DSP Implementation of the Particle Swarm and Genetic Algorithms for Real-Time Design of Thinned Array Antennas

Efficient implementation of sophisticated algorithms on digital signal processing (DSP) chips is a key issue in the implementation of software-defined radios. Here, focusing on beamforming and using the average calculation time and hardware usage as the two indicators of efficiency, a performance co...

Full description

Saved in:
Bibliographic Details
Published in:IEEE antennas and wireless propagation letters 2012, Vol.11, p.1170-1173
Main Authors: Damin Cao, Modiri, A., Sureka, G., Kiasaleh, K.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Antenna arrays
Arrays
Binary particle swarm optimization (BPSO)
Digital signal processing
evolutionary algorithm
genetic algorithm (GA)
Genetic algorithms
Particle swarm optimization
Signal processing algorithms
thinned array antenna (TAA)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Efficient implementation of sophisticated algorithms on digital signal processing (DSP) chips is a key issue in the implementation of software-defined radios. Here, focusing on beamforming and using the average calculation time and hardware usage as the two indicators of efficiency, a performance comparison between two versions of binary particle swarm optimization (PSO) and genetic algorithm, as the two popular evolutionary techniques, is presented. Using our proposed multirun strategy in DSP platforms, we show that modified PSO results in a reduction by 52% and 67% in the hardware utilization and calculation time as compared to genetic algorithm and binary PSO, respectively.
ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2012.2220514