High Reconfigurability Research Articles

Photonic microwave frequency divider with a tunable division ratio and harmonic suppression capability

A photonic microwave frequency divider that is capable to realise tunable high order frequency division, is presented. It is based on injecting an RF phase modulated optical signal into an off-the-shelf DFB laser operating at period-N state. Optical frequency components with a frequency separation of 1/N times the input RF signal frequency are generated by the DFB laser. An optical bandpass filter can be employed to select two optical frequency components to be detected by a photodetector to obtain a divide-by-N RF signal without harmonic components. The proposed frequency divider can be operated over a wide frequency range and has high reconfigurability as it is free of electrical components. Experimental results demonstrate the realisation of frequency division operation with a tunable 1/2 to 1/5 division ratio for different input RF signal frequencies of 8 to 20 GHz by adjusting the DFB laser forward bias current. Over 35 dB harmonic component suppression is demonstrated. A proof-of-concept experiment is also set up to show the frequency divider based on an optically injected semiconductor laser is capable to operate at a high input RF signal frequency of 50 GHz and has a tunable high order division ratio of 1/2 to 1/8.

Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems

Human cyber-physical production systems (HCPS) - as an extension of cyber-physical production systems (CPPS) - focus on the human being in the system and the development of socio-technical systems. Humans and therefore anthropogenic behavior have to be integrated into the manufacturing system and its processes. Due to the shift towards customized products, CPPS require high reconfigurability, flexibility and individual manufacturing processes. As a result, the role of and requirements for humans are fundamentally changing, creating the necessity for new interfaces to interact with machines within reconfigurable manufacturing process. Scalable human machine interfaces (HMI) are needed that incorporate emerging technologies as well as allowing mobility for the operator while interacting with different machines. Therefore, new approaches for HMI in the context of CPPS and HCPS are needed, which are simultaneously sufficiently mobile, scalable, and modular as well as human centered. High mobility of HMIs can be ensured by using the 5G communication standard that enables wireless migration of computational resources to an edge server with high reliability, low latency, and high data rates. This paper develops, implements, and evaluates a 5G-based, framework for highly mobile, scalable HMI in CPPS by utilizing the new 5G communication technology. The capabilities of the framework and of the new communication standard are demonstrated and evaluated for a use case, where a brain-computer interface (BCI) is used to control a robot arm. For better accuracy, the BCI is supported by an eye tracker and visual feedback is received via an augmented reality environment, and all devices are embedded via 5G communication. In particular, the influence of 5G communication on the system performance is examined, evaluated, and discussed. For this purpose, experiments are designed and conducted with different network configurations.

Distributed LSTM-based cloud resource allocation in Network Function Virtualization Architectures

The high reconfiguration time of cloud resources in Network Function Virtualization environments has led to the proposal of prediction-based resource allocation algorithms, with extensive use of artificial intelligence techniques. The prediction of processing capacities performed jointly and centrally has proved to be very complex due to the high communication overhead required. For this reason, we propose a distributed prediction technique in which Long Short-Term Memory neural networks exchange only a few weights in order to drastically reduce the communication overhead compared to the centralized case. We propose and investigate three different distributed solutions and show how they allow for low prediction errors.

An RF-Source-Free Reconfigurable Microwave Photonic Radar With High-Resolution and Fast Detection Capability

This paper presents a novel microwave photonic (MWP) radar scheme that is capable of optically generating and processing broadband linear frequency-modulated (LFM) microwave signals without using any radio-frequency (RF) sources. In the transmitter, a broadband LFM microwave signal is generated by controlling the period-one (P1) oscillation of an optically injected semiconductor laser. After targets reflection, photonic de-chirping is implemented based on a dual-drive Mach-Zehnder modulator (DMZM), which is followed by a low-speed analog-to-digital converter (ADC) and digital signal processer (DSP) to reconstruct target information. Without the limitations of external RF sources, the proposed radar has an ultra-flexible tunability, and the main operating parameters are adjustable, including the central frequency, bandwidth, frequency band, and temporal period. In the experiment, a fully photonics-based radar with a bandwidth of 4 GHz is established for high-resolution and fast detection. The results show that a high range resolution reaching ∼1.88 cm, and a two-dimensional (2D) imaging resolution as high as ∼1.88 cm × ∼2.00 cm is achieved with a sampling rate of 100 MSa/s in the receiver. The flexible tunability of the radar is also experimentally demonstrated. The proposed radar scheme features low cost, simple structure, and high reconfigurability, which may pave the way for future multifunction adaptive and miniaturized radars.

