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Application of Hidden Markov models to blind channel estimation and data detection in a GSM environment

机译:隐马尔可夫模型在GSM环境下盲信道估计和数据检测中的应用

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In this paper, we present an algorithm based on the Hidden Markov Models (HMM) theory to solve the problem of blind channel estimation and sequence detection in mobile digital communications. The environment in which the algorithm is tested is the Paneuropean Mobile Radio System, also known as GSM. In this system, a large part in each burst is devoted to allocate a training sequence used to obtain a channel estimate. The algorithm presented would not require this sequence, and that would imply an increase of the system capacity. Performance, evaluated for standard test channels, is close to that of non-blind algorithms.
机译:在本文中,我们提出了一种基于隐马尔可夫模型(HMM)的算法,以解决移动数字通信中的盲信道估计和序列检测问题。测试该算法的环境是Paneuropean移动无线电系统,也称为GSM。在该系统中,每个脉冲串中的很大一部分专用于分配用于获得信道估计的训练序列。提出的算法将不需要此序列,这将意味着系统容量的增加。经标准测试通道评估的性能接近于非盲算法。

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