EURASIP Journal on Wireless Communications and Networking - Special issue on innovative signal transmission and detection techniques for next generation cellular CDMA systems
Multiuser channel estimation for ultra-wideband systems using up to the second-order statistics
EURASIP Journal on Applied Signal Processing
A subspace approach to blind multiuser detection for ultra-wideband communication systems
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
A signal perturbation free whitening-rotation-based semiblind approach for MIMO channel estimation
IEEE Transactions on Signal Processing
Optimal design of learning based MIMO cognitive radio systems
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Ziv-zakai bounds on time delay estimation in unknown convolutive random channels
IEEE Transactions on Signal Processing
A signal-perturbation-free transmit scheme for MIMO-OFDM channel estimation
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Hi-index | 35.69 |
Subspace decomposition has been exploited in different applications. Due to perturbations from various sources such as finite data samples and measurement noise, perturbations arise in subspaces. Therefore, some loss is introduced to performance of subspace-based algorithms. Although first-order perturbation results have been proposed in the literature and applied to various problems, up to second-order perturbation analysis can provide more accurate analytical results and is studied in this paper. Based on the orthogonality principle, perturbations of subspaces and singular values (or eigenvalues) are derived explicitly as functions of a perturbation in the objective matrix up to the second-order, respectively, all in closed forms. It is shown that by keeping only the first-order terms, the derived results reduce to those from existing approaches. Examples to apply the proposed results to both matrix computation and subspace-based channel estimation are provided to verify our analysis.