DESIGN AND SYNTHESIS OF AN ULTRA WIDE BAND FSS FOR MM-WAVE APPLICATION VIA GENERAL REGRESSION NEURAL NETWORK AND MULTIOBJECTIVE BAT ALGORITHM

Authors

  • Miércio C. A. Neto
  • Jasmine P. L. Araújo
  • Raimundo J. S. Mota
  • Fabrício J. B. Barros
  • Flávio H. C. S. Ferreira
  • Gervásio P. S. Cavalcante
  • Bruno S. L. Castro

DOI:

https://doi.org/10.1590/2179-10742019v18i41729

Keywords:

hybrid technique, general regression neural network (GRNN), multiobjective bat algorithm (MOBA), Frequency Selective Surfaces (FSS)

Abstract

In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient’s scattering matrix (dB), were obtained at the cutoff threshold at -10dB, to control the bandwidth of the device.

References

[1] X. S. Yang, S. Koziel, "Computational Optimization and Applications in Engineering and Industry," Springer, 2011.
[2] M. C. Alcantara Neto, J. P. L. Araújo, F. J. B. Barros, A. N. Silva, G. P. S. Cavalcante, and A. G. D’Assunção, "Bioinspired
multiobjective synthesis of x-band fss via general regression neural network and cuckoo search algorithm," Microwave and
Optical Technology Letters, vol. 57, no. 10, pp. 2400-24005, October 2015.
[3] M. C. Alcântara Neto, F. J. B. Barros, J. P. L. Araújo, H. S. Gomes, G. P. S. Cavalcante, A. G. D’Assunção, "A
Metaheuristic Hybrid Optimization Technique for Designing Broadband FSS," SBMO/IEEE MTT-S International Microwave
and Optoelectronics Conference (IMOC), pp. 1 -5, November 2015.
[4] X. S. Yang, "Bat Algorithm for Multiobjective Optimization," Int. J. Bio-Inspired Computation, vol. 3, no. 5, pp. 267-274,
September 2011.
[5] R. Saidi, M. Titaouine, A. Djouimaa, T. R. Sousa, A. Gomes Neto, H. Baudrand, "Characterization of Switchable
Rectangular Ring FSS with Non Coupled Parallel Metallic Strips for Multi Band and Dual Polarized Applications Using WCIP
Method," Journal of Microwaves, Optoelectronics and Electromagnetic Applications, vol. 17, no. 1, pp. 102-120, March 2018.
[6] K. Bencherif, M. Titaouine, R. Saidi, A. Djouimaa, I. Adoui, T. R. Sousa, A. Gomes Neto, H. Baudrand, "Multiband FSS
Analysis and Synthesis Based on Parallel Non Coupled Metallic Strips Using WCIP Method," Journal of Microwaves,
Optoelectronics and Electromagnetic Applications, vol. 17, no. 4, pp. 433-456, December 2018.
[7] I. Adoui, M. Titaouine1, H. Choutri, R. Saidi, T. R. Sousa, A. Gomes Neto, H. Baudrand, "WCIP Method Applied To
Modeling an L-Notched Rectangular Metallic Ring FSS for Multiband Applications and its Equivalent Structure," Journal of
Microwaves, Optoelectronics and Electromagnetic Applications, vol. 17, no. 4, pp. 457-476, December 2018.
[8] W. Y. Yong, S. K. A. Rahim, M. Himdi, F. C. Seman, D. L. Suong, M. R. Ramli, and H. A. Elmobarak, "Flexible
Convoluted Ring Shaped FSS for X-Band Screening Application," IEEE Access, vol. 6, pp. 11657-11665, March 2018.
[9] Y. Ma, W. Wu , Y. Yuan , W. Yuan, and N. Yuan, "A High-Selective Frequency Selective Surface With Hybrid Unit
Cells," IEEE Access, vol. 6, pp. 75259-75267, October 2018.
[10] C. C. Chen, “Transmission through a conducting screen perforated periodically with apertures,” IEEE Trans. Microwave
Theory Tech., vol. MTT-18, pp. 627-632,1970.
[11] L. Ragan, A. Hassibi, T. S. Rappaport, C. L. Christianson, “Novel on-chip antenna structures and frequency selective
surface (FSS) approaches for millimeter wave devices,” Vehicular Technology Conference (VTC), 66th IEEE Conference, pp.
2051-2055, 2007.
[12] "Amendment of Parts 2 15 and 97 of the Commission's Rules to Permit Use of Radio Frequencies Above 40 GHz for
New Radio Applications", FCC 95–499 ET Docket no. 94-124 RM-8308, Dec. 1995.
[13] J. P. L. Araújo, J. C. Rodrigues, S. G. C. Fraiha, H. Gomes, G. P. S. Cavalcante, C. e R. L. Francês, “A WLAN planning
proposal through computational intelligence and genetic algorithms hybrid approach,” The International Conference on
Mobile Technology, Applications & Systems (Mobility Conference), pp. 10-12, Ilan, Taiwan, 2008.
[14] D. F. Specht, “A general regression neural network,” IEEE Transactions on Neural Networks, vol. 2, no. 6, 1991.
