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Movable Antenna Enhanced Integrated Sensing and Communication Via Antenna Position Optimization

Wenyan Ma, Lipeng Zhu, Rui Zhang

TL;DR

This work studies movable-antenna (MA) aided ISAC systems, introducing a two-timescale design that optimizes antenna positions $\tilde{\bm{r}}$ using statistical CSI while adapting precoding to instantaneous channels. It derives Cramer-Rao bounds for AoA sensing as functions of MA positions and formulates a nonconvex joint optimization to maximize the expected minimum user rate under sensing-CRB constraints, solved via an alternating optimization with zero-forcing precoding. The proposed algorithm demonstrates that MA arrays can substantially enlarge the communication-sensing trade-off region and reduce steering-vector correlation compared to fixed-position arrays, with sensing performance (AoA MSE) approaching the CRB. The approach offers a practical path to dynamic, high-resolution ISAC by exploiting the additional degree of freedom provided by movable antennas, while keeping antenna movements manageable on larger timescales. The results suggest significant potential for MA-aided ISAC in dense multiuser scenarios and time-varying environments.

Abstract

In this paper, we propose an integrated sensing and communication (ISAC) system aided by the movable-antenna (MA) array, which can improve the communication and sensing performance via flexible antenna movement over conventional fixed-position antenna (FPA) array. First, we consider the downlink multiuser communication, where each user is randomly distributed within a given three-dimensional zone with local movement. To reduce the overhead of frequent antenna movement, the antenna position vector (APV) is designed based on users' statistical channel state information (CSI), so that the antennas only need to be moved in a large timescale. Then, for target sensing, the Cramer-Rao bounds (CRBs) of the estimation mean square error for different spatial angles of arrival (AoAs) are derived as functions of MAs' positions. Based on the above, we formulate an optimization problem to maximize the expected minimum achievable rate among all communication users, with given constraints on the maximum acceptable CRB thresholds for target sensing. An alternating optimization algorithm is proposed to iteratively optimize one of the horizontal and vertical APVs of the MA array with the other being fixed. Numerical results demonstrate that our proposed MA arrays can significantly enlarge the trade-off region between communication and sensing performance compared to conventional FPA arrays with different inter-antenna spacing. It is also revealed that the steering vectors of the designed MA arrays exhibit low correlation in the angular domain, thus effectively reducing channel correlation among communication users to enhance their achievable rates, while alleviating ambiguity in target angle estimation to achieve improved sensing accuracy.

Movable Antenna Enhanced Integrated Sensing and Communication Via Antenna Position Optimization

TL;DR

This work studies movable-antenna (MA) aided ISAC systems, introducing a two-timescale design that optimizes antenna positions using statistical CSI while adapting precoding to instantaneous channels. It derives Cramer-Rao bounds for AoA sensing as functions of MA positions and formulates a nonconvex joint optimization to maximize the expected minimum user rate under sensing-CRB constraints, solved via an alternating optimization with zero-forcing precoding. The proposed algorithm demonstrates that MA arrays can substantially enlarge the communication-sensing trade-off region and reduce steering-vector correlation compared to fixed-position arrays, with sensing performance (AoA MSE) approaching the CRB. The approach offers a practical path to dynamic, high-resolution ISAC by exploiting the additional degree of freedom provided by movable antennas, while keeping antenna movements manageable on larger timescales. The results suggest significant potential for MA-aided ISAC in dense multiuser scenarios and time-varying environments.

Abstract

In this paper, we propose an integrated sensing and communication (ISAC) system aided by the movable-antenna (MA) array, which can improve the communication and sensing performance via flexible antenna movement over conventional fixed-position antenna (FPA) array. First, we consider the downlink multiuser communication, where each user is randomly distributed within a given three-dimensional zone with local movement. To reduce the overhead of frequent antenna movement, the antenna position vector (APV) is designed based on users' statistical channel state information (CSI), so that the antennas only need to be moved in a large timescale. Then, for target sensing, the Cramer-Rao bounds (CRBs) of the estimation mean square error for different spatial angles of arrival (AoAs) are derived as functions of MAs' positions. Based on the above, we formulate an optimization problem to maximize the expected minimum achievable rate among all communication users, with given constraints on the maximum acceptable CRB thresholds for target sensing. An alternating optimization algorithm is proposed to iteratively optimize one of the horizontal and vertical APVs of the MA array with the other being fixed. Numerical results demonstrate that our proposed MA arrays can significantly enlarge the trade-off region between communication and sensing performance compared to conventional FPA arrays with different inter-antenna spacing. It is also revealed that the steering vectors of the designed MA arrays exhibit low correlation in the angular domain, thus effectively reducing channel correlation among communication users to enhance their achievable rates, while alleviating ambiguity in target angle estimation to achieve improved sensing accuracy.
Paper Structure (15 sections, 2 theorems, 71 equations, 9 figures, 2 algorithms)

This paper contains 15 sections, 2 theorems, 71 equations, 9 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Communication Subsystem
  4. Sensing Subsystem
  5. Problem Formulation
  6. Proposed Algorithm
  7. Optimization of $\bm{y}$ with Given $\bm{z}$
  8. Optimization of $\bm{z}$ with Given $\bm{y}$
  9. Overall Algorithm
  10. Initialization
  11. Upper-bound of $\tilde{R}(\tilde{\bm{r}})$ and Lower-bound of $\eta$
  12. Numerical Results
  13. Conclusions
  14. Proof of Theorem 1
  15. Proof of Theorem 2

Key Result

Theorem 1

The MLE of the two spatial AoAs is given by which can be solved by exhaustively searching for $\bar{\bm{\chi}}=[\bar{u},\bar{v}]^{\mathsf T}$ over the interval $[-1,1]\times[-1,1]$.

Figures (9)

  • Figure 1: The considered MA-aided ISAC system.
  • Figure 2: Illustration of the considered communication user zones.
  • Figure 3: Convergence behavior of Algorithm \ref{['alg2']}.
  • Figure 4: Illustration of the MAs’ positions for different CRB thresholds.
  • Figure 5: Comparison of minimum achievable rate--reciprocal of CRB threshold region for different schemes.
  • ...and 4 more figures

Theorems & Definitions (4)

  • Theorem 1
  • proof
  • Theorem 2
  • proof