Dynamic Metasurface Antennas Research Articles

Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media

Metasurface-programmable radio environments are considered a key ingredient of next-generation wireless networks. Yet, identifying a metasurface configuration that yields a desired wireless functionality in an unknown complex environment was so far only achieved with closed-loop iterative feedback schemes. Here, we introduce open-loop wave control in metasurface-programmable complex media by estimating the parameters of a compact physics-based forward model. Our experiments demonstrate orders-of-magnitude advantages over deep-learning-based digital-twin benchmarks in terms of accuracy, compactness and required calibration examples. Strikingly, our parameter estimation also works without phase information and without providing measurements for all considered scattering coefficients. These unique generalization capabilities of our pure-physics model unlock unforeseen and previously inaccessible frugal wave control protocols that significantly alleviate the measurement complexity. For instance, we achieve coherent wave control (focusing or perfect absorption) and phase-shift-keying backscatter communications in metasurface-programmable complex media with intensity-only measurements. Our approach is also directly relevant to dynamic metasurface antennas, microwave-based signal processors and emerging in situ reconfigurable nanophotonic, optical and room-acoustical systems.

Energy Beamforming for RF Wireless Power Transfer With Dynamic Metasurface Antennas

Energy Beamforming for RF Wireless Power Transfer With Dynamic Metasurface Antennas

A Block Quantum Genetic Interference Mitigation Algorithm for Dynamic Metasurface Antennas and Field Trials

A Block Quantum Genetic Interference Mitigation Algorithm for Dynamic Metasurface Antennas and Field Trials

Physical-layer key generation based on multipath channel diversity using dynamic metasurface antennas

Physical layer key generation (PKG) technology leverages the reciprocal channel randomness to generate the shared secret keys. The low secret key capacity of the existing PKG schemes is due to the reduction in degree-of-freedom from multipath fading channels to multipath combined channels. To improve the wireless key generation rate, we propose a multipath channel diversity-based PKG scheme. Assisted by dynamic metasurface antennas (DMA), a two-stage multipath channel parameter estimation algorithm is proposed to efficiently realize super-resolution multi-path parameter estimation. The proposed algorithm first estimates the angle of arrival (AOA) based on the reconfigurable radiation pattern of DMA, and then utilizes the results to design the training beamforming and receive beamforming to improve the estimation accuracy of the path gain. After multipath separation and parameter estimation, multi-dimensional independent path gains are utilized for generating secret keys. Finally, we analyze the security and complexity of the proposed scheme and give an upper bound on the secret key capacity in the high signal-to-noise ratio (SNR) region. The simulation results demonstrate that the proposed scheme can greatly improve the secret key capacity compared with the existing schemes.

Energy Efficiency Maximization of Massive MIMO Communications With Dynamic Metasurface Antennas

Future wireless communications are largely inclined to deploy massive numbers of antennas at the base stations (BSs) by leveraging cost- and energy-efficient as well as environmentally friendly antenna arrays. The emerging technology of dynamic metasurface antennas (DMAs) is promising to realize such massive antenna arrays with reduced physical size, hardware cost, and power consumption. The goal of this paper is the optimization of the energy efficiency (EE) performance of DMA-assisted massive multiple-input multiple-output (MIMO) wireless communications. Focusing on the uplink, we propose an algorithmic framework for designing the transmit precoding of each multi-antenna user and the DMA tuning strategy at the BS to maximize the EE performance, considering the availability of either instantaneous or statistical channel state information (CSI). Specifically, the proposed framework is shaped around Dinkelbach's transform, alternating optimization, and deterministic equivalent methods. In addition, we obtain a closed-form solution to the optimal transmit signal directions for the statistical CSI case, which simplifies the corresponding transmission design for the multiple-antenna case. Our numerical results verify the good convergence behavior of the proposed algorithms, and showcase the considerable EE performance gains of the DMA-assisted massive MIMO transmissions over the baseline schemes.

A Liquid Crystal Tunable Metamaterial Unit Cell for Dynamic Metasurface Antennas

This communication presents a liquid crystal (LC)-based electronically tunable metamaterial unit cell that can serve as a building block for dynamic metasurface antennas (DMAs). The metamaterial unit cell was designed based on a complementary electric-inductive-capacitive (cELC) resonator, whose structure was modified into double metal layers for ease of loading the LC mixture. The equivalent capacitance, and thus the transmission coefficient of the metamaterial unit cell, can be tuned by external biasing voltages. The metamaterial unit cell couples to the transverse magnetic (TM) field, making it easy to be embedded into waveguide-fed structures such as microstrip lines or parallel-plate waveguides. In addition, it is individually addressable, which meets the design requirement of DMAs. Experimental results show that the transmission coefficient of the metamaterial unit cell can be continuously tuned from −2.7 to −6.5 dB at 29 GHz with a biasing voltage swinging from 2.5 to 10 Vrms. The response times are around 150 ms for both switch-ON and swtich-OFF cases.

Leveraging the Role of Dynamic Reconfigurable Antennas in Viewpoint of Industry 4.0 and Beyond

Industry 4.0 is a digital paradigm that refers to the integration of cutting-edge computing and digital technologies into global industries because of which the state of manufacturing, communication, and control of smart industries has changed altogether. Industry 4.0 has been profoundly influenced by some major disruptive technologies such as the Internet of Things (IoT), smart sensors, machine learning and artificial intelligence, cloud computing, big data analytics, advanced robotics, augmented reality, 3D printing, and smart adaptive communication. In this review paper, we discuss physical layer-based solutions with a focus on high reliability and seamless connectivity for Industry 4.0 and beyond applications. First, we present a harmonized review of the industrial revolution journey, industrial communication infrastructure, key performance requirements, and potential sub-6-GHz frequency bands. Then, based on that, we present a comprehensive review of intelligent tunable dynamic antenna systems at sub-6 GHz as key enablers for next-generation smart industrial applications. State-of-the-art smart antenna techniques such as agile pattern reconfigurability using electrical components, machine learning- and artificial intelligence-based agile beam-scanning antennas, and beam-steerable dynamic metasurface antennas are thoroughly reviewed and emphasized. We unfolded the exciting prospects of reconfigurable dynamic antennas for intelligent and reliable connectivity in application scenarios of Industry 4.0 and beyond such as Industrial IoT and smart manufacturing.

Development of Fast Fourier-Compatible Image Reconstruction for 3D Near-Field Bistatic Microwave Imaging With Dynamic Metasurface Antennas

The emerging technology of dynamic metasurface antennas (DMAs) offers a promising solution to revolutionize future wireless communications by reducing hardware costs, physical size and power consumption. Especially in the field of radar imaging, DMAs can be used as an effective alternative platform for modern computational imaging; because they can simplify the physical hardware architecture and increase the data acquisition rate. Fourier transform (FT)-based scene image reconstruction techniques are known as cost-effective computing solutions for the imaging system processing unit. However, due to the physical layer compression in DMAs and the fact that they do not produce uniform radiation patterns, the information provided by them is not compatible with Fourier-based techniques and cannot be applied directly. In this article, we first introduce a 3D near-field bistatic imaging approach using two one-dimensional (1D) DMAs as a panel-to-panel model in a Mills Cross structure. Then, based on the introduced mathematical model, we derive a Fourier-based algorithm for the image reconstruction problem. The proposed algorithm consists of five main steps: (i) pre-processing (to transfer the data provided by the transmitter and receiver DMAs to a set of equivalent spatial measurements), (ii) applying FTs to the transferred signal, (iii) filtering in the Fourier domain, (iv) a simplified interpolation, and (v) applying a 3D inverse FT to retrieve scene information. The results of numerical simulations confirm the satisfactory performance of the proposed approach.

Electromagnetic Based Communication Model for Dynamic Metasurface Antennas

Dynamic metasurface antennas (DMAs) arise as a promising technology in the field of massive multiple-input multiple-output (mMIMO) systems, offering the possibility of integrating a large number of antennas in a limited —and potentially large— aperture while keeping the required number of radio-frequency (RF) chains under control. Although envisioned as practical realizations of mMIMO systems, DMAs represent a new paradigm in the design of signal processing techniques (such as beamforming) due to the constraints inherent to their physical implementation, for which no complete models are available yet. In this work, we propose a complete and electromagnetic-compliant narrowband communication model for a generic DMA based system. Specifically, the model accounts for: i) the wave propagation and reflections throughout the waveguides that feed the antenna elements, ii) the mutual coupling both through the air and the waveguides, and iii) the insertion losses. Also, we integrate the electromagnetic model in the conventional digital communication model, providing a complete and useful framework to design and characterize the performance of these systems. Finally, the accuracy of the model is verified through full-wave simulations.

