Multi-band Antenna Design Optimization Using Nature-inspired Evolutionary Algorithm For 5G Wireless Communication
Main Article Content
Abstract
Automation and telecommunication systems are increasingly improving and becoming more easily integrated thanks to wireless communication technology, in which the essential component is the antenna. Designing and optimizing antenna structures still takes a lot of time, especially for complex structures with multiple operating frequency bands or complex material layers. With modern computing power, the speed of computation is increasingly efficient, and combining automated computation for optimization and design is entirely feasible. Many research groups around the world have implemented automated antenna design through optimization algorithms, genetic algorithms, swarm algorithms, collectively referred to as evolutionary algorithms. These algorithms simplify the antenna design process, making it more automated and optimized. In this paper, the Improved Black Hole algorithm is proposed and used to optimize the design of a CPW-Fed slot microstrip antenna.
Keywords
Nature-inspired optimization, Black Hole algorithm, Antenna design, 5G communication, Multi-band antenna, Sub-6 GHz band
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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antenna arrays using a hybrid MoM/GA algorithm,
IEEE Antennas and Wireless Propagation Letters, vol.
1, pp. 1232-1235, October 2011.
https://doi.org/10.1109/LAWP.2011.2174189
[2] D. Zhou, R. A. Abd-Alhameed, C. H. See M. S. BinMelha, etc., New antenna designs for wideband
harmonic-suppression using adaptive surface meshing
and genetic algorithms”, IET Microwaves, Antennas &
Propagation, 2011, pp.1054 - 1061.
https://doi.org/10.1049/iet-map.2010.0218
[3] J. Robinson, and Y. Rahmat-Samii, Particle swarm
optimization in electromagnetics, IEEE Transactions on
Antennas and Propagation, vol.52, pp. 397-407, 2004.
https://doi.org/10.1109/TAP.2004.823969
[4] H. J. Mohammed, A. S. Abdullah, R. S. Ali, R. A. AbdAlhameed, Y. I. Abdulraheem, & J. M. Noras, "The
design of a uniplanar printed triple band rejected uwb
antenna using particle swarm optimization and the
firefly algorithm", IET MAP, vol. 11, issue 1, 2016, pp.
31-37.
https://doi.org/10.1049/iet-map.2014.0736
[5] J. M. Johnson and Y. R. Samii, Genetic algorithms in
engineering electromagnetics, IEEE Antennas
Propagation Magazine, vol. 39, no. 4, pp. 7-21, 1997.
https://doi.org/10.1109/74.632992
[6] M. A. Panduro and C. A. Brizuela, A comparative
analysis of the performance of GA, PSO and DE for
circular antenna arrays, in Proc. Antennas Propag. Soc.
Int. Symp., 2009, pp. 1-4
https://doi.org/10.1109/APS.2009.5171514
[7] A. Hatamlou, Black hole: A new heuristic optimization
approach for data clustering, Inf. Sci. 222 pp.175-184,
2013
https://doi.org/10.1016/j.ins.2012.08.023
[8] K. Lenin, B. R. Reddy, and M. S. Kalavathi, Black hole
algorithm for solving optimal reactive power dispatch
problem, International Journal of Research in
Management, Science and Technology, vol. 2, pp.
2321-3264, 2014.
https://doi.org/10.12720/ijeee.2.4.321-326
[9] N. Ghaffarzadeh and S. Heydari, Optimal coordination
of digital overcurrent relays using black hole algorithm,
TI Journals of World Applied Programming, vol. 5, pp.
50-55, 2015.
[10] E. Pashaei, N. Aydin, Binary black hole algorithm for
feature selection and classification on biological data.
Applied Soft Computing, vol. 56, pp. 94-106, 2017.
https://doi.org/10.1016/j.asoc.2017.03.002
[11] W. Xie, J. S. Wang, C. Xing, S. S. Guo, M. W. Guo,
L. F. Zhu, Extreme learning machine soft-sensor model
with different activation functions on grinding process
optimized by improved black hole algorithm. IEEE
Access 8, pp. 25084- 25110, 2020.
https://doi.org/10.1109/ACCESS.2020.2970429
[12] Yaghoobi, Saber, Mojallali, Hamed, Modified black
hole algorithm with genetic operators, International
Journal of Computational Intelligence Systems, vol 9
(4), pp. 652-665, 2016.
https://doi.org/10.1080/18756891.2016.1204114
[13] H. Deeb, A. Sarangi, D. Mishra, S. K. Kumar Sarangi,
Improved black hole optimization algorithm for data
clustering, J King Saud Univ-Comput Inf Sci, vol. 34,
pp. 5020-5029, 2022.
https://doi.org/10.1016/j.jksuci.2020.12.013
[14] J. Chen, Dual-frequency slot antennas fed by
capacitively coplanar waveguide, Microw. Opt.
Technol. Lett., 32 (2002), pp. 452-453
https://doi.org/10.1002/mop.10207
[15] C. P. Wen, Coplanar waveguide: a surface strip
transmission line suitable for nonreciprocal
gyromagnetic device applications, IEEE Trans.
Microw. Theor. Tech., 17 (1969), pp. 1087-1090
https://doi.org/10.1109/TMTT.1969.1127105
[16] W. Hu, Q. Long, S. Gao, Le-Hu Wen, L. Qi, H. Xu,
X. Liu, W. Wang, Dual-band eight-element MIMO
array using multi-slot decoupling technique for 5G
terminals, IEEE Access, 7 (2019), pp. 153911-153920
https://doi.org/10.1109/ACCESS.2019.2948639
[17] A. T. Abed, A. M. Jawad, Compact size MIMO amer
fractal slot antenna for 3G, LTE (4G), WLAN,
WiMAX, ISM and 5G communications, IEEE Access,
7 (2019), pp. 125542-125551.
https://doi.org/10.1109/ACCESS.2019.2938802
[18] Krishnamoorthy, R., Desai, A., Patel, R. et al. 4
Element compact triple band MIMO antenna for sub6 GHz 5G wireless applications. Wireless Netw 27,
3747-3759 (2021).
https://doi.org/10.1007/s11276-021-02734-8
[19] Kulkarni, J., Sim, CYD., Desai, A. et al. A Compact
Four Port Ground-Coupled CPWG-Fed MIMO
Antenna for Wireless Applications. Arab J Sci Eng 47,
14087-14103 (2022).
https://doi.org/10.1007/s13369-022-06620-z
[20] Yang, L., Tahseen, H. U., Hussain, S. S. I. et al. Tripleband dual-polarized dipole antenna for 5G Sub-6 GHz
Communications. Wireless Pers Commun 124, 2109-
2120 (2022).
https://doi.org/10.1007/s11277-021-09447-3