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Improved Extended-Kalman-Filter Beam Tracking Algorithm for Indoor Sub-THz Communications

Published:29 April 2024Publication History

ABSTRACT

In indoor sub-THz communication systems, due to interference, there is often an angle deviation between the transmitted beam and received beam, resulting in a sharp decline in the quality of receiving signal. In order to better cater to the needs of data transmission, this paper first designs beam precoders at the transmitter based on the concepts of successive interference cancellation (SIC) and equivalent channel. Next, considering the advantages of extended Kalman filter (EKF) algorithm in complexity and adaptability, which is suitable for mobile environments. In this article, we further use EKF for tracking and predicting the real and imaginary part of channel gain, the departure angle of beam separately to achieve the design of beam. Subsequently, the influence of factors such as the size of transmitter arrays and variance of angle changes on the proposed algorithm were studied. The simulation results indicate that proposed algorithm can perform beam tracking well and is suitable for practical mobile communication systems, thereby improving the signal quality and stability of mobile communication systems significantly.

References

  1. Akyildiz I F, Kak A, Nie S. 2020. 6G and beyond: The future of wireless communications systems. IEEE Access. 8, 133995-134030.Google ScholarGoogle ScholarCross RefCross Ref
  2. Xu L, Zhong W Z, Chen X M, 2018. A multi-beam training method for millimeter wave hybrid beamforming system. Journal of Microwaves. 34(6), 88-92.Google ScholarGoogle Scholar
  3. Zhu D L, Choi J, Cheng Q, 2018. High-resolution angle tracking for mobile wideband millimeter-wave systems with antenna array calibration. IEEE Transactions on Wireless Communications. 17(11), 7173-7189.Google ScholarGoogle ScholarCross RefCross Ref
  4. lkhateeb A, Heath R W. 2016. Frequency selective hybrid precoding for limited feedback millimeter wave systems. IEEE Transactions on Communications. 64(5), 1801-1818.Google ScholarGoogle ScholarCross RefCross Ref
  5. Alkhateeb A, El Ayach O, Leus G, 2014. Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE Journal of Selected Topics in Signal Processing. 8(5), 831-846.Google ScholarGoogle ScholarCross RefCross Ref
  6. Zhang R, Zhang H, Xu W, 2019. Subarray-cooperation-based multi-resolution codebook and beam alignment design for mmWave backhaul links. IEEE Access. 7, 18319-18331.Google ScholarGoogle ScholarCross RefCross Ref
  7. Zhang C, Guo D, Fan P. 2016. Tracking angles of departure and arrival in a mobile millimeter wave channel. 2016 IEEE International Conference on Communications. IEEE, 1-6.Google ScholarGoogle ScholarCross RefCross Ref
  8. Va V, Vikalo H, Heath R W. 2016. Beam tracking for mobile millimeter wave communication systems. 2016 IEEE Global Conference on Signal and Information Processing. IEEE, 743-747.Google ScholarGoogle ScholarCross RefCross Ref
  9. Han S, Xu Z, Rowell C. 2015. Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G. IEEE Communications Magazine. 53(1), 186-194.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. R. W. Heath Jr., N. Gonzalez-Prelcic, S. Rangan, W. Roh, and A. Sayeed. 2016. An overview of signal processing techniques for millimeter wave MIMO systems. IEEE Journal of Selected Topics in Signal Processing. 10(3), 436–453.Google ScholarGoogle ScholarCross RefCross Ref
  11. Xu X, Zhang R, Qian Y. 2022. Location-based hybrid precoding schemes and QOS-aware power allocation for radar-aided UAV–UGV cooperative systems. IEEE Access. 10, 50947-50958.Google ScholarGoogle ScholarCross RefCross Ref
  12. Zhang R, Zhang H, Xu W, 2019. Subarray-based simultaneous beam training for multiuser mmWave massive MIMO systems. IEEE Wireless Communications Letters. 8(4), 976-979.Google ScholarGoogle ScholarCross RefCross Ref
  13. Giordani M, Mezzavilla M, Barati C N, 2016. Comparative analysis of initial access techniques in 5G mmWave cellular networks[C]//2016 Annual Conference on Information Science and Systems. 268-273.Google ScholarGoogle Scholar
  14. Omar E A, Sridhar R, Heath R W. 2014. Spatially sparse precoding in millimeter wave MIMO systems. IEEE Transactions on Wireless Communications, 13(3), 1164-1179.Google ScholarGoogle Scholar
  15. Gao X, Dai L, Han S, 2016. Energy-efficient hybrid analog and digital precoding for mmWave MIMO systems with large antenna arrays. IEEE Journal on Selected Areas in Communications. 34(4), 998-1009.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Cui M, Zou W. 2019. Low complexity joint hybrid precoding for millimeter wave MIMO systems. China Communications, 16(2): 49-58.Google ScholarGoogle Scholar
  17. H. Gui, Y. Xie, Q. Song, Y. Qian and R. Zhang. 2023. Improved SIC-SVD Hybrid Precoding Algorithm for Indoor Sub-THz Systems. IEEE Access. 11, 93691-93700.Google ScholarGoogle ScholarCross RefCross Ref
  18. Zhang P, Zhang J, Xiao H, 2022. RIS-Aided 6G Communication System With Accurate Traceable User Mobility. IEEE Transactions on Vehicular Technology, 72(2): 2718-2722.Google ScholarGoogle ScholarCross RefCross Ref
  19. Jayaprakasam S, Ma X, Choi J W, 2017. Robust beam-tracking for mmWave mobile communications. IEEE Communications Letters. 21(12), 2654-2657.Google ScholarGoogle ScholarCross RefCross Ref
  20. B. Ristic, S. Arulampalm, and N. Gordon, Beyond the Kalman filter: particle filters for tracking applications. Artech House Boston, Ma. London, 2004.Google ScholarGoogle Scholar

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  • Published in

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    ICEITSA '23: Proceedings of the 3rd International Conference on Electronic Information Technology and Smart Agriculture
    December 2023
    541 pages
    ISBN:9798400716775
    DOI:10.1145/3641343

    Copyright © 2023 ACM

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    Publication History

    • Published: 29 April 2024

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