Hybrid RIS and DMA Assisted Multiuser MIMO Uplink Transmission With Electromagnetic Exposure Constraints

In the fifth-generation and beyond era, reconfigurable intelligent surface (RIS) and dynamic metasurface antennas (DMAs) are emerging metamaterials keeping up with the demand for high-quality wireless communication services, which promote the diversification of portable wireless terminals. However, along with the rapid expansion of wireless devices, the electromagnetic (EM) radiation increases unceasingly and inevitably affects public health, which requires a limited exposure level in the transmission design. To reduce the EM radiation and preserve the quality of communication service, we investigate the spectral efficiency (SE) maximization with EM constraints for uplink transmission in hybrid RIS and DMA assisted multiuser multiple-input multiple-output systems. Specifically, alternating optimization is adopted to optimize the transmit covariance, RIS phase shift, and DMA weight matrices. We first figure out the water-filling solutions of transmit covariance matrices with given RIS and DMA parameters. Then, the RIS phase shift matrix is optimized via the weighted minimum mean square error, block coordinate descent and minorization-maximization methods. Furthermore, we solve the unconstrainted DMA weight matrix optimization problem in closed form and then design the DMA weight matrix to approach this performance under DMA constraints. Numerical results confirm the effectiveness of the EM aware SE maximization transmission scheme over the conventional baselines.

Analyses of Grating Lobe and Beam Fixation Problems of Low-Profile Dynamic Antenna

Dynamic metasurface antennas (DMAs) and dynamic antenna arrays (DAAs) are emerging concepts in low-profile antenna design, providing alternative structures with lower circuit complexity and power requirements for radar and communication systems. However, dynamic antennas are prone to significant grating lobe and beam fixation problems due to their discrete amplitude and phase control. The reasons behind these issues are explored through mathematical and simulation analysis of three specific cases, and solutions are subsequently proposed and partially experimentally verified.

Frequency Domain Image Reconstruction for Imaging With Multistatic Dynamic Metasurface Antennas

Dynamic metasurface antennas (DMAs) have recently been introduced as a computational imaging (CI) platform that offers significant advantages over conventional imaging systems. Such antennas are able to produce tailored radiation patterns that are later used to encode the scene’s information into a few measurements. However, since the signal is compressed, image reconstruction in the frequency domain using the conventional range migration algorithm (RMA) cannot be directly applied to CI-based apertures synthesized with DMAs. More sophisticated algorithms need to be developed to overcome this limitation, which transfers the complexity of such systems to the software layer. This paper proposes a new multistatic DMA RMA (MD-RMA) technique that achieves decompression of the compressed signals collected from multistatic DMA apertures and processes the decompressed data in the Fourier domain followed by a multistatic-to-monostatic conversion. Simulation results verify that the proposed approach can produce high quality 3D radar images, which alleviates the need to mechanically move the aperture. Moreover, since the image reconstruction is fully conducted in the frequency domain, leveraging the fast Fourier transform (FFT) algorithm, the complexity of the algorithm, and thus the execution time, is significantly reduced in contrast with conventional spatial domain algorithms.

Fourier-Based Near-Field Three-Dimensional Image Reconstruction in a Multistatic Imaging Structure Using Dynamic Metasurface Antennas

Due to physical layer compression, and consequently, the failure to produce uniform radiation patterns, it is not possible to develop fast Fourier-based image reconstruction algorithms using the raw measurements collected from metasurface antennas. An effective solution in the literature is a sub-wavelength sampling of the aperture. However, this solution is currently limited to a panel-to-probe model which requires a mechanical raster scan. On the other hand, existing works are based on time-division multiplexing. This means that only a single transmit/receive channel is active in each time slot. In this paper, we introduce a panel-to-panel model in a multistatic structure. Based on this model, two pre-processing (for two different individually measured signal and combined measured signal (CMS) scenarios) are derived to convert the raw measurements into the space-frequency domain. Then, by using the output data from the pre-processing stage and according to the configuration of the introduced imaging system, the range migration algorithm is adapted. The importance of the proposed solution for the CMS scenario is that, for the first time, it demonstrates the capability of using dynamic metasurface antennas diversity to achieve simultaneous data acquisition. The performance of the proposed approach is compared with state-of-art works in terms of reconstructed image quality and computational complexity using numerical simulations and analytical discussions.

