Full-time study

4 years

doc. Ing. Martin Štumpf, Ph.D.

Chairman :
doc. Ing. Martin Štumpf, Ph.D.
Councillor internal :
prof. Ing. Aleš Prokeš, Ph.D.
doc. Ing. Jiří Petržela, Ph.D.
doc. Ing. Jaroslav Láčík, Ph.D.
doc. Ing. Roman Šotner, Ph.D.
doc. Ing. Tomáš Götthans, Ph.D.
prof. Dr. Ing. Zbyněk Raida
Councillor external :
Ing. Ondřej Číp, Ph.D.
doc. Ing. Milan Polívka, Ph.D.

Provide doctoral education to graduates of a master's degree in electronics and communication technologies. To deepen students' theoretical knowledge in selected parts of mathematics and physics and to give them the necessary knowledge and practical skills in applied informatics and computer science. To teach them the methods of scientific work.

The Ph.D. graduate will be able to solve scientific and complex technical problems in the field of electronics and communications. Graduates of the doctoral program "Electronics and Communication Technologies" will be competent to work in the field of electronics and communication technology as scientists and researchers in fundamental or applied research, as high-specialists in development, design, and construction in many R&D institutions, electrical and electronic manufacturing companies and producers and users of communication systems and devices, where they will be able to creatively use modern computer, communication, and measurement technique.

The doctors are able to solve independently scientific and complex engineering tasks in the area of electronics and communications. Thanks to the high-quality theoretical education and specialization in the study program, graduates of doctoral studies are sought as specialists in in the area of electronic engineering and communications. Graduates of the doctoral program will be able to work in the field of electronics and communications technology as researchers in fundamental or applied research, as specialists in development, design and construction in various research and development institutions, electrotechnical and electronic manufacturing companies, where they will be able to creative exploit modern computing, communication and measuring technologies.

Doctoral studies are carried out in agreement with the individual study plan, which will prepare supervisor together with the doctoral student at the beginning of the study. The individual study plan specifies all the duties given by the BUT Study and Examination Rules, which the doctoral student must fulfill to finish his study successfully. These duties are scheduled into entire the study period. They are classified by points and their fulfilment is checked at fixed deadlines. The student enrolls and performs examination from compulsory subjects (Modern digital wireless communication, Modern electronic circuit design), at least from two compulsory-elective subjects aimed at the dissertation area, and at least from two optional courses such as English for PhD students, Solutions for Innovative Entries, Scientific Publishing from A to Z).
The students may enroll for the state exam only if all the examinations specified in his/her individual study plan have been completed. Before the state exam, the student prepares a short version of dissertation thesis describing in detail the aims of the thesis, state of the art in the area of dissertation, eventually the properties of methods which are assumed to be applied in the research topics solution. The defense of the short version of thesis, which is reviewed, is the first part of the state exam. In the next part of the exam the student has to prove deep theoretical and practical knowledges in the field of electrical engineering, electronics, communication techniques, fundamental theory of circuits and electromagnetic field, signal processing, antenna and high-frequency techniques. The state exam is oral and, in addition to the discussion on the dissertation thesis, it also consists of areas related to compulsory and compulsory elective courses.
The student can ask for the dissertation defense after successful passing the state exam and after fulfilling all conditions for termination of studies such as participation in teaching, scientific and professional activities (creative activities), and a study or a work stay at a foreign institution no shorter than one month, or participation in an international project.

