Category: Issue 3 (197)

Issue 3 (197), article 6

DOI:https://doi.org/10.15407/kvt197.03.080

Cybernetics and Computer Engineering, 2019, 3(197), pp.

Kiforenko S.I.¹, DSc (Biology), Senior Researcher,
Leading Researcher of the Department of Mathematical and Technical
Methods Application in Biology and Medicine
e-mail: skifor@ukr.net

Hontar T.M.¹, PhD (Biology), Senior Researcher,
Senior Researcher of the Department of Mathematical and Technical
Methods Application in Biology and Medicine
e-mail: gtm_kiev@ukr.net

Orlenko V.L.², PhD (Medicine), Senior Researcher,
Head of the Department of Scientific-Advisory Department of Ambulatory and Preventive Care
for Patients with Endocrine Pathology
e-mail: orleva@ukr.net

Ivaskiva K.Y.², PhD (Medicine),
Senior Researcher of the Department of Scientific-Advisory Department of Ambulatory and Preventive Care
for Patients with Endocrine Pathology
e-mail: k_iva@ukr.net

Obelets T. A.¹,
Junior Researcher of the Department of Mathematical and Technical
Methods Application in Biology and Medicine
e-mail: obel.tet@gmail.com

¹International Research and Training Centre for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
40, Glushkov av., Kyiv, 03187, Ukraine

²State Institution “V.P. Komisarenko Institute of Endocrinology and Metabolism of NAMS of Ukraine”,
69, Vyshgorodska st., Kyiv, 04114, Ukraine

INFORMATION TECHNOLOGY FOR SUPPORTING SELF-CONTROL IN THE FORMATION OF A RATIONAL LIFESTYLE FOR DIABETICS PATIENTS

Introduction. Modern Diabetes mellitus is dangerous, chronic endocrine disease that originates from the disorder of metabolism, connected primarily with violation of carbohydrate exchange. Providing the necessity of independent self-control of health status of diabetes patients is the urgent problem of present time. The use of information technologies and mobile medicine facilitates enhancing of efficiency of self-control of health status by the patient.

The purpose of the work is to develop a combined information technology to enhance the efficiency of glycemic self-control in case of diabetes at different stages of treatment.

Results. We offer the algorithm of determination of the state of glycaemia regulation system based on the analysis of test results of glucose tolerance and the extended classification scale of glycaemia control (norm, violated tolerance (non-obvious diabetes, latent form), risk zone) that enhances the split ability of standardized methodology and enables timely measures of prophylactic actions to prevent real violations in glycaemia control system. An algorithm is implemented into software for desktops, tablets and mobiles under Android OS.

The developed information technology of decision-making support to choose an adequate mode of activity and meals for patients with diabetes helps to calculate the misbalance between energy gained by chosen menu (by the set of foods and dishes) and energy spent at the different types of the pre-arranged activity (physical, intellectual etc.).

Conclusions. Introduction of the designed algorithm in mobile devices is aimed to facilitate the availability of early diagnostics of violations in carbohydrate regulation system that may assist to reduce risks of emergence of obvious forms of diabetes mellitus. The use in the designed technology the principle of the external combined adjustment, that unites positive features of adjustment by disturbance with adjustment with feedback provides the possibility to enhance efficiency of self-control of the health status for the patient. The technology is implemented for desktops, tablets and mobiles on Android OS and enables access to information for the user with different degree of violation in carbohydrate exchange adjustment — at the state of preambulatory help and during the treatment.

Keywords: information technology, diabetes mellitus, self-control of patient’s health, management principles, M-medicine mobile media: information technology, self-monitoring of patient’s health, management principles, mobile applications.

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Received 19.06.2019

Issue 3 (197), article 5

DOI:https://doi.org/10.15407/kvt197.03.065

Cybernetics and Computer Engineering, 2019, 3(197), pp.

