Skip to main content
Log in

Design optimization of CPW-fed microstrip patch antenna using constrained ABFO algorithm

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

This paper explores the potential of bio-inspired soft computational technique known as adaptive bacterial foraging optimization (ABFO) for the joint optimization of geometrical parameters of compact coplanar waveguide (CPW)-fed microstrip patch antenna with defected ground structure. The presented research work is divided into three phases. In the initial phase, the intended antenna is designed and analyzed using finite element-based electromagnetic simulator Ansoft HFSS 15.0. In the subsequent phase, the analytical equations of various design parameters are modeled using curve fitting technique in MATLAB and root mean square error-based fitness functions are derived for individual design parameters. Then, a joint cost function is formulated from individual fitness functions for evaluation in optimization algorithm. Adaptive BFO is an improvement in classical BFO algorithm that dynamically adjusts the run-length unit parameter to maintain the balance between exploration–exploitation trade-off. In the final phase, a variation in the adaptive BFO algorithm termed as ‘constrained ABFO’ is projected and designed to suit the bounded constraints imposed by anticipated antenna structure. The modified algorithm is efficaciously used for joint optimization of specific design parameters to transform ‘dual-band performance’ into ‘broadband performance’ for high-speed point-to-point wireless services. The performance of design optimization using constrained ABFO is compared with the original BFO, particle swarm optimization (PSO), hybrid bacterial foraging–particle swarm optimization (BF-PSO), invasive weed optimization (IWO) and artificial bee colony (ABC) techniques to scrutinize its adequacy.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Agarwal R, Saini G (2014) Optimized antenna for 5.2 GHz applications. Int J Comput Appl 98(13):38–41. doi:10.5120/17247-7586

    Article  Google Scholar 

  • Angelopoulos ES, Anastopoulos AZ, Kaklamani DI, Alexandridis AA (2006) Circular and elliptical CPW-fed slot and microstrip-fed antennas for ultrawideband applications. IEEE antennas and wireless propagation letters 5:294–297. doi:10.1109/LAWP.2006.878882

    Article  Google Scholar 

  • Arya Y, Kumar N (2016) Design and analysis of BFOA-optimized fuzzy PI / PID controller for AGC of multi-area traditional / restructured electrical power systems. Soft Comput. doi:10.1007/s00500-016-2202-2

    Article  Google Scholar 

  • Ather SN, Singhal PK (2014) Broadband CPW-Fed Rectangular Antenna with Parasitic Patches. In: International conference on computational intelligence and communication networks, pp 26–29. doi:10.1109/CICN.2014.17

  • Chen H (2003) Broadband CPW-fed square slot antennas with a widened tuning stub. IEEE Trans Antennas Propag 51(8):1982–1986. doi:10.1109/TAP.2003.814747

    Article  Google Scholar 

  • Chen H, Zhu Y, Hu K (2008) Self-Adaptation in Bacterial Foraging Optimization Algorithm. In: 3rd international conference on intelligent system and knowledge engineering, pp 1026–1031. Xiamen, China: IEEE. doi:10.1109/ISKE.2008.4731080

  • Chen H, Zhu Y, Hu K (2009) Cooperative bacterial foraging optimization. Discrete Dynamics in Nature and Society, Hindawi Publishing Corporation, (Article ID 815247), p 1–17. doi:10.1155/2009/815247

    Google Scholar 

  • Chen H, Zhu Y, Hu K (2011) Adaptive bacterial foraging optimization. Abstract and Applied Analysis, Hindawi Publishing Corporation, (Article ID 108269), 1–27. doi:10.1155/2011/108269

    MathSciNet  MATH  Google Scholar 

  • Chen Y, Lin W (2009) An improved bacterial foraging optimization. In: IEEE international conference on robotica and biomimetics, pp 2057–2062. Guillin, China: IEEE. doi:10.1109/ROBIO.2009.5420524

  • Dasgupta S, Das S, Biswas A, Abraham A (2010) Automatic circle detection on digital images with an adaptive bacterial Foraging algorithm. Soft Comput 14(11):1151–1164. doi:10.1007/s00500-009-0508-z

    Article  Google Scholar 

  • Deng W, Chen R, He B, Liu Y (2012) A novel two-stage hybrid swarm intelligence optimization algorithm and application. Soft Comput. doi:10.1007/s00500-012-0855-z

    Article  Google Scholar 

  • Deng W, Zhao H, Liu J, Yan X, Li Y, Ding Yin LC, (2014) An improved CACO algorithm based on adaptive method and multi-variant strategies. Soft Comput. doi:10.1007/s00500-014-1294-9

