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JOURNALS // Informatika i Ee Primeneniya [Informatics and its Applications] // Archive

Inform. Primen., 2022 Volume 16, Issue 2, Pages 102–108 (Mi ia792)

Density analysis of mmWave NR deployments for delivering scalable AR/VR video services

V. A. Beschastnyia, D. Yu. Ostrikovaa, S. Ya. Shorginb, D. A. Moltchanovc, Yu. V. Gaidamakaab

a Peoples' Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Str., Moscow 117198, Russian Federation
b Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119133, Russian Federation
c Tampere University, 7 Korkeakoulunkatu, Tampere 33720, Finland

Abstract: The 5G New Radio (NR) technology operating in millimeter-wave (mmWave) frequency band is designed to support bandwidth-greedy applications requiring extraordinary rates at the access interface. In NR systems, the use of antenna arrays that form directional radiation patterns allows to avoid high propagation losses and interference but at the same time reduces the coverage area of a single beam and, hence, the number of multicast users that can be served by the beam. As a result, efficient algorithms are required to support such services in both terrestrial systems and drone-assisted systems that utilize unmanned aerial vehicles as access points. The present authors consider the streaming data delivery of virtual reality services using scalable video coding technology which utilizes multicast capabilities for baseline layer and unicast transmissions for delivering an enhanced experience. By utilizing the tools of stochastic geometry and queuing theory, the authors develop a simple method allowing one to estimate the deployment density of mmWave NR base stations to provide a given performance of multilayer multicast services depending on their various requirements and structure as well as on the density of users.

Keywords: 5G, New Radio, mmWave, multi-layer VR, multicasting, scalable video coding, clustering.

Received: 30.01.2022

DOI: 10.14357/19922264220213



© Steklov Math. Inst. of RAS, 2024