Year: 2011
    On the application of compressed sensing in communication networks
    CHINACOM
    ICST
    DOI: 10.4108/chinacom.2010.53
Xiao Wang1,2, Zhifeng Zhao1,2,*, Ning Zhao1,2, Honggang Zhang1,2
  • 1: York-Zhejiang Lab for Cognitive Radio and Green Communications
  • 2: Department of Information Science and Electronic Engineering, Zhejiang University, Zheda Road 38, Hangzhou, 310027 China
*Contact email: zhaozf@zju.edu.cn

Abstract

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.