The results of the development of a scientific and methodological apparatus that provide an assessment of the detection range of small-sized unmanned aerial vehicles are presented. The general problems of radar detection of small objects are considered. A mathematical formulation of the research problem is carried out from the stand-point of detecting radar signals in noise based on a probabilistic approach. Substantiated are the parameters of radar stations, which are of the most significant importance for increasing the reliability of detecting objects with a small effective scattering surface. The functional dependences of the detection range of small unmanned aerial vehicles on the value of the signal-to-noise ratio in the channel and the sensitivity of the receiving devices are given. The dependence of the detection range on the wavelength of radiation from radar stations has been studied. A quantitative assessment of the probabilities of correct detection of small targets and false alarms is presented for various values of the decision threshold. Nomograms have been developed to assess the capabilities of detectors of unmanned aerial vehicles of the Phantom 3 type. The requirements for the structure of radar signals used to detect small targets are substantiated.

This research is devoted to the study of the properties of the microbending of an optical fiber. It is shown that an increase in the diameter of a microbend at a constant force in the area of its formation led to an increase in the power of optical radiation output from the fiber in the area of the microbend. It has been established that the smallest value of the optical radiation power branched in the microbending region and the smallest value of the radiation power loss at the microbending for the entire range of wavelengths under study is observed for the G657 optical fiber. The largest value of the radiation power branched off in the microbending region and the largest value of the radiation power loss at the microbending for the entire range of wavelengths under study is observed for the G655 optical fiber. The results of the article can be used in systems for protecting information transmitted over fiber-optic communication lines.

This article studies the possibility of using circuit formats to describe radio components in electrodynamic modeling problems. The study was carried out on the example of a controlled metamaterial in the form of an electromagnetic crystal with SPICE-models of equivalent circuits of pin-diodes and MEMS-keys. Also, the possibility of using Touchstone files as an alternative format for describing radio-electronic components was considered. The obtained results are illustrated by scatter matrix plots, as well as equivalent circuits and SPICE code. Obtained results can be used for the design of structures that combine active nonlinear radio components and microwave devices.

The article proposes a simple method from the point of view of computational costs for encoding a fractional number of bits per symbol with amplitude-phase modulation (APM). The presentation is performed in relation to the case when it is necessary to form the value of the specific transmission rate with an accuracy of up to a quarter of a bit per symbol. Algorithms for the operation of the encoder and decoder, the formation of a synchro signal and the amount of energy gain achieved by using this method are given. The proposed coding method was used in the development and modernization of high-speed modems, the tests of which confirmed the reliability of the results obtained.

The evolution of 1G to 4G radio access networks (RANs) over the past 40 years has shown that beamforming (BF) capabilities add an additional spatial dimension to traditional device multiplexing methods. When base stations (gNodeB - gNB) and user equipment (UE) form narrow antenna radiation patterns (APPs), in addition to frequency, time and code division of channels, an additional spatial dimension appears that implements spatial multiplexing. This concept has been known for quite a long time, but the full implementation of its capabilities in practice is expected with the widespread adoption of millimeter wave (mmWave) ultra-dense networks (UDN) of the fifth (5G) and subsequent (B5G) generations. To control APP, the approach of preliminary analysis of training sequences about the current situation in the radio channel  - CSI (Channel State Information) - can be used, but its overhead costs become unacceptably high in conditions of ultra-dense distribution of devices. An alternative approach is positioning-based BF. The validity, relevance and prospects of this approach are determined by the fact that for 5G networks, unlike previous generations, for the first time the requirements for UE positioning accuracy up to one meter are formalized. Initial research in the field of location-aware BF has already been carried out over the past years, however, mainly for particular scenarios of one or more radio links between gNBs and fixed UEs. In this work, for the first time, a scientifically based methodology for controlling the beam pattern of a stationary gNB based on the positioning of a mobile UE for a two-radio link scenario is formalized and implemented in software. The problem of practical implementation of BF is the difficulties to predict level of interference due to the mutual influence of radio links with mobile UEs. When estimating the instantaneous signal-to-interference ratio in a two-radio link scenario between two fixed gNBs that perform BF based on the current location of mobile UEs as they move, it is necessary to take into account the mutual influence of each other's radio links on each other. In such a scenario, a transmitter on one radio link acts both as a source of a wanted signal for one UE and as a source of an interfering signal for another UE. The task of assessing interference for such a scenario is complicated by the nonlinearity of the transmitter and/or receiver ARPs. The model developed and implemented in software in this work uses the functions of the Phased Array System Toolbox Matlab extension package. The simulation results show a significant scatter (tens of dB) of the instantaneous signal-to-interference ratio depending on the territorial separation of devices and can be used to justify scenarios for the construction and operation of 5G/B5G UDN.

