Recent Submissions

Now showing 1 - 5 of 18
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    Fractional Regularized Distorted Born Iterative Method for Permittivity Reconstruction
    (Společnost pro radioelektronické inženýrství, 2022-04) Magdum, Amit; Erramshetty, Mallikarjun; Jagannath, Ravi Prasad K.
    In this paper, we propose a fractional regularized distorted Born iterative method (DBIM) to solve non-linear ill-posed problems of microwave imaging. Fractional regularization is a modification to Tikhonov regularization, where singular values are weighed with fractional power. As a result, the well-known effect of oversmoothing present in Tikhonov regularization is reduced, thereby the output image quality is improved. The results of this method are compared with standard DBIM using Tikhonov regularization. Various numerical examples of simulated and experimental datasets containing homogeneous as well as heterogeneous scatterers are considered to validate the effectiveness of the proposed approach. It is found that the proposed method improves the accuracy of estimated images over conventional DBIM.
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    Classification of Microwave Planar Filters by Deep Learning
    (Společnost pro radioelektronické inženýrství, 2022-04) Vesely, Jiri; Olivova, Jana; Gotthans, Jakub; Gotthans, Tomas; Raida, Zbynek
    Over the last few decades, deep learning has been considered to be powerful tool in the classification tasks, and has become popular in many applications due to its capability of processing huge amount of data. This paper presents approaches for image recognition. We have applied convolutional neural networks on microwave planar filters. The first task was filter topology classification, the second task was filter order estimation. For the task a dataset was generated. As presented in the results, the created and trained neural networks are very capable of solving the selected tasks.
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    Multiobjective Reinforcement Learning Based Energy Consumption in C-RAN enabled Massive MIMO
    (Společnost pro radioelektronické inženýrství, 2022-04) Sharma, Shruti; Yoon, Wonsik
    Multiobjective optimization has become a suitable method to resolve conflicting objectives and enhance the performance evaluation of wireless networks. In this study, we consider a multiobjective reinforcement learning (MORL) approach for the resource allocation and energy consumption in C-RANs. We propose the MORL method with two conflicting objectives. Herein, we define the state and action spaces, and reward for the MORL agent. Furthermore, we develop a Q-learning algorithm that controls the ON-OFF action of remote radio heads (RRHs) depending on the position and nearby users with goal of selecting the best single policy that optimizes the trade-off between EE and QoS. We analyze the performance of our Q-learning algorithm by comparing it with simple ON-OFF scheme and heuristic algorithm. The simulation results demonstrated that normalized ECs of simple ON-OFF, heuristic and Q-learning algorithm were 0.99, 0.85, and 0.8 respectively. Our proposed MORL-based Q-learning algorithm achieves superior EE performance compared with simple ON-OFF scheme and heuristic algorithms.
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    New Reflector Shaping Methods for Dual-Reflector Antenna
    (Společnost pro radioelektronické inženýrství, 2022-04) Quzwain, Kamelia; Yamada, Yoshihide; Kamardin, Kamilia; Abd Rahman, Nurul Huda; Ismail, Alyani
    In the fifth-generation (5G) mobile system, new millimeter-wave technologies such as small cell size and multibeam operation are introduced at the base station. Currently, linear array antennas are used at base stations, however higher design complexity and increased losses in feeding network are expected when the same technology is used to produce multibeams in 5G operation. Through a suitable configuration, a dual-reflector antenna system seems to be a promising candidate to replace the currently used array antennas due to the feasibility of achieving high gain and good multibeam characteristics. In the previous authors’ work, in order to increase the antenna gain at on-focus beams, a reflector shaping method was applied to the dual-reflector antenna, and constant phase and adequate amplitude distribution were achieved on the aperture plane. Furthermore, a good multibeam performance was validated through the consistency of multiple off-focus beam patterns, where a shaped spherical reflector antenna has been used. However, during off-focus conditions, spherical aberration has degraded the phase distribution on the aperture plane and caused reduction in the antenna gain. In this paper, modification to the reflector shaping method using equivalent parabola and equivalent circle method is performed to achieve a reflector antenna system having a constant phase distribution on the aperture plane. The idea of modifying the reflector shaping method comes from the equivalent parabola concept in the Cassegrain dual reflector antenna. During modification, first, the equivalent parabola and circle equation is implemented in the reflector shaping algorithms. Second, a Matrix Laboratory (MATLAB) program is developed in order to solve the reflector design equations and to obtain the main and sub reflector shapes. The MATLAB program is able to generate ray path, aperture illumination distribution and radiation pattern to estimate the adequacy of the reflector shaping results. In the final step, multibeam performance is validated using an electromagnetic simulator, FEKO. Through comparison of the equivalent parabola with the equivalent circle reflectors, an antenna efficiency of 67.6% is obtained and better multibeam radiation patterns are demonstrated using the equivalent circle reflector. Therefore, the usefulness of the newly developed shaping method employing equivalent circle reflector is ensured.
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    On the RSSI-Based Indoor Localization Employing LoRa in the 2.4 GHz ISM Band
    (Společnost pro radioelektronické inženýrství, 2022-04) Simka, Marek; Polak, Ladislav
    Demand for systems and technologies ensuring indoor localization or tracking of an object with high and stable accuracy is continuously increasing. Nowadays, there are exist several wireless technologies, for instance Bluetooth or Wi-Fi, which can be employed for indoor positioning. In the future, Long Range (LoRa), originally developed for long range communication with high link budget, can extend the family of these technologies. This paper focuses on the LoRa technology and its employing in the licence free 2.4,GHz band for Received Signal Strength Indicator (RSSI) based indoor localization. To measure and collect the values of RSSI, a simple measurement setup is proposed. The RSSI values are used to calculate the position of an object according to the principle of trilateration. Measurements are conducted in three different indoor environments for different signal configurations of LoRa. The recorded dataset is available online for future research purposes. The results, analysed in terms of localization accuracy, revealed good performance of LoRa. However, this performance is highly depending on the signal configuration of LoRa and on the position of nodes.