Convex Optimization and its Applications in Robust Adaptive Beamforming

被引：0
|
作者：
Yu, Z. L. [1 ]
Gu, Z. [1 ]
Ser, W. [2 ]
Er, M. H. [2 ]
机构：
[1] S China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China
[2] Nanyang Technol Univ, Sch EEE, Singaproe 639798, Singapore
来源：
2013 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING (ICICS) | 2013年
关键词：
Convex Optimization; Robust adaptive beamforming; adaptive array; constraints on magnitude response; worst-case optimization; SPECTRAL FACTORIZATION; CONSTRAINTS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Convex optimization plays an important role in science and engineering research. In many signal processing applications, convex optimization is one of the critical mathematical tools. For example, robust adaptive beamformer is always formulated as quadratic optimization problem with some linear or quadratic constraints. In this paper, we review some of the progresses of our group on using Constraints on Magnitude Response (CMRs) for robust adaptive beamforming. Some mathematical skills on how to transform the beamformer with CMRs into convex programming problems are introduced. With proper convex formulations, the proposed beamformers posses simple implementation, flexible performance control, as well as significant SINR enhancement.
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页数：5
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