Artificial Intelligence Algorithms Based Null-Steering vis-à-vis Classical Beam-Steering in Smart Antennas
AbstractModern antenna array systems utilize intelligent algorithms to optimize radiation patterns (beamforming) in wireless communication links in accordance to particular criterions, hence the name “smart antennas”. Major criterions utilized include beam-steering, null-steering, reference signal based approaches and statistical blind approaches. Null and beam steering criterions are viable in situations in which the desired maximal and minimal radiation (or reception) directions are known. Particle Swarm Optimization (PSO) and Genetic (GA) algorithms perform well in multimodal optimization problems, and are consequently viable for application in beamforming. In this paper, comparison is made between use of classical beam-steering techniques and PSO/ GA optimized null-steering techniques in beamforming. This comparison is done on the basis of a linear antenna array.The resultant radiation patterns are used as performance measures. The GA/ PSO optimized null-steering technique is found more efficient compared to the classical beam-steering technique. The former is found to generate radiation patterns of lower side-lobe levels, and has the ability to generate radiation nulls in undesiredradiation directions as compared to the latter.
Jun 13, 2016
How to Cite
MACHARIA, Robert; LANGAT, Kibet; KIHATO, Peter. Artificial Intelligence Algorithms Based Null-Steering vis-à-vis Classical Beam-Steering in Smart Antennas. Proceedings of Sustainable Research and Innovation Conference, [S.l.], p. 213-217, june 2016. ISSN 2079-6226. Available at: <http://sri.jkuat.ac.ke/ojs/index.php/proceedings/article/view/430>. Date accessed: 23 nov. 2017.
Linear antenna array; Particle swarm optimization algorithm; Genetic algorithm; Beam/ null steering
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