Phased arrays in communication system based on Taguchi‐neural networks

Smida, Besma; Ghayoula, Ridha; Nemri, Nadhem; Trabelsi, H.; Gharsallah, Ali; Grenier, Dominic

doi:10.1002/dac.2625

Cited by 16 publications

(20 citation statements)

References 25 publications

(53 reference statements)

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“…Smart antennas are always using to mitigate ISI, fading, and Bit Error Rate (BER) reduction when there is occurrence of multipath fading. Least Squares Constant Modulus Algorithm (LSCMA) has the capacity to reduce BER [62][63][64].…”

Section: A Multipath Mitigation (Mm)mentioning

confidence: 99%

See 1 more Smart Citation

Features and Futures of Smart Antennas for Wireless Communications: A Technical Review

Oluwole¹,

Srivastava²

2018

JESTR

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Smart antenna is one of the most proficient and dominant technological innovations for maximizing capacity, improve quality, and coverage in wireless communications system. This work presents relevant comprehensive technical review of research work, unanswered questions, and untried methods on smart antennas technology for wireless communication systems. This also examines most of the significant improvements in the field of smart antennas technologies and the related fields in wireless communication systems. An evaluation of the analytical techniques for the theoretical analysis of adaptive beamforming algorithm, level of the system performance optimization approaches has been highlighted. Performance realistic evaluation and implementation cogent parameters areas for the deployment of smart antennas on the performance system in wireless communication systems have been also examined.

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Section: A Multipath Mitigation (Mm)mentioning

confidence: 99%

“…The receiver power is maximized and it does not null the interference. Phased array using active array configurations can adapt the antenna pattern according to the change of mobile communication environment [62].…”

Section: B Dynamically Phased Array (Direction Finding) Systemsmentioning

confidence: 99%

Features and Futures of Smart Antennas for Wireless Communications: A Technical Review

Oluwole¹,

Srivastava²

2018

JESTR

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“…where t = 1, 2, ..., T is the index of the training set. This is an iterative process using the back-propagation algorithm described in [15]. For each iteration, the weights w ij and w ki are updated by The ability of generalize is one of the main advantages of NN.…”

Section: Neural Networkmentioning

confidence: 99%

Radiation pattern synthesis using hybrid fourier-woodward-lawson-neural networks for reliable mimo antenna systems

Ghayoula

Bouallègue

Ghayoula

et al. 2017

2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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In this paper, we implement hybrid Woodward-Lawson-Neural Networks and weighted Fourier method to synthesize antenna arrays. The neural networks (NN) is applied here to simplify the modeling of MIMO antenna arrays by assessing phases. The main problem is obviously to find optimal weights of the linear antenna array elements giving radiation pattern with minimum sidelobe level (SLL) and hence ameliorating the antenna array performance. To attain this purpose, an antenna array for reliable Multiple-Input Multiple-Output (MIMO) applications with frequency at 2.45 GHz is implemented. To validate the suggested method, many examples of uniformly excited array patterns with the main beam are put in the direction of the useful signal. The Woodward-Lawson-Neural Networks synthesis method permits to find out interesting analytical equations for the synthesis of an antenna array and highlights the flexibility between the system parameters in input and those in output. The performance of this hybrid optimization underlines how well the system is suitable for a wireless communication and how it participates in reducing interference, as well.

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“…, P is the index of the training set. This is an iterative process using the backpropagation algorithm described in [12]. The weights w ij and w ki are updated for each iteration by…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…In [11] RBF neural network is used to optimize the radiation pattern of non-uniform linear arrays of High superconducting rectangular microstrip antennas. Phased array in communication system based on Taguchi-neural networks is presented in [12]. In [20] the authors present a usual application of back-propagation neural networks for synthesis and optimization of antenna array.…”

Section: Introductionmentioning

confidence: 99%

Pattern Synthesis Using Hybrid Fourier-Neural Networks for Ieee 802.11 Mimo Application

Ghayoula¹,

Ghayoula²,

Haj-Taieb³

et al. 2016

PIER B

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Abstract-In this paper, the application of Artificial Neural Network (ANN) with back-propagation algorithm and weighted Fourier method are used for the synthesis of antenna arrays. The neural networks facilitate the modelling of antenna arrays by estimating the phases. The most important synthesis problem is to find the weights of the linear antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the sidelobe level. This technique is used to prove its effectiveness in improving the performance of the antenna array. To achieve this goal, antenna array for Wi-Fi IEEE 802.11a with frequency at 2.4 GHz to 2.5 GHz is implemented using Hybrid Fourier-Neural Networks method. To verify the validity of the technique, several illustrative examples of uniform excited array patterns with the main beam are placed in the direction of the useful signal. The neural network synthesis method not only allows to establish important analytical equations for the synthesis of antenna array, but also provides a great flexibility between the system parameters in input and output which makes the synthesis possible due to the explicit relation given by them.

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Phased arrays in communication system based on Taguchi‐neural networks

Cited by 16 publications

References 25 publications

Features and Futures of Smart Antennas for Wireless Communications: A Technical Review

Features and Futures of Smart Antennas for Wireless Communications: A Technical Review

Radiation pattern synthesis using hybrid fourier-woodward-lawson-neural networks for reliable mimo antenna systems

Pattern Synthesis Using Hybrid Fourier-Neural Networks for Ieee 802.11 Mimo Application

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