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Secure Full-Duplex Communication via Movable Antennas

Jingze Ding, Zijian Zhou, Chenbo Wang, Wenyao Li, Lifeng Lin, Bingli Jiao

TL;DR

This work addresses secure wireless communication by exploiting movable antennas (MAs) in a full-duplex base station to secure both uplink and downlink transmissions against a single-antenna eavesdropper. It formulates a sum secrecy-rate (SSR) maximization problem that jointly optimizes transmit/receive beamformers and MA positions, and solves it via an alternating optimization framework that combines successive convex approximation (SCA), semidefinite relaxation (SDR), and particle swarm optimization (PSO). The proposed MA-FD-PSO scheme achieves substantial SSR gains over fixed-antenna and HD benchmarks, validating the benefits of dynamic MA positioning and joint beamforming with artificial noise. The results demonstrate that MA mobility, FD operation, and AN together substantially enhance security performance in constrained wireless environments, offering a practical path toward more secure, high-throughput systems.

Abstract

This paper investigates physical layer security (PLS) in a movable antenna (MA)-assisted full-duplex (FD) system. In this system, an FD base station (BS) with multiple MAs for transmission and reception provides services for an uplink (UL) user and a downlink (DL) user. Each user operates in half-duplex (HD) mode and is equipped with a single fixed-position antenna (FPA), in the presence of a single-FPA eavesdropper (Eve). To ensure secure communication, artificial noise (AN) is transmitted to obstruct the interception of Eve. The objective of this paper is to maximize the sum secrecy rate (SSR) of the UL and DL users by jointly optimizing the beamformers of the BS and the positions of MAs. This paper also proposes an alternating optimization (AO) method to address the non-convex problem, which decomposes the optimization problem into three subproblems and solves them iteratively. Simulation results demonstrate a significant performance gain in the SSR achieved by the proposed scheme compared to the benchmark schemes.

Secure Full-Duplex Communication via Movable Antennas

TL;DR

This work addresses secure wireless communication by exploiting movable antennas (MAs) in a full-duplex base station to secure both uplink and downlink transmissions against a single-antenna eavesdropper. It formulates a sum secrecy-rate (SSR) maximization problem that jointly optimizes transmit/receive beamformers and MA positions, and solves it via an alternating optimization framework that combines successive convex approximation (SCA), semidefinite relaxation (SDR), and particle swarm optimization (PSO). The proposed MA-FD-PSO scheme achieves substantial SSR gains over fixed-antenna and HD benchmarks, validating the benefits of dynamic MA positioning and joint beamforming with artificial noise. The results demonstrate that MA mobility, FD operation, and AN together substantially enhance security performance in constrained wireless environments, offering a practical path toward more secure, high-throughput systems.

Abstract

This paper investigates physical layer security (PLS) in a movable antenna (MA)-assisted full-duplex (FD) system. In this system, an FD base station (BS) with multiple MAs for transmission and reception provides services for an uplink (UL) user and a downlink (DL) user. Each user operates in half-duplex (HD) mode and is equipped with a single fixed-position antenna (FPA), in the presence of a single-FPA eavesdropper (Eve). To ensure secure communication, artificial noise (AN) is transmitted to obstruct the interception of Eve. The objective of this paper is to maximize the sum secrecy rate (SSR) of the UL and DL users by jointly optimizing the beamformers of the BS and the positions of MAs. This paper also proposes an alternating optimization (AO) method to address the non-convex problem, which decomposes the optimization problem into three subproblems and solves them iteratively. Simulation results demonstrate a significant performance gain in the SSR achieved by the proposed scheme compared to the benchmark schemes.
Paper Structure (13 sections, 19 equations, 4 figures, 1 table, 1 algorithm)

This paper contains 13 sections, 19 equations, 4 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. MIMO Channel for ${\mathbf{H}_\mathrm{SI}} \left( {\tilde{ \mathbf{t}}}, {\tilde{ \mathbf{r}}} \right)$
  5. SIMO or MISO Channels for ${\mathbf{h}_\mathrm{UB}} \left( {\tilde{ \mathbf{r}}} \right)$, ${\mathbf{h}_\mathrm{BD}} \left( {\tilde{ \mathbf{t}}} \right)$, and ${\mathbf{h}_\mathrm{BE}} \left( {\tilde{ \mathbf{t}}} \right)$
  6. Problem Formulation
  7. Proposed Solution
  8. Subproblem 1: Optimize $\mathbf{w}_\mathrm{r}$ With Given $\mathbf{w}$, $\mathbf{v}$, $\tilde{\mathbf{t}}$, and $\tilde{\mathbf{r}}$
  9. Subproblem 2: Optimize $\mathbf{w}$ and $\mathbf{v}$ With Given $\mathbf{w}_\mathrm{r}$, $\tilde{\mathbf{t}}$, and $\tilde{\mathbf{r}}$
  10. Subproblem 3: Optimize $\tilde{\mathbf{t}}$ and $\tilde{\mathbf{r}}$ With Given $\mathbf{w}_\mathrm{r}$, $\mathbf{w}$, and $\mathbf{v}$
  11. Overall Algorithm and Analysis
  12. Simulation Results
  13. Conclusion

Figures (4)

  • Figure 1: An illustration for the proposed communication system.
  • Figure 2: Sum secrecy rate versus normalized region size.
  • Figure 3: Sum secrecy rate versus the SIC coefficient.
  • Figure 4: Sum secrecy rate versus the number of antennas.