Paper Info
Title
A dual perspective on separable semidefinite programming with applications to optimal beamforming.
Abstract
Consider the downlink beamforming optimization problem with signal-to-interference-plus-noise ratio constraints, null-shaping interference constraints and multiple groups of individual shaping constraints. We propose an efficient algorithm for the problem, which consists of firstly solving the dual of the semidefinite programm (SDP) relaxation, secondly formulating a linear program (LP) and solving it to find a rank-one solution of the SDP relaxation. In contrast to the existing algorithms, the analysis of the proposed algorithm includes neither the rank reduction steps (purification process) nor the Perron-Frobenius theorem.
Year
DOI
Venue
2010
10.1109/ICASSP.2010.5496110
ICASSP
Keywords
Field
DocType
signal to noise ratio,base stations,constraint optimization,quality of service,downlink,signal to interference plus noise ratio,linear program,optimization problem,linear programming
Beamforming,Mathematical optimization,Perron–Frobenius theorem,Computer science,Signal-to-noise ratio,Separable space,Linear programming,Optimization problem,Semidefinite programming,Constrained optimization
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4244-4296-6
978-1-4244-4296-6
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Yongwei Huang181450.83
Daniel Pérez Palomar22146134.10