非线性有限冲激响应Volterra信道的盲辨识

提出了单输入多输出有限冲激响应（ＳＩＭＯ ＦＩＲ）Ｖolterra系统的盲辨识及盲均衡的子空间方法，首先描述了ＳＩＭＯ非线性Ｖolterra信道模型，并将此模型转化为多输入多输出（ＭＩＭＯ）信道 模型；接着讨论了ＦＩＲＶolterra系统盲可辨识条件，并给出了ＳＩＭＯＶolterra系统的盲辨子空间算法；进一步讨论了ＶolterraＦＩＲ非线性信道的确定性盲均衡问题；最后用仿真实例验证了此算法的有效性，所提方法与确定性的线性多信道方法相比，它的最大优点就在于所需约束条件少，此方仅需要输入信号的相关矩在奇异，且在低信噪比情况下（ＳＮＲ为５dB)也有效。

Blind Identification of Nonlinear Finite Impulse Response Volterra Channels

A subspace approach to blind identification and equalization of a nonlinear single-input multiple-output (SIMO) finite impulse response (FIR) Volterra system is proposed. Firstly, a SIMO nonlinear Volterra channel model is described, and is transformed into a MIMO blind channel model. Then, the blind identificable conditions for FIR Volterra system are discussed and a subspace approach to blind identification of SIMO Volterra system is given; furthermore, the deterministic blind equalization of Volterra FIR nonlinear channel is studied. Finally, the validity of this method is verified by a simulation example. The advantage of this method is that it requires less restriction conditions, i.e., it only requires that the auto-correlation matrix of an input signal is non-singular and can work well in the case of low SNR in comparison with the deterministic approach.