Photonic Crystal Microstrip Antenna Array Design Using an Improved Boolean Particle Swarm Optimization

  • Jianxia Liu
  • Hui Miao
  • Xiaohui YuanEmail author
  • Jianfang Shi
Conference paper
Part of the Studies in Distributed Intelligence book series (SDI)


Photonic crystals have been used in antenna arrays to suppress mutual coupling. The design of microstrip antenna based on periodic photonic crystal structure is non-trivial and requires optimization of multiple factors. In this paper, we propose a Chaotic Boolean PSO algorithm for the design of microstrip antenna array with 2D mushroom photonic crystals. In our method, two different chaos sequences are employed to diversify the initialization and particle updates, which improves the particle search coverage and accelerates the convergence. The return loss and mutual coupling are used to construct the fitness function for the proposed CB-PSO. Experiments are conducted using multi-modal functions to evaluate the robustness of the proposed method against the state-of-the-art optimization methods as well as antenna design. Our results demonstrate that the proposed CB-PSO consistently achieved the best performance among state-of-the-art methods. Compared to the second best results, the improvements in CB-PSO are at least two folds. In our experiments of optimizing photonic crystal layout, CB-PSO achieves an optimized antenna design with much-improved performance. The mutual coupling is reduced by 5 dB with respect to the antenna with a full array of photonic crystal component; that is an improvement of 29.4%. In addition, the number of photonic crystal component is reduced from 48 to 24, which shows an advantage in the manufacture of photonic crystal microstrip antenna array.


