Performance analysis of anti-jamming technique using angle of Arrival estimation in CRN's

Abstract

Jamming has been one of the major attacks in any wireless network causing denial of service by disrupting the system. Jamming includes transmission of random signals with the high power towards the receiver causing interference and denial of service. This paper presents an anti-jamming mechanism for receivers in a cognitive radio network using Angle of Arrival (AoA) estimation method combined with adaptive beamforming. The receiver obtains the required signal at the particular angle found by AoA estimation followed by improving the SNR of the signal using beamforming neglecting interference from signals sent by jammers at other angles. AoA techniques like Esprit, Music and Root-Music algorithms are used to estimate the angle of arrival of the incoming signal. The Conjugate gradient method is used in the process of adaptive beamforming which continuously adapts to the varying angle provided by the AoA estimation. Simulations results are given comparing the Esprit, Music and Root-Music algorithms based on different angle of arrivals and SNR values. Simulation results are also provided for the combined mechanism of AoA estimation with Conjugate gradient method which will prove to be an effective way to avoid jamming.