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Rotatable Antenna Enabled Wireless Communication and Sensing: Opportunities and Challenges

Beixiong Zheng, Tiantian Ma, Changsheng You, Jie Tang, Robert Schober, Rui Zhang

arXiv:2505.16828v3cs.IT

TL;DR

Conventional MIMO scaling can impose high hardware, deployment, and processing costs, motivating compact flexible antennas that adapt to channel conditions. This article surveys RA architectures and uses communication and sensing analyses plus experiments and simulations to evaluate boresight reconfiguration. The reported results show improved communication performance and sharper, lower-sidelobe sensing spectra, supporting RA as a flexible approach for future wireless systems.

  • Problem

    Conventional MIMO performance scaling increases hardware, deployment, and processing complexity, motivating alternatives that provide spatial flexibility within compact apertures.

  • Method

    The article surveys RA hardware and radiation-pattern characterization, explains communication and sensing mechanisms, and evaluates optimized boresight control through experiments and simulations.

  • Results

    RA maintains stable received SNR during user-angle variation, improves max-min SINR by up to 2 dB over random boresight and 3.2 dB over fixed boresight, and produces sharper sensing peaks with lower sidelobes.

  • Takeaways & Limitations

    RA’s 3D boresight adjustment provides additional spatial degrees of freedom for communication and sensing without requiring additional antenna resources or deployment space.

Abstract

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Non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. Among them, rotatable antenna (RA) is an emerging technology that offers significant potential to enhance wireless communication and sensing performance by flexibly adjusting the boresight of directional antennas. Specifically, RA can flexibly reconfigure its boresight direction via mechanical or electronic means, thereby improving communication channel conditions and/or enhancing sensing resolution and range. In this article, we first provide an overview of RA, covering its hardware architectures and radiation pattern characterization. We then illustrate how RA improves communication performance through interference mitigation, spatial multiplexing, and flexible beamforming, as well as sensing capabilities in terms of coverage, resolution, and multi-target/dimensional sensing. Furthermore, we highlight representative applications of RA and discuss key design challenges in RA systems, including rotational scanning scheduling, channel estimation/sensing, boresight optimization, and RA configuration. Finally, both experimental and simulation results are provided to validate the performance gains achieved by RA for both communication and sensing. Leveraging its unique capabilities in flexible antenna/array rotation to adapt to various communication/sensing requirements and channel conditions, RA is poised to become a key enabler of future intelligent, resilient, and agile wireless networks.

I. INTRODUCTION

RA is introduced as a compact, low-cost flexible antenna architecture that independently adjusts antenna boresights to improve communication and sensing while supporting demanding 6G requirements. The article surveys RA architectures, advantages, applications, challenges, and experimental and simulation validation.

  • 6G systems demand higher spectral efficiency and spatial resolution, but enlarging conventional MIMO arrays increases hardware cost, deployment complexity, and processing complexity.
  • RA provides additional spatial degrees of freedom while maintaining a compact aperture and low hardware cost.
  • By independently adjusting each antenna’s 3D boresight mechanically or electronically, RA enables precise beam alignment, extended coverage, and adaptive interference management.
  • Unlike earlier systems focused on whole-array orientation, the RA considered here independently adjusts boresight directions for individual antennas within an array.
  • RA supports deployment in space- and cost-constrained platforms such as IoT nodes and wearable devices.
  • The article examines RA fundamentals, hardware, performance advantages, applications, practical challenges, and validation through experiments and simulations.

II. HARDWARE ARCHITECTURE AND RADIATION PATTERN CHARACTERIZATION

RA hardware combines conventional communication components with control mechanisms that reconfigure antenna or array boresights mechanically or electronically. Its key radiation-pattern distinction from movable antennas is rotation rather than translation, with flexibility shaped by implementation trade-offs.

  • Hardware architectures: RA adds a dedicated control module to conventional communication hardware for rotating each antenna’s or antenna array’s boresight.
  • Mechanical implementations: Mechanical RA uses actuators, servomotor platforms, or MEMS structures to physically rotate antenna orientation in 3D space.
  • Electronic implementations: Electronic RA keeps antenna orientation fixed while rotating the radiation pattern through multi-feed activation or electronically tuned parasitic elements.
  • Implementation trade-offs: Mechanical methods generally provide broader boresight control, whereas electronic methods offer better compatibility with existing wireless platforms.
  • Implementation trade-offs: Co-designed mechanical-electronic architectures can combine wide-angle adjustment with rapid radiation-pattern reconfiguration.
  • Array-level rotation: Independent antenna rotation enables finer boresight control than array-level rotation but increases control overhead and design complexity.
  • Radiation-pattern characterization: MA translates an intrinsic radiation pattern by moving antenna position, while RA rotates that pattern by changing antenna or array boresight.

