ABSTRACT. Over the past few decades, a variety of nonlinear behavioral modeling techniques have been developed for microwave GaN power transistors in order to accurately capture their nonlinear behavior. Despite these efforts, there is still a lack of systematic studies on the comparisons and analyses of the performance of the various modeling techniques proposed over the years. An overview of these large-signal behavioral modeling approaches, including both traditional approximation methods and machine learning (ML) methods, is provided in this paper. In addition, in order to explain the basic theory and application areas of each behavioral model, prediction capabilities are also discussed.

ABSTRACT. This paper presents the design of an 8-bit successive-approximation (SAR) analog-to-digital converter (ADC) using 130 nm UMC CMOS technology. The ADC contains a sample and hold circuit, a comparator, a serial D flip-flop based SAR and a digital-to-analog converter (DAC). A two-stage operation amplifier based comparator gives a simple ADC structure with very low power consumption. With a 1.2 V supply voltage and input signal frequency of 10.1 kHz, the sampling rate is 90 kS/s with 0.636 mW power consumption. The average integral non-linearity (INL) and differential non-linearity (DNL) are less than 1 LSB with effective number of bits (ENOB) of 7.52 bits and the signal to noise and distortion ratio (SNDR) of 47.01 dB.

ABSTRACT. This paper presents a front-end GaN MMIC designed for an aperture-level in-band full-duplex phased array system. The MMIC is an asymmetric single-pole double-throw (SPDT) switch co-designed with a variable-gain low-noise amplifier (LNA). A specified switch isolation is designed for sampling of the transmit-path signal to assist digital self-interference cancellation (SIC) after downconversion and digitization. The MMIC is implemented in a 250nm GaN on SiC process, with a design frequency range of 2.75 - 3.25 GHz. The switch exhibits an insertion loss less then 1 dB up to 40dBm of input power with a transmit observation range greater than 20 dB. With the switch setting for receive mode, the LNA-switch combination gain exceeds 14 dB across the band with a predicted noise figure of 3 dB.

ABSTRACT. In this paper, we present a systematic analysis of how concurrent signals within a specified frequency band affect the linearity and spectral efficiency of a high-efficiency power amplifier (PA). Using a large-signal measurement setup with a wide instantaneous bandwidth, a PA is characterized with 1 to 8 multi-carrier signals, each with a 10MHz bandwidth. The signals are evenly spaced within a 500MHz band centered around 4.35 GHz. The single-stage hybrid PA is designed with a GaN-on-SiC packaged device with CW output power above 10W from 4 to 5 GHz. In the design band from 4.1-4.6 GHz, the PAE exceeds 50% with a saturated gain above 8 dB at 28V drain bias, agreeing well with nonlinear simulations. The efficiency, output power, noise power ratio, and spectral efficiency are quantified in measurement and show that the overall performance can be appropriately defined by an equally weighted figure of merit which is a function of the number of signals.

ABSTRACT. This paper presents a design sensitivity analysis for microwave power amplifiers (PAs). Specifically, the variation of matching circuit elements within a given range is taken into account during the design process using a multi-objective interactive visualization method. The method is illustrated on the example of a 5-W peak power GaN MMIC intended to operate around 8-14 GHz over a range of drain supply voltages for envelope tracking. In this circuit, the measured performance is shifted to higher frequencies compared to the design. Applying a sensitivity analysis method demonstrates how a ±20% variation of capacitors used in the process affects performance. We demonstrate that the method can be used to analyze trade-offs between multiple output performance metrics in PA design, additionally demonstrating a design sensitivity metric that can be included in future designs.

ABSTRACT. The current-gain peak (CGP) appearing in the frequency-dependent behaviour of the magnitude of the short-circuit current-gain (h21) is, currently, attracting much attention. Recently, a systematic procedure has been proposed for accomplishing a straightforward fitting of h21 using the complex Lorentzian function and, then, an effective identification of a set of parameters for an accurate and complete assessment of the size and shape of CGP. The attention has been focused on the study of CGP versus ambient temperature and drain-source voltage (VDS) by considering a gallium nitride (GaN) high electron-mobility transistor (HEMT) as device under test (DUT). This contribution is aimed at providing a further insight into the analysis of CGP by applying the developed procedure for investigating the impact of the gate-source voltage on the size and shape of CGP.

