Multi-User Content Diversity in Wireless Networks

TL;DR

The work addresses the mismatch between wireless resource allocation and the varying content complexity across users, which impacts UX in XR and real-time media. It introduces Multi-User Content Diversity and develops both optimal (network-centered and network-assisted) and lightweight (suboptimal) frameworks that use content complexity information to improve UX capacity and fairness, often outperforming conventional RTT-based and Prague congestion controls. The contributions include explicit algorithms (MaxCap and MaxMin), a UX-aware PF scheduler, and an RTT-PSNR-based rate control, along with signaling avenues (SCONE, AQP, PDU-set metadata, MAC-CEs) and standardization considerations. The findings suggest substantial practical impact for 6G systems, enabling more efficient, content-aware wireless networks that adapt to dynamic media complexity while maintaining scalable signaling.

Abstract

Immersive applications such as eXtended Reality (XR), cloud gaming, and real-time video streaming are central to the vision of 6G networks. These applications require not only low latency and high data rates, but also consistent and high-quality User Experience (UX). Traditional rate allocation and congestion control mechanisms in wireless networks treat users uniformly based on channel conditions, rely only on network-centric Key Performance Indicators (KPIs), and ignore the content diversity, which can lead to inefficient resource utilization and degraded UX. In this paper, we introduce the concept of Multi-User Content Diversity, which recognizes that different users concurrently consume media with varying complexity, and therefore have different bitrate requirements to achieve satisfactory UX. We propose multiple different frameworks that exploit multi-user content diversity and lead to overall network-wide gains in terms of UX. For each framework, we demonstrate the required information exchange between Application Servers (ASs), Application Clients (ACs), and the network, and the algorithms that run in each of these components to optimize a network-wide UXbased objective. Simulation results demonstrate that exploiting multi-user content diversity leads to significant gains in UX capacity, UX fairness, and network utilization, when compared to conventional rate control methods. These findings highlight the potential of content-aware networking as a key enabler for emerging wireless systems.

Figures (12)

• Figure 1: Scenario of interest: UEs consuming video traffic with similar channel conditions will receive similar network resources, despite their different video complexities. More efficient management of video traffic can be transformative since it is an elastic traffic that constitutes the majority of mobile traffic volume ericsson_mobility_2018.
• Figure 2: Summary of the proposed rate control algorithms to exploit multi-user content diversity.
• Figure 3: Snapshots of different scenes of a cloud game and their RF (PSNR) curves. Scene 1 requires a bitrate of $\sim 19$ Mbps to achieve a PSNR of 35 dB, while Scene 2 requires only $\sim 3$ Mbps to achieve the same PSNR value.
• Figure 4: Optimal network-centered architecture: A UX Controller logical entity in the network receives content complexity information from application servers/clients and allocates the bitrate accordingly.
• Figure 5: Optimal network-assisted architecture: NW shares assistance information related to its current utilization level, and devices utilize this information (along with their own knowledge of content complexity) to optimally adjust their rates locally.