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A Survey on Reconfigurable and Movable Antennas for Wireless Communications and Sensing

Wenyan Ma, Lipeng Zhu, Yanhua Tan, Beixiong Zheng, Yujie Zhang, Yuchen Zhang, Keke Ying, Zhen Gao, He Sun, Xiaodan Shao, Zhenyu Xiao, Dusit Niyato, Rui Zhang

arXiv:2602.17977v1eess.SP

TL;DR

Conventional large-array wireless systems face overhead, energy, and hardware challenges, while fixed antennas cannot fully adapt to dynamic environments and diverse functions. This survey synthesizes RA and MA/6DMA fundamentals, architectures, applications, performance comparisons, and research directions, showing complementary benefits across communication and sensing settings.

  • Problem

    Large-array systems face signal-processing, energy, hardware-complexity, and cost challenges, motivating more adaptable antenna technologies.

  • Method

    The paper provides a unified survey of RA and MA/6DMA history, hardware architectures, communication and sensing applications, numerical comparisons, challenges, and future directions.

  • Results

    MRA combines MA’s large aperture with RA’s directional focusing and achieves the best performance near the evaluated directions in the reported AoA-estimation comparison.

  • Takeaways & Limitations

    RA and MA/6DMA provide complementary ways to add optimization degrees of freedom through radiation reconfiguration and antenna movement.

Abstract

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Reconfigurable antennas (RAs) and movable antennas (MAs) have been recognized as promising technologies to enhance the performance of wireless communication and sensing systems by introducing additional degrees of freedom (DoFs) in tuning antenna radiation and/or placement. This paradigm shift from conventional non-reconfigurable/movable antennas offers tremendous new opportunities for realizing multi-functional, more adaptive, and efficient next-generation wireless networks. In this paper, we provide a comprehensive survey on the fundamentals, architectures, and applications of these two emerging antenna technologies. First, we provide a chronological overview of the parallel historical development of both RA and MA technologies. Next, we review and classify the state-of-the-art hardware architectures for implementing RAs and MAs, followed by a detailed comparison of their distinct mechanisms, performance metrics, and functionalities. Subsequently, we focus on various applications of RAs and MAs in wireless communication systems, analyzing their respective performance advantages and key design considerations such as mode selection, movement optimization, and channel acquisition. We also explore the significant roles of RAs and MAs in advancing wireless sensing and integrated sensing and communication (ISAC). Furthermore, we present numerical performance comparisons to illustrate the distinct characteristics and complementary advantages of RA and MA systems. Finally, we outline key challenges and identify promising future research directions to inspire further innovations in this burgeoning field.

I. INTRODUCTION

Future wireless systems need greater spatial-domain exploitation, but large arrays intensify signal-processing, energy, hardware, and cost challenges. RAs adapt internal antenna characteristics, whereas MAs adapt external properties such as position, creating additional optimization degrees of freedom.

  • A. Background: XL-MIMO can counteract high-frequency path loss and form ultra-narrow beams, but it intensifies system-level challenges.The identified challenges include signal-processing overhead, energy consumption, and hardware complexity.
  • A. Background: Large-array systems require substantial CSI acquisition, pilot signaling, and high-dimensional resource allocation, which can reduce spectral efficiency.Pilot contamination in multi-cell systems further hinders performance gains and interference mitigation.
  • A. Background: Increasing active antennas raises RF-front-end power and baseband-processing energy, while dense integrations increase calibration, mutual-coupling, and manufacturing challenges.Fully digital systems typically require a dedicated RF chain for each antenna, and cumulative hardware costs can become prohibitive.
  • B. Emerging Antenna Techniques and Motivation: Existing antenna-selection strategies reduce active-antenna count and associated costs but retain fixed structures that cannot fully adapt to dynamic environments or diverse functions.This limitation motivates more adaptable antenna technologies.
  • C. Introduction of RA and MA: RAs dynamically alter internal antenna characteristics through switching, mechanical adjustment, or tunable materials, including frequency, radiation-pattern, and polarization reconfiguration.These capabilities support multi-standard operation, beam adaptation, and polarization mismatch mitigation.
  • C. Introduction of RA and MA: MAs dynamically alter external properties such as antenna position and orientation, while RAs can provide diverse functions with potentially lower hardware complexity, cost, and power than large phased arrays.Three-dimensional position and orientation adjustment is also termed six-dimensional MA (6DMA).

