A low-complexity adaptive blind subspace channel estimation algorithm
Wei Kang, Benoı̂t Champagne · 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). · 2004
A low-complexity adaptive blind subspace channel estimation algorithm is proposed for direct sequence spread spectrum CDMA systems. Compared with so-called hybrid adaptive channel estimation algorithms, where only the subspace estimation is carried out adaptively, the proposed algorithm is fully adaptive in that both subspace and channel estimates are updated recursively. The new algorithm is derived by exploiting common structural properties of plane rotation-based subspace trackers (e.g. Proteus, RO-FST, etc.). It is characterized by a low-complexity of implementation and numerical robustness over long periods of operation, an essential requirement for wireless radio applications. Moreover, we find in the case of a heavily loaded system that the proposed algorithm has better performance than previous hybrid algorithms.