Introduction. Conventional implementations of adaptive MIMO-OFDM make suboptimal use of computational resources, as they require parallel execution of distinct algorithmic architectures: Space-Time Block Coding (STBC) for transmission reliability and spatial multiplexing for increased throughput. Consequently, the algorithmic development of a unified signal-processing architecture remains an open problem.
Aim. This study develops and evaluates a unified adaptive MIMO-OFDM architecture that eliminates dedicated hardware STBC encoders from the transmit chain. This is achieved by compensating for the loss of orthogonality through an iterative receiver with soft interference cancellation while maintaining stable channel adaptation.
Materials and methods. The proposed algorithm performs iterative soft-information exchange between a Soft V-BLAST detector and a Low-Density Parity-Check (LDPC) decoder. Its performance was evaluated through computer simulation against established reference schemes. To assess operability under non-stationary conditions, a link-adaptation algorithm for the Modulation and Coding Scheme (MCS) was implemented using the block-error-rate criterion.
Results. The proposed iterative receiver achieves BER performance comparable to that of conventional STBC schemes within two iterations, without employing orthogonal transmit coding. Integrating the detector into the adaptation loop enables dynamic maintenance of a target error rate, effectively trading the diversity gain for increased channel throughput.
Conclusion. The proposed unified architecture enables software-defined adjustment of the transmission strategy from maximum reliability to maximum spectral efficiency within a single algorithmic core, thereby minimizing computational and logic-resource overhead in transceiver implementation.

Introduction. Improving the accuracy of estimating the location of a radio source directly depends on the accuracy of its angular coordinates. Therefore, the task of improving the operational accuracy of direction finding, taking into account the complexity of the signal and noise environment and the characteristics of wave propagation in the HF band, remains relevant. Modern radio direction finding systems typically use antennas sensitive to only one component of the electric field and do not account for changes in signal polarization when reflected in the ionosphere. This leads to direction finding errors of approximately 1°, which is insufficient for precise localization of the radio source.
Aim. Modeling of the correlation interferometer and MUSIC methods taking into account the polarization structure of the received wave based on an antenna system consisting of triorthogonal antennas, and comparison of their accuracy characteristics with conventional direction-finding methods.
Materials and methods. Mathematical modeling of polarization correlation interferometer and polarization MUSIC methods in the MATLAB software environment.
Results. The mathematical model of a radio direction finder, incorporating an antenna system consisting of triorthogonal antennas and the proposed signal processing methods, was developed. The accuracy of estimating the angular coordinates of a radio source was compared depending on the signal-to-noise ratio and the amplitude ratio of the horizontal and vertical components of the electric field. It is shown that the use of a triorthogonal antenna system in combination with the proposed methods yields a several-fold increase in direction finding accuracy compared to conventional approaches. Dependencies on the signal-to-noise ratio for estimating the accuracy of polarization parameters (tilt angle and ellipticity of the polarization ellipse) were also obtained.
Conclusion. Incorporating additional scanning of the polarization ellipse's tilt angle and ellipticity into the correlation interferometer and MUSIC methods provides a more accurate estimate of the angular coordinates of the radio source, taking into account the elliptical polarization of waves in the HF band. The proposed approach not only improves spatial resolution but also enables estimation of signal polarization parameters, which can be used to reconstruct the propagation trajectory of radio waves.

Introduction. Quantum well infrared photodetectors (QWIPs) are among the key components of modern infrared imaging systems and are widely used for various applications, including space research, medical diagnostics, etc. One of the most important characteristics of a QWIP is the background-limited performance (BLIP) temperature, which is determined based on the equality condition between the background current and the dark current flowing through the photodetector. This parameter represents the operating temperature of the photodetector. Increasing the operating temperature can significantly reduce the requirements imposed on the cooling system. Since the background current depends on environmental conditions and the cryostat aperture, it is primarily requir ed to reduce the dark current values. The dark current is strongly dependent on the doping level of the quantum wells. However, the doping concentration also affects the photodetector sensitivity, creating a trade-off between sensitivity and dark current level.
Aim. To investigate the effect of the doping level of quantum wells based on the GaAs/AlGaAs material system on the BLIP temperature.
Materials and methods. Experimental photodetectors were fabricated by molecular beam epitaxy. The parameters of the samples were selected to ensure a peak spectral response wavelength in the range of 8…9 μm. The variable parameter was the doping level of the quantum wells with silicon. After completing the planar processing technological route, the current–voltage characteristics of all test photodetectors were measured in the temperature range of 65…77 K, and the corresponding curves of static current sensitivity were plotted.
Results. A reduction in the doping level from 9.0·1017 to 4.5·1017 cm–3 was found to lead to a significant decrease in the dark current within the operating voltage range. This made it possible to increase the BLIP temperature from 69 to 71 K. This was associated with the expected decrease in photosensitivity; however, its value remained above the threshold level of 0.15 A/W.
Conclusion. The obtained data demonstrate that optimization of the quantum well doping level in QWIPs provides for a reduction in the photodetector dark current. As a result, the device can be operated at higher temperatures.

