Blind identification of FIR MIMO channels by decorrelating subchannels
dc.contributor.author | Hua, Y. | |
dc.contributor.author | An, Senjian | |
dc.contributor.author | Xiang, Y. | |
dc.date.accessioned | 2017-01-30T10:32:23Z | |
dc.date.available | 2017-01-30T10:32:23Z | |
dc.date.created | 2010-06-03T20:02:30Z | |
dc.date.issued | 2003 | |
dc.identifier.citation | Hua, Yingbo and An, Senjian and Xiang, Yong. 2003. Blind identification of FIR MIMO channels by decorrelating subchannels. IEEE Transactions on Signal Processing. 51 (5): pp. 1143-1155. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/3558 | |
dc.description.abstract |
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. | |
dc.publisher | IEEE Signal Processing Society | |
dc.subject | Adaptive signal processing | |
dc.subject | blind channel deconvolution | |
dc.subject | colored sources | |
dc.subject | sensor array processing | |
dc.subject | blind system identification | |
dc.subject | MIMO channels | |
dc.subject | decorrelation | |
dc.title | Blind identification of FIR MIMO channels by decorrelating subchannels | |
dc.type | Journal Article | |
dcterms.source.volume | 51 | |
dcterms.source.number | 5 | |
dcterms.source.startPage | 1143 | |
dcterms.source.endPage | 1155 | |
dcterms.source.issn | 1053-587X | |
dcterms.source.title | IEEE Transactions on Signal Processing | |
curtin.note |
Copyright © 2003 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
curtin.accessStatus | Open access | |
curtin.faculty | School of Science and Computing | |
curtin.faculty | Department of Computing | |
curtin.faculty | Faculty of Science and Engineering |