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Clipping noise cancellation receiver for the downlink of massive MIMO OFDM system (2306.17455v1)

Published 30 Jun 2023 in cs.NI, cs.IT, and math.IT

Abstract: Massive multiple-input multiple-output (mMIMO) technology is considered a key enabler for the 5G and future wireless networks. In most wireless communication systems, mMIMO is employed together with orthogonal frequency-division multiplexing (OFDM) which exhibits a high peak-to-average-power ratio (PAPR). While passing the OFDM signal through one of the common RF front-ends of limited linearity, significant distortion of the transmitted signal can be expected. In mMIMO systems, this problem is still relevant as in some channels the distortion component is beamformed in the same directions as the desired signal. In this work, we propose a multi-antenna clipping noise cancellation (MCNC) algorithm for the downlink of the mMIMO OFDM system. Computer simulations show it can remove nonlinear distortion even under severe nonlinearity. Next, a simplified version of the algorithm is proposed. It was observed that for the direct visibility channels, its performance is only slightly degraded with respect to the MCNC algorithm.

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References (30)
  1. E. Björnson, J. Hoydis, and L. Sanguinetti, “Massive MIMO has unlimited capacity,” IEEE Transactions on Wireless Communications, vol. 17, no. 1, pp. 574–590, 2018.
  2. E. Björnson, J. Hoydis, M. Kountouris, and M. Debbah, “Massive MIMO systems with non-ideal hardware: Energy efficiency, estimation, and capacity limits,” IEEE Transactions on Information Theory, vol. 60, no. 11, pp. 7112–7139, 2014.
  3. E. G. Larsson and L. Van Der Perre, “Out-of-band radiation from antenna arrays clarified,” IEEE Wireless Communications Letters, vol. 7, no. 4, pp. 610–613, 2018.
  4. L. Anttila, A. Brihuega, and M. Valkama, “On antenna array out-of-band emissions,” IEEE Wireless Communications Letters, vol. 8, no. 6, pp. 1653–1656, 2019.
  5. C. Mollén, U. Gustavsson, T. Eriksson, and E. G. Larsson, “Spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities,” IEEE Transactions on Wireless Communications, vol. 17, no. 10, pp. 6663–6679, 2018.
  6. C. Mollen, E. G. Larsson, U. Gustavsson, T. Eriksson, and R. W. Heath, “Out-of-band radiation from large antenna arrays,” IEEE Communications Magazine, vol. 56, no. 4, pp. 196–203, 2018.
  7. S. H. Han and J. H. Lee, “An overview of peak-to-average power ratio reduction techniques for multicarrier transmission,” IEEE Wireless Communications, vol. 12, no. 2, pp. 56–65, 2005.
  8. X. Li and L. Cimini, “Effects of clipping and filtering on the performance of OFDM,” IEEE Communications Letters, vol. 2, no. 5, pp. 131–133, 1998.
  9. D. Kim and G. Stuber, “Clipping noise mitigation for OFDM by decision-aided reconstruction,” IEEE Communications Letters, vol. 3, no. 1, pp. 4–6, 1999.
  10. H. Chen and A. Haimovich, “Iterative estimation and cancellation of clipping noise for OFDM signals,” IEEE Communications Letters, vol. 7, no. 7, pp. 305–307, 2003.
  11. Y. Sun and H. Ochiai, “Performance analysis and comparison of clipped and filtered OFDM systems with iterative distortion recovery techniques,” IEEE Transactions on Wireless Communications, vol. 20, no. 11, pp. 7389–7403, 2021.
  12. S. R. Aghdam and T. Eriksson, “On the performance of distortion-aware linear receivers in uplink massive MIMO systems,” in 2019 16th International Symposium on Wireless Communication Systems (ISWCS), 2019, pp. 208–212.
