Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/799
Title: Optimized metamaterial-loaded fractal antenna using modified hybrid BF-PSO algorithm.
Authors: Gupta, N
Saxena, J
Bhatia, K S
Keywords: Fractal antenna
Metamaterial
Modified hybrid bacterial foraging–particle swarm optimization
Split-ring resonator
Issue Date: 2020
Publisher: Neural Computing and Applications, 32,
Series/Report no.: ;7153-7169.
Abstract: The paper proposes optimization of square split-ring resonator (SRR) metamaterial unit cell using modified hybrid bacterial foraging–particle swarm optimization (BF-PSO). Optimized metamaterial unit cells are loaded into novel designed square fractal antenna for its bandwidth enhancement. The presented research is alienated in three phases: Novel design of microstrip line-fed square fractal antenna with defected ground structure is proposed in the initial phase that provides dual band performance. In second phase, with the aim of bandwidth enhancement, quasi-static model of SRR unit cell is used to optimize its structural parameters so that optimized structure resonates at desired frequency region. Modifications are included in hybrid BF-PSO algorithm as per size constraints of SRR unit cell to be optimized and for improving the convergence behavior of algorithm. The performance of modified hybrid BF-PSO algorithm is assessed against four other evolutionary techniques named as classical BFO, chaos PSO, IWO and ABC. In later phase, optimized SRR unit cells are loaded into initially designed square fractal antenna that results in broadband performance suitable for upper S-band and lower C-band wireless applications. The designed square fractal antenna without and with SRR unit cells is fabricated and tested to verify the experimental results.
URI: https://doi.org/10.1007/s00521-019-04202-z
http://localhost:8080/xmlui/handle/123456789/799
ISSN: 1433-3058
Appears in Collections:Research Papers

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