Technical Program

Paper Detail

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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