Abstract
The 5G New Radio (NR) technology operating in millimeter wave (mmWave) frequency band is designed for support bandwidth-greedy applications requiring extraordinary rates at the access interface. However, the use of directional antenna radiation patterns, as well as extremely large path losses and blockage phenomenon, requires efficient algorithms to support these services. In this study, we consider the multi-layer virtual reality (VR) service that utilizes multicast capabilities for baseline layer and unicast transmissions for delivering an enhanced experience. By utilizing the tools of stochastic geometry and queuing theory we develop a simple algorithm allowing to estimate the deployment density of mmWave NR base stations (BS) supporting prescribed delivery guarantees. Our numerical results show that the highest gains of utilizing multicast service for distributing base layer is observed for high UE densities. Despite of its simplicity, the proposed multicast group formation scheme operates close to the state-of-the-art algorithms utilizing the widest beams with longest coverage distance in approximately 50–70% of cases when UE density is λ≥0.3. Among other parameters, QoS profile and UE density have a profound impact on the required density of NR BSs while the effect of blockers density is non-linear having the greatest impact on strict QoS profiles. Depending on the system and service parameters the required density of NR BSs may vary in the range of 20–250 BS/km2.
Highlights
Introduction published maps and institutional affilNowadays, 3rd Generation Partnership Project (3GPP) has already finished the major steps in New Radio (NR) technology standardization in Release and Release [1]
M/M/C queuing system [31], where λ is the intensity of requests for the layer delivery, μ−1 is the mean duration of the requested video fragment that is supposed to follow exponential distribution, and C is the number of active unicast sessions that should be maintained to fulfill the specified probability of successful delivery
We numerically elaborate on the proposed multi-layer virtual reality (VR) delivery scheme
Summary
As an example of the service requiring both multicast and unicast transmissions, we consider a multi-layer VR service. A grouping algorithm allows to achieve better spectral efficiency and obtain an optimal resource allocation using convex optimization Their algorithm provides the opportunity to create sessions with many tiles of different quality, the number of sessions is equal to the number of user groups. This paper notes that serving a large number of users in one multicast group can degrade system performance because the overall multicast data rate is limited by the rate of the user with the worst signal-to-noise ratio (SNR) To solve this problem, it has been proposed to dynamically divide the set of serving users into multiple multicast groups using the spatial degrees of freedom offered by a large number of transmit antennas.
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