The doctoral studies of a student follow the Individual Study Plan (ISP), which is defined by the supervisor and the student at the beginning of the study period. The ISP is obligatory for the student, and specifies all duties being consistent with the Study and Examination Rules of BUT, which the student must successfully fulfill by the end of the study period. The duties are distributed throughout the whole study period, scored by credits/points and checked in defined dates. The current point evaluation of all activities of the student is summarized in the “Total point rating of doctoral student” document and is part of the ISP. At the beginning of the next study year the supervisor highlights eventual changes in ISP. By October, 15 of each study year the student submits the printed and signed ISP to Science Department of the faculty to check and archive.
Within the first four semesters the student passes the exams of compulsory, optional-specialized and/or optional-general courses to fulfill the score limit in Study area, and concurrently the student significantly deals with the study and analysis of the knowledge specific for the field defined by the dissertation thesis theme and also continuously deals with publishing these observations and own results. In the follow-up semesters the student focuses already more to the research and development that is linked to the dissertation thesis topic and to publishing the reached results and compilation of the dissertation thesis.
By the end of the second year of studies the student passes the Doctor State Exam, where the student proves the wide overview and deep knowledge in the field linked to the dissertation thesis topic. The student must apply for this exam by April, 30 in the second year of studies. Before the Doctor State Exam the student must successfully pass the exam from English language course.
In the third and fourth year of studies the student deals with the required research activities, publishes the reached results and compiles the dissertation thesis. As part of the study duties is also completing a study period at an abroad institution or participation on an international research project with results being published or presented in abroad or another form of direct participation of the student on an international cooperation activity, which must be proved by the date of submitting the dissertation thesis.
By the end of the winter term in the fourth year of study the students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The final dissertation thesis is expected to be submitted by the student by the end of the fourth year of the studies.
In full-time study form, during the study period the student is obliged to pass a pedagogical practice, i.e. participate in the education process. The participation of the student in the pedagogical activities is part of his/her research preparations. By the pedagogical practice the student gains experience in passing the knowledge and improves the presentation skills. The pedagogical practice load (exercises, laboratories, project supervision etc.) of the student is specified by the head of the department based on the agreement with the student’s supervisor. The duty of pedagogical practice does not apply to students-payers and combined study program students. The involvement of the student in the education process within the pedagogical practice is confirmed by the supervisor in the Information System of the university.

1. AI-based Estimation of Signal Coverage and Performance in Cellular Networks

   In contemporary industries, there is a growing need for robust technical platforms capable of handling large volumes of data generated by various sensors, while maintaining high levels of reliability. Cellular and wireless networks have emerged as vital components in meeting these requirements. As the adoption of these networks continues to expand, it becomes increasingly important to understand factors such as signal coverage, reliability, and capacity to optimize performance and ensure seamless connectivity, especially in complex environments such as manufacturing facilities. The utilization of professional hardware equipment and software tools is often necessary to facilitate the collection and analysis of data from these networks [1]-[3]. Recent research [3], [4] suggests that machine and deep learning (ML and DL) technologies could offer effective solutions for estimating signal coverage provided by cellular networks and improving forecasting capabilities in terms of cellular network performance. This work is focused on the research in the development of advanced ML and DL algorithms for estimating signal coverage and performance in 4G/5G cellular networks. The initial phase involves defining the essential Key Performance Indicators (KPIs) associated with measuring and evaluating the performance of 4G/5G networks, as well as establishing principles for conducting long-term measurements to collect data. A portable measurement setup equipped with suitable hardware and software tools will be developed to facilitate the long-term collection and processing of data from indoor and outdoor measurements. During these measurements, various environmental factors will be examined (such as the time of day and its impact on network load due to population mobility), which can affect the quality of radio connections in wireless communications. These collected data, among others, will be used to construct coverage maps for the measured areas. Leveraging the multitude of parameters available, ML and DL architectures will be employed to extract and learn more features from the data. The research will focus on developing, validating, and optimizing artificial intelligence models and algorithms (ML and DL) to improve the prediction of cellular signal quality and coverage under various scenarios and transmission conditions. The ML/DL algorithms must strike a balance between complexity, accuracy, and efficiency. They are expected to be implemented in Python or MATLAB using available libraries (such as PyTorch, Keras, TensorFlow) and toolboxes (such as Deep Learning Toolbox), respectively. Ultimately, the dataset obtained from long-term measurement campaigns, along with the ML/DL models and algorithms, will be made freely available to the wider scientific community. This approach ensures not only the reproducibility of the achieved results but also serves as the foundation for further research and development in the field of wireless and cellular communications. References: [1] V. Raida, P. Svoboda, M. Koglbauer and M. Rupp, "On the Stability of RSRP and Variability of Other KPIs in LTE Downlink – An Open Dataset," GLOBECOM 2020–2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020, pp. 1-6, doi: 10.1109/GLOBECOM42002.2020.9348145. [2] M. Rochman and et al., " A comprehensive analysis of the coverage and performance of 4G and 5G deployments," Computer Networks, vol. 237, pages 110060, 2023, doi: 10.1016/j.comnet.2023.110060. [3] L. Zhang, X. Chu and M. Zhai, "Machine Learning-Based Integrated Wireless Sensing and Positioning for Cellular Network," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-11, 2023, Art no. 5501011, doi: 10.1109/TIM.2022.3224513. [4] A. Al-Thaedan and et al., „A machine learning framework for predicting downlink throughput in 4G-LTE/5G cellular networks,“ Int. j. inf. tecnol., vol. 16, pp. 651–657, 2024, doi: 10.1007/s41870-023-01678-w.

