Comparative study of Cuckoo search optimization and differential evolution algorithm for design of microstrip fed microstrip patch antenna

Manna, Suvrajit; Sharma, Udit; Gangopadhyaya, Malay; Mukherjee, Pinaki; Gupta, Bhaskar; Ghose, Rahul; Saha, Ayoshna

doi:10.1109/iemcon.2015.7344439

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Some rather newly developed bio-inspired algorithms such as bacterial foraging [81], biogeography-based optimization [82], artificial bee colony [83], cuckoo search [84] and firefly algorithm [85] have also been applied on MPAs to obtain significant performance improvements.…”

Section: Other Bio-inspired Algorithmsmentioning

confidence: 99%

Bio-Inspired Algorithms Applied on Microstrip Patch Antennas: a Review

Saraereh

Saraira

Alsafasfeh³

et al. 2016

IRECAP

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Design of small broadband, multiband and high-directivity microstrip patch antennas (MPAs) is a challenging task for the antenna research community since the classical MPAs do not perform well enough to be used in the real world applications. In this sense, various performance improvement techniques such as stacked patches, air gaps, compact meandering geometries, fractal-shapes and shorting pins are applied to design improved MPAs. Use of bio-inspired algorithms along with these techniques is trending due to their capability of manipulating antenna parameters to achieve optimized performance. Literature presents use of bio-inspired algorithms such as Genetic algorithms (GA), Particle swarm optimization (PSO), Differential evolution (DE), Invasive weed optimization (IWO), Wind driven optimization (WDO) and Ant colony optimization (ACO) on MPAs for performance enhancement. This paper begins with an introduction to MPAs followed by an analysis of the performance improvement techniques. Evolution of bio-inspired algorithms and their applications in the field of MPAs are also presented. Based on the compilation of studies, importance of applying multi-objective bio-inspired algorithms for simultaneous optimization of multiple antenna parameters is emphasized. Further, research voids in the field are revealed and direction is shown to design compact multifunctional MPAs.

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Section: Other Bio-inspired Algorithmsmentioning

confidence: 99%

Bio-Inspired Algorithms Applied on Microstrip Patch Antennas: a Review

Saraereh

Saraira

Alsafasfeh³

et al. 2016

IRECAP

View full text Add to dashboard Cite

show abstract

“…Accordingly, PSO and curve fitting have been introduced in [18], and the overall bandwidth of the inverted E-shaped microstrip patch antenna was increased by 15%. Authors in [20][21][22][23] have proposed mathematical models of the RMPA considering the center frequency as well as return loss, and the optimal designs are obtained via the CS, PSO, and DE algorithms. However, none of them involve improving antenna gain, widening antenna bandwidth, and minimization of antenna size.…”

mentioning

confidence: 99%

“…Nevertheless, most of the designs that have been mentioned previously do not consider the minimization of antenna size, which could potentially limit the application of the RF harvester. In [18][19][20][21][22][23], heuristic optimization approaches including the DE and CS algorithms have been utilized to determine the geometrical characteristics of the optimal patch antenna. Conventionally, patch antennas suffer from a narrow bandwidth.…”

mentioning

confidence: 99%

Bio-inspired optimization algorithms applied to rectenna design

Wang

Leach

et al. 2018

Big Data Anal

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A comparative study of the use of bio-inspired optimization technologies including the Cuckoo Search (CS) algorithm, the Differential Evolution (DE) algorithm, and Quantum-behaved Particle Swarm Optimization (QPSO) in the design of microstrip patch antennas for use in RF energy harvesting systems is presented. Radio frequency (RF) energy harvesting is considered as an eco-friendly energy source and has become a focus of intense research especially for use in distributed sensor networks. In a RF energy harvesting system, the antenna is responsible for capturing RF signals over a certain frequency band, and it is a vital element in determining the performance of the RF energy harvester. In this paper, a new mathematical weighted evaluation model involving antenna efficiency, center frequency, and bandwidth is proposed to evaluate the performance of a rectangular microstrip patch antenna (RMPA) for a RF harvesting system based on both the transmission-line model and the cavity model. With the evaluation model as the objective function, bio-inspired optimization approaches are utilized to determine the geometrical parameters of the optimal antenna based on given constraints. Moreover, the optimised designs of an antenna for harvesting energy from the Global System for Mobile Communications (GSM) frequency band are proposed via the mathematical model and bio-inspired optimization approaches using simulations. Furthermore, a comparative study of the DE, CS, and QPSO techniques is conducted via the evaluation of the properties of the antenna designs.

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