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The Scientific World Journal
Volume 2014, Article ID 473178, 9 pages
Research Article

Compressed Sensing Based Fingerprint Identification for Wireless Transmitters

1Department of Communication Engineering, Xiamen University, Xiamen, Fujian 361005, China
2Department of Computer Science and Information Engineering, National Taitung University, Taitung 95092, Taiwan

Received 12 March 2014; Accepted 1 April 2014; Published 29 April 2014

Academic Editor: Han-Chieh Chao

Copyright © 2014 Caidan Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Caidan Zhao, Zhibiao Cai, Minmin Huang, Mingxian Shi, Xiaojiang Du, and Mohsen Guizani, “The Identification of Secular Variation in IoT Based on Transfer Learning,” 2018 International Conference on Computing, Networking and Communications (ICNC), pp. 878–882, . View at Publisher · View at Google Scholar
  • Jian Chen, and Tiandong Duan, “Nonlinear feature extraction of power amplifiers in multipath,” 2015 4th International Conference on Computer Science and Network Technology (ICCSNT), pp. 1132–1136, . View at Publisher · View at Google Scholar
  • Caidan Zhao, Lianfen Huang, Yifeng Zhao, and Xiaojiang Du, “Secure Machine-Type Communications toward LTE Heterogeneous Networks,” IEEE Wireless Communications, vol. 24, no. 1, pp. 82–87, 2017. View at Publisher · View at Google Scholar
  • Gianmarco Baldini, and Gary Steri, “A Survey of Techniques for the Identification of Mobile Phones Using the Physical Fingerprints of the Built-In Components,” IEEE Communications Surveys & Tutorials, vol. 19, no. 3, pp. 1761–1789, 2017. View at Publisher · View at Google Scholar
  • Kevin Merchant, Shauna Revay, George Stantchev, and Bryan Nousain, “Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks,” IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 1, pp. 160–167, 2018. View at Publisher · View at Google Scholar