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Energy-Efficient Active Element Selection in RIS-aided Massive MIMO Systems (2402.14994v2)

Published 22 Feb 2024 in cs.IT, eess.SP, and math.IT

Abstract: This chapter delves into the critical aspects of optimizing energy efficiency (EE) in active reconfigurable intelligent surface (RIS)-assisted massive MIMO (M-MIMO) wireless communication systems. We develop a comprehensive and unified theoretical framework to analyze the boundaries of EE within M-MIMO systems integrated with active RIS while adhering to practical constraints. Our research focuses on a formulated EE optimization problem aiming to maximize the EE for active RIS-assisted M-MIMO communication systems. Our goal is to strategically find the number of active RIS elements for outperforming the EE attainable by an entirely passive RIS. Besides, the proposed novel solution has been tailored to the innovative problem. The formulation and solution design consider analytical optimization techniques, such as lagrangian dual transform (LDT) and fractional programming (FP) optimization, facilitating the effective implementation of RIS-aided M-MIMO applications in real-world settings. In particular, our results show that the proposed algorithm can provide up to 120% higher EE than the entirely passive RIS. Besides, we found that the active RIS can operate with less than half of the reflecting elements for the entirely passive RIS. Finally, in view of active RIS achieving the complete utilization of amplification power available, it should be equipped with a reasonable number of reflecting elements above N = 49.

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References (52)
  1. Q. Wu and R. Zhang, “Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network,” IEEE Communications Magazine, vol. 58, no. 1, pp. 106–112, 2020.
  2. S. Gong, X. Lu, D. T. Hoang, D. Niyato, L. Shu, D. I. Kim, and Y.-C. Liang, “Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey,” IEEE Communications Surveys and Tutorials, vol. 22, no. 4, pp. 2283–2314, 2020.
  3. A. Taha, M. Alrabeiah, and A. Alkhateeb, “Enabling Large Intelligent Surfaces With Compressive Sensing and Deep Learning,” IEEE Access, vol. 9, pp. 44 304–44 321, 2021.
  4. R. Long, Y.-C. Liang, Y. Pei, and E. G. Larsson, “Active Reconfigurable Intelligent Surface-Aided Wireless Communications,” IEEE Transactions on Wireless Communications, vol. 20, no. 8, pp. 4962–4975, 2021.
  5. J. An, C. Yuen, L. Dai, M. D. Renzo, M. Debbah, and L. Hanzo, “Toward Beamfocusing-Aided Near-Field Communications: Research Advances, Potential, and Challenges,” 2023.
  6. X. Zhang and H. Zhang, “Hybrid Reconfigurable Intelligent Surfaces-Assisted Near-Field Localization,” IEEE Communications Letters, vol. 27, no. 1, pp. 135–139, 2023.
  7. Z. Wu and L. Dai, “Multiple Access for Near-Field Communications: SDMA or LDMA?” IEEE Journal on Selected Areas in Communications, vol. 41, no. 6, pp. 1918–1935, 2023.
  8. I. Ahmed, M. K. Shahid, H. Khammari, and M. Masud, “Machine Learning Based Beam Selection With Low Complexity Hybrid Beamforming Design for 5G Massive MIMO Systems,” IEEE Transactions on Green Communications and Networking, vol. 5, no. 4, pp. 2160–2173, 2021.
  9. T. Huang, W. Yang, J. Wu, J. Ma, X. Zhang, and D. Zhang, “A Survey on Green 6G Network: Architecture and Technologies,” IEEE Access, vol. 7, pp. 175 758–175 768, 2019.
  10. Y. Liu, Z. Wang, J. Xu, C. Ouyang, X. Mu, and R. Schober, “Near-Field Communications: A Tutorial Review,” IEEE Open Journal of the Communications Society, vol. 4, pp. 1999–2049, 2023. [Online]. Available: https://doi.org/10.1109%2Fojcoms.2023.3305583
  11. K. Shen and W. Yu, “Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching,” IEEE Transactions on Signal Processing, vol. 66, no. 10, pp. 2631–2644, 2018.
  12. ——, “Fractional Programming for Communication Systems—Part I: Power Control and Beamforming,” IEEE Transactions on Signal Processing, vol. 66, no. 10, pp. 2616–2630, 2018.
  13. H. Guo, Y.-C. Liang, J. Chen, and E. G. Larsson, “Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 3064–3076, 2020.
  14. C. Pan, H. Ren, K. Wang, W. Xu, M. Elkashlan, A. Nallanathan, and L. Hanzo, “Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces,” IEEE Transactions on Wireless Communications, vol. 19, no. 8, pp. 5218–5233, 2020.
