Blind fractionally-spaced equalization, perfect-reconstruction filter banks and multichannel linear prediction

@inproceedings{citeulike:2002827, abstract = {Equalization for digital communications constitutes a very particular blind deconvolution problem in that the received signal is cyclostationary. Oversampling (OS) (w.r.t. the symbol rate) of the cyclostationary received signal leads to a stationary vector-valued signal (polyphase representation (PR)). OS also leads to a fractionally-spaced channel model and equalizer. In the PR, channel and equalizer can be considered as an analysis and synthesis filter bank. Zero-forcing (ZF) equalization corresponds to a perfect-reconstruction filter bank. We show that in the OS case FIR ZF equalizers exist for a FIR channel. In the PR, the multichannel linear prediction of the noiseless received signal becomes singular eventually, reminiscent of the single-channel prediction of a sum of sinusoids. As a result, the channel can be identified from the received signal second-order statistics by linear prediction in the noise-free case, and by using the Pisarenko method when there is additive noise. In the given data case, MUSIC (subspace) or ML techniques can be applied}, author = {Slock, D. T. M. }, booktitle = {Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on}, citeulike-article-id = {2002827}, journal = {Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on}, keywords = {blind, equalization, multipath}, pages = {IV/585--IV/588 vol.4}, posted-at = {2007-11-28 10:36:02}, priority = {2}, title = {Blind fractionally-spaced equalization, perfect-reconstruction filter banks and multichannel linear prediction}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=389749}, volume = {iv}, year = {1994} }

TY - CONF ID - citeulike:2002827 L3 - citeulike-article-id:2002827 TI - Blind fractionally-spaced equalization, perfect-reconstruction filter banks and multichannel linear prediction T2 - Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on JF - Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on VL - iv SP - IV/585 EP - IV/588 vol.4 N2 - Equalization for digital communications constitutes a very particular blind deconvolution problem in that the received signal is cyclostationary. Oversampling (OS) (w.r.t. the symbol rate) of the cyclostationary received signal leads to a stationary vector-valued signal (polyphase representation (PR)). OS also leads to a fractionally-spaced channel model and equalizer. In the PR, channel and equalizer can be considered as an analysis and synthesis filter bank. Zero-forcing (ZF) equalization corresponds to a perfect-reconstruction filter bank. We show that in the OS case FIR ZF equalizers exist for a FIR channel. In the PR, the multichannel linear prediction of the noiseless received signal becomes singular eventually, reminiscent of the single-channel prediction of a sum of sinusoids. As a result, the channel can be identified from the received signal second-order statistics by linear prediction in the noise-free case, and by using the Pisarenko method when there is additive noise. In the given data case, MUSIC (subspace) or ML techniques can be applied KW - blind KW - equalization KW - multipath AU - Slock, DTM PY - 1994/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=389749 ER -