Multi-functional tunable ultra-broadband water-based metasurface absorber with high reconfigurability

Promising microwave ultra-broadband water-based metasurface absorbers have attracted increasing attention due to their novel applications in EM radiation prevention, stealth technology, and energy harvesting. In this paper, the proposed water-based metasurface absorber, composed of mushroom-shaped and layer-shaped water with resin shell, can reach over 90% polarization-insensitive and wide-angle absorption from 7.2 to 100 GHz with a relative bandwidth of 173%. Moreover, the proposed absorber is reconfigurable to control the water content, salinity, and type of inside liquid for tunable absorption and infrared radiation with thermally tunable absorption. Since the experimental and simulated ultra-broadband absorption originates from multiple resonances concentrated on the top, the ground-free all-dielectric design is achieved. Furthermore, the proposed curved absorber is fabricated and demonstrated for omnidirectional absorption. The water-based metasurface absorber shows great potential in achieving both microwave and infrared radiation camouflage for practical shaped structures in both civil and military domains.

Magnetically Actuated Reactive Oxygen Species Scavenging Nano‐Robots for Targeted Treatment

Magnetic micro/nanorobots (MagRobots) with unparalleled advantages, including remote mobility, high reconfigurability and programmability, lack of fuel requirement, and versatility, can be manipulated under a magnetic field, which has attracted considerable research attention in the biomedicine. Magnetic materials, as the key components of MagRobots, generate reactive oxygen species (ROS) in vivo to induce tissue/organ damage through Fenton/Fenton‐like reactions, which may hinder the clinical application of MagRobots. Here, the biologically active Prussian blue is generated on the surfaces of MagRobots via an in situ reaction to obtain magnetically actuated ROS‐scavenging nano‐robots (ROSrobots). The generated Prussian blue blocks ROS production and endows the MagRobots with additional functionalities, markedly expanding their potential medical applications. Under the action of a magnetic field, the reconfigurable ROSrobots realize multimode transformation, locomotion, and manipulation in complex environments. Importantly, a simple control method is proposed to achieve movement in 3D geometries to allow the completion of tasks in a complex environment. Furthermore, the osteoarthritis (OA) rat model was employed for proof of concept. Notably, under the guidance of ultrasound imaging, ROSrobots can be accurately injected into the articular cavity to actively target the treatment of OA. This research may further promote the clinical application of MagRobots.

Highly Versatile Broadband RF Photonic Fractional Hilbert Transformer Based on a Kerr Soliton Crystal Microcomb

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr micro-comb source featuring a record low free spectral range of 48.9 GHz, yielding 75 microcomb lines across the C-band. By programming and shaping the comb lines according to calculated tap weights, we demonstrate that the Hilbert transformer can achieve tunable bandwidths ranging from 1.2 to 15.3 GHz, switchable centre frequencies from baseband to 9.5 GHz, and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shift. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement the standard as well as fractional Hilbert transformers with broad and switchable processing bandwidths and centre frequencies, together with high reconfigurability and greatly reduced size and complexity.

Heterogeneous origami-architected materials with variable stiffness

Origami, the ancient art of paper folding, has shown its potential as a versatile platform to design various reconfigurable structures. The designs of most origami-inspired architected materials rely on a periodic arrangement of identical unit cells repeated throughout the whole system. It is challenging to alter the arrangement once the design is fixed, which may limit the reconfigurable nature of origami-based structures. Inspired by phase transformations in natural materials, here we study origami tessellations that can transform between homogeneous configurations and highly heterogeneous configurations composed of different phases of origami unit cells. We find that extremely localized and reprogrammable heterogeneity can be achieved in our origami tessellation, which enables the control of mechanical stiffness and in-situ tunable locking behavior. To analyze this high reconfigurability and variable stiffness systematically, we employ Shannon information entropy. Our design and analysis strategy can pave the way for designing new types of transformable mechanical devices.

