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Embracing Reconfigurable Antennas in the Tri-hybrid MIMO Architecture for 6G and Beyond

Miguel Rodrigo Castellanos, Siyun Yang, Chan-Byoung Chae, Robert W. Heath

arXiv:2501.16610v2cs.ITcs.ETcs.NI

TL;DR

Large-scale MIMO faces rising power consumption and hardware complexity, motivating more efficient architectures for 6G and beyond. The paper introduces tri-hybrid MIMO, combining reconfigurable antennas with digital and analog precoding, and analyzes its spectral-efficiency and power trade-offs against existing architectures. The results identify substantial energy-efficiency benefits while also highlighting hardware and reconfigurability challenges.

  • Problem

    Large-scale fully digital and hybrid MIMO systems face increasing power consumption and hardware demands as antenna dimensions grow.

  • Method

    The paper models a tri-hybrid architecture that combines digital precoding, analog precoding, and reconfigurable-antenna electromagnetic precoding, including a dynamic metasurface antenna design.

  • Results

    The analysis compares tri-hybrid, fully digital, hybrid, and analog architectures in terms of spectral efficiency and power consumption, reporting energy-efficiency advantages for tri-hybrid designs.

  • Takeaways & Limitations

    Tri-hybrid MIMO offers a framework for adding antenna-level signal processing and low-power reconfiguration to future large-scale wireless architectures.

  • Takeaways & Limitations

    The comparison does not cover all architecture and component options, and the paper leaves optimal architecture design for future work.

Abstract

from arXiv · show

Multiple-input multiple-output (MIMO) communication has led to immense enhancements in data rates and efficient spectrum management. The evolution of MIMO, though, has been accompanied by increased hardware complexity and array sizes, causing the system power consumption to increase. Despite past advances in power-efficient hybrid architectures, new solutions are needed to enable extremely large-scale MIMO deployments for 6G and beyond. In this paper, we introduce a novel architecture that integrates low-power reconfigurable antennas with both digital and analog precoding. This \emph{tri-hybrid} approach addresses key limitations in traditional and hybrid MIMO systems by improving power consumption and adds a new layer for signal processing. We provide an analysis of the proposed architecture and compare its performance with existing solutions, including fully-digital and hybrid MIMO systems. The results demonstrate significant improvements in energy efficiency, highlighting the potential of the tri-hybrid system to meet the growing demands of future wireless networks. We conclude the paper with a summary of design and implementation challenges, including the need for technological advancements in reconfigurable array hardware and tunable antenna parameters.

I. INTRODUCTION

The paper motivates tri-hybrid MIMO as a response to the power and scaling challenges of large antenna arrays, combining digital and analog precoding with reconfigurable antennas. It surveys antenna functionality and architectures as foundations for modeling this approach.

  • Motivation: Scaling MIMO dimensions increases power consumption because fully digital systems require an RF chain and data converter for every antenna.Hybrid architectures reduce RF-chain counts but can still consume enormous power in large-scale deployments.
  • Antenna foundations: Reconfigurable antennas can adapt polarization, gain patterns, and frequency responses by changing antenna states and surface-current distributions.The paper presents current distribution as the electromagnetic mechanism underlying reconfigurable radiation behavior.
  • Proposed architecture: The proposed tri-hybrid architecture combines hybrid precoding with highly reconfigurable antenna arrays to add an antenna-level signal-processing layer.The architecture replaces static antenna arrays with reconfigurable apertures while retaining digital and analog precoding.
  • Paper scope: The paper surveys reconfigurable antenna functionality, tri-hybrid configurations, and antenna-selection criteria before developing analytical models and comparisons.The stated evaluation considers spectral efficiency and power consumption, including a dynamic metasurface antenna design.

C. Gain pattern

Gain-pattern reconfiguration changes radiation directionality through controllable current distributions, while related antenna technologies provide beam, frequency, polarization, and bandwidth flexibility for tri-hybrid systems.

  • C. Gain pattern: Gain-pattern reconfiguration changes an antenna’s radiation strength across directions by modifying its current distribution.Different operating states can produce omnidirectional or directional patterns suited to different channel conditions.
  • D. Frequency response: Frequency reconfiguration alters antenna frequency selectivity to support multiband, wideband, narrowband, and interference-rejection operation.Changing antenna geometry or resonance can enable multiple operating frequencies without separate antennas for each band.
  • Antenna categories: The surveyed antenna categories include metasurface-based, parasitic element-assisted, and structurally reconfigurable designs.These categories are evaluated for frequency tuning, radiation-pattern control, and polarization manipulation.
  • A. Metasurface antennas: Metasurface antennas use subwavelength resonators to provide low-profile designs, wide bandwidths, rapid response, and functions such as gain enhancement and mutual-coupling reduction.Dynamic metasurface antennas use tunable slots and low-power components for beamforming across multiple frequency bands.
  • A. Metasurface antennas: Metasurface designs can also reconfigure polarization, steer beams, and tune frequency, supporting flexible multiband operation in tri-hybrid systems.One reported design achieves a 750 MHz shift for every 1 mm change in feeder–metasurface distance.