Aralova N.I., PhD (Engineering), Senior Researcher,
Senior Researcher of the Department of Controlled Processes Optimization
email: aralova@ukr.net

Aralova A.A., PhD (Phys and Math),
Researcher of the Department of Methods for Discrete Optimization,
Mathematical Modelling and Analyses of Complex Systems
email: aaaralova@gmail.com

Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine,
40, Acad.Glushkov av., 03187, Kyiv, Ukraine

MATHEMATICAL MODELS OF CONFLICT CONTROLLED PROCESSES UNDER FUNCTIONAL SELF-ORGANIZATION OF THE RESPIRATORY SYSTEM

Introduction. Modern human life imposes more stringent requirements for ability to adapt to increasingly complex conditions, such as unfavorable environmental conditions, potential danger, increased responsibility, extreme physical exertion and their combined effect. This leads to a decrease in exercise tolerance, unfavorable changes in hemodynamic parameters, and disorders in the functional activity of other body organs and tissues. The decisive role in the adaptation of the organism to physical and psycho-emotional stress belongs to the oxygen transport system. However, at present, the possibilities of instrumental methods are rather limited, moreover, they can only characterize the state of the body at the current moment, and not predict its reserve capabilities in case of disturbances in the internal and external environment, in the process of recovery and rehabilitation. Partially, this gap can be filled by mathematical models of the functional respiratory system, which allow to imitate disturbances of the internal and external environment of an organism in the dynamics of the respiratory cycle and, thus, predict possible controlling actions of the organs of self-regulation of the organism when adapting to these disturbances.

The purpose of the article is to build a mathematical model of a functional respiration system that simulates resolving a conflict situation between executive and managing bodies of self-regulation in the conflict for oxygen, which allows predicting the parameters of self-organization of the respiratory system under internal and external disturbances.

Results. A mathematical model of mass transfer and mass transfer of respiratory gases in the human body is presented in the form of a system of non-linear differential equations, which is a controlled dynamic system, the state of which is determined at each time point by oxygen and carbon dioxide stresses in each structural link of the respiratory system (alveoli, blood and tissues). The control (self-regulation) of the condition under permanent or at a given time interval of the current disturbance (high functional activity of certain groups of tissues) is carried out by the self-regulation organs — respiratory muscles that form the necessary level of ventilation to compensate for the resulting hypoxic states, cardiac muscle providing the minute blood volume, and smooth muscles, vessels, vasodilation and vasocostriction which contributes to the distribution of systemic blood flow through the organs and tissues. There are also passive mechanisms of self-regulation: the concentration of hemoglobin in the blood, myoglobin in skeletal and cardiac muscles, their ability to oxygenate, the concentration of buffer bases in the blood etc. It is assumed that the decision on the choice of the values of compensating influences is made by the decision center based on the information activity and degree of oxygen deficiency, excessive accumulation of carbon dioxide in all tissue regions of the body, is transmitted to the executive bodies of self-regulation, increases their functional activity, which ensures the implementation of the main function of respiration.

Conclusion The per-set mathematical model of the FRS allows the researcher to analyze the oxygen and carbon dioxide regimes of body in dynamics at various levels of functional load and under various environmental conditions; to form such regimes of the external respiration system, which contribute to an increase in the oxygen supply in the body and thereby increase the resource of the cardiac muscle during the regulation of hypoxic states that occur when the combined effects of hypobaric hypoxia and hypermetabolic hypoxia; predict the state of the body during various physical efforts and evaluate the effectiveness of the preparation process; plan and distribute heavy loads, taking into account the functionality of the individual and depending on the prevailing situations. The work presents the results of numerical experiments with a model for simulating internal (physical activity) and external (hypoxic hypoxia) disturbances on the human body.

Keywords: conflict-controlled processes, a functional system of respiration, functional self-organization of the respiratory system, adaptation to stress.

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REFERENCES

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6 Aralova N.I. Mathematical model of the mechanism short- and medium-functional adaptation of breath of persons work in extreme conditions high. Kibernetika i vyčislitelnaâ tehnika. 2015, no 182, pp. 15-25. (in Russian) https://doi.org/10.15407/kvt182.02.045

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Received 20.05.2019

Issue 3 (197), article 4

DOI:https://doi.org/10.15407/kvt197.03.051

Cybernetics and Computer Engineering, 2019, 3(197), pp.

