Steering an adaptive antenna array by LMS algorithm

Gargouri, Lamia; Ghayoula, Ridha; Fadlallah, Najib; Gharsallah, Ali; Rammal, M.

doi:10.1109/icecs.2009.5410893

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The Taguchi method, pioneered by Genichi Taguchi, is a statistical approach used to enhance quality and optimize processes in engineering and manufacturing. When applied to antenna arrays, this method involves systematically adjusting various design parameters to improve the array's performance [49,50].…”

Section: Taguchi Methodsmentioning

confidence: 99%

Enhancing Beamforming Efficiency: Utilizing Taguchi Optimization and Neural Network Acceleration

Kheder,

Ghayoula,

Smida

et al. 2024

Preprint

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The article presents an innovative method for synthesizing radiation patterns efficiently by 1 combining the Taguchi method and neural networks, while validating the results on a 10-element 2 antenna array. The Taguchi method aims to minimize product and process variability, while neural 3 networks are used to model the relationship between antenna design parameters and radiation 4 pattern characteristics. This approach utilizes Taguchi parameters as inputs for the neural network, 5 which is then trained on a dataset generated by the Taguchi method. After training, the network is 6 validated using a real 10-element antenna array. Analytical results demonstrate that this method 7 enables efficient synthesis of radiation patterns with a significant reduction in computation time 8 compared to traditional approaches. Furthermore, validation on the antenna array confirms the 9 accuracy and robustness of the approach, showing a high correlation between predicted performances 10 by the neural network model and actual measurements on the antenna array.In summary, our article 11 highlights that the combined use of the Taguchi method and neural networks, with validation on a 12 real antenna array, offers a promising approach for efficient synthesis of antenna radiation patterns. 13 This approach combines speed, accuracy, and reliability in antenna system design.

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Section: Taguchi Methodsmentioning

confidence: 99%

Enhancing Beamforming Efficiency: Utilizing Taguchi Optimization and Neural Network Acceleration

Kheder,

Ghayoula,

Smida

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Taguchi Methodsmentioning

confidence: 99%

Enhancing Beamforming Efficiency Utilizing Taguchi Optimization and Neural Network Acceleration

Kheder,

Ghayoula,

Smida

et al. 2024

Telecom

View full text Add to dashboard Cite

This article presents an innovative method for efficiently synthesizing radiation patterns by combining the Taguchi method and neural networks, validating the results on a ten-element antenna array. The Taguchi method aims to minimize product and process variability, while neural networks are used to model the relationship between antenna design parameters and radiation pattern characteristics. This approach utilizes Taguchi parameters as inputs for the neural network, which is then trained on a dataset generated by the Taguchi method. After training, the network is validated using a real ten-element antenna array. Analytical results demonstrate that this method enables efficient synthesis of radiation patterns, with a significant reduction in computation time compared to traditional approaches. Furthermore, validation on the antenna array confirms the accuracy and robustness of the approach, showing a high correlation between the performance predicted by the neural network model and actual measurements on the antenna array. In summary, our article highlights that the combined use of the Taguchi method and neural networks, with validation on a real antenna array, offers a promising approach for efficient synthesis of antenna radiation patterns. This approach combines speed, accuracy, and reliability in antenna system design.

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“…The simplest and most widely used adaptive algorithm is the Least Mean Square (LMS) algorithm and its modifications [1][2][3][4][5]. In [2], the authors used an array image factor, sandwiched in between two LMS algorithms sections.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Array Beamforming Using a Chaotic Beamforming Algorithm

Jovanović

Lazović

Rubežić

2016

International Journal of Antennas and Propagation

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The Chaotic beamforming adaptive algorithm is new adaptive method for antenna array’s radiation pattern synthesis. This adaptive method based on the optimization of the Least Mean Square algorithm using Chaos theory enables fast adaptation of antenna array radiation pattern, reduction of the noisy reference signal’s impact, and the improvement of the tracking capabilities. We performed simulations for linear and circular antenna arrays. We also compared the performances of the used and existing algorithms in terms of the radiation pattern comparison.

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Steering an adaptive antenna array by LMS algorithm

Cited by 7 publications

References 8 publications

Enhancing Beamforming Efficiency: Utilizing Taguchi Optimization and Neural Network Acceleration

Enhancing Beamforming Efficiency: Utilizing Taguchi Optimization and Neural Network Acceleration

Enhancing Beamforming Efficiency Utilizing Taguchi Optimization and Neural Network Acceleration

Adaptive Array Beamforming Using a Chaotic Beamforming Algorithm

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