    Article  Google Scholar 

  • Deng W, Zhao H, Zou L (2016) A novel collaborative optimization algorithm in solving complex optimization problems. Soft Comput. doi:10.1007/s00500-016-2071-8

    Article  Google Scholar 

  • Fu Z, Sun X, Ji S, Xie G (2016) Towards efficient content-aware search over encrypted outsourced data in cloud. In: 35th annual international conference on computer communications, INFOCOM, 2016 pp 1–9. San Francisco, CA, USA: IEEE. doi:10.1109/INFOCOM.2016.7524606

  • Islam MT, Misran N, Take TC, Moniruzzaman M (2009) Optimization of microstrip patch antenna using particle swarm optimization with curve fitting. In: Electrical engineering and informatics Vol. 4, pp 4–7. Selangor, Malaysia: IEEE. doi:10.1109/ICEEI.2009.5254724

  • Islam MT, Moniruzzaman M, Misran N, Shakib MN (2009) Curve Fitting based Particle Swarm Optimization for UWB Patch Antenna. J Electromagn Waves Appl 23(17–18):2421–2432. doi:10.1163/156939309790416008

    Article  Google Scholar 

  • Kamakshi K, Singh A, Aneesh M, Ansari J A (2014) Novel Design of Microstrip Antenna with Improved Bandwidth. Int J Microwave Sci Technol, Hindawi Publishing Corporation, (Article ID 659592), 1–7. doi:10.1155/2014/659592

    Article  Google Scholar 

  • Karaboga D, Basturk B (2007) A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm. J Glob Optim. doi:10.1007/s10898-007-9149-x

    Article  MathSciNet  MATH  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle Swarm Optimization. In: IEEE international conference on neural networks, Vol. 4, pp 1942–1948. doi:10.1109/ICNN.1995.488968

  • Kong Y, Zhang M, Ye D (2017) A belief propagation-based method for task allocation in open and dynamic cloud environments. Knowl-Based Syst 115:123–132. doi:10.1016/j.knosys.2016.10.016

    Article  Google Scholar 

  • Korani WM (2009) Bacterial foraging oriented by particle swarm optimization strategy for PID tuning. In: IEEE international symposium on computational intelligence in robotics and automation, pp 1–6. Daejeon, South Korea. IEEE. doi:10.1109/CIRA.2009.5423165

  • Kumar G, Ray K, (2003) Broadband microstrip antennas. Artech House, antenna and propagation library. Norwood

  • Kumar R, Gupta N, Sharma V (2015) Curve fitting inspired particle swarm optimization of CPW-fed patch antenna with defected ground structure. I-Manager’s J Commun Eng Syst 4(3):30–37

    Article  Google Scholar 

  • Li Z, Zhang C-X, Wang G-M, Su W-R (2008) Designs on CPW-Fed Aperture Antenna for Ultra-Wideband Applications. Prog Electromagn Res C 2:1–6. doi:10.2528/PIERC08030501

    Article  Google Scholar 

  • Liang J, Guo L, Chiau CC, Chen X, Parini CG (2005) Study of CPW-fed circular disc monopole antenna for ultra wideband applications. IEE Proc–Microwaves, Antennas Propag 152(6):520–526. doi:10.1049/ip-map

    Article  Google Scholar 

  • Liu J, Ma D, Ma T, Zhang W (2016) Ecosystem particle swarm optimization. Soft Comput 21(7):1667–1691. doi:10.1007/s00500-016-2111-4

    Article  Google Scholar 

  • Liu W, Yeh F (2008) Compact dual-and wide-band CPW-fed slot antenna for wireless applications. Microwave Opti Technol Lett 50(3):574–575. doi:10.1002/mop

    Article  Google Scholar 

  • Liu, Y., Si, L.-M., Wei, M., Yan, P., Yang, P., Lu, H., Sun, H. (2012). Some recent developments of microstrip antenna. Int J Antennas Propag, Hindawi Publishing Corporation, (Article ID 428284), 1–10. doi:10.1155/2012/428284

    Google Scholar 

  • Majhi R, Panda G, Sahoo G, Dash PK, Das DP (2007) Stock market prediction of S&P 500 and DJIA using bacterial foraging optimization technique. In: Proceedings of the IEEE congress on evolutionary computation, IEEE Service Center, Singapore, pp 2569–2575. Singapore: IEEE. doi:10.1109/CEC.2007.4424794

  • Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Ecol Inform 1(4):355–366. doi:10.1016/j.ecoinf.2006.07.003