Introduction. Issues associated with group methods for fabricating protective masks on substrates in high-resolution projection X-ray lithography are discussed.
Aim. To study the lithographic characteristics of X-ray resists and the specific features of their application under various operating modes.
Materials and methods. Studies were conducted using an RSM-500 X-ray spectrometer-monochromator. Absorption coefficient measurements were performed on monochromatic X-ray lines in the wavelength range of 5…50 Å. Film thickness was monitored using an MII-4 interference microscope.
Results. Spectral dependencies of the absorption coefficients in the soft X-ray range (5…50 Å) were obtained. At certain wavelengths, a sharp increase in the absorption coefficient was observed. Absorption jumps were detected at wavelengths of 23 and 43 Å. This phenomenon is associated with the fact that the X-ray photon energy becomes sufficient to ionize electrons from specific atomic energy levels of the absorbing material. It was shown that the X-ray absorption coefficient increases with increasing wavelength. Between the absorption jumps, the coefficient can be approximated by a smooth function over certain wavelength intervals. Analytical approximations of the obtained dependencies in the form of power-law functions were proposed. A comparison of the experimental data with the calculated values showed satisfactory agreement.
Conclusion. A technique for measuring the spectral dependences of X-ray resist absorption coefficients was developed. Soft X-ray absorption coefficients were experimentally obtained.

Introduction. The development of telecommunication networks and radar systems operating in the 10…100 GHz range requires materials with low dielectric permittivity (ε less than two). Additive technologies, such as digital light processing (DLP), are promising for fabrication of 3D devices; however, controlling air void distribution in photopolymers remains challenging due to their rheological properties. This paper proposes an approach for developing a composite material based on a photopolymer matrix and hollow glass microspheres (HGM) aimed at reducing the effective permittivity of the material.
Aim. To study approaches for obtaining a mixture of a photopolymer binder and HGM and to compare the microwave parameters of samples obtained by layer-by-layer photocuring and polymerization from a suspension, to achieve ε less than two.
Materials and methods. The effective permittivity was calculated using the finite element method in both electrostatic and electrodynamic (10 GHz) modes. The Anycubic Clear transparent photopolymer resin was used as the composite matrix, and hollow silicon dioxide microspheres with an average particle size of about 50 μm were used as the filler. Electrophysical parameters were measured using a Ceyear 3272C vector network analyzer.
Results. A mixture recycling system for DLP printers is developed, enabling the production of composites with a low filler volume fraction. The 5.5:1 mixture of photopolymer and HGM reduced permittivity by 10% compared to the unfilled photopolymer. The preparation of an HGM suspension in the resin volume made it possible to significantly increase the filler content, which led to a 40 % reduction in permittivity.
Conclusion. The use of a suspension reduces the dielectric constant from 2.9 to 1.75, corresponding to a 40 % decrease. The developed recirculation system is compatible with commercial 3D printers and enables the fabrication of samples with low HGM concentrations (up to 5…7 %).

Introduction. A major challenge in AlGaAs-based heterostructure devices is the presence of DX centers in heavily doped n-type layers. These deep donor traps degrade the performance of pseudomorphic high electron mobility transistors (pHEMTs). This study examines the influence of DX centers on pHEMT characteristics through a systematic analysis of output and transfer current–voltage characteristics (IVCs) as functions of two key parameters: the empirical binding energy coefficient Eb and the aluminum content in the AlGaAs donor layer. Variations in these parameters modify the concentration of DX centers, which in turn governs the formation of localized states within the band gap.
Aim. To investigate DX centers in an AlGaAs/InGaAs/GaAs pHEMT model using technology computer-aided design (TCAD) tools.
Materials and methods. The study employed numerical simulation based on the fundamental semiconductor equations (Poisson, continuity, and transport equations) implemented within a hydrodynamic framework that accounts for quantum-well features. Model validation was carried out using experimental structures fabricated at AO "Svetlana-Rost".
Results. The numerical pHEMT model, which incorporates DX centers, reproduces experimental characteristics, including threshold voltage and saturation current. The DX center concentration, governed by the Eb parameter and the aluminum mole fraction, is a key factor controlling channel charge density. Analysis of the IVCs indicates that the model provides a reliable means of quantitatively evaluating point-defect (DX center) concentrations in real heterostructures.
Conclusion. The developed numerical model captures the adverse impact of DX centers on pHEMT IVCs. The results show that DX center concentration strongly affects final device parameters, modulating channel carrier density and introducing operational instability. These findings offer a basis for reducing the influence of DX centers on pHEMT performance through optimization of transistor design and epitaxial growth conditions.

