Skip to main content
SpringerLink
Log in

Performance Investigations of S-shaped RMSA Using Multilayer Perceptron Neural Network for S-Band Applications

  • Published:
Radioelectronics and Communications Systems Aims and scope Submit manuscript

Abstract

In this article an S-shaped rectangular microstrip patch antenna (RMSA) is investigated for S-band applications using artificial neural network (ANN). The authors have done the parametric study of different radiating structures to obtain S-shaped RMSA. The size of inserted notches on the radiating patch for achieving wideband operation is computed through multilayer perceptron artificial neural network (MLP-ANN) over a desired range of its performance effecting parameters such as frequency, gain, directivity, antenna efficiency, and radiation efficiency. MLP-ANN model is trained and tested with seven different algorithms. The research found that Levenberg-Marquardt (LM) training algorithm takes less computational time with better accuracy for computation of notches size on radiating patch over a priory defined performance parameters. To verify the work, a prototype of S-shaped RMSA is physically fabricated on foam substrate and tested experimentally. The experimental results are in good agreement with the simulated results that are produced with ANN.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. I. J. Bahl, P. Bhartia, Microstrip Antennas (Artech House, Dedham, Mass, 1980).

    Google Scholar 

  2. T. U. Huynh, K.-F. Lee, “Single-layer single-patch wideband microstrip antenna,” Electron. Lett. 31, No. 16, 1310 (June 1995). DOI: https://doi.org/10.1049/el:19950950.

    Article  Google Scholar 

  3. G. Rafi, L. Shafai, “Broadband microstrip patch antenna with V-slot,” IEE Proc. Microwave Antenna Propag. 151, No. 5, 435 (Nov. 2004). DOI: https://doi.org/10.1049/ip-map:20040846.

    Article  Google Scholar 

  4. A. A. L. Neyestanak, F. H. Kashani, K. Barkeshli, “W-shaped enhanced-bandwidth patch antenna for wireless communication,” Wireless Pers. Commun. 43, No. 4, 1257 (Dec. 2007). DOI: https://doi.org/10.1007/s11277-007-9299-7.

    Article  Google Scholar 

  5. V. K. Pandey, B. R. Vishwakarma, “Analysis of an E-shaped patch antenna,” Microwave Opt. Technol. Lett. 49, No. 1, 4 (Jan. 2007). DOI: https://doi.org/10.1002/mop.22024.

    Article  Google Scholar 

  6. J. A. Ansari, S. K. Dubey, A. Mishra, “Analysis of half E-shaped patch for wideband application,” Microwave Opt. Technol. Lett. 51, No. 6, 1576 (June 2009). DOI: https://doi.org/10.1002/mop.24367.

    Article  Google Scholar 

  7. A. Singh, M. Aneesh, K. Kamakshi, J. A. Ansari, “Circuit theory analysis of aperture coupled patch antenna for wireless communication,” Radioelectron. Commun. Syst. 61, No. 4, 168 (2018). DOI: https://doi.org/10.3103/S0735272718040040.

    Article  Google Scholar 

  8. P. Kaur, S. K. Aggarwal, A. De, “Performance enhancement of rectangular microstrip patch antenna using double H shaped metamaterial,” Radioelectron. Commun. Syst. 59, No. 11, 496 (2016). DOI: https://doi.org/10.3103/S0735272716110030.

    Article  Google Scholar 

  9. A. A. Deshmukh, G. Kumar, “Compact broadband S-shaped microstrip antennas,” Electron. Lett. 42, No. 5, 260 (Mar. 2006). DOI: https://doi.org/10.1049/el:20064194.

    Article  Google Scholar 

  10. R. K. Mishra, A. Patnaik, “Neural network-based CAD model for the design of square-patch antennas,” IEEE Trans. Antennas Propag. 46, No. 12, 1890 (Dec. 1998). DOI: https://doi.org/10.1109/8.743842.

