Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Secure MIMO Communication Relying on Movable Antennas

Jun Tang, Cunhua Pan, Yang Zhang, Hong Ren, Kezhi Wang

TL;DR

The paper tackles securing MA-aided MIMO communications by maximizing the secrecy rate $R_S=[R_I-R_E]^+$ through joint optimization of the transmit precoder $\mathbf{V}$, AN covariance $\mathbf{V}_E$, and MA positions $\mathbf{T}$ under $P_{\max}$ and spacing constraints. It develops a block coordinate descent with majorization-minimization (BCD-MM) framework: reformulating the SR using MMSE with auxiliary variables to obtain semi-closed-form updates for $\mathbf{V}$ and $\mathbf{V}_E$, and applying MM to iteratively refine each MA position while keeping others fixed. The proposed algorithm converges monotonically to a stationary SR bound and demonstrates significant SR gains of MA-aided systems over fixed-position antenna baselines, with performance improving with larger transmission regions, more paths, and higher power. The results also reveal sensitivity to field-response information accuracy, underscoring the practical importance of precise channel knowledge for MA-enabled security gains.

Abstract

This paper considers a movable antenna (MA)-aided secure multiple-input multiple-output (MIMO) communication system consisting of a base station (BS), a legitimate information receiver (IR) and an eavesdropper (Eve), where the BS is equipped with MAs to enhance the system's physical layer security (PLS). Specifically, we aim to maximize the secrecy rate (SR) by jointly optimizing the transmit precoding (TPC) matrix, the artificial noise (AN) covariance matrix and the MAs' positions under the constraints of the maximum transmit power and the minimum distance between MAs. To solve this non-convex problem with highly coupled optimization variables, the block coordinate descent (BCD) method is applied to alternately update the variables. Specifically, we first reformulate the SR into a tractable form by utilizing the minimum mean square error (MMSE) method, and derive the optimal TPC matrix and the AN covariance matrix with fixed MAs' positions by applying the Lagrangian multiplier method in semi-closed forms. Then, the majorization-minimization (MM) algorithm is employed to iteratively optimize each MA's position while keeping others fixed. Finally, simulation results are provided to demonstrate the effectiveness of the proposed algorithms and the significant advantages of the MA-aided system over conventional fixed position antenna (FPA)-based system in enhancing system's security.

Secure MIMO Communication Relying on Movable Antennas

TL;DR

The paper tackles securing MA-aided MIMO communications by maximizing the secrecy rate through joint optimization of the transmit precoder , AN covariance , and MA positions under and spacing constraints. It develops a block coordinate descent with majorization-minimization (BCD-MM) framework: reformulating the SR using MMSE with auxiliary variables to obtain semi-closed-form updates for and , and applying MM to iteratively refine each MA position while keeping others fixed. The proposed algorithm converges monotonically to a stationary SR bound and demonstrates significant SR gains of MA-aided systems over fixed-position antenna baselines, with performance improving with larger transmission regions, more paths, and higher power. The results also reveal sensitivity to field-response information accuracy, underscoring the practical importance of precise channel knowledge for MA-enabled security gains.

Abstract

This paper considers a movable antenna (MA)-aided secure multiple-input multiple-output (MIMO) communication system consisting of a base station (BS), a legitimate information receiver (IR) and an eavesdropper (Eve), where the BS is equipped with MAs to enhance the system's physical layer security (PLS). Specifically, we aim to maximize the secrecy rate (SR) by jointly optimizing the transmit precoding (TPC) matrix, the artificial noise (AN) covariance matrix and the MAs' positions under the constraints of the maximum transmit power and the minimum distance between MAs. To solve this non-convex problem with highly coupled optimization variables, the block coordinate descent (BCD) method is applied to alternately update the variables. Specifically, we first reformulate the SR into a tractable form by utilizing the minimum mean square error (MMSE) method, and derive the optimal TPC matrix and the AN covariance matrix with fixed MAs' positions by applying the Lagrangian multiplier method in semi-closed forms. Then, the majorization-minimization (MM) algorithm is employed to iteratively optimize each MA's position while keeping others fixed. Finally, simulation results are provided to demonstrate the effectiveness of the proposed algorithms and the significant advantages of the MA-aided system over conventional fixed position antenna (FPA)-based system in enhancing system's security.
Paper Structure (19 sections, 71 equations, 10 figures, 2 algorithms)

This paper contains 19 sections, 71 equations, 10 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Channel Model
  5. Problem Formulation
  6. Proposed BCD-MM-based Algorithm
  7. Problem Reformulation
  8. Optimize ${\bf{V}}$ and ${\bf{V}}_E$
  9. Optimize ${\bf{T}}$
  10. Overall Algorithm
  11. Simulation Results
  12. Simulation Setup
  13. Convergence Behaviour of the Proposed Algorithms
  14. Baseline Schemes
  15. Performance Analysis Compared to Baseline Schemes
  16. ...and 4 more sections

Figures (10)

  • Figure 1: The MA-aided secure MIMO communication system.
  • Figure 2: The far-field-response channel model.
  • Figure 3: Convergence behaviour of the BCD algorithm.
  • Figure 4: Convergence behaviour of the MM algorithm.
  • Figure 5: SR versus the size of transmit region.
  • ...and 5 more figures