  13. N. D. Lahbib, M. Cherif, M. Hizem, and R. Bouallegue, “BER analysis and CS-based channel estimation and HPA nonlinearities compensation technique for massive MIMO system,” IEEE Access, vol. 10, pp. 27 899–27 911, 2022.
  14. M. Cherif and R. Bouallegue, “The NDIC algorithm of HPA nonlinearity on MU-massive MIMO system performance,” in 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2020, pp. 1–4.
  15. F. Gregorio, S. Werner, T. I. Laakso, and J. Cousseau, “Receiver cancellation technique for nonlinear power amplifier distortion in SDMA–OFDM systems,” IEEE Transactions on Vehicular Technology, vol. 56, no. 5, pp. 2499–2516, 2007.
  16. N. Kamiya, “Deliberate clipping and iterative distortion recovery for UCA-based OAM multiplexing systems,” IEEE Access, vol. 9, pp. 169 250–169 260, 2021.
  17. S. V. Zhidkov and R. Dinis, “Belief propagation receivers for near-optimal detection of nonlinearly distorted OFDM signals,” in 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 2019, pp. 1–6.
  18. J. Felix, J. Guerreiro, R. Dinis, and P. Montezuma, “Reduced-complexity quasi-optimum detection for MIMO-OFDM signals with strong nonlinear distortion,” in 2019 IEEE Globecom Workshops (GC Wkshps), 2019, pp. 1–6.
  19. 3GPP, “Study on channel model for frequencies from 0.5 to 100 GHz,” 3rd Generation Partnership Project (3GPP), Technical Specification (TS) 38.901, 03 2022, version 17.0.0 Release 17.
  20. R. Raich, H. Qian, and G. Zhou, “Optimization of SNDR for amplitude-limited nonlinearities,” IEEE Transactions on Communications, vol. 53, no. 11, pp. 1964–1972, 2005.
  21. H. E. Rowe, “Memoryless nonlinearities with gaussian inputs: Elementary results,” The Bell System Technical Journal, vol. 61, no. 7, pp. 1519–1525, 1982.
  22. H. Yoo, F. Guilloud, and R. Pyndiah, “Probability distribution analysis of M-QAM-modulated OFDM symbol and reconstruction of distorted data,” EURASIP Journal on Advances in Signal Processing, vol. 2011, no. 135, 2011.
  23. S. Wei, D. L. Goeckel, and P. A. Kelly, “Convergence of the complex envelope of bandlimited OFDM signals,” IEEE Transactions on Information Theory, vol. 56, no. 10, pp. 4893–4904, 2010.
  24. V. A. Bohara and S. H. Ting, “Theoretical analysis of OFDM signals in nonlinear polynomial models,” in 2007 6th International Conference on Information, Communications & Signal Processing, 2007, pp. 1–5.
  25. MathWorks, “Compute square root using CORDIC,” 2022, available at https://www.mathworks.com/help/fixedpoint/ug/compute-square-root-using-cordic.html.
  26. S. Jaeckel, L. Raschkowski, K. Börner, and L. Thiele, “QuaDRiGa: A 3-D multi-cell channel model with time evolution for enabling virtual field trials,” IEEE Transactions on Antennas and Propagation, vol. 62, no. 6, pp. 3242–3256, 2014.
  27. 3GPP, “5G NR multiplexing and channel coding,” 3rd Generation Partnership Project (3GPP), Technical Specification (TS) 38.212, 04 2022, version 17.1.0 Release 17.
  28. MathWorks, “5G Toolbox,” 2023, available at https://www.mathworks.com/help/5g/ref/nrdlsch-system-object.html.
  29. J. Zhou, J. He, X. Lu, G. Wang, Y. Bo, G. Liu, Y. Huang, L. Li, C. Yang, H. Wang, W. Mo, W. Liu, C. Yu, and Z. Li, “100G fine-granularity flexible-rate passive optical networks based on discrete multi-tone with PAPR optimization,” Journal of Optical Communications and Networking, vol. 14, no. 11, pp. 944–950, 2022.
  30. A. Serra Pagès, J. Olmos, and M. Lema, “Modelling channel estimation error in LTE link level simulations,” IC1004 TD(12)03067, 01 2012.
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