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| Paper: | SPTM-P4.3 |
| Session: | Adaptive Filters I |
| Time: | Wednesday, May 19, 13:00 - 15:00 |
| Presentation: |
Poster |
| Topic: |
Signal Processing Theory and Methods: Adaptive Systems & Filtering |
| Title: |
REDUCED-RANK BLIND ADAPTIVE FREQUENCY-SHIFT FILTERING FOR SIGNAL EXTRACTION |
| Authors: |
Lai Yin Ngan; Chinese University of Hong Kong | | |
| | Shan Ouyang; Guilin University of Electronic Technology | | |
| | P. C. Ching; Chinese University of Hong Kong | | |
| Abstract: |
In this paper, we first illustrate that a blind adaptive frequency-shift (BA-FRESH) filter can be represented as a generalized sidelobe canceler (GSC). Since the computational power of the BA-FRESH filter is quite high, a reduced-rank implementation is thus proposed and achieved by using the eigen-subspace method. To avoid under representation, a rule for choosing the rank/dimension of the signal subspace is introduced by looking at the eigenvalue spread of the signal covariance matrix. The proposed PCA-based reduced-rank BA-FRESH filter not only has a lower computational complexity, but is also more efficient in signal extraction when compared with the conventional, CSP-based and Krylov subspace-based BA-FRESH filters. The performance of this new method in reducing the spectrally overlapped interference of BPSK signals has been examined rigorously. |
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