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QoE-driven cross-layer optimization in wireless networks addressing system efficiency and utility fairness

机译:QoE驱动的无线网络跨层优化解决了系统效率和效用公平性问题

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We address a multi-criteria Quality of Experience (QoE) driven optimization problem for multi-user wireless video delivery. The optimization is done in a cross-layer fashion by using parameterized models of application and link layer in order to determine the application data rate and the network resources that fulfill the criteria. Mean Opinion Score (MOS) is used as a unified utility metric that encompasses the user-perceived quality under certain receiving conditions for the user application. We consider two partially contrary objectives, which are maximizing the total perceived quality of the whole system and maximizing the utility fairness among all users. A tuning mechanism is proposed, which allows the network operator to change dynamically its operating point of the resource allocation based on its pre-defined policy of any combinations of these two objectives. We implemented the proposed tuning algorithm in an emulated Long-Term Evolution (LTE) system and verified its feasibility through simulations.
机译:我们针对多用户无线视频交付解决了多标准体验质量(QoE)驱动的优化问题。通过使用应用程序和链路层的参数化模型以跨层的方式完成优化,以便确定满足标准的应用程序数据速率和网络资源。平均意见分数(MOS)用作统一的效用度量标准,它涵盖了在用户应用程序的某些接收条件下的用户感知质量。我们考虑了两个部分相反的目标,即最大化整个系统的总体感知质量和最大化所有用户之间的效用公平性。提出了一种调整机制,该调整机制允许网络运营商根据其对这两个目标的任意组合的预定义策略,动态更改其资源分配的工作点。我们在仿真的长期演进(LTE)系统中实施了建议的调整算法,并通过仿真验证了其可行性。

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