Showing papers in "Journal of Lightwave Technology in 2019"

Probabilistic Constellation Shaping for Optical Fiber Communications

Abstract: We review probabilistic constellation shaping (PCS), which has been a key enabler for several recent record-setting optical fiber communications experiments. PCS provides both fine-grained rate adaptability and energy efficiency (sensitivity) gains. We discuss the reasons for the fundamentally better performance of PCS over other constellation shaping techniques that also achieve rate adaptability, such as time-division hybrid modulation, and examine in detail the impact of sub-optimum shaping and forward error correction (FEC) on PCS systems. As performance metrics for systems with PCS, we compare information-theoretic measures such as mutual information (MI), generalized MI (GMI), and normalized GMI, which enable optimization and quantification of the information rate (IR) that can be achieved by PCS and FEC. We derive the optimal parameters of PCS and FEC that maximize the IR for both ideal and non-ideal PCS and FEC. To avoid plausible pitfalls in practice, we carefully revisit key assumptions that are typically made for ideal PCS and FEC systems.

An Optical Communication's Perspective on Machine Learning and Its Applications

Abstract: Machine learning (ML) has disrupted a wide range of science and engineering disciplines in recent years. ML applications in optical communications and networking are also gaining more attention, particularly in the areas of nonlinear transmission systems, optical performance monitoring, and cross-layer network optimizations for software-defined networks. However, the extent to which ML techniques can benefit optical communications and networking is not clear and this is partly due to an insufficient understanding of the nature of ML concepts. This paper aims to describe the mathematical foundations of basic ML techniques from communication theory and signal processing perspectives, which in turn will shed light on the types of problems in optical communications and networking that naturally warrant ML use. This will be followed by an overview of ongoing ML research in optical communications and networking with a focus on physical layer issues.

Toward Commercial Polymer Fiber Bragg Grating Sensors: Review and Applications

Abstract: Interest in polymer optical fiber Bragg gratings (POFBGs) arises from the different material properties and sensing modalities brought by polymers relative to silica. Polymer fibers typically offer twice the sensitivity to temperature of conventional silica fiber and increased sensitivity to strain overall. In addition, polymer fibers have higher elastic limits and as a result a larger range of operation for physical constraints. While some polymers are effectively humidity insensitive, others present inherent humidity sensitivity. Their organic properties also allow a variety of chemical processes to create (bio)chemical sensors, with the consequences of fiber breakage in situ being less hazardous than silica. These attributes have led to the use of POFBGs for applications that remain complex using silica fibers. This review paper covers the progress toward commercialization and the increasing number of specific applications.

Probabilistic Shaping and Forward Error Correction for Fiber-Optic Communication Systems

Abstract: This tutorial paper provides a foundation for integrating probabilistic shaping (PS) and forward error correction (FEC). A layered PS-FEC architecture consisting of a PS encoder and an FEC encoder is introduced, of which probabilistic amplitude shaping is a practical instance. Achievable PS encoding rates and achievable FEC decoding rates are derived using information-theoretic arguments. The developed tools are applied to the design and performance assessment of optical transponders based on measurements from optical transmission experiments.

A 128 Gb/s PAM4 Silicon Microring Modulator With Integrated Thermo-Optic Resonance Tuning

Abstract: We report the first demonstration of a silicon photonic microring modulator with modulation data rate up to 128 Gb/s (64 Gbaud PAM4). The microring modulator exhibits an electro-optic phase efficiency of V $_\pi \cdot$ L = 0.52 V $\cdot$ cm, an electro-optic bandwidth of 50 GHz, and a measured transmitter dispersion eye closure quaternary of 3.0 dB at this data rate. In addition, the resonant wavelength of the microring modulator can be tuned across a full free spectral range using an integrated heater with a thermo-optic phase efficiency of 19.5 mW $/\pi$ -phase shift.

15.73 Gb/s Visible Light Communication With Off-the-Shelf LEDs

Abstract: Visible light communication (VLC) can provide high-speed data transmission that could alleviate the pressure on the conventional radio frequency spectrum with the looming capacity crunch for digital communication systems In this paper, we present experimental results of a VLC system with a data rate of 1573 Gb/s after applying forward error correction coding over a 16 m link Wavelength division multiplexing is utilized to efficiently modulate four wavelengths in the visible light spectrum Four single color low-cost commercially available light emitting diodes (LEDs) are chosen as light sources This confirms the feasibility and readiness of VLC for high-data rate communication Orthogonal frequency division multiplexing (OFDM) with adaptive bit loading is used The system with the available components is characterized and its parameters, such as LED driving points and OFDM signal peak-to-peak scaling factor, are optimized To the best of our knowledge, this is the highest data rate ever reported for LED-based VLC systems