Dynamic Metasurface Antennas for MIMO-OFDM Receivers With Bit-Limited ADCs

The combination of orthogonal frequency modulation (OFDM) and multiple-input multiple-output (MIMO) techniques plays an important role in modern communication systems. In order to meet the growing throughput demands, future MIMO-OFDM receivers are expected to utilize a massive number of antennas, operate in dynamic environments, and explore high frequency bands, while satisfying strict constraints in terms of cost, power, and size. An emerging technology to realize massive MIMO receivers of reduced cost and power consumption is based on dynamic metasurface antennas (DMAs), which inherently implement controllable compression in acquisition. In this work we study the application of DMAs for MIMO-OFDM receivers operating with bit-constrained analog-to-digital converters (ADCs). We present a model for DMAs which accounts for the configurable frequency selective profile of its metamaterial elements, resulting in a spectrally flexible hybrid structure. We then exploit previous results in task-based quantization to show characterized the achievable OFDM recovery accuracy for a given DMA configuration in the presence of bit-constrained ADCs, and propose methods for adjusting the DMA parameters based on channel state information. Our numerical results demonstrate that by properly exploiting the spectral diversity of DMAs, notable performance gains are obtained over existing designs of conventional hybrid architectures, demonstrating the potential of DMAs for realizing high performance massive antenna arrays of reduced cost and power consumption.

A High-Efficiency Reconfigurable Element for Dynamic Metasurface Antenna

A high-efficiency reconfigurable element for dynamic metasurface antennas (DMA), consisting of a complimentary electric-LC (CELC) resonator fed through the cavity from a waveguide slot, is proposed in this paper, with positive- intrinsic-negative (PIN) diodes loaded to realize the coding performance. To begin with, the low efficiency problem of a traditional CELC element is demonstrated before the introduction of the proposed element. Subsequently, an equivalent circuit is illustrated to analyse the resonant performance, with extensive parametric study for verification. The proposed element has a low ohmic loss when the diode is switched on, 25 times less than the traditional element. Furthermore, the radiation efficiency of a DMA with 10 proposed elements is compared with a traditional design, showing a significant efficiency improvement from 25% to 75% when half diodes are switched on. Finally, measurements are conducted to verify the feasibility of the dynamic element to achieve radiation ON and OFF states, showing a 12 dB radiation gain difference between two states.

Dynamic Metasurface Antennas for Higher-order MIMO Systems in Indoor Environments

We propose a MIMO system using a dynamic cavity-backed metasurface antenna (DMA) as a transmit antenna to improve the channel capacity of indoor MIMO channels. The DMA is a printed cavity loaded with tunable metamaterial radiators and fed by radio frequency ports. The DMA can generate radiation patterns that are adaptive to MIMO channels by individual tuning of the metamaterial radiators. In this letter, we study a 4 $\times $ 4 MIMO system operating at 5.9 GHz, consisting of a simulated DMA as transmit antenna and a linear dipole array as receive antenna. Using a ray tracing technique, we simulate indoor MIMO channels and compute MIMO channel capacity at different receiver locations. We demonstrate that the adaptive radiation pattern generated by the DMA can increase the channel capacity. The MIMO system using the DMA can be low cost and low in power consumption, and can find applications where bandwidth, power, and cost represent constraints.

