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Near-field wideband channel estimation for extremely large-scale MIMO

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Abstract

Extremely large-scale multiple-input-multiple-output (XL-MIMO) at millimeter-wave (mmWave) and terahertz (THz) bands plays an important role in supporting extreme high beamforming gain as well as ultra-wideband spectrum resources. Unfortunately, accurate wideband XL-MIMO channel estimation suffers from a new challenge called the near-field beam split effect. Prior studies either neglect the accurate near-field channel model or fail to exploit the beam split effect, resulting in poor channel estimation accuracy for wideband XL-MIMO. To tackle this problem, this paper proposes a bilinear pattern detection (BPD)-based approach to accurately recover the wideband XL-MIMO channel. Specifically, by analyzing the characteristics of near-field wideband channels, we first reveal the bilinear pattern of the near-field beam split effect, which implies that the sparse support set of near-field channels in both the angle and the distance domains can be regarded as a linear function against frequency. Then, inspired by the classical simultaneously orthogonal matching pursuit technique, we use the bilinear pattern to estimate the angle-of-arrival (AoA) and distance parameters of each near-field path component at all frequencies. In this way, the entire wideband XL-MIMO channel can be recovered by compressed sensing algorithms. Moreover, we provide the computational complexity of the proposed algorithm compared with existing algorithms. Finally, simulation results demonstrate that our scheme can achieve the accurate estimation of the near-field wideband XL-MIMO channel in the presence of near-field beam split effect.

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References

  1. Rappaport T S, Xing Y, Kanhere O, et al. Wireless communications and applications above 100 GHz: opportunities and challenges for 6G and beyond. IEEE Access, 2019, 7: 78729–78757

    Article  Google Scholar 

  2. Zhang Z, Xiao Y, Ma Z, et al. 6G wireless networks: vision, requirements, architecture, and key technologies. IEEE Veh Technol Mag, 2019, 14: 28–41

    Article  Google Scholar 

  3. Ning B, Tian Z, Chen Z, et al. Prospective beamforming technologies for ultra-massive MIMO in terahertz communications: a tutorial. 2021. ArXiv:2107.03032

  4. Lin C, Li G Y L. Terahertz communications: an array-of-subarrays solution. IEEE Commun Mag, 2016, 54: 124–131

    Article  Google Scholar 

  5. Akdeniz M R, Liu Y, Samimi M K, et al. Millimeter wave channel modeling and cellular capacity evaluation. IEEE J Sel Areas Commun, 2014, 32: 1164–1179

    Article  Google Scholar 

  6. Akyildiz I F, Han C, Nie S. Combating the distance problem in the millimeter wave and terahertz frequency bands. IEEE Commun Mag, 2018, 56: 102–108

    Article  Google Scholar 

  7. Akyildiz I F, Jornet J M, Han C. Terahertz band: next frontier for wireless communications. Phys Commun, 2014, 12: 16–32

    Article  Google Scholar 

  8. Sohrabi F, Yu W. Hybrid digital and analog beamforming design for large-scale antenna arrays. IEEE J Sel Top Signal Process, 2016, 10: 501–513

    Article  Google Scholar 

  9. Heath R W, Gonzalez-Prelcic N, Rangan S, et al. An overview of signal processing techniques for millimeter wave MIMO systems. IEEE J Sel Top Signal Process, 2016, 10: 436–453

    Article  Google Scholar 

  10. Lee J, Gil G T, Lee Y H. Channel estimation via orthogonal matching pursuit for hybrid MIMO systems in millimeter wave communications. IEEE Trans Commun, 2016, 64: 2370–2386

    Article  Google Scholar 

  11. Huang C, Liu L, Yuen C, et al. Iterative channel estimation using LSE and sparse message passing for mmWave MIMO systems. IEEE Trans Signal Process, 2019, 67: 245–259

    Article  MathSciNet  MATH  Google Scholar 

  12. Rodriguez-Fernandez J, Gonzalez-Prelcic N, Venugopal K, et al. Frequency-domain compressive channel estimation for frequency-selective hybrid millimeter wave MIMO systems. IEEE Trans Wireless Commun, 2018, 17: 2946–2960

