Subspace-based adaptive widely linear blind channel estimation for constrained minimum variance CDMA receiver
Nuan Song, Vimal Radhakrishnan, Rodrigo C. de Lamare, Martin Haardt
Abstract
We propose a subspace-based Widely Linear (WL) blind channel estimation scheme based on the iterative power method for the WL constrained minimum variance Code Division Multiple Access (CDMA) receiver. The novel technique approximates the noise subspace by using a matrix power and the WL processing fully exploits the second-order non-circularity of the signal. Two adaptive recursive least squares algorithms are developed using power iterations, which completely avoid the computationally intensive singular value decomposition. Simulation results show an improved performance of the proposed algorithms in terms of convergence and complexity as compared to their linear counterparts.
BibTeX
@inproceedings{icassp2016_subspacebasedada,
title = {Subspace-based adaptive widely linear blind channel estimation for constrained minimum variance CDMA receiver},
author = {Nuan Song and Vimal Radhakrishnan and Rodrigo C. de Lamare and Martin Haardt},
booktitle = {ICASSP 2016},
year = {2016}
}