Title :
Modern Antenna Designs using Nature Inspired Optimization Techniques: Let Darwin and the bees help designing your Multi band MIMO antennas
Author :
Rahmat-Samii, Yahya
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA
Abstract :
Recent MIMO applications have noticeably magnified the importance of multi antennas. Antenna engineers are therefore constantly challenged with the temptation to search for optimum designs. In recent years, evolutionary optimization (EO) techniques are finding growing applications to the design of electromagnetic systems of increasing complexity. Among various EO´s, nature inspired techniques such as genetic algorithms (GA) and particle swarm optimization (PSO) have attracted considerable attention. GA utilizes an optimization methodology which allows a global search of the cost surface via the mechanism of the statistical random processes dictated by the Darwinian evolutionary concept. 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. This invited paper will focus on an engineering introduction to GA and PSO, and demonstrate potential applications of GAs and PSO´s to a variety of antenna designs applicable to personal communication antennas such as wideband and multiband antennas, MIMO antennas for laptops and handheld devices, implanted antennas, wearable antennas, etc
Keywords :
MIMO communication; antenna arrays; broadband antennas; genetic algorithms; multifrequency antennas; particle swarm optimisation; personal communication networks; random processes; statistical analysis; stochastic processes; evolutionary optimization; genetic algorithms; modem antenna designs; multi band MIMO antennas; nature inspired optimization techniques; particle swarm optimization; personal communication antennas; robust stochastic evolutionary computation technique; statistical random processes; wideband antennas; Broadband antennas; Cost function; Design engineering; Design optimization; Genetic algorithms; MIMO; Optimization methods; Particle swarm optimization; Random processes; Robustness; Antenna; MIMO; evolutionary optimizations; genetic algorithms; particle swarm optimization;
Conference_Titel :
Radio and Wireless Symposium, 2007 IEEE
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0445-2
Electronic_ISBN :
1-4244-0445-2
DOI :
10.1109/RWS.2007.351868