论文标题

从PHY到QoE:参数化框架设计

From PHY to QoE: A Parameterized Framework Design

论文作者

Wang, Hao, Ji, Lei, Gao, Zhenxing

论文摘要

5G通信技术的快速发展诞生了各种实时宽带通信服务,例如增强现实(AR),虚拟现实(VR)和云游戏。与传统服务相比,消费者在利用这些服务时倾向于更多地关注他们的主观经验。同时,在5G及以后的功耗问题尤为明显。物理层(PHY)接收器的传统设计是基于最大化频谱效率或最小化错误的基础,但这将不再是考虑能源效率和这些新服务的服务后最好的。因此,本文使用经验质量(QOE)作为PHY算法的优化标准。为了建立PHY和QOE之间的关系,本文从UE的角度对端到端的传输进行了建模,并提出了一个基于分层分析方法的五层框架,其中包括系统级模型,Bitstream模型,数据包模型,服务质量质量模型和体验质量模型。 5G网络中的实际数据分别用于训练每种服务的涉及模型的参数。结果表明,PHY算法可以从QoE的角度简化。

The rapid development of 5G communication technology has given birth to various real-time broadband communication services, such as augmented reality (AR), virtual reality (VR) and cloud games. Compared with traditional services, consumers tend to focus more on their subjective experience when utilizing these services. In the meantime, the problem of power consumption is particularly prominent in 5G and beyond. The traditional design of physical layer (PHY) receiver is based on maximizing spectrum efficiency or minimizing error, but this will no longer be the best after considering energy efficiency and these new-coming services. Therefore, this paper uses quality of experience (QoE) as the optimization criterion of the PHY algorithm. In order to establish the relationship between PHY and QoE, this paper models the end-to-end transmission from UE perspective and proposes a five-layer framework based on hierarchical analysis method, which includes system-level model, bitstream model, packet model, service quality model and experience quality model. Real data in 5G network is used to train the parameters of the involved models for each type of services, respectively. The results show that the PHY algorithms can be simplified in perspective of QoE.

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