Full-time study

4 years

doc. Ing. Jiří Hošek, Ph.D.

Chairman :
doc. Ing. Jiří Hošek, Ph.D.
Councillor internal :
prof. Ing. Jaroslav Koton, Ph.D.
prof. Ing. Zdeněk Smékal, CSc.
prof. Ing. Jiří Mišurec, CSc.
doc. Ing. Vladislav Škorpil, CSc.
doc. Ing. Radim Burget, Ph.D.
Councillor external :
prof. Ing. Ivan Baroňák, Ph.D.
doc. Ing. Miloš Orgoň, Ph.D.
doc. Ing. Otto Dostál, CSc.

The student is fostered to use the theoretical knowledge and experience gained through own research activities in an innovative manner. He/She is able to efficiently use the gathered knowledge for the design of own and prospective solutions within their further experimental development and applied research. The emphasis is put on gaining both theoretical and practical skill, ability of self-decisions, definition of research and development hypotheses to propose projects spanning from basic to applied research, ability to evaluation of the results and their dissemination as research papers and presentation in front of the research community.

The doctor study program "Electronics and Information Technologies" aims to generate top research and development specialists, who have deep knowledge of principles and techniques used in communication and data wired and wireless networks and also in related areas and also in data/signal acquisition, processing and the back representation of user data on the level of application layer. The main parts of the studies are represented by areas dealing with information theory and communication techniques. The graduate has deep knowledge in communication and information technologies, data transfer and their security. The graduate is skilled in operation systems, computer languages and database systems, their usage and also design of suitable software and user applications. The graduate is able to propose new technology solution of communication tools and information systems for advanced transfer of information.

Graduates of theprogram "Electronics and Information Technologies" apply in particular in research, development and design teams, in the field of professional activity in production or business organizations, in the academic sphere and in other institutions involved in science, research, development and innovation, in all areas of the company where communication systems and information transfer through data networks are being applied and used.
Our graduates are particularly experienced in the analysis, design, creation or management of complex systems aimed for data transfer and processing, as well as in the programming, integration, support, maintenance or sale of these systems.

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 mainly 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 full-time students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The combined students submit the elaborated dissertation thesis by the end of winter term in the fifth year of study. The final dissertation thesis is expected to be submitted by the student by the end of the fourth or fifth year of the full-time or combined study form, respectively.
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-Aided Wireless Communication in Emerging Aerial Applications

   The rapid advancement of the next-generation wireless communication technologies and artificial intelligence (AI) has led to the development of new techniques for improving communication in high mobility applications, including mmWave communications and unmanned aerial vehicle (UAV) applications. This doctoral topic deals first with an overview of the state-of-the-art AI-aided wireless communication technologies in different aerial applications, highlighting their capabilities and limitations. Later, the research should focus on the challenges associated with ultra-reliable low latency communications (URLLC) in 5G+ wireless systems. The key goal of this topic is a design of novel AI-aided technique than will help in overcoming current challenges and issues related to the deployment of 5G+ mobile networks. Moreover, the thesis should also explore the potential benefits of AI-aided wireless communication technologies in mmWave networks, including improved performance, reliability, and energy efficiency.

   Tutor: Hošek Jiří, doc. Ing., Ph.D.

2. Content Delivery Networks

   Content Delivery Networks (CDN) are used to provide fast delivery of data. The data are replicated and located at different geographical places. The goal of the study is to optimize data replication based on selected criteria, such as to reduce the time to access the data and balance the load of the servers.

   Tutor: Komosný Dan, prof. Ing., Ph.D.

3. Digital data forensics

   The study deals with forensic methods to obtain digital evidence from mass storage devices and volatile memory. The goal is to optimize searching for evidence including the links between them. An example is searching for links between the system journal entries on more devices. The student can deal with various types of devices and operating systems.

   Tutor: Komosný Dan, prof. Ing., Ph.D.

4. Improving the perceptual quality of compressed audio signals using deep neural networks

   Athough a great attention is paid to audio coding, coders with a low bit budget still produce perceptually unpleasant results. The study would be focused on the design of an generative adversarial deep neural network (GAN) which would improve the perceptual quality of the compressed files. The network's input would therefore be the compressed signal, and its output would be the perceptually improved version.

   Tutor: Rajmic Pavel, prof. Mgr., Ph.D.

5. Machine learning in photonics

   Photonic systems cover a wide range of areas from data transmission, through sensors to quantum networks. Each photonic system has its own requirements for the transmission infrastructure, but also for input and output parameters. Manual optimization of large networks based on different types of signals is almost impossible. With the help of machine learning, the optimization of both the transmitted signals and the entire infrastructure can be achieved in photonic networks. Last but not least, machine learning algorithms can be used to detect and classify non-standard network behavior to minimize security risks.

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

6. Methods for Optimization of Ultra-Wideband Analog Integrated Systems-on-Chip Using Parasitic Effects of Transistors

   The thesis focuses on designing optimization methods of MOS-only analog ultra-wideband analog integrated systems-on-chip of arbitrary integer and fractional order. The aim is to research and develop low-voltage and low-power applications by practical usage of transistor parasitics that work in frequency range units of GHz. Selected novel implementations of true-time delay circuits, oscillators, second- or higher-order filters, emulators of synthetic inductors, etc., with potential applications in 6G communication systems will undergo on-chip fabrication and experimental verification.

   Tutor: Herencsár Norbert, doc. Ing., Ph.D.

7. Modeling Directional XR Communications in Higher Frequency Bands

   Wireless data transmission using higher frequency bands in the order of GHz or even THz is one of the cornerstones of modern mobile networks to meet the ever-increasing demands for overall capacity and scalability of cellular systems. However, the propagation of a radio signal in those frequency bands entails a number of new technological requirements and challenges that need to be addressed for successful deployment in real-world scenarios. The aim of this doctoral thesis is a detailed analysis of key requirements of evolving applications such as extended reality (XR) and the subsequent design of a propagation model considering transmissions in 3D space and other specifics of the radio channel in the above-6 GHz frequency bands. The proposed model will be verified by simulations and / or experimental measurements.

   Tutor: Hošek Jiří, doc. Ing., Ph.D.

8. Objective metrics for estimating subjective evaluation of perceptual quality of degraded audio signals

   Most of today's objective metrics of audio quality is focused on assessing quality after signal compression. However, in practice we need to estimate the quality of signals degraded also by other means (clipping, distortion, drop-outs etc.). The student would concentrate on a modification of the established metrics like PEAQ, PEMO-Q or VisQOLAudio for these non-linear degradations. Deep learning wil be involved. Co-advised by: Jiří Schimmel (FEEC), cooperation with dr. František Rund (ČVUT Prague).

   Tutor: Rajmic Pavel, prof. Mgr., Ph.D.

9. Reconstruction of three-dimensional magnetic-resonance data using compressed sensing

   The non-Cartesian acquisition methods attract attention because of a variety of unique properties which can be exploited for different applications such as: acquisition acceleration, insensitivity to motion and the possibility to image tissues with very short T2s (e.g. cortical bones, tendons, ligaments, menisci and myelin). The objectives of the PhD study are to: a) develop an efficient volume reconstruction method from UTE data for quantitative analyses of ultrashort T2 components, based on nonconvex optimization, b) explore the limits of the spatial resolution when reducing the number of UTE projections for acceleration, c) apply and perform quantitative in vivo MR data analyses. Collaboration with CEITEC MU center, processing of data from the experimental MR scanner, supervisor specialist Ing. Peter Latta, CSc. Potential financial support from CEITEC.

   Tutor: Rajmic Pavel, prof. Mgr., Ph.D.

10. Research of Analog Active Function Blocks for Biosensors

    The dissertation focuses on researching novel structures of non-conventional analog active function blocks such as current or voltage conveyors using a chemical description of their terminal variables. The research aims to develop novel structures of chemical conveyors of different generations and their utilization in measurement systems for sensing fundamental quantities in biomedical systems. Selected systems will undergo on-chip fabrication and experimental verification.

    Tutor: Herencsár Norbert, doc. Ing., Ph.D.

11. Research of Fractional-Order Element Emulators for Reliable Modeling of Real-World Systems

    The thesis is focused on the research of analog emulators of fractional-order elements (FOEs) with an order of (-1; +1). The aim is the development of reliable low-voltage and low-power MOS transistor-based emulators of capacitors and inductors by practical usage of influences of transistor parasitics. Selected novel implementations of FOEs will be used to model different varieties and types of agricultural products and biomedical tissues (fruit/vegetable aging, ear channel/lung/liver modeling of humans and animals, etc.) based on real measured data collected via electrical impedance spectroscopy measurement technique.

