Статті в журналах: "Microwave networks"

1

Son, Wonhyung, Won-Kwang Park, and Seong-Ho Son. "A Neural Network-Based Microwave Imaging Method for Object Localization." Journal of Electromagnetic Engineering and Science 22, no. 5 (September 30, 2022): 576–79. http://dx.doi.org/10.26866/jees.2022.5.r.125.

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This paper presents a new microwave imaging method using artificial neural networks to localize an object. The trained neural network reconstructs a tomographic image from the measured scattering data, such as a nonlinear electromagnetic inverse scattering solver. The appropriate number of hidden neurons is determined through the cross-entropy between network predictions and target values. To verify this method experimentally, we set up a testbed consisting of 16 antennas that transmit and receive 950 MHz microwaves underwater and used a metal rod with a diameter of 2 mm as a localizing target. The results show excellent imaging performance with fewer artifacts and less than a 2-mm localization error.

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2

Stepanets, I. V., V. A. Stepanets, E. M. Zaychik, and S. M. Odoevsky. "FEATURES OF THE APPLICATION AND PLANNING OF THE MICROWAVE TRANSMISSION IN THE 5th GENERATION NETWORKS." Informatization and communication, no. 3 (May 24, 2019): 77–83. http://dx.doi.org/10.34219/2078-8320-2019-10-3-77-83.

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Goal. Architecture and radio access technologies of 5G networks set high requirements towards throughput, latency and reliability of the distributive transport networks. Regarding to this, the goal of this paper is to carry out the analysis of actual characteristics of microwave transmission planning and its application, which is essential for the wireless segment of the distributive transport network of 5G. Materials and methods. The requirements for automatization of the planning processes were defined for communication networks in general and for microwave transmission in particular. This requirements definition is based on analysis of 5G network architecture, its characteristics and development tendency. The automatization must embrace all of the planning phases, including the solutions of the calculation and information tasks. Moreover, the automatization must represent an instrument for the decision support in development, modernization and optimization of the telecommunication networks, including microwave transmission. This must be based on the modelling within a specialized software platform, which is able to cooperate with the external databases and management systems. Results. The longstanding research of the authors is embodied in the software complex for planning and optimization of telecommunication networks ONEPLAN, which has a module architecture. This allows to carry out the planning and optimization of microwave transmission, throughput capabilities and data traffic distribution within the transport networks, as well as to make the analysis for data traffic reliability. Conclusion. Planning process automatization by the software platform ONEPLAN maintains efficiently the forehanded, technically and economically reasonable decision making for the development, modernization and optimization of the telecommunication networks including the wireless segment of 5G transport networks based on microwave transmission.

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3

Semennikov, Anton V. "MICROWAVE ELECTRONICS TECHNOLOGIES FOR 5G AND 6G WIRELESS NETWORKS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 9/6, no. 150 (2024): 176–84. http://dx.doi.org/10.36871/ek.up.p.r.2024.09.06.020.

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The article is devoted to the study of microwave electronics technologies, which play a key role in the development of fifth- and sixth-generation wireless networks (5G and 6G). The main aspects of the development and integration of microwave components, including power amplifiers, antennas, and modulators, are considered, and the challenges and prospects for their application are discussed. Particular attention is paid to innovations in the field of materials science and semiconductors, which can significantly improve network performance, providing high data rates and low latencies. Forecasts are given for the further development of microwave technologies in the context of 6G networks.

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4

Overeem, A., H. Leijnse, and R. Uijlenhoet. "Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network." Atmospheric Measurement Techniques Discussions 8, no. 8 (August 7, 2015): 8191–230. http://dx.doi.org/10.5194/amtd-8-8191-2015.

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Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

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5

Katkevičius, Andrius, Darius Plonis, Robertas Damaševičius, and Rytis Maskeliūnas. "Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review." Electronics 11, no. 15 (July 28, 2022): 2360. http://dx.doi.org/10.3390/electronics11152360.

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The usage of techniques of the artificial neural networks (ANNs) in the field of microwave devices has recently increased. The advantages of ANNs in comparison with traditional full-wave methods are that the prediction speed when the traditional time-consuming iterative calculations are not required and also the complex mathematical model of the microwave device is no longer needed. Therefore, the design of microwave device could be repeated many times in real time. However, methods of artificial neural networks still lag behind traditional full-wave methods in terms of accuracy. The prediction accuracy depends on the structure of the selected neural network and also on the obtained dataset for the training of the network. Therefore, the paper presents a systematic review of the implementation of ANNs in the field of the design and analysis of microwave devices. The guidelines for the systematic literature review and the systematic mapping research procedure, as well as the Preferred Report Items for Systematic Reviews and Meta-Analysis statements (PRISMA) are used to conduct literature search and report the results. The goal of the paper is to summarize the application areas of usage of ANNs in the field of microwave devices, the type and structure of the used artificial neural networks, the type and size of the dataset, the interpolation and the augmentation of the training dataset, the training algorithm and training errors and also to discuss the future perspectives of the usage of ANNs in the field of microwave devices.

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6

Wang, Lin, Guangying Wang, and Jingxu Chen. "IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing." Mobile Information Systems 2022 (September 27, 2022): 1–10. http://dx.doi.org/10.1155/2022/1351399.

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When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree.

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7

Milovanovic, Bratislav, Vera Markovic, Zlatica Marinkovic, and Zoran Stankovic. "Some applications of neural networks in microwave modeling." Journal of Automatic Control 13, no. 1 (2003): 39–46. http://dx.doi.org/10.2298/jac0301039m.

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This paper presents some applications of neural networks in the microwave modeling. The applications are related to modeling of either passive or active structures and devices. Modeling is performed using not only simple multilayer perception network (MLP) but also advanced knowledge based neural network (KBNN) structures.