Bondarenko M.A., PhD (Phys and Math),
Assistant Professor, the Department of Medical and Biological
Physics and Medical Informatics
e-mail: bondaren.koma3007@gmail.com

Knigavko V.G., DSc (Biology), Professor,
Head of the Department of Medical and Biological
Physics and Medical Informatics
e-mail: vknigavko@gmail.com

Zaytseva O.V., DSc (Biology), Professor,
the Department of Medical and Biological Physics and Medical Informatics
e-mail: olgvaszay@gmail.com

Rukin A.S., PhD (Phys and Math),
Senior Lecturer of the Department of Medical and Biological Physics and Medical Informatics
e-mail: aleksej.rukin@gmail.com

Kharkiv National Medical University
4, Nauky av., Kharkiv, 61022, Ukraine

MATHEMATICAL MODELING OF DNA DAMAGES IN IRRADIATED CELLS AT DIFFERENT OXYGENATION DEGREES

Introduction. In radiotherapy, the degree of oxygenation of tumors is of vital importance. Tumors with greater oxygenation are much more responsive to radiation therapy than tumors with significant hypoxia: well-oxygenated tumors react 2.5…3 times better. Mathematical modeling of DNA damage of irradiated cells at different degrees of their oxygenation is of current interest.

The purpose of the article is to develop a mathematical model of DNA damage in irradiated cells at different degrees of their oxygenation; to study the dependence of the number of radiation damages of DNA per unit volume of the irradiated medium on the radiation dose and the concentration of oxygen in the medium; to estimate the cell cycle duration depending on the oxygen concentration.

Results. A mathematical model of oxygen effect in cells in the case of irradiation
by X-rays or gamma-radiation is proposed. On the basis of this model, the dependence of the number of radiation DNA damages in the unit volume of the irradiated medium on the radiation dose and the concentration of oxygen in the medium is obtained. Triple damage to DNA molecules is determined by primary radiation damage and attacks of two radicals of oxygen on the DNA molecule.

The effect of potentially lethal lesions (PLL) on survival of cells under irradiation conditions is studied. The phenomenon of increasing the survival of tumor cells in their irradiation under hypoxia conditions is also due to the phenomenon of potentially lethal lesions. The optimal indicator of the severity of the PLL effect is the cell cycle duration. Thus, the task of modeling PLL was reduced to creation of a mathematical model that allows estimating the value of that indicator depending on the oxygen concentration.

Conclusions. The mathematical model created in the article allows estimating the number of radiation DNA damages in the unit volume of the irradiated medium on the radiation dose and the concentration of oxygen in the medium. The dependence of the cell cycle duration on the oxygen concentration was obtained.

Keywords: radiobiology, mathematical modeling, oxygen effect, oxygen enhancement ratio, DNA damage.

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30 Tannock I. Oxygen diffusion and the distribution of cellular radiosensitivity in tumours. Br. J. Radiol. 1972. Vol. 45, pp. 515-524. https://doi.org/10.1259/0007-1285-45-535-515

31 Grimes D. R., Fletcher A. G., Partridge M. Oxygen consumption dynamics in steady-state tumour models. R. Soc. Open Sci. 2014. Vol. 1. https://doi.org/10.1098/rsos.140080

Received 29.03.2019

Issue 3 (197), article 3

DOI:https://doi.org/10.15407/kvt197.03.033

Cybernetics and Computer Engineering, 2019, 3(197), pp.

Zhiteckii L.S.¹, PhD (Engineering),
Acting Head of the Intelligent Automatic Systems Department
e-mail: leonid_zhiteckii@i.ua

Azarskov V.N.², DSc. (Engineering), Professor,
Chief of the Aerospace Control Systems Department,
e-mail: azarskov@nau.edu.ua

Solovchuk K.Y.³,
Assistant of the Department of Computer Information Technologies and Systems
e-mail: solovchuk_ok@ukr.net

¹International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

²National Aviation University, Kyiv, Ukraine.
1, Kosm. Komarova av., Kyiv, 03680, Ukraine

³Poltava National Technical Yuri Kondratyuk University, Poltava, Ukraine.
24, Pershotravneva av., Poltava, 36011, Ukraine

SOLVING A PROBLEM OF ADAPTIVE STABILIZATION FOR SOME STATIC MIMO SYSTEMS

Introduction. The adaptive stabilization of some classes of uncertain multivariable static plants with arbitrary unmeasurable bounded disturbances is addressed in this article. The cases where the number of the control inputs does not exceed the number of the outputs are studied. It is assumed that the plant parameters defining the elements of its gain matrix are unknown. Again, the rank of this matrix may be arbitrary. Meanwhile, bounds on external disturbances are supposed to be known. The problem stated and solved in this work is to design adaptive controllers to be able to ensure the boundedness of the all input and output system’s signals in the presence of parameter uncertainties.