D. Contribution and Organization

The paper unifies RA and MA/6DMA in a comprehensive survey spanning their history, architectures, applications, comparisons, and future directions. It organizes these topics across communication, sensing, and ISAC perspectives.

  • D. Contribution and Organization: The survey unifies RA and MA/6DMA because both reshape wireless channels in the electromagnetic domain.It covers their fundamentals, architectures, applications, and comparison within one framework.
  • D. Contribution and Organization: It traces the parallel historical development of RA and MA/6DMA across antenna architecture, communication, and sensing communities.
  • D. Contribution and Organization: It reviews and classifies element-level and array-level hardware architectures, comparing their mechanisms, performance metrics, and functionalities.
  • D. Contribution and Organization: It analyzes communication applications, performance advantages, and design considerations including mode selection, movement optimization, and channel acquisition.
  • D. Contribution and Organization: It examines RA and MA/6DMA roles in wireless sensing and ISAC, including their benefits and design trade-offs.
  • D. Contribution and Organization: It presents numerical comparisons, then identifies challenges and future research directions for communication and sensing systems.The paper is organized around architectures, communications, sensing and ISAC, and future research.

E. Historical Development

RA and MA technologies developed through parallel but distinct historical paths, from mechanically adjusted antennas and movable platforms to electronically tunable, fluidic, pinching, and rotatable implementations. Their modern convergence reflects growing use of internal reconfiguration and physical movement to add wireless-system degrees of freedom.

  • E. Historical Development: Modern RAs trace back to mechanically adjustable antennas in the 1930s, while electronic control expanded in the mid-1990s through PIN and varactor diodes.MEMS and tunable materials later enabled more precise frequency and radiation-pattern control.
  • E. Historical Development: RA development broadened from frequency tuning to radiation and polarization reconfiguration, supporting radar, MIMO, interference reduction, and cognitive-radio applications.
  • E. Historical Development: MA precursors include mechanical signaling and movable directional antennas, followed by theoretical optimization of multi-antenna capacity through antenna-location variation in 2000.
  • E. Historical Development: The MA lineage includes the formal movable-antenna concept, fluid antennas, and a 2009 study of spatial diversity for a single receive MA.
  • E. Historical Development: Recent variants include rotatable antennas, which fix position while varying boresight, and pinching antennas, which radiate from arbitrary points along dielectric waveguides.Pinching antennas have been applied to SISO, NOMA, and MISO communication scenarios since 2024.
  • E. Historical Development: RA and MA technologies add degrees of freedom by changing internal radiation characteristics or external antenna properties, and can be used jointly or individually across communication and sensing scenarios.RA systems can electronically steer beams or change polarization, whereas MA systems can physically reposition or reorient antennas.

2) Optical Communications:

RAs and MAs provide adaptable optical, acoustic, radar, imaging, and sensing capabilities by tuning radiation or antenna placement. Their architectures span frequency, pattern, polarization, and compound reconfiguration, implemented through devices and materials with different performance trade-offs.

