Kernel-based nonlinear beamforming construction using orthogonal forward selection with Fisher ratio class separability measure
Chen, S., Hanzo, L. and Wolfgang, A. (2004) Kernel-based nonlinear beamforming construction using orthogonal forward selection with Fisher ratio class separability measure. IEEE Signal Processing Letters, 11, (5), 478-481.
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Description/Abstract
This letter shows that the wireless communication system capacity is greatly enhanced by employing nonlinear beamforming and the optimal Bayesian beamformer outperforms the standard linear beamformer significantly in terms of a reduced bit error rate, at a cost of increased complexity. Block-data adaptive implementation of the Bayesian beamformer is realized based on an orthogonal forward selection procedure with Fisher ratio for class separability measure.
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 259267 |
| Date Deposited: | 20 Apr 2004 |
| Last Modified: | 02 Mar 2012 02:29 |
| Contributors: | Chen, S. (Author) Hanzo, L. (Author) Wolfgang, A. (Author) |
| Date: | May 2004 |
| Status: | Published |
| Publisher: | IEEE Signal Processing Society |
| Further Information: | Google Scholar |
| ISI Citation Count: | 9 |
| URI: | http://eprints.soton.ac.uk/id/eprint/259267 |
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- Kernel-based nonlinear beamforming construction using orthogonal forward selection with Fisher ratio class separability measure. (deposited 20 Apr 2004) [Currently Displayed]
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