Rotatable Antenna-Enabled Wireless Communication: Modeling and Optimization

Non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. In this paper, we propose a new rotatable antenna (RA) model to improve the performance of wireless communication systems. Different from conventional fixed antennas, the proposed RA system can flexibly and independently alter the boresight direction of each antenna via mechanical or electronic means to exploit new spatial degrees-of-freedom (DoFs). Specifically, we investigate an RA-enabled uplink communication system, where the receive beamforming and the boresight directions of all RAs at the base station (BS) are jointly optimized to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all the users. In the special single-user and free-space propagation setup, the optimal boresight directions of RAs are derived in closed form with the maximum-ratio combining (MRC) beamformer applied at the BS. In the general multi-user and multipath channel setup, we first propose an alternating optimization (AO) algorithm to alternately optimize the receive beamforming and the boresight directions of RAs in an iterative manner. Then, a two-stage algorithm that solves the formulated problem without the need for iteration is proposed to further reduce computational complexity. Moreover, we extend the channel model to incorporate polarization effects and frequency-selective fading while catering to antenna boresight rotation. Simulation results are provided to validate our analytical results and demonstrate that the proposed RA system can significantly improve the communication performance as compared to other benchmark schemes.

💡 Research Summary

The paper introduces a novel rotatable antenna (RA) architecture that enables each antenna element in a base‑station array to independently adjust its boresight direction in three‑dimensional space while keeping its physical position fixed. This capability adds a new spatial degree‑of‑freedom (DoF) without the mechanical complexity of moving the antenna’s location, as required by fluid antenna systems (FAS) or movable antennas (MA). The authors model the RA’s orientation using a unit pointing vector parameterized by zenith and azimuth angles, constrained within a practical range θ_max (0 ≤ θ_z ≤ θ_max). A directional gain pattern G_e(ε,φ)=G_0·cos^{2p}(ε) is adopted, where p controls beamwidth and G_0 ensures power conservation.

A comprehensive geometric‑based channel model is derived that incorporates both path loss and the antenna’s directional gain. For each user‑RA link, line‑of‑sight (LoS) and non‑LoS components are expressed as functions of the pointing vectors, distances, and scatterer clusters. The model is later extended to include polarization effects and frequency‑selective fading.

The system under study is an uplink scenario where K single‑antenna users transmit simultaneously to a base station equipped with an N‑element uniform planar array (UPA) of RAs. The design goal is to maximize the minimum signal‑to‑interference‑plus‑noise ratio (SINR) across all users by jointly optimizing the receive beamforming matrix and the RA pointing vectors.

For the special case of a single user in free‑space propagation, the authors prove that the maximum‑ratio combining (MRC) beamformer is optimal and derive closed‑form expressions for the optimal pointing vectors. They further provide analytical SNR expressions and bounds, showing that SNR grows linearly with N until it saturates at a limit dictated by the antenna directivity p and the allowed rotation range θ_max.

In the general multi‑user, multipath setting, the problem becomes a non‑convex joint optimization. Two solution approaches are proposed:

1. Alternating Optimization (AO) – The algorithm iteratively (i) fixes the RA orientations and solves a convex receive‑beamforming problem, then (ii) fixes the beamformer and updates each RA’s pointing vector by solving a per‑antenna subproblem. Convergence is guaranteed because each step reduces the objective, and simulations show rapid convergence within a few iterations.

2. Two‑Stage Non‑Iterative Algorithm – To reduce computational load, the authors first adopt a zero‑forcing (ZF) beamformer, which decouples users. Then they solve a weighted channel‑power maximization problem to obtain the pointing vectors in closed form, eliminating the need for iteration. This method achieves performance close to AO with substantially lower complexity.

Extensive Monte‑Carlo simulations compare the RA system against benchmark schemes: fixed‑orientation antennas, FAS, and MA. Results demonstrate that even with modest rotation limits (θ_max ≈ 15°), the RA system yields 3–6 dB SINR improvement over fixed antennas, especially when the antenna directivity p is high (narrow beams). The gains persist under the extended channel model with polarization and frequency‑selective fading.

The paper concludes that rotatable antennas provide a cost‑effective, scalable means to exploit the “six‑dimensional” spatial DoF (3‑D position + 3‑D orientation) while avoiding the bulky hardware of full 6‑DMA. Future work is suggested on real‑time rotation control, multi‑cell coordination, and joint radar‑communication applications.