Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Sense-Then-Train: An Active-Sensing-Based Beam Training Design for Near-Field MIMO Systems (2402.15634v2)

Published 23 Feb 2024 in cs.IT, eess.SP, and math.IT

Abstract: An active-sensing-based sense-then-train (STT) scheme is proposed for beam training in near-field multiple-input multiple-output (MIMO) systems. Compared to conventional codebook-based schemes, the proposed STT scheme is capable of not only addressing the complex spherical-wave propagation but also effectively exploiting the additional degrees-of-freedoms (DoFs). The STT scheme is tailored for both single-beam and multi-beam cases. 1) For the single-beam case, the STT scheme first utilizes a sensing phase to estimate a low-dimensional representation of the near-field MIMO channel in the truncated wavenumber domain. Then, in the subsequent training phase, the neural network modules at transceivers are updated online to align beams, utilizing sequentially received ping-pong pilots. This approach can efficiently obtain the aligned beam pair without relying on predefined codebooks or training datasets. 2) For the multi-beam case, based on the single-beam STT, a Gram-Schmidt method is further utilized to guarantee the orthogonality between beams in the training phase. Numerical results unveil that 1) the proposed STT scheme can significantly enhance the beam training performance in the near field compared to the conventional far-field codebook-based schemes, and 2) the proposed STT scheme can perform fast and low-complexity beam training, while achieving a near-optimal performance without full channel state information in both cases.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (35)
  1. H. Jiang, Z. Wang, and Y. Liu, “Active-sensing-based beam alignment for near field MIMO communications,” in Proc. IEEE Intl. Conf. Commun. (ICC), Accepted to appear, Jun. 2024.
  2. W. Jiang, B. Han, M. A. Habibi, and H. D. Schotten, “The road towards 6G: A comprehensive survey,” IEEE Open J. Commun. Soc., vol. 2, pp. 334–366, 2021.
  3. I.-R. S. M.2370-0, “IMT traffic estimates for the years 2020 to 2030,” Jun. 2015.
  4. A. Shafie, N. Yang, C. Han, J. M. Jornet, M. Juntti, and T. Kürner, “Terahertz communications for 6G and beyond wireless networks: Challenges, key advancements, and opportunities,” IEEE Netw., vol. 37, no. 3, pp. 162–169, May/Jun. 2023.
  5. X. Wang, L. Kong, F. Kong, F. Qiu, M. Xia, S. Arnon, and G. Chen, “Millimeter wave communication: A comprehensive survey,” IEEE Commun. Surveys Tuts., vol. 20, no. 3, pp. 1616–1653, Jun. 2018.
  6. T. Jiang, F. Sohrabi, and W. Yu, “Active sensing for two-sided beam alignment and reflection design using ping-pong pilots,” IEEE J. Sel. Areas Info. Theory, vol. 4, pp. 24–39, May 2023.
  7. T. Nitsche, A. B. Flores, E. W. Knightly, and J. Widmer, “Steering with eyes closed: Mm-wave beam steering without in-band measurement,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Aug. 2015, pp. 2416–2424.
  8. M. Qurratulain Khan, A. Gaber, P. Schulz et al., “Machine learning for millimeter wave and terahertz beam management: A survey and open challenges,” IEEE Access, vol. 11, pp. 11 880–11 902, Feb. 2023.
  9. Y. Heng and J. G. Andrews, “Grid-free MIMO beam alignment through site-specific deep learning,” IEEE Trans. Wireless Commun., Early Access, Jun. 2023, doi: 10.1109/TWC.2023.3283475.
  10. M. Giordani, M. Polese, A. Roy, D. Castor, and M. Zorzi, “A tutorial on beam management for 3GPP NR at mmwave frequencies,” IEEE Commun. Surveys Tuts., vol. 21, no. 1, pp. 173–196, Firstquarter 2019.
  11. Y. Liu, Z. Wang, J. Xu, C. Ouyang, X. Mu, and R. Schober, “Near-field communications: A tutorial review,” IEEE Open J. Commun. Soc., vol. 4, pp. 1999–2049, Aug. 2023.
  12. C. Wu, C. You, Y. Liu, L. Chen, and S. Shi, “Two-stage hierarchical beam training for near-field communications,” IEEE Trans. Veh. Tech., pp. 1–13, Early Access, Sept. 2023, doi: 10.1109/TVT.2023.3311868.
  13. Y. Liu, C. Ouyang, Z. Wang, J. Xu, X. Mu, and A. L. Swindlehurst, “Near-field communications: A comprehensive survey,” arXiv preprint arXiv:2401.05900, Jan. 2024.
  14. J. Song, J. Choi, and D. J. Love, “Common codebook millimeter wave beam design: Designing beams for both sounding and communication with uniform planar arrays,” IEEE Trans. Commun., vol. 65, no. 4, pp. 1859–1872, Apr. 2017.
  15. J. Zhang, Y. Huang, Y. Zhou, and X. You, “Beam alignment and tracking for millimeter wave communications via bandit learning,” IEEE Trans. Commun., vol. 68, no. 9, pp. 5519–5533, Sept. 2020.
