Rotatable Antennas for Integrated Sensing and Communications

2025-03-13

AI Summary

To address the challenge of jointly enhancing communication rate and target angle estimation accuracy in Integrated Sensing and Communication (ISAC) systems, this paper introduces, for the first time, physical rotation of the base station antenna array as a controllable degree of freedom. We propose a multi-objective optimization framework jointly designing beamforming and array rotation angle. By modeling the equivalent aperture extension effect and rotation-induced gain arising from antenna rotation, we formulate an optimization problem that minimizes the Cramér–Rao Bound (CRB) for angle estimation while maximizing the multi-user sum rate. The problem is solved via a block coordinate descent algorithm combined with one-dimensional search. Experimental results demonstrate that, compared to fixed-antenna baselines, the proposed method significantly improves both sum rate and angle estimation accuracy in joint sensing-communication scenarios. Furthermore, ablation studies in pure communication and pure sensing sub-scenarios separately validate the effectiveness of rotation gain and equivalent aperture extension.

Technology Category

Search and Optimization: Mixed Discrete/Continuous SearchIntelligent Robots: Learning & Optimization for ROBPlanning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applicationsSecurity and Privacy: Large-scale security measurementsUser Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

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 Cram'er-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).

Problem

• Enhance communication and sensing using rotatable antennas.
• Optimize beamforming and rotation for multi-objective performance.
• Improve sensing accuracy and communication rate with spatial DoF.

Innovation

• Rotatable antennas enhance communication and sensing.
• Multi-objective optimization maximizes sum-rate and minimizes CRB.
• Block coordinate descent solves non-convex subproblems effectively.