  15. K. Zhi, C. Pan, H. Ren, and K. Wang, “Ergodic Rate Analysis of Reconfigurable Intelligent Surface-Aided Massive MIMO Systems With ZF Detectors,” IEEE Communications Letters, vol. 26, no. 2, pp. 264–268, 2022.
  16. M. Zeng, E. Bedeer, O. A. Dobre, P. Fortier, Q.-V. Pham, and W. Hao, “Energy-Efficient Resource Allocation for IRS-Assisted Multi-Antenna Uplink Systems,” IEEE Wireless Communications Letters, vol. 10, no. 6, pp. 1261–1265, 2021.
  17. W. de Souza and T. Abrão, “Energy Efficiency Maximization for Intelligent Surfaces Aided Massive MIMO With Zero Forcing,” IEEE Transactions on Green Communications and Networking, pp. 1–1, 2023.
  18. Z. Li, J. Zhang, J. Zhu, and L. Dai, “RIS Energy Efficiency Optimization with Practical Power Models,” in 2023 International Wireless Communications and Mobile Computing (IWCMC), 2023, pp. 1172–1177.
  19. Y. He, Y. Cai, H. Mao, and G. Yu, “RIS-Assisted Communication Radar Coexistence: Joint Beamforming Design and Analysis,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 7, pp. 2131–2145, July 2022.
  20. J. Kang, H. Wymeersch, C. Fischione, G. Seco-Granados, and S. Kim, “Optimized Switching Between Sensing and Communication for mmWave MU-MISO Systems,” in 2022 IEEE International Conference on Communications Workshops (ICC Workshops), 2022, pp. 498–503.
  21. J. Wu, S. Kim, and B. Shim, “Energy-Efficient Power Control and Beamforming for Reconfigurable Intelligent Surface-Aided Uplink IoT Networks,” IEEE Transactions on Wireless Communications, vol. 21, no. 12, pp. 10 162–10 176, 2022.
  22. T. Ji, M. Hua, C. Li, Y. Huang, and L. Yang, “Robust Max-Min Fairness Transmission Design for IRS-Aided Wireless Network Considering User Location Uncertainty,” IEEE Transactions on Communications, vol. 71, no. 8, pp. 4678–4693, 2023.
  23. H. Xie, J. Xu, and Y.-F. Liu, “Max-Min Fairness in IRS-Aided Multi-Cell MISO Systems With Joint Transmit and Reflective Beamforming,” IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 1379–1393, 2021.
  24. T. Jiang and W. Yu, “Interference Nulling Using Reconfigurable Intelligent Surface,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 5, pp. 1392–1406, 2022.
  25. J. V. Alegría and F. Rusek, “Channel Orthogonalization with Reconfigurable Surfaces,” in 2022 IEEE Globecom Workshops (GC Wkshps), 2022, pp. 37–42.
  26. M. Liu, H. Ren, C. Pan, B. Wang, Z. Yu, R. Weng, K. Zhi, and Y. He, “Joint Beamforming Design for Double Active RIS-assisted Radar-Communication Coexistence Systems,” 2024.
  27. S. Zargari, A. Hakimi, C. Tellambura, and S. Herath, “Multiuser MISO PS-SWIPT Systems: Active or Passive RIS?” IEEE Wireless Communications Letters, vol. 11, no. 9, pp. 1920–1924, 2022.
  28. Z. Zhang, L. Dai, X. Chen, C. Liu, F. Yang, R. Schober, and H. V. Poor, “Active RIS vs. Passive RIS: Which Will Prevail in 6G?” IEEE Transactions on Communications, vol. 71, no. 3, pp. 1707–1725, 2023.
  29. J. Ye, M. Rihan, P. Zhang, L. Huang, S. Buzzi, and Z. Chen, “Energy Efficiency Optimization in Active Reconfigurable Intelligent Surface-Aided Integrated Sensing and Communication Systems,” 2023.
  30. W. Lv, J. Bai, Q. Yan, and H. M. Wang, “RIS-Assisted Green Secure Communications: Active RIS or Passive RIS?” IEEE Wireless Communications Letters, vol. 12, no. 2, pp. 237–241, 2023.
  31. J. H. I. de Souza, J. C. M. Filho, A. Amiri, and T. Abrão, “QoS-Aware User Scheduling in Crowded XL-MIMO Systems Under Non-Stationary Multi-State LoS/NLoS Channels,” IEEE Transactions on Vehicular Technology, vol. 72, no. 6, pp. 7639–7652, 2023.
  32. H. L. dos Santos, J. C. Marinello, C. M. Panazio, and T. Abrão, “Machine learning-aided pilot and power allocation in multi-cellular massive MIMO networks,” Physical Communication, vol. 52, p. 101646, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1874490722000295
  33. J. C. M. Filho, G. Brante, R. D. Souza, and T. Abrão, “Exploring the Non-Overlapping Visibility Regions in XL-MIMO Random Access and Scheduling,” IEEE Transactions on Wireless Communications, vol. 21, no. 8, pp. 6597–6610, 2022.