III. PERFORMANCE ADVANTAGES OF RA

RA’s principal performance advantages arise from reconfigurable radiation patterns that support interference mitigation, spatial multiplexing, flexible beamforming, and improved sensing capabilities.

  • RA performance advantages include interference mitigation, spatial multiplexing, flexible beamforming, sensing resolution, sensing coverage, and multi-target or dimensional sensing.

A. Wireless Communication •

RA improves wireless communication by using boresight reconfiguration to suppress interference, create more resolvable spatial channels, and jointly control antenna patterns and array weights for flexible beamforming.

  • Wireless Communication: RA uses boresight reconfigurability to mitigate interference more directly than conventional resource allocation and signal-processing techniques.
  • Wireless Communication: RA can restore spatial multiplexing opportunities when dominant LoS or reflected paths reduce effective channel rank, especially in near-field scenarios.
  • Wireless Communication: Dynamic boresight adjustment enhances angular separation among signal paths, improving spatial resolvability and enabling concurrent transmission of multiple data streams.
  • Wireless Communication: Jointly optimizing array weights and individual antenna boresights enables precise far-field beam steering and near-field beam focusing with more flexible power distribution.

B. Wireless Sensing

RA enhances wireless sensing by steering individual antenna boresights to focus energy, broaden coverage, and resolve multiple targets or target dimensions with fewer antennas.

  • Sensing resolution: RA boresight alignment combines with near-field beam focusing to concentrate energy at specific 3D points, improving directional gain and spatial resolution.Coherently directing all RAs toward a target makes the array act as a sensing spotlight.
  • Sensing coverage: RA can scan wider 3D regions over time, enabling wide-angle coverage and more reliable detection of mobile targets.Flexible redirection can also complement fixed arrays by mitigating blind spots.
  • Sensing coverage: Hybrid RA and fixed-antenna deployments combine flexible redirection with established coverage to support sensing in distributed or irregular target scenarios.The RA component helps mitigate blind spots in the fixed-antenna coverage.
  • Multi-target/dimensional sensing: Independent boresight adjustment lets RA arrays sequentially or concurrently scan multiple directions, improving separation of closely spaced targets with fewer antennas.Diverse angular observations also support extracting direction, velocity, size, and orientation.

IV. POTENTIAL APPLICATIONS OF RA

RA’s reconfigurable 3D boresight supports applications requiring flexible connectivity, coverage, localization, sensing, and spatial resource allocation across terrestrial, aerial, and space environments.

  • Machine-type communication (MTC): In MTC, RA adapts boresights to device distributions, improving spatial-DoF utilization, signal quality, and interference suppression without requiring large antenna arrays.The article presents this as a lightweight and scalable approach for dense, small-payload deployments.
  • Space-air-ground integrated network (SAGIN): For SAGIN, RA extends coverage and tracking across 3D space or enables aerial and spaceborne nodes to maintain links through flexible beam control.RA can be co-deployed at base stations or installed on aerial and spaceborne platforms.
  • Indoor sensing and localization: In indoor sensing and localization, RA redirects radiation toward reflected paths and builds channel knowledge maps for more accurate, robust environment-aware operation.The same reconfigurability supports SLAM in robotic networks.
  • Integrated sensing and communication (ISAC): For ISAC, independent 3D boresight control separates communication and sensing directions, improving angular resolution, link quality, and coverage efficiency.Antenna resources can be allocated adaptively according to user and target locations.

V. DESIGN CHALLENGES: UNLOCKING THE FULL POTENTIAL OF RA

RA introduces design challenges in coordinating rotational scans with system tasks and performance objectives, because scanning expands environmental awareness while adding overhead and latency.

  • Overall challenges: RA design must address rotational scanning scheduling, channel estimation/sensing, boresight optimization, and antenna configuration.These challenges require forward-looking solutions for practical RA-enabled communication and sensing.
  • Rotational scanning scheduling: Scanning schedules trade communication and sensing performance against system overhead while acquiring environmental information across multiple directions.The schedule therefore affects both information collection and operational cost.
  • Rotational scanning scheduling: Scanning can support wide-area sensing and tracking of highly mobile targets, but its control overhead and latency may reduce sensing accuracy and data rates.The degradation is especially relevant under dynamic channel or mobility conditions.
  • Rotational scanning scheduling: Scheduling must jointly select scanning range, frequency, and pattern while coordinating with signal-processing tasks and diverse communication, sensing, navigation, and localization requirements.These interacting requirements make scheduling inherently intricate.