   Tutor: Polák Ladislav, doc. Ing., Ph.D.

2. Electromagnetic analysis of time-varying metasurfaces

   The space-time electromagnetic behavior of metasurfaces whose constitutive properties are time-invariant has been extensively studied and is well understood. The demanding objectives of 6G communication systems, however, call for the use of unconventional intelligent technologies that would overcome physical bounds of standard time-invariant systems. A promising hardware technology to achieve the goal is the reconfigurable intelligent metasurface whose electromagnetic properties vary in response to time-varying environments. As the state-of-the-art electromagnetic modeling approaches do not allow its efficient analysis, the PhD research will yield fundamentally new computational and analytical approaches to address the issue, thereby providing key enablers for designing truly intelligent time-varying metasurfaces. Owing to their unrivalled computational efficiency, particular attention will be paid to analytical solutions and time-domain integral equation approaches based on the Cagniard-DeHoop technique.

   Tutor: Štumpf Martin, doc. Ing., Ph.D.

3. Memetic Algorithms for Multi-objective Optimization of EM Structures

   The vast majority of design tasks are multi-objective where we try to minimize/maximize several parameters of the designed system at once. These parameters are often in conflict and it is then advantageous to know the shape of the Pareto front expressing the trade-off between the parameters [1]. Existing global algorithms for multi-objective optimization are able to find trade-off solutions lying close to the Pareto front, but they work very inefficiently. Therefore, it is proposed to combine them with local algorithms (e.g., Newton's method, conjugate gradient method, etc.) that converge very quickly to local minima, but require only a single-objective formulation. Thus, the subject of this Ph.D. thesis will be to develop a so-called memetic algorithm [2] that appropriately combines global multi-objective algorithms with efficient local algorithms. The memetic algorithm will be implemented in the FOPS toolbox [3] written in MATLAB. Then, the memetic algorithm will be used to design advanced EM components such as antennas, filters, etc. [1] DEB, Kalyanmoy. Multi-objective optimization using evolutionary algorithms. Wiley paperback series. Chichester: John Wiley, c2001. ISBN 0-471-87339-X. [2] CAPEK, Miloslav; JELINEK, Lukas; KADLEC, Petr a GUSTAFSSON, Mats. Optimal Inverse Design Based on Memetic Algorithms—Part I: Theory and Implementation. Online. IEEE Transactions on Antennas and Propagation. 2023, roč. 71, č. 11, s. 8806-8816. ISSN 0018-926X. Dostupné z: https://doi.org/10.1109/TAP.2023.3308587. [cit. 2024-03-19]. [3] MAREK, Martin; KADLEC, Petr a ČAPEK, Miloslav. FOPS: A new framework for the optimization with variable number of dimensions. Online. International Journal of RF and Microwave Computer-Aided Engineering. 2020, roč. 30, č. 9. ISSN 1096-4290. Dostupné z: https://doi.org/10.1002/mmce.22335. [cit. 2024-03-19].

   Tutor: Kadlec Petr, doc. Ing., Ph.D.

