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Artificial Noise Aided Physical Layer Security for Near-Field MIMO with Fluid Antenna Systems

Peng Zhang, Jian Dang, Miaowen Wen, Ziyang Liu, Chen Zhao, Huaifeng Shi, Chengsheng Pan, Zaichen Zhang

TL;DR

The paper tackles physical-layer security in near-field MIMO systems equipped with fluid antenna systems by jointly optimizing beamforming and artificial noise under a hybrid beamforming architecture. An alternating-optimization approach decomposes the problem into continuous BF/AN design and discrete port-selection subproblems, using generalized spectral water-filling and a prune–refit port-selection rule guided by group-sparsity theory. The BF/AN design achieves closed-form solutions within the AO framework and is realized with embedded AN in baseband, while the port-selection leverages row-energy cues to efficiently activate ports. Numerical results show significant secrecy gains for realistically sized FA-MIMO arrays in the NF regime, with clear advantages over BF-only schemes and additional gains from FA port reconfiguration compared to fixed FPAs. The approach gracefully transitions to BF-dominant performance as the array grows, highlighting NF geometry as a valuable asset for secure communications in 6G-era systems.

Abstract

With the evolution of wireless systems toward large-scale arrays and high-frequency reconfigurable architectures, fluid antenna systems (FAS) operating in the near-field (NF) regime provide new degrees of freedom (DoF) for physical layer security (PLS). This paper proposes an artificial-noise (AN)-aided PLS scheme for NF fluid-antenna multiple-input multiple-output (FA-MIMO) systems, with joint beamforming (BF) and AN design for both compact and large arrays. An alternating-optimization (AO) framework addresses the sparsity-constrained non-convex design by splitting it into a continuous BF/AN joint-design subproblem and a discrete FAS port-selection subproblem. Closed-form fully digital BF/AN solutions are obtained via a generalized spectral water-filling procedure within a block coordinate descent (BCD) surrogate and realized by a hardware-efficient hybrid beamforming (HBF) architecture that embeds AN in the baseband without extra radio-frequency (RF) chains. For FAS port selection, a row-energy based prune--refit rule, aligned with Karush--Kuhn--Tucker (KKT) conditions of a group-sparsity surrogate, enables efficient active-port determination. Simulation results confirm that the proposed design exploits the geometry and position-domain DoF of FAS and significantly improves secrecy performance, particularly for non-extremely-large arrays where NF beam focusing alone is inadequate.

Artificial Noise Aided Physical Layer Security for Near-Field MIMO with Fluid Antenna Systems

TL;DR

The paper tackles physical-layer security in near-field MIMO systems equipped with fluid antenna systems by jointly optimizing beamforming and artificial noise under a hybrid beamforming architecture. An alternating-optimization approach decomposes the problem into continuous BF/AN design and discrete port-selection subproblems, using generalized spectral water-filling and a prune–refit port-selection rule guided by group-sparsity theory. The BF/AN design achieves closed-form solutions within the AO framework and is realized with embedded AN in baseband, while the port-selection leverages row-energy cues to efficiently activate ports. Numerical results show significant secrecy gains for realistically sized FA-MIMO arrays in the NF regime, with clear advantages over BF-only schemes and additional gains from FA port reconfiguration compared to fixed FPAs. The approach gracefully transitions to BF-dominant performance as the array grows, highlighting NF geometry as a valuable asset for secure communications in 6G-era systems.

Abstract

With the evolution of wireless systems toward large-scale arrays and high-frequency reconfigurable architectures, fluid antenna systems (FAS) operating in the near-field (NF) regime provide new degrees of freedom (DoF) for physical layer security (PLS). This paper proposes an artificial-noise (AN)-aided PLS scheme for NF fluid-antenna multiple-input multiple-output (FA-MIMO) systems, with joint beamforming (BF) and AN design for both compact and large arrays. An alternating-optimization (AO) framework addresses the sparsity-constrained non-convex design by splitting it into a continuous BF/AN joint-design subproblem and a discrete FAS port-selection subproblem. Closed-form fully digital BF/AN solutions are obtained via a generalized spectral water-filling procedure within a block coordinate descent (BCD) surrogate and realized by a hardware-efficient hybrid beamforming (HBF) architecture that embeds AN in the baseband without extra radio-frequency (RF) chains. For FAS port selection, a row-energy based prune--refit rule, aligned with Karush--Kuhn--Tucker (KKT) conditions of a group-sparsity surrogate, enables efficient active-port determination. Simulation results confirm that the proposed design exploits the geometry and position-domain DoF of FAS and significantly improves secrecy performance, particularly for non-extremely-large arrays where NF beam focusing alone is inadequate.

Paper Structure

This paper contains 11 sections, 83 equations, 7 figures.

Figures (7)

  • Figure 1: Illustration of FA port array at the transmitter and FPA array at the receiver.
  • Figure 2: Illustration of FA port array at the transmitter and FPA array at the receiver.
  • Figure 3: SC for FA–MIMO with $L=64$ and $N_{\text{t}}=16$; comparison with an FPA-based BF-only baseline, with ablations over array type (FA vs. FPA), AN co-design (with/without), and implementation (DBF vs. HBF after power balancing).
  • Figure 4: SC for FA–MIMO with $L=512$ and $N_{\text{t}}=128$; comparison with an FPA-based BF-only baseline, with ablations over array type (FA vs. FPA), AN co-design (with/without), and implementation (DBF vs. HBF after power balancing).
  • Figure 5: Secrecy performance of PLS schemes with Bob fixed at $d_{\text{U}}=15\,\mathrm{m}$ and transmit power $P_\text{t}=-10\,\mathrm{dBm}$, evaluated over different distances between Alice and Eve: (a) small array ($L=64$, $N_{\text{t}}=16$); (b) large array ($L=512$, $N_{\text{t}}=128$).
  • ...and 2 more figures