Introduction. Polyvinyl alcohol (PVA) films are widely used in flexible electronics, biosensors, and liquid-crystal optical elements. Like many polymer materials, these films exhibit relatively low mechanical strength, which often necessitates additional protective layers that may reduce the efficiency of electronic and optical components. Sensitization with various nanoparticles is a well-established strategy for tuning the physical and chemical properties of polymer systems. In this study, shungite nanoparticles were selected as a sensitizer, as this natural, nontoxic carboncontaining material is known to enhance mechanical strength.
Aim. To obtain PVA films sensitized with shungite nanoparticles; to investigate their spectral and mechanical characteristics as functions of synthesis parameters; and to identify processing conditions that provide an optimal balance between optical performance and mechanical stability.
Materials and methods. Films were synthesized using the method developed at the S. I. Vavilov State Optical Institute. PVA served as the polymer matrix, and Karelian shungite nanoparticles containing 30 % carbon were introduced as a filler. Spectral characteristics were measured with a UV-3200 spectrophotometer, and mechanical properties were evaluated using a PMT-3M microhardness tester (LOMO).
Results. The films exhibited a polarization degree exceeding 90 % across the visible spectral range without additional lamination. Incorporation of shungite nanoparticles increased the mechanical strength of PVA films by up to 1.6-fold.
Conclusion. Modern photonic devices require materials that combine high polarization efficiency and optical transmittance with mechanical robustness. The developed approach strengthens PVA polarizing films while preserving their optical properties, thereby expanding current understanding of mechanical-property control in nanocomposite systems.

Introduction. Electret capacitive receiving transducers with moving plates are used in various devices, particularly as microphones in mobile phones. However, methods for calculating their sensitivity, including taking into account the electrical load parameters and other characteristics of such transducers, are insufficiently developed.
Aim. To develop a mathematical model of membrane-type electret sensors for evaluating their sensitivity, taking into account the static deflection of the membrane, the characteristics of mechanical vibrations under the influence of an external periodic force of various origins, and the influence of the electrical load.
Materials and methods. Computer simulation in the MATLAB environment.
Results. The proposed calculation procedure is divided into three interconnected stages. The static stage accounts for membrane deflection under the influence of the electret-induced electric field. The dynamic stage describes membrane vibrations caused by an external periodic disturbance. The electrical stage determines the resulting electrical voltage at the transducer terminals. Analytical expressions for the static deflection of the membrane are derived, and the limits of its steady state are determined as functions of the parameters of the electret transducer capsule, including membrane tension, air gap thickness, electret film thickness, relative permittivity of the electret material, membrane and counter-electrode dimensions, etc. The technique for calculating membrane vibrations uses equivalent lumped parameters (membrane mass, acting forces, etc.) instead of distributed parameters, thereby eliminating the need to solve partial differential equations.
Conclusion. The proposed calculation procedure provides a basis for the rational selection of electret transducer parameter values depending on the target performance requirements. The derived expressions enables the calculation of the amplitude–frequency characteristics of various electret transducer generators. The results obtained are useful for those designing new and optimizing existing electret transducer designs

Introduction. The Sentinel-1 (equipped with synthetic aperture radar) and Sentinel-2 (equipped with multispectral cameras) satellites are valuable tools for environmental monitoring, particularly for assessing vegetation cover and soil erosion. The data obtained by these systems can be processed using machine learning techniques to generate accurate vegetation classification maps.
Aim. To develop and evaluate machine learning models capable of efficiently fusing Sentinel satellite data to produce more accurate and detailed maps of urban vegetation, essential for urban planning, environmental monitoring, and climate change mitigation. The integration of Sentinel-1 and Sentinel-2 satellite data is intended to overcome the limitations associated with using each data type in isolation, particularly in complex urban environments where spectral signatures can be ambiguous and radar provides only structural information.
Materials and methods. A classification map of urban vegetation on Kotlin Island (St Petersburg) was generated by integrating data from Sentinel-1 (synthetic aperture radar) and Sentinel-2 (multispectral imagery) using the Random Forest algorithm, Tensorflow and Sklearn Python libraries. Conventional urban vegetation mapping often relies on a single data source, leading to limited accuracy and inability to differentiate subtle vegetation types. The vegetation classes considered in this research were coniferous forest, deciduous forest, wetland vegetation, and coastal meadows.
Results. The integrated analysis of radar and multispectral data enabled more accurate identification of erosion-prone zones in non-vegetated areas and more reliable estimation of plant moisture content. Such a fusion approach showed significantly improved classification accuracy and reduced error rate compared to techniques relying on individual indices.
Conclusion. The fusion method demonstrated superior performance in classifying vegetation types, which confirms its potential for applications in remote sensing and environmental monitoring. Future research will focus on integrating radar and multispectral data from Sentinel satellites for urban vegetation classification using the Support Vector Machine algorithm.