对CDMA时变色散信道基于离散正则模型的盲辨识方法

Blind Identification of CDMA Time-Varying Dispersive Channels Based on Discrete-Time Canonical Model

本文通过将扩展函数在时延扩展域和Ｄｏｐｐｌｅｒ扩展域进行采样，得到了ＣＤＭＡ时变色散信迢的离散正则模型，此模型适宜于采用二阶统计量方法对ＣＤＭＡ时变色散系统进行盲信号处理。文章同时给出了一种对正则采样值的子空间盲辨识算法。与基于基展开模型处理时变信道的方法不同的是，这种基于离散正则模型的盲辨识方法不需借助高阶统计量估计信道的指数基频率，也不必假设相邻符号间的时延变化呈线性关系，而且赋予了基展开坐标明确的物理意义。文章通过仿真验证了算法的有效性。

In this paper, the discrete-time canonical model of CDMA time-varying (TV) dispersive channels is developed by sampling the spreading function in delay-spreading domain and Doppler-spreading domain. The model is suitable for blind signal processing for the CDMA-TV dispersive channels exploiting the second-order statistics-based approaches. A subspace method is also presented for blind identification of the canonical samples. Unlike existing methods that based on basis expansion model, this new algorithm neither requires estimate of the base frequencies by higher-order statistics, nor needs the assumption of linearly varying delays across symbols, and it offers definite explanation of the coordinates. Simulations demonstrate the effectiveness of the proposed algorithm.