    Article  Google Scholar 

  11. K. Guney, S. Sagiroglu, M. Erler, “Generalized neural method to determine resonant frequencies of various microstrip antennas,” Int. J. RF Microwave Computer-Aided Engineering 12, No. 1, 131 (2002). DOI: https://doi.org/10.1002/mmce.10006.abs.

    Article  Google Scholar 

  12. S. S. Pattnaik, D. C. Panda, S. Devi, “Radiation resistance of coax-feed rectangular microstrip patch antenna with the use of artificial neural networks,” Microwave Opt. Technol. Lett. 34, No. 1, 51 (July 2002). DOI: https://doi.org/10.1002/mop.10370.

    Article  Google Scholar 

  13. S. S. Pattnaik, D. C. Panda, S. Devi, “Input impedance of rectangular microstrip patch antenna using artificial neural networks,” Microwave Opt. Technol. Lett. 32, No. 5, 381 (Mar. 2002). DOI: https://doi.org/10.1002/mop.10184.

    Article  Google Scholar 

  14. D. K. Neog, S. S. Pattnaik, D. C. Panda, S. Devi, B. Khuntia, M. Dutta, “Design of a wideband microstrip antenna and the use of artificial neural networks in parameter calculation,” IEEE Antennas Propag. Mag. 47, No. 3, 60 (2005). DOI: https://doi.org/10.1109/map.2005.1532541.

    Article  Google Scholar 

  15. K. Saikavara, “Artificial neural network based design of a three-layered microstrip circular ring antenna with specified multi-frequency operation,” Neural Comput. Appl. 18, No. 1, 57 (Jan. 2009). DOI: https://doi.org/10.1007/s00521-007-0153-3.

    Article  Google Scholar 

  16. G. Washington, “Aperture antenna shape prediction by feedforward neural networks,” IEEE Trans. Antennas Propag. 45, No. 4, 683 (Apr. 1997). DOI: https://doi.org/10.1109/8.564094.

    Article  Google Scholar 

  17. A. Akdagli, A. Toktas, A. Kayabasi, I. Develi, “An application of artificial neural network to compute the resonant frequency of E-shaped compact microstrip antennas,” J. Electrical Engineering 64, No. 5, 317 (2013). DOI: https://doi.org/10.2478/jee-2013-0046.

    Article  Google Scholar 

  18. Ali Akdagli, Mustafa Berkan Biçer, Seda Ermiş, “A novel expression for resonant length obtained by using artificial bee colony algorithm in calculating resonant frequency of C-shaped compact microstrip antennas,” Turk. J. Elec. Eng. & Comp. Sci. 19, No. 4, 597 (2011). DOI: https://doi.org/10.3906/elk-1006-466.

    Google Scholar 

  19. M. Aneesh, J. A. Ansari, A. Singh, Kamakshi, S. S. Sayeed, “Analysis of microstrip line feed slot loaded patch antenna using artificial neural network,” PIER B 58, 35 (2014). DOI: https://doi.org/10.2528/pierb13111105.

    Article  Google Scholar 

  20. Nurhan Türker, Filiz Güneş, Tülay Yildirim, “Artificial neural design of microstrip antennas,” Turk. J. Elec. Eng. & Comp. Sci. 14, No. 3, 445 (2006).

    Google Scholar 

  21. Q.-J. Zhang, K. C. Gupta, V. K. Devabhaktuni, “Artificial neural networks for RF and microwave design -from theory to practice,” IEEE Trans. Microwave Theory Tech. 51, No. 4, 1339 (Apr. 2003). DOI: https://doi.org/10.1109/tmtt.2003.809179.

    Article  Google Scholar 

  22. R. K. Mishra, A. Patnaik, “Designing rectangular patch antenna using the neurospectral method,” IEEE Trans. Antennas Propag. 51, No. 8, 1914 (Aug. 2003). DOI: https://doi.org/10.1109/tap.2003.814748.

    Article  Google Scholar 

  23. P. M. Watson, K. C. Gupta, R. L. Mahajan, “Development of knowledge based artificial neural network models for microwave components,” IEEE MTT-S Int. Microwave Symp. Dig. 1, 9 (1998). DOI: https://doi.org/10.1109/mwsym.1998.689312.