Selection of Emission Wavelength of Lasing via a Hybrid Microcavity

In the applications of optical communication and light-matter interaction manipulation, the capability of on-demand lasing output with programmable and continuous wavelength tunability over a broad spectral range under low threshold is key functionality. However, the ability to control multiwavelength lasing characteristics within a small mode volume with high reconfigurability remains challenging. The number of dyes and the emission wavelengths of existing materials always restrict the color gamut. In this Letter, we introduce a selection of emission wavelength laser by injecting Rhodamine 6G solution mixed with $\mathrm{Au}$ nanoparticles in the metal-cladded slab-capillary hybrid microcavity. A mechanism for tuning laser emission wavelengths is designed by manipulating the diameter of $\mathrm{Au}$ nanoparticles in Rhodamine 6G solution. Precision control of distinctive lasing wavelengths and a narrower peak are achieved, along with a stable lasing beam output from both ends of the capillary due to coherent superposition. Our findings offer possibilities for realizing a micro selection of emission wavelength laser from a single overall structure.

Energy-Efficient Non-Von Neumann Computing Architecture Supporting Multiple Computing Paradigms for Logic and Binarized Neural Networks

Different in-memory computing paradigms enabled by emerging non-volatile memory technologies are promising solutions for the development of ultra-low-power hardware for edge computing. Among these, SIMPLY, a smart logic-in-memory architecture, provides high reconfigurability and enables the in-memory computation of both logic operations and binarized neural networks (BNNs) inference. However, operation-specific hardware accelerators can result in better performance for a particular task, such as the analog computation of the multiply and accumulate operation for BNN inference, but lack reconfigurability. Nonetheless, a solution providing the flexibility of SIMPLY while also achieving the high performance of BNN-specific analog hardware accelerators is missing. In this work, we propose a novel in-memory architecture based on 1T1R crossbar arrays, which enables the coexistence on the same crossbar array of both SIMPLY computing paradigm and the analog acceleration of the multiply and accumulate operation for BNN inference. We also highlight the main design tradeoffs and opportunities enabled by different emerging non-volatile memory technologies. Finally, by using a physics-based Resistive Random Access Memory (RRAM) compact model calibrated on data from the literature, we show that the proposed architecture improves the energy delay product by >103 times when performing a BNN inference task with respect to a SIMPLY implementation.

Programmable Rainbow-Colored Optofluidic Fiber Laser Encoded with Topologically Structured Chiral Droplets.

Optofluidic lasers are emerging building blocks with immense potential in the development of miniaturized light sources, integrated photonics, and sensors. The capability of on-demand lasing output with programmable and continuous wavelength tunability over a broad spectral range enables key functionalities in wavelength-division multiplexing and manipulation of light-matter interactions. However, the ability to control multicolor lasing characteristics within a small mode volume with high reconfigurability remains challenging. The color gamut is also restricted by the number of dyes and emission wavelength of existing materials. In this study, we introduce a fully programmable multicolor laser by encapsulating organic-dye-doped cholesteric liquid crystal microdroplet lasers in an optofluidic fiber. A mechanism for tuning laser emission wavelengths was proposed by manipulating the topologically induced nanoshell structures in microdroplets with different chiral dopant concentrations. Precision control of distinctive lasing wavelengths and colors covering the entire visible spectra was achieved, including monochromatic lasing, dual-color lasing, tri-color lasing, and white colored lasing with tunable color temperatures. Our findings revealed a CIE color map with 145% more perceptible colors than the standard RGB space, shedding light on the development of programmable lasers, multiplexed encoding, and biomedical detection.

Elastic Photonic Microcapsules Containing Colloidal Crystallites as Building Blocks for Macroscopic Photonic Surfaces.

Colloidal crystals develop structural colors through wavelength-selective diffraction. Recently, a granular format of colloidal crystals has emerged as building blocks to construct macroscopic photonic surfaces or architectures with high reconfigurability through the secondary assembly. Here, we design elastic photonic microcapsules containing colloidal crystallites along the inner wall as a building block. Water-in-oil-in-water double-emulsion templates are microfluidically prepared to have an aqueous dispersion of polystyrene particles in the inner droplet and polydimethylsiloxane prepolymers in the shell. Colloidal particles are enriched in the presence of depletant and salt by osmotic compression, with the crystallization at the inner interface by depletion attraction. The number of nucleation sites depends on the rate of the enrichment, which enables control over the size and surface coverage of the crystallites with osmotic conditions. The enrichment is ceased by transferring the droplets into an isotonic solution, and the oil shell is cured to form an elastic membrane. As the elastic microcapsules have a large void in the core, they are deformable without structural damage in the crystallites. Therefore, the microcapsules can be closely packed to form macroscopic surfaces while achieving a high quality of structural colors with a collection of crystallites aligned along the flattened membrane.