B. Parasitic element-assisted antenna

Parasitic element-assisted and related metasurface systems use tunable electromagnetic interactions to shape beams, polarization, frequency response, and signal processing while reducing or controlling hardware burdens.

  • B. Parasitic element-assisted antenna: Parasitic element-assisted antennas use tunable passive elements around active antennas to alter collective radiation patterns and generate compact high-directivity multibeams.This approach is discussed as part of electromagnetic precoding for shaping electromagnetic fields.
  • B. Parasitic element-assisted antenna: Metasurface auxiliaries can improve coverage through reflection or transmission while requiring fewer changes to the transceiver structure than fully integrated designs.The paper identifies reflectors and transmitarrays as indirect performance-enhancement mechanisms.
  • B. Parasitic element-assisted antenna: Metasurface transmitarrays can reduce antenna thickness while maintaining focal behavior and enabling ±30° beam coverage with 19.1 dBi gain.The cited design combines feed movement with a low-cost phased array and reports low sidelobe levels.
  • B. Parasitic element-assisted antenna: Stacked intelligent metasurfaces perform signal processing directly in the electromagnetic domain through layered interactions and simultaneous wave re-radiation.The paper describes this as a route toward wave-domain beamforming and reduced reliance on high-resolution DACs.
  • B. Parasitic element-assisted antenna: The surveyed configurations include spatial-coupling control, polarization rotation, varactor-based phase tuning, and electromagnetic-bandgap suppression of surface waves and back radiation.These functions target gain, mutual coupling, polarization, beam steering, efficiency, and wearable-device performance.

C. Structurally reconfigurable arrays

Structurally reconfigurable arrays change antenna geometry or material configuration to adapt radiation behavior, but the field remains active and involves configuration-specific trade-offs.

  • C. Structurally reconfigurable arrays: Structurally reconfigurable arrays alter the physical geometry of the antenna to change its electromagnetic properties.They differ from metasurface antennas, which primarily manipulate electromagnetic properties without the same direct structural alteration.
  • C. Structurally reconfigurable arrays: Fluid-driven element arrays modify effective radiating-element placement or electromagnetic properties through controlled conductive or dielectric-fluid motion.The described mechanism changes capacitance or resonance without physically displacing solid antenna elements.
  • C. Structurally reconfigurable arrays: Liquid-metal radiators dynamically reshape conductive elements to tune frequency and polarization.The category includes liquid metal or ionized solutions used as reconfigurable radiating elements.
  • C. Structurally reconfigurable arrays: Deformable structural arrays bend, fold, or stretch flexible materials to control radiation characteristics across communication scenarios.The paper identifies these designs as one of three broad flexible and fluid antenna categories.
  • C. Structurally reconfigurable arrays: These antenna configurations remain an active research area, with distinct advantages and inherent trade-offs.The paper presents specific fluid-surface-wave and liquid-metal slot-antenna examples rather than a single dominant implementation.
  • C. Structurally reconfigurable arrays: Flexible arrays use rotatable, bendable, or foldable structures to change element positions and orientations for different performance demands.Experimental results are cited as demonstrating structural changes that support dynamic adaptation.

IV. TRI-HYBRID MIMO ARCHITECTURE

Tri-hybrid MIMO separates signal processing across digital, analog, and antenna domains, incorporating reconfigurable antenna structures into existing MIMO architectures.

  • Tri-hybrid MIMO separates signal processing into three domains: digital, analog, and antenna.
  • The architecture incorporates reconfigurable antennas into existing MIMO architectures as an additional signal-processing layer.

A. MIMO with hybrid analog-digital precoding

Hybrid analog-digital MIMO uses fewer digital ports than antennas, with digital and analog precoding jointly mapping data streams to the antenna array while reducing hardware complexity and power consumption.

  • Hybrid precoding generally uses fewer digital ports than antennas and applies analog beamforming to map digital signals to the larger antenna array.
  • The transmitter processes symbols with a frequency-selective digital precoder followed by a frequency-flat analog precoder.
  • The transmit signal is x[k] = FanaFdig[k]s[k], with the hybrid precoder Fhyb[k] = FanaFdig[k].
  • Fully connected architectures feed all antennas, whereas partially connected architectures divide antennas into equal-size subarrays with block-diagonal analog precoding.
  • Partial connectivity reduces RF paths and simplifies hardware implementation, making it a comparison point for tri-hybrid architectures.

