Artificial-Noise-Aided Secure Transmission Scheme With Limited Training and Feedback Overhead

We design a novel artificial-noise-aided secure onoff transmission scheme in a wiretap channel. We consider a practical scenario where the multi-antenna transmitter only obtains partial channel knowledge from the single-antenna receiver through limited training and feedback but has no channel knowledge about the single-antenna eavesdropper. In the design, we first propose a three-period block transmission protocol to capture the practical training and quantization features. We then characterize the statistics of the received signal-to-noise ratios (SNRs) at the receiver and the eavesdropper. Under the secrecy outage constraint, we exploit the on-off scheme to perform secure transmission and derive a closed-form expression for the secrecy throughput. Moreover, we investigate the optimization problem of maximizing the secrecy throughput by proposing an iterative algorithm to determine the optimal power allocation between the information signal and artificial noise, as well as the optimal codeword transmission rate. Furthermore, we define the net secrecy throughput (NST) which takes the signaling overhead into account and address the problem of optimally allocating the block resource to the training and feedback overhead. Numerical results clearly demonstrate how the optimal signaling overhead changes with the number of transmit antennas, and there exists an optimal number of antennas that maximizes the NST.ARC Discovery Projects Grant DP15010390

Secret Channel Training to Enhance Physical Layer Security With a Full-Duplex Receiver

This work proposes a new channel training (CT) scheme for a full-duplex receiver to enhance physical layer security. Equipped with NB full-duplex antennas, the receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to reduce the non-cancellable self-interference due to the transmitted AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits a limited number of pilot symbols which are known only to itself. Such a secret CT scheme prevents an eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrading the eavesdropping capability. We analytically examine the connection probability (i.e., the probability of the data being successfully decoded by the receiver) of the legitimate channel and the secrecy outage probability due to eavesdropping for the proposed secret CT scheme. Based on our analysis, the optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined. Our examination shows that the newly proposed secret CT scheme significantly outperforms the non-secret CT scheme that uses publicly known pilots when the number of antennas at the eavesdropper is larger than one.ARC Discovery Projects Grant DP15010390

Secure Transmission Design With Feedback Compression for the Internet of Things

ARC Discovery Projects Grant DP150103905

Artificial-Noise-Aided Secure Transmission Scheme with Limited Training and Feedback Overhead

We design a novel artificial-noise-aided secure ON-OFF transmission scheme in a wiretap channel. We consider a practical scenario, where the multi-antenna transmitter only obtains partial channel knowledge from the single-antenna receiver through limited training and feedback but has no channel knowledge about the single-antenna eavesdropper. In the design, we first propose a three-period block transmission protocol to capture the practical training and quantization features. We then characterize the statistics of the received signal-to-noise ratios at the receiver and the eavesdropper. Under the secrecy outage constraint, we exploit the ON-OFF scheme to perform secure transmission and derive a closed-form expression for the secrecy throughput. Moreover, we investigate the optimization problem of maximizing the secrecy throughput by proposing an iterative algorithm to determine the optimal power allocation between the information signal and artificial noise, as well as the optimal codeword transmission rate. Furthermore, we define the net secrecy throughput (NST), which takes the signaling overhead into account and address the problem of optimally allocating the block resource to the training and feedback overhead. Numerical results clearly demonstrate how the optimal signaling overhead changes with the number of transmit antennas, and there exists an optimal number of antennas that maximizes the NS