A Secure Beamforming Design: When Fluid Antenna Meets NOMA
Lifeng Mai, Junteng Yao, Jie Tang, Tuo Wu, Kai-Kit Wong, Hyundong, Shin, Fumiyuki Adachi

TL;DR
This paper introduces a secure beamforming approach for NOMA systems with fluid antennas, optimizing both beamforming vectors and antenna positions to significantly improve secrecy rates over traditional fixed-antenna systems.
Contribution
It presents a novel joint optimization method for secure beamforming and fluid antenna positioning in NOMA systems, enhancing physical layer security.
Findings
Proposed scheme outperforms conventional MISO NOMA in secrecy rate.
Joint optimization of beamforming and antenna positions yields significant security improvements.
Numerical results validate the effectiveness of the fluid antenna NOMA design.
Abstract
This letter proposes a secure beamforming design for downlink non-orthogonal multiple access (NOMA) systems utilizing fluid antenna systems (FAS). We consider a setup where a base station (BS) with fluid antennas (FAs) communicates to a cell-center user (CU) and a cell-edge user (CEU), each with a FA. The CU is the intended recipient while the CEU is regarded as a potential eavesdropper. Our aim is to maximize the achievable secrecy rate by jointly optimizing the secure beamforming vectors and the positions of FAs. To tackle this, we adopt an alternating optimization (AO) algorithm that optimizes secure beamforming and the positions of the FAs iteratively while keeping the other variables fixed. Numerical results illustrate that when FAs meet NOMA, the proposed scheme greatly enhances the secrecy rate compared to conventional multiple-input single-output (MISO) fixed antenna NOMA…
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
TopicsAntenna Design and Analysis · Advanced Wireless Communication Technologies · Energy Harvesting in Wireless Networks
MethodsBalanced Selection · Feedback Alignment · ADaptive gradient method with the OPTimal convergence rate
