Papers
Topics
Authors
Recent
Search
2000 character limit reached

Physics-Inspired Discrete-Phase Optimization for 3D Beamforming with PIN-Diode Extra-Large Antenna Arrays

Published 30 Oct 2023 in cs.IT, cs.ET, and math.IT | (2311.16128v2)

Abstract: Large antenna arrays can steer narrow beams towards a target area, and thus improve the communications capacity of wireless channels and the fidelity of radio sensing. Hardware that is capable of continuously-variable phase shifts is expensive, presenting scaling challenges. PIN diodes that apply only discrete phase shifts are promising and cost-effective; however, unlike continuous phase shifters, finding the best phase configuration across elements is an NP-hard optimization problem. Thus, the complexity of optimization becomes a new bottleneck for large-antenna arrays. To address this challenge, this paper suggests a procedure for converting the optimization objective function from a ratio of quadratic functions to a sequence of more easily solvable quadratic unconstrained binary optimization (QUBO) sub-problems. This conversion is an exact equivalence, and the resulting QUBO forms are standard input formats for various physics-inspired optimization methods. We demonstrate that a simulated annealing approach is very effective for solving these sub-problems, and we give performance metrics for several large array types optimized by this technique. Through numerical experiments, we report 3D beamforming performance for extra-large arrays with up to 10,000 elements.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (33)
  1. Beamforming via large and dense antenna arrays above a clutter. IEEE Journal on Selected Areas in Communications, 31(2), 314–325, 2013.
  2. M. Aramon, et al. Physics-inspired optimization for quadratic unconstrained problems using a digital annealer. Frontiers in Physics, 7, 48, 2019.
  3. D. Bertsimas, J. Tsitsiklis. Simulated annealing. Statistical science, 8(1), 10–15, 1993.
  4. S. P. Boyd, L. Vandenberghe. Convex optimization. Cambridge University Press, 2004.
  5. W. C. Brown. The history of power transmission by radio waves. IEEE Transactions on microwave theory and techniques, 32(9), 1230–1242, 1984.
  6. Practical hybrid beamforming with finite-resolution phase shifters for reconfigurable intelligent surface based multi-user communications. IEEE Transactions on Vehicular Technology, 69(4), 4565–4570, 2020.
  7. Hybrid beamforming for reconfigurable intelligent surface based multi-user communications: Achievable rates with limited discrete phase shifts. IEEE Journal on Selected Areas in Communications, 38(8), 1809–1822, 2020.
  8. A quantum approximate optimization algorithm. arXiv preprint 1411.4028, 2014.
  9. L. C. Godara. Application of antenna arrays to mobile communications. ii. beam-forming and direction-of-arrival considerations. Proceedings of the IEEE, 85(8), 1195–1245, 1997.
  10. Dynamical beam manipulation based on 2-bit digitally-controlled coding metasurface. Scientific reports, 7(1), 42,302, 2017.
  11. T. Inagaki, et al. A coherent Ising machine for 2000-node optimization problems. Science, 354(6312), 603–606, 2016.
  12. E. Ising. Beitrag zur Theorie des Ferromagnetismus. Zeitschrift für Physik, 31(1), 253–258, 1925.
  13. Warm-started quantum sphere decoding via reverse annealing for massive iot connectivity. ACM MobiCom, 2022.
  14. Leveraging quantum annealing for large mimo processing in centralized radio access networks. ACM SIGCOMM, 241–255, 2019.
  15. Blind beamforming for intelligent reflecting surface in fading channels without csi. arXiv preprint arXiv:2305.18998, 2023.
  16. Quantum-assisted combinatorial optimization for reconfigurable intelligent surfaces in smart electromagnetic environments. IEEE Transactions on Antennas and Propagation, 2023.
  17. Grassmannian beamforming for multiple-input multiple-output wireless systems. IEEE transactions on information theory, 49(10), 2735–2747, 2003.
  18. A fully programmable 100-spin coherent ising machine with all-to-all connections. Science, 354(6312), 614–617, 2016.
  19. Equation of state calculations by fast computing machines. The journal of chemical physics, 21(6), 1087–1092, 1953.
  20. N. Metropolis, S. Ulam. The Monte Carlo method. Journal of the American statistical association, 44(247), 335–341, 1949.
  21. Maximum efficiency beam synthesis of radiating planar arrays for wireless power transmission. IEEE Transactions on Antennas and Propagation, 61(5), 2490–2499, 2013.
  22. Joint optimal power control and beamforming in wireless networks using antenna arrays. IEEE transactions on communications, 46(10), 1313–1324, 1998.
  23. C. Ross, et al. Engineering reflective metasurfaces with ising hamiltonian and quantum annealing. IEEE Transactions on Antennas and Propagation, 70(4), 2841–2854, 2021.
  24. F. Sohrabi, W. Yu. Hybrid digital and analog beamforming design for large-scale antenna arrays. IEEE Journal of Selected Topics in Signal Processing, 10(3), 501–513, 2016.
  25. Beamforming optimization for intelligent reflecting surfaces without csi. IEEE Wireless Communications Letters, 9(9), 1476–1480, 2020.
  26. A. Stockley, K. Briggs. Optimizing antenna beamforming with quantum computing. 2023 17th European Conference on Antennas and Propagation (EuCAP), 1–5. IEEE, 2023.
  27. H. L. Van Trees. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory. Wiley-Interscience, New York, 2002.
  28. H. L. Van Trees. Optimum array processing: Part IV of detection, estimation, and modulation theory. John Wiley & Sons, 2002.
  29. T. Wang, J. Roychowdhury. Oim: Oscillator-based ising machines for solving combinatorial optimisation problems. Unconventional Computation and Natural Computation: 18th International Conference, UCNC 2019, Tokyo, Japan, June 3–7, 2019, Proceedings 18, 232–256. Springer, 2019.
  30. Coherent ising machine based on degenerate optical parametric oscillators. Physical Review A, 88(6), 063,853, 2013.
  31. Q. Wu, R. Zhang. Beamforming optimization for wireless network aided by intelligent reflecting surface with discrete phase shifts. IEEE Transactions on Communications, 68(3), 1838–1851, 2019.
  32. Optimal discrete beamforming of RIS-aided wireless communications: an inner product maximization approach. arXiv preprint arXiv:2211.04167, 2022.
  33. Configuring intelligent reflecting surface with performance guarantees: Optimal beamforming. IEEE Journal of Selected Topics in Signal Processing, 16(5), 967–979, 2022.
Citations (1)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.