The purpose of this article is to show that it is possible to stabilize any uncertain multivariable static plant which gain matrix may be either square or nonsquare and may have an arbitrary rank remaining unknown for the designer.

Methods. The methods based on recursive point estimation of unknown plant parameters are utilized to design the adaptive inverse model-based controller.

Results. The asymptotic properties of the adaptive controllers have been established. Simulation results have been presented to support the theoretic studies.

Conclusion. The adaptive control laws proposed in this article can guarantee the boundedness of all the signals generated by the feedback control systems. However, this important feature will achieve via an “overparameterization” of these systems. Nevertheless, the simulation experiments demonstrate their efficiency.

Keywords: adaptive control, boundedness, discrete time, estimation algorithm, feedback, multivariable system, uncertainty.

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REFERENCES

1 Maciejowski J. M. Multivariable Feedback Design. Wokinghan: Addison-Wesley, 1989.

2 Skogestad S., Postlethwaite I. Multivariable Feedback Control. UK, Chichester: Wiley, 1996.

3 Albertos P., Sala A. Multivariable Control Systems: An Engineering Approach. London: Springer, 2006.

4 Pukhov G. E., Zhuk K. D. Synthesis of Interconnected Control Systems via Inverse Operator Method. Kiev: Nauk. dumka, 1966. (in Russian).

5 Lyubchyk L. M. Disturbance rejection in linear discrete multivariable systems: inverse model approach. Prep. 18th IFAC World Congress (2011, Milano, Italy). Milano, 2011, pp. 7921-7926. https://doi.org/10.3182/20110828-6-IT-1002.02121

6 Skurikhin V. I., Gritsenko V. I., Zhiteckii L. S., Solovchuk K. Yu. Generalized inverse operator method in the problem of optimal controlling linear interconnected static plants. Dopovidi NAN Ukrainy. 2014. no. 8, pp. 57-66. (in Russian). https://doi.org/10.15407/dopovidi2014.08.057

7 Polyak, B.T., Shcherbakov, P. S. Robust Stability and Control. Moscow: Nauka, 2002. (in Russian).

8 Kuntsevich V. M. Control under Uncertainty: Guaranteed Results in Control and Identification Problems. Kyiv: Nauk. dumka, 2006. (in Russian).

9 Sokolov V.F. Robust Control with Bounded Disturbances. Syktyvkar: Komi Scientific Center, Ural Branch of the RAS, 2011. (in Russian).

10 Zhiteckii L. S., Solovchuk K. Yu. Pseudoinversion in the problems of robust stabilizing multivariable discrete-time control systems of linear and nonlinear static objects under bounded disturbances. Journal of Automation and Information Sciences. 2017. vol. 49. no. 5, pp. 35-48. https://doi.org/10.1615/JAutomatInfScien.v49.i5.30

11 Zhitetskii L. S., Skurikhin V. I., Solovchuk K. Yu. Stabilization of a nonlinear multivariable discrete-time time-invariant plant with uncertainty on a linear pseudoinverse model. Journal of Computer and Systems Sciences International. 2017. vol. 56, no. 5, pp. 759-773. https://doi.org/10.1134/S1064230717040189

12 Zhiteckii L. S., Azarskov V. N., Solovchuk K. Yu., Sushchenko O. A. Discrete-time robust steady-state control of nonlinear multivariable systems: a unified approach. Proc. 19th IFAC World Congress. (2014, Cape Town, South Africa). Cape Town, 2014, pp. 8140-8145. https://doi.org/10.3182/20140824-6-ZA-1003.01985

13 Bunich A.L. On some nonstandard problems of the synthesis of discrete systems. Autom. Remote Control. 2000. no. 6, pp. 994-1002.

14 Fomin V. N., Fradkov A. L., Yakubovich V. A. Adaptive Control of Dynamic Plants. Moscow: Nauka, 1981. (in Russian).

15 Goodwin G.C., Sin K.S. Adaptive Filtering, Prediction and Control. Engewood Cliffs, NJ.: Prentice-Hall, 1984.

16 Landau I. D., Lozano R., M’Saad M. Adaptive Control. London: Springer, 1997. https://doi.org/10.1007/978-0-85729-343-5

17 Zhiteckii L. S., Skurikhin V. I. Adaptive Control Systems with Parametric and Nonparametric Uncertainties. Kyiv: Nauk. dumka, 2010. (in Russian).

