New semidefinite relaxations for a class of complex quadratic programming problems
From MaRDI portal
Publication:6166105
DOI10.1007/s10898-023-01290-zarXiv2305.09934MaRDI QIDQ6166105
Cheng Lu, Yingzhe Xu, Zhi-bin Deng, Ya-Feng Liu
Publication date: 2 August 2023
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2305.09934
approximation algorithmquadratic optimizationsemidefinite relaxationdiscrete transmit beamformingphase quantized waveform design
Semidefinite programming (90C22) Quadratic programming (90C20) Approximation methods and heuristics in mathematical programming (90C59)
Cites Work
- Tightness of the maximum likelihood semidefinite relaxation for angular synchronization
- Argument division based branch-and-bound algorithm for unit-modulus constrained complex quadratic programming
- On approximating complex quadratic optimization problems via semidefinite programming relaxations
- A spatial branch-and-cut method for nonconvex QCQP with bounded complex variables
- Approximation algorithms for MAX-3-CUT and other problems via complex semidefinite programming
- Phase recovery, MaxCut and complex semidefinite programming
- Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
- Design of Phase Codes for Radar Performance Optimization With a Similarity Constraint
- Design of Optimized Radar Codes With a Peak to Average Power Ratio Constraint
- Designing Unimodular Codes Via Quadratic Optimization
- Tightness of a New and Enhanced Semidefinite Relaxation for MIMO Detection
- An Efficient Quadratic Programming Relaxation Based Algorithm for Large-Scale MIMO Detection
- Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence
- Convex Relaxation of Optimal Power Flow—Part II: Exactness
- Complex Quadratic Optimization and Semidefinite Programming
This page was built for publication: New semidefinite relaxations for a class of complex quadratic programming problems
