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