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Cognitive Radio System Operational Control Algorithm

Blagodatsky G.A., Kopysov A.A., Khvorenkov V.V., Baturin I.S.


The paper presents an algorithm for optimal control of the cognitive radio communication system. The algorithm is based on the application of decision-making criteria in a dynamic environment. The basis of the algorithm is to solve the optimization problem of maximizing the coefficient of efficiency of the system in a given mode. Thus, the cognitive radio system can choose the most optimal mode of operation, both in a specific situation Tj and choose the general preferred Ei in the integrated assessment of the external situation.

For efficient information transfer, with a significantly discharged battery, the radio system needs to switch to E3 (power 1, 3, 10 W; speed 2400, 9600 bps; CCM type (modulation type) 4FSK, QPSK, QPSK; frequency 30 ... 300 VHF MHz; Band 6.25 / 12.5; 6.25 / 12.5; 25/50/100/150 kHz) mode. To increase the efficiency of information transfer in this mode, it is also advisable to continue the control of signal-code constructions. When continuing to work in time constraints, it is necessary to switch to the E4 (power 1, 3, 10 W; speed 2400, 9600 bps; CCM type (modulation type) 4FSK, QPSK, QPSK; Frequency 300 ... 3000 UHF MHz; Band 6.25 / 12.5; 6.25 / 12.5; 25/50/100/150 12.5 kHz) operating mode and direct the resources of the radio system to control the transmission power, thereby increasing the efficiency by increasing the energy of the radio line. To transmit the digital speech with a discharged battery, it is necessary to switch to E1 (power 1, 10, 100 W; speed 2400, 1200, 800 bit / s; CCM type (modulation type) OFDM (SSB), QPSK; Frequency 3 ... 30, HF MHz; 3.1 kHz band) mode and to increase the efficiency; and the control of signal-code structures is required here. When time constraints occur, the radio system needs to switch to E2 (power 1, 3, 10 W; speed 2400, 1200, 800 bit / s; CCM type (modulation type) 4FSK, QPSK, QPSK; Frequency 30 ... 300, VHF (VHF) MHz; Band 6.25 / 12.5; 6.25 / 12.5; 25/50/100/150 kHz) mode of operation and to increase the reliability of reception and transmission; and the resources are required to be spent on transmit power control.

Considering the efficiency of the radio system in analog and digital modes, we can conclude that, when time constraints occur, it is effective to control the transmitter power (increase the energy of the radio line). However, when working in digital modes, the decrease in efficiency is much slower than when using analog modes. Analysis of operation within radio power limitations also shows a slower decrease in the efficiency with digital modes; moreover, the resource consumption rate is significantly reduced in digital modes, while it is sharply increased in analog modes.


cognitive, radio, optimal control, efficiency, decision making, stochastic environment

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References References

Rupali B.P., Kulat K.D., Gandhi A.S. SDR Based Energy Detection Spectrum Sensing in Cognitive Radio for Real Time Video Transmission. Modelling and Simulation in Engineering, 2018, Article ID 2424305, 10 p. doi: org/10.1155/2018/2424305.

Tanveer A., Khan Z.U., Malik A.N., Qureshi I.M., Lee S. Flexible Queuing Model for Number of Active Users in Cognitive Radio Network Environment. Wireless Communications and Mobile Computing, 2018.

Halloush R., Musa A., Salameh H.B., Halloush M., Almalkawi I. A resource sharing platform for resource-constrained software defined cognitive radio networks. Fifth International Conference on Software Defined Systems (SDS), Barcelona, 2018, pp. 32-39. doi: 10.1109/


Fabio Principe, Giacomo Bacci, Filippo Giannetti, Marco Luise. Software-Defined Radio Technologies for GNSS Receivers: A Tutorial Approach to a Simple Design and Implementation. International Journal of Navigation and Observation, 2011, Article ID 979815, 27 p. doi: org/10.1155/2011/979815.

Van Tam Nguyen, Frederic Villain, Yann Le Guillou. Cognitive Radio RF: Overview and Challenges. VLSI Design, 2012, Article ID 716476, 13 p. doi: org/10.1155/2012/716476.

