While the rollout of the fifth-generation mobile network (5G) is underway across the globe with the intention to deliver 4K/8K UHD videos, Augmented Reality (AR), and Virtual Reality (VR) content to the mass amounts of users, the coverage and throughput are still one of the most significant issues, especially in the rural areas, where only 5G in the low-frequency band are being deployed. This called for a high-performance adaptive bitrate (ABR) algorithm that can maximize the user quality of experience given 5G network characteristics and data rate of UHD contents. Recently, many of the newly proposed ABR techniques were machine-learning based. Among that, Pensieve is one of the state-of-the-art techniques, which utilized reinforcement-learning to generate an ABR algorithm based on observation of past decision performance. By incorporating the context of the 5G network and UHD content, Pensieve has been optimized into Pensieve 5G. New QoE metrics that more accurately represent the QoE of UHD video streaming on the different types of devices were proposed and used to evaluate Pensieve 5G against other ABR techniques including the original Pensieve. The results from the simulation based on the real 5G Standalone (SA) network throughput shows that Pensieve 5G outperforms both conventional algorithms and Pensieve with the average QoE improvement of 8.8% and 14.2%, respectively. Additionally, Pensieve 5G also performed well on the commercial 5G NR-NR Dual Connectivity (NR-DC) Network, despite the training being done solely using the data from the 5G Standalone (SA) network.
翻译:虽然第五代移动网络(5G)正在全球推广,目的是向用户提供4K/8K UHD视频、增强现实(AR)和虚拟现实(VR)内容,但覆盖面和吞吐量仍然是最重要的问题之一,特别是在农村地区,在低频带中仅部署了5G,农村地区只有5G。这要求采用高性能适应比特法(ABR)算法,根据5G网络的特点和UHD内容的数据速率,最大限度地提高用户的经验质量。最近,许多新提出的ABR技术是以机器学习为基础的。其中,Pensieve是最新技术之一,利用强化学习生成ABR算法,以观察过去的决定性能为基础。通过将5G网络和UHE内容纳入Pensieve 5G。新的QE衡量法,更准确地代表UHD视频流在不同类型设备上的QE流动。 Pensieve 5G网络使用5G的原始培训结果,包括5G版本的原始数据。