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首页> 外文期刊>Communications, IET >Wireless channel model using stochastic high-level Petri nets for cross-layer performance analysis in orthogonal frequency-division multiplexing system
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Wireless channel model using stochastic high-level Petri nets for cross-layer performance analysis in orthogonal frequency-division multiplexing system

机译：正交频分复用系统中使用随机高级Petri网进行跨层性能分析的无线信道模型

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摘要

In this study, the authors form a wireless channel model for orthogonal frequency-division multiplexing (OFDM) systems with stochastic high-level Petri net (SHLPN) formalism in order to simplify the cross-layer performance analysis of modern wireless systems. Compared with existing finite state Markov channel model whose state space grows exponentially with the number of OFDM subchannels, the author's proposed SHLPN model uses state aggregation technique to deal with this problem. Closed-form expressions to calculate the transition probabilities among the compound markings of the SHLPN model are provided. When applied to derive the performance measures for OFDM system in terms of the average throughput, average delay and packet dropping probability, the SHLPN model can accurately capture the correlated time-varying nature of wireless channels. Simulation is performed to show that the numerical results offered by the proposed model are more accurate compared with other simplified channel models for avoiding state space complexity.
机译：在这项研究中，作者为具有随机高级Petri网（SHLPN）形式主义的正交频分复用（OFDM）系统形成了一个无线信道模型，以简化现代无线系统的跨层性能分析。与现有的有限状态马尔可夫信道模型相比，状态空间随着OFDM子信道的数量呈指数增长，作者提出的SHLPN模型使用状态聚合技术来解决此问题。提供了用于计算SHLPN模型的复合标记之间的转换概率的闭式表达式。当用于根据平均吞吐量，平均延迟和丢包概率推导OFDM系统的性能指标时，SHLPN模型可以准确地捕获无线信道的相关时变特性。仿真表明，与其他简化的通道模型相比，所提出的模型提供的数值结果更加准确，从而避免了状态空间的复杂性。

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