Dual-Band Antenna Array Optimizations Using Heuristic Algorithms and the Multilevel Fast Multipole Algorithm

Date

2015-05-24

Author

Onol, Can
Gokce, Ozer
Ergül, Özgür Salih

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

172
views

0
downloads

We consider design and simulations of dual-band antenna arrays and their optimizations via heuristic algorithms, particularly, genetic algorithms (GAs) and particle swarm optimization (PSO) methods. As shown below, these arrays consist of patch antennas of different sizes, depending on the target frequencies. The resulting radiation problems are solved iteratively, where the matrix-vector multiplications are performed efficiently with the multilevel fast multipole algorithm (MLFMA). MLFMA allows for realistic simulations of antenna arrays of finite extent, without any periodicity and similarity assumptions, while including all mutual couplings between the antennas. This way, we obtain effective and realistic optimizations.

URI

https://hdl.handle.net/11511/40224

DOI

https://doi.org/10.1109/ursi-at-rasc.2015.7302878

Conference Name

2015 1st URSI Atlantic Radio Science Conference (URSI AT-RASC)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm DEĞERTEKİN, SADIK ÖZGÜR; Saka, M. P.; HAYALİOĞLU, MEHMET SEDAT (Elsevier BV, 2008-01-01) In this paper, algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search and genetic algorithm. Tabu search utilizes the features of short-term memory facility (tabu list) and aspiration criteria. Genetic algorithm employs reproduction, crossover and mutation operators. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange...
Antenna Switch Optimizations Using Genetic Algorithms Accelerated With the Multilevel Fast Multipole Algorithm Onol, Can; Karaosmanoglu, Bariscan; Ergül, Özgür Salih (2015-07-24) We present antenna switch optimizations using an efficient mechanism based on genetic algorithms and the multi-level fast multipole algorithm (MLFMA). Genetic algorithms are used to determine switch states for desired radiation and input characteristics, while cost-function evaluations are performed efficiently via an MLFMA implementation with dynamic error control. MLFMA is integrated into the genetic algorithm by extracting common computations to be performed once per optimization. Iterative convergence r...
Implicit monolithic parallel solution algorithm for seismic analysis of dam-reservoir systems Özmen, Semih; Kurç, Özgür; Department of Civil Engineering (2016) This research mainly focuses on developing a computationally scalable and efficient solution algorithm that can handle linear dynamic analysis of dam-reservoir interaction problem. Lagrangian fluid finite elements are utilized and compressibility and viscosity of the fluid are taken into consideration during the reservoir modeling. In order to provide computational scalability and efficiency, domain decomposition methods implemented with parallel computing approaches such as Finite Element Tearing and Inter...
Improving Computational Efficiency of Particle Swarm Optimization for Optimal Structural Design Hasançebi, Oğuzhan (2013-06-01) This paper attempts to improve the computational efficiency of the well known particle swarm optimization (PSO) algorithm for tackling discrete sizing optimization problems of steel frame structures. It is generally known that, in structural design optimization applications, PSO entails enormously time-consuming structural analyses to locate an optimum solution. Hence, in the present study it is attempted to lessen the computational effort of the algorithm, using the so called upper bound strategy (UBS), wh...
Optimizations of Patch Antenna Arrays Using Genetic Algorithms Supported by the Multilevel Fast Multipole Algorithm Onol, Can; Ergül, Özgür Salih (2014-12-01) We present optimizations of patch antenna arrays using genetic algorithms and highly accurate full-wave solutions of the corresponding radiation problems with the multilevel fast multipole algorithm (MLFMA). Arrays of finite extent are analyzed by using MLFMA, which accounts for all mutual couplings between array elements efficiently and accurately. Using the superposition principle, the number of solutions required for the optimization of an array is reduced to the number of array elements, without resorti...

Citation Formats

C. Onol, O. Gokce, and Ö. S. Ergül, “Dual-Band Antenna Array Optimizations Using Heuristic Algorithms and the Multilevel Fast Multipole Algorithm,” presented at the 2015 1st URSI Atlantic Radio Science Conference (URSI AT-RASC), Las Palmas, Spain, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40224.