Blind Identification of Sparse Multipath Channels Under the Background of Internet of Things

  • Ying Li
  • Feng JinEmail author
  • Qi Liu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 302)


To improve the ability of blind identification and scheduling of sparse multipath channels in wireless communication networks under the background of Internet of things, a blind identification algorithm for sparse multipath wireless communication based on random sampling interval equalization and BPSK modulation is proposed. The sparse multipath channel model of wireless communication network under the background of Internet of things is constructed, and the multipath characteristics of sparse multipath channel of wireless communication network are analyzed. The BPSK modulation method is used to filter the inter-symbol interference of sparse multipath channel of wireless communication network. Based on the adaptive random sampling interval equalization technique, blind channel identification is designed, and the tap delay line model is used to suppress the multi-path of sparse multipath channel in wireless communication network. The simulation results show that the blind identification of sparse multipath channels in wireless communication networks is well balanced and the bit error rate (BER) is reduced.


Internet of things Sparse multipath channel Blind identification Communication 


  1. 1.
    Hu, S., Ding, Z., Ni, Q.: Beamforming optimisation in energy harvesting cooperative full-duplex networks with self-energy recycling protocol. IET Commun. 10(7), 848–853 (2016)CrossRefGoogle Scholar
  2. 2.
    Tang, L., Yang, X., Shi, Y.J., Chen, Q.B.: ARMA-prediction based online adaptive dynamic resource allocation in wireless virtualized networks. J. Electron. Inf. 41(1), 16–23 (2019)Google Scholar
  3. 3.
    Zhang, M., Jin, L.X., Li, G.N., Wu, Y.N., et al.: Design of image simulation system of TDICCD space camera. Chin. J. Liq. Cryst. Displays 31(2), 208–214 (2016)Google Scholar
  4. 4.
    Li, Y.B., Wang, D., et al.: Distributive beamforming design in multicell downlinks using interference and power control. Acta Electronica Sin. 43(3), 597–600 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Li, H., Huang, C., Cui, S.: Multiuser gain in energy harvesting wireless communications. IEEE Access 34(5), 10052–10061 (2017)CrossRefGoogle Scholar
  6. 6.
    Wang, Y., Sun, R., Wang, X.: Transceiver design to maximize the weighted sum secrecy rate in full-duplex SWIPT systems. IEEE Signal Process. Lett. 23(6), 883–887 (2016)CrossRefGoogle Scholar
  7. 7.
    Eo, D.W., Lee, J.H., Lee, H.S.: Optimal coupling to achieve maximum output power in a WPT system. IEEE Trans. Power Electron. 31(6), 3994–3998 (2016)CrossRefGoogle Scholar
  8. 8.
    Dai, H., Huang, Y., Li, C., et al.: Energy-efficient resource allocation for device-to-device communication with WPT. IET Commun. 11(3), 326–334 (2017)CrossRefGoogle Scholar
  9. 9.
    Helmy, A., Hedayat, A., Al-Dhahir, N.: Robust weighted sum-rate maximization for the multi-stream MIMO interference channel with sparse equalization. IEEE Trans. Commun. 60(10), 3645–3659 (2015)CrossRefGoogle Scholar
  10. 10.
    Alfaro, V.M., Vilanovab, R.: Robust tuning of 2DoF five-parameter PID controllers for inverse response controlled processes. J. Process Control 23(4), 453–462 (2013)CrossRefGoogle Scholar
  11. 11.
    Han, D.Z., Chen, X.G., Lei, Y.X., et al.: Real-time data analysis system based on spark streaming and its application. J. Comput. Appl. 37(5), 1263–1269 (2017)Google Scholar
  12. 12.
    Feng, W., Wang, Y., Lin, D., et al.: When mm wave communications meet network densification, a scalable interference coordination perspective. IEEE J. Sel. Areas Commun. 35(7), 1459–1471 (2017)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Information and Communication CollegeNational University of Defense TechnologyXi’anChina

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