Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints

For the robust adaptive beamforming problem of the gen l signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. A simple robust adaptive beamformer was derived by modeling and transforming. Not only an appr...

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Main Authors: Ding-jie XU, Rui HE, Feng SHEN
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2013-03-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.03.001/
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author Ding-jie XU
Rui HE
Feng SHEN
author_facet Ding-jie XU
Rui HE
Feng SHEN
author_sort Ding-jie XU
collection DOAJ
description For the robust adaptive beamforming problem of the gen l signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. A simple robust adaptive beamformer was derived by modeling and transforming. Not only an approximate closed-form solution to the optimal weight vector was derived with low complexity, but also the performance improvement could be obtained. The final simulation attests its effectiveness and correctness.
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institution DOAJ
issn 1000-436X
language zho
publishDate 2013-03-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-b29822650fbe4fc3983eeb5a8412250c2025-08-20T02:41:14ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-03-01341559670566Robust beamforming based on the worst-case performance optimization with positive semi-definite constraintsDing-jie XURui HEFeng SHENFor the robust adaptive beamforming problem of the gen l signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. A simple robust adaptive beamformer was derived by modeling and transforming. Not only an approximate closed-form solution to the optimal weight vector was derived with low complexity, but also the performance improvement could be obtained. The final simulation attests its effectiveness and correctness.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.03.001/adaptive beamformingworst-case performance optimizationgeneral signal modelssitive semi-definite constraints
spellingShingle Ding-jie XU
Rui HE
Feng SHEN
Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
Tongxin xuebao
adaptive beamforming
worst-case performance optimization
general signal models
sitive semi-definite constraints
title Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
title_full Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
title_fullStr Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
title_full_unstemmed Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
title_short Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
title_sort robust beamforming based on the worst case performance optimization with positive semi definite constraints
topic adaptive beamforming
worst-case performance optimization
general signal models
sitive semi-definite constraints
url http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.03.001/
work_keys_str_mv AT dingjiexu robustbeamformingbasedontheworstcaseperformanceoptimizationwithpositivesemidefiniteconstraints
AT ruihe robustbeamformingbasedontheworstcaseperformanceoptimizationwithpositivesemidefiniteconstraints
AT fengshen robustbeamformingbasedontheworstcaseperformanceoptimizationwithpositivesemidefiniteconstraints