Antenna Design and Direction of Arrival Estimation in Meta-Heuristic Paradigm: A Review

Nilanjan Dey and Amira S. Ashour
Additional contact information
Nilanjan Dey: Department of Information Technology, Techno India College of Technology, Kolkata, India
Amira S. Ashour: Department of Electronics & Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 2016, vol. 7, issue 3, 1-18

Abstract: Antennas are considered as a significant component in any wireless system. There are numerous factors and constraints that affect its design. Therefore, recently several algorithms are developed to allow the designers optimize the antenna with respect to numerous different criteria, general constraints and the desired performance characteristics. In recent years there has been an increasing attention to some novel evolutionary techniques, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Bacteria-Foraging (BF), Biogeography Based Optimization (BBO), and Differential Evolution (DE) that used for antenna optimization. The current study discussed three popular population-based meta-heuristic algorithms for optimal antenna design and direction of arrival estimation. Basically, single and multi-objective population-based meta-heuristic algorithms are included. Besides hybrid methods are highlighted. This paper reviews antenna array design optimization as well as direction of arrival optimization problem for different antennas configurations.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 8/IJSSMET.2016070101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jssmet:v:7:y:2016:i:3:p:1-18

Access Statistics for this article

International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) is currently edited by Ahmad Taher Azar

More articles in International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) from IGI Global
Bibliographic data for series maintained by Journal Editor ().