Blind estimation of finite alphabet digital signals using eigenspace-based beamforming techniques

摘要

The eigenspace-based decoupled weighted iterative least-square with projection (DWILSP) is presented here, which utilizes the eigenstructure of the correlation matrix to enhance the performance of the DWILSP algorithm. In the DWILSP, the signal estimate is interpreted as the minimum variance distortionless response (MVDR) beamforming problem. However, the MVDR beamformer is sensitive to the finite samples and steering vector errors, which cause the performance degradation on the estimate of signals. We then use the eigenspace-based beamformer instead of the MVDR beamformer to alleviate the performance degradation, where the output signal-to-interference-plus-noise ratio is increased during the estimate of signal of interest. Further, to reduce the computational complexity of the developed algorithm, an efficient implementation approach is proposed. It is shown that the projection operations in the eigenspace-based beamformer can be performed in the whitening domain. Using the fact, the computational complexity of the eigenspace-based DWILSP is reduced considerably and even lower than that of the DWILSP. Computer simulations are given to demonstrate that the eigenspace-based DWILSP outperforms the other iterative least-square approaches.