Algorithm comparison for in-situ beamforming

This paper compares the Simple Genetic Algorithm (SGA) to a Triallelic Diploid Genetic Algorithm (TDGA) in evolving an anti-jamming beamforming array in situ. The SGA and TDGA are both able to find reasonable beamformer settings to thwart two jammers while allowing reception of a signal of interest (SOI). The array operates in the 2.4 GHz 802.11g band, and the results presented are applicable to other applications because the SGA and TGDA do not require signal directions and modulation schemes a priori. An analysis of SGA and TDGA convergence times is also presented.

[1]  Jason D. Lohn,et al.  An anti-jamming beamformer optimized using evolvable hardware , 2011, 2011 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS 2011).

[2]  Eric Michielssen,et al.  The control of adaptive antenna arrays with genetic algorithms using dominance and diploidy , 2001 .

[3]  Jason D. Lohn,et al.  An evolved anti-jamming adaptive beamforming network , 2011, Genetic Programming and Evolvable Machines.

[4]  A. Massa,et al.  Planar antenna array control with genetic algorithms and adaptive array theory , 2004, IEEE Transactions on Antennas and Propagation.

[5]  J. D. Lohn,et al.  An in-situ optimized anti-jamming beamformer for mobile signals , 2012, Proceedings of the 2012 IEEE International Symposium on Antennas and Propagation.

[6]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .