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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kai-Jian Lin Yinman Lee |
| Copyright Year | 2008 |
| Description | Author affiliation: Grad. Inst. of Commun. Eng., Nat. Chi Nan Univ., Puli (Kai-Jian Lin; Yinman Lee) |
| Abstract | In this paper, we present an efficient detection scheme for spatial multiplexing over time-varying multiple-input multiple-output (MIMO) channels. The filter weights for detection are optimized by the minimum variance (MV) criterion. The resultant MV detector is adaptively realized with the generalized sidelobe canceller (GSC) structure. With the up-to-date channel state information (CSI), we show that the signal matched filter and blocking matrix in GSC can be determined through the use of the Householder transformation. The advantage of this approach is that it avoids the abrupt changes in the adaptive process whenever the signal matched filter and blocking matrix are updated according to the changing MIMO channel. All adaptation operations are implemented with the least-mean- square (LMS) algorithm. Simulations reveal that the proposed adaptive MV detector can outperform the conventional adaptive minimum mean-squared-error (MMSE) detector in time-varying channel environments. |
| Starting Page | 1360 |
| Ending Page | 1364 |
| File Size | 194992 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424416448 |
| ISSN | 15502252 |
| DOI | 10.1109/VETECS.2008.286 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-11 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | MIMO Detectors Receiving antennas Matched filters Transmitting antennas Least squares approximation Maximum likelihood detection Channel state information Signal processing Transmitters |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Electrical and Electronic Engineering Computer Science Applications |
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