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Maximum Likelihood Estimation of Constellation Vectors for Blind Separation of Co-Channel BPSK Signals and Its Performance Analysis

机译:同信道BPSK信号盲分离星座矢量的最大似然估计及其性能分析

摘要

In this paper, we present a method for blind separation of co-channel BPSK signals arriving at an antenna array. This method consists of two parts: the maximum likelihood constellation estimation and assignment. We show that at high SNR, the maximum likelihood constellation estimation is well approximated by the smallest distance clustering algorithm, which we proposed earlier on heuristic grounds. We observe that both these methods for estimating the constellation vectors perform very well at high SNR and nearly attain Cramer-Rao bounds. Using this fact and noting that the assignment algorithm causes negligible error at high SNR, we derive upper bounds on the probability of bit error for the above method at high SNR. These upper bounds fall very rapidly with increasing SNR, showing that our constellation estimation-assignment approach is very efficient. Simulation results are given to demonstrate the usefulness of the bounds.
机译:在本文中,我们提出了一种盲分离到达天线阵列的同信道BPSK信号的方法。该方法包括两部分:最大似然星座估计和分配。我们表明,在高SNR时,最大似然星座估计值可以通过最小距离聚类算法很好地近似,该算法是我们先前在启发式基础上提出的。我们观察到,这两种用于估计星座矢量的方法在高SNR时表现都非常好,并且几乎达到了Cramer-Rao边界。利用这一事实并注意到分配算法在高SNR时产生的误差可忽略不计,我们得出了上述方法在高SNR时误码概率的上限。这些上限随着SNR的增加而迅速下降,这表明我们的星座估计分配方​​法非常有效。仿真结果表明了边界的有效性。

著录项

  • 作者

    Kannan Anand; Reddy VU;

  • 作者单位
  • 年度 1997
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 入库时间 2022-08-31 14:51:52

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