Method Ensuring Electromagnetic Compatibility With Cognitive Frequency Resource Allocation in a Mobile Communication System

2017;
: pp. 25 - 30
1
Kharkov National University of Radio Electronics, (Ukraine)
2
Kharkov National University of Radio Electronics, (Ukraine)

Individual elements of systems and networks using radio links, to interfere with other network elements, and in turn, they are subject to interference effects. Designed by many methods, techniques, theoretical studies devoted to improving the electromagnetic environment in radio, the problem of electromagnetic compatibility. We can assume that in a hospital, especially when considering dueling (transmitter — receiver) electromagnetic compatibility problems at the design stage is almost solved. The situation itself and the electromagnetic environment complicates the fact that this situation is often made various random factors that bear unpredictable character. Under these conditions in advance to calculate the electromagnetic environment and to solve the problem of electromagnetic compatibility with sufficient accuracy is not always possible, and often impossible due to a priori uncertainties.

With the advent of mobile network signal and interference environment has become much more complicated. An increasing number of radio electronic devices for different purposes lead to the formation of the plural character of the electromagnetic interactions between them. At the same time it becomes even more fundamental shortage of frequency resources, exacerbated by the problem of electromagnetic compatibility. Find ways to solve this problem, you can use cognitive frequency resource allocation with frequency reuse. Cognitive system with the allocation of resources, including the frequency and must have self- mechanisms with different levels of ability to adapt to a changing radio environment. At the same time self-arrangements based on the principles of learning and artificial intelligence.

When the cognitive spectrum distribution network, each subscriber station must continuously be monitored spectrum for the presence of free channels. The analysis results are transmitted base station, and it takes the final decision on channel availability. When deciding the base station based on results of spectrum analysis, the location information and the auxiliary information.

An algorithm for solving the problem of optimizing the allocation of frequency resource for mobile networks. The algorithm is based on local optimization method — one of the approximate methods of discrete programming. In this case, local optimality condition is that the subscriber station is assigned the next operating frequency to be closest to the assigned frequency in the previous step, but it must be carried out electromagnetic compatibility conditions

1. Багатоканальний електрозв’язок та телекомунікаційні технології: підручник з грифом МОН України / [В. В. Поповський, В. А. Лошаков, С. О. Сабурова ті інш.]; під редакцією В. В Поповського. — Харків: СМІТ, 2010. — 469 с. 2. Mitola J. III. Cognitive Radio for Flexible Mobile Multimedia Communications// Mobile Multimedia Communications (MoMuC’99), IEEE International Workshop, San Diego, CA, USA, Nov. 1999. — P. 3–10. 3. Mitola J. III. Cognitive Radio. An Integrated Agent Architecture for Software Defined Radio: Doctor of Technology Dissertation/ Mitola Joseph III. — Sweden: Royal Institute of Technology, 2000. — 313 р. 4. Гурьянов И. О. Когнитивное радио: новые подходы к обеспечению радиочастотным ресурсом перспективных радиотехнологий / И. О. Гурьянов // ЭЛЕКТРОСВЯЗЬ. — 2012. — № 8. — С. 5–8. 5. Кизима С. В. Когнитивные радиотехнологии. Аспекты практической реализации [С. В. Кизима, С. Г. Митченков, Б. Б. Емельянников] // ЭЛЕКТРОСВЯЗЬ. — 2014. — № 9. — С. 44–48. 6. Metzger B. H. Spectrum management technique / B. H. Metzger // Presented at the 38-th National ORSA Meeting, Detroit, Michigan, USA, 1970 р. 34–46. 7. Survey on Spectrum Management in Cognitive Radio Networks / [I. F. Akyildiz, W. Y. Lee, M. C. Vuran, M. A. Shantidev] // IEEE Communications Magazine. — 2008. — Vol. 46. — P. 40–48. — DOI: 10.1109/MCOM. .2008.4473090. 8. Ghasemi A. Spectrum sensing in cognitive radio networks: Requirements, hallenges, and design trade-off / A.Ghasemi, S.E. Sousa // IEEE Communications Magazine. — 2008. — Vol. 46, — P. 32–39. — DOI: 10.1109/MCOM. 2008.4473090. 9. Ермаков А. И. Алгоритмы оптимизации выделяемой полосы частот для группы однотипных радиоэлектронных средств по условиям обеспечения их ЭМС / А. И. Ермаков, Н. В. Соловьев // Радиотехника. Научно- техн. и теор. журнал. — М.: Радио и связь, 1983. — № 3. — Р. 123–126. 10. Коляденко А. В. Оптимизация распределения частотного ресурса в когнитивных радиосетях / А. В. Коляденко // Материалы XVІІ Международного молодежного форума «Радиоэлектроника и молодежь в XXI веке». Харьков, 2013. — С. 103–104. 11. Коляденко Ю. Ю. Анализ алгоритмов управления частотным ресурсом в системах сотовой связи / Ю. Ю. Коляденко // Международная научная конференция «Интеллектуальные системы принятия решений и прикладные аспекты информационных технологий» (ISDMIT’2006). — Евпатория, 2006. — С. 56–57. 12. Кристофидес Н. Теория графов. Алгоритмический подход. — М.: Мир, 1978. — 430 с.