2023/1

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Recent Submissions

Now showing 1 - 5 of 19
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    Design and Implementation of Closed TEM Cells: Simulation-Based Approach
    (Společnost pro radioelektronické inženýrství, 2023-04) Bednarsky, V.; Raida, Z.; Drinovsky, J.
    In the paper, a simulation-based design procedure for the implementation of a TEM cell (the Crawford cell) is presented. The empirical approach uses computer simulations carried out in the CST Microwave Studio to design the cell that operates in the frequency range from 100 kHz to 400 MHz. Following the developed procedure, the TEM cell was implemented, and the cell was tested experimentally. The TEM cell can be used for electromagnetic susceptibility (EMS) measurements, where the DUT is irradiated by the field in a wide frequency band. The DUT is tested to operate without the performance degradation under the influence of electromagnetic disturbances. In addition, the cell can be used for electromagnetic interference (EMI) measurements focused on interference emissions generated by the DUT.
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    A Compact Band-Notched UWB MIMO Antenna with Enhanced Isolation Using Comb Shaped Decoupling Element
    (Společnost pro radioelektronické inženýrství, 2023-04) Chatterjee, S.; Rana, S.; Sanyal, R.
    A compact 37mm × 26 mm two element multiple-input-multiple-output (MIMO) antenna is presented for ultra wide band (UWB) system application with band notched characteristics. The proposed antenna comprises two semi trapezoidal shaped monopole radiating elements. The band rejection feature around 3.5 GHz has been achieved by incorporating the open ended quarter wavelength spiral shaped slot resonator on the patched surface. In order to realize the enhanced isolation, comb shaped symmetrical stub arrangement are embedded at the U shaped etched periphery to the stepped ground plane between the monopole radiators. This novel design approach leads towards isolation enhancement better than 20 dB throughout the UWB spectral range (3.1 -10.6 GHz) with peak isolation near about 46 dB. The Envelope Correlation Coefficient is significantly lower than 0.005 in entire operating range except the WiMAX rejection band.
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    SCA-CGAN:A New Side-Channel Attack Method for Imbalanced Small Samples
    (Společnost pro radioelektronické inženýrství, 2023-04) Wang, W; Wang, J. N.; Hu, F. L.; Ni, F.
    In recent years, many deep learning and machine learning based side channel analysis (SCA) techniques have been proposed, most of which are based on the optimization of existing network models to improve the performance of SCA. However, in practice, the attacker often captures unbalanced and small samples of data due to various environmental factors that limit and interfere with the successful implementation of SCA. To address this problem, in this paper, we firstly introduced the Conditional Generation Adversarial Network (CGAN). We proposed a new model SCA-CGAN that combines SCA and CGAN. We used it to generate a specified number and class of simulated energy traces to expand and augment the original energy traces. Finally, we used the augmented data to implement SCA and achieved a good result. Through experiments on the unprotected ChipWhisperer (CW) data and the ASCAD jittered dataset, the results shown that the SCA using the augmented data is the most efficient, and the correct key is successfully recovered on both datasets. For the CW dataset, the model accuracy is improved by 20.75% and the traces number required to recover the correct key is reduced by about 79.5%. For the ASCAD jittered dataset, when the jitter is 0 and 50, the traces number required to recover the correct key is reduced by about 76.8% and 75.7% respectively.
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    SAMPLE Dataset Objects Classification Using Deep Learning Algorithms
    (Společnost pro radioelektronické inženýrství, 2023-04) Turcanik, M.; Perdoch, J.
    The main topic of the article is automatic target classification of the synthetic aperture radar images based on the dataset composed of measured and synthetic data. The original contribution of the authors is their own topology of the convolutional neural network (CNN) with 1, 2, 3, and 4 tiers. The original convolutional neural network is used to classify radar images from the Synthetic And Measured Paired and Labeled Experiment (SAMPLE) dataset which consists of SAR imagery from publicly available datasets and well-matched synthetic data. The presented topologies of the CNN with 1, 2, 3, and 4 tiers were analyzed in 3 different scenarios: trained on the basis of real measured data and tested by synthetic data, trained on the basis of synthetic data, and tested by real measured data, and in the last case training and testing sets were formed by combining real measured and synthetic data. Based on the results of testing we could not use the proposed convolutional neural network trained with real measured data to classify synthetic radar images and vice versa (the 1st and the 2nd scenarios). The only last scenario with a combination of real measured and synthetic data in the training, validation, and testing data sets generates excellent results. The authors also present some confusion matrices, which can explain the reasons for the misclassification of radar images of military equipment. Comparing achieved results with another SAMPLE dataset classification results we can prove the usability of proposed and tested CNN structures for automatic target classification of the synthetic aperture radar images. The classification accuracy of the original convolutional network is 96.1%, which is better than the results of the other research so far.
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    An Overview of Fully On-Chip Inductors
    (Společnost pro radioelektronické inženýrství, 2023-04) Ondica, R.; Kovac, M.; Hudec, A.; Ravasz, R.; Maljar, D.; Stopjakova, V.; Arbet, D.
    This paper focuses on full integration of passive devices, especially inductors with emphasis on multi-layer stacked (MLS) structures of fully integrated inductors using patterned ground shield (PGS) and fully integrated capacitor. Comparison of different structures is focused on the main electrical parameters of integrated inductors (e.g. inductance L, inductance density LA, quality factor Q, frequency of maximum quality factor F Qmax, self-resonant frequency FSR, and series resistance R DC ) and other non-electrical parameters (e.g. required area, manufacturing process, purpose, etc.) that are equally important during comparison of the structures. Categorization of inductor structures with most significant results that was reported in the last years is proposed according to manufacturing process. Final geometrical and electrical properties of the structure in great manner accounts to the fabrication process of integrated passive device. This work offers an overview and state-of-the-art of the integrated inductors as well as manufacturing processes used for their fabrication. Second purpose of this paper is insertion of the proposed structure from our previous work among the other results reported in the last 7 years. With the proposed solution, one can obtain the highest inductance density L A = 23.59 nH/mm 2 and second highest quality factor Q = 10.09 amongst similar solutions reported in standard technologies that is also suitable competition for integrated inductors manufactured in advanced technology nodes.