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Movable-Element STAR-RIS for 6G: From Programmable Propagation to Programmable Geometry

Wali Ullah Khan, Muhammad Adil

arXiv:2609.08545v1cs.ET

TL;DR

Conventional STAR-RIS controls transmission and reflection but retains fixed element locations. This article presents ME-STAR-RIS as a system-level approach combining electronic response control with element movement. Its representative case study reports average spectral-efficiency improvements of 11.0% at 0 dB and 12.6% at 5 dB over the fixed benchmark.

  • Problem

    Conventional RIS and STAR-RIS architectures retain fixed element locations after deployment, limiting control to the elements’ electromagnetic responses.

    Source: §I · p. 1

  • Method

    The article presents a system-level perspective on ME-STAR-RIS, combining transmission/reflection control with movable elements and discussing applications, architectures, and deployment challenges.

    Source: §I · pp. 1–2

  • Results

    11.0% at 0 dB and 12.6% at 5 dB average improvement over the fixed benchmark were reported for the movable surface in the representative case study.

    Source: B. Spectral-Efficiency Gain Across… · p. 5

  • Takeaways & Limitations

    The article concludes that limited, energy-aware element movement may capture meaningful gains, while practical hardware remains the key challenge.

    Source: §VI · p. 7

    Practical hardware will constrain displacement range, positioning resolution, movement direction, and actuation speed, unlike the continuous movement often assumed in existing studies.

    Source: A. Hardware, Energy, and Reliability · p. 6

Abstract

from arXiv · show

Reconfigurable intelligent surfaces (RISs) make the wireless propagation environment programmable, while simultaneously transmitting and reflecting RISs (STAR-RISs) extend this capability to users located on both sides of a surface. However, conventional STAR-RIS architectures retain a fixed physical geometry after deployment. Movable-element STAR-RIS (ME-STAR-RIS) introduces an additional spatial degree of freedom by allowing the surface elements to reposition within prescribed regions while maintaining electronic control of their transmission and reflection responses. This combination of electromagnetic and geometric reconfiguration can alter propagation distances, multipath combinations, spatial correlation, interference, near-field focusing, and sensing geometry. This article presents a system-level perspective on ME-STAR-RIS through the concept of programmable geometry. We discuss its operating principles, movement architectures, and promising applications in communications, security, near-field systems, sensing, and high-mobility networks. A representative case study comparing optimized fixed and movable STAR-RIS architectures illustrates measurable spectral-efficiency gains from limited local displacement and the resulting saturation behavior. Finally, key hardware, channel-acquisition, electromagnetic, energy, reliability, and control challenges are discussed toward practical ME-STAR-RIS deployment.

I. INTRODUCTION

Conventional STAR-RIS can control transmission and reflection, but its elements remain at fixed physical locations. ME-STAR-RIS adds controlled displacement, and this article frames the resulting electromagnetic and geometric control as programmable geometry.

I. INTRODUCTION

  • Conventional RIS and STAR-RIS elements remain at fixed locations after deployment, even when their electromagnetic responses are electronically tuned.The surface changes how a wave is handled, not the spatial point at which it is sampled.Source: §I · p. 1
  • Small controlled displacements can select more favorable channel locations and alter path lengths, multipath combinations, spatial correlation, and interference.These effects add geometric control to the familiar adjustment of an element’s complex coefficient.Source: §I · p. 1
  • Earlier ME-STAR-RIS studies span joint beamforming, STAR coefficients, and element positions, as well as security, near-field wideband communication, and sensing.The literature is described as early-stage and dominated by application-specific optimization problems.Source: §I · p. 1
  • ME-STAR-RIS adds element position to the controllable surface configuration, extending the progression from programmable reflection to transmission and reflection and then to programmable geometry.Fig. 1 presents this evolution from conventional reflecting RIS through fixed STAR-RIS and movable-element RIS to movable-element STAR-RIS.Source: §I · p. 1, Figure 1 · p. 2
  • The article surveys ME-STAR-RIS principles, movement architectures, applications, a fixed-versus-movable communication case study, and practical deployment challenges.Applications include communication, security, near-field, sensing, localization, and high-mobility scenarios; challenges include hardware, channel acquisition, electromagnetic effects, energy, reliability, and control.Source: §I · p. 2

II. HOW MOVABLE STAR-RIS WORKS?

ME-STAR-RIS combines electronic control of transmission and reflection with geometric control over element positions. Because displacement changes the channel before electronic coefficients are applied, the design couples element locations to multiple links and can affect near-field focusing.