Antenna array Optimization Particle swarm Chaos 


  1. 1.
    E. Yablonovitch, Inhibited spontaneous emission in solid-state physics and electronics. Phys. Rev. Lett. 58, 2059–2062 (1987)CrossRefGoogle Scholar
  2. 2.
    J. Kennedy, W.M. Spears, Matching algorithms to problems: an experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator, in IEEE International Conference on Evolutionary Computation Proceedings, May 1998, pp. 78–83Google Scholar
  3. 3.
    J. McCall, Genetic algorithms for modelling and optimisation. J. Comput. Appl. Math. 184(1), 205–222 (2005)MathSciNetCrossRefGoogle Scholar
  4. 4.
    A.S.S. Ramna, Design of rectangular microstrip patch antenna using particle swarm optimization. Int. J. Adv. Res. Comput. Commun. Eng. 2, 2918–2920 (2013)Google Scholar
  5. 5.
    M. Dorigo, C. Blum, Ant colony optimization theory: a survey. Theoret. Comput. Sci. 344(2), 243–278 (2005)MathSciNetCrossRefGoogle Scholar
  6. 6.
    S. Al-Sharhan, Artificial immune systems - models, algorithms and applications. Int. J. Res. Rev. Appl. Sci. 3, 118–131 (2010)Google Scholar
  7. 7.
    A. Askarzadeh, A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm. Comput. Struct. 169, 1–12 (2016)CrossRefGoogle Scholar
  8. 8.
    D. Gorse, Binary particle swarm optimisation with improved scaling behaviour, in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, April 2013, pp. 24–26Google Scholar
  9. 9.
    S. Prakash, D.P. Vidyarthi, A hybrid immune genetic algorithm for scheduling in computational grid. Int. J. Bio-Inspired Comput. 6(6), 397–408 (2014)CrossRefGoogle Scholar
  10. 10.
    M.S. Kıran, E. Özceylan, M. Gündüz, T. Paksoy, A novel hybrid approach based on particle swarm optimization and ant colony algorithm to forecast energy demand of Turkey. Energy Convers. Manage. 53(1), 75–83 (2012)CrossRefGoogle Scholar
  11. 11.
    A. Marandi, F. Afshinmanesh, P.P.M. So, Design of a highly focused photonic crystal lens using Boolean particle swarm optimization, in IEEE Lasers and Electro-Optics Society Annual Meeting Conference Proceedings, October 2007, pp. 931–932Google Scholar
  12. 12.
    S. Gunasundari, S. Janakiraman, S. Meenambal, Velocity bounded Boolean particle swarm optimization for improved feature selection in liver and kidney disease diagnosis. Exp. Syst. Appl. 56, 28–47 (2016)CrossRefGoogle Scholar
  13. 13.
    F. Afshinmanesh, A. Marandi, M. Shahabadi, Design of a single-feed dual-band dual-polarized printed microstrip antenna using a Boolean particle swarm optimization. IEEE Trans. Antenn. Propag. 56(7), 1845–1852 (2008)CrossRefGoogle Scholar
  14. 14.
    L. Shen, Z. Ye, S. He, Design of two-dimensional photonic crystals with large absolute band gaps using a genetic algorithm. Phys. Rev. B 68, 1–5 (2003)Google Scholar
  15. 15.
    Paras, R.P.S. Gangwar, Design of compact and multiband antenna array using genetic algorithm optimization. 6, 221–227 (2011)Google Scholar
  16. 16.
    J.W. Jayasinghe, D.N. Uduwawala, A novel miniature multi-frequency broadband patch antenna for WLAN applications, in IEEE 8th International Conference on Industrial and Information Systems, December 2013, pp. 361–363Google Scholar
  17. 17.
    J.M.J.W. Jayasinghe, J. Anguera, D. Uduwawala, Genetic algorithm optimization of a high-directivity microstrip patch antenna having a rectangular profile. Radioengineering 22, 700–707 (2013)Google Scholar
  18. 18.
    M. Lamsalli, A. El Hamichi, M. Boussouis, N. Touhami, T. Elhamadi, Genetic algorithm optimization for microstrip patch antenna miniaturization. Progr. Electromagn. Res. Lett. 60, 113–120 (2016)CrossRefGoogle Scholar
  19. 19.
    P. Civicioglu, Circular antenna array design by using evolutionary search algorithms. Progr. Electromagn. Res. B 54, 265–284 (2013)CrossRefGoogle Scholar
  20. 20.
    J. Nanbo, R.-S. Yahya, Particle swarm optimization for antenna designs in engineering electromagnetics. J. Artif. Evol. Appl. 2008, 10 pp. (2008)Google Scholar
  21. 21.
    S. Rani, A.P. Singh, On the design and optimisation of new fractal antenna using PSO. Int. J. Electron. 100(10), 1383–1397 (2013)CrossRefGoogle Scholar
  22. 22.
    C. Rai, Optimization of h-shape micro strip patch antenna using PSO and curve fitting. Int. J. Res. Appl. Sci. Eng. Technol. 993–996 (2017).
  23. 23.
    N.Z. Wang, X.B. Wang, J.D. Xu, Design of a novel compact broadband patch antenna using binary PSO. Microw. Opt. Technol. Lett. 54(2), 434–438 (2012)MathSciNetCrossRefGoogle Scholar
  24. 24.
    D. Estrada-Wiese, E.A. del Rio-Chanona, J.A. del Rio, Stochastic optimization of broadband reflecting photonic structures. Sci. Rep. 8(1), 1193 (2018)Google Scholar
  25. 25.
    F. Afshinmanesh, Design of photonic crystals and binary supergratings using Boolean particle swarm optimization. PhD thesis, University of Tehran, 2006Google Scholar
  26. 26.
    S. Bhaskaran, R. Varma, J. Ghosh, A comparative study of GA, PSO and APSO: feed point optimization of a patch antenna. Int. J. Sci. Res. Publ. 3, 1–5 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Jianxia Liu
    • 1
  • Hui Miao
    • 1
  • Xiaohui Yuan
    • 2
    Email author
  • Jianfang Shi
    • 1
  1. 1.College of Information and ComputerTaiyuan University of TechnologyTaiyuanChina
  2. 2.Department of Computer Science and EngineeringUniversity of North TexasDentonUSA

Personalised recommendations