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International Conference on Machine Learning and Intelligent Communications

MLICOM 2021: Machine Learning and Intelligent Communications pp 1–8Cite as

Deep Learning Network for Frequency Offset Cancellation in OFDM Communication System

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Abstract

A deep learning network for OFDM system is proposed to eliminate the CFO (carrier frequency offset) interference in OFDM system. The CFO greatly reduces the BER performance for the communication system. The frequency offset interference introduced needs to be eliminated before signal demodulation. Therefore, we propose the method to eliminate weights by establishing a deep learning network, and then form the optimization elimination weight matrix through iteration. Among them, the hidden layer and weights are trained and fine-tuned in the forward direction to cancel the interference introduced by CFO. Compared with MMSE and LS algorithm, the proposed deep learning network greatly improves the bit error rate performance. The simulation has proved that the proposed deep learning network algorithm has BER performance in OFDM systems.

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References

  1. Cao, Z.R., Tureli, U., Yao, Y.D.: Analysis of two receiver schemes for interleaved OFDMA uplink. In: IEEE International Conference on Signals, Systems and Computers, vol. 2, pp. 1818–1821 (2002)

    Google Scholar 

  2. Huang, M., Chen, X., Zhou, S., et al.: Iterative ICI cancellation algorithm for uplink OFDMA system with carrier-frequency offset. In: IEEE International Conference on Vehicular Technology, vol. 3, pp. 1613–1617 (2005)

    Google Scholar 

  3. Choi, J.H., Lee, C., Jung, H.W., et al.: Carrier frequency offset compensation for uplink of OFDM-FDMA systems. IEEE Trans. Commun. Lett. 4(12), 414–416 (2000)

    Article  Google Scholar 

  4. Pun, M.O., Morelli, M., Kuo, C.J.: Iterative detection and frequency synchronization for OFDMA uplink transmissions. IEEE Trans. Wirel. Commun. 6(2), 629–639 (2007)

    Article  Google Scholar 

  5. Fantacci, R., Marabissi, D., Papini, S.: Multiuser interference cancellation receivers for OFDMA uplink communications with carrier frequency offset. In: IEEE International Conference on Globecom 2004, vol. 5, pp. 2808–2812 (2004)

    Google Scholar 

  6. Trajkovic, V.D., Rapajic, P.B., Kennedy, R.A.: Adaptive ordering for imperfect successive decision feedback multiuser detection. IEEE Trans. Commun. 56(2), 173–176 (2008)

    Article  Google Scholar 

  7. Tevfik, Y., Huseyin, A.: Carrier frequency offset compensation with successive cancellation in uplink OFDMA systems. IEEE Trans. Wireless Commun. 6(10), 3546–3551 (2007)

    Article  Google Scholar 

  8. Hou, S.W., Ko, C.: Intercarrier interference suppression for OFDMA uplink in time and frequency selective rayleigh fading channels. In: IEEE International Conference on Vehicular Technology, pp. 1438–1442 (2008)

    Google Scholar 

  9. Weeraddana, P., Rajatheva, N., Minn, H.: Probability of error analysis of BPSK OFDM systems with random residual frequency offset. IEEE Trans. Commun. 57(1), 106–116 (2005)

    Article  Google Scholar 

  10. Huang, D., Letaief, K.B.: An interference cancellation scheme for carrier frequency offsets correction in OFDMA systems. IEEE Trans. Wireless Commun. 53(7), 1155–1165 (2005)

    Article  Google Scholar 

  11. Yong, S., Xiong, Z., Wang, X.: EM-based iterative receiver design with carrier-frequency offset estimation for MIMO OFDM systems. IEEE Trans. Commun. 53(4), 581–586 (2005)

    Article  Google Scholar 

  12. Lashkarian, N., Kiaei, S.: Class of cyclic-based estimators for frequency-offset estimation of OFDM systems. IEEE Trans. Commun. 48(12), 2139–2149 (2000)

    Article  Google Scholar 

  13. Krongold, B.S.: Analysis of cyclic-prefix correlation statistics and their use in OFDM timing and frequency synchronization. In: IEEE International Conference on Signals, Systems and Computers, pp. 1466–1470 (2005)

    Google Scholar 

  14. Stoica, P., Soderstrom, T.: Statistical analysis of MUSIC and subspace rotation estimates of sinusoidal frequencies. IEEE Trans. Signal Process. 39(8), 1836–1847 (1991)

    Article  MATH  Google Scholar 

  15. Visser, M.A., Zong, P.P., Bar-Ness, Y.: A novel method for blind frequency offset correction in an OFDM system. In: IEEE International Conference on Personal, Indoor and Mobile Radio Communications, vol. 2, pp. 816–820 (1998)

    Google Scholar 

  16. Chiavaccini, E., Vitetta, G.M.: Maximum-likelihood frequency recovery for OFDM signals transmitted over multipath fading channels. IEEE Trans. Commun. 52(2), 244–251 (2004)

    Article  Google Scholar 

  17. MerliFZ, V.: Blind feedforward frequency estimation for OFDM signals transmitted over multipath fading channels. IEEE Trans. Wireless Commun. 6(6), 2055–2059 (2007)

    Article  Google Scholar 

  18. Kuang, L.L., Ni, Z.Y., Lu, J.H., et al.: A time-frequency decision-feedback loop for carrier frequency offset tracking in OFDM systems. IEEE Trans. Wireless Commun. 4(2), 367–373 (2005)

    Article  Google Scholar 

  19. Ylioinas, J., Juntti, M.: EM based iterative receiver for joint decoding and channel parameter estimation in space-frequency turbo coded OFDM. In: IEEE International Conference on Personal, Indoor and Mobile Radio Communications, pp. 1–5 (2006)

    Google Scholar 

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Acknowledgment

This work was supported by the Scientific Research Initiation Funds for the Doctoral Program of Xi'an International University (Grant No. XAIU2019002), Regional Innovation Capability Guidance Project (Grant No. 2021QFY01-08) and the General Project of science and Technology Department of Shaanxi Province (Grant No. 2020JM-638).

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Authors and Affiliations

  1. College of Engineering, Xi’an International University, Xi’an, 710077, China

    Qingyang Guan & Shuang Wu

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  1. Qingyang Guan
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  2. Shuang Wu
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Correspondence to Shuang Wu .

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Editors and Affiliations

  1. Jinhua Advanced Research Institute, Jinhua, China

    Xiaolin Jiang

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Guan, Q., Wu, S. (2022). Deep Learning Network for Frequency Offset Cancellation in OFDM Communication System. In: Jiang, X. (eds) Machine Learning and Intelligent Communications. MLICOM 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 438. Springer, Cham. https://doi.org/10.1007/978-3-031-04409-0_1

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  • DOI: https://doi.org/10.1007/978-3-031-04409-0_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04408-3

  • Online ISBN: 978-3-031-04409-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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