B. Incorporating reconfigurable antennas to realize the tri-hybrid architecture

Reconfigurable antennas add a low-power, adaptable layer to hybrid MIMO, reducing analog hardware, expanding effective aperture size, and enabling responses to channel and spectrum conditions.

  • Reconfigurable components such as PIN diodes and tunable meta-elements consume less power than traditional RF processing components such as phase shifters.Dynamic metasurface antennas can shift signal-processing burden from analog hardware to low-power antenna elements, reducing phase shifters and associated components.
  • Replacing an 8-antenna subarray with a reconfigurable antenna can scale an Nt = 100 array's effective aperture to 8 × 100 = 800 radiators.The paper identifies this aperture expansion as relevant to scaling arrays toward thousands of antennas for 6G upper-midband applications.
  • Reconfigurability supports polarization, frequency, and pattern adaptation for depolarization mitigation, wider bandwidths, and reduced transmissions toward spectrum incumbents.The paper describes these functions as ways to adapt to dynamic channel conditions.

C. Re-thinking precoding in the context of the tri-hybrid MIMO architecture

Tri-hybrid precoding introduces an antenna-domain precoder alongside digital and analog precoders, requiring array-specific signal models and power constraints that reflect reconfigurable radiation behavior.

  • The effective number of radiating elements N_rad_t can exceed the conventional antenna count Nt through DMA slots, parasitic elements, or orthogonal polarization arrays.
  • The tri-hybrid transmit signal is xant[k] = Fant[k]FanaFdig[k]s[k], combining antenna, analog, and digital precoding.
  • The antenna precoder Fant[k] models reconfigurable-array behavior, while Fana connects digital and analog ports and Fdig[k] maps data streams to RF ports.
  • Power constraints may be imposed at the antenna input or output, with antenna-output constraints incorporating reconfigurable-array radiation efficiency and losses.
  • Fig. 7 compares dynamic metasurface, parasitic, and polarization-reconfigurable arrays, each with different precoding structures.
  • Tri-hybrid models are not straightforward extensions of hybrid MIMO because each reconfigurable antenna implementation produces a unique architecture.

V. PERFORMANCE COMPARISON BETWEEN MIMO ARCHITECTURES

The paper analyzes a DMA-based tri-hybrid architecture and uses DMAs as a concrete example for studying reconfigurable-array constraints. DMA beamforming is limited by Lorentzian phase–amplitude coupling and waveguide-fed structure.

  • V. PERFORMANCE COMPARISON BETWEEN MIMO ARCHITECTURES: DMA-based tri-hybrid MIMO extends hybrid MIMO by combining reconfigurable-array precoding with existing precoding stages.The analysis uses DMAs as the representative reconfigurable architecture.
  • V. PERFORMANCE COMPARISON BETWEEN MIMO ARCHITECTURES: Lorentzian constraints couple DMA slot phase and amplitude responses, shaping the beamforming patterns that the architecture can achieve.The constraints arise from the behavior of passive reconfigurable slots.

A. Tri-hybrid precoding

The tri-hybrid transmitter cascades DMA, analog, and digital precoding, while modeling DMA-specific waveguide and Lorentzian constraints. Its precoders are optimized separately to obtain a tractable design and performance baseline.

  • A. Tri-hybrid precoding: The DMA precoder is frequency-flat and produces the electromagnetic precoding layer before analog and digital precoding.The transmitted signal is x_dma[k] = F_dma F_ana F_dig[k] s[k].
  • A. Tri-hybrid precoding: Each DMA waveguide forms a subarray because it has a single input port, imposing a block-diagonal structure on F_dma.The nth subarray beamformer is represented by f_dma,n.
  • A. Tri-hybrid precoding: DMA slot weights satisfy Lorentzian constraints that couple phase and gain, while waveguide propagation adds a channel term η_m,n.These effects jointly determine the feasible DMA beamformers.
  • A. Tri-hybrid precoding: The received-signal model uses a wireless channel between DMA slots and a fully-digital receiver under perfect channel knowledge and synchronization assumptions.The additive noise is modeled as circularly symmetric Gaussian noise with variance σ^2 per entry.
  • A. Tri-hybrid precoding: Because joint optimization is complex, the method optimizes each precoding matrix separately and uses waterfilling for the hybrid precoder with fixed F_dma.A Lorentzian mapping then produces a feasible DMA precoder for the resulting design.
  • A. Tri-hybrid precoding: The resulting procedure provides a feasible but suboptimal tri-hybrid design that serves as an energy-efficiency performance baseline.The hybrid precoder is subsequently obtained under hybrid precoding constraints.

B. Power consumption models

The power models account for RF chains, converters, oscillators, phase shifters, amplifiers, and associated losses across DMA, hybrid, and fully-digital architectures. The comparisons expose trade-offs between radiating-element count, precoding flexibility, performance, and power.