High frequency meta-ferroelectrics by inverse design

Composites with subwavelength features exhibit effective properties that depend on microstructure morphology and materials, which can be adjusted to obtain enhanced characteristics. We detail the systematic design of electromagnetic metamaterials composed of dielectric inclusions in a ferroelectric matrix that, under an applied voltage, present an optimized effective tunability higher than the bulk due to a nonlinear local electric field enhancement. The effect of volume fraction, losses, and biasing field on homogenized properties is investigated and the analysis of the photonic band diagram is carried out, providing the frequency dependence of the anisotropic effective index and tunability. Such metaceramics can be used in microwave antennas and components with higher reconfigurability and reduced power consumption.

Reshaping the Role of Destination Management Organizations: Heritage Promotion through Virtual Enterprises—Case Study: Bresciatourism

Cooperation in tourism is considered crucial for sustainable destination promotion, addressing several opportunities to decrease the level of competition among actors to achieve advantages for all. Global markets force rapid, virtual teaming up and high reconfigurability through heavy reliance on information and communications technology in the pursuit of specific market opportunities for a destination’s heritage promotion. In light of a reshaped destination management organization role, this work focuses on temporary cooperation and adapts the dynamic virtual enterprise model to tourism. A case history in Brescia was examined to support the theoretical construct. The resulting conceptual schema highlights the main features of a virtual enterprise in tourism (VEt), the life cycle stages—qualified by dynamic adaptation—and the leadership role of the destination management organizations. In generating a VEt model, four conditions for effectiveness emerge.

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.

Due to the huge success and rapid development of convolutional neural networks (CNNs), there is a growing demand for hardware accelerators that accommodate a variety of CNNs to improve their inference latency and energy efficiency, in order to enable their deployment in real-time applications. Among popular platforms, field-programmable gate arrays (FPGAs) have been widely adopted for CNN acceleration because of their capability to provide superior energy efficiency and low-latency processing, while supporting high reconfigurability, making them favorable for accelerating rapidly evolving CNN algorithms. This article introduces a highly customized streaming hardware architecture that focuses on improving the compute efficiency for streaming applications by providing full-stack acceleration of CNNs on FPGAs. The proposed accelerator maps most computational functions, that is, convolutional and deconvolutional layers into a singular unified module, and implements the residual and concatenative connections between the functions with high efficiency, to support the inference of mainstream CNNs with different topologies. This architecture is further optimized through exploiting different levels of parallelism, layer fusion, and fully leveraging digital signal processing blocks (DSPs). The proposed accelerator has been implemented on Intel's Arria 10 GX1150 hardware and evaluated with a wide range of benchmark models. The results demonstrate a high performance of over 1.3 TOP/s of throughput, up to 97% of compute [multiply-accumulate (MAC)] efficiency, which outperforms the state-of-the-art FPGA accelerators.

A Facile Strategy to Achieve Synergistic Multiple Hydrogen Bonding Interactions for Constructing Robust Hydrogels with Self‐healing Capability, Shape Transformation and Actuation Function

AbstractThe double network (DN) hydrogels, especially the physically crosslinked DN hydrogels, have attracted increasing attention due to their high reconfigurability, multi‐sensitivity, and efficient energy dissipation, but their applications still suffer from the relatively low mechanical strength, complex preparation process, and insufficient functionality. In this work, a simple but efficient strategy to fabricate robust and multitasking polyvinyl alcohol (PVA)/poly(N‐acryloyl glycinamide) (PNAGA) DN hydrogels via an ultraviolet (UV)‐initiated one‐pot in situ polymerization and a subsequent freezing‐thawing treatment is reported. The PVA/PNAGA DN hydrogels are fully physically linked DN network via multiple hydrogen bonding interactions, which contain hard PVA crystalline microdomains and soft PNAGA regions. The synergetic multiple hydrogen bonding interactions and the cooperation of hard and soft regions in PVA/PNAGA hydrogels as well as the polyhydroxy matrix can not only impart the PVA/PNAGA hydrogels with super mechanical strength, high toughness, good stretchability, and rapid shape‐recoverability, but also endow the hydrogels with tailorable self‐healability, multiple shape memory, and actuation function. Considering the easily available materials, simple preparation process, and highly multitasking properties, this novel strategy should greatly enrich the methodological toolbox for the synthesis of robust and multifunctional hydrogels for the diversity of applications.