A. Dual Electromagnetic and Geometric Reconfiguration

  • ME-STAR-RIS retains STAR-RIS transmission and reflection control while adding element movement within constrained regions.Movement may involve individual elements or groups, with continuous, track-based, or discrete positions.Source: A. Dual Electromagnetic and Geometric… · p. 2
  • Displacement changes propagation distance and phase before electronic adjustment, potentially changing multipath combinations and received amplitude.Different positions can transform destructive multipath combinations into constructive ones, or vice versa.Source: A. Dual Electromagnetic and Geometric… · p. 2
  • Moving one element changes multiple cascaded links, so a location that helps one user can alter interference toward another user or an eavesdropper.The array layout must be chosen against the network objective, rather than treating movement as phase optimization alone.Source: A. Dual Electromagnetic and Geometric… · p. 2
  • In near-field wideband systems, element positions affect distance-dependent focal regions and can help reduce frequency-dependent focusing errors.Prior work has reported advantages over fixed-position STAR-RIS for addressing near-field wideband beam-squint effects.Source: A. Dual Electromagnetic and Geometric… · p. 3
  • The architecture has two control domains: faster electronic variables set transmission, reflection, and phase, while slower geometric variables set element locations.Geometry adds a control layer rather than replacing existing STAR-RIS electromagnetic control.Source: A. Dual Electromagnetic and Geometric… · p. 3

B. Movement Architectures and Operating Timescales

Movement need not track electronic reconfiguration at the same rate. The paper argues for limited geometric flexibility that captures much of the channel gain while reducing mechanical complexity and control overhead.

B. Movement Architectures and Operating Timescales

  • Element positions may be updated when large-scale geometry, user distribution, blockage, or propagation statistics change, while electronic coefficients track faster variations.Mechanical movement is expected to be slower and more energy-consuming than semiconductor-based phase control.Source: B. Movement Architectures and… · p. 3
  • Restricted tracks, grouped movement, or a few discrete positions can reduce actuator count and control overhead while retaining much of the mobility benefit.The engineering objective is the minimum geometric flexibility needed to capture most of the available channel gain, not maximum movement freedom.Source: B. Movement Architectures and… · p. 3

III. WHERE CAN PROGRAMMABLE GEOMETRY MATTER MOST?

The value of programmable geometry depends on whether movement changes the relevant channel or sensing conditions. In the investigated security scenario, movable STAR-RIS improves secrecy over a fixed-position design, with gains that saturate as the movement region grows.

III. WHERE CAN PROGRAMMABLE GEOMETRY MATTER MOST?

  • ME-STAR-RIS is most attractive when small positional changes create meaningfully different communication, interference, or sensing conditions.If the channel varies little across the allowable movement region, displacement may provide only marginal benefit.Source: §III · p. 3

A. Communications, Interference Management, and Security

  • Approximately 25% secrecy improvement over conventional fixed-position STAR-RIS was reported for the investigated scenario, with benefits eventually saturating as the movement region grows.The percentage is not universal; the reported behavior suggests a relatively limited movement region may capture most available geometric diversity.Source: A. Communications, Interference… · p. 3

B. Near-Field, ISAC, and Localization

ME-STAR-RIS can adapt both communication channels and sensing geometry, with potential applications in near-field systems, ISAC, localization, and high-mobility networks. A two-timescale approach pairs slower geometry updates with faster electronic adaptation.

