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Blind Recognition of Linear Space–Time Block Codes: A Likelihood-Based Approach

机译:线性时空分组码的盲识别:一种基于可能性的方法

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Blind recognition of communication parameters is a research topic of high importance for both military and civilian communication systems. Numerous studies about carrier frequency estimation, modulation recognition as well as channel identification are available in literature. This paper deals with the blind recognition of the space-time block coding (STBC) scheme used in multiple-input-multiple-output (MIMO) communication systems. Assuming there is perfect synchronization at the receiver side, this paper proposes three maximum-likelihood (ML)-based approaches for STBC classification: the optimal classifier, the second-order statistic (SOS) classifier, and the code parameter (CP) classifier. While the optimal and the SOS approaches require ideal conditions, the CP classifier is well suited for the blind context where the communication parameters are unknown at the receiver side. Our simulations show that this blind classifier is more easily implemented and yields better performance than those available in literature.
机译:通信参数的盲目识别对于军事和民用通信系统都是非常重要的研究课题。文献中对载波频率估计,调制识别以及信道识别进行了大量研究。本文涉及在多输入多输出(MIMO)通信系统中使用的空时分组编码(STBC)方案的盲目识别。假设接收器端具有完美的同步,本文提出了三种基于最大似然(ML)的STBC分类方法:最优分类器,二阶统计量(SOS)分类器和代码参数(CP)分类器。尽管最佳方法和SOS方法需要理想条件,但CP分类器非常适合盲环境,在盲环境中,接收方的通信参数未知。我们的仿真表明,与文献中提供的分类器相比,该盲分类器更容易​​实现,并且产生更好的性能。

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