Trends and New Opportunities in Digital Phase-Locked Loop Design: Design Principles, Key Overheads, and New Opportunities in This Emerging Architecture

Phase-locked loop (PLL)-based frequency synthesizers are pervasively utilized in almost every electronic system for generating welldefined clock frequencies of interest. For instance, in a modern wireless transceiver, a radio-frequency (RF) synthesizer is typically used as a local oscillator to upconvert/downconvert the desired signal to and from the proper communication bands. A similar utilization of RF PLL can be seen in a wireline transceiver, which modulates and demodulates the data symbol at a precise frequency and phase. In addition to RF applications, PLL is also commonly used in baseband and digital circuitry, such as generating a sampling clock for switched-capacitor circuits and clocking the sequential logic of the digital circuitry. As the complexity of the modern system-onchip (SoC) platform continues to grow, it is likely to require numerous highperformance PLLs. Moreover, interference coupling through the same silicon substrate is exacerbated. As a result, the low implementation (area and power) cost, high reconfigurability, resilience over interferences, and reduced design time of a PLL have become increasingly important in light of this new trend.

Novel microwave photonic applications based on integrated microcombs (Invited)

Microresonator-based frequency combs (microcombs) are very promising for microwave photonic applications for their advantages including wide bandwidth, large line spacing, and compact volume. Recently, various microcomb-based microwave photonic systems have been reported such as high-spectral-purity microwave generation, microwave photonic signal processing, true-time-delay beamforming, etc. Outstanding performances including low phase noise, high reconfigurability, and large Nyquist bandwidth have been demonstrated, showing a bright future of microcomb-based microwave photonics.

Multiple Master-Slave FPGA Architecture of a Stereo Visual Odometry

Estimating relative camera pose is the key problem of visual odometry (VO). To achieve better efficiency, sparse key-points are usually relied on for the estimation. Yet, feature extraction and matching are still computationally demanding, hindering the overall VO from real-time processing. Exploiting the superiorities of an FPGA in terms of high efficiency, low power consumption, and low cost, this paper proposes a multiple master-slave FPGA architecture for an SIFT-based stereo VO. The master-slave design enables high reconfiguration for the data throughputs among various modules. These modules include SIFT, matching, pose estimation, and their corresponding controllers. In the SIFT module, hardware implemented image pyramid is proposed, where scales are determined off-line via a minimization approach. Local linear exhausted search (LES) matching is considered for both the stereo and the frame matching. In the pose estimation module, a novel hardware design of deriving closest orthogonal matrix for 3D-3D correspondences of relative pose estimation is proposed. Experimental results show that 33.2 fps can be achieved using KITTI dataset without the need of a large number of hardware resources. The proposed reconfigurable design also facilitates its expansions of adopting CCD cameras as well as developing SLAM and other applications.

An SDN architecture for time sensitive industrial IoT

Industrial Internet of Things (IoT) applications have diverse network session requirements. Certain critical applications, such as emergency alert relay, industrial floor evacuation, and surveillance systems, require fresh updates that can maintain the most recently delivered packets. This requires high reconfigurability to an extent where the system can measure the impact of an event and adapt the network accordingly. Several approaches have been proposed that provide high precision transmission and bounded latencies. One prominent solution strategy in the literature is based on Software Defined Networking (SDN) control to resolve latency-related issues, such as congestion, for factory floor transmissions. The OpenFlow protocol is a key interface used in SDN to create a low-latency environment. However, the existing approaches provide only offline solutions that are typically compute intensive. Therefore, this article proposes an algorithm based on simple online strategies that utilize an SDN controller with a global view of the network. More specifically, within the context of the IEEE Time Sensitive Networking (TSN) standards this article: (1) designs a control policy framework called TSNu that guarantees transmission time-slot allocations for Scheduled Traffic while mitigating network congestion, (2) develops a utility maximization approach to jointly optimize scheduling, routing, and admission control while ensuring network stability and maximizing the flow admission to the network, and (3) presents extensive theoretical analysis and simulation to evaluate the proposed TSNu design. The conducted evaluations indicate substantially improved performance compared with state-of-the-art policies.