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8

Overeem, Aart, Hidde Leijnse, and Remko Uijlenhoet. "Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network." Atmospheric Measurement Techniques 9, no. 5 (June 1, 2016): 2425–44. http://dx.doi.org/10.5194/amt-9-2425-2016.

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Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language “R”) is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

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9

Mu, Zhong Guo, Xue Lian Bai, Yi Ding Luo, Jian Ting Mei, and Ming Hu Zhang. "Study on Microwave Curing of Polyurethane (PU)/Epoxy (EP) Interpenetrating Networks (IPN)." Applied Mechanics and Materials 556-562 (May 2014): 649–52. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.649.

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Microwave curing of PU/EP IPN was studied in this paper. Microwave curing IPN was prepared by means of intermittent microwave heating, The results indicates that microwave curing technique can shorten curing time remarkably. The microwave curing and thermal curing IPN have identical structure, tensile property of microwave curing IPN is better than that of thermal curing IPN, Impact strength of thermal curing IPN is slightly higher.

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10

Wang, Lulu. "Holographic Microwave Image Classification Using a Convolutional Neural Network." Micromachines 13, no. 12 (November 23, 2022): 2049. http://dx.doi.org/10.3390/mi13122049.

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Holographic microwave imaging (HMI) has been proposed for early breast cancer diagnosis. Automatically classifying benign and malignant tumors in microwave images is challenging. Convolutional neural networks (CNN) have demonstrated excellent image classification and tumor detection performance. This study investigates the feasibility of using the CNN architecture to identify and classify HMI images. A modified AlexNet with transfer learning was investigated to automatically identify, classify, and quantify four and five different HMI breast images. Various pre-trained networks, including ResNet18, GoogLeNet, ResNet101, VGG19, ResNet50, DenseNet201, SqueezeNet, Inception v3, AlexNet, and Inception-ResNet-v2, were investigated to evaluate the proposed network. The proposed network achieved high classification accuracy using small training datasets (966 images) and fast training times.

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11

Wu, Dong Rong, He Jun Wu, and Xiao Lu Zhu. "Microwave Directional Wireless Power Transmission for Wireless Sensor Networks." Advanced Materials Research 756-759 (September 2013): 746–50. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.746.

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Power shortage is one of critical issues stalling the development of wireless sensor networks. This paper attempts to address this issue by means of microwave power transmission. In this paper, we propose a sensor node framework using a high-frequency microwave power transmitting module to allow sensor nodes to transmit power to others. We introduce the process of exchanging power between two adjacent sensor nodes and design a power transmission routing protocol called PTR in this paper. PTR optimizes the power transmission of a whole network so that the power of energy sources can efficiently reach any sensor node in the network. We have done simulations and analysis on this framework and the results are positive.

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12

Dobrowolski, Janusz A. "Differential and Common Mode Noise Waves and Correlation Matrices." International Journal of Electronics and Telecommunications 60, no. 2 (June 1, 2014): 133–41. http://dx.doi.org/10.2478/eletel-2014-0016.

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Abstract This paper presents an innovative extention of the noise wave definition to mixed mode, differential - and commonmode noise waves which can be used for noise analysis of differential microwave networks. Mixed mode noise waves are used next to define generalized mixed mode noise wave correlation matrices of microwave multiport networks. Presented approach may be used for noise analysis of microwave differential networks with differential ports as well as with conventional single ended ports.

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13

Gopalakrishnan, Keerthy, Aakriti Adhikari, Namratha Pallipamu, Mansunderbir Singh, Tasin Nusrat, Sunil Gaddam, Poulami Samaddar, et al. "Applications of Microwaves in Medicine Leveraging Artificial Intelligence: Future Perspectives." Electronics 12, no. 5 (February 23, 2023): 1101. http://dx.doi.org/10.3390/electronics12051101.

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Microwaves are non-ionizing electromagnetic radiation with waves of electrical and magnetic energy transmitted at different frequencies. They are widely used in various industries, including the food industry, telecommunications, weather forecasting, and in the field of medicine. Microwave applications in medicine are relatively a new field of growing interest, with a significant trend in healthcare research and development. The first application of microwaves in medicine dates to the 1980s in the treatment of cancer via ablation therapy; since then, their applications have been expanded. Significant advances have been made in reconstructing microwave data for imaging and sensing applications in the field of healthcare. Artificial intelligence (AI)-enabled microwave systems can be developed to augment healthcare, including clinical decision making, guiding treatment, and increasing resource-efficient facilities. An overview of recent developments in several areas of microwave applications in medicine, namely microwave imaging, dielectric spectroscopy for tissue classification, molecular diagnostics, telemetry, biohazard waste management, diagnostic pathology, biomedical sensor design, drug delivery, ablation treatment, and radiometry, are summarized. In this contribution, we outline the current literature regarding microwave applications and trends across the medical industry and how it sets a platform for creating AI-based microwave solutions for future advancements from both clinical and technical aspects to enhance patient care.

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14

Naik, Deepa, Soumyadeb Maity, and Tanmay De. "Light Trail Based Cost Efficient Traffic Grooming in Optical WiMAX Hybrid Network." Journal of Computational and Theoretical Nanoscience 17, no. 1 (January 1, 2020): 425–33. http://dx.doi.org/10.1166/jctn.2020.8685.

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Integrating Passive Optical Network (PON) and Worldwide Interoperability for Microwave Access network (WiMAX)achieves universal internet connectivity at a higher data rate. Here Passive Optical Networks (PONs) are used as the backbone. Base stations in WiMAX are connected to Optical Network Units. In this work cost, routing and resource allocation related issues in hybrid networks are investigated. Light trails are used for traffic grooming. Various network topologies are used for simulation and results are obtained, compared. and analyzed. The results confirm a lower cost solution by using hybrid networks for universal connectivity.