  • 2) Optical Communications:: RA beam steering and MA position or orientation adjustment can improve FSO alignment, link stability, pointing error, and throughput under turbulence, sway, or vibration.RA provides faster beam steering, while MA adjusts the optical transceiver position or orientation.
  • 2) Optical Communications:: RA tunable beam patterns or frequencies and MA spatial positioning can mitigate underwater acoustic multipath fading and improve SNR.These capabilities address severe multipath propagation, limited bandwidth, and slow sound speed in underwater or through-medium acoustic communication.
  • 4) Radar:: MA arrays can synthesize a larger virtual aperture without increasing antenna count, enhancing radar angular resolution and target detection while enabling clutter and interference suppression.RA adapts beam shapes, whereas MA dynamically reconfigures array geometry; MA also supports flexible sensing–communication trade-offs in ISAC.
  • 5) Imaging:: RA electronic scanning and MA sparse-array repositioning can provide high-resolution microwave or mmWave imaging over wide areas with fewer antennas than dense fixed arrays.MA optimizes antenna positions for specific imaging tasks, while RA adapts beams or patterns.
  • 6) Sensors:: In wireless sensor networks, RA adapts communication patterns and MA repositions nodes to improve links, sensing coverage, source-localization geometries, or environmental field mapping.These capabilities address fixed sensor placements that may be suboptimal for communication or sensing in dynamic environments.
  • 1) Reconfigurable Antenna-Element:: RAs are classified as pattern-, frequency-, or polarization-RAs, with representative capabilities including 3D beamforming, continuous frequency tuning, and multi-polarization generation.The survey also discusses compound reconfiguration, which jointly adjusts multiple antenna properties such as frequency and pattern or pattern and polarization.
  • 1) Reconfigurable Antenna-Element:: Frequency-RAs typically tune resonant dimensions using liquid metal, liquid crystal, PIN diodes, or varactors, with common designs allowing up to 50% tuning and one reported design reaching 83%.The 83% tuning range is achieved by switching between planar inverted-F antenna and patch modes.
  • 1) Reconfigurable Antenna-Element:: RA implementation methods include semiconductor diodes, liquid metal, MEMS, reconfigurable apertures, origami, phase-change materials, and shape-memory alloys, each presenting distinct integration, speed, loss, or frequency-band trade-offs.Liquid metal offers high conductivity and low insertion loss at mmWave and THz frequencies but requires complex microfluidics and may move slowly; PIN diodes switch within several nanoseconds.

2) Reconfigurable Antenna-Array:

RA arrays provide multiple reconfiguration strategies for controlling radiation with different trade-offs among performance, complexity, power, and implementation cost. The survey classifies these architectures and highlights challenges in balancing fine-grained control with practical scalability.

  • Classification: RA arrays include independently reconfigurable elements and grouped configurations, trading fine-grained radiation control against control complexity and power consumption.Partitioning elements into subarrays reduces hardware and power requirements but limits reconfiguration precision.
  • Reconfigurable Methods: Antenna selection activates a channel-dependent subset of antennas, reducing RF-chain count and power consumption while retaining much of large-array performance.It requires fast adaptive switching and provides less beamforming gain than full-array control.
  • Reconfigurable Methods: Analog, digital, and hybrid beamforming reshape radiation patterns with distinct trade-offs among performance, flexibility, energy efficiency, and implementation complexity.Analog beamforming uses RF phase shifters and variable-gain amplifiers, whereas hybrid beamforming balances performance and cost through analog and digital resources.
  • Reconfigurable Methods: IRS dynamically tunes passive reflecting elements to reshape wireless channels, while DMA uses waveguide-fed tunable metamaterial elements to support many antennas with fewer RF chains.DMA can reduce hardware cost, power consumption, and system complexity relative to conventional architectures.
  • Design Challenges and Possible Solutions: Advanced RA architectures face practical barriers including accurate channel estimation, hardware scalability, mutual coupling, and near-field modeling.These challenges motivate integrated strategies that combine complementary RA technologies for flexible and efficient wireless networks.

B. MA Architectures

MA/6DMA hardware architectures determine how antenna positions or orientations are physically altered to adapt to wireless environments. They are broadly distinguished by whether individual elements or entire arrays and subarrays move.

  • MA Architectures: MA/6DMA implementations are categorized by movement of individual antenna elements versus movement of complete arrays or subarrays.Each category uses distinct mechanical strategies to provide spatial adaptability.

1) Movable Antenna-Element:

Movable antennas provide spatial degrees of freedom through element translation, orientation, and array-level movement. The survey reviews mechanical, liquid, pinching, deployable, and subarray-based implementations alongside their practical constraints.

