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An SMDP approach to optimal PHY configuration in wireless networks

机译：无线网络中用于最佳PHY配置的SMDP方法

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In this work, we study the optimal configuration of the physical layer in wireless networks by means of Semi-Markov Decision Process (SMDP) modeling. In particular, assume the physical layer is characterized by a set of potential operating points, with each point corresponding to a rate and reliability pair; for example, these pairs might be obtained through a now-standard diversity-vs-multiplexing tradeoff characterization. Given the current network state (e.g., buffer occupancies), a Decision Maker (DM) needs to dynamically decide which operating point to use. The SMDP problem formulation allows us to choose from these pairs an optimal selection, which is expressed by a decision rule as a function of the number of awaiting packets in the source's finite queue, channel state, size of the packet to be transmitted. We derive a general solution which covers various model configurations, including packet size distributions and varying channels. For the specific case of exponential transmission time, we analytically prove the optimal policy has a threshold structure. Numerical results validate this finding, as well as depict muti-threshold policies for time varying channels such as the Gilber-Elliot channel.
机译：在这项工作中，我们通过半马尔可夫决策过程（SMDP）建模研究无线网络中物理层的最佳配置。特别是，假设物理层的特征在于一组潜在的工作点，每个点对应一个速率和可靠性对;例如，可以通过现在标准的分集与多路复用权衡表征获得这些对。给定当前网络状态（例如，缓冲器占用），决策者（DM）需要动态地决定使用哪个操作点。 SMDP问题公式使我们能够从这些对中选择最佳选择，由决策规则表示，该选择取决于源有限队列中等待数据包的数量，信道状态，要传输的数据包的大小。我们得出了一个通用的解决方案，它涵盖了各种模型配置，包括数据包大小分布和变化的通道。对于指数传输时间的特定情况，我们通过分析证明了最优策略具有阈值结构。数值结果证实了这一发现，并描述了时变通道（如Gilber-Elliot通道）的多阈值策略。

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