[15] W. C. Araújo, H. W. C. Lins, A. G. D’Assunção Jr., J. L. G. Medeiros and A. G. D’Assunção, “A bioinspired hybrid
optimization algorithm for designing broadband frequency selective surfaces,” Microwave and Optical Technology Letters,
vol. 56, no. 2, 2014.
[16] H. W. C. Lins, E. L. F. Barreto e A. G. D’Assunção, “Enhanced wideband performance of coupled frequency selective
surfaces using metaheuristics,” Microwave and Optical Technology Letters, vol. 55, no. 4, 2013.
[17] P. H. F. Silva, R. M. S. Cruz e A. G. D’Assunção, “Blending PSO and ANN for optimal design of FSS filters with Koch
Island patch elements,” IEEE Transactions on Magnetics, vol. 46, no. 8, 2010.
[18] A. Hoorfar, “Evolutionary programming in electromagnetic optimization: a review,” IEEE Trans. Antenna and Propag.,
pp. 523–537, 2007.
[19] G. R. MacCartney, Jr. and T. S. Rappaport, “Study on 3GPP Rural Macrocell Path Loss Models for Millimeter Wave
Wireless Communications,” in 2017 IEEE International Conference on Communications (ICC), Paris, France, May 2017, pp.
1-7.
[20] S. Sun, G. R. MacCartney Jr., and T. S. Rappaport, "A Novel Millimeter-Wave Channel Simulator and Applications for
5G Wireless Communications," 2017 IEEE International Conference on Communications (ICC), May 2017.
[21] S. Sun, H. Yan, G. R. MacCartney Jr., and T. S. Rappaport, "Millimeter Wave Small-Scale Spatial Statistics in an Urban
Microcell Scenario," 2017 IEEE International Conference on Communications (ICC), May 2017.
[22] S. Sun and T. S. Rappaport, "Millimeter Wave MIMO Channel Estimation Based on Adaptive Compressed Sensing,”
2017 IEEE International Conference on Communications Workshop (ICCW), May 2017.
[23] J. Ryan, G. R. MacCartney, Jr., and T. S. Rappaport, “Indoor Office Wideband Penetration Loss Measurements at 73
GHz,” in 2017 IEEE International Conference on Communications Workshop (ICCW), Paris, France, May 2017, pp. 1-6.
[24] G. R. MacCartney, Jr., H. Yan, S. Sun, and T. S. Rappaport, “A Flexible Wideband Millimeter-Wave Channel Sounder
with Local Area and NLOS to LOS Transition Measurements,” in 2017 IEEE International Conference on Communications
(ICC), Paris, France, May 2017, pp. 1-7.
[25] X. S. Yang, “A new metaheuristic bat-inspired algorithm,” Nature Inspired Cooperative Strategies for Optimization,
Springer Berlin, vol. 284, pp. 65-74, 2010.
[26] V. Pareto, Cours d'Economie Politique, Rouge, 1886.
[27] E. A. Nadaraya, “On estimating regression,” Theory of Probab. Applicat., vol. 9, pp. 141–142, 1964.
[28] G. S. Watson, “Smooth regression analysis,” Sankhya Series A, vol. 26, pp. 359–372, 1964.
[29] L. P. Devroye and L. Györfi, “Nonparametric density estimation: the L_1 view,” U.K.: Wiley, 1983.
[30] R. L. Eubank, “Spline smoothing and nonparametric regression,” New York and Basel: Marcel Dekker, 1988.
[31] L. Rutkowski, “Sequential estimates of probability densities by orthogonal series and their application in pattern
classification,” IEEE Trans. Syst., Man, Cybern., vol. SMC-10, no. 12, pp. 918–920, 1980.
[32] L. Rutkowski, “Sequential estimates of a regression function by orthogonal series with applications in discrimination,” in
Lectures Notes in Statistics, vol. 8. New York, pp. 236–244, 1981.
[33] D. E. Rumelhart, G. E. Hinton, and R.J. Williams, “Learning internal representations by error Propagation,” D. E.
Rumelhart, J. L. McClelland and The PDP Research Group, Parallel distributed processing: Explorations in the microstructure
of cognition, Foundations, MIT Press, vol. 1, pp. 318–362, Cambridge, MA, 1986.

Downloads

Published

2020-04-10

How to Cite

Miércio C. A. Neto, Jasmine P. L. Araújo, Raimundo J. S. Mota, Fabrício J. B. Barros, Flávio H. C. S. Ferreira, Gervásio P. S. Cavalcante, & Bruno S. L. Castro. (2020). DESIGN AND SYNTHESIS OF AN ULTRA WIDE BAND FSS FOR MM-WAVE APPLICATION VIA GENERAL REGRESSION NEURAL NETWORK AND MULTIOBJECTIVE BAT ALGORITHM. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 18(4), 530-544. https://doi.org/10.1590/2179-10742019v18i41729

Issue

Section

Regular Papers

Most read articles by the same author(s)