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CSI-Free Optimization of Reconfigurable Intelligent Surfaces with Interference by Using Multiport Network Theory (2402.17651v1)

Published 27 Feb 2024 in cs.IT, eess.SP, and math.IT

Abstract: Reconfigurable Intelligent Surfaces (RIS) will play a pivotal role in next-generation wireless systems. Despite efforts to minimize pilot overhead associated with channel estimation, the necessity of configuring the RIS multiple times before obtaining reliable Channel State Information (CSI) may significantly diminish their benefits. Therefore, we propose a CSI-free approach that explores the feasibility of optimizing the RIS for the uplink of a communication system in the presence of interfering users without relying on CSI estimation but leveraging solely some a priori statistical knowledge of the channel. In this context, we consider a multiport network model that accounts for several aspects overlooked by traditional RIS models used in Communication Theory, such as mutual coupling among scattering elements and the presence of structural scattering. The proposed approach targets the maximization of the average achievable rate and is shown to achieve performance that, in some cases, can be very close to the case where the RIS is optimized leveraging perfect CSI.

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References (54)
  1. C. Liaskos and al., “A new wireless communication paradigm through software-controlled metasurfaces,” IEEE Comm. Mag., vol. 56, no. 9, pp. 162–169, Sep. 2018.
  2. M. Di Renzo and al., “Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come,” EURASIP Journal on Wir. Comm. and Net., vol. 2019, no. 1, p. 129, 2019.
  3. Q. Wu and al., “Intelligent reflecting surface aided wireless communications: A tutorial,” IEEE Trans. on Comm., 2021.
  4. M. Di Renzo and al., “Smart radio environments empowered by reconfigurable intelligent surfaces: How it works, state of research, and road ahead,” IEEE JSAC, vol. 38, no. 11, pp. 2450–2525, July 2020.
  5. Y. Liu and al., “Reconfigurable intelligent surfaces: Principles and opportunities,” arXiv:2007.03435, 2020.
  6. M. Di Renzo and al., “Analytical modeling of the path-loss for reconfigurable intelligent surfaces – Anomalous mirror or scatterer ?” 21st Int. Workshop on Signal Proc. Advances in Wir. Comm., May 2020.
  7. E. Björnson, H. Wymeersch, B. Matthiesen, P. Popovski, L. Sanguinetti, and E. de Carvalho, “Reconfigurable intelligent surfaces: A signal processing perspective with wireless applications,” IEEE Signal Process. Mag., vol. 39, no. 2, pp. 135–158, Mar. 2022.
  8. X. Wei, D. Shen, and L. Dai, “Channel estimation for ris assisted wireless communications—part i: Fundamentals, solutions, and future opportunities,” IEEE Communications Letters, vol. 25, no. 5, pp. 1398–1402, 2021.
  9. Ö. T. Demir and E. Björnson, “Is channel estimation necessary to select phase-shifts for RIS-assisted massive MIMO?” IEEE Trans. Wireless Commun., pp. 1–1, Jun. 2022.
  10. Ö. T. Demir, E. Björnson, and L. Sanguinetti, “Exploiting array geometry for reduced-subspace channel estimation in RIS-aided communications,” in 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2022, pp. 455–459.
  11. X. Wei, D. Shen, and L. Dai, “Channel estimation for ris assisted wireless communications—part ii: An improved solution based on double-structured sparsity,” IEEE Communications Letters, vol. 25, no. 5, pp. 1403–1407, 2021.
  12. G. Zhou, C. Pan, H. Ren, P. Popovski, and A. L. Swindlehurst, “Channel estimation for RIS-aided multiuser millimeter-wave systems,” IEEE Trans. Signal Process., vol. 70, pp. 1478–1492, Mar. 2022.
  13. T. L. Jensen and E. De Carvalho, “An optimal channel estimation scheme for intelligent reflecting surfaces based on a minimum variance unbiased estimator,” in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 5000–5004.
  14. J. Chen, Y.-C. Liang, H. V. Cheng, and W. Yu, “Channel estimation for reconfigurable intelligent surface aided multi-user mmWave MIMO systems,” IEEE Trans. Wireless Commun., vol. 22, no. 10, pp. 6853–6869, Oct. 2023.
  15. A. de Jesus Torres, L. Sanguinetti, and E. Björnson, “Electromagnetic interference in RIS-aided communications,” IEEE Wireless Commun. Lett., vol. 11, no. 4, pp. 668–672, Apr. 2022.
  16. W.-X. Long, M. Moretti, L. Sanguinetti, and R. Chen, “Channel estimation in RIS-aided communications with interference,” IEEE Wireless Commun. Lett., vol. 12, no. 10, pp. 1751–1755, Oct. 2023.