18 Narendra K. S., Annaswamy A. M. Stable Adaptive Systems. NY: Dover Publications, 2012.

19 Ioannou P., Sun J. Robust Adaptive Control. NY: Dover Publications, 2013.

20 Astrom K. J., Wittenmark B. Adaptive Control: 2nd Edition. NY: Dover Publications, 2014.

21 Bakan G.M., Volosov V.V., Salnikov N.N. Adaptive control of a linear static plant by a model with unknown parameters. Kibernetika. 1984, no. 2, pp. 63-68. https://doi.org/10.1007/BF01069181

22 Lublinskii B.S., Fradkov A.L. Adaptive control of nonlinear statistical processes with an implicit characteristic. Autom. Remote Control. 1983, no. 4, pp. 510-518.

23 Bakan G.M. Adaptive control of a multi-dimensional static process under nonstatistical uncertainty. Autom. Remote Control. 1987, no. 1, pp. 76-88.

24 Zhiteckii L. S., Solovchuk K. Yu. Adaptive stabilization of some multivariable systems with nonsquare gain matrices of full rank. Cybernetics and Computer Engineering. 2018, no. 2, pp. 44-61. https://doi.org/10.15407/kvt192.02.044

25 Zhiteckii L. S., Solovchuk K. Yu. Robust adaptive pseudoinverse model-based control of an uncertain SIMO memoryless system with bounded disturbances. Proc. IEEE 2nd Ukraine Conference on Electrical and Computer Engineering (UKRCON-2019), Lviv, Ukraine, 2019, pp. 628-633. https://doi.org/10.1109/UKRCON.2019.8879824

26 Azarskov V.N., Zhiteckii L.S., Solovchuk K.Yu. Parametric identification of the interconnected static closed-loop system: a special case. Proc. 12th All-Russian Control Problems Council (VSPU-2014), Moscow, 2014, pp. 2764-2776.

27 Zhiteckii L.S., Azarskov V.N., Solovchuk K.Yu. Adaptive robust control of inter-connected static plants with nonsquare gain matrixes. Proc. 13th All-Russian Control Problems Council (VSPU-2019), Moscow, 2019.

28 Anderson B.D.O., Bitmead R.R., Johnson C.R., Kokotovic P.V., Kosut R.L., Mareels I.M.Y., Praly L., and Riedle B.D. Stability of Adaptive Systems: Passivity and Averaging Analysis. USA, Mas.: MIT Press. 1986.

29 Marcus M., Minc H. A Survey of Matrix Theory and Matrix Inequalities. Boston: Aliyn and Bacon, 1964.

Received 30.05.2019

Issue 3 (197), article 2

DOI:https://doi.org/10.15407/kvt197.03.020

Cybernetics and Computer Engineering, 2019, 3 (197), pp.

Barseghyan V.R., DSc (Phys and Math), Professor,
Leading Researcher of the Institute of Mechanics
of the National Academy of Sciences of Armenia,
Professor of the Faculty of Mathematics
and Mechanics of Yerevan State University
email: barseghyan@sci.am
Yerevan State University, Institute of Mechanics of NAS of Armenia
18, Bakunts st., 0033, Yerevan, Republic of Armenia

THE PROBLEM OF CONTROL OF MEMBRANE VIBRATIONS WITH NON-SEPARATED MULTIPOINT CONDITIONS AT INTERMEDIATE MOMENTS OF TIME

Introduction. Many control processes from various fields of science and technology lead to the necessity to study multipoint boundary value problems of control, in which, along with classical boundary conditions, non-separated multi-point intermediate conditions are also given. A characteristic feature of multipoint boundary value problems of control is the presence of non-separated conditions at several intermediate points of the study interval. Such control problems have important applied and theoretical value, a necessity naturally arises for their investigation in various settings. In this article, the problem of control of vibrations of a rectangular membrane with given initial, final conditions and non-separated values of the deflection function and velocities at intermediate moments of time is considered.

The purpose of the article is to develop a constructive approach to construct a function of control action to control the vibrations of a rectangular membrane with given initial, final conditions and non-separated (non-local) values of the deflection and velocities of membrane points at intermediate moments of time.

Results. By the method of separation of variables, the problem is reduced to the problem of control of ordinary differential equations with given initial, final, and non-separated multipoint intermediate conditions. Using the methods of the theory of control of finite-dimensional systems with multipoint intermediate conditions, a control action to control vibrations of a rectangular membrane is constructed.

