An evolved anti-jamming adaptive beamforming network

Authors:
Jason D. Lohn;Jonathan M. Becker;Derek S. Linden
Affiliations:
Department of Electrical and Computer Engineering, Carnegie Mellon University, Mountain View, USA;Department of Electrical and Computer Engineering, Carnegie Mellon University, Mountain View, USA;X5 Systems Inc, Ashburn, USA
Venue:
Genetic Programming and Evolvable Machines
Year:
2011

Citing 3
Cited 0

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Abstract

Interference in wireless networks is undesirable, whether it is due to unintentional or malicious causes. Adaptive beamforming is a spatial filtering technique that can prevent jammers from disrupting wireless networks. This paper presents an evolvable hardware (EH) application in which an evolutionary algorithm (EA) is used to configure an adaptive beamformer to achieve two goals: (1) steering nulls towards jamming signals and (2) directing gain in the direction of the desired signal. This is the first demonstration of an EA-configured adaptive beamformer to counter a jamming system. Simulation results show that the EA is able to thwart up to three jamming signals. The results suggest that EH is a promising approach towards wireless network security.