ABSTRACT. This paper presents the design and development of two voltage-controlled oscillators for a quantum receiver at 11 and 15 GHz. These quantum radio-frequency receivers use a vapour of Rydberg atoms to detect the magnitude of an incident microwave field. When a microwave local oscillator (LO) is included, both amplitude and phase of the incident field can be detected with high sensitivity and high Q. Here we show the design of MMIC oscillators manufactured in the WIN Semiconductor GaAs HEMT process, which serve as the LO and are designed to couple to a resonant field-enhancing cavity that encases the vapor cells. The X-band oscillator had a measured phase noise of -108 dBc/Hz at 1 MHz offset and a tuning range of 100 MHz. The Ku-band oscillator had a measured phase noise of -85 dBc/Hz at 1 MHz and a bandwidth of 360 MHz. Potential mounting methods for the oscillators are also discussed.

ABSTRACT. Heterogeneous integration allows the use of multiple RF technologies within the same packaging process. Interconnects are required to transition between different embedded structures and between different layers in multi-layer packaging processes. The State-of-the-Art Heterogeneous Integrated Packaging (SHIP) program is developing a packaging method with six metalized organic dielectric layers on a central silicon interposer. Using this process, various interconnect structures are designed for dc to 50 GHz operation. These interconnects transition between different types of transmission lines fabricated on different organic dielectric layers. Simulations and measurements of three different interconnect structures are presented. A return loss above 12 dB is achieved across all the structures with a maximum insertion loss of 0.5 dB, measured from 2 to 50 GHz

ABSTRACT. This paper presents a study for subsurface object detection using different scanning acquisition paths. The air coupled system is considered, which can be easily attached to the unnamed aerial vehicle (UAV). The objective is to determine which acquisition scenario can acquire the largest area of interest. The SFCW radar can generate 200 samples within a frequency range of 500MHz – 2.5GHz with pulse repetition interval of 100ms. The TEM antennas are used for transmitting and receiving signals. The following configurations of air coupled GPR are presented: monostatic down-looking and side-looking configurations, bistatic configuration, where antennas were separated for 2 meters, circular configuration with platform rotating along its vertical axis and circular configuration with platform moving along trajectory. The experiments were conducted using a polygon of 3×3×0.5 meters with homogeneous clay structure. Experiments showed that bistatic and circular acquisitions can be used for scanning ground areas of interest between 1 and 1.5 meters, when platform is placed 0.75 m above surface.

ABSTRACT. The occurrence of landslides, especially in anthropic areas, brings to notable consequences for both the economy and society. In the years, Wireless Sensor Networks (WSNs) based geotechnical monitoring systems have been gaining relevance for their flexibility. In this paper we propose a LoRa-based WSN for landslide and flood monitoring in the locality of Posta, Italy. The system is composed of several nodes for data retrieving which give information about rockfall and floods risk, sending information through LoRa peer-to-peer packets. The first layer employs a custom data protocol, while the second layer is shifted to the LoRaWAN standard for the information to be sent on the internet. The system uses a mixed protocol multi-hop structure for packet transportation due to the conformation of the installation location and the subsequent radio coverage needs. Data is gathered on a user-friendly interface, exploiting an IoT-based structure. The system has been implemented and tested in the aforementioned locality, providing a reliable safety means for rockfall and floods risks.

ABSTRACT. To find the future directions for the anti drone radar (ADR) industry, we compare 14 commercial off-the-shelf (COTS) ADR by 14 criteria, and classify them by 3 criteria. Our analysis shows that COTS ADR manufacturers could benefit from focusing on passive ADR, multiple-input multiple-output ADR, and classification based on machine learning.

ABSTRACT. In this paper we are concerned with the low probability of detection (LPD) and covert radars employing optical incoherent sources. Key idea of our proposed LPD/covert radar concept is to hide the radar signal in solar radiation by employing the broadband (30 nm) Erbium-doped fiber amplifier source, modulating such source output beam with a constant amplitude modulation format at high-speed, and detect the presence of the target by the cross-correlation method. To demonstrate the proposed concept we developed an outdoor free-space optical (FSO) testbed at the University of Arizona campus. To improve the tolerance to atmospheric turbulence effects the adaptive optics is used. We demonstrate that the LPD/covert radar concept over strong turbulent FSO channel is feasible in a desert environment.

ABSTRACT. The paper presents the design of a dispersive filter for an analog pulse compression radar. The architecture of the analog pulse compression radar is presented with its equations, limitations, trade-off and architecture comparison with the more traditional FMCW radar. In the past decades, the matched filter of analog pulse compression radar has been implemented with SAW filters, having a reduced bandwidth and then poor resolution. Here the matched filter is designed with a passive dispersive filter instead of a SAW. The design of the filter is described, measured, and compared to the state-of-the-art of dispersive filter. The use of wideband passive analog matched filter paves the way to better signal-to-noise ratio and reduced power consumption compared to its traditional FMCW counterpart. The measured filter, composed of 2 passive cells achieved with components of the shelves has a group delay downslope of -1 ns/GHz which is one of the strongest downslope reported in the literature. The considered bandwidth is [700MHz – 1:9GHz].

ABSTRACT. This paper presents research on methods for implementation of NFC technology into ESP32 based IoT systems. Two main methods are proposed, first with the commercial modules that incorporate built-in antenna and module that is universal transceiver and decoder, and second method, where all of the integral parts of the system are designed separately. Methods are analyzed and compared in terms of feasibility, speed, resources and cost, using specially developed tests. Tests consist of multiple writing and reading tasks from the NFC tag, ESP32 and the smartphone. Tests also examine the compatibility with the ESP32 for IoT applications and with NFC enabled smartphones. Results point out that first implementation method offers higher performance rate in terms of the most of criteria, while the second method gives broader versatility and wider compatibility range.

ABSTRACT. Digital predistortion (DPD) is recognized as an effective solution for power amplifier (PA) linearization. The DPD provides conformity of wireless infrastructure to telecommunication standard requirements (regarding bit error rate (BER), transmit spectrum mask (TSM), error vector magnitude (EVM) …) by making PA more linear, while at the same time reduces the running cost of the telecommunication infrastructure. Different PA models were used for simulation of DPD algorithm: Memoryless, Complex Valued Memory Polynomial model, Hammerstein and Wiener. The simulations results are provided in the paper as well the measured results obtained by Class-J GaN HEMPT amplifier linearization.

ABSTRACT. This paper overviews the most recent advances in the unstructured Transmission Line Modelling method that is uniquely placed for modeling advanced photonic applications with multi-scale features. The paper focuses on the holistic approach that needs to be taken when considering these applications which involves not just the electromagnetic solver, but also important aspects of the unstructured mesh generation and geometry definition. The capability of the UTLM is demonstrated on the complex geometry of a photonic polarization splitter that incorporates diverse components namely tapers, multimoded waveguides and a photonic crystal region.

ABSTRACT. Deep seated tumors are neoplasms grown in challenging sites that call for innovative interventional strategies. Thanks to the development of magnetic nanocomposite biomaterials, multifunctional electromagnetic-responsive thermoseeds, called magnetic scaffolds, can be used as hyperthermia agents to control the local recurrence rate of deep-seated cancers through radiofrequency (RF) heating. To achieve an effective and high-quality treatment, the planning through multiphysics simulations is mandatory. A computational framework for solving the coupled electromagnetic and thermal phenomena ruling the RF heating of magnetic scaffolds will be presented and used to study different biomaterials, physio-pathological scenarios and applications.

ABSTRACT. This paper considers both experimental and numerical TLM simulation results of shielding effectiveness analysis of an enclosure with two metal plates placed at certain angles inside enclosure. As damping technique, metal plates are used with dimensions which are determined to affect the enclosure’s first resonant frequency. The obtained results show that the first and the second resonant frequencies are shifted toward higher frequencies while the third is shifted toward the lower, which can considerably extend a useful frequency range of considered enclosure.

ABSTRACT. This paper delves into the exploration of a digital modeling approach known as wave digital technique, specifically its application in accurately capturing (characterizing) the behavior of multiport microstrip circuits with stepped-impedance resonators (SIRs). The SIRs can be used in design of couplers, filters, etc.

ABSTRACT. DTMF is a signalling system used in telephony. When DTMF is sent in-band and carrying sensitive information, this data often must be removed. Inaccurate removal procedure results in fractions of DTMF remaining. In this paper MUSIC is presented as a powerful method for removal of DTMF fractions. Compared to standard methods that utilize periodogram, e.g. Goertzel algorithm – MUSIC is quicker, more robust and accurate. For reliable DTMF detection in 8 kHz telephony, MUSIC needs only 8 samples (1 ms), Goertzel needs at least 110 samples (13.75 ms).

ABSTRACT. The work is fulfilled within the framework of Erasmus+ project “The Future is in Applied Artificial Intelligence” (FAAI) and devoted to the development the methodology for collecting and analyzing good practices in the field of applied artificial intelligence (AAI) regarding the competences, training, existing solutions and real cases, which can be used for developing training courses of competence based education. Here we propose the definition of good practice in the field of AAI together with the corresponding criteria and features. The offered methodology uses system research based on the data gathered from existing training courses in AAI, labor market, surveys filled in by academics, students and employers, AAI use cases in science and industry.