Keywords: control of vibrations, membrane vibration, intermediate values, non-separated multipoint conditions.

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REFERENCES

1 Butkovskiy A.G. Methods of the systems control with distributed parameters. Moscow: Nauka. 1975. (in Russian).

2 Sirazetdinov T.K. Systems optimization with distributed parameters. Moscow: Nauka. 1977. (in Russian)

3 Znamenskaya, L.N. Control of elastic vibrations. Moscow: FIZMATLIT. 2004. (in Russian)

4 Kopets M.M. Optimal control of vibrations of a rectangular membrane. Kibernetika i vycislitelnaa tehnika. 2014. Iss. 177, pp. 28-42. (in Russian).

5 Barseghyan V.R. Control of Compound Dynamic Systems and of Systems with Multipoint Intermediate Conditions. Moscow: Nauka. 2016. (in Russian).

6 Barseghyan V.R. and Barseghyan T.V. On an Approach to the Problems of Control of Dynamic System with Nonseparated Multipoint Intermediate Conditions. Automation and Remote Control, 2015, Vol. 76, no 4, pp. 549-559. https://doi.org/10.1134/S0005117915040013

7 Barseghyan V.R., Saakyan, M. A. The optimal control of wire vibration in the states of the given intermediate periods of time. Proc. of NAS RA: Mechanics, 2008, 61(2), pp. 52-60. (in Russian)

8 Barseghyan V.R. Optimal control of a membrane vibration with fixed intermediate states. Proceedings of YSU. 1998. 188 (1), pp. 24-29. (in Russian).

9 Barseghyan V.R. On the problem of boundary control of string oscillations with given states at intermediate moments of time. Proceedings The XIth All-Russian Congress on Basic Problems of Theoretical and Applied Mechanics (Kazan, 20-24th of Aug, 2015), Kazan, 2015. part 1. P. 354-356. (in Russian).

10 Barseghyan V.R. About one problem of optimal boundaery control of string vibrations with restrictions in the intermediate moment of time. Proceedings of the 11th International Chetaev Conference. Analytical mechanics, stability and control (Kazan, 14 – 18th of June, 2017). Kazan, 2017. Vol. 3, part 1. P. 119-125. (in Russian).

11 Korzyuk V.I., Kozlovskia I.S. Two-point boundary problem for the equation of string vibration with the given velocity at the certain moment of time. Proceedings of the Institute of Math. NAS of Belarus. 2010. 18(2), pp. 22-35. (in Russian).

12 Korzyuk V.I., Kozlovskia I.S. Two-point boundary problem for the equation of string vibration with the given velocity at the certain moment of time. Proceedings of the Institute of Math. NAS of Belarus. 2010. 19(1). pp. 62-70. (in Russian).

13 Makarov A.A., Levkin D.A. Multipoint boundary value problemfor pseudodierential equations in multilayer. Vistnyk of V.N. Karazin Kharkiv National University. Ser. Mathematics, Applied Mathematics and Mechanics. 2014. No 1120. Vol. 69, pp. 64-74. (in Ukrainian).

14 Assanova A.T., Imanchiev A.E On the solvability of a nonlocal boundary value problem for a loadedhyperbolic equations with multi-point conditions. Bulletin of the Karaganda University. Series: Mathematics. 2016, no 1 (81), pp. 15-20. (in Russian).

15 Bakirova E.A., Kadirbayeva Zh.M. On a Solvability of Linear Multipoint Boundary Value Problem for the Loaded Differential Equations. Izvestiya NAS RK. Ser. fiz.-mat., 2016, Vol. 5, no 309, pp. 168-175. (in Russian).

16 Krasovsky N.N. The Theory of Motion Control. Moscow: Nauka. 1968. (in Russian).

17 Zubov V.I. Lectures on the Theory of Control. Moscow: Nauka. 1975. (in Russian).

Received 06.05.2019

Issue 3 (197), article 1

DOI:https://doi.org/10.15407/kvt197.03.005

Cybernetics and Computer Engineering, 2019, 3(197), pp.

