WANG Kai, LIU Yulin, WAN Qun, JING Xiaojun. Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements[J]. Chinese Journal of Electronics, 2015, 24(2): 388-392. doi: 10.1049/cje.2015.04.027
Citation: WANG Kai, LIU Yulin, WAN Qun, JING Xiaojun. Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements[J]. Chinese Journal of Electronics, 2015, 24(2): 388-392. doi: 10.1049/cje.2015.04.027

Compressed Sensing of Wireless Sensor Networks Data with Missed Measurements

doi: 10.1049/cje.2015.04.027
Funds:  This work is supported by the Program for New Century Excellent Talents in University (No.NCET-11-0873), the Program for Innovative Research Team in University of Chongqing (No.KJTD201343), the Key Project of Chongqing Natural Science Foundation (No.CSTC2011BA2016), and the Program for Fundamental and Advanced Research of Chongqing (No.CSTC2013JCYJA40045).
  • Publish Date: 2015-04-10
  • In Wireless sensor networks (WSNs), missed measurements may be caused by the sensor malfunction and interruption of communication between sensor nodes. The feasibility of exact recovery of WSNs data with missed measurements is analyzed in the framework of compressed sensing. A new incomplete measurement model was developed and the data reconstruction algorithm was proposed. The required number of the missing measurements and the sparsity condition of network data are found for exact compressed sensing ofWSNs data. Theoretical derivation shows that aWSNs data of length N with no more than M/(log(N/M)+1) nonzero coefficients can be exactly recovered with M Gaussian measurements, provided that fraction of the missed measurements is less than a quarter of the Restricted isometry property (RIP) constant squared. Simulation results validate the theoretical results.
  • loading
  • I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “Wireless sensor networks: A survey”, Computer Networks, Vol.38, No.4, pp.393-422, 2002.
    C.Y. Chong and S.P. Kumar, “Sensor networks: Evolution, opportunities, and challenges”, Proceedings of the IEEE, Vol.91, No.8, pp.1247-1256, 2003.
    E. Candes, J. Romberg and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”, IEEE Transaction on Information Theory, Vol.52, No.4, pp.489-509, 2006.
    Y. Eldar and G. Kutyniok, Compressed Sensing: Theory and Applications, Cambridge University Press, New York, USA, 2012.
    D. Haiqiong, F. Changjun and J. Xiangyang, “Research on compressed sensing”, Chinese Journal of Computers, Vol.54, No.3, pp.425-434, 2011.
    J. Haupt, W. Bajwa, M. Rabbat and R. Nowak, “Compressed sensing for networked data”, Signal Processing Magazine, IEEE, Vol.25, No.2, pp.92-101, 2008.
    C. Buratti, A. Conti, D. Dardari and R. Verdone, “An overview on wireless sensor networks technology and evolution”, Sensors, Vol.9, No.9, pp.6869-6896, 2009.
    A. Silberstein, K.Munagala and J. Yang, “Energy-efficient monitoring of extreme values in sensor networks”, Proceeding of the ACM International Conference on Management of Data, New York, pp.169-180, 2006.
    X.Y. Yang, H.B. Lim, T.M. Ozsu and K.L. Tan, “In-network execution of monitoring queries in sensor networks”, Proceeding of ACM SIGMOD International Conference on Management of Data, New York, pp.521-532, 2007.
    L.Q. Pan and J.Z Li, “A multiple regression model based missing values imputation algorithm in wireless sensor network”, Journal of Computer Research and Development, Vol.46, No.12, pp.2101-2110, 2009.
    Y. Zhang, “When is missing data recoverable?”, CAAM Technical Report, TR06-15, 2006.
    Z. Charbiwala, S. Chakraborty, S. Zahedi and K. Younghun, “Compressive oversampling for robust data transmission in sensor networks”, Proceeding of INFOCOM, San Diego, pp.1-9, 2010.
    D. Needell and J. Tropp, “Cosamp: Iterative signal recovery from incomplete and inaccurate samples”, Applied and Computational Harmonic Analysis, Vol.26, No.3, pp.301-321, 2009.
    D. Donoho, Y. Tsaig, I. Drori and S. Jeanluc, “Sparse solution of underdetermined linear equations by stage-wise orthogonal matching pursuit”, IEEE Transactions on Information Theory, Vol.58, No.2, pp.1094-1121, 2012.
    R. Baraniuk, M. Davenport and R. DeVore. “A simple proof of the restricted isometry property for random matrices”, Constructive Approximation, Vol.28, No.3, pp.253-263, 2008.
    Intel berkeley lab wsn, available at http://db.csail.mit.edu/labdata/labdata.html, 2004-6-2.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (214) PDF downloads(1098) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return