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15

Cao, Shun-Feng, Yong-Chang Jiao, and Zheng Zhang. "Applications of Generalized Cascade Scattering Matrix on the Microwave Circuits and Antenna Arrays." International Journal of Antennas and Propagation 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/759439.

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The ideal lossless symmetrical reciprocal network (ILSRN) is constructed and introduced to resolve the complex interconnections of two arbitrary microwave networks. By inserting the ILSRNs, the complex interconnections can be converted into the standard one-by-one case without changing the characteristics of the previous microwave networks. Based on the algorithm of the generalized cascade scattering matrix, a useful derivation on the excitation coefficients of antenna arrays is firstly proposed with consideration of the coupling effects. And then, the proposed techniques are applied on the microwave circuits and antenna arrays. Firstly, an improved magic-T is optimized, fabricated, and measured. Compared with the existing results, the prototype has a wider bandwidth, lower insertion loss, better return loss, isolation, and imbalances. Secondly, two typical linear waveguide slotted arrays are designed. Both the radiation patterns and scattering parameters at the input ports agree well with the desired goals. Finally, the feeding network of a two-element microstrip antenna array is optimized to decrease the mismatch at the input port, and a good impedance matching is successfully achieved.

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16

Ambrosanio, Michele, Stefano Franceschini, Vito Pascazio, and Fabio Baselice. "An End-to-End Deep Learning Approach for Quantitative Microwave Breast Imaging in Real-Time Applications." Bioengineering 9, no. 11 (November 4, 2022): 651. http://dx.doi.org/10.3390/bioengineering9110651.

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(1) Background: In this paper, an artificial neural network approach for effective and real-time quantitative microwave breast imaging is proposed. It proposes some numerical analyses for the optimization of the network architecture and the improvement of recovery performance and processing time in the microwave breast imaging framework, which represents a fundamental preliminary step for future diagnostic applications. (2) Methods: The methodological analysis of the proposed approach is based on two main aspects: firstly, the definition and generation of a proper database adopted for the training of the neural networks and, secondly, the design and analysis of different neural network architectures. (3) Results: The methodology was tested in noisy numerical scenarios with different values of SNR showing good robustness against noise. The results seem very promising in comparison with conventional nonlinear inverse scattering approaches from a qualitative as well as a quantitative point of view. (4) Conclusion: The use of quantitative microwave imaging and neural networks can represent a valid alternative to (or completion of) modern conventional medical imaging techniques since it is cheaper, safer, fast, and quantitative, thus suitable to assist medical decisions.

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17

Siddique, Uzma, Laeeq Ahmad, and Gulistan Raja. "Microwave Attenuation and Prediction of Rain Outage for Wireless Networks in Pakistan's Tropical Region." International Journal of Microwave Science and Technology 2011 (February 23, 2011): 1–6. http://dx.doi.org/10.1155/2011/714927.

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The microwave attenuation due to rainfall in tropical regions has not been very widely studied yet. In Pakistan's tropical environment, line-of-sight microwave communication links were set up and have been operated for several years to study the microwave attenuation characteristics due to tropical rainfall. In this paper the experimental results are presented, including the cumulative distributions of microwave attenuation and the relationship between specific attenuation and rainfall rate. In addition, a rain outage prediction model is proposed which not only predicts microwave radio link performance but will also be useful in calculating the link degradations due to interference issues. The main focus of this research work has been done keeping in mind the wireless networks of Pakistan. The results show that the rainfall rate, the microwave propagation characteristics, and outage predictions in Pakistan differ from the International Radio Consultative Committee predictions and ITU recommendation P530.7/8, respectively.

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18

Capmany, Jose, and Pascual Munoz. "Integrated Microwave Photonics for Radio Access Networks." Journal of Lightwave Technology 32, no. 16 (August 15, 2014): 2849–61. http://dx.doi.org/10.1109/jlt.2014.2333369.

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19

Chen, H. "Symbolic analysis of large-scale microwave networks." IEE Proceedings - Microwaves, Antennas and Propagation 141, no. 6 (1994): 433. http://dx.doi.org/10.1049/ip-map:19941309.

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20

Wang, Jiafu, Shaobo Qu, Zhuo Xu, Hua Ma, Jieqiu Zhang, Yinghong Li, and Xinhua Wang. "Super-Thin Cloaks Based on Microwave Networks." IEEE Transactions on Antennas and Propagation 61, no. 2 (February 2013): 748–54. http://dx.doi.org/10.1109/tap.2012.2220326.

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21

Bansal, R. "Microwave surfing. Wireless networks: an electronic battlefield?" IEEE Microwave Magazine 2, no. 4 (2001): 32–34. http://dx.doi.org/10.1109/6668.969933.

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22

Tilly, K., I. Kerese, T. Zsemlye, B. Vadasz, and Z. Szalay. "Intelligent Supervisory System for Microwave Telecommunication Networks." IFAC Proceedings Volumes 25, no. 6 (May 1992): 511–16. http://dx.doi.org/10.1016/s1474-6670(17)50958-1.

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23

Berceli, T. "Microwave communications systems and networks in Hungary." IEEE Journal on Selected Areas in Communications 12, no. 7 (1994): 1253–60. http://dx.doi.org/10.1109/49.312958.

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24

Zakaria, Zikri Kurniawan. "Long Term Evolution Network Planning Using The Backhaul Microwave Link in The Village Wangunharja Lembang District." [CEPAT] Journal of Computer Engineering: Progress, Application and Technology 2, no. 01 (February 26, 2023): 36. http://dx.doi.org/10.25124/cepat.v2i01.5810.

