An introduction to convex optimization for communications and signal processing

Convex optimization methods are widely used in the design and analysis of communication systems and signal processing algorithms. This tutorial surveys some of recent progress in this area. The tutorial contains two parts. The first part gives a survey of basic concepts and main techniques in convex...

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Vydané v:	IEEE journal on selected areas in communications Ročník 24; číslo 8; s. 1426 - 1438
Hlavní autori:	Luo, Zhi-Quan, Yu, Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2006 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithm design and analysis Algorithms Communication systems Conics Convex optimization Design engineering Digital communication digital communications Digital signal processing duality Lagrangian functions Linear programming Optimization Optimization methods Programming Robustness second-order cone programming (SOCP) semidefinite programming (SDP) Signal processing Signal processing algorithms Surveys Symmetric matrices
ISSN:	0733-8716, 1558-0008
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Abstract	Convex optimization methods are widely used in the design and analysis of communication systems and signal processing algorithms. This tutorial surveys some of recent progress in this area. The tutorial contains two parts. The first part gives a survey of basic concepts and main techniques in convex optimization. Special emphasis is placed on a class of conic optimization problems, including second-order cone programming and semidefinite programming. The second half of the survey gives several examples of the application of conic programming to communication problems. We give an interpretation of Lagrangian duality in a multiuser multi-antenna communication problem; we illustrate the role of semidefinite relaxation in multiuser detection problems; we review methods to formulate robust optimization problems via second-order cone programming techniques
AbstractList	Convex optimization methods are widely used in the design and analysis of communication systems and signal processing algorithms. This tutorial surveys some of recent progress in this area. The tutorial contains two parts. The first part gives a survey of basic concepts and main techniques in convex optimization. Special emphasis is placed on a class of conic optimization problems, including second-order cone programming and semidefinite programming. The second half of the survey gives several examples of the application of conic programming to communication problems. We give an interpretation of Lagrangian duality in a multiuser multi-antenna communication problem; we illustrate the role of semidefinite relaxation in multiuser detection problems; we review methods to formulate robust optimization problems via second-order cone programming techniques
Author	Wei Yu Zhi-Quan Luo
Author_xml	– sequence: 1 givenname: Zhi-Quan surname: Luo fullname: Luo, Zhi-Quan – sequence: 2 givenname: Wei surname: Yu fullname: Yu, Wei
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SubjectTerms	Algorithm design and analysis Algorithms Communication systems Conics Convex optimization Design engineering Digital communication digital communications Digital signal processing duality Lagrangian functions Linear programming Optimization Optimization methods Programming Robustness second-order cone programming (SOCP) semidefinite programming (SDP) Signal processing Signal processing algorithms Surveys Symmetric matrices
Title	An introduction to convex optimization for communications and signal processing
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