基于矩阵填充和三阶相关的长短码DS-CDMA信号多伪码盲估计

由于长短码直扩码分多址(LSC-DS-CDMA)信号包含了多个用户的长码和短码，已有的直扩码分多址信号的盲伪码估计方法不再适用。为此该文提出一种基于矩阵填充和三阶相关的伪码估计方法。首先从理论上将结构复杂的LSC-DS-CDMA信号构建为多用户短码扩频的缺失矩阵模型，将复合码矩阵估计建模为盲源信号分离问题；然后将矩阵填充理论应用于复合码矩阵估计，提出基于奇异值阈值算法和快速独立成分分析算法的各用户复合码序列估计方法；最后利用m序列的移位相加性特性，提出延迟三阶相关算法，从各用户复合码序列中估计其包含的长短伪码序列。仿真表明，当信噪比高于-2 dB时，该文算法的长短伪码估计平均误码率低于0.1%。

Blind Estimation of LSC-DS-CDMA Signal Based on Matrix Completion and Triple Correlation

As the Long and Short Codes Direct Sequence Code Division Multiple Access (LSC-DS-CDMA) signal contains long and short PN codes of multi-user, the existing methods of PN codes blind estimation for the Direct Sequence Code Division Multiple Access (DS-CDMA) signal are no longer applicable. Then a pseudo random (PN) codes estimation method based on matrix completion and triple correlation is proposed. Firstly, LSC-DS-CDMA signal is represented as a matrix model with missing data for multi-user short code and the composite code matrix estimation is modeled as a blind source separation problem in the theory. Secondly, matrix completion theory is used to estimate the composite code subspace. A method of the composite code sequences estimation is proposed based on the singular value thresholding algorithm and Fast-ICA algorithm. Finally, the delayed triple correlation algorithm is presented to estimate the long and short PN codes from the composite code sequences based on the shift-and-add property of m sequence. Simulations show that the bit error rate of long and short codes sequences can be reduced to 0.1% when the SNR is above -2 dB.