  • Classification: Movable antenna elements provide translation and orientation degrees of freedom for adapting phase-center position, directional gain, or polarization alignment.Translation can occur along 1D, 2D, or 3D paths, while orientation can involve one or multiple rotation axes.
  • Implementation Methods: Mechanical element movement uses motors, gears, shafts, or linear actuators, with typical response times ranging from milliseconds to seconds.MEMS offers a more compact and potentially faster mechanical implementation.
  • Implementation Methods: Liquid-based methods move conductive or dielectric fluids through confined channels using syringes, pumps, or electrowetting.Fluid selection must satisfy electrical, physical, chemical, safety, and stability requirements.
  • Implementation Methods: Pinching antennas create a movable radiation point by bringing a separate dielectric material near an RF-fed waveguide at a selected location.This changes the radiating point without physically moving the entire antenna structure.
  • Design Challenges and Possible Solutions: Mechanically movable elements face actuator, maintenance, RF-connection, coupling, energy-efficiency, and repositioning-latency constraints.Liquid-based elements additionally require suitable electromagnetic properties and controlled fluid motion.
  • Movable Antenna-Array: Arrays of individually movable elements maximize geometric degrees of freedom, whereas movable subarrays are more constrained but often mechanically feasible.Moving subarrays changes inter-subarray distances, baseline, sparsity, effective aperture, and beamforming characteristics.
  • Implementation Methods: Sliding and rotatable arrays alter geometry or pointing direction, with rotatable arrays supporting yaw, pitch, and roll adjustments toward user clusters.Inflatable and foldable arrays trade deployable aperture for stowage or motion constraints.

C. Comparison of RA and MA

RA and MA/6DMA add degrees of freedom through different mechanisms: RAs alter internal electromagnetic behavior, whereas MAs change physical position or orientation. Their complementary speed, range, and adaptation properties motivate hybrid architectures.

  • Mechanisms and Metrics: RA adapts internal operational characteristics, while MA/6DMA changes external spatial properties through physical position or orientation.Their performance metrics therefore emphasize electromagnetic adaptability for RA and displacement capabilities for MA/6DMA.
  • Functionality Comparison: RA typically reconfigures electronically faster than 6DMA rotates mechanically, whereas 6DMA can provide a wider continuous 3D angular range.An RA electronically tilts its beam; a 6DMA physically rotates its structure to produce a similar directional effect.
  • Functionality Comparison: RA can shift its effective radiating center electronically, while MA physically translates elements through continuous or finely discretized movement regions.These mechanisms can produce related spatial effects despite differing physical realizations.
  • System-Level Benefits: Both technologies target improved communication capacity, reliability, coverage, interference mitigation, sensing accuracy, resolution, and detection probability.RA adapts electromagnetic response, whereas MA/6DMA seeks favorable channel conditions through translation or orientation.
  • Future Directions: Hybrid architectures could combine RA’s rapid fine-grained channel adaptation with MA’s large-scale spatial optimization.The proposed division is electronic adaptation for short-term conditions and physical movement for longer-term channel improvement.

III. RA AND MA FOR WIRELESS COMMUNICATIONS

RAs improve wireless communication by dynamically tuning radiation pattern, frequency, and polarization, while MAs add spatial degrees of freedom through antenna movement. The surveyed systems require corresponding mode-selection and channel-estimation methods to exploit these benefits.

  • RAs dynamically adjust radiation pattern, operating frequency, and polarization to improve spectral efficiency, energy efficiency, spectrum utilization, link reliability, and data rate.
  • Pattern-RAs: Pattern-RAs enhance mMIMO spectral efficiency by optimizing radiation-pattern combinations within hybrid analog/digital architectures.
  • Pattern-RAs: Pattern-reconfigurable mMIMO consistently achieves higher spectral efficiency than traditional mMIMO across different numbers of user equipments.
  • Frequency-RAs: Frequency-RAs dynamically change resonant frequency to support multiple services, improve spectrum utilization, enable carrier aggregation, and facilitate channel randomization.
  • Polarization-RAs: Polarization-RAs provide polarization diversity and additional throughput using a single adjustable-polarization antenna, reducing system size for constrained devices.
  • Optimization and channel acquisition: RA optimization includes discrete pattern selection and continuous pattern design, while pattern-RA channel estimation must address multiple channel states and pilot overhead.

