Anti-Eavesdropping Schemes for Interference Alignment (IA)-Based Wireless Networks

In interference alignment (IA)-based networks, interferences are constrained into certain subspaces at the unintended receivers, and the desired signal can be recovered free of interference. Due to the superposition of signals from legitimate users at the eavesdropper, the IA-based network seems to be more secure than conventional wireless networks. Nevertheless, when adequate antennas are equipped, the legitimate information can still be eavesdropped. In this paper, we analyze the performance of the external eavesdropper, and propose two anti-eavesdropping schemes for IA-based networks. When the channel state information (CSI) of eavesdropper is available, zero-forcing scheme can be utilized, in which the transmitted signals are zero-forced at the eavesdropper through the precoding of transmitters in IA-based networks. Furthermore, a more generalized artificial noise (AN) scheme is proposed for IA-based networks without the knowledge of eavesdropper's CSI. In this scheme, a single-stream AN is generated by each user, which will disrupt the eavesdropping without introducing any additional interference to the legitimate transmission of IA-based networks. In addition, the feasibility conditions, transmission rate, and eavesdropping rate are analyzed in detail, and an iterative algorithm to achieve the scheme is also designed. Extensive simulation results are provided to verify our analysis results and show the effectiveness of the proposed anti-eavesdropping schemes for IA-based networks.

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