4. Millimeter wave channel characterization using machine learning

   Steadily growing number of communication devices per area and increasing quality of services require allocation of more frequency resources. Millimeter wave (MMW) frequencies between 30 and 300 GHz have been attracting growing attention as a possible candidate for next-generation broadband cellular networks. Specific limitations of MMW signal propagation, extremely large bandwidth and time variable environment caused by mobile users connected to a backhaul networks traveling in rugged municipal environments create unprecedented challenges to the development of broadband communication systems using advanced technologies for eliminating the undesirable time varying channel features. The general objective of the project is measurement and modelling of the broadband time varying MMW channels between mobile users and infrastructure in delay and spatial domain and extension of our previous research focused on the characterization of intra-vehicle and V2X channels for the purposes of stochastic channel modeling [1]. The parametrization of channel models needs an accurate extraction of the channel parameters such as number, position and amplitudes of multipath components (MPC), clusters, LOS, and NLOS components, etc. in the delay and spatial domains from measured data. Real time capturing of MPCs in a very wide spatial angle is provided, for example, by measuring systems with a fast-spinning antenna. However, such a system produces a huge amount of data. Thus, to get all the MPC related parameters, some automated algorithm is needed. Such algorithms are based for example on identifying the changes in the slope of a channel impulse response or generally on parameter threshold-based identification. Due to the limited accuracy and reliability of many of these methods, we are going to use machine learning (ML) techniques such as Gaussian Mixture Model or K-means algorithm for gathering MPCs with similar parameters behavior [2]. Further the project also envisages the use of supervised ML such as Deep Neural Networks or Support Vector Machine to predict and estimate the channel parameters and examine large and small-scale fading including parameters such as path loss, delay path loss exponent, Doppler spread, angle of arrival, and other variables describing the channel [3]. The above algorithms are expected to be implemented using Machine Learning Workflow with Keras, Tensorflow, and Python [4]. An alternative implementation in MATLAB also possible. The student will be a member of the international team of scientists from Brno University of Technology, TU Vienna, Austrian Institute of Technology Vienna, University of Southern California, National Institute of Technology Durgapur India, and Military University of Technology Warsaw. [1] E. Zöchmann, M. Hofer, M. Lerch, S. Pratschner, L. Bernado, J. Blumenstein, S. Caban, S. Sangodoyin, H. Groll, T. Zemen, A. Prokeš, M. Rupp, A. Molisch, C. Mecklenbräuker, Position-Specific Statistics of 60 GHz Vehicular Channels During Overtaking. IEEE Access, 2019, vol. 7, no. 1, p. 14216-14232. [2] S. M. Aldossari, K.C. Chen, Machine Learning for Wireless Communication Channel Modeling: An Overview, Wireless Personal Communications, 2019, 106, p. 41 – 70. [3] R. A. Osman, S. N. Saleh, Y. N. M. Saleh, M. N. Elagamy, Enhancing the Reliability of Communication between Vehicle and Everything (V2X) Based on Deep Learning for Providing Efficient Road Traffic Information. Applied Science, 2021, vol. 11, art. no. 11382. [4] C. A. Mattmann, Machine Learning with TensorFlow, Second Edition, Manning Publications, 2021.

   Tutor: Prokeš Aleš, prof. Ing., Ph.D.

5. Novel analog blocks, concepts and methods for sensing and processing of electrical and nonelectrical quantities

   The integrated circuits are very important for processing of signals from sensors and sensor readouts as a part of modern physical layer of communication systems [1], [2]. They offer significant minimization of system area and low power consumption. Therefore, these concepts are highly useful for biomedical applications (blood analysis – presence of various chemicals, bio-impedances measurement and evaluation, etc. [3], [4]), in mechanics (distance influences capacity) [5], etc. This topic includes study of utilization of discrete of-the-shelf as well as integrated active building cells and blocks (amplifiers, converters, generators, flip-flop circuits, etc.) and study of features of currently available types of sensors for various physical quantities. The recommendations, requirements, models, methodologies and specific solutions for various specific active sensor readouts and processing of signals are expected to be formulated for proposals of novel and advanced systems. The initial state of work concentrates on review of state of the art in discussed areas and results achieved at the workplace. It allows to find the most suitable specific topic (methodology, verification and measurement, modeling, discrete/integrated analog/mixed low-power or complex systems design) fitting to interests of candidate. These activities expect involvement in experimental work (in frame of projects of basic research – cooperation with research team including foreign experts) on design and implementation of integer-order as well as fractional-order circuits [4], modules (sensing readouts) [5] and components in discrete or integrated form and writing and dissemination of publications. This specialization offers significant enhancement of skills and competences in work with modern software tools (PSpice, Cadence Virtuoso/Spectre) of analog/mixed design approaches and further experience in detailed principles of advanced circuit solutions including cooperation on design of application specific integrated circuit. References [1] R. Sotner, J. Jerabek, L. Polak, J. Petrzela, W. Jaikla and S. Tuntrakool, “Illuminance Sensing in Agriculture Applications Based on Infra-Red Short-Range Compact Transmitter Using 0.35 um CMOS Active Device.” IEEE Access, vol. 8, pp. 18149-18161, 2020, doi: 10.1109/ACCESS.2020.2966752 [2] R. Sotner, L. Polak, J. Jerabek, “Low-cost remote distance and height sensing analog device for laboratory agriculture environments.” Measurement Science and Technology, online first, 2022, doi: 10.1088/1361-6501/ac543c [3] C. Vastarouchas, C.Psychalinos, A.S. Elwakil, A.A.Al-Ali, “Novel Two-Measurements-Only Cole-Cole Bio-Impedance Parameters Extraction Technique.” Measurement, vol. 131, pp. 394–399, 2019. doi: 10.1016/j.measurement.2018.09.008 [4] S. Kapoulea, C. Psychalinos, A. S. Elwakil, “Realization of Cole-Davidson function-based impedance models: Application on Plant Tissues.” Fractal and Fractional Journal, vol. 4, 54, 2020. doi: 10.3390/fractalfract4040054 [5] L. Polak, R. Sotner, J. Petrzela, J. Jerabek, “CMOS Current Feedback Operational Amplifier-Based Relaxation Generator for Capacity to Voltage Sensor Interface.” Sensors, vol. 18, 4488, 2018. doi: 10.3390/s18124488

