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Research on OTFS Performance Based on Joint-Sparse Fast Time-Varying Channel Estimation

  • Wenjing GaoEmail author
  • Shanshan Li
  • Lei Zhao
  • Wenbin Guo
  • Tao Peng
Conference paper
  • 180 Downloads
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 312)

Abstract

Contraposing the problem of high pilot overhead and poor estimation performance for OFDM system in fast time-varying channels, a novel channel estimation method based on joint-sparse basis expansion model is proposed. In order to resist the inter-carrier interference (ICI) of OFDM system over fast time-varying channel, we introduce the OTFS (Orthogonal Time Frequency Space) technique and propose an implementation scheme of OTFS system based on time-frequency domain channel estimation. Simulation results demonstrate that the proposed OTFS system has higher reliability and better adaptability than the OFDM system in high dynamic scenarios.

Keywords

Time-varying channel estimation OTFS Joint-sparse basis expansion model Compressed sensing 

Notes

Acknowledgment

This work was partially supported by National Natural Science Foundation of China (NSFC 61271181, 61571054) and the Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Foundation

References

  1. 1.
    Mostofi, Y., Cox, D.C.: ICI mitigation for pilot-aided OFDM mobile systems. IEEE Trans. Wirel. Commun. 4(2), 764–774 (2005)CrossRefGoogle Scholar
  2. 2.
    Hlawatsch, F., Matz, G.: Wireless Communications Over Rapidly Time-Varying Channels (2001)Google Scholar
  3. 3.
    Rabbi, M.F., Hou, S.W., Ko, C.C.: High mobility orthogonal frequency division multiple access channel estimation using basis expansion model. IET Commun. 4(3), 353 (2010)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Deng, L., Chen, Z., Zhao, Y.: Basis expansion model for channel estimation in LTE-R communication system. Digit. Commun. Netw. 2(2), 92–96 (2016)CrossRefGoogle Scholar
  5. 5.
    Wang, X., Wang, G., Fan, R., et al.: Channel estimation with expectation maximization and historical information based basis expansion model for wireless communication systems on high speed railways. IEEE Access 6, 72–80 (2018)CrossRefGoogle Scholar
  6. 6.
    Wang, X., Wang, J., et al.: Doubly selective underwater acoustic channel estimation with basis expansion model. In: 2017 IEEE International Conference on Communications, pp. 1–6 (2017)Google Scholar
  7. 7.
    Ma, X., Yang, F., Liu, S., et al.: Sparse channel estimation for MIMO-OFDM systems in high-mobility situations. IEEE Trans. Veh. Technol. 67, 6113–6124 (2018)CrossRefGoogle Scholar
  8. 8.
    Liu, T., Zheng, K., Wang, P.: Compressive sensing based channel estimation for scattered pilot OFDM Systems over doubly-selective Rician channel. In: 2016 25th Wireless and Optical Communication Conference (WOCC) (2018)Google Scholar
  9. 9.
    Le, T.B., Makula, P., Bui, T.T., et al.: Group successive ICI cancellation for MIMO-OFDM systems in underwater acoustic channels. In: International Conference on Mechatronics-Mechatronika. IEEE (2017)Google Scholar
  10. 10.
    Park, K., Kim, H., Lee, A., et al.: Iterative frequency-domain inter-carrier interference cancellation for coded spectrally efficient frequency division multiplexing. Electron. Lett. 53(19), 1333–1335 (2017)CrossRefGoogle Scholar
  11. 11.
    Hadani, R., Rakib, S., Molisch, A.F., et al.: Orthogonal Time Frequency Space (OTFS) modulation for millimeter-wave communications systems. In: 2017 IEEE MTT-S International Microwave Symposium (IMS), pp. 681–683 (2017) Google Scholar
  12. 12.
    Hadani, R., Monk, A.: OTFS: a new generation of modulation addressing the challenges of 5G (2018)Google Scholar
  13. 13.
    Vahidi, V., Saberinia, E.: Channel estimation for wideband doubly selective UAS channels. In: International Conference on Unmanned Aircraft Systems. IEEE (2017)Google Scholar
  14. 14.
    Hu, D., Wang, X., He, L.: A new sparse channel estimation and tracking method for time-varying OFDM systems. IEEE Trans. Veh. Technol. 62(9), 4648–4653 (2013)CrossRefGoogle Scholar
  15. 15.
    Tropp, J.A., Gilbert, A.C., Strauss, M.J.: Simultaneous sparse approximation via greedy pursuit. In: IEEE International Conference on Acoustics. IEEE (2005)Google Scholar
  16. 16.
    Qin, Q., Gui, L., Gong, B., et al.: Structured distributed compressive channel estimation over doubly selective channels. IEEE Trans. Broadcast. 62, 521–531 (2016)CrossRefGoogle Scholar
  17. 17.
    Murali, K.R., Chockalingam, A.: On OTFS modulation for high-doppler fading channels. In: 2018 Information Theory and Applications Workshop (ITA), pp. 1–10 (2018)Google Scholar
  18. 18.
    Joel, A., Anna, C., et al.: Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans. Inf. Theory 53(12), 4655–4666 (2007)MathSciNetCrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020

Authors and Affiliations

  • Wenjing Gao
    • 1
    • 2
    Email author
  • Shanshan Li
    • 1
  • Lei Zhao
    • 1
  • Wenbin Guo
    • 1
    • 2
  • Tao Peng
    • 1
  1. 1.Wireless Signal Processing and Network LaboratoryBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Science and Technology on Information Transmission and Dissemination in Communication Networks LaboratoryBeijingChina

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