Dynamic Metasurface Antennas for Uplink Massive MIMO Systems

Massive multiple-input-multiple-output (MIMO) communications are the focus of considerable interest in recent years. While the theoretical gains of massive MIMO have been established, implementing MIMO systems with large-scale antenna arrays in practice is challenging. Among the practical challenges associated with massive MIMO systems are increased cost, power consumption, and physical size. In this paper, we study the implementation of massive MIMO antenna arrays using dynamic metasurface antennas (DMAs), an emerging technology which inherently handles the aforementioned challenges. Specifically, DMAs realize large-scale planar antenna arrays and can adaptively incorporate signal processing methods such as compression and analog combining in the physical antenna structure, thus reducing the cost and power consumption. First, we propose a mathematical model for massive MIMO systems with DMAs and discuss their constraints compared to ideal antenna arrays. Then, we characterize the fundamental limits of uplink communications with the resulting systems and propose two algorithms for designing practical DMAs for approaching these limits. Our numerical results indicate that the proposed approaches result in practical massive MIMO systems whose performance is comparable to that achievable with ideal antenna arrays.

Single-frequency 3D synthetic aperture imaging with dynamic metasurface antennas.

Through aperture synthesis, an electrically small antenna can be used to form a high-resolution imaging system capable of reconstructing three-dimensional (3D) scenes. However, the large spectral bandwidth typically required in synthetic aperture radar systems to resolve objects in range often requires costly and complex RF components. We present here an alternative approach based on a hybrid imaging system that combines a dynamically reconfigurable aperture with synthetic aperture techniques, demonstrating the capability to resolve objects in three dimensions (3D), with measurements taken at a single frequency. At the core of our imaging system are two metasurface apertures, both of which consist of a linear array of metamaterial irises that couple to a common waveguide feed. Each metamaterial iris has integrated within it a diode that can be biased so as to switch the element on (radiating) or off (non-radiating), such that the metasurface antenna can produce distinct radiation profiles corresponding to different on/off patterns of the metamaterial element array. The electrically large size of the metasurface apertures enables resolution in range and one cross-range dimension, while aperture synthesis provides resolution in the other cross-range dimension. The demonstrated imaging capabilities of this system represent a step forward in the development of low-cost, high-performance 3D microwave imaging systems.

Generalized range migration algorithm for synthetic aperture radar image reconstruction of metasurface antenna measurements

Waveguide-fed dynamic metasurface antennas (DMAs) can be used in a variety of synthetic aperture radar (SAR) modalities for microwave and millimeter-wave imaging. The DMA consists of an electrically large array of resonant, dynamically reconfigurable metamaterial radiators, each excited by the fields of a guided wave. A given metamaterial element can be modeled as a polarizable dipole, with polarizability that equates to a complex weighting factor in the context of antenna array calculations. The DMA produces a sequence of diverse radiation patterns as a function of the weights, which can be rapidly varied by external control. The unconventional radiation patterns of the DMA, however, introduce added computational complexity for traditional SAR processing algorithms. One SAR reconstruction approach that has successfully been adapted for the static (motionless) DMA is the range migration algorithm (RMA). Here, we extend the RMA to scenarios in which the DMA is physically translated in one or two dimensions, deriving the RMA for each case and providing experimental demonstrations using a fabricated microstrip-based DMA. Excellent reconstruction quality is observed in all cases, verifying the efficacy of the proposed algorithms and demonstrating the imaging capabilities of the DMA in the synthetic aperture context. The combination of the DMA platform with efficient reconstruction algorithms can find applications in fields such as Earth observation, security screening, and autonomous vehicle navigation.

Enhanced Resolution Stripmap Mode Using Dynamic Metasurface Antennas

To maintain sufficient signal-to-noise ratio (SNR) for image reconstruction and image interpretation, conventional synthetic aperture radar (SAR) systems must trade off resolution and scene size. This paper proposes a new SAR mode of operation, which improves resolution while maintaining good SNR and a large scene size. It leverages the unique properties of dynamic metasurface antennas (MSAs) to subsample a large virtual beamwidth utilizing multiple small distinct antenna beams. Due to this parallelization in scene sampling, the constraints on the azimuth sampling rate can be relaxed while maintaining an aliasing-free cross range. Due to the versatile properties of MSAs and their cost effective manufacturing process, this paper proposes SAR systems, which can obtain high resolution images over a wide scene size with lower cost and complexity than competing approaches. Point-spread functions and proof-of-concept SAR simulations are shown to verify this approach. In addition, laboratory experiments using a commercial prototype MSA are presented, which show an improvement of 62% in cross-range resolution of the proposed approach, compared with the cross-range resolution of stripmap mode SAR with the same aperture.