   Tutor: Šotner Roman, doc. Ing., Ph.D.

6. Physical layer security methods for 5G/6G networks

   In the future generation of 6G mobile communication systems, some innovative technologies and approaches are foreseen - for example, reconfigurable smart surfaces or sharing of radio resources for simultaneous communication and sensing (e.g. radar-based). Moreover, we are already witnessing the development of so-called OpenRAN, i.e., open radio access networks. One of the currently explored alternative approaches to increase the security and robustness of wireless networks is to exploit the properties of the physical layer parameters (PHY layer security) - for example, knowledge of the radio channel between the user and the base station, or hidden hardware differences of individual transmitters (nonlinearity, IQ asymmetry, etc.). The aim of this work is to assess how the performance of these methods will be affected (and to propose and evaluate the necessary methods) by the introduction of new technologies for 6G, and conversely how these technologies (e.g. radar-based sensing) can contribute to improving the reliability of communications. As part of the study we expect a student takes part in a Ministry of interior funded project, the international COST project, and there is also a possibility of an internship at one of the collaborating foreign universities.

   Tutor: Maršálek Roman, prof. Ing., Ph.D.

7. Sensing, extraction and modeling of impedance responses of various substances

   Recent development indicated importance of impedance characteristic for many scientific fields (agriculture, food quality and safety, material sciences, biology, biomedicine, etc.) [1]. Current research focuses on design and development of sensing methods applicable for measurement of impedance responses of various substances (solid, liquid, organic, inorganic, …). The research targets on modeling of these characteristics based on data acquisition using various sensing approaches and determined for character of analyzed substance. This work includes evaluation of impact of real measuring arrangement (electrodes, materials, cables, measuring device, conditions, etc.). The most important part of this work includes analysis of obtained results and fitting of measured responses to models represented by electrical circuit as well as symbolical representation of measured impedance. Fractional-order character of circuit elements allows precise and detailed construction of accurate model [2]. The application part of this topic includes development of measuring device (and methods of evaluation) for analysis of measured sample based on comparison with known impedance responses (or with specific bands/frequencies of these responses). The initial state of work concentrates on review of state of the art in discussed areas and results achieved at the workplace. It allows to find the most suitable specific topic (methodology, verification and measurement, modeling, discrete/integrated analog/mixed low-power or complex systems design) fitting to interests of candidate. These activities expect involvement in experimental work (in frame of projects of basic research – cooperation with research team including foreign experts) on design and implementation of integer-order as well as fractional-order circuits, modules (sensing readouts) [3] and components in discrete or integrated form and writing and dissemination of publications. This specialization offers significant enhancement of skills and competences in work with modern software tools (PSpice, Cadence Virtuoso/Spectre) of analog/mixed design, further experience with laboratory equipment (vector network analyzer, impedance analyzer) and instrumentation (development of measuring device incl. sensing readouts). [1] T. J. Freeborn, “A Survey of Fractional-Order Circuit Models for Biology and Biomedicine.” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 3, no. 3, pp. 416-424, 2013. [2] S. Kapoulea, C. Psychalinos, A. S. Elwakil, “Realization of Cole-Davidson function-based impedance models: Application on Plant Tissues.” Fractal and Fractional Journal, vol. 4, 54, 2020, doi: 10.3390/fractalfract4040054 [3] R. Sotner, L. Polak, J. Jerabek, “Low-cost remote distance and height sensing analog device for laboratory agriculture environments.” Measurement Science and Technology, vol. 33, no. 6, pp. 1-16, 2022, doi: 10.1088/1361-6501/ac543c

   Tutor: Šotner Roman, doc. Ing., Ph.D.