B. Near-Field, ISAC, and Localization

  • For ISAC, element movement changes communication channels, target illumination, spatial focusing, and clutter relationships, and may affect localization sensitivity.Communication- and sensing-oriented configurations may favor different spatial relationships.Source: B. Near-Field, ISAC, and Localization · pp. 3–4
  • In near-field wideband systems, ME-STAR-RIS mobility has been studied as an alternative or complement to true-time-delay structures for mitigating beam squint.Different movement modes trade performance against implementation complexity.Source: B. Near-Field, ISAC, and Localization · p. 4

C. High-Mobility and Non-Terrestrial Networks

  • For satellite, UAV, and vehicular settings, geometry could adapt to long-term trajectories, dominant directions, user distributions, or persistent blockage while electronic coefficients track faster variations.This two-timescale view pairs slower mechanical adaptation with fast electronic tracking.Source: C. High-Mobility and Non-Terrestrial… · p. 4
  • The emerging literature covers communication, security, near-field, and sensing scenarios, while leaving room for a broader system and deployment perspective.The cited works span joint position and beamforming optimization, full-space eavesdropping, near-field beam-squint mitigation, and sensing with covert communication.Source: C. High-Mobility and Non-Terrestrial… · p. 4

IV. CASE STUDY: HOW MUCH DOES MOBILITY BUY?

The case study is designed to isolate the value of programmable geometry through a comparison between fixed and movable STAR-RIS architectures.

IV. CASE STUDY: HOW MUCH DOES MOBILITY BUY?

  • The case study aims to isolate the value of programmable geometry in a compact terrestrial setting.The fixed and movable architectures use the same system resources and channel realizations.Source: §IV · pp. 4–5
  • Table I is titled as a summary of emerging research directions in movable-element STAR-RIS.Source: Table I · p. 5
  • The comparison holds the base-station array, STAR-element count, propagation realizations, and energy-splitting operation constant.The movable architecture adds only local shifts around nominal element positions.Source: §IV · p. 5

A. Scenario and Fair Benchmarking

In the illustrative two-user case study, the movable surface outperforms the optimized fixed benchmark across the tested transmit-power range, with the largest reported gains at low-to-moderate power. The comparison uses matched electronic optimization and channel realizations to assess the additional geometric degree of freedom.

A. Scenario and Fair Benchmarking

  • The illustrative setup uses a four-antenna base station, a 4 × 4 STAR surface, and one user in each of the reflection and transmission regions.The surface starts on a 0.8λ grid, with local square movement regions and a minimum pairwise separation of 0.5λ.Source: A. Scenario and Fair Benchmarking · p. 5
  • Both architectures use the same coordinate-search procedure for electronic design, while the movable design alternates those updates with feasible position updates.The fixed benchmark holds the regular grid unchanged; results average ten channel realizations shared by both configurations.Source: A. Scenario and Fair Benchmarking · p. 5

B. Spectral-Efficiency Gain Across Transmit Power

  • About 11.0% at 0 dB and 12.6% at 5 dB are the average improvements in sum spectral efficiency; the gain falls to a few percent around 20–30 dB.With maximum local displacement ∆max = 0.15λ, the movable surface remains above the fixed benchmark throughout the tested range.Source: B. Spectral-Efficiency Gain Across… · p. 5
  • The reported gains are representative of this case study, not universal, and vary with channel richness, direct-path strength, element count, and allowed movement geometry.Geometry complements rather than replaces transmit power or electronic beamforming.Source: B. Spectral-Efficiency Gain Across… · p. 5

C. How Much Movement Is Enough?

In the considered geometry, small local displacements produce much of the spectral-efficiency gain, after which the curve nearly saturates. The case study suggests limited local motion rather than unrestricted travel.

C. How Much Movement Is Enough?

  • About 6.4% average gain comes from 0.025λ motion, rising to about 8.0% at 0.05λ and roughly 9.1% at 0.10λ before near-saturation.These displacement comparisons are at a representative 20-dB power level.Source: C. How Much Movement Is Enough? · p. 5, Figure 4 · p. 6
  • Small local movement cells can capture much of the available spatial diversity, while additional mechanical range delivers little benefit beyond saturation.The suggested engineering target is the smallest range that captures most of the geometry gain.Source: C. How Much Movement Is Enough? · p. 5
  • The design lessons are that geometry complements electromagnetic control and that the value of mobility is nonlinear in movement range.The first small displacement can be more valuable than extending an already adequate movement region.Source: C. How Much Movement Is Enough? · p. 6

V. FROM THEORY TO DEPLOYABLE SURFACES

Making ME-STAR-RIS practical requires matching movement to hardware limits, energy cost, and reliability rather than assuming unrestricted element motion. The article proposes constrained architectures and movement triggered by sufficient expected benefit.