    Article  Google Scholar 

  13. Gao Z, Hu C, Dai L, et al. Channel estimation for millimeter-wave massive MIMO with hybrid precoding over frequency-selective fading channels. IEEE Commun Lett, 2016, 20: 1259–1262

    Article  Google Scholar 

  14. Eldar Y C. Sampling Theory: Beyond Bandlimited Systems. Cambridge: Cambridge University Press, 2015

    MATH  Google Scholar 

  15. Liao A, Gao Z, Wang D, et al. Terahertz ultra-massive MIMO-based aeronautical communications in space-air-ground integrated networks. IEEE J Sel Areas Commun, 2021, 39: 1741–1767

    Article  Google Scholar 

  16. Tan J, Dai L. Wideband channel estimation for THz massive MIMO. China Commun, 2021, 18: 66–80

    Article  Google Scholar 

  17. Dovelos K, Matthaiou M, Ngo H Q, et al. Channel estimation and hybrid combining for wideband terahertz massive MIMO systems. IEEE J Sel Areas Commun, 2021, 39: 1604–1620

    Article  Google Scholar 

  18. Yang J, Zeng Y, Jin S, et al. Communication and localization with extremely large lens antenna array. IEEE Trans Wireless Commun, 2021, 20: 3031–3048

    Article  Google Scholar 

  19. Chen Y, Yan L, Han C. Hybrid spherical- and planar-wave modeling and DCNN-powered estimation of terahertz ultra-massive MIMO channels. IEEE Trans Commun, 2021, 69: 7063–7076

    Article  Google Scholar 

  20. Cui M, Dai L. Channel estimation for extremely large-scale MIMO: far-field or near-field? IEEE Trans Commun, 2022, 70: 2663–2677

    Article  Google Scholar 

  21. Cui M, Wu Z, Lu Y, et al. Near-field MIMO communications for 6G: fundamentals, challenges, potentials, and future directions. IEEE Commun Mag, 2023, 61: 40–46

    Article  Google Scholar 

  22. Selvan K T, Janaswamy R. Fraunhofer and fresnel distances: unified derivation for aperture antennas. IEEE Antennas Propag Mag, 2017, 59: 12–15

    Article  Google Scholar 

  23. Zhang H, Shlezinger N, Guidi F, et al. Beam focusing for near-field multiuser MIMO communications. IEEE Trans Wireless Commun, 2022, 21: 7476–7490

    Article  Google Scholar 

  24. Cui M, Dai L, Wang Z, et al. Near-field rainbow: wideband beam training for XL-MIMO. IEEE Trans Wireless Commun, 2022. doi: https://doi.org/10.1109/TWC.2022.3222198

  25. Zhou Z, Gao X, Fang J, et al. Spherical wave channel and analysis for large linear array in LoS conditions. In: Proceedings IEEE Globecom Workshops, San Diego, 2015

  26. Wei L, Huang C, Alexandropoulos G C, et al. Channel estimation for RIS-empowered multi-user MISO wireless communications. IEEE Trans Commun, 2021, 69: 4144–4157

    Article  Google Scholar 

  27. Zhang Z, Dai L. A joint precoding framework for wideband reconfigurable intelligent surface-aided cell-free network. IEEE Trans Signal Process, 2021, 69: 4085–4101

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant No. 62031019), National Key Research and Development Program of China (Grant No. 2020YFB1805005), and European Commission through the H2020-MSCA-ITN META WIRELESS Research Project (Grant No. 956256).

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Authors and Affiliations

  1. Department of Electronic Engineering, Tsinghua University, Beijing National Research Center for Information Science and Technology (BNRist), Beijing, 100084, China

    Mingyao Cui & Linglong Dai

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  1. Mingyao Cui
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  2. Linglong Dai
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Correspondence to Linglong Dai.

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Cui, M., Dai, L. Near-field wideband channel estimation for extremely large-scale MIMO. Sci. China Inf. Sci. 66, 172303 (2023). https://doi.org/10.1007/s11432-022-3654-y

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  • DOI: https://doi.org/10.1007/s11432-022-3654-y

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