8. Space compression for guided wave structures at microwave frequencies

   Space compression involves a reduction of free-space distances between optical elements by a thin device/material called a spaceplate [1], [2]. Recently, it gained importance due to novel approaches in the emerging field of non-local metamaterials. The issue of size reduction becomes prominent in quasi-optical systems common to the terahertz and microwave frequency region where the physical size of the elements can be limiting factor in the design process. This project is focused on the research of the space compression for guided wave structures. The problem will be studied on two-dimensional structures such as dielectric slabs, parallel plate waveguide or substrate integrated waveguides. The main attention will be concentrated on the investigation of periodic media and their application to guided wave structures to reach desired space compression. The special attention should be also paid to manufacturing and experimental characterization of the developed structures. References: [1] RESHEF, O., et al., An optic to replace space and its application towards ultra-thin imaging systems, Nature Communication, 2021, vol. 12, art. no. 3512. [2] MRNKA, M., et al., Space squeezing optics: Performance limits and implementation at microwave frequencies. APL Photonics, 2022, vol. 7, no. 7, p. 1-7.

   Tutor: Láčík Jaroslav, doc. Ing., Ph.D.

9. Wireless Communication using Artificial Intelligence

   Nowadays, various wireless communication systems often share common radiofrequency (RF) bands. In the future, the prevalence of scenarios where multiple wireless systems utilize the same RF band is expected to increase. This phenomenon, known as the coexistence of wireless communication systems, can have varying degrees of impact. In some cases, it may lead to critical issues, such as partial or complete loss of wireless services provided by communication systems, while in others, the systems can coexist without significant performance degradation [1]-[3]. Contemporary research [4], [5] suggests that machine learning (ML) and deep learning (DL) technologies could serve as effective tools for enhancing the reliability and efficiency of wireless communication systems, particularly in situations influenced by diverse transmission conditions. This work focuses on developing advanced machine learning (ML) and deep learning (DL) algorithms for classifying coexistence scenarios between different wireless communication systems based on RF signals. Initially, it is essential to define and measure various transmission scenarios for mobile and wireless communication systems operating in licensed and unlicensed RF bands. As part of these measurements, key environmental factors, such as multipath propagation, will be investigated, as they can significantly impact the quality of radio connections in wireless communications. Attention will also be given to studying parameters with the highest influence on the interfering signal's characteristics, such as idle signals and types of digital modulation. These parameters enable ML and DL architectures to learn more features from the data [5]. Subsequently, the research will focus on realizing, validating, and optimizing artificial intelligence models and algorithms (ML and DL) to enhance the efficiency and reliability of wireless communication links under different transmission conditions. The ML/DL models created will be trained and validated using data obtained from real-world, long-term measurement campaigns. The ML/DL algorithms must strike a balance between complexity, accuracy, and efficiency. They are expected to be implemented in Python or MATLAB using available libraries (such as PyTorch, Keras, TensorFlow) and toolboxes (such as Deep Learning Toolbox), respectively. Ultimately, the dataset obtained from long-term measurement campaigns, along with the ML/DL models and algorithms, will be made freely available to the wider scientific community. This approach ensures not only the reproducibility of the achieved results but also serves as the foundation for further research and development in the field of wireless communications. [1] A. M. Voicu, L. Simić and M. Petrova, "Survey of Spectrum Sharing for Inter-Technology Coexistence," IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1112-1144, Secondquarter 2019, DOI: 10.1109/COMST.2018.2882308 [2] D. Zorbas, D. Hacket and B. O'Flynn, " On the Coexistence of LoRa and RF Power Transfer," 2023, First Online: https://www.researchgate.net/publication/368961826_On_the_Coexistence_of_LoRa_and_RF_Power_Transfer8 [3] L. Polak and J. Milos, “ Performance analysis of LoRa in the 2.4 GHz ISM band: coexistence issues with Wi-Fi,” Telecommunication Systems, vol. 74, no. 3, pp. 299-309, July 2020. DOI: 10.1007/s11235-020-00658-w [4] Y. Shi, K. Davaslioglu, Y. E. Sagduyu, W. C. Headley, M. Fowler and G. Green, "Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments," In Proc of. Int. Symp. DySPAN, Nov. 2019, pp. 1-10, DOI: 10.1109/DySPAN.2019.8935684. [5] K. Pijackova and T. Gotthans, "Radio Modulation Classification Using Deep Learning Architectures," In Proc of. 31st Int. Conf. Radioelektronika, Apr. 2021, pp. 1-5, DOI: 10.1109/RADIOELEKTRONIKA52220.2021.9420195.

   Tutor: Polák Ladislav, doc. Ing., Ph.D.