Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Rotatable Antennas for Integrated Sensing and Communications

Chao Zhou, Changsheng You, Beixiong Zheng, Xiaodan Shao, Rui Zhang

TL;DR

This work introduces rotatable antennas (RAs) at the base station to expand the spatial DoF for integrated sensing and communications (ISAC). By jointly optimizing transmit beamforming and the array rotation angle, the authors formulate a multi-objective problem balancing sum-rate and target-angle CRB, and solve it via a two-stage approach using block coordinate descent for beamforming and 1D exhaustive search for rotation. They show that RA rotation provides benefits beyond fixed antennas in both communication and sensing: it enhances the downlink SNR in the communication-only case and enlarges the effective spatial aperture in the sensing-only case, thereby improving CRB. Numerical results corroborate significant performance gains of the RA-enabled ISAC system over fixed-rotation setups, validating the proposed design and its practical potential.

Abstract

In this letter, we propose to deploy rotatable antennas (RAs) at the base station (BS) to enhance both communication and sensing (C&S) performances, by exploiting a new spatial degree-of-freedom (DoF) offered by array rotation. Specifically, we formulate a multi-objective optimization problem to simultaneously maximize the sum-rate of multiple communication users and minimize the Cramér-Rao bound (CRB) for target angle estimation, by jointly optimizing the transmit beamforming vectors and the array rotation angle at the BS. To solve this problem, we first equivalently decompose it into two subproblems, corresponding to an inner problem for beamforming optimization and an outer problem for array rotation optimization. Although these two subproblems are non-convex, we obtain their high-quality solutions by applying the block coordinate descent (BCD) technique and one-dimensional exhaustive search, respectively. Moreover, we show that for the communication-only case, RAs provide an additional rotation gain to improve communication performance; while for the sensing-only case, the equivalent spatial aperture can be enlarged by RAs for achieving higher sensing accuracy. Finally, numerical results are presented to showcase the performance gains of RAs over fixed-rotation antennas in integrated sensing and communications (ISAC).

Rotatable Antennas for Integrated Sensing and Communications

TL;DR

This work introduces rotatable antennas (RAs) at the base station to expand the spatial DoF for integrated sensing and communications (ISAC). By jointly optimizing transmit beamforming and the array rotation angle, the authors formulate a multi-objective problem balancing sum-rate and target-angle CRB, and solve it via a two-stage approach using block coordinate descent for beamforming and 1D exhaustive search for rotation. They show that RA rotation provides benefits beyond fixed antennas in both communication and sensing: it enhances the downlink SNR in the communication-only case and enlarges the effective spatial aperture in the sensing-only case, thereby improving CRB. Numerical results corroborate significant performance gains of the RA-enabled ISAC system over fixed-rotation setups, validating the proposed design and its practical potential.

Abstract

In this letter, we propose to deploy rotatable antennas (RAs) at the base station (BS) to enhance both communication and sensing (C&S) performances, by exploiting a new spatial degree-of-freedom (DoF) offered by array rotation. Specifically, we formulate a multi-objective optimization problem to simultaneously maximize the sum-rate of multiple communication users and minimize the Cramér-Rao bound (CRB) for target angle estimation, by jointly optimizing the transmit beamforming vectors and the array rotation angle at the BS. To solve this problem, we first equivalently decompose it into two subproblems, corresponding to an inner problem for beamforming optimization and an outer problem for array rotation optimization. Although these two subproblems are non-convex, we obtain their high-quality solutions by applying the block coordinate descent (BCD) technique and one-dimensional exhaustive search, respectively. Moreover, we show that for the communication-only case, RAs provide an additional rotation gain to improve communication performance; while for the sensing-only case, the equivalent spatial aperture can be enlarged by RAs for achieving higher sensing accuracy. Finally, numerical results are presented to showcase the performance gains of RAs over fixed-rotation antennas in integrated sensing and communications (ISAC).

Paper Structure

This paper contains 11 sections, 1 theorem, 21 equations, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. Model for Communication Users
  4. Model for Target Sensing
  5. Performance Metrics
  6. Problem Formulation and Proposed Solution
  7. Problem Formulation
  8. Proposed Solutions to Problems (P2) and (P3)
  9. Discussions
  10. Numerical Results
  11. Conclusions

Key Result

Lemma 1

Under the uniform linear array model of Sum_dis_tr, the CRB for target angle estimation $\tilde{\theta}$ can be rewritten as where $\chi = \frac{ 3 \lambda^2 ( M_{\rm r}-1)}{2 \pi^2 T \text{SNR}_{\rm s} M_{\rm r} (M_{\rm r} + 1) D_{\rm r}^2 }$, with $D_{\rm r} = (M_{\rm r} - 1)d$ representing the aperture of the receive array.

Figures (3)

  • Figure 1: The schematic of RA-enabled ISAC systems.
  • Figure 2: Normalized beamforming gain for different cases.
  • Figure 3: Achievable C&S performances for different schemes.

Theorems & Definitions (3)

  • Lemma 1
  • proof
  • Definition 1: Rotation Gain