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Wangunharja village has an area of 832 ha and a population of 8256. In this village, 4G LTE network coverage still does not reach the entire region. Therefore, LTE network planning is needed to expand coverage in the area. This study was carried out by analyzing and planning LTE networks use microwave backhaul in Wangunharja Village. The first step is to check the quality of the signal along the main line of the village. Then, plan for capacity and LTE network coverage to determine the number of sites needed. Next, microwave backhaul planning is carried out with work frequency based on the distance of the backhaul link. Based on the LTE network planning the calculations show that two sites are required to cover the Wangunharja Village area. Furthermore, planning simulations are carried out using simulation software, and the values of the three parameters measured have met the operator's KPI standards. With a microwave link distance of 2.87 km, the operating frequency of the microwave antenna operates at 11 GHz.The results of microwave link calculations and simulations for the value of the received power level are -18.95 dBm, with a gain antenna of 45.8 dBi obtained fading margin of 49.04 dBm so that the availability value or level of availability in one year is 99.999%.

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25

Feng, Tiantian, Peng Jiang, Xiaomin Liu, and Xinyu Ma. "Applications of Deep Learning-Based Super-Resolution Networks for AMSR2 Arctic Sea Ice Images." Remote Sensing 15, no. 22 (November 17, 2023): 5401. http://dx.doi.org/10.3390/rs15225401.

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Studies have indicated that the decrease in the extent of Arctic sea ice in recent years has had a significant impact on the Arctic ecosystem and global climate. In order to understand the evolution of sea ice, it is becoming increasingly imperative to have continuous observations of Arctic-wide sea ice with high spatial resolution. Passive microwave sensors have the benefit of being less susceptible to weather, wider coverage, and higher temporal resolution. However, it is challenging to retrieve accurate parameters of sea ice due to the low spatial resolution of passive microwave images. Therefore, improving the spatial resolution of passive microwave images is beneficial for reducing the uncertainty of sea ice parameters. In this paper, four competitive multi-image super-resolution (MISR) networks are selected to explore the applicability of the networks on multi-frequency Advanced Microwave Scanning Radiometer 2 (AMSR2) images of Arctic sea ice. The upsampling factor is set to 4 in the experiment. Firstly, the optimal input lengths of the image sequence for the four MISR networks are found, and then the best network on different frequency band images is further identified. Furthermore, some factors, including seasons, sea ice motion, and polarization mode of images, that may affect the super-resolution (SR) results are analyzed. The experimental results indicate that utilizing images from winter yields superior SR results. Conversely, SR results are the worst during summer across all four MISR networks, exhibiting the largest difference in PSNR of 4.48 dB. Additionally, the SR performance is observed to be better for images with smaller magnitudes of sea ice motion compared to those with larger motions, with the maximum PSNR difference of 2.04 dB. Finally, the SR results for vertically polarized images surpass those for horizontally polarized images, showcasing an average advantage of 4.02 dB in PSNR and 0.0061 in SSIM. In summary, valuable suggestions for selecting MISR models for passive microwave images of Arctic sea ice at different frequency bands are offered in this paper. Additionally, the quantification of the various impact factors on SR performance is also discussed in this paper, which provides insights into optimizing MISR algorithms for passive microwave sea ice imagery.

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Katkevičius, Andrius. "MODELLING MICROWAVE DEVICES USING ARTIFICIAL NEURAL NETWORKS / MIKROBANGŲ ĮTAISŲ MODELIAVIMAS, TAIKANT DIRBTINIŲ NEURONŲ TINKLUS." Mokslas - Lietuvos ateitis 4, no. 1 (April 23, 2012): 81–84. http://dx.doi.org/10.3846/mla.2012.18.

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Artificial neural networks (ANN) have recently gained attention as fast and flexible equipment for modelling and designing microwave devices. The paper reviews the opportunities to use them for undertaking the tasks on the analysis and synthesis. The article focuses on what tasks might be solved using neural networks, what challenges might rise when using artificial neural networks for carrying out tasks on microwave devices and discusses problem-solving techniques for microwave devices with intermittent characteristics. Santrauka Nagrinėjamos dirbtinių neuronų tinklų taikymo galimybės mikrobangų įtaisams tirti. Apžvelgiami eksperimentiniai ir teoriniai darbai. Pateikiama apibendrinta informacija apie uždavinius, sprendžiamus taikant neuronų tinklus, problemas, kylančias dirbtinius neuronų tinklus taikant mikrobangų uždaviniams spręsti, ir problemų sprendimo būdus. Pateikiama bendra neuronų tinklų struktūra ir konkretūs neuronų tinklų naudojimo pavyzdžiai.

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SHANKARANARAYANAN, N. K., and KAM Y. LAU. "ELECTRICAL SUBCARRIER-MULTIPLE-ACCESS FOR LIGHTWAVE NETWORKS." International Journal of High Speed Electronics and Systems 03, no. 02 (June 1992): 235–60. http://dx.doi.org/10.1142/s0129156492000096.

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Multiplexing of information on microwave carriers, whose frequencies are within the direct modulation and detection bandwidths of semiconductor lasers and photoreceivers, can be used to provide multiple concurrent channels for lightwave networks in multiaccess applications. This is in effect an electrical multiplexing scheme applied to optical systems which is referred to as “Subcarrier Frequency-Division Multiple Access” (SFDMA). This paper provides an introduction to this subject, which includes discussions on factors that determine the performance of such a network as well as network architecture issues.

