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Optimised 4 × 4 millimetre-wave antenna array with DGS using hybrid ECFO-NM algorithm for 5G mobile networks
A novel optimised 4 × 4 microstrip patch antenna array operating in the 28−38 GHz frequency range for fifth generation mobile networks is presented. The proposed structure is fed by the corporate feed network printed on the same side of the substrate. To improve the array radiation characteristics,...
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Published in: | IET microwaves, antennas & propagation antennas & propagation, 2017-09, Vol.11 (11), p.1516-1523 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Request full text |
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Summary: | A novel optimised 4 × 4 microstrip patch antenna array operating in the 28−38 GHz frequency range for fifth generation mobile networks is presented. The proposed structure is fed by the corporate feed network printed on the same side of the substrate. To improve the array radiation characteristics, a defected ground plane structure (DGS), which acts as coupled c-shaped in the ground plane, is used. The dimensions of the antenna array structure are optimised using a new hybrid approach involving the enhanced central force optimisation (ECFO) and Nelder–Mead (NM) algorithms. To illustrate the convergence capability of the ECFO-NM algorithm, the results are compared with those obtained using stand-alone ECFO and particle swarm optimisation algorithms. The results show the effect of DGS on the antenna performance characteristics, i.e. the radiation efficiency and return loss are improved, on average, by ∼17.14 and 69.2%, respectively. Furthermore, the realised antenna gain was increased by 2.44 dBi with a negligible effect on the half-power beamwidth. The optimised antenna array yielded a broadband impedance bandwidth higher than 32% for a reflection coefficient lower than −12 dB and a total realised gain of up to 18.65 dBi, which makes it suitable for imaging applications and millimetre-wave wireless communications. |
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ISSN: | 1751-8725 1751-8733 1751-8733 |
DOI: | 10.1049/iet-map.2016.0959 |