    Article  Google Scholar 

  • Mishra S (2005) A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation. IEEE Trans Evol Comput 9(1):61–73. doi:10.1109/TEVC.2004.840144

    Article  Google Scholar 

  • Mishra S, Bhende CN (2007) Bacterial foraging technique-based optimized active power filter for load compensation. IEEE Trans Power Deliv 22(1):457–465. doi:10.1109/TPWRD.2006.876651

    Article  Google Scholar 

  • Mu MA, Halgamuge SK, Alfonso W, Caicedo EF (2010) Simplifying the bacteria foraging optimization algorithm. In: IEEE congress on evolutionary computation (CEC), pp. 1–7. Barcelona, Spain: IEEE. doi:10.1109/CEC.2010.5586025

  • Niu B, Wang H (2011) Improved BFO with adaptive chemotaxis step for global optimization. In: Seventh international conference on computational intelligence and security, pp 76–80. Hainan, China: IEEE. doi:10.1109/CIS.2011.25

  • Passino KM (2002) Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst 22(3):52–67. doi:10.1109/MCS.2002.1004010

    Article  MathSciNet  Google Scholar 

  • Rani S, Singh AP (2014) A novel design of hybrid fractal antenna using BFO. J Intell Fuzzy Syst 27(3):1233–1241. doi:10.3233/IFS-131088

    Article  Google Scholar 

  • Shameena VA, Mridula S, Pradeep A, Jacob S, Lindo AO, Mohanan P (2012) A compact CPW fed slot antenna for ultra wide band applications. AEUE—Int J Electron Commun 66(3):189–194. doi:10.1016/j.aeue.2011.03.015

    Article  Google Scholar 

  • Shao Y, Chen H (2009) A novel cooperative bacterial foraging algorithm. In: IEEE fourth international conference on bio-inspired computing, pp 44–47. Beijing, China: IEEE. doi:10.1109/BICTA.2009.5338157

  • Shehata G, Mohanna M, Lotfy M (2015) Tri-band small monopole antenna based on SRR units. NRIAG J Astron Geophys 4(2):185–191. doi:10.1016/j.nrjag.2015.08.003

    Article  Google Scholar 

  • Singh A, Singh S (2016) Design and optimization of a modified Sierpinski fractal antenna for broadband applications. Appl Soft Comput 38:843–850. doi:10.1016/j.asoc.2015.10.013

    Article  Google Scholar 

  • Tiang J-J, Islam MT, Misran N, Singh MJ (2014) Design of a dual-band microstrip antenna using particle swarm optimization with curve fitting. Annals Telecommun 69(11–12):633–640. doi:10.1007/s12243-014-0421-z

    Article  Google Scholar 

  • Ulagammai M, Venkatesh P, Kannan PS, Prasad N (2007) Application of bacterial foraging technique trained artificial and wavelet neural networks in load forecasting. Neurocomputing 70(16–18):2659–2667. doi:10.1016/j.neucom.2006.05.020

    Article  Google Scholar 

  • Wen X, Shao L, Xue Y, Fang W (2015) A rapid learning algorithm for vehicle classification. Inf Sci 295:395–406. doi:10.1016/j.ins.2014.10.040

    Article  Google Scholar 

  • Weng LH, Guo YC, Shi XW, Chen XQ (2008) An overview on defected ground structure. Progress Electromagn Res 7:173–189. doi:10.2528/PIERB08031401

    Article  Google Scholar 

  • Xia Z, Wang X, Sun X, Wang B (2014) Steganalysis of least significant bit matching using multi-order differences. Secur Commun Netw 7(8):1283–1291. doi:10.1002/sec.864

    Article  Google Scholar 

  • Xue Y, Jiang J, Zhao B, Ma T (2017) A self-adaptive artificial bee colony algorithm based on global best for global optimization. Soft Comput. doi:10.1007/s00500-017-2547-1

    Article  Google Scholar 

  • Zavosh F, Aberle JT (1996) Improving the performance of microstrip-patch antennas. IEEE Antennas Propag Mag 38(4):7–12. doi:10.1109/74.537361

    Article  Google Scholar 

  • Zhao F, Jiang X, Wang J (2013) An activity improved bacterial foraging optimization and its performance analysis. J Comput Inf Syst 18(61064011):7397–7405. doi:10.12733/jcisP0202

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nancy Gupta.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, N., Saxena, J. & Bhatia, K.S. Design optimization of CPW-fed microstrip patch antenna using constrained ABFO algorithm. Soft Comput 22, 8301–8315 (2018). https://doi.org/10.1007/s00500-017-2775-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-017-2775-4

Keywords

Navigation