In modern conditions, with the integration of organizational and technical systems (OTS), the relevance of ensuring interoperability in such systems is increasing. In this paper, the issues of forming a structural-functional model of OTS interoperability are considered. The processes, categories and objects included in the OTS are singled out, their classification is carried out. The factors influencing interoperability at semantic, organizational and technical levels are revealed. The interoperability of the main processes, categories and objects as part of the interoperability model is considered. Recommendations are presented for the further direction of research in order to improve the quality of interoperability in the interaction of OTS.

Statement of the problem: the development of the infocommunication system is accompanied by the development of communication technologies and services. The general trends of this process are expressed in three main directions: the growth of throughput, reducing the delay in data delivery and mass communications. The latter is characterized by the development of the Internet of Things (IoT). IoT networks are built using various technologies. A large number of connected devices requires the use of new approaches to modeling and methods for building and managing such networks. To model networks with a high density of devices, it is often not enough to use flat models, but you have to resort to building models in three-dimensional space. For the functioning of networks with a large number of nodes, effective methods for choosing their structure are needed, such as choosing head nodes, clustering, and choosing traffic delivery routes. The task of routing is a classic task of building a logical structure of a communication network, however, in conditions of high density networks, it is necessary to use additional opportunities to increase the efficiency of its solution. Classical routing methods and algorithms operate, as a rule, with one selection criterion, which may not be an effective solution in such conditions. In high-density IoT wireless networks, more parameters must be taken into account, since the quality of the route in them depends on many factors. Thus, to improve the efficiency of IoT networks, it is important to develop a routing method according to a number of criteria. This problem is the subject of the present work. The aim of the work is to develop a method for multi-criteria traffic routing in a high-density IoT network. To achieve the goal, the paper proposes an approach to the use of Gray Relational Analysis, which makes it possible to effectively solve the problem of multi-criteria route optimization, including with a small amount of initial data. The object of the study is the Internet of Things network. The subject of the study is the multi-criteria routing method implemented using Gray Relational Analysis. The results of simulation modeling showed the effectiveness of the proposed method in comparison with the methods of single-criteria route selection. The method used is the method of Gray Relational Analysis, which allows solving problems of multicriteria optimization. The novelty of the work lies in the proposed method of applying Gray Relational Analysis to solve a multicriteria routing problem in a high-density IoT network. The result of the work is a method of applying Gray Relational Analysis in the problem of multi-criteria traffic routing in a high-density IoT network. Theoretical/Practical significance. The theoretical significance of the obtained results lies in the description of a new method of applying Gray Relational Analysis in the routing problem and confirmation of its effectiveness by simulation results. The practical significance lies in the fact that this method can be used in traffic routing protocols in high-density IoT networks.

 Known methods of ensuring information security of information and telecommunication networks with the use in modern conditions are not effective enough, since not all means of detecting external threats are used. In this article, the authors raise the issue of the possibility of using the procedure for determining IP geolocation in the framework of ensuring the information security of the network. Purpose: to ensure the level of security of the information and telecommunications network above the required value by effectively detecting external intruders through the use of tools for determining the geolocation of the intruder in the process of ensuring information security. Result: a method is proposed for improving the security of an information and telecommunication network, taking into account the introduction of software for determining the geolocation of an intruder after intrusion detection.

Modern computer networks (CN), having a complex and often heterogeneous structure, generate large volumes of multi-dimensional multi-label data. Accounting for information about multi-label experimental data (ED) can improve the efficiency of solving a number of information security problems: from CN profiling to detecting and preventing computer attacks on CN. The aim of the work is to develop a multi-label artificial neural network (ANN) architecture for detecting and classifying computer attacks in multi-label ED, and its comparative analysis with known analogues in terms of binary metrics for assessing the quality of classification. A formalization of ANN in terms of matrix algebra is proposed, which allows taking into account the case of multi-label classification and the new architecture of ANN with multiple output using the proposed formalization. The advantage of the proposed formalization is the conciseness of a number of entries associated with the ANN operating mode and learning mode. Proposed architecture allows solving the problems of detecting and classifying multi-label computer attacks, on average, 5% more efficiently than known analogues. The observed gain is due to taking into account multi-label patterns between class labels at the training stage through the use of a common first layer. The advantages of the proposed ANN architecture are scalability to any number of class labels and fast convergence.

The remote electronic voting system based on homomorphic encryption and blockchain technologies is analyzed. The existing methods of protecting the voting system from an attack related to incorrect filling a ballot by the voter are studied. The method to protect against an attack of violation of the rules for filling a ballot as a whole is developed, which increases the security of voting system by ensuring secrecy of total number of votes given by voter during the verification correctness of filling a ballot.