A Distributionally Robust Minimum Variance Beamformer Design
IEEE This paper is concerned with a robust minimum variance beamformer design. To hedge the mismatch between the true and the assumed steering vectors, a distributionally robust beamformer (DR-beamformer) is proposed. The tractable reformulation of this beamformer is developed. Compared with the exi...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Institute of Electrical and Electronics Engineers
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/62307 |
| _version_ | 1848760827483521024 |
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| author | Li, Bin Rong, Yue Sun, Jie Teo, Kok Lay |
| author_facet | Li, Bin Rong, Yue Sun, Jie Teo, Kok Lay |
| author_sort | Li, Bin |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | IEEE This paper is concerned with a robust minimum variance beamformer design. To hedge the mismatch between the true and the assumed steering vectors, a distributionally robust beamformer (DR-beamformer) is proposed. The tractable reformulation of this beamformer is developed. Compared with the existing robust beamformers (worst-case robust beamformer, Gaussian robust beamformer), the proposed robust beamformer does not assume full knowledge of the channel mismatch. Therefore, it is more flexible in practice and more general in formulation. In addition, the relationships of the proposed robust beamformer with the existing ones are investigated. The performance gain of the DR-beamformer over the other robust beamformers is highlighted through numerical simulations. |
| first_indexed | 2025-11-14T10:21:58Z |
| format | Journal Article |
| id | curtin-20.500.11937-62307 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:21:58Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-623072018-02-01T05:55:55Z A Distributionally Robust Minimum Variance Beamformer Design Li, Bin Rong, Yue Sun, Jie Teo, Kok Lay IEEE This paper is concerned with a robust minimum variance beamformer design. To hedge the mismatch between the true and the assumed steering vectors, a distributionally robust beamformer (DR-beamformer) is proposed. The tractable reformulation of this beamformer is developed. Compared with the existing robust beamformers (worst-case robust beamformer, Gaussian robust beamformer), the proposed robust beamformer does not assume full knowledge of the channel mismatch. Therefore, it is more flexible in practice and more general in formulation. In addition, the relationships of the proposed robust beamformer with the existing ones are investigated. The performance gain of the DR-beamformer over the other robust beamformers is highlighted through numerical simulations. 2017 Journal Article http://hdl.handle.net/20.500.11937/62307 10.1109/LSP.2017.2773601 Institute of Electrical and Electronics Engineers restricted |
| spellingShingle | Li, Bin Rong, Yue Sun, Jie Teo, Kok Lay A Distributionally Robust Minimum Variance Beamformer Design |
| title | A Distributionally Robust Minimum Variance Beamformer Design |
| title_full | A Distributionally Robust Minimum Variance Beamformer Design |
| title_fullStr | A Distributionally Robust Minimum Variance Beamformer Design |
| title_full_unstemmed | A Distributionally Robust Minimum Variance Beamformer Design |
| title_short | A Distributionally Robust Minimum Variance Beamformer Design |
| title_sort | distributionally robust minimum variance beamformer design |
| url | http://hdl.handle.net/20.500.11937/62307 |