Proactive Jamming Toward Interference Alignment Networks: Beneficial and Adversarial Aspects

Abstract

Interference alignment (IA) is a prospective method to achieve interference management in wireless networks. On the other hand, jamming can be deemed either as a potential threat to degrade the performance of wireless networks, or as a helper to combat the eavesdropping for the legitimate networks. In this paper, we consider these two opposite scenarios, beneficial and adversarial jamming, toward IA networks, and based on which two proactive jamming schemes are proposed. In the first scheme, the jammer utilizes its precoding vector to constrain the jamming signal into the same subspace as the interference at each IA receiver, which will disrupt the potential eavesdropping significantly without affecting the transmission of IA users. Specifically, secure transmission can be guaranteed through the jamming without any additional cooperation with the IA users. In the second scheme, the jammer utilizes its precoding vector to project the jamming signal into the same subspace as that of the desired signal at each IA receiver secretly. Thus, the IA users cannot detect the concealed jamming signal, which will result in the performance degradation of the IA network. Extensive simulation results are presented to show the effectiveness of the two proposed jamming schemes toward IA networks.