基于MMPP流量的时变微宏蜂窝网络性能评价

Mushlah Uddin Sarkar, M. Islam, M. Amin
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引用次数: 0

摘要

二维(2D)和三维(3D)稳态马尔可夫链被广泛用于分析通信网络的业务性能。当网络的特性随时间变化时,这种稳态马尔可夫链无法确定不同的概率状态。马尔可夫调制泊松过程(MMPP)是马尔可夫到达过程(MAP)的一种特殊情况,到达率取决于概率状态。本文建立了具有时变交通负荷的微宏元胞网络的交通模型,并利用MMPP方法对网络在不同观测时段的变负荷条件下的概率状态进行了评估。
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Performance evaluation of time dependent micro macro cellular network using MMPP traffic
Two-dimensional (2D) and three-dimensional (3D) steady state Markov chains are widely used to analyze the traffic performance of communications networks. When the characteristics of the network changes with time, such steady state Markov chain is unable to determine different probability states. Markov Modulated Poisson Process (MMPP) is a special case of Markov Arrival Process (MAP) where arrival rate depends on probability states. In this paper, a traffic model of micro-macro cellular network of time dependent traffic load is modeled and its probability states are evaluated using MMPP varying load condition of the network under different parts of observation time.
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