Hidden Markov modeling for network communication channels
Hidden Markov modeling for network communication channels
复制标题
DOI：
10.1145/378420.378439
复制
发表时间：
2001-06
期刊：
影响因子：
5.2
通讯作者：
Kave Salamatian;Sandrine Vaton
中科院分区：
文献类型：
--
作者：
Kave Salamatian;Sandrine Vaton
在本文中，我们进行了互联网通信渠道的统计分析。我们的研究是基于隐马尔可夫模型（HMM）。信道在不同的状态之间切换;每个状态对应于发送器发送的数据包丢失的概率。信道的不同状态之间的转换由马尔可夫链控制;该马尔可夫链不能直接观察到，但是接收到的分组流提供了关于信道的当前状态的一些概率信息，以及关于模型的参数的一些信息。在本文中，我们详细介绍了一些有用的算法的信道参数的估计，并作出推断的信道状态。我们讨论的马尔可夫模型的信道的相关性，我们还讨论了有多少国家需要有针对性地模拟一个真实的通信信道。
In this paper we perform the statistical analysis of an Internet communication channel. Our study is based on a Hidden Markov Model (HMM). The channel switches between different states; to each state corresponds the probability that a packet sent by the transmitter will be lost. The transition between the different states of the channel is governed by a Markov chain; this Markov chain is not observed directly, but the received packet flow provides some probabilistic information about the current state of the channel, as well as some information about the parameters of the model. In this paper we detail some useful algorithms for the estimation of the channel parameters, and for making inference about the state of the channel. We discuss the relevance of the Markov model of the channel; we also discuss how many states are required to pertinently model a real communication channel.