Advanced Adaptive Photonic RF Filters with 80 Taps Based on an Integrated Optical Micro-Comb Source

Abstract: We demonstrate a photonic radio frequency (RF) transversal filter based on an integrated optical micro-comb source featuring a record low free spectral range of 49 GHz, yielding 80 micro-comb lines across the C -band. This record high number of taps, or wavelengths for the transversal filter results in significantly increased performance including a Q RF factor more than four times higher than previous results. Furthermore, by employing both positive and negative taps, an improved out-of-band rejection of up to 48.9 dB is demonstrated using a Gaussian apodization, together with a tunable center frequency covering the RF spectra range, with a widely tunable 3-dB bandwidth and versatile dynamically adjustable filter shapes. Our experimental results match well with theory, showing that our transversal filter is a competitive solution to implement advanced adaptive RF filters with broad operational bandwidth, high frequency selectivity, high reconfigurability, and potentially reduced cost and footprint. This approach is promising for applications in modern radar and communications systems.

DeepRMSA: A Deep Reinforcement Learning Framework for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks

Abstract: This paper proposes DeepRMSA, a deep reinforcement learning framework for routing, modulation and spectrum assignment (RMSA) in elastic optical networks (EONs). DeepRMSA learns the correct online RMSA policies by parameterizing the policies with deep neural networks (DNNs) that can sense complex EON states. The DNNs are trained with experiences of dynamic lightpath provisioning. We first modify the asynchronous advantage actor-critic algorithm and present an episode-based training mechanism for DeepRMSA, namely, DeepRMSA-EP. DeepRMSA-EP divides the dynamic provisioning process into multiple episodes (each containing the servicing of a fixed number of lightpath requests) and performs training by the end of each episode. The optimization target of DeepRMSA-EP at each step of servicing a request is to maximize the cumulative reward within the rest of the episode. Thus, we obviate the need for estimating the rewards related to unknown future states. To overcome the instability issue in the training of DeepRMSA-EP due to the oscillations of cumulative rewards, we further propose a window-based flexible training mechanism, i.e., DeepRMSA-FLX. DeepRMSA-FLX attempts to smooth out the oscillations by defining the optimization scope at each step as a sliding window, and ensuring that the cumulative rewards always include rewards from a fixed number of requests. Evaluations with the two sample topologies show that DeepRMSA-FLX can effectively stabilize the training while achieving blocking probability reductions of more than 20.3% and 14.3%, when compared with the baselines.

Machine Learning With Neuromorphic Photonics

Abstract: Neuromorphic photonics has experienced a recent surge of interest over the last few years, promising orders of magnitude improvements in both speed and energy efficiency over digital electronics. This paper provides a tutorial overview of neuromorphic photonic systems and their application to optimization and machine learning problems. We discuss the physical advantages of photonic processing systems, and we describe underlying device models that allow practical systems to be constructed. We also describe several real-world applications for control and deep learning inference. Finally, we discuss scalability in the context of designing a full-scale neuromorphic photonic processing system, considering aspects such as signal integrity, noise, and hardware fabrication platforms. The paper is intended for a wide audience and teaches how theory, research, and device concepts from neuromorphic photonics could be applied in practical machine learning systems.

Passive Optical Networks for 5G Transport: Technology and Standards

Abstract: As the ink is drying on 5G New Radio standards, the industry is now setting its sight on specifying the transport network layer to support 5G deployments. Among the contending technologies, passive optical networks (PONs) stand out as an attractive choice because of the point-to-multipoint topology for efficient use of fiber resources and the wide deployments around the world. In this paper, we review key 5G wireless transport standards, discuss optical access technologies and standards development activities, and finally, highlight several state-of-the-art PON technologies.

Evolution of Radio-Over-Fiber Technology

Abstract: Radio-over-fiber technology provides a simpler pathway for the distribution of wireless signals in broadband wireless networks via optical means. The technology has evolved over the last 30 years, with many challenges already overcome and with many more to address. This paper provides an overview of the technology evolutionary path of RoF with a review of its past, evaluation of its present, and a discussion of its challenges into the future.

