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Movable Antenna Empowered Covert Dual-Functional Radar-Communication

Ran Yang, Ning Wei, Zheng Dong, Lin Zhang, Wanting Lyu, Yue Xiu, Ahmad Bazzi, Chadi Assi

TL;DR

This paper studies a secured dual-functional radar-communication system aided by movable antennas, and develops a minimum mean square error (MMSE)-based algorithm to address the colluding detection problem.

Abstract

Movable antenna (MA) has emerged as a promising technology to flexibly reconfigure wireless channels by adjusting antenna placement. In this paper, we study a secured dual-functional radar-communication (DFRC) system aided by movable antennas. To enhance the communication security, we aim to maximize the achievable sum rate by jointly optimizing the transmitter beamforming vectors, receiving filter, and antenna placement, subject to radar signal-to-noise ratio (SINR) and transmission covertness constraints. We consider multiple Willies operating in both non-colluding and colluding modes. For noncolluding Willies, we first employ a Lagrangian dual transformation procedure to reformulate the challenging optimization problem into a more tractable form. Subsequently, we develop an efficient block coordinate descent (BCD) algorithm that integrates semidefinite relaxation (SDR), projected gradient descent (PGD), Dinkelbach transformation, and successive convex approximation (SCA) techniques to tackle the resulting problem. For colluding Willies, we first derive the minimum detection error probability (DEP) by characterizing the optimal detection statistic, which is proven to follow the generalized Erlang distribution. Then, we develop a minimum mean square error (MMSE)-based algorithm to address the colluding detection problem. We further provide a comprehensive complexity analysis on the unified design framework. Simulation results demonstrate that the proposed method can significantly improve the covert sum rate, and achieve a superior balance between communication and radar performance compared with existing benchmark schemes.

Movable Antenna Empowered Covert Dual-Functional Radar-Communication

TL;DR

This paper studies a secured dual-functional radar-communication system aided by movable antennas, and develops a minimum mean square error (MMSE)-based algorithm to address the colluding detection problem.

Abstract

Movable antenna (MA) has emerged as a promising technology to flexibly reconfigure wireless channels by adjusting antenna placement. In this paper, we study a secured dual-functional radar-communication (DFRC) system aided by movable antennas. To enhance the communication security, we aim to maximize the achievable sum rate by jointly optimizing the transmitter beamforming vectors, receiving filter, and antenna placement, subject to radar signal-to-noise ratio (SINR) and transmission covertness constraints. We consider multiple Willies operating in both non-colluding and colluding modes. For noncolluding Willies, we first employ a Lagrangian dual transformation procedure to reformulate the challenging optimization problem into a more tractable form. Subsequently, we develop an efficient block coordinate descent (BCD) algorithm that integrates semidefinite relaxation (SDR), projected gradient descent (PGD), Dinkelbach transformation, and successive convex approximation (SCA) techniques to tackle the resulting problem. For colluding Willies, we first derive the minimum detection error probability (DEP) by characterizing the optimal detection statistic, which is proven to follow the generalized Erlang distribution. Then, we develop a minimum mean square error (MMSE)-based algorithm to address the colluding detection problem. We further provide a comprehensive complexity analysis on the unified design framework. Simulation results demonstrate that the proposed method can significantly improve the covert sum rate, and achieve a superior balance between communication and radar performance compared with existing benchmark schemes.
Paper Structure (26 sections, 69 equations, 8 figures, 1 table, 2 algorithms)

This paper contains 26 sections, 69 equations, 8 figures, 1 table, 2 algorithms.

Figures (8)

  • Figure 1: The MA-enhanced DFRC system.
  • Figure 2: Convergence behaviour.
  • Figure 3: The covert sum rate versus transmission power $P_t$.
  • Figure 4: The covert sum rate versus radar SINR $\Gamma$.
  • Figure 5: The covert sum rate versus covertness level $\epsilon$.
  • ...and 3 more figures