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Bonavera, L., S. L. Suarez Gomez, J. González-Nuevo, M. M. Cueli, J. D. Santos, M. L. Sanchez, R. Muñiz, and F. J. de Cos. "Point source detection with fully convolutional networks." Astronomy & Astrophysics 648 (April 2021): A50. http://dx.doi.org/10.1051/0004-6361/201937171.

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Context. Point sources are one of the main contaminants to the recovery of the cosmic microwave background signal at small scales, and their careful detection will be important for the next generation of cosmic microwave background experiments like LiteBird. Aims. We want to develop a method based on fully convolutional networks to detect sources in realistic simulations, and to compare its performance against one of the most used point source detection method in this context, the Mexican hat wavelet 2 (MHW2). The frequencies for our analysis are the 143, 217, and 353 GHz Planck channels. Methods. We produce realistic simulations of point sources at each frequency taking into account potential contaminating signals as the cosmic microwave background, the cosmic infrared background, the Galactic thermal emission, the thermal Sunyaev-Zel’dovich effect, and the instrumental and point source shot noises. We first produce a set of training simulations at 217 GHz to train the neural network that we named PoSeIDoN. Then we apply both PoSeIDoN and the MHW2 to recover the point sources in the validating simulations at all the frequencies, comparing the results by estimating the reliability, completeness, and flux density estimation accuracy. Moreover, the receiver operating characteristic (ROC) curves are computed in order to asses the methods’performance. Results. In the extra-galactic region with a 30° galactic cut, the neural network successfully recovers point sources at 90% completeness corresponding to 253, 126, and 250 mJy for 143, 217, and 353 GHz respectively. In the same validation simulations the wavelet with a 3σ flux density detection limit recovers point sources up to 181, 102, and 153 mJy at 90% completeness. To reduce the number of spurious sources, we also apply a safer 4σ flux density detection limit, the same as in the Planck catalogues, increasing the 90% completeness levels: 235, 137, and 192 mJy. In all cases PoSeIDoN produces a much lower number of spurious sources with respect to MHW2. As expected, the results on spurious sources for both techniques worsen when reducing the galactic cut to 10°. Conclusions. Our results suggest that using neural networks is a very promising approach for detecting point sources using data from cosmic microwave background experiments, providing overall better results in dealing with spurious sources with respect to the more usual filtering approaches. Moreover, PoSeIDoN gives competitive results even at the 217 GHz nearby channels where the network was not trained.

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Samundiswary, P., and Sivasindhu M. "Performance analysis of integrated WLAN-WiMAX-UMTS networks for multimedia applications." International Journal of Engineering & Technology 7, no. 3.29 (August 24, 2018): 214. http://dx.doi.org/10.14419/ijet.v7i3.29.18798.

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Next Generation Wireless networks (NGWN) are the integration of different types of available wireless networks. These integrated networks will provide seamless connectivity for multimedia user applications. Among various wireless networks, the networks such as Wireless Local Area network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX) and Universal Mobile Telecommunications System (UMTS) have their own unique characteristics and support for wide range of multimedia user applications. So, the integration of these networks and their performance analysis in respect of Quality of Service (QoS) is a major concern nowadays. Hence, this paper deals with the integration of WLAN, WiMAX and UMTS networks by considering QoS parameter. Further, the integration of these networks are analyzed with loose coupling and tight coupling architecture along with and without QoS. Furthermore, the performance analysis of the above mentioned integrated network for multimedia applications is also done. The simulation is performed through Opnet simulator.

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30

Rosario Núñez, Victor, Alfonso Hernández, Iván Rodríguez, Ignacio Fernández-Pacheco Ruiz, and Luis Acevedo. "Artificial Intelligence Applied to Microwave Heating Systems: Prediction of Temperature Profile through Convolutional Neural Networks." Thermo 4, no. 3 (August 3, 2024): 346–72. http://dx.doi.org/10.3390/thermo4030018.

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Microwave heating, which is caused by the interaction of electromagnetic radiation and materials, has become an important component in industrial operations across numerous industries. Despite their importance, conventional numerical simulations of microwave heating are computationally intensive. Concurrently, advances in artificial intelligence (AI), particularly machine learning algorithms, have transformed data processing by increasing accuracy while decreasing computational time. This study tackles the difficulty of efficient and accurate modelling in microwave heating by combining convolutional neural networks (CNNs) with traditional simulation techniques. The major goal of this research is to use CNNs to forecast temperature profiles in a variety of industrial materials, including susceptors, semi-transparent, and microwave-transparent materials, under varying power settings and heating periods. This unique strategy greatly reduces prediction times, with up to 60-fold speed increases over standard methods. Our research is based on examining the electromagnetic and thermal responses of these materials under microwave heating. This study’s findings emphasise the need for extensive datasets and show the transformational potential of CNNs in optimising material processing. It uses artificial intelligence to pave the way for more effective and exact simulations, supporting breakthroughs in industrial microwave heating applications.

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31

Appasani, Bhargav, and Dusmanta Kumar Mohanta. "A two-stage Markov model–aided frequency-duration technique for reliability analysis of phasor measurement unit microwave communication networks." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 3 (July 20, 2018): 355–68. http://dx.doi.org/10.1177/1748006x18785685.

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The necessity for effective real-time monitoring and control, coupled with the developments in the fields of communication and sensor technologies, led to the emergence of the smart grid. The phasor measurement unit has emerged as an important sensor for the smart grid. The phasor measurement unit communication network is another crucial component which transfers the real-time sensor data measured by the phasor measurement unit to the phasor data concentrator for subsequent monitoring and control. Thus, its reliable operation is essential. The key parameters for assessment of reliability are the failure rate and the steady-state availability. This article presents a two-stage Markov model–aided frequency-duration technique for the reliability analysis of the phasor measurement unit microwave communication networks. Microwave communication network is a complex system as it requires several intermediate relaying towers or the microwave repeaters for communication feasibility. The Markov model explores the transition to the different system states and the frequency-duration approach estimates the frequency and duration of each of these states, thereby providing a simple and elegant means to compute the failure rates of a complex system. It provides a generalized expression for evaluating the systems availability and aids in diagnosing the components that are more prone to failure. Subsequently, this approach is used for the optimal placement of the phasor measurement units such that their resultant microwave communication networks are maximally available. Case study results for the Eastern power grid of India are presented to validate the credibility of the proposed approach.

