Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates

Roshani, Sobhan; Koziel, Slawomir; Yahya, Salah I.; Chaudhary, Muhammad Akmal; Ghadi, Yazeed Yasin; Roshani, Sobhan; Golunski, Lukasz

doi:10.3390/s23167089

Cited by 16 publications

(10 citation statements)

References 86 publications

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“…The T/R module mainly completes the amplitude and phase adjustment of the transmitted and received signals. The fault of transmitting and receiving channels and the coupling [ 9 ] between different channels are important problems in the application of array antennas. When a fault occurs in the transceiver channel, such as the T/R module being faulty, the array antenna’s performance will be changed.…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation Method for Array Antenna Considering Performance Changes

Huang,

Zhu,

Liang

2024

Sensors

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The existing array antenna reliability evaluation method based on the n/k system is analyzed. As the failed T/R module’s influence on the array antenna’s performance is not considered, the reliability of the array antenna is overestimated. To improve the accuracy of the array antenna reliability evaluation, the performance changes caused by T/R failures in different locations are considered. The reliability evaluation method considering the performance changes is established. The performance and probability of the array antenna’s state are calculated, and accurate reliability is obtained by calculating all the available state’s probabilities. The complexity of the reliability evaluation method is analyzed, and the reliability evaluation method for large-scale array antennae is established. The large-scale array antenna is divided into several subarrays. The performance and reliability of each subarray are analyzed, and the array antenna’s reliability is calculated through subarrays. The array antenna’s performance changes are considered with the proposed method, the overestimation problem of the existing reliability evaluation method is solved, and the accuracy of the array antenna reliability evaluation is improved.

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Section: Introductionmentioning

confidence: 99%

Reliability Evaluation Method for Array Antenna Considering Performance Changes

Huang,

Zhu,

Liang

2024

Sensors

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“…To counter these threats, numerous preventive strategies have been proposed to fortify the security of the network layer within WSNs [ 10 , 11 , 12 ]. These strategies encompass a variety of techniques, including authentication, intrusion-detection systems, and secure routing protocols.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks

Khan,

Alnazzawi

2024

Sensors

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Wireless sensor networks (WSNs) are essential in many areas, from healthcare to environmental monitoring. However, WSNs are vulnerable to routing attacks that might jeopardize network performance and data integrity due to their inherent vulnerabilities. This work suggests a unique method for enhancing WSN security through the detection of routing threats using feed-forward artificial neural networks (ANNs). The proposed solution makes use of ANNs’ learning capabilities to model the network’s dynamic behavior and recognize routing attacks like black-hole, gray-hole, and wormhole attacks. CICIDS2017 is a heterogeneous dataset that was used to train and test the proposed system in order to guarantee its robustness and adaptability. The system’s ability to recognize both known and novel attack patterns enhances its efficacy in real-world deployment. Experimental assessments using an NS2 simulator show how well the proposed method works to improve routing protocol security. The proposed system’s performance was assessed using a confusion matrix. The simulation and analysis demonstrated how much better the proposed system performs compared to the existing methods for routing attack detection. With an average detection rate of 99.21% and a high accuracy of 99.49%, the proposed system minimizes the rate of false positives. The study advances secure communication in WSNs and provides a reliable means of protecting sensitive data in resource-constrained settings.

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“…Trough the training of ANNs on data collected from complicated systems, the underlying behaviors can be captured, facilitating precise predictions and refned control over these systems [42][43][44]. AI tools have been also widely used in designing of electronics and microwave devices, such as antennas, couplers, and power dividers [8,[45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Design of a Microwave Quadrature Hybrid Coupler with Harmonic Suppression Using Artificial Neural Networks

Roshani,

Yahya,

Assaad

et al. 2024

Active and Passive Electronic Components

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In this paper, a compact and simple structure of an elliptic microstrip lowpass filter (LPF) is designed for harmonic suppression in microwave quadrature hybrid coupler (QHC) applications. A radial resonator and a rectangular resonator are used to produce an elliptic LPF. The proposed LPF is used on the outer sides of the branch line coupler, which has improved the coupler harmonic suppression. Furthermore, artificial neural networks (ANNs) are incorporated to improve the LPF design process. The LPF best structure is obtained using the proposed ANN model. The proposed LPF has a compact size, which only occupies 16.4 mm × 7.3 mm equals to 0.164 λg × 0.073 λg, has a cut frequency of 2.2 GHz, and shows a sharp transmission band with a roll-off rate of 158.3 dB/GHz. Finally, the deigned QHC operates correctly at 1 GHz, which shows high harmonic suppression ability. The proposed QHC provides wide suppression band from 2.25 GHz up to more than 14 GHz, which can effectively suppress 3rd, to 14th harmonics. The proposed coupler features desirable parameters of S11, S21, S31, and S41, with magnitude of −21 dB, −3.4 dB, −3.3 dB, and −22.5 dB, at the operating frequency. The proposed approach mitigates the complexity of the circuit fabrication, compared with the previous methods while achieved desirable performances for the proposed QHC.

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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates

Cited by 16 publications

References 86 publications

Reliability Evaluation Method for Array Antenna Considering Performance Changes

Reliability Evaluation Method for Array Antenna Considering Performance Changes

Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks

Design of a Microwave Quadrature Hybrid Coupler with Harmonic Suppression Using Artificial Neural Networks

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