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A Study of Pilot Placement Optimization with Constrained MDPs in IEEE802.11p Systems

机译:IEEE802.11p系统中受约束MDP的飞行员位置优化研究

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This paper proposes a decision-assisted pilot placement optimization method in IEEE802.11p physical layer. The fast time-varying channel is first modeled as a typical Gaussian-Markov process. Under the constraint of state-spaces, the pilot optimization problem is further formulated as constrained Markov decision processes (MDPs). Secondly, for achieving compatibility with existing standards, our goal is to determine the optimal pilot placement and employ only very limited pilot patterns in response to fast varying channels. We develop a channel state matched pilot optimization method, where the optimization procedures focus on how to respond the different channel variations in the time and frequency domains. To jointly evaluate the severity of channel variations in the time and frequency domains, we derive an effective mutual information measurement criterion. Simulation and numerical results show the efficiency of the pilot optimization decision scheme in reducing the channel estimation error, and mutual information measurement can yield an accurate performance evaluation in relatively fast time-varying vehicular communication scenarios.
机译:本文提出了一种在IEEE802.11p物理层上的决策辅助导频布局优化方法。快速时变信道首先被建模为典型的高斯-马尔可夫过程。在状态空间的约束下,进一步将飞行员优化问题表述为约束马尔可夫决策过程(MDP)。其次,为了实现与现有标准的兼容性,我们的目标是确定最佳的导频位置,并仅采用非常有限的导频模式来响应快速变化的频道。我们开发了一种信道状态匹配的导频优化方法,其中的优化过程着重于如何响应时域和频域中不同的信道变化。为了共同评估时域和频域中信道变化的严重性,我们导出了有效的互信息测量标准。仿真和数值结果表明,导频优化决策方案在减少信道估计误差方面是有效的,并且互信息测量可以在相对快速的时变车辆通信场景中产生准确的性能评估。

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