Хворенков В. В., Батурин И. С., Савельев А. В. Автоматизированное рабочее место главного конструктора радиоэлектронных средств на основе теории многоагентных систем // Вестник ИжГТУ имени М. Т. Калашникова. 2017. Т. 20, № 4. С. 77–81. doi: 10.22213/2413-1172-2017-4-77-81

Использование технологии «интернет вещей» для создания автоматизированных систем контроля и тестирования радиосистем / А. Н. Копысов, В. В. Хворенков, А. А. Зыкин, М. М. Марков, А. А. Богданов // Успехи современной радиоэлектроники. 2018. № 12. С. 71–76. doi: 10.18127/j20700784-201812-15

Растригин Л. А. Адаптация сложных систем. Рига : Зинатне, 1981. 375 с.

Анализ иерархической модели автоматизированной системы управления параметрами радиолиний когнитивной радиосистемы / Г. А. Благодатский, А. Н. Копысов, В. В. Хворенков, И. С. Батурин // Наукоемкие технологии в космических исследованиях Земли. 2018. Т. 10, № 6. С. 51–67. DOI: 10.24411/


Blagodatsky G.A., Kopysov A.N., Khvorenkov V.V., Baturin I.S. Research and development of hierarchical models of automated control systems for the parameters of the radio line of the cognitive radio system // Сб. тр.V Междунар. конф молодежной школы «Информационные технологии и нанотехнологии» (Самара, 21–24 мая 2019 г.). Самара : Новая техника, 2019. С. 1–11.

Канторович Л. В. Математико-экономические работы. Новосибирск : Наука, 2011. 760 с.

Dantzig G.B. and Thapa M.N. Linear programming. Springer-Verlag, 2003, 448 p. doi: 10.1007/b97283

Мюшик Э., Мюллер П. Методы принятия технических решений. М. : Мир, 1990. 208 с.

Triantaphyllou, Evangelos. Multi-criteria decision making methods: a comparative study. Applied optimization. 44. Dordrecht, Netherlands, Kluwer Academic Publ., 2000, 320 p. doi: 10.1007/978-1-4757-3157-6

Brockmann Erich N., Anthony William P. Tacit knowledge and strategic decision making. Group & Organization Management, December 2016, 27, pp. 436-455. doi: 10.1177/1059601102238356

Jonathan Rosenhead, Martin Elton, Shiv K. Gupta. Robustness and Optimality as Criteria for Strategic Decisions. Operational Research Quarterly, 1972, 23, pp. 413-431.

Saaty Thomas L. Relative Measurement and its Generalization in Decision Making: Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors - The Analytic Hierar-chy/Network Process. Review of the Royal Academy of Exact, Physical and Natural Sciences, Series A: Mathe-matics (RACSAM), 2008, vol. 102, no. 2, pp. 251-318. doi: 10.1007/bf03191825

Liu Z., Huang M., Tang Z., Liu T. Selection and Evaluation of Assembly Dimension Chain Based on Analytical Hierarchy Process. Proc. of the Seventh Asia International Symposium on Mechatronics: Lecture Notesin Electrical Engineering, 2000, vol. 588. Singa-pore, Springer. doi: 10.1007/978-981-32-9437-0_89

Zhidyaev A., ZagidullinYu.T., Kopysov A., Khvorenkov V., Klimov I. Development of signal detection algorithm for multi-rate HF telecommunication sys-tem. Proc. International Siberian Conference on Control and Communications (SIBCON-2016) (May 12-14, 2016). IEEE, 2016, pp. 866-869. doi: 10.1109/SIBCON.2016.7491834

Kopysov A., Klimov I., Zagidullin Yu., Muravev V., Muraveva O. The use of polarization characteristic of ionosphere for data communications. Proc. International Conference on Mechanical Engineering, Automation and Control Systems (MEACS). IEEE, 2014, pp. 1-2. doi: 10.1109/MEACS.2014.6986926


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