COMBINED CRITERION FOR THE CHOICE OF ROUTING BASED ON D2D TECHNOLOGY
Keywords:internet of things, device-device, routing, clustering.
Context. 5G network is able to improve existing services and provide a new quality of services. 5G communication networks combine various radio technologies and technologies of fixed communication networks, therefore they are often called heterogeneous, which emphasizes their difference from other networks. One of the main features of such networks is over-density and ultra-low latency. It is the Internet of things that is the basic component of the concept of super dense networks. 3GPP suggests planning 5G networks based on the condition that 1 million devices is 1 km2. Also, ultra-low latency communications networks have a big impact on networking methods, especially for the tactile Internet concept. Such networks require decentralization through 1 ms delay requirements. This requires new approaches to building a new generation of networks, which is the reason for the development of new technologies. One such technology is D2D (device-to-device) technology. This technology allows you to reduce the load on the core of the network due to the use of a significant proportion of the traffic directly between devices and reduces the delay in providing services.
Objective. The goal of the work is to create an optimal combined criterion for choosing effective traffic routes in a wireless network based on D2D technology.
Method. Many modern works are devoted to the study of D2D technology, but they are not exhaustive in the study of routing in such networks. It is objective enough to study networks built on the basis of the interaction of devices with each other using D2D technology, since such interactions have proven to be effective technologies. This, in turn, involves the development of appropriate routing methods in networks using D2D technology, especially taking into account the property of over-density 5G networks. The paper proposes a criterion for selecting routes, taking into account interference within the channels forming the network nodes. This criterion combines the choice of routes according to the length criteria and the criterion of maximum throughput.
Results. A developed combined criterion for selecting traffic routing in a wireless network that uses D2D technology. The results of the study are shown in graphic data.
Conclusions. The experiments confirmed the efficiency and effectiveness of the developed method and allow us to recommend this method for practical use as a result of route selection, taking into account those network properties that are more likely to affect the quality of the route.
Liu Z., Lu O., Wang W. Transmission capacity of D2D communication under heterogeneous networks with dual bands, 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2012, pp. 169–174.
Jankowski N., Grochowski M. Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks, IEEE Transactions on Communications, 2014, Vol. 62, No. 11, pp. 4147–4161. DOI: 10.1109/ TCOMM.2014.2363849.
Sakr A. H., Hossain E. Cognitive and energy Harvesting-based D2D communication in cellular networks: stochastic geometry modeling and analysis, IEEE Transactions on Communications, 2015, Vol 63, No. 5, pp. 1867–1880. DOI: 10.1109/ TCOMM.2015.2411266
Gao H., Zhang S., Su Y. Joint resource allocation and power control algorithm for cooperative D2D heterogeneous networks, IEEE Access, 2019, Vol. 7, pp. 20632–20643. DOI: 10.1109/ACCESS.2019.2895975.
Muthanna A., Ateyar A. A., Khakimov K., Al-Bahri M. Delay tolerant network model based on D2D communication, 4th MEC International Conference on Big Data and Smart City, 2019, No. 6, pp. 37–66. DOI: 10.1109/ ICBDSC.2019.8645609.
Borodin А. S., Kucherjavyj A. E., Paramonov A. I. Metod postroenija seti svjazi na baze D2D-tehnologij s ispol’zovaniem dopolnitel’nyh marshrutizatorov, E'lektrosvyaz’, 2019, Vol. 4, pp. 86–92.
Borodin А. S., Paramanov A. I. Marshrutizacija trafika v seti besprovodnoj svjazi, postroennoj na baze D2D-tehnologij, Electrosvyaz magazine, 2019, Vol. 2, pp. 38–44.
Bulashenko А. V. Ocinka zv’jaznosti D2D komunikacij u merezhah 5G, Visnyk NTUU KPI Seriia – Radiotekhnika Radioaparatobuduvannia, 2020, No. 81, pp. 21–29. DOI: 10.20535/RADAP.2020.81.21-29.
Muthanna A., Khakimov A., Ateya A. A., Paramonov A., Koucheryavy A. Enabling M2M Communication through MEC and SDN, Communications in Computer and Information Science, 2018, Vol. 919, pp. 95–105.
Borodin А. S., Kucherjavyj A. E., Paramonov A. I. Osobennosti ispol’zovanija D2D-tehnologij v zavisimosti ot plotnosti pol’zovatelej i ustrojstv, Electrosvyaz magazine, 2018, Vol. 10, pp. 40–45.
Jankowski N. Data regularization, Neural Networks and Soft Computing : Fifth Conference, Zakopane, 6–10 June 2000 : proceedings. Częstochowa, Polish Neural Networks Society, 2000, pp. 209–214.
Hussejn O. A., Paramonov A. I., Kucherjavyj A. E. Analiz klasterizacii D2D-ustrojstv v setjah pjatogo pokolenija, Electrosvyaz magazine, 2018, Vol. 9, pp. 32–38.
Dao Ch. N., Paramonov A. I. Metod vybora stabil’nogo marshruta v seti s podvizhnymi uzlami, Electrosvyaz magazine, 2018, Vol. 8, pp. 37–44.
Wang Z., Zhou T., Hu H. Iterative greesdy user clustering algorithm for D2D-relay in vehicular communication systems, IEEE Microwaves, antennas and propagation, 2019, Vol. 13, No. 8, pp. 1087–1095. DOI: 10.1049/iet-map.2018.6123.
Nuermaimaiti N., Ma Z., Wu X. Modeling and Performance optimization of heterogeneous cellular and D2D networks, 28th Wireless and optical communication conference (WOCC), 9–10 May 2019, Beijing, 2019. DOI: 10.1109/ WOCC.2019.8770597.
Mumtaz S., Al-Dulaimi A., Frascolla V., Hassan S. A., Dobre O. A. Guest Editorial Special Issue on 5G and beyond – mobile technologies and applications for IoT, IEEE Internet of Things Journal, 2019, Vol. 6, No. 1, pp. 203–206. DOI: 10.1109/ JIOT.2019.2896749.
Evans R. Fundamental Limits of Caching in Wireless D2D Networks, IEEE Transactions on Information Theory, 2016, Vol. 62, No. 2, pp. 849–869. DOI: 10.1109/ TIT.2015.2504556
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