Blind identification of FIR MIMO channels by decorrelating subchannels
We study blind identification and equalization of finite impulse response (FIR) and multi-input and multi-output (MIMO) channels driven by colored signals. We first show a sufficient condition for an FIR MIMO channel to be identifiable up to a scaling and permutation using the second-order statistic...
| Main Authors: | , , |
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| Format: | Journal Article |
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IEEE Signal Processing Society
2003
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| Online Access: | http://hdl.handle.net/20.500.11937/3558 |
| _version_ | 1848744264675098624 |
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| author | Hua, Y. An, Senjian Xiang, Y. |
| author_facet | Hua, Y. An, Senjian Xiang, Y. |
| author_sort | Hua, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We study blind identification and equalization of finite impulse response (FIR) and multi-input and multi-output (MIMO) channels driven by colored signals. We first show a sufficient condition for an FIR MIMO channel to be identifiable up to a scaling and permutation using the second-order statistics of the channel output. This condition is that the channel matrix is irreducible (but not necessarily column-reduced), and the input signals are mutually uncorrelated and of distinct power spectra. We also show that this condition is necessary in the sense that no single part of the condition can be further weakened without another part being strengthened. While the above condition is a strong result that sets a fundamental limit of blind identification, there does not yet exist a working algorithm under that condition. In the second part of this paper, we show that a method called blind identification via decorrelating subchannels (BIDS) can uniquely identify an FIR MIMO channel if a) the channel matrix is nonsingular (almost everywhere) and column-wise coprime and (b) the input signals are mutually uncorrelated and of sufficiently diverse power spectra. The BIDS method requires a weaker condition on the channel matrix than that required by most existing methods for the same problem. |
| first_indexed | 2025-11-14T05:58:42Z |
| format | Journal Article |
| id | curtin-20.500.11937-3558 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T05:58:42Z |
| publishDate | 2003 |
| publisher | IEEE Signal Processing Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-35582017-01-30T10:32:24Z Blind identification of FIR MIMO channels by decorrelating subchannels Hua, Y. An, Senjian Xiang, Y. Adaptive signal processing blind channel deconvolution colored sources sensor array processing blind system identification MIMO channels decorrelation We study blind identification and equalization of finite impulse response (FIR) and multi-input and multi-output (MIMO) channels driven by colored signals. We first show a sufficient condition for an FIR MIMO channel to be identifiable up to a scaling and permutation using the second-order statistics of the channel output. This condition is that the channel matrix is irreducible (but not necessarily column-reduced), and the input signals are mutually uncorrelated and of distinct power spectra. We also show that this condition is necessary in the sense that no single part of the condition can be further weakened without another part being strengthened. While the above condition is a strong result that sets a fundamental limit of blind identification, there does not yet exist a working algorithm under that condition. In the second part of this paper, we show that a method called blind identification via decorrelating subchannels (BIDS) can uniquely identify an FIR MIMO channel if a) the channel matrix is nonsingular (almost everywhere) and column-wise coprime and (b) the input signals are mutually uncorrelated and of sufficiently diverse power spectra. The BIDS method requires a weaker condition on the channel matrix than that required by most existing methods for the same problem. 2003 Journal Article http://hdl.handle.net/20.500.11937/3558 IEEE Signal Processing Society fulltext |
| spellingShingle | Adaptive signal processing blind channel deconvolution colored sources sensor array processing blind system identification MIMO channels decorrelation Hua, Y. An, Senjian Xiang, Y. Blind identification of FIR MIMO channels by decorrelating subchannels |
| title | Blind identification of FIR MIMO channels by decorrelating subchannels |
| title_full | Blind identification of FIR MIMO channels by decorrelating subchannels |
| title_fullStr | Blind identification of FIR MIMO channels by decorrelating subchannels |
| title_full_unstemmed | Blind identification of FIR MIMO channels by decorrelating subchannels |
| title_short | Blind identification of FIR MIMO channels by decorrelating subchannels |
| title_sort | blind identification of fir mimo channels by decorrelating subchannels |
| topic | Adaptive signal processing blind channel deconvolution colored sources sensor array processing blind system identification MIMO channels decorrelation |
| url | http://hdl.handle.net/20.500.11937/3558 |