On Secrecy Rate of the Generalized Artificial-Noise Assisted Secure Beamforming for Wiretap Channels
Pin-Hsun Lin, Szu-Hsiang Lai, Shih-Chun Lin, Hsuan-Jung Su

TL;DR
This paper proposes a generalized artificial-noise beamforming scheme for secure wireless communication, improving secrecy rates by optimally injecting noise in the main channel, especially when the legitimate channel quality is poor.
Contribution
It introduces a novel AN-assisted beamforming method that injects noise into the message direction, optimizing secrecy rate under partial eavesdropper channel knowledge.
Findings
Outperforms previous schemes, especially with poor legitimate channels.
Enlarges the regime of non-zero secrecy rate.
Provides an efficient algorithm for power allocation.
Abstract
In this paper we consider the secure transmission in fast Rayleigh fading channels with full knowledge of the main channel and only the statistics of the eavesdropper's channel state information at the transmitter. For the multiple-input, single-output, single-antenna eavesdropper systems, we generalize Goel and Negi's celebrated artificial-noise (AN) assisted beamforming, which just selects the directions to transmit AN heuristically. Our scheme may inject AN to the direction of the message, which outperforms Goel and Negi's scheme where AN is only injected in the directions orthogonal to the main channel. The ergodic secrecy rate of the proposed AN scheme can be represented by a highly simplified power allocation problem. To attain it, we prove that the optimal transmission scheme for the message bearing signal is a beamformer, which is aligned to the direction of the legitimate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Communication Security Techniques · Advanced MIMO Systems Optimization · Cooperative Communication and Network Coding