Gritsenko V.I., Corresponding Member of NAS of Ukraine,
Director of International Research and Training
Center for Information Technologies and Systems
of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine
e-mail:  vig@irtc.org.ua

Surovtsev I.V., DSc (Engineering),
Head of the Ecological Digital Systems Department
e-mail: dep175@irtc.org.ua, igorsur52@gmail.com

Babak O.V., PhD (Engineering), Senior Researcher
of the Ecological Digital Systems Department
e-mail: dep175@irtc.org.ua

International Research and Training Center for Information
Technologies and Systems of the National Academy
of Sciences of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., 03187, Kyiv, Ukraine

5G WIRELESS COMMUNICATION SYSTEM

Introduction. The 5G high-speed mobile communication system is actively developing in many countries around the world. It is important to understand the scientific and technical prerequisites of 5G wireless technology in order to effectively utilize them in the new intelligent information technology.

The purpose of the article is to describe in an accessible way the architectural features, communication methods, the Internet and the tasks that underlie 5G.

Results. It is shown that specific technical and technological problems have to be solved in order to reach the wide possibilities of 5G mobile communication. At the same time, 5G technology will soon be standardized and implemented around the world, including Ukraine. The ability to connect many external devices in conditions of electromagnetic interference using LTE connections in the case of distribution over a large area and with strict requirements for process delays makes it possible to state that 5G wireless technology is necessary and indispensable in research and production.

Conclusions. Wireless technology 5G and cloud computing are prerequisites for creating high-speed mobile communications, cyber-physical systems and providing a wide range of services to consumers.

Keywords: technology 5G, mobile communication, communication architecture 5G, Internet, cyberphysical systems.

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REFERENCES

1 Rodriguez J. (Ed.) Fundamentals of 5G Mobile Networks. Wiley, 2015. https://doi.org/10.1002/9781118867464

2 Pankaj Sharma. Evolution of Mobile Wireless Communication Networks-1G to 5G as well as Future Prospective of Next Generation Communication Network. IJCSMC. 2013. Vol. 2, no 8. pp. 47-53.

3 Liu L., Chen R., Geirhofer S. Downlink MIMO in LTE-Advanced: SU-MIMO vs. MU-MIMO. IEEE Communications Magazine. 2012. No 50(2). pp. 140-147. https://doi.org/10.1109/MCOM.2012.6146493

4 Jordan R. and Abdallah C.T. Wireless Communications and Networking: An Overview. IEEE Antennas and Propagation Magazine. 2002. Vol. 44. no 1. pp.185-193. https://doi.org/10.1109/74.997963

5 Approved Draft Standard for IT – Telecommunications and Information Exchange Between Systems – LAN/MAN – Specific Requirements – Part 11: Wireless LAN Medium Access Control and Physical Layer Specifications – Amd 4: Enhancements for Very High Throughput for operation in bands below 6GHz”. 2013. pp. 1-456.

6 Palaskas Y., Ravi A. and Pellerano S. MIMO Techniques for High Data Rate Radio Communications, IEEE Custom Integrated Circuits Conference, 2008. CICC 2008. https://doi.org/10.1109/CICC.2008.4672042

7 Hu Fei. Opportunities in 5G Networks: A Research and Development Perspective. CRC Press, 2016. https://doi.org/10.1201/b19698

8 World’s First 5G WiFi 802.11ac SoC. 2012. URL: https://www.broadcom.com/docs/press/80211ac_for_Enterprise.pdf

9 Wallace J.W. and Jensen M.A. Mutual Coupling in MIMO Wireless Systems: A Rigorous Network Theory Analysis. IEEE Transactions on Wireless Communications. 2004. Vol. 3. no 4. pp. 1317-1325. https://doi.org/10.1109/TWC.2004.830854

10 More Spectrum – Especially for Small Cells. URL: https://www.qualcomm.com/documents/1000x-more-spectrum-especially-small-cells

11 Yavuz M., Meshkati F., Nanda S. Interference Management and Performance Analysis of UMTS/HSPA+ Femtocells. IEEE Communications Magazine. 2009. Vol. 6, no 9. https://doi.org/10.1109/MCOM.2009.5277462

12 Tudzarov A., Janevski T. Functional Architecture for 5G Mobile Networks. International Journal of Advanced Science and Technology. 2011, no 3(2), pp. 65-78. https://doi.org/10.5296/npa.v3i1.656

13 Zahir T., Arshad K., Nakata A. and Moessner K. Interference Management in Femtocells. Communications Surveys & Tutorials. 2013. Vol. 15. no 1. pp. 293-311. https://doi.org/10.1109/SURV.2012.020212.00101

14 Telecommunication Management; Self-Organizing Networks (SON); Concepts and requirements, TS 32.500 (Release 11), 2011.

