DocumentCode :
2677992
Title :
Let swarms of bees optimize your future communication antennas
Author :
Rahmat-Samii, Yahya
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Los Angeles, CA, USA
fYear :
2011
fDate :
16-19 Jan. 2011
Firstpage :
3
Lastpage :
3
Abstract :
Optimization is the process of upgrading something to perform better. Engineers constantly look for improving their designs in multi parametric solution space. Imagine that you will be able to use nature´s evolutionary processes to obtain the best parameters for your designs. This is the subject of this presentation. The ever increasing advances in computational power have fueled the temptation of using global optimization techniques. The well-known brute force design methodologies are systematically being replaced by the state-of-the-art Evolutionary Optimization (EO) techniques. In recent years, EO techniques are finding growing applications to the design of all kind of systems with increasing complexity. Among various EO´s, nature inspired techniques such as Particle Swarm Optimization (PSO) have attracted considerable attention. PSO is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms of bees looking for the most fertile feeding location applying their cognitive and social knowledge. This presentation will focus on: (a) an engineering introduction to PSO by describing in a novel fashion the underlying concepts and recent advances for those who have used these techniques and for those who have not had any experiences in these areas, (b) ease of deployment of PSO on parallel computational platforms, (c) demonstration of the potential applications of PSO to a variety of communication antenna designs including advanced cellphone antennas, E-shaped antennas for multiband and broadband MIMO applications, novel reconfigurable antennas and array antennas, and (d) assessment of the advantages and limitations of this technique.
Keywords :
mobile antennas; particle swarm optimisation; E-shaped antennas; array antennas; bees let swarms; broadband MIMO applications; cellphone antennas; cognitive knowledge; communication antennas; evolutionary optimization techniques; multi parametric solution space; multiband MIMO applications; parallel computational platforms; particle swarm optimization; reconfigurable antennas; robust stochastic evolutionary computation technique; social knowledge;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radio and Wireless Symposium (RWS), 2011 IEEE
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-4244-7687-9
Type :
conf
DOI :
10.1109/RWS.2011.5725518
Filename :
5725518
Link To Document :
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