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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | An, J.F. |
| Copyright Year | 2012 |
| Description | Author affiliation: Communications and Guidance Engineering Dept., National Taiwan Ocean University, Keelung, Taiwan (An, J.F.) |
| Abstract | Instead of using eigen-beamforming approach to increase capacity gain, an optimal pre-weighting scheme is employed in the closed-loop multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (MIMO-OFDM) wireless system design under subcarrier cluster constraint. This scheme adopts an uplink scale weight vector on the space-time block code (STBC) signals in accordance to its space-time constellation, without utilizing the transmit channel state information (TCSI). A Bayes decision algorithm is considered to generate the optimum weight vectors using channel coefficients measured from pilot subcarriers in each MIMO sub-channel. Analytical expressions of the signal-to-noise power ratio (SNR) improvement are derived over spatially correlated MIMO fading channels. Our Monte Carlo simulations show that the proposed scheme outperforms the Alamouti detection scheme in terms of the symbol-error-rate (SER) performance of 16QAM modulating with respect to various pilot intervals. The maximizing eigenvalue distributions (EVD) also validate our results. |
| Starting Page | 255 |
| Ending Page | 260 |
| File Size | 562315 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467347266 |
| e-ISBN | 9781467347280 |
| e-ISBN | 9781467347273 |
| DOI | 10.1109/APCC.2012.6388143 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-15 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | OFDM MIMO Channel estimation Transmitting antennas Vectors Receiving antennas Fading Bayes decision closed-loop MIMO ST-MIMO Rayleigh fading space-time coding |
| Content Type | Text |
| Resource Type | Article |
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