Projects per year
Abstract / Description of output
Many optimization problems in communications and signal processing can be formulated as rankone constrained optimization problems. This has motivated the development of methods to solve such problem in specific scenarios. However, due to the nonconvex nature of the rankone constraint, limited progress has been made in solving generic rankone constrained optimization problems. In particular, the problem of efficiently finding a locally optimal solution to a generic rankone constrained problem remains open. This paper focuses on solving general rankone constrained problems via relaxation techniques. However, instead of dropping the rankone constraint completely as is done in traditional rankone relaxation methods, a novel algorithm that gradually relaxes the rankone constraint, termed the sequential rankone constraint relaxation (SROCR) algorithm, is proposed. Compared with previous algorithms, the SROCR algorithm can solve general rankone constrained problems, and can find feasible solutions with favorable complexity.
Original language  Undefined/Unknown 

Title of host publication  2017 25th European Signal Processing Conference (EUSIPCO) 
Pages  10601064 
Number of pages  5 
DOIs  
Publication status  Published  1 Aug 2017 
Keywords / Materials (for Nontextual outputs)
 concave programming
 relaxation theory
 signal processing
 SROCR algorithm
 generic rankone constrained optimization problems
 locally optimal solution
 nonconvex nature
 optimization problems
 rankone constrained problems
 sequential constraint relaxation algorithm
 sequential rankone constraint relaxation algorithm
 Complexity theory
 Convex functions
 Eigenvalues and eigenfunctions
 Europe
 Optimization
 Signal processing
 Signal processing algorithms
Projects
 1 Finished

Seamless and Adaptive Wireless Access for Efficient Future Networks (SERAN)
Thompson, J. & Haas, H.
1/01/15 → 31/12/18
Project: Research