  17. A. Abrardo, D. Dardari, M. Di Renzo, “Intelligent Reflecting Surfaces: Sum-Rate Optimization Based on Statistical Position Information,” IEEE Transactions on Communications, vol. 69, no. 10, pp 7121-7136
  18. A. Zappone and al., “Overhead-aware design of reconfigurable intelligent surfaces in smart radio environments,” IEEE Trans. on Wireless Comm., Vol. 20, no. 1, pp. 126-141, 2021
  19. M.-M. Zhao, Q. Wu, M.-J. Zhao, and R. Zhang, “Intelligent reflecting surface enhanced wireless networks: Two-timescale beamforming optimization,” IEEE Transactions on Wireless Communications, vol. 20, no. 1, pp. 2–17, 2021.
  20. F. Jiang, A. Abrardo, K. Keykhosravi, H. Wymeersch, D. Dardari, and M. D. Renzo, “Two-timescale transmission design and ris optimization for integrated localization and communications,” IEEE Trans. on Wireless Comm., vol. 22, no. 12, pp. 8587–8602, April 2023.
  21. Q.-U.-A. Nadeem, A. Chaaban, and M. Debbah, “Opportunistic beamforming using an intelligent reflecting surface without instantaneous CSI,” IEEE Wireless Communications Letters, to appear, 2020.
  22. Z. Peng, T. Li, C. Pan, H. Ren, W. Xu, and M. Di Renzo, “Analysis and optimization for IRS-aided multi-pair communications relying on statistical csi,” arXiv:2007.11704, 2020.
  23. D. Dardari and D. Massari, “Using metaprisms for performance improvement in wireless communications,” arXiv:2003.13505, 2020.
  24. M. Di Renzo, F. H. Danufane, and S. A. Tretyakov, “Communication models for reconfigurable intelligent surfaces: From surface electromagnetics to wireless networks optimization,” Proc. IEEE, vol. 110, no. 9, pp. 1164–1209, 2022.
  25. M. Di Renzo, A. Ahmed, A. Zappone, V. Galdi, G. Gradoni, M. Moccia, and G. Castaldi, “Digital reconfigurable intelligent surfaces: On the impact of realistic reradiation models,” CoRR, vol. abs/arXiv:2205.09799, 2022.
  26. S. Abeywickrama, R. Zhang, Q. Wu, and C. Yuen, “Intelligent reflecting surface: Practical phase shift model and beamforming optimization,” IEEE Trans. Commun., vol. 68, no. 9, pp. 5849–5863, 2020.
  27. M. Di Renzo, A. Mohamed, A. Zappone, G. Gradoni, M. Rossi, M. Moccia, G. Castaldi, and V. Galdi, “Effects of realistic reradiation models in digital reconfigurable intelligent surfaces,” Journal of Information and Intelligence, 2023.
  28. A. Rafique, N. U. Hassan, M. Zubair, I. H. Naqvi, M. Q. Mehmood, M. Di Renzo, M. Debbah, and C. Yuen, “Reconfigurable intelligent surfaces: Interplay of unit cell and surface-level design and performance under quantifiable benchmarks,” IEEE Open J. Commun. Soc., vol. 4, pp. 1583–1599, 2023.
  29. M. T. Ivrlac and J. A. Nossek, “Toward a circuit theory of communication,” IEEE Trans. Circuits Syst. I Regul. Pap., vol. 57-I, no. 7, pp. 1663–1683, 2010.
  30. M. Di Renzo, A. Zappone, M. Debbah, M. Alouini, C. Yuen, J. de Rosny, and S. A. Tretyakov, “Smart radio environments empowered by reconfigurable intelligent surfaces: How it works, state of research, and the road ahead,” IEEE J. Sel. Areas Commun., vol. 38, pp. 2450–2525, 2020.
  31. M. Movahediqomi, G. Ptitcyn, and S. Tretyakov, “Comparison between different designs and realizations of anomalous reflectors for extreme deflections,” IEEE Transactions on Antennas and Propagation, pp. 1–1, 2023.
  32. Y. Li, X. Ma, X. Wang, G. Ptitcyn, M. Movahediqomi, and S. A. Tretyakov, “Tunable perfect anomalous reflection using passive aperiodic gratings,” CoRR, vol. abs/arXiv:2303.05411, 2023.
  33. M. D. R. G. Gradoni, “End-to-end mutual coupling aware communication model for reconfigurable intelligent surfaces: An electromagnetic-compliant approach based on mutual impedances,” IEEE Wireless Commun. Lett., vol. 10, no. 5, pp. 938–942, May 2021.
