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A Polymatroid Flow Model for Network Coded Multicast in Wireless Networks

机译:无线网络中网络编码组播的多类流模型

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We propose a new model for the wireless broadcast advantage based on a polymatroid structure. This model is a generalization of the predominating hypergraph model. The polymatroid structure yields a general max-flow min-cut characterization of multicast rate regions, which applies to a large variety of channel, physical layer, and medium access models. It includes the state-of-the-art hypergraph flow regions with lossless and lossy hyperarcs, i.e., Shannon rate models and packet erasure networks. Additionally, it generalizes to various other rate regions, e.g., the cut-set outer bounds for networks of a large variety of independent broadcast channels, including networks of independent Gaussian multiple-input multiple-output channels, and the capacity regions for networks of independent deterministic broadcast channels, which can in general not be modeled by the hypergraph flow model. We propose a dual decomposition approach for network utility optimization problems on the polymatroid broadcast flow region, which subsumes existing dual decomposition approaches based on lossless and lossy hypergraph flow regions. Our approach significantly simplifies the decomposition, especially for lossy hypergraph models in packet erasure networks, by fully exploiting the inherent polymatroid structure of the wireless broadcast. Additionally, it can be directly used to fully characterize and evaluate the cut-set bounds for networks of independent broadcast channels with polymatroid structure without previous knowledge about the relevant cuts.
机译:我们提出了一种基于多类拟态结构的无线广播优势的新模型。该模型是占优势的超图模型的概括。多类拟态结构产生了多播速率区域的一般最大流最小割特征,适用于多种信道,物理层和介质访问模型。它包括具有无损和有损超弧的最新超图流区域,即香农速率模型和数据包擦除网络。另外,它概括为各种其他速率区域,例如,各种独立广播频道的网络的割集外边界,包括独立高斯多输入多输出频道的网络,以及独立网络的容量区域确定性广播频道,通常无法通过超图流模型来建模。针对多类拟广播流区域上的网络效用优化问题,我们提出了一种双重分解方法,该方法分解了现有的基于无损和有损超图流动区域的双重分解方法。我们的方法通过充分利用无线广播的固有多类拟态结构,极大地简化了分解,尤其是对于数据包擦除网络中的有损超图模型。另外,它可以直接用于全面表征和评估具有多类拟似结构的独立广播频道网络的割集范围,而无需事先了解相关割据。

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