ABSTRACT. This article is fulfilled within the framework of Erasmus+ project “The Future is in Applied Artificial Intelligence” (FAAI) and examines research of collecting IT specifications of good practices in Area of Artificial Intelligence (AAI). The article describes research conducted, the purpose of which is to find IT specifications of good practices in AI and describe their characteristics, like an area of implementation of the AI solution, the result of processing the data, the source of data, Data processing, and quality, what tools are used for processing data, and others. AAI application cases are reviewed and the technologies used to implement it, the specifics of the data, and the applications used are described. The analysis of the technologies thus described will give an idea of the preferred ones among them and give the picture of the so-called "good practices" in this field. The research was done by looking at cases all over the world. The analysis of the data provides insight in several directions:  Application area of ML/AI  Type of machine learning problems in described good practices in Artificial Intelligence  Type of models were developed within the projects  What is the area of implementation of AI solution  Used AI libraries (frameworks).

ABSTRACT. This article is fulfilled within the framework of Erasmus+ project “The Future is in Applied Artificial Intelligence” (FAAI) andexamines the study of practical solutions implemented using applied artificial intelligence. The research was done by preparing an online survey containing a total of 7 questions, open and closed. The purpose of the study is to find real working applications of applied artificial intelligence projects, describe their application in what field, and record the name of the projects found to describe their activity. The study was done by looking at cases all over the world. The analysis of the data provides insight in several directions: - in which countries are more real cases of artificial intelligence solutions used - what is the distribution of realized cases - depending on whether the country is a member of the EU or not EU. - In what category is the real case developed. - whether the country of the real case works in collaboration with other countries or implements the real case only the country. The research and analysis done provide a clear picture of the developed projects using artificial intelligence. The obtained results will guide in what areas to organize the practical training. Also, the research would help future AI application developers

ABSTRACT. ERASMUS+ project The Future is in Applied Artificial Intelligence (FAAI) aims to increase the quality and relevance of students' and graduates' knowledge and skills in AI/ML-specific topics based on skills needed in the labor market. This paper presents the results of the survey that was conducted in the context of the FAAI project to assess the needs of employers in project participants’ countries in graduates’ competencies in Artificial Intelligence, Machine Learning, and Data Science in general for the purpose of training specialists in the field of Applied AI. The survey was filled in by 38 companies and consisted of 31 questions related to general required competencies, type of machine learning problems solved, AI libraries used in companies, required soft skills, employers’ satisfaction with the level of preparedness of master's degree graduates in the field of AI.

ABSTRACT. This article is fulfilled within the framework of Erasmus+ project “The Future is in Applied Artificial Intelligence (FAAI). It gives overview of current job market related to the field of Applied Artificial Intelligence. The data is obtained from online survey, and it gives highlights of several aspects of labor market divided into research and analysis of the market, and specific requirements necessary. Regarding research and analysis, the data provided deals with: - positions offered in the market. - machine learning problems occurring. - models being developed while resolving the real-world problem. - machine learning tasks to be solved. The collected data in the domain of job market requirements gives highlight about: - required programming languages. - educational requirements. - required competencies. Results given can serve as a guide to which competencies are necessary in the field of AAI and provide information for both professionals and curriculum creators.

ABSTRACT. We comprehensively examine the efficacy of LSTM models in predicting financial time series. We evaluate the performance of LSTM networks based on various numbers of units determined by temporal granularity, considering aspects such as prediction accuracy. This study contributes to the ongoing discourse on the role of AI in financial markets, offering a nuanced perspective on the practicality and limitations of LSTM models in this critical domain

ABSTRACT. The work is devoted to designing a manufacturing network incorporating logistic-production sites that are located at the nodes of the squared lattice with the help of the AI technique. We focused on qualitative analysis of the dynamic behavior of the dynamic lattice model. The model includes rate constants and initial conditions affecting the trajectories of the model which can be classified either as a stable node, limit cycle, or chaotic attractor. We aim to solve the problem of the model qualitative behavior as an AI classification problem. The training dataset is constructed with the help of Monte-Carlo simulation with high-performance computing in Julia. The AI model is built as a C5.0 decision tree. The work was fulfilled with the framework of Erasmus+ Project No. 2022-1-PL01-KA220-HED000088359 entitled "The Future is in Applied Artificial Intelligence" (FAAI) and offers a use case to be studied during the applied AI training course.