Mueller Matrix Polarimetry—An Emerging New Tool for Characterizing the Microstructural Feature of Complex Biological Specimen

Abstract: Recently, with the emergence of new light sources, polarization devices, and detectors, together with a prominent increase in data processing capability, polarization techniques find more and more applications in various areas, one of which is biomedicine. For probing the characteristic features of complex biomedical specimen, Mueller matrix polarimetry has demonstrated distinctive advantages. Mueller matrix polarimetry can be achieved on other optical techniques by adding the polarization state generator and analyzer to their existing optical paths appropriately. Common biomedical optical equipment, such as microscopes and endoscopes, can be upgraded to fulfill Mueller matrix imaging and measurement abilities. Compared with traditional non-polarization optical methods, Mueller matrix polarimetry can provide far more information to characterize the samples, including the anisotropic optical properties, such as birefringence and diattenuation, as well as the distinctive features of various scattering particles and microstructures. Also, Mueller matrix polarimetry is more sensitive to scattering by sub-wavelength microstructures. As a label-free and non-invasive tool, Mueller matrix polarimetry has broad application prospects in biomedical studies and clinical diagnosis. In this review, we provide an introduction to the Mueller matrix methodology, including the Stokes–Mueller formalism, and also the decomposition and transformation methods to derive new parameters. We also summarize the status of the Mueller matrix polarimetric field, including recent improvements, both in instrumentation and data analysis. The current and future applications of Mueller matrix polarimetry in biomedicine are provided and discussed.

One-Dimensional CNN-Based Intelligent Recognition of Vibrations in Pipeline Monitoring With DAS

Abstract: The vibration recognition along the fiber is still a challenging problem in pipeline monitoring with distributed optical-fiber acoustic sensor (DAS), because the burying environments in a wide range are complicated, and there are many different vibration sources interfering at different fiber locations, which are unpredictable and changing from time to time. Conventional machine learning methods with fixed hand-crated feature extraction are always time-consuming and laborious, and the recognition is relying heavily on expert knowledge, which has poor generalization ability. Thus, deep learning algorithms have been tried in this area. However, in this paper, it is found that one-dimensional (1-D) CNN can extract the distinguishable properties of the vibration signals of DAS with better performance and efficiency than the 2-D CNN through real field data experiments. And there are two main increment of the work: First, we try to use an efficient 1-D CNN to replace the 2-D CNN for feature extraction, which can improve the computation efficiency by directly feeding raw or the denoised data without any transformation or other manual work, and using simpler network structure; second, we optimize the classification further by replacing the softmax layer by the support vector machine (SVM) classifier, which is selected optimally from several typical classifiers, such as SVM, random forest, and extreme gradient boosting. Finally, the proposed method (1-D CNN+SVM) can achieve an average recognition accuracy of over 98% for five main classes of typical DAS signals in the oil pipeline monitoring application, which is superior to the conventional machine learning methods with fixed hand-crated feature. At the same time, both accuracy and efficiency of the method are better than those of the 2-D CNN.

Low-Insertion-Loss and Power-Efficient 32 × 32 Silicon Photonics Switch With Extremely High-Δ Silica PLC Connector

Abstract: We fabricate a 32 × 32 silicon photonics switch on a 300-mm silicon-on-insulator wafer by using our complementary metal-oxide-semiconductor pilot line equipped with an immersion ArF scanner and demonstrate an average fiber-to-fiber insertion loss of 10.8 dB with a standard deviation of 0.54 dB, and on-chip electric power consumption of 1.9 W. The insertion loss and the power consumption are approximately 1/60, and less than 1/4 of our previous results, respectively. These significant improvements are achieved by design and fabrication optimization of waveguides and intersections on the chip, and by employing a novel optical fiber connector based on extremely-high-Δ silica planar-lightwave-circuit (PLC) technology. The minimum crosstalk was −26.6 dB at a wavelength of 1547 nm, and −20-dB crosstalk bandwidth was 3.5 nm. Furthermore, we demonstrate low-crosstalk bandwidth expansion by using output port exchanged element switches. We achieve a −20 dB crosstalk bandwidth of 14.2 nm, which is four-times wider than that of the conventional element switch based 32 × 32 switch.

A Closed-Form Approximation of the Gaussian Noise Model in the Presence of Inter-Channel Stimulated Raman Scattering

Abstract: An accurate, closed-form expression evaluating the nonlinear interference (NLI) power in coherent optical transmission systems in the presence of inter-channel stimulated Raman scattering (ISRS) is derived. The analytical result enables a rapid estimate of the signal-to-noise ratio and avoids the need for integral evaluations and split-step simulations. The formula also provides a new insight into the underlying parameter dependence of ISRS on the NLI. Additionally, it accounts for the dispersion slope and arbitrary launch power distributions including variably loaded fiber spans. The latter enables real-time modeling of optical mesh networks. The results is applicable for lumped amplified, dispersion unmanaged, and ultra-wideband transmission systems. The accuracy of the closed-form expression is compared to numerical integration of the ISRS Gaussian noise model and split-step simulations in a point-to-point transmission, as well as in a mesh optical network scenario.