V. FROM THEORY TO DEPLOYABLE SURFACES

  • Practical ME-STAR-RIS value depends on implementing movement with acceptable latency, energy consumption, calibration burden, and hardware reliability.The article frames deployment around whether these costs can be managed alongside communication gains.Source: §V · p. 6

A. Hardware, Energy, and Reliability

  • Movement range, positioning resolution, direction, and actuation speed constrain physical actuation, motivating hardware-aware mobility models.Possible implementations include microelectromechanical mechanisms, miniature tracks, deformable substrates, and mechanically reconfigurable subarrays.Source: A. Hardware, Energy, and Reliability · p. 6
  • Movement should be triggered when expected performance benefit justifies actuation, calibration, and control overhead.Repeatedly repositioning many elements can impose non-negligible actuation cost, even if stationary elements consume little energy.Source: A. Hardware, Energy, and Reliability · p. 6
  • Restricted architectures can reduce mechanical complexity while retaining some geometric diversity through grouped movement, predefined tracks, or tested configuration codebooks.Frequent movement may introduce mechanical wear, positioning errors, and long-term calibration drift.Source: A. Hardware, Energy, and Reliability · p. 6

B. Channel Acquisition and Two-Timescale Control

Variable element positions make channel acquisition more demanding because transmitter–surface and surface–user channels vary with position. The article proposes geometry-aware inference and slower physical adaptation alongside fast electronic control.

B. Channel Acquisition and Two-Timescale Control

  • Movable elements make transmitter–surface and surface–user channels position-dependent, so exhaustive estimation over candidate locations is impractical.Geometry-aware models can use path angles, propagation distances, dominant scatterers, and user locations to predict channel evolution.Source: B. Channel Acquisition and… · p. 6
  • Fast STAR coefficients can track instantaneous channel variations while geometry changes more slowly with user distribution, dominant paths, blockage, or mobility trends.This treats movement as structural adaptation rather than tracking each small-scale fading realization.Source: B. Channel Acquisition and… · p. 6
  • Roadside surfaces may adapt geometry to traffic patterns while electronically tracking vehicles; UAV or NTN surfaces may configure geometry for predicted trajectories or elevation ranges.Fast electronic control compensates for shorter-term fluctuations in the UAV or NTN examples.Source: B. Channel Acquisition and… · p. 7

C. Electromagnetic-Aware and AI-Assisted Control

ME-STAR-RIS control must account for electromagnetic interactions and mechanical constraints as well as coordinate beamforming, STAR coefficients, and element locations. The article favors practical, limited movement with low overhead and reliable operation.

C. Electromagnetic-Aware and AI-Assisted Control

  • Element movement can change mutual coupling, impedance, radiation patterns, and local electromagnetic interactions, especially in irregular or tightly spaced configurations.The article calls for coupling-aware, hardware-informed models, potentially using reduced-complexity surrogates from full-wave simulations.Source: C. Electromagnetic-Aware and… · p. 7
  • Beamforming, STAR coefficients, and element locations must be coordinated under coupled electromagnetic and mechanical constraints.Model-assisted AI could predict when movement is worthwhile, identify low-dimensional configurations, estimate spatial channel maps, or approximate costly optimization.Source: C. Electromagnetic-Aware and… · p. 7
  • Digital twins, model-driven learning, and graph-based architectures can incorporate movement limits, minimum spacing, and transmission/reflection operation while learning environmental dynamics.The stated objective is to capture most available performance gain with limited movement, low control overhead, and reliable hardware operation.Source: C. Electromagnetic-Aware and… · p. 7

VI. CONCLUSION

  • The article concludes that programmable geometry adds element position as a controllable resource, with limited, energy-aware movement and slower geometry updates among promising practical directions.Fast electronic STAR control remains part of the proposed practical approach.Source: §VI · p. 7, C. Electromagnetic-Aware and… · p. 7
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