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Improving the generalized likelihood ratio test for unknown linear Gaussian channels

机译：改进未知线性高斯信道的广义似然比检验

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摘要

In this work, we consider the decoding problem for unknown Gaussian linear channels. Important examples of linear channels are the intersymbol interference (ISI) channel and the diversity channel with multiple transmit and receive antennas employing space-time codes (STC). An important class of decoders is based on the generalized likelihood ratio test (GLRT). Our work deals primarily with a decoding algorithm that uniformly improves the error probability of the GLRT decoder for these unknown linear channels. The improvement is attained by increasing the minimal distance associated with the decoder. This improvement is uniform, i.e., for all the possible channel parameters, the error probability is either smaller by a factor (that is exponential in the improved distance), or for some, may remain the same. We also present an algorithm that improves the average (over the channel parameters) error probability of the GLRT decoder. We provide simulation results for both decoders.
机译：在这项工作中，我们考虑未知高斯线性信道的解码问题。线性信道的重要示例是符号间干扰（ISI）信道和具有多个采用空时码（STC）的发射和接收天线的分集信道。一类重要的解码器基于广义似然比测试（GLRT）。我们的工作主要涉及一种解码算法，该算法统一提高了这些未知线性通道的GLRT解码器的错误概率。通过增加与解码器相关的最小距离来获得改进。这种改进是统一的，即对于所有可能的信道参数，错误概率要么减小一个因数（在改进的距离上呈指数关系），要么对于某些误差保持不变。我们还提出了一种算法，可以提高GLRT解码器的平均（在信道参数上）错误概率。我们提供两种解码器的仿真结果。

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