Ultra-Wideband WDM Transmission in S-, C-, and L-Bands Using Signal Power Optimization Scheme

Abstract: Ultra-wideband (UWB) wavelength division multiplexed (WDM) transmission using high-order modulation formats is one of the key techniques to expand the transmission capacity per optical fiber. For UWB systems, the nonlinear interaction caused by inter-band stimulated Raman scattering (SRS) must be considered. Therefore, we have proposed and demonstrated a scheme to optimize the fiber input powers for UWB transmission systems considering the signal power transition caused by the inter-band SRS. We demonstrated a single-mode capacity of 150.3 Tb/s using the proposed power optimization scheme with 13.6-THz UWB in the S-, C-, and L-bands over 40-km transmission. Spectral efficiency of 11.05 b/s/Hz was achieved with 272-channel 50-GHz spaced WDM signals of 45-GBaud polarization division multiplexed 128 quadrature amplitude modulation.

Microwave and RF Photonic Fractional Hilbert Transformer Based on a 50 GHz Kerr Micro-Comb

Abstract: We report a photonic microwave and radio frequency (RF) fractional Hilbert transformer based on an integrated Kerr micro-comb source. The micro-comb source has a free spectral range (FSR) of 50 GHz, generating a large number of comb lines that serve as a high-performance multi-wavelength source for the transformer. By programming and shaping the comb lines according to calculated tap weights, we achieve both arbitrary fractional orders and a broad operation bandwidth. We experimentally characterize the RF amplitude and phase response for different fractional orders and perform system demonstrations of real-time fractional Hilbert transforms. We achieve a phase ripple of <0.15 rad within the 3-dB pass-band, with bandwidths ranging from 5 to 9 octaves depending on the order. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a new way to implement high-performance fractional Hilbert transformers with broad processing bandwidth, high reconfigurability, and greatly reduced size and complexity.

Optical Communications for Short Reach

Abstract: Systems modulating, transporting, and detecting lightwaves have evolved tremendously in the past four decades. The first systems, which were relying on intensity modulation with direct detection have little in common with those manufactured today. Not only have optical fibers and electro-optic components drastically improved, systems now employ digital signal processing for its agility and versatility, initially deployed for long-reach communication systems but slowly making its way into systems covering shorter distances. Due to several network transforming reasons, we are now observing needs for massive deployment of fiber-optic transceivers covering distances of only 10 to 100 km but delivering much faster throughputs than those offered by legacy systems targeting these distances while maintaining low cost and power consumption, small foot print and very-low latency. In this paper, we review the evolution of fiber-optic communication systems, from intensity modulation with direct detection to coherent transceivers and digital signal processing-assisted direct detection. We address the main impairments preventing large bitrate-reach products for systems relying on intensity modulation with direct detection. We present a few reasons leading to the recent surge of the short-reach transceiver market segment, especially transceivers covering distances between 10 to 100 km. We summarize a few proposals for this market modulating and recovering an increasing number of degrees of freedom of the lightwave while maintaining self-beating direct detection. We conclude with remarks on the use of coherent technologies to address this market segment.

Optics in Computing: From Photonic Network-on-Chip to Chip-to-Chip Interconnects and Disintegrated Architectures

Abstract: Following a decade of radical advances in the areas of integrated photonics and computing architectures, we discuss the use of optics in the current computing landscape attempting to redefine and refine their role based on the progress in both research fields. We present the current set of critical challenges faced by the computing industry and provide a thorough review of photonic Network-on-Chip (pNoC) architectures and experimental demonstrations, concluding to the main obstacles that still impede the materialization of these concepts. We propose the employment of optics in chip-to-chip (C2C) computing architectures rather than on-chip layouts toward reaping their benefits while avoiding technology limitations on the way to manycore set-ups. We identify multisocket boards as the most prominent application area and present recent advances in optically enabled multisocket boards, revealing successful 40 Gb/s transceiver and routing capabilities via integrated photonics. These results indicate the potential to bring energy consumption down by more than 60% compared to current QuickPath Interconnect (QPI) protocol, while turning multisocket architectures into a single-hop low-latency setup for even more than four interconnected sockets, which form currently the electronic baseline. We go one step further and demonstrate how optically-enabled eight-socket boards can be combined via a 256 × 256 Hipoλaos Optical Packet Switch into a powerful 256-node disaggregated system with less than 335 ns latency, forming a highly promising solution for the latency-critical rack-scale memory disaggregation era. Finally, we discuss the perspective for disintegrated computing via optical technologies as a mean to increase the number of synergized high-performance cores overcoming die area constraints, introducing also the concept of cache disintegration via the use of future off-die ultrafast optical cache memory chiplets.