15 Feng S. and Seidel E. Self-Organizing Networks (SON) in 3GPP Long Term Evolution. NOMOR whitepaper, May 2010.

16 Mobile and Wireless Communications Enablers for the Twenty-Twenty Information Society 5G. FP7 ICT project. URL: https://www.metis2020.com

17 Fettweis G. and Alamouti S. 5G: Personal Mobile Internet beyond What Cellular Did to Telephony. IEEE Communications Magazine. 2014, no 52(2), pp. 140-145. https://doi.org/10.1109/MCOM.2014.6736754

18 Xiang Wei, Zheng Kan et al. (Eds.) 5G Mobile Communications. Springer, 2016. 690 p. https://doi.org/10.1007/978-3-319-34208-5

19 Rajagopal, S., Abu-Surra, S., Pi, Z. and Khan, F.Antenna Array Design for Multi-Gbps mmWave Mobile Broadband Communication. Samsung, IEEE Globecom. 2011. https://doi.org/10.1109/GLOCOM.2011.6133699

20 Rusek F., Persson D., Lau B.K. Scaling up MIMO: Opportunities and Challenges with Very Large Arrays. IEEE Signal Processing Magazine. 2013. Vol. 30, no 1, pp. 40-60. https://doi.org/10.1109/MSP.2011.2178495

21 Bizaki H.K. (Ed.) Towards 5G Wireless Networks: A Physical Layer Perspective. ExLi4EvA, 2016. https://doi.org/10.5772/63098

22 Pirmoradian M., Adigun O. and Politis C. Adaptive Power Control Scheme for Energy Efficient Cognitive Radio Networks. IEEE ICC 2012 Workshop on Cognitive Radio and Cooperation for Green Networking (10-15th of June 2012, Ottawa, Canada). Ottawa, 2012. https://doi.org/10.1109/ICC.2012.6364836

23 GSR 2012: Spectrum Policy in a Hyper-connected Digital Mobile World, 2012. URL: http://www.ictregulationtoolkit.org/en/toolkit/docs/Document/4030

24 Gur G. and Alagoz F. Green Wireless Communications via Cognitive Dimension: An Overview. Network, IEEE. Vol. 25, no. 2, pp. 50-56, March-April 2011. https://doi.org/10.1109/MNET.2011.5730528

25 Chowdhury N. M. K. and Boutaba R. Network Virtualization: State of the Art and Research Challenges. IEEE Communications Magazine. 2009, no 47(7), pp. 20-26. https://doi.org/10.1109/MCOM.2009.5183468

26 Osseiran A., Monserrat J.F., Marsch P., Dohler M., Nakamura T. (ed.) 5G Mobile and Wireless Communications Technology. Cambridge University Press, 2016.

27 Mavromoustakis C., Mastorakis G., Batalla J. (edit.) Internet of Things (IoT) in 5G Mobile Technologies. Springer, 2016. https://doi.org/10.1007/978-3-319-30913-2

28 Gold N., Mohan A., Knight C. and Munro M. Understanding Service-Oriented Software. IEEE Software. 2004. Vol. 21, no. 2, pp. 71-77. https://doi.org/10.1109/MS.2004.1270766

29 Fitzek F.H.P. and Katz M. Mobile Clouds: Exploiting Distributed Resources in Wireless, Mobile and Social Networks. NJ: Hoboken, 2014. https://doi.org/10.1002/9781118801338

30 Platzer A. Logical Foundations of Cyber-Physical Systems. Springer, Cham, 2018. 659 p. https://doi.org/10.1007/978-3-319-63588-0

31 Sabella R., Thuelig A, Carrozza M.C., Ippolito M. Industrial automation enabled by robotics, machine intelligence and 5G. 2018. URL: https://www.ericsson.com/en/ericsson-technology-review/archive/2018/industrial-automation-enabled-by-robotics-machine-intelligence-and-5g

32 Perry Lee. The architecture of the Internet of things. DMK-Press, 2019 . (in Russian).

33 Odarchenko R.S., Abakumova A.O., Dyka N.V. Doslidzhennya vymoh do stilnykovykh merezh novoho pokolinnya ta mozhlyvosti yikh rozhortannya v Ukrayini. Problems of Informatization and Management. 2016. Vol. 2(54), pp. 52-59. (in Ukrainian).

Received 03.06.2019