三种不同结构的自举盲自适应多信号同信道分离算法的收敛性和性能比较

A. Dinc, Y. Bar-Ness
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引用次数: 14

摘要

作者将先前报道的三种自举盲自适应分离器结构扩展到多信号通道情况。他们提出了一种递归权重更新算法,适用于三种结构:功率-功率、相关器-相关器和功率相关器。在没有噪声的情况下,通过分析找到了这些分离器的最佳权重。通过输出学习曲线对信号分离过程进行仿真。结果表明,对于两个或三个信号通道,不同的自举分离器收敛到稳态的速度几乎相同。三种分离器的稳态干扰残差不同,功率-功率分离器最小,相关-相关分离器最大。在这些结构的输出端使用均衡(自动增益控制)可以显著地改善干扰消除的深度。
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Convergence and performance comparison of three different structures of bootstrap blind adaptive algorithm for multisignal co-channel separation
The authors extend the previously reported three structures of bootstrap blind adaptive separators to the multisignal channel case. They suggest a recursive weight updating algorithm for the three structures: power-power, correlator-correlator, and power-correlator. The optimum weights for these separators were found analytically in the absence of noise. The signal separation process was shown via simulation by the output learning curve. It was shown that the different bootstrap separators converge to their steady states almost with the same speed for a two or three signal channel. The steady-state interference residues of the three separators are different, lowest for power-power and highest for correlator-correlator. The use of equalization (automatic gain control) at the output of these structures improves the depth of interference cancellation dramatically.<>
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