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Hidden Markov models for packet-level errors in bursty digital wireless channels

机译:突发性数字无线信道中数据包级错误的隐马尔可夫模型

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Packet-level generative models are designed to be employed for evaluating and designing high layer wireless communications protocols. The significance of these models arises from their ability to replace the entire physical communication layer, hence reducing the time and complexity of wireless system simulations. In this paper, an enhanced general packet radio service (EGPRS) transmission system is utilized to obtain reference bursty packet error sequences. We then propose a new hidden Markov model with two processes to generate packet error sequences of any desired length. The attained burst error statistics demonstrate a satisfactory performance compared to those of reference packet error sequences.
机译:数据包级生成模型旨在用于评估和设计高层无线通信协议。这些模型的重要性在于它们具有替换整个物理通信层的能力,从而减少了无线系统仿真的时间和复杂性。本文利用增强型通用分组无线业务(EGPRS)传输系统来获取参考突发分组错误序列。然后,我们提出了一个新的隐马尔可夫模型,该模型具有两个过程来生成任何所需长度的分组错误序列。与参考分组错误序列相比,获得的突发错误统计数据显示出令人满意的性能。

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