Name of the project:
The research of network technologies with ultra-low-latency and ultra-high density relying on the extensive use of artificial intelligence for 6G networks.
Goals of project:
The goal of the project is to create the scientific foundations for the proactive implementation of sixth-generation communication networks with the rational use of artificial intelligence technologies in principal networking technologies on which 6G networks can rely.
Project objective:
- To develop principles of constructing sixth-generation communication networks accounting for the peculiarities of the territorial and administrative division of Russia, the varying density of population, workforce across the territory of the country in accordance with the types of economic activity, the road network, the landscape and the distance between settlements.
- To develop methods of building fractal communication networks in the setting of a three-dimensional space and ultra-high density, up to 100 devices per cubic meter and methodologies of the planning of such networks in the context of an inhomogeneous environment.
- To develop optimal routing methods in the context of the limitations caused by the ultra-high density of the network in a three-dimensional space, the influence of the load of the adjacent nodes on the quality of service in a specific route and ensuring the stability of the communication network under the influence imposed on the network leading to failure of nodes and (or) fragments of the network.
- To develop methods for the positioning of network routers in the setting of a three-dimensional ultra-dense space and a space enriched with biomass that hinders the propagation of terahertz signals, including in crowds of people at a stadium, on a street etc.
- To develop a model network for the research and training in technologies and services provided by 6G networks. To create a laboratory of 6G networks and services based on a model network, to lay the groundwork at the Saint Petersburg State University of Telecommunications in the formation of a model network for the research and training in the field of telepresence services.
- To develop methods of transmission of holographic copies of humans in the context of network technologies in the context of network technologies with ultra-low latency in three-dimensional 6G communication networks and to determine requirements for the quality of service and the quality of perception for such services.
- To develop methods of providing augmented reality services in the context of network technologies with ultra-low latency in three-dimensional 6G communication networks, to determine the requirements for the quality of services and the quality of perception of such services.
- To develop methods of providing services using avatar robots in the context of network technologies with ultra-low latency in three-dimensional 6G communication networks and to determine requirements for the quality of service and the quality of perception for such services.
- To develop methods of providing services using humanoid robots in the context of network technologies with ultra-low latency in three-dimensional 6G communication networks and to determine requirements for the quality of service and the quality of perception of such services.
- To develop methods of placing network routers on tethered drones and ensuring routing by a swarm of drones in the context of a three-dimensional ultra-dense space and a space enriched with biomass that impedes the propagation of terahertz signals, including in crowds of people at a stadium, on a street etc..
- To develop algorithms for prototyping traffic and other network characteristics on the basis of machine and deep learning in three-dimensional 6G networks to ensure the rational distribution of resources of the network as a whole and (or) its fragments in the context of super big data, ultra-low latency, the requirements for ultra-high reliability and ensuring the stability of 6G communication networks.
- To develop algorithms for the migration of services on the basis of machine and deep learning for traffic balancing, indiscriminate access to services of 6G communication networks for all users regardless of whether it is a human or a robot, ensuring the quality of service and the quality of perception and the stability of 6G communication networks.
- To research technologies of network coding for 6G networks, including the impact of coding methods on latency in 6G networks. To form an approach and to research the peculiarities of the use of artificial intelligence technologies when network coding is used. To research methods of noise-free coding for 6G networks, including the impact of methods of noise-free coding on delays in 6G networks. To develop adaptive methods of noise-free coding based on artificial intelligence systems for 6G networks.
- To research and develop requirements for precision and operation rate, methods of network positioning for moving and stationary devices in three-dimensional ultra-dense 6G networks. To research and develop models and methods for the assessment of the accuracy and speed of the determination of the time and the angle of arrival of a signal for moving and stationary devices in three-dimensional ultra-dense 6G networks. To research and develop models and methods of the secondary processing of primary measurements of the time and the angle of arrival of a signal in stationary and moving in three-dimensional ultra-dense 6G networks.
- To develop new network protocols for 6G communication networks accounting for their peculiarities outlined above.
Research directions: Computer and information sciences
Hosting organization
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Field of studies
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City
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Invited researcher
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Time span of the project
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Laboratory «Hybrid modeling and optimization methods in complex systems»
Siberian federal University - (SibFU) |
Computer and information sciences |
Krasnoyarsk |
Stanimirović Predrag Stefan
Serbia |
2022-2024 |
Laboratory for Non-linear and Microwave Photonics
Ulyanovsk State University - (USU) |
Computer and information sciences |
Ulyanovsk |
Taylor James Roy
United Kingdom, Ireland |
2021-2023 |
Multi-scale Neurodynamics for Smart Systems
Skolkovo Institute of Science and Technology - (Skoltech) |
Computer and information sciences |
Moscow |
Wang Jun |
2021-2023 |