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32

Kopru, Ramazan. "Termination Transformation Theorem for Microwave Power Transfer Networks." Journal of Circuits, Systems and Computers 29, no. 03 (June 3, 2019): 2050043. http://dx.doi.org/10.1142/s0218126620500437.

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Termination transformation theorem (TTT) proposed in this work transforms a doubly complex terminated microwave power transfer network (PTN) to an equivalent doubly resistively terminated termination transformed network (TTN) which is essentially a filter network. In this work, the transducer power gain (TPG) formula, Tgen, based on S and transmission (ABCD) parameters for the PTN have been restudied from the classical literature. Then, a new TPG formula, Tgen1, based on the newly proposed TTT has been derived using the transformed TTN network. To be able to show the validity of the proposed TTT, the newly derived TPG formula Tgen1 and the classical TPG formula Tgen have been computed within the scope of an example PTN design. The theorem has been proved mathematically, and experimentally as well with the aid of a Matlab code. The performance plots yielded from the Matlab code have clearly shown that both TPG formulae, i.e., Tgen and Tgen1, are in complete agreement with each other. In that sense, the proposed TTT might be considered as an alternative and helpful technique to be used in microwave engineering.

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33

Shiryaev, Boris, Aleksey Bezruk, Dmitry Argunov, and Aleksey Yushchenko. "Algorithm for automated visual inspection of MMIC using a classifier based on neural networks." ITM Web of Conferences 30 (2019): 04012. http://dx.doi.org/10.1051/itmconf/20193004012.

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We present the algorithm for automated visual inspection of microwave monolithic integrated circuits (MMIC) using computer vision and artificial neural networks. The artificial neural network classifies each pixel of a microphotograph to a certain photomask area. The algorithm detects defectiveness of an MMIC according to classification result and photomask comparison.

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34

David, Noam, Omry Sendik, Hagit Messer, and Pinhas Alpert. "Cellular Network Infrastructure: The Future of Fog Monitoring?" Bulletin of the American Meteorological Society 96, no. 10 (October 1, 2015): 1687–98. http://dx.doi.org/10.1175/bams-d-13-00292.1.

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Abstract Severe visibility limitations resulting from fog may lead to acute transportation accidents and high losses of property and lives. Thus, reliable monitoring facilities are of extreme importance. Nevertheless, current monitoring instruments suffer from low spatial resolution, high costs, or lack of precision at near-surface levels. It has, however, recently been shown that the commercial microwave links that form the infrastructure of cellular communication networks can provide crucial information regarding the appearance of dense fog and its intensity. Typical microwave systems currently in operation make use of frequencies between 6 and 40 GHz and, thus, can only monitor heavy fog. However, there is a growing demand for high data rates and expanded bandwidth in modern mobile radio networks. As a result, higher frequencies (e.g., around 80 GHz) are being implemented in order to fulfill these increased requirements. Notably, the attenuation induced as a result of fog at a given intensity increases as operating frequency rises, allowing, for the first time, the possibility of using this system to monitor typical fog intensities, at high resolution and low cost. Here, a theoretical simulation is presented in which simulated fog patches are introduced into an area where a network of links is deployed. Two-dimensional maps are generated utilizing the simulated microwave network to represent sensitivity thresholds for fog detection at three different frequencies: 20, 38, and 80 GHz. Real-data measurements of fog are also demonstrated using 38-GHz band links. The results indicate the vast future potential of commercial microwave links as an opportunistic system for monitoring fog.

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35

Irwansyah, Irwansyah, Ade Davy Wiranata, Tupan Tri Muryono, and Agus Budiyantara. "SISTEM PAKAR DETEKSI KERUSAKAN JARINGAN LOCAL AREA NETWORK (LAN) MENGGUNAKAN METODE BECKWARD CHAINING BERBASIS WEB." Infotech: Journal of Technology Information 8, no. 2 (November 30, 2022): 135–42. http://dx.doi.org/10.37365/jti.v8i2.150.

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The form of computer network connection can be via cable or wireless such as fiber optic, microwave, wireless, or satellite. One type of computer network that is often used to connect personal computers and workstations in an office or an organization, company or factory for the use of shared resources is a local area network. The purpose of this research is to analyze, design and create an application that can detect damage to Local Area Network (LAN) networks. The research method used is backward chaining. The results of this study are applications that can detect damage to local area networks using the web-based backward chaining method. With this expert system application, it can speed up and make it easier to detect damage to Local Area Network networks.

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36

Sedoyeka, Eliamani, and Ziad Hunaiti. "WiMAX Networks." International Journal of Handheld Computing Research 3, no. 4 (October 2012): 72–86. http://dx.doi.org/10.4018/jhcr.2012100105.

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Every new technology comes with its challenges and lessons to be learnt. With a number of unknowns, deploying a new technology becomes a challenge. Worldwide Interoperability for Microwave Access (WiMAX) is one of these new technologies currently on the rise. This paper presents the finding of the research conducted to investigate technical and non technical aspects of network operators in Tanzania. The research looked into WiMAX network operational challenges faced by the network owners as well as the level of services experienced by the end users. This paper is suitable researchers, network operators and investors interested in WiMAX technology. It is mostly usefully for those looking into solutions to problem facing rural and remote areas of the world. The research is discussed in detail throughout of the article.

