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Antenna Current Optimization using MATLAB and CVX

Gustafsson, Mats LU ; Tayli, Doruk LU ; Ehrenborg, Casimir LU ; Cismasu, Marius LU and Nordebo, Sven LU (2016) In FERMAT 15.
Abstract
Antenna current optimization is a tool that offers many possibilities in antenna technology. Optimal currents are determined in the antenna design region and used for physical understanding, as a priori estimates of the possibilities to
design antennas, physical bounds and as figures of merits for antenna designs. Antenna current optimization is particularly useful for small antennas and antennas that are constrained by their electrical size. The initial non-convex antenna design optimization problem is reformulated as a convex optimization
problem expressed in the currents on the antenna. This convex optimization problem is solved efficiently at a computational cost comparable to a Method of Moments (MoM) solution of the same... (More)
Antenna current optimization is a tool that offers many possibilities in antenna technology. Optimal currents are determined in the antenna design region and used for physical understanding, as a priori estimates of the possibilities to
design antennas, physical bounds and as figures of merits for antenna designs. Antenna current optimization is particularly useful for small antennas and antennas that are constrained by their electrical size. The initial non-convex antenna design optimization problem is reformulated as a convex optimization
problem expressed in the currents on the antenna. This convex optimization problem is solved efficiently at a computational cost comparable to a Method of Moments (MoM) solution of the same geometry. In this paper a tutorial description of antenna current optimization is presented. Stored energies and their relation to the impedance matrix in MoM is reviewed. The convex optimization problems are solved using MATLAB and CVX. MoM data is
included together with MATLAB and CVX codes to optimize the antenna current for strip dipoles and planar rectangles. Codes and numerical results for maximization of the gain to Q-factor quotient and minimization of the Q-factor for prescribed radiated fields are provided. (Less)
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in
FERMAT
volume
15
pages
29 pages
language
English
LU publication?
yes
id
27f6f8b4-9048-4d35-a247-57532a77e87c
alternative location
http://www.e-fermat.org/articles/gustafsson-art-2016-vol15-may-jun-005/
date added to LUP
2016-04-28 11:50:19
date last changed
2016-04-28 12:28:26
@misc{27f6f8b4-9048-4d35-a247-57532a77e87c,
  abstract     = {Antenna current optimization is a tool that offers many possibilities in antenna technology. Optimal currents are determined in the antenna design region and used for physical understanding, as a priori estimates of the possibilities to<br/>design antennas, physical bounds and as figures of merits for antenna designs. Antenna current optimization is particularly useful for small antennas and antennas that are constrained by their electrical size. The initial non-convex antenna design optimization problem is reformulated as a convex optimization<br/>problem expressed in the currents on the antenna. This convex optimization problem is solved efficiently at a computational cost comparable to a Method of Moments (MoM) solution of the same geometry. In this paper a tutorial description of antenna current optimization is presented. Stored energies and their relation to the impedance matrix in MoM is reviewed. The convex optimization problems are solved using MATLAB and CVX. MoM data is<br/>included together with MATLAB and CVX codes to optimize the antenna current for strip dipoles and planar rectangles. Codes and numerical results for maximization of the gain to Q-factor quotient and minimization of the Q-factor for prescribed radiated fields are provided.},
  author       = {Gustafsson, Mats and Tayli, Doruk and Ehrenborg, Casimir and Cismasu, Marius and Nordebo, Sven},
  language     = {eng},
  pages        = {29},
  series       = {FERMAT},
  title        = {Antenna Current Optimization using MATLAB and CVX},
  volume       = {15},
  year         = {2016},
}