Planar Antenna Arrays Beamforming Using Various Optimization Algorithms

Ghattas, Nancy; Ghuniem, Atef M.; Abdelsalam, Abdelazeem A.; Magdy, Ahmed

doi:10.1109/access.2023.3292792

Cited by 5 publications

References 56 publications

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On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta‐heuristic optimization

Dutta,

Mahanti

2024

Int J Communication

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SummaryThe investigations related to the planar antenna array have attracted much attention due to their vast applications in the areas of advanced wireless communication and electromagnetics. This article presents an effective synthesis method of a sparsely thinned symmetric planar antenna array using three well‐known meta‐heuristics including symbiotic organism search (SOS) algorithm, moth fly optimization (MFO), and multi‐verse optimization (MVO) algorithms. The main aim of this work is to optimize the positions of the switched‐on antenna elements on the array aperture in order to reduce the value of side‐lobe levels in the radiation field pattern in multiple planes for a desired first null beam width and subsequently to obtain the maximum reduced number of array‐elements in the antenna array. Two different cases are performed to optimize the radiation pattern in different azimuth angles with two different examples. The proposed methods can constrain the total number of array elements, inter‐element distance, and aperture area of the array. The radiation pattern characteristic and computation time linked with each example and each algorithm are recorded and compared with each other as well as with a fully populated planar symmetric rectangular array antenna of same aperture size for arriving at the conclusion. The simulation‐based results demonstrate the effectiveness of the proposed design and the efficiency of the performance using the SOS algorithm.

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On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta‐heuristic optimization

Dutta,

Mahanti

2024

Int J Communication

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Beamforming Antenna Array for Wireless Communications-Based Improved Grey Wolf Optimizer Algorithm

Ghattas,

Ghuniem,

Abdelsalam

et al. 2024

Smart Innovation, Systems and Technologies

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Planar array sparse distribution based on T-2GWO algorithm

Wang,

Zhang,

Meng

2024

J. Phys.: Conf. Ser.

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This paper introduces an approach termed T-2GWO (Tent chaos-dual channel Grey Wolf Optimization) algorithm designed for achieving sparse distribution within constrained position ranges for planar arrays. The initial population is generated by using the Tent Chaos algorithm, modeling individual coordinate positions within the population as a two-channel matrix. Subsequently, the Grey Wolf Algorithm is employed for optimization purposes. The algorithm has verified its effectiveness under the assumption of uniform excitation and can obtain the minimum peak side lobe level, reaching peak side lobe levels of -25.78 dB and - 26.15 dB in the azimuth and pitch directions. Compared with the genetic algorithm, the reduction is 3.53 dB and 10.32 dB respectively. At the same time, better main beam radiation can be obtained.

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Planar Antenna Arrays Beamforming Using Various Optimization Algorithms

Cited by 5 publications

References 56 publications

On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta‐heuristic optimization

On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta‐heuristic optimization

Beamforming Antenna Array for Wireless Communications-Based Improved Grey Wolf Optimizer Algorithm

Planar array sparse distribution based on T-2GWO algorithm

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