ABSTRACT. Wireless communications constitute a vital sector within telecommunications. Multiple wireless technologies, such as 4G, 5G, WiFi, etc., are available to users. One of the most important benefits of wireless communications is enabling the user mobility. However, this feature often requires handover between access points or base stations. Moreover, modern user equipment has the support for multiple wireless technologies, which brings possibility for network selection and vertical handover (VHO) between different wireless technologies. The importance of network selection and VHO has been further amplified in recent years because satellite communications are increasingly perceived as extensions to terrestrial wireless technologies. This paper provides a comprehensive review of the current state-of-the-art methods, algorithms and techniques used in network selection and VHO. It delves into the underlying mathematical approaches and models that underpin each method. Detailed performance comparison with listed advantages and disadvantages of the analyzed methods is also presented in the paper.

ABSTRACT. This paper proposes a traffic forecasting approach that uses neural networks based on graphs. The method minimizes the communication network (between vehicles and the database servers) load and represents a reasonable trade-off between communication network load and forecasting accuracy. To traffic is forecasting using a LTSM neural network with a regression layer. The inputs of the neural network are sequences - obtained from graph that represent the road network - at specific moments of time that are read from traffic sensors or the outputs of neural network (forecasting sequences). The input sequences can be filtered to improve the forecasting accuracy. Also, the paper illustrates a general framework to implement a graph neural network. Two cases are studied: one case in which the traffic sensors are periodically read and the other case in which the traffic sensors are read when their values changes are detected. A comparison between the cases are made and the influence of filtering are evaluated.

ABSTRACT. Achieved spectral efficiency is one of the most important metrics in mobile communication systems performance assessment. In this paper methodology on how to assess it in 5G/NR systems is discussed, as well as examples of relevant network performance analysis from commercially deployed network, through underperforming channels identification and troubleshooting. It is shown that proposed methodology provides valuable network insights.

ABSTRACT. Due to its increasing impact on human health, air pollution is becoming a progressively important topic in modern society. Particulate matter with a diameter of 2.5 μm is cited as one of the main air pollutants. Thus, prediction of concentration of these particles presents a very important research topic. Therefore, in this paper, we observed a Deep Learning based spatial prediction of this concentration realized by using the installed high-cost sensors and/or low-cost sensors, which are simulated. Based on the obtained analysis results, a proposal was made to employ the low-cost sensors, completely or partially, with distributed Deep Learning Neural Networks, instead of the currently used high-cost sensors in the wireless sensor network for PM2.5 concentration measuring. It is shown that in this way we can lower complexity, datasets and time for training without the loss (or even with the gain) in the prediction quality.

ABSTRACT. In this paper we analyze a user-centric handover procedure, which can be used to improve the downstream communication from low Earth orbit satellite network to end-users, in presence of shadowed-Rician fading. We consider usage of DVB-S2X protocol and numerically express the improvement, measured by average spectral efficiency and data loss rate, achievable with employment of multiple satellites. The improvement is a consequence of the proposed strategy to predict the signal-to-noise ratio in the considered communication channel.

ABSTRACT. Educational platforms are generally of great importance in the education process of students of technical sciences, because through the experimental work the increase of their practical knowledge is enabled. When considering highly specialized systems, such as IoT systems that rely on satellite link communication, then such platforms are even more significant because training courses at real systems in these cases are impractical for many reasons. One example of these educational platforms was developed and implemented at the Vlatacom Institute for the needs of technical sciences students during their mandatory internship. The aim of this specific educational platform is to provide the possibility to examine the influence of the simulated satellite link on overall communication inside of different IoT systems.

ABSTRACT. The market share of electric vehicles is growing rapidly. As a consequence of this trend, there is a great need for commercial and private renewable sources powered stations for electric vehicles charging. The installed stations can be introduced into a smart city environment for increasing the usage of stations, achieving energy and cost savings, and increasing the quality of life in the community. In this paper, we propose renewable sources powered station for electric vehicles charging that integrates in the smart city environment. The paper proposes IoT based architecture that aims to standardize the integration of stations into smart city concept. In this way, the interoperability problems would be significantly decreased and the integration process would be easier, faster and cheaper.

ABSTRACT. In this paper, we study physical layer security of an unmanned aerial vehicle (UAV)-assisted communication system, where a UAV collects data from a sensor node and UAV-eavesdropper tends to overhear confidential information. In particular, assuming Fisher-Snedecor fading environment, we derive the closed-form expression of the intercept probability and we examine the effect of different system/channel parameters on this performance metric. Numerical results are also presented to verify analytical result; and to highlight the impact of specific fading/shadowing conditions over the main and wiretap channel, as well as the impact of UAVs’ positions.