4) Extension to IRS-aided Wireless Communications:

IRS extends antenna reconfiguration from device-level EM control to environment-level programmability, complementing RA and MA mechanisms. The resulting systems introduce additional channel-estimation, deployment, and joint-optimization requirements.

  • Active RAs are constrained by localized hardware adaptability, intrinsic reconfiguration range, physical placement, dense-multipath coverage, and rapid-pattern energy consumption.
  • IRS uses digitally controlled passive elements to manipulate reflected waves, providing an energy-efficient complement to RA-based transceivers.
  • IRS channel acquisition: Passive IRSs cannot directly sense the wireless environment, making CSI acquisition difficult and motivating active sensors, designed pilots, element grouping, compressed sensing, and codebook feedback.
  • IRS deployment: Mobile IRS deployments address rapid environmental changes but require joint trajectory and reflection optimization.
  • IRS deployment: Single-IRS deployments face limited reflection coverage, blockage susceptibility, constrained beamforming gains, and low spatial multiplexing.
  • RA–IRS integration: RA–IRS integration combines internal antenna adjustment with external propagation control, but accurate cascaded channel estimation and practical beamforming remain challenges.
  • Movable antennas: MAs exploit spatial channel variations by repositioning antennas to align multipath phases, enhance received power, or suppress interference.
  • Movable antennas: MA arrays can reshape geometry for beam nulling, multi-beam forming, wide-beam coverage, and improved received power under LoS and NLoS conditions.

3) Channel Acquisition:

MA channel acquisition constructs channel information across antenna movement regions using model-based or model-free methods, with optimization choices tied to CSI type and movement overhead. Comparative results show complementary RA–MA advantages across SNR and user angular separation.

  • Channel Acquisition: MA channel acquisition requires instantaneous or statistical CSI across transmitter and receiver movement regions, forming a channel map over those regions.
  • Channel Acquisition: Model-based acquisition estimates wave vectors and path response matrices from limited measurements by exploiting angular sparsity and compressed sensing.
  • Channel Acquisition: Model-free acquisition samples channels at discrete positions and interpolates or predicts unmeasured locations without assuming a predefined channel structure.
  • Channel Acquisition: Sub-wavelength spatial sampling makes model-free measurement overhead scale with the movement region’s size and dimensionality.
  • Movement Optimization: Movement optimization uses acquired CSI to maximize received SNR, mitigate interference, enhance MIMO capacity, or improve beam flexibility, while balancing estimation, computation, and repositioning costs.
  • Performance Comparison: MA, RA, and MRA systems substantially outperform FPA systems in the evaluated MIMO capacity comparison.
  • Performance Comparison: MRA exceeds MA at low SNR, whereas MA exceeds RA and MRA at high SNR because radiation-pattern control favors beamforming while position optimization exploits multipath decorrelation.
  • Performance Comparison: In multiuser systems, MA and RA outperform FPA; MA is stronger at small angular spans, while RA becomes more effective as user channels become less correlated.

IV. RA AND MA FOR WIRELESS SENSING AND ISAC

RAs and IRSs extend wireless sensing and ISAC by controlling antenna EM properties or the propagation environment. The survey covers RA sensing architectures, IRS-assisted sensing paradigms, and associated scope boundaries.

  • RAs add sensing degrees of freedom by dynamically adjusting EM properties, allowing a single antenna to perform functions such as angle-of-arrival estimation.
  • RA-based sensing architectures: Pattern-RAs use tunable passive parasitic elements around an active radiator to steer beams and support frequency-independent angle-of-arrival estimation.
  • RA-based sensing architectures: Leaky-wave antennas steer beams through frequency-dependent wave leakage, mapping signal frequencies to angles for continuous frequency scanning and higher angular resolution.
  • RA-based sensing architectures: Sectorized antennas selectively receive predefined spatial sectors while attenuating out-of-sector signals, whereas switched-beam antennas are excluded because they lack EM-domain reconfigurability.
  • IRS-aided sensing and ISAC: IRS can create virtual line-of-sight paths and manipulate reflections to address blockage, path loss, and coverage limitations in wireless sensing and ISAC.
  • IRS-aided sensing: IRS-assisted radar sensing can phase-align reflected echoes to enhance received radar power and establish virtual links for blind-spot detection.
  • IRS-aided sensing: Target-mounted IRS addresses limited radar cross-section by enabling high-precision sensing with limited receiver deployment and supporting electromagnetic stealth.
  • Future directions: Further progress depends on IRS deployment strategies, reflection and waveform optimization, and continued development for wireless sensing and ISAC.

