| 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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