By Topic

A Comparative Study of Optimization Techniques in Adaptive Antenna Array Processing: The Bacteria-Foraging Algorithm and Particle-Swarm Optimization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Datta, T. ; Dept. of Electron. & Telecommun. Eng., Jadavpur Univ., Kolkata, India ; Misra, I.S.

This paper presents a comparative study between the Bacteria-Foraging (BF) and Particle-Swarm Optimization (PSO) algorithms, and their application to the antenna-array optimization problem. The performance of the Bacteria-Foraging Algorithm is studied by varying its different parameters in beamforming and null-steering problems. Null steering along with sidelobe suppression is also done for various degrees of complexity. A generic cost function is developed, the parameters of which can be controlled to meet the requirements of the particular application. The two algorithms are compared for null depth, average sidelobe level, and rate of convergence for different numbers of interference signals. The performance of these methods are compared for output noise power for the same noise inputs. Results are shown for a linear dipole antenna-array system.

Published in:

Antennas and Propagation Magazine, IEEE  (Volume:51 ,  Issue: 6 )