About
Wireless Networks Lab (WNL) is a ‘Megagrant’ lab established in 2017 around the project on Cloudified Wireless Networks for 5G and beyond, led by Prof. Ian F. Akyildiz. The project aims to design a novel cloud architecture for wireless networks based on software-defined networking and network function virtualization concepts and essential management tools which allow satisfying the requirements for 5G and beyond.
Our areas of interest include
- Dynamic reconfiguration of the cloudified networks, which allow significantly reducing telecom operator CAPEX and OPEX while providing high quality of experience for the end users.
- Traffic classification in wireless networks.
- Resource allocation for heterogeneous traffic in multi-RRH environment
- Cooperation and coexistence for the technologies working in licensed and unlicensed spectrum (including LTE-U, LAA, Wi-Fi coexistence)
- Centralized algorithms for managing multihop mmWave networks, including fast link setup and beamforming algorithms, routing algorithms, and resources scheduling algorithms.
- Ultra-reliable low latency communications
- Massive Machine-Type Communications
- Visible light and Terahertz Communications
Recent News
- Head of Wireless Networks Lab Evgeny Khorov Supports Investment in Research Programs in Telecommunications at the Government Round Table (March 18, 2019)
The round table gathered government delegates, experts, heads and representatives of Russian science and industry to discuss the problems of the Digital economy in Russia. The primary attention of debating was focusing on the national market of telecommunications equipment and the current state of competition in the national marketplace and abroad.
- Researchers of Wireless Networks Lab to Receive Prestigious Moscow Government Award for Young Scientists 2018 (January 28, 2019)
Researchers of the Wireless Networks Lab Anton Kiryanov, Artem Krasilov, and Alexander Krotov have received a prestigious award from Moscow Government for their outstanding results in communication technologies. They have developed and studied novel methods improving the performance of the next generation wireless networks under high load and high user density.
- WNL Designs a Modular and Reconfigurable Architecture for 5G Systems (December 2, 2018)
WNL team has designed a novel architecture called ARBAT for 5G systems. It introduces innovative features which aim at providing highly efficient Quality-of-Experience aware communications in heterogeneous environments with low CAPEX and OPEX.
- Mikhail Liubogoshchev et al. Present a New Platform Enabling Communication between Applications and the 5G Network at IEEE Globecom 2018 in Abu Dhabi, UAE (December 1, 2018)
xStream provides a control channel between the applications and the networking equipment, which - together with new algorithms - triple the network capacity in terms of satisfied users.
- HUAWEI AWARDS IITP RAS FOR THE BEST COOPERATION PROJECT IN 2018 (November 30, 2018)
The project focuses on new architectures for cross-layer optimization in 4G and 5G cellular systems. - Head of Wireless Networks Lab Evgeny Khorov Gets Scopus Award (November 15, 2018)
The academic publisher Elsevier has awarded Russian scholars with the best citation indices in the Scopus database of research publications. Among the winners is Evgeny Khorov, the head of the Wireless Networks Lab
- A Tutorial on IEEE 802.11ax High Efficiency WLANs Is Published in Top-rated IEEE Communications Surveys and Tutorials (September 22, 2018)
A Tutorial on IEEE 802.11ax High Efficiency WLANs by Evgeny Khorov, Anton Kiryanov, Andrey Lyakhov and Giuseppe Bianchi is published online in the top-rated IEEE Communications Surveys and Tutorials journal. The tutorial provides a thorough review of a hype future protocol which will soon replace the current flagman Wi-Fi version - 802.11ac. The team members have participated in the standardization process and made several proposals for the new standard. The tutorial discusses and evaluates the main new features of 802.11ax. It raises open issues and formulates optimization problems.