Study On Physical-layer Information Security Based On Artificial Noise

Given the broadcast nature of the wireless medium, the security of data communication has received considerable attentions. As a complement to cryptographic encryption, physical-layer security has become a new research area. Using artificial noise (AN) aided in transmitted signal is one of the efficient methods to guarantee secret communications over fading channels. Hence, the thesis does an in-depth study on the physical-layer security based on AN with convex optimization as math tools. It focuses on the secret communications in multi-input single-output (MISO) systems and cognitive radio networks and their robustness design. The major work and innovations are as follows:To guarantee the secret transmission between transmitter and the legal receiver, artificial noise which lies in the null space of the main channel (channel between transmitter and the legal receiver) according to physical-layer characteristics, to depress the signal-noise-ratio (SNR) at the illegal receiver by crippling its channel. The simulation results prove that the design with AN aided can fade the wire-tap channel while it has no impact on the main channel. And it can guarantee the secret communication between transmitter and legal receiver, but fails to take the optimization of power allocation into consideration.To allocate the transmitted power reasonably, a joint beamforming and artificial noise design are discussed here. On the assumption that transmitter has known perfect channel statement information (CSI) of both the main channel and the eavesdropping channel, to guarantee the legal receiver’s quality of service (QoS), minimizing the transmitted power is set as the object with the maximum SINRs of eavesdroppers and the minimum SINRs of the intended receiver as constraints. The simulation results show that the joint design based on AN can save more transmitting power to achieve the secret communications with the same level,compared with design without AN. Besides, the impact of artificial noise on guaranteeing the secret communication is proved.In allusion to the case that transmitter only knows the mean value and there are channel errors within limits, a robustness design based on AN is proposed, which sets optimizing power as object. Mathematical modeling and solution of the optimization problems are studied. Given the presence of channel uncertainties, the restrictions mentioned before are infinite. To solve the problem efficiently, the constraints are turned into linear matrix inequalities via S-procedure. The simulation results indicate that robustness design can improve the stability of the system.In view of the fact that cognitive radio technique can increase frequency spectrum utilization, the physical-layer security of cognitive radio networks is studied, with joint beamforming and artificial noise design. Firstly, the maximum SNR at SU-Rx is viewed as the objective function, constraining the maximum SNR at eavesdroppers and maximum value of interference temperature (the allowable interference power level at primary receiver) and transmitted power. On that basis above, a new design scheme is proposed. The minimum transmitted power is set as objective function. And the minimum SNR at SU-Rx are maximum value of interference temperature and maximum SNR at eavesdroppers as constraints. Moreover, the robustness designs of the two schemes are given. The simulation results testify the impact of artificial noise on improving the secret communications’ safety performance in cognitive radio networks.