B. Channel Estimation/Sensing

RA channel estimation and sensing require accurate environmental information for boresight control while exploiting adaptive scans to obtain richer spatial observations without excessive processing overhead.

  • Channel estimation and sensing: RA requires accurate CSI for effective boresight control but estimates fewer environmental parameters than FAS or MA/6DMA position optimization typically requires.RA’s orientation changes avoid reconstructing full CSI over an antenna movement region.
  • Channel estimation and sensing: Sequential or adaptive boresight scans provide multi-view observations that can improve estimation and sensing resolution.These observations are collected across changing wireless-environment viewpoints.
  • Channel estimation and sensing: Multi-view observations require more complex space-time signal processing, motivating low-overhead methods that exploit geometric knowledge and spatio-temporal correlations.Learning-based models can capture correlations across boresight directions under high-dimensional or noisy measurements.
  • Boresight direction optimization: Boresight optimization can use continuous relaxation followed by quantization, greedy search, hierarchical scanning, or learning-based methods depending on discrete levels and CSI availability.The alternatives address discrete direction constraints, imperfect CSI, and settings without explicit CSI.

D. Antenna Configuration

RA configuration must be matched to system tasks because boresight control, rotational scale, array structure, and deployment affect performance, efficiency, and integration complexity. Sparse arrays favor sensing resolution but can increase communication interference, while experiments validate RA gains in communication and sensing.

  • Configuration challenges: RA configuration choices affect control accuracy, latency, size, cost, performance, and integration complexity.These choices include boresight control methods, rotational scale, array structure, and deployment strategy.
  • Deployment constraints: Spaceborne and aerial RA deployments additionally require miniaturization and ruggedization.These requirements make configuration considerations more critical on such platforms.
  • Task-dependent configuration: Sparse RA arrays can improve sensing resolution through larger apertures and reduced coupling, but may cause severe inter-user interference in communication.The communication risk occurs when users fall into each other’s beam grating lobes.
  • Validation: RA performance advantages are evaluated through a mechanically driven single-user communication experiment and simulations of multi-user communication and multi-target sensing.The evaluation covers both practical hardware operation and simulated multi-user or multi-target scenarios.

A. Experimental Results: Single-User Communication

The results evaluate RA in practical single-user communication and simulated multi-user communication and multi-target sensing. RA maintains communication quality across user azimuths, improves multi-user SINR over fixed and random boresight schemes, and sharpens sensing peaks.

  • Single-user communication: RA dynamically tracks user azimuth through boresight adjustment, maintaining stable received SNR as the user varies from −π/3 to π/3.The experiment uses an indoor mechanically driven RA transmitter at 5.8 GHz with 16-QAM, 5.8 dBm transmit power, and 0.5 Mbps data rate.
  • Multi-user communication: The multi-user evaluation measures max-min SINR against the maximum RA zenith angle.The simulated system includes four users under multipath channels and a 4 × 4 directional-RA planar array.
  • Multi-user communication: Up to 2 dB and 3.2 dB max-min SINR improvements are achieved over random-boresight and fixed-boresight baselines, respectively.The proposed RA system outperforms both baselines across all tested maximum zenith angles.
  • Multi-user communication: Significant SINR improvement occurs even when θmax ≤π/10, showing that optimized RA can benefit from a small or moderate boresight-adjustment range.The result indicates that large rotational ranges are not required in the reported setting.
  • Multi-target sensing: Optimized RA boresight directions produce sharper target-aligned spatial-power-spectrum peaks and lower sidelobes than random or fixed boresight schemes.The reported sensing comparison involves three targets under line-of-sight channels.

VII. CONCLUSIONS

The conclusion presents RA as a compact, cost-effective way to add spatial degrees of freedom for communication and sensing without extra antenna resources or deployment space. It also points toward increasingly autonomous RAs that scan, sense, track, and learn from wireless environments.

  • Conclusions: 3D boresight adjustment enhances communication and sensing performance without additional antenna resources or extra deployment space.The conclusion frames this as a cost-effective source of additional spatial degrees of freedom.
  • Future directions: Future RAs are envisioned to automatically scan, sense, track, and learn from wireless environments.The stated evolution targets more adaptive directional and flexible communications.
  • Future directions: The envisioned evolution is intended to enhance signal strength and mitigate interference for more agile, efficient, and intelligent wireless networks.This consequence is stated in the conclusion as a direction for future RA-enabled communications.
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