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37

Huang, Le, Jingru Chen, Bingjun Liu, Pengfei Zhao, Lusheng Liao, Jinlong Tao, Yueqiong Wang, Bingbing Wang, Jing Deng, and Yanfang Zhao. "Morphology and Microwave-Absorbing Performances of Rubber Blends with Multi-Walled Carbon Nanotubes and Molybdenum Disulfide." Nanomaterials 13, no. 10 (May 15, 2023): 1644. http://dx.doi.org/10.3390/nano13101644.

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This study details microwave-absorbing materials made of natural rubber/nitrile butadiene rubber (NR/NBR) blends with multi-walled carbon nanotubes (MWCNTs) and molybdenum disulfide (MoS2). The mechanical blending method and the influences of fabrication on the morphology and microwave-absorbing performance of resulting compounds were logically investigated. It was found that interfacial differences between the fillers and matrix promote the formation of MWCNTs and MoS2 networks in NR/NBR blends, thus improving microwave-absorbing performance. Compared with direct compounding, masterbatch-based two-step blending is more conducive to forming interpenetrating networks of MWCNTs/MoS2, endowing the resulting composite with better microwave attenuation capacity. Composites with MWCNTs in NR and MoS2 in NBR demonstrate the best microwave-absorbing performance, with a minimum reflection loss of −44.54 dB and an effective absorption bandwidth of 3.60 GHz. Exploring the relationship between morphology and electromagnetic loss behavior denotes that such improvement results from the selective distribution of dual fillers, inducing networking and multi-component-derived interfacial polarization enhancement.

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38

Michalski, Jerzy Julian. "ARTIFICIAL NEURAL NETWORKS APPROACH IN MICROWAVE FILTER TUNING." Progress In Electromagnetics Research M 13 (2010): 173–88. http://dx.doi.org/10.2528/pierm10053105.

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39

Rosolowski, Dawid, Wojciech Wojtasiak, and Daniel Gryglewski. "27 dBm Microwave Amplifiers with Adaptive Matching Networks." International Journal of Electronics and Telecommunications 57, no. 1 (March 1, 2011): 103–8. http://dx.doi.org/10.2478/v10177-011-0015-x.

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27 dBm Microwave Amplifiers with Adaptive Matching Networks The paper describes adaptive amplifier design with varactors and pin diodes as regulators of matching networks. As examples the two amplifiers with SHF-0189 HFET transistor and different matching sections were designed and manufactured. The output power level of 27 dBm and gain higher than 13 dB within L and S-band have been achieved. The amplifier design methodology is based on the small-signal approach and DC characteristics of transistors and regulators. Amplifier adaptivity allows us to remotely control the chosen parameters such as: frequency range, output power level, gain and etc.

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40

Haynes, Mark. "Series Reversion Solution for MIMO Microwave Feed Networks." IEEE Transactions on Microwave Theory and Techniques 61, no. 10 (October 2013): 3794–99. http://dx.doi.org/10.1109/tmtt.2013.2279376.

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41

Stojilovic, Mirjana, Marcos Rubinstein, and Antonije R. Djordjevic. "Quasi-Impulse Response of Frequency-Periodic Microwave Networks." IEEE Transactions on Electromagnetic Compatibility 58, no. 2 (April 2016): 468–76. http://dx.doi.org/10.1109/temc.2015.2513009.

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42

Sussman-Fort, Stephen E. "The computer-aided design of microwave matching networks." International Journal of Microwave and Millimeter-Wave Computer-Aided Engineering 1, no. 3 (1991): 288–305. http://dx.doi.org/10.1002/mmce.4570010307.

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43

Hallbjörner, Paul. "Simplified calculations on some common passive microwave networks." Microwave and Optical Technology Letters 29, no. 4 (April 10, 2001): 285–88. http://dx.doi.org/10.1002/mop.1156.

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44

Bogdanov, Sergey. "Application of Neural Networks in the Construction of Nonlinear Models of Field-Effect Transistors." Infocommunications and Radio Technologies 5, no. 1 (March 25, 2022): 45–53. http://dx.doi.org/10.29039/2587-9936.2022.05.1.03.

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The nonlinear model of a field-effect transistor based on the mathematical apparatus of the theory of artificial neural networks was developed. The main feature of this model is the possibility of training neural networks used to approximate the current-voltage characteristic and the gate-drain and gate-source capacitances of a nonlinear transistor model by using optimization algorithms built into popular microwave CAD systems. This makes it possible to use the well-known advantages of neural networks in the problems of function approximation to increase the reliability of the results of non-linear modeling of microwave devices based on field-effect transistors.

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45

Araujo, Elsie, Armando Encinas, Yenni Velázquez-Galván, Juan Manuel Martínez-Huerta, Gaël Hamoir, Etienne Ferain, and Luc Piraux. "Artificially modified magnetic anisotropy in interconnected nanowire networks." Nanoscale 7, no. 4 (2015): 1485–90. http://dx.doi.org/10.1039/c4nr04800h.

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Track etched polycarbonate membranes produced using a double energetic heavy ion irradiation with fixed incidence angles as templates to fabricate crossed magnetic nanowire networks with tunable magnetic anisotropy and microwave absorption properties.

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46

Ostrometzky, Jonatan, Dani Cherkassky, and Hagit Messer. "Accumulated Mixed Precipitation Estimation Using Measurements from Multiple Microwave Links." Advances in Meteorology 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/707646.