  16. S. Wang and S. Bi, “Improving beam alignment accuracy in mmwave communication systems with auxiliary tasks,” IEEE Sig. Process. Lett., vol. 30, pp. 992–996, Jul. 2023.
  17. Z. Xiao, T. He, P. Xia, and X.-G. Xia, “Hierarchical codebook design for beamforming training in millimeter-wave communication,” IEEE Trans. Wireless Commun., vol. 15, no. 5, pp. 3380–3392, Jan. 2016.
  18. C. Qi, K. Chen, O. A. Dobre et al., “Hierarchical codebook-based multiuser beam training for millimeter wave massive MIMO,” IEEE Trans. Wireless Commun., vol. 19, no. 12, pp. 8142–8152, Sept. 2020.
  19. T. He and Z. Xiao, “Suboptimal beam search algorithm and codebook design for millimeter-wave communications,” Mobile Netw. Appl., vol. 20, pp. 86–97, Feb. 2015.
  20. M. Li, C. Liu, S. V. Hanly, I. B. Collings, and P. Whiting, “Explore and eliminate: Optimized two-stage search for millimeter-wave beam alignment,” IEEE Trans. Wireless Commun., vol. 18, no. 9, pp. 4379–4393, Jun. 2019.
  21. F. Sohrabi, T. Jiang, W. Cui, and W. Yu, “Active sensing for communications by learning,” IEEE J. Sel. Areas Commun., vol. 40, no. 6, pp. 1780–1794, Jun. 2022.
  22. F. Las-Heras, M. Pino, S. Loredo, Y. Alvarez, and T. Sarkar, “Evaluating near-field radiation patterns of commercial antennas,” IEEE Trans. Antennas and Propag., vol. 54, no. 8, pp. 2198–2207, Aug. 2006.
  23. M. Cui and L. Dai, “Channel estimation for extremely large-scale MIMO: Far-field or near-field?” IEEE Trans. Commun., vol. 70, no. 4, pp. 2663–2677, Jan. 2022.
  24. Y. Zhang, X. Wu, and C. You, “Fast near-field beam training for extremely large-scale array,” IEEE Wireless Commun. Lett., vol. 11, no. 12, pp. 2625–2629, Oct. 2022.
  25. X. Zhang, H. Zhang, J. Zhang, C. Li, Y. Huang, and L. Yang, “Codebook design for extremely large-scale MIMO systems: Near-field and far-field,” IEEE Trans. Commun., early access, Nov. 2023, doi: 10.1109/TCOMM.2023.3329224.
  26. M. Cui, L. Dai, Z. Wang, S. Zhou, and N. Ge, “Near-field rainbow: Wideband beam training for XL-MIMO,” IEEE Trans. Wireless Commun., vol. 22, no. 6, pp. 3899–3912, Jun. 2023.
  27. C. Ouyang, Y. Liu, X. Zhang, and L. Hanzo, “Near-field communications: A degree-of-freedom perspective,” arXiv preprint arXiv:2308.00362, Aug. 2023.
  28. Z. Wang, X. Mu, and Y. Liu, “Near-field integrated sensing and communications,” IEEE Commun. Lett., vol. 27, no. 8, pp. 2048–2052, May, 2023.
  29. L. Rothman, I. Gordon, Y. Babikov et al., “The HITRAN2012 molecular spectroscopic database,” J. Quant. Spectrosc. Radiati. Transf., vol. 130, pp. 4–50, 2013.
  30. A. Tang, J.-B. Wang, Y. Pan, W. Zhang, Y. Chen, H. Yu, and R. C. de Lamare, “Line-of-sight extra-large MIMO systems with angular-domain processing: Channel representation and transceiver architecture,” IEEE Trans. Commun., vol. 72, no. 1, pp. 570–584, Oct. 2024.
  31. A. Pizzo, L. Sanguinetti, and T. L. Marzetta, “Fourier plane-wave series expansion for holographic MIMO communications,” IEEE Trans. Wireless Commun., vol. 21, no. 9, pp. 6890–6905, Mar. 2022.
  32. L. Wei, C. Huang, G. C. Alexandropoulos, W. E. I. Sha, Z. Zhang, M. Debbah, and C. Yuen, “Multi-user holographic MIMO surfaces: Channel modeling and spectral efficiency analysis,” IEEE J. Sel. Topics Signal Process., vol. 16, no. 5, pp. 1112–1124, May, 2022.
  33. X. Yu, J.-C. Shen, J. Zhang et al., “Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems,” IEEE J. Sel. Topics Signal Process., vol. 10, no. 3, pp. 485–500, Feb. 2016.
  34. T. Dahl, N. Christophersen, and D. Gesbert, “Blind MIMO eigenmode transmission based on the algebraic power method,” IEEE Trans. Signal Process., vol. 52, no. 9, pp. 2424–2431, Sept. 2004.
  35. Z. Xie, Y. Liu, J. Xu, X. Wu, and A. Nallanathan, “Performance analysis for near-field MIMO: Discrete and continuous aperture antennas,” IEEE Wireless Commun. Lett., vol. 12, no. 12, pp. 2258–2262, Dec. 2023.
Citations (1)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now