B. MA for Wireless Sensing and ISAC

MAs extend wireless sensing and ISAC by optimizing antenna positions and array geometries, improving aperture, resolution, and sensing–communication flexibility. Their benefits require sufficient movement resources, careful array design, calibration, and joint optimization of sensing and communication objectives.

  • MAs dynamically optimize antenna positions and array geometries, adding degrees of freedom for sensing accuracy, resolution, and ISAC integration.
  • Larger effective apertures improve far-field angular resolution and angle-of-arrival estimation, while near-field sensing exploits spherical wavefronts carrying range and angle information.
  • MA-aided sensing requires adequate movement time and region, with region size determining achievable resolution and target dynamics requiring sufficient speed and motion prediction.
  • Array geometry must avoid grating lobes, and accurate calibration is needed for coherent processing and high sensing accuracy.
  • ISAC requires jointly optimizing antenna positions, communication beamformers, and sensing waveforms while managing movement time and energy across tasks.

C. Performance Comparison

The comparison shows complementary sensing advantages: MAs provide broad-angle angular resolution through aperture enlargement, whereas RAs focus energy in selected angular sectors. Future deployment depends on efficient architectures, channel acquisition, low-complexity optimization, and movement-aware control.

  • C. Performance Comparison: MA achieves lower AoA-estimation MSE than FPA across the full angular range by enlarging the effective aperture.The comparison uses an 18-antenna linear array, MUSIC estimation, and 5 dB receive SNR.
  • C. Performance Comparison: MRA performs best near the angular center by combining MA’s large aperture with RA’s directional energy focusing.
  • C. Performance Comparison: RA offers sector-specific estimation accuracy through radiation-pattern reconfiguration, while MA provides consistently high angular resolution across a wider angle.
  • A. Efficient Antenna Architectures: Future RA architectures should improve switching speed, reconfiguration range, loss, power consumption, compactness, and multifunctional parameter control.
  • A. Efficient Antenna Architectures: Future MA architectures should provide compact, energy-efficient, fast, precise multidimensional actuation and scalable movable-array designs.
  • A. Efficient Antenna Architectures: Hybrid RA–MA systems require coordinated control of reconfiguration and movement while addressing dynamic coupling, interference, energy efficiency, and high-dimensional optimization.
  • Channel acquisition remains difficult for large movement regions, continuous motion, positioning errors, and integrated systems whose channels vary with position, orientation, and antenna state.
  • Real-time deployment requires low-complexity configuration, position optimization, and movement control that balances performance gains against energy, latency, computational, and mechanical costs.

D. Synergy with Other Technologies and Applications

RA and MA technologies can complement emerging wireless applications by adapting channels, antenna states, positions, and beam patterns. The survey concludes that these synergies extend across edge computing, AirComp, physical-layer security, wireless power, multiple access, and AI-based control.

  • MAs can optimize links for MEC offloading and AirComp aggregation, while RAs can adapt beam patterns for mobile users and channel shaping.
  • RAs and MAs can improve physical-layer security by strengthening legitimate links while degrading eavesdropper links through joint beamformer and antenna optimization.
  • In WPT and SWIPT, antenna states and positions can balance information-decoding SINR against harvested received power.
  • Mechanical movement energy could potentially power low-energy RA reconfiguration circuits or other low-power electronics through integrated piezoelectric or kinetic harvesters.
  • RA/MA control can shape inter-user correlations to support spatial division multiple access, NOMA, and RSMA objectives.
  • AI techniques, including LLMs, are proposed to manage RA state selection and MA movement through adaptive real-time control policies.
  • The survey synthesizes RA and MA fundamentals, architectures, applications, comparative characteristics, challenges, and future research directions.
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