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Orthogonal space-time block codes: maximum likelihood detection for unknown channels and unstructured interferences

机译:正交空时分组码:未知信道和非结构干扰的最大似然检测

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Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have been attracting increased attention. The so-called orthogonal space-time block codes (OSTBCs) have been of particular interest due to their good performance and low decoding complexity. In this paper, we take a systematic maximum-likelihood (ML) approach to the decoding of OSTBC for unknown propagation channels and unknown noise and interference conditions. We derive a low-complexity ML decoding algorithm based on cyclic minimization and assisted by a minimum amount of training data. Furthermore, we discuss the design of optimal training sequences and optimal information transfer to an outer decoder. Numerical examples demonstrate the performance of our algorithm.
机译:使用多个发射和接收天线的通信系统的时空编码(STC)方案已引起越来越多的关注。所谓的正交空时分组码(OSTBC)由于其良好的性能和较低的解码复杂性而引起了人们的特别关注。在本文中,我们针对未知的传播信道以及未知的噪声和干扰条件,采用系统的最大似然(ML)方法对OSTBC进行解码。我们推导了一种基于循环最小化并辅以最少训练数据的低复杂度ML解码算法。此外,我们讨论了最佳训练序列的设计以及向外部解码器的最佳信息传递。数值例子证明了我们算法的性能。

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