    Tutor: Herencsár Norbert, doc. Ing., Ph.D.

1. round (applications submitted from 01.04.2023 to 30.04.2023)

1. Cellular 5G-IoT Procedure Optimization for the Massive Machine-Type Communication Scenarios

   Research activities and development in the area of heterogeneous mobile networks (5G+) aim to meet the demanding requirements of the communication networks, i.e., increased communication speeds, optimized communication latency, enhanced quality of service, and exponentially growing number of connected devices to the network. The ubiquitous connectivity is supposed to be achieved while utilizing new communication principles, progressive technologies, innovative mechanisms for managing the network resources, essential modifications of the frequency spectrum, and an advanced selection of the serving cells. The communication technologies operating in licensed and license-free frequency bands will then be integrated into one heterogeneous communication system. The aim of the dissertation thesis is to study up-to-date communication technologies for the communication scenarios known as massive Machine-Type Communication (mMTC) defined by 3GPP in Rel.15 and newer. During the initial phase, attention will be given to: (i) the 5G-IoT communication technologies operating in the licensed frequency bands, i.e., Narrowband IoT, LTE Cat-M, LTE Cat1, LTE Cat1bis and (ii) high-speed 5G NSA (Non-StandAlone) and SA (StandAlone). The initial findings will be used to fully understand the fundamental principles of “Cellular 5G-IoT” technologies. Also, to extend the knowledge, real measurement campaigns will take place using the communication prototypes built at the Brno University of Technology. Finally, the obtained data will be used as the input data sets for complex simulation scenarios / analytical modeling. Next, the results will be analyzed, and proposals of the new communication mechanisms targeting the optimization of the utilization of the network resources will be discussed. The attention will be focused on: (i) procedure optimization for the control plane and data plane, (ii) predictive switching between serving cells/communication technologies, (iii) optimization of the control plane traffic with the option to transmit the user data within the signaling traffic, (iv) switching between device operation states (connected, idle, power saving), (v) utilization of the multi-RAT approach where the device will switch between different technologies based on the defined requirements. The proposed principles will be implemented in the selected tools (Network Simulator 3 or Matlab) and further implemented/tested on the side of the end device. The actual evaluation will take place in the unique laboratories UniLab and RICAIP at BUT and CEITEC, respectively. Also, the student will use the already established international cooperation with industry companies and universities.

   Tutor: Mašek Pavel, Ing., Ph.D.

2. Optical fiber infrastructure security

   Fiber optic networks have evolved rapidly in recent years to meet the ever-increasing demand for increasing capacity. Today, optical fibers are widely used in all types of networks due to not only transmission speed or maximum achievable distance but also security. Although fiber optic networks are considered completely secure, there are ways to capture or copy part of the data signal. Both imperfections of passive optical components and, for example, monitoring outputs of active devices can be used. With the advent of quantum computers, current encryption could be broken. It is therefore necessary to address the security of fiber-optic networks, analyze security risks and propose appropriate countermeasures.

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

3. Quantum key distribution in telecommunication networks

   Today's digital world is dependent on data security during communication but also in storage, for example in e-banking, e-commerce, e-health or e-government. With the advent of quantum computers, there is a risk of potential security breaches today. Quantum Key Distribution (QKD) provides a way to distribute and share secret keys that are necessary for cryptographic protocols. The information is coded into individual photons. Integrating QKD systems into existing network infrastructure used for telecommunications is a topical challenge. Some other major challenges include increasing of the key rate, increasing the range of the QKD system, or reducing the complexity and robustness of existing solutions.

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

4. Reconstruction of degraded audio signals based on deep neural networks

   The doctoral study will cope with modern methods of audio restoration. The need to complete the missing segment of an audio signal or to restore saturated signal samples are interesting tasks with the practical use (historical recordings, dropouts in VoIP calls, etc.). Current methods are capable of high quality interpolation of signals that are stationary in the vicinity of the missing section and have harmonic character. The study will focus on methods that combine approaches that have been successful in recent years, namely mathematical optimization methods and the deep neural networks (DNNs). Psychoacoustic viewpoint of the problem will be covered as well. (Collaboration with the Acoustics Research Institute, Vienna)

   Tutor: Rajmic Pavel, prof. Mgr., Ph.D.