Mobile networks have to cope with an ever increasing demand for video streaming, an application that imposes high quality requirements for user satisfaction. In this paper, we present an analytical model to calculate two important quality measures for streaming traffic, namely the video startup delay distribution and the buffer starvation probability. The queuing-theoretic model differs from related work by incorporating data flow dynamics of the considered cell, as well as the dynamics of fluctuating interference from neighboring cells, with the goal of accurately representing a multi-cellular environment. In this regard, we propose a finite-volume method to approximate the solution of the involved system of partial differential equations, where other approaches from comparable work were faced with numerical problems. We also evaluate two simplified versions of the model, where only the interference dynamics or all coupling terms are omitted, respectively. The model allows us to study the impact of different parameters on buffered video streaming performance. Additionally, we propose a user-centric metric to measure quality of experience (QoE). To the best of our knowledge, our approach is novel and has not been covered by comparable work. The presented results can help to design future cellular networks with enhanced video streaming experience.

中文翻译：

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受限蜂窝网络中用于缓冲视频流的QoE建模

移动网络必须应对对视频​​流的不断增长的需求，该应用对用户满意度提出了高品质的要求。在本文中，我们提出了一种分析模型，用于计算流传输流量的两个重要质量度量，即视频启动延迟分布和缓冲区饥饿概率。排队理论模型与相关工作的不同之处在于，它合并了所考虑小区的数据流动态以及相邻小区的波动干扰动态，目的是精确表示多小区环境。在这方面，我们提出了一种有限体积的方法来近似求解所涉及的偏微分方程组的解，其中来自可比工作的其他方法都面临数值问题。我们还评估了该模型的两个简化版本，分别仅省略了干扰动力学或所有耦合项。该模型使我们能够研究不同参数对缓冲视频流性能的影响。此外，我们提出了一种以用户为中心的度量标准，以衡量体验质量（QoE）。据我们所知，我们的方法是新颖的，可比的工作还没有涉及。呈现的结果可以帮助设计具有增强的视频流体验的未来蜂窝网络。据我们所知，我们的方法是新颖的，可比的工作还没有涉及。呈现的结果可以帮助设计具有增强的视频流体验的未来蜂窝网络。据我们所知，我们的方法是新颖的，可比的工作还没有涉及。呈现的结果可以帮助设计具有增强的视频流体验的未来蜂窝网络。