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Recently, microwave communication networks have been shown to be valuable tools for rainfall monitoring, based on the well-known Power-Law which relates rain-rate to attenuation in microwave frequencies. However, once precipitation other than pure rain exists (e.g., snow), the Power-Law relation is no longer accurate. In this paper we propose a model which relates the induced attenuation to rain, snow, and sleet. Based on this model we propose estimating the total accumulated precipitation, regardless of the precipitation type, using measurements from multiple microwave links. Our technique takes advantage of the commercial communication networks, need for redundancy, which dictates the use of multiple microwave links at the same area. We show that by using measurements from at least three microwave links better estimation of the total accumulated precipitation fall can be provided, when rain, snow, sleet, or a mixture of them coexists. To demonstrate the proposed approach, it has been applied on actual microwave links attenuation measurements, which were provided by a cellular carrier. The estimation results were compared with Rain-Gauges and disdrometer measurements and show very good agreement and improved accuracy.

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47

Tan, Xiangyang, Kaixue Ma, and Fangli Dou. "A Convolutional Neural Network and Attention-Based Retrieval of Temperature Profile for a Satellite Hyperspectral Microwave Sensor." Atmosphere 15, no. 2 (February 17, 2024): 235. http://dx.doi.org/10.3390/atmos15020235.

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As numerical weather forecasting advances, there is a growing demand for higher-quality atmospheric data. Hyperspectral instruments can capture more atmospheric information and increase vertical resolution, but there has been limited research into retrieval algorithms for obtaining hyperspectral microwaves in the future. This study proposes an atmospheric temperature profile detection algorithm based on Convolutional Neural Networks (CNN) and Local Attention Mechanisms for local feature extraction, applied to hyperspectral microwave sensors. The study utilizes the method of information entropy to extract more effective channels in the vicinities of 60 GHz, 118 GHz, and 425 GHz. The algorithm uses the brightness temperature as the input of the network. The algorithm addresses common issues encountered in conventional networks, such as overfitting, gradient explosion, and gradient vanishing. Additionally, this method isolates the three oxygen-sensitive frequency bands for modularized local feature extraction training, thereby avoiding abrupt changes in brightness temperature between adjacent frequency bands. More importantly, the algorithm considers the correlation between multiple channels and information redundancy, focusing on variations in local information. This enhances the effectiveness of hyperspectral microwave channel information extraction. We simulated the brightness temperatures of the selected channels through ARTS and divided them into training, validation, and test sets. The retrieval capability of the proposed method is validated on a test dataset, achieving a root mean square error of 1.46 K and a mean absolute error of 1.4 K for temperature profile. Detailed comparisons are also made between this method and other commonly used networks for atmospheric retrieval. The results demonstrate that the proposed method significantly improves the accuracy of temperature profile retrieval, particularly in capturing fine details, and is more adaptable to complex environments. The model also exhibits scalability, extending from one-dimensional (pressure level) to three-dimensional space. The error for each pressure level is controlled within 0.7 K and the average error is within 0.4 K, demonstrating effectiveness across different scales with impressive results. The computational efficiency and accuracy have both been improved when handling a large amount of radiation data.

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48

Yadav, Rahul, Adel Omrani, Guido Link, Marko Vauhkonen, and Timo Lähivaara. "Microwave Tomography Using Neural Networks for Its Application in an Industrial Microwave Drying System." Sensors 21, no. 20 (October 19, 2021): 6919. http://dx.doi.org/10.3390/s21206919.

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The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities.

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49

Goldstein, Samuel, Guy Pardo, Naftali Kirsh, Niklas Gaiser, Ciprian Padurariu, Björn Kubala, Joachim Ankerhold, and Nadav Katz. "Compact itinerant microwave photonics with superconducting high-kinetic inductance microstrips." New Journal of Physics 24, no. 2 (February 1, 2022): 023022. http://dx.doi.org/10.1088/1367-2630/ac45cc.

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Abstract Microwave photonics is a remarkably powerful system for quantum simulation and technologies, but its integration in superconducting circuits, superior in many aspects, is constrained by the long wavelengths and impedance mismatches in this platform. We introduce a solution to these difficulties via compact networks of high-kinetic inductance microstrip waveguides and coupling wires with strongly reduced phase velocities. We demonstrate broadband capabilities for superconducting microwave photonics in terms of routing, emulation and generalized linear and nonlinear networks.

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50

Agrawal, Anurag Vijay, and Meenakshi Rawat. "Reliable Integrated Satellite Terrestrial Communications using MIMO for Mitigation of Microwave Absorption by Earths Oxygen." Defence Science Journal 69, no. 5 (September 17, 2019): 458–63. http://dx.doi.org/10.14429/dsj.69.14951.

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Microwaves are used to communicate with satellite and terrestrial communication networks. But as microwaves pass through the Earth’s atmosphere, the oxygen gas absorbs microwave. In this 5G era, when the whole world is moving towards high data-rates and reliable communications, this absorption affects the data transmission in Integrated Satellite/Terrestrial Communication (ISTC) systems, which leads to degradation of the system performance. The multiple-input-multiple-output (MIMO) technology has become a boon for modern wireless communication systems to achieve the necessities of higher data-rates and communication reliability. The paper analyses the MIMO effect on block error rate (BLER), error vector magnitude (EVM) and throughput performance of the data transmission with different MIMO configurations. The paper establishes that better data-rates as well as reliable data communication is achieved with higher order MIMO configurations. MIMO 8×1 provides 5, 20 and 42.5 times improved performance to BLER; 5.26%, 25% and 81.82% in throughput; and 10.34%, 23.07% and 28% in EVM calculations as comparable to MIMO 4×1, MIMO 2×1 and SISO 1×1, respectively at 15 dB signal-to-noise ratio (SNR). The authors also give a new concept of multi-cellular layers based mobile communication network, useful for future smart cities.

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