  34. J. H. Inacio de Souza, J. C. Marinello Filho, T. Abrão, and C. Panazio, “Reconfigurable Intelligent Surfaces to Enable Energy-Efficient IoT Networks,” in 2022 Symposium on Internet of Things (SIoT), 2022, pp. 1–4.
  35. J. C. Marinello, T. Abrão, A. Amiri, E. de Carvalho, and P. Popovski, “Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems,” IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 13 305–13 318, 2020.
  36. L. M. Taniguchi, J. H. I. de Souza, D. W. M. Guerra, and T. Abrão, “Resource Efficiency and Pilot Decontamination in XL-MIMO Double-Scattering Correlated Channels,” Transactions on Emerging Telecommunications Technologies, vol. 32, no. 12, p. e4365, 2021. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.4365
  37. G. A. Ubiali, J. C. Marinello, and T. Abrao, “Energy-efficient Flexible and Fixed Antenna Selection Methods for XL-MIMO Systems,” AEU-International Journal of Electronics and Communications, vol. 130, p. 153568, 2021.
  38. J. C. M. Filho, T. Abrão, E. Hossain, and A. Mezghani, “Reconfigurable Intelligent Surfaces-Enabled Intra-Cell Pilot Reuse in Massive MIMO Systems,” IEEE Transactions on Wireless Communications, pp. 1–1, 2024.
  39. K. B. Rosa and T. Abrão, “Improving the Resource Efficiency in Massive MIMO-NOMA Systems,” Journal of Network and Systems Management, vol. 31, no. 4, p. 74, 2023.
  40. Q. Wu and R. Zhang, “Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming,” IEEE Transactions on Wireless Communications, vol. 18, no. 11, pp. 5394–5409, 2019.
  41. C. You, B. Zheng, and R. Zhang, “Fast Beam Training for IRS-Assisted Multiuser Communications,” IEEE Wireless Communications Letters, vol. 9, no. 11, pp. 1845–1849, 2020.
  42. L. Jiang, X. Li, M. Matthaiou, and S. Jin, “Joint User Scheduling and Phase Shift Design for RIS Assisted Multi-Cell MISO Systems,” IEEE Wireless Communications Letters, vol. 12, no. 3, pp. 431–435, 2023.
  43. E. Björnson, L. Sanguinetti, J. Hoydis, and M. Debbah, “Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?” IEEE Transactions on Wireless Communications, vol. 14, no. 6, pp. 3059–3075, 2015.
  44. J. Wang, W. Tang, J. C. Liang, L. Zhang, J. Y. Dai, X. Li, S. Jin, Q. Cheng, and T. J. Cui, “Reconfigurable Intelligent Surface: Power Consumption Modeling and Practical Measurement Validation,” 2024.
  45. X. Pei, H. Yin, L. Tan, L. Cao, Z. Li, K. Wang, K. Zhang, and E. Bjornson, “RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials,” IEEE Transactions on Communications, vol. 69, no. 12, p. 8627–8640, Dec. 2021. [Online]. Available: http://dx.doi.org/10.1109/TCOMM.2021.3116151
  46. R. K. Fotock, A. Zappone, and M. D. Renzo, “Energy Efficiency in RIS-Aided Wireless Networks: Active or Passive RIS?” 2023.
  47. W. Dinkelbach, “On Nonlinear Fractional Programming,” Manage. Sci., vol. 133, no. 7, pp. 492–498, 1967.
  48. Y. Jong, “An Efficient Global Optimization Algorithm for Nonlinear Sum-of-Ratios Problem,” Optimization Online, 2012.
  49. Z.-q. Luo, W.-k. Ma, A. M.-c. So, Y. Ye, and S. Zhang, “Semidefinite Relaxation of Quadratic Optimization Problems,” IEEE Signal Processing Magazine, vol. 27, no. 3, pp. 20–34, 2010.
  50. M. Grant and S. Boyd, “CVX: Matlab software for disciplined convex programming, version 2.1,” https://cvxr.com/cvx, Mar. 2014.
  51. Y. Xu, H. Xie, Q. Wu, C. Huang, and C. Yuen, “Robust Max-Min Energy Efficiency for RIS-Aided HetNets With Distortion Noises,” IEEE Transactions on Communications, vol. 70, no. 2, pp. 1457–1471, 2022.
  52. N. Sidiropoulos and Z.-Q. Luo, “A Semidefinite Relaxation Approach to MIMO Detection for High-Order QAM Constellations,” IEEE Signal Processing Letters, vol. 13, no. 9, pp. 525–528, 2006.

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