  34. P. C. Chaumet, “The discrete dipole approximation: A review,” Mathematics, vol. 10, no. 17, 2022.
  35. R. Faqiri, C. Saigre-Tardif, G. C. Alexandropoulos, N. Shlezinger, M. F. Imani, and P. del Hougne, “Physfad: Physics-based end-to-end channel modeling of ris-parametrized environments with adjustable fading,” IEEE Trans. Wirel. Commun., vol. 22, no. 1, pp. 580–595, 2023.
  36. M. D. R. X. Qian, “Mutual coupling and unit cell aware optimization for reconfigurable intelligent surfaces,” IEEE Wireless Commun. Lett., vol. 10, no. 6, pp. 1183–1187, June 2021.
  37. H. E. Hassani, X. Qian, S. Jeong, N. S. Perovic, M. D. Renzo, P. Mursia, V. Sciancalepore, and X. Costa-Perez, “Optimization of ris-aided mimo – a mutually coupled loaded wire dipole model,” arXiv, June 2023.
  38. N. S. Perovic, L. Tran, M. Di Renzo, and M. F. Flanagan, “Optimization of ris-aided SISO systems based on a mutually coupled loaded wire dipole model,” CoRR, vol. abs/arXiv:2305.12735, 2023.
  39. M. Akrout, F. Bellili, A. Mezghani, and J. A. Nossek, “Physically consistent models for intelligent reflective surface-assisted communications under mutual coupling and element size constraint,” CoRR, vol. abs/arXiv:2302.11130, 2022.
  40. K. Konno, S. Terranova, Q. Chen, and G. Gradoni, “Generalised impedance model of wireless links assisted by reconfigurable intelligent surfaces,” CoRR, vol. abs/arXiv:2306.03761, 2023.
  41. P. Zheng, X. Ma, and T. Y. Al-Naffouri, “On the impact of mutual coupling on ris-assisted channel estimation,” CoRR, vol. abs/arXiv:2309.04990, 2023.
  42. S. Shen, B. Clerckx, and R. Murch, “Modeling and architecture design of reconfigurable intelligent surfaces using scattering parameter network analysis,” IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 1229–1243, 2022.
  43. A. Abrardo, A. Toccafondi, and M. D. Renzo, “Analysis and optimization of reconfigurable intelligent surfaces based on s-parameters multiport network theory,” arXiv:2308.16856 [cs.IT], accepted in IEEE EUCAP 2024, August 2023.
  44. ——, “Design of reconfigurable intelligent surfaces by using s-parameter multiport network theory – optimization and full-wave validation,” arXiv:2311.06648 [cs.IT], November 2023.
  45. W.-X. Long, M. Moretti, A. Abrardo, L. Sanguinetti, and R. Chen, “Mmse design of ris-aided communications,” arXiv:2312.07864 [cs.IT], December 2023.
  46. N. S. Perovic and al., “Achievable rate optimization for mimo systems with reconfigurable intelligent surfaces,” arXiv:2008.09563, 2020.
  47. T. V. Chien and al., “Reconfigurable intelligent surface-assisted cell-free massive mimo systems over spatially-correlated channels,” https://arxiv.org/pdf/2104.08648.pdf, 2021.
  48. O.T.Demir, E. Bjornson, and L. Sanguinetti, “Exploiting array geometry for reduced-subspace channel estimation in ris-aided communications,” 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop, pp. 445–459, 2022.
  49. W.-X. Long, M. Moretti, A. Abrardo, L. Sanguinetti, and R. Chen, “Mmse design of ris-aided communications,” arXiv:2312.07864, 2023.
  50. B. Hassibi and B. M. Hochwald, “How much training is needed in multiple-antenna wireless links?” IEEE Trans. Inf. Theor., vol. 49, no. 4, pp. 951–963, Apr 2003.
  51. M.-M. Zhao, Q. Wu, M.-J. Zhao, and R. Zhang, “Intelligent Reflecting Surface Enhanced Wireless Network: Two-timescale Beamforming Optimization,” arXiv e-prints, Dec. 2019.
  52. M. McKay and I. Collings, “General capacity bounds for spatially correlated rician mimo channels,” IEEE Transactions on Information Theory, vol. 51, no. 9, pp. 3121–3145, 2005.
  53. Ö. T. Demir, E. Björnson, and L. Sanguinetti, “Channel modeling and channel estimation for holographic massive MIMO with planar arrays,” IEEE Wireless Commun. Lett., vol. 11, no. 5, pp. 997–1001, May 2022.
  54. E. Björnson and L. Sanguinetti, “Rayleigh fading modeling and channel hardening for reconfigurable intelligent surfaces,” IEEE Wireless Commun. Lett., vol. 10, no. 4, pp. 830–834, Apr. 2021.

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