    Google Scholar 

  24. K. Guney, N. Sarikaya, “A hybrid method based on combining artificial neural network and fuzzy inference system for simultaneous computation of resonant frequencies of rectangular, circular, and triangular microstrip antennas,” IEEE Trans. Antennas Propag. 55, No. 3, 659 (Mar. 2007). DOI: https://doi.org/10.1109/tap.2007.891566.

    Article  Google Scholar 

  25. Z. Wang, S. Fang, Q. Wang, H. Liu, “An ANN-based synthesis model for the single-feed circularly-polarized square microstrip antenna with truncated corners,” IEEE Trans. Antennas Propag. 60, No. 12, 5989 (Dec. 2012). DOI: https://doi.org/10.1109/tap.2012.2214195.

    Article  Google Scholar 

  26. T. Khan, A. De, M. Uddin, “Prediction of slot-size and inserted air-gap for improving the performance of rectangular microstrip antennas using artificial neural networks,” IEEE Antennas Wireless Propag. Lett. 12, 1367 (Oct. 2013). DOI: https://doi.org/10.1109/lawp.2013.2285381.

    Article  Google Scholar 

  27. Zeland software, Inc. IE3D simulation software, version 14.05 Zeland software, CA (2008).

  28. S. Haykin, Neural Networks: A Comprehensive Foundation, 3rd ed. (Prentice-Hall, 2007).

  29. D. J. Higham, N. J. Higham, Matlab ANN toolbox MATLAB Guide (SIAM, Philadelphia, 2005).

    MATH  Google Scholar 

  30. J. S. Sivia, A. P. S. Pharwaha, T. S. Kamal, “Analysis and design of circular fractal antenna using artificial neural networks,” PIER B 56, 251 (2013). DOI: https://doi.org/10.2528/pierb13091611.

    Article  Google Scholar 

  31. D. Karaboga, K. Guney, S. Sagiroglu, M. Erler, “Neural computation of resonance frequency of electrically thin and thick rectangular microstrip antennas,” IEE Proc. Microwaves Antennas Propag. 146, No. 2, 155 (Apr. 1999). DOI: https://doi.org/10.1049/ip-map:19990136.

    Article  Google Scholar 

  32. M. T. Hagan, M. B. Menhaj, “Training feedforward networks with the Marquardt algorithm,” IEEE Trans. Neural Netw. 5, No. 6, 989 (Nov. 1994). DOI: https://doi.org/10.1109/72.329697.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Veer Bahadur Singh Purvanchal University, Jaunpur, India

    Mohammad Aneesh

  2. NMAM Institute of Technology, Nitte, Karkala, India

    Ashish Singh

  3. Institute of Management Studies, Ghaziabad, India

    Kumari Kamakshi

  4. University of Allahabad, Allahabad, India

    Jamshed Aslam Ansari

Authors
  1. Mohammad Aneesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ashish Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kumari Kamakshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jamshed Aslam Ansari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Aneesh.

Additional information

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional Information

The initial version of this paper in Russian is published in the journal “Izvestiya Vysshikh Uchebnykh Zavedenii. Radioelektronika,” ISSN 2307-6011 (Online), ISSN 0021-3470 (Print) on the link https://doi.org/radio.kpi.ua/article/view/S002134701908003X with DOI: https://doi.org/10.20535/S002134701908003X.

Russian Text © The Author(s), 2019, published in Izvestiya Vysshikh Uchebnykh Zavedenii, Radioelektronika, 2019, Vol. 62, No. 8, pp. 479–488.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aneesh, M., Singh, A., Kamakshi, K. et al. Performance Investigations of S-shaped RMSA Using Multilayer Perceptron Neural Network for S-Band Applications. Radioelectron.Commun.Syst. 62, 400–408 (2019). https://doi.org/10.3103/S073527271908003X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S073527271908003X

Search

Navigation