  • B. Power consumption models: Transmit power is modeled from power amplifiers, DACs, local oscillators, RF components, phase shifters, and component losses.The model distinguishes phase-shifter and power-divider losses through L_PS and L_D(N_a).
  • B. Power consumption models: The DMA-only architecture uses one DMA, one RF chain, and no phase shifters, yielding the lowest power consumption among the baselines.Its radiating-element count is determined by the DMA dimensions.
  • B. Power consumption models: Adding digital precoding to DMA precoding improves performance over DMA-only operation but increases power consumption.This defines the DMA-digital hybrid trade-off.
  • B. Power consumption models: Partially-connected hybrid precoding reduces RF-chain count by assigning each chain to a subarray of Nsub = Nt/N_RF antennas.It provides a direct comparison with tri-hybrid architectures because both use subarrays.
  • B. Power consumption models: Fully-connected hybrid precoding offers better performance than partially-connected hybrid precoding but consumes more power because every antenna uses phase-shifter connections to all RF chains.The added phase shifters account for the higher power consumption.
  • B. Power consumption models: Fully-digital precoding provides the greatest precoding control and serves as the spectral-efficiency upper performance limit, but substantially increases power consumption.Each antenna is connected to its own RF chain.
  • B. Power consumption models: DMA-based architectures can provide more radiating elements at the same power as hybrid architectures, or the same number with lower power.This advantage follows from replacing antennas with DMA structures.
  • B. Power consumption models: The DMA advantage comes with reduced flexibility in the DMA precoding matrix, and the comparison does not cover all architecture and component choices.The authors leave optimal architecture design for future work.

C. Numerical results

The numerical evaluation compares tri-hybrid and baseline precoding architectures under matched input-power and radiating-element conditions. It shows that tri-hybrid designs trade lower spectral efficiency for substantially better energy efficiency across a broad input-power range.

  • Evaluation setup: DMA-based tri-hybrid evaluation uses a planar array with Nr = 64, Nt = 64, and transmitter spacings dx = λ/4 and dy = λ/2.The setup also uses dr = λ/2, M = 2 for DMA-based hybrid architectures, and a raised-cosine filter with roll-off factor 1.
  • Evaluation setup: The comparison controls for fairness by assigning each architecture the same input power and number of radiating elements.Transmit power is obtained from input power and architecture component loss, while energy efficiency is computed as spectral efficiency divided by system power consumption.
  • Results: Tri-hybrid spectral efficiency is lower than fully-digital and hybrid architectures because DMA precoding constraints and waveguide losses reduce achievable weights and signal strength.The Lorentzian constraint couples beamforming phase and amplitude, while waveguide attenuation introduces additional loss.
  • Results: Across a broad range of input-power values, all tri-hybrid architectures significantly outperform analog, hybrid, and digital architectures in energy efficiency.The reported benefit is moderate spectral efficiency at very low power consumption.

VI. FUTURE OUTLOOK

The future outlook presents tri-hybrid MIMO as a framework combining antenna, analog, and digital precoding, while identifying hardware, reconfigurability, optimization, and channel-tracking challenges. Future progress depends on more adaptable antenna technologies and scalable implementations that are evaluated within the complete tri-hybrid design.

  • Architecture and framework: Tri-hybrid MIMO adds antenna precoding to conventional analog and digital precoding and can unify multiple reconfigurable-array approaches.The paper gives a DMA-based design as a detailed example while describing broader configurations at a higher level.
  • Advanced antenna designs: Current reconfigurable antennas remain limited in adaptability and efficiency, motivating metasurface and tunable-material designs with finer control of beamforming, polarization, and frequency response.These designs should be evaluated as components of a larger tri-hybrid precoding system, not only with traditional antenna metrics.
  • Multi-parameter reconfigurability: Simultaneous reconfiguration of polarization, frequency, and gain pattern could increase flexibility but introduces greater hardware and software complexity.The challenge is to balance multi-parameter reconfigurability with practical implementation constraints.
  • Circuit and hardware considerations: Large-scale deployment still requires lower-power, high-efficiency RF and analog hardware together with scalable, cost-effective manufacturing.The paper identifies RF chains, phase shifters, and other analog components as continuing implementation challenges as systems scale.
  • Precoder design: New optimization methods are needed to design the antenna, analog, and digital precoders under their respective constraints.The paper identifies nonlinear optimization and machine-learning-based optimization as possible directions.
  • Channel estimation and tracking: Channel estimation and tracking must determine how antenna configuration is incorporated alongside analog and digital precoding.Existing beam-based procedures estimate analog precoding and then the effective channel and digital precoding, leaving antenna configuration integration unresolved.
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