Toward a New Generation of Radar Systems Based on Microwave Photonic Technologies

Abstract: This paper reviews on the latest advances in microwave photonics applied to radar systems, tracing the evolutions of functionalities in the photonic radar toward a new generation of enhanced-performance systems. Photonics is demonstrated to enable a new generation of miniaturized, heterogeneous, and distributed radars, i.e., future radars on chip with different features, working in different radio spectral regions, and organized in spatially distributed sensors for the enhanced detection of a wider range of target properties. In these systems, the use of photonics assures benefits in terms of frequency flexibility, accuracy, and computational load reduction. Innovative capabilities supported by the photonic approach are presented, such as the use of coherent sparse bands for the synthesis of ultrawide bands, the use of distributed sensors for multiple-input multiple-output detections, and the use of an ultrawide band photonics-based receiver for radio frequency spectrum scanning. The presented novel concepts will open the way to new research activities both in photonic technology and radar systems, contributing to the development of a new generation of remote sensing systems. This expanding cross fertilization will lead to exciting and challenging research activities in the years to come.

A BaTiO 3 -Based Electro-Optic Pockels Modulator Monolithically Integrated on an Advanced Silicon Photonics Platform

Abstract: To develop a new generation of high-speed photonic modulators on silicon-technology-based photonics, new materials with large Pockels coefficients have been transferred to silicon substrates. Previous approaches focus on realizing stand-alone devices on dedicated silicon substrates, incompatible with the fabrication process in silicon foundries. In this work, we demonstrate monolithic integration of electro-optic modulators based on the Pockels effect in barium titanate (BTO) thin films into the back-end-of-line of a photonic integrated circuit (PIC) platform. Molecular wafer bonding allows fully PIC-compatible integration of BTO-based devices and is, as shown, scalable to 200 mm wafers. The PIC-integrated BTO Mach–Zehnder modulators outperform conventional Si photonic modulators in modulation efficiency, losses, and static tuning power. The devices show excellent V π L (0.2 Vcm) and V π Lα (1.3 VdB), work at high speed (25 Gbps), and can be tuned at low-static power consumption (100 nW). Our concept demonstrates the possibility of monolithic integration of Pockels-based electro-optic modulators in advanced silicon photonic platforms.

A Tutorial on Machine Learning for Failure Management in Optical Networks

Abstract: Failure management plays a role of capital importance in optical networks to avoid service disruptions and to satisfy customers’ service level agreements. Machine learning (ML) promises to revolutionize the (mostly manual and human-driven) approaches in which failure management in optical networks has been traditionally managed, by introducing automated methods for failure prediction, detection, localization, and identification. This tutorial provides a gentle introduction to some ML techniques that have been recently applied in the field of the optical-network failure management. It then introduces a taxonomy to classify failure-management tasks and discusses possible applications of ML for these failure management tasks. Finally, for a reader interested in more implementative details, we provide a step-by-step description of how to solve a representative example of a practical failure-management task.

Simultaneous Measurement of Axial Strain, Bending and Torsion With a Single Fiber Bragg Grating in CYTOP Fiber

Abstract: This paper presents the development of a three-dimensional (3-D) displacement sensor based on one fiber Bragg grating (FBG). In order to obtain higher sensitivity and dynamic range, the FBG is inscribed in low-loss, multimode, cyclic transparent amorphous fluoropolymers using the direct-write, plane-by-plane femtosecond laser inscription method. The proposed sensor is based on the influence of each displacement condition, namely, axial strain, torsion, and bending on the FBG reflection spectrum. Such influence is analyzed with respect to the FBG wavelength shift, reflectivity, and full width half maximum. The operation principle and theoretical background of the proposed approach is numerically analyzed by means of finite element analysis for the strain along the grating length and coupled-mode theory with a modified transfer matrix formulation for the FBG spectrum. The sensor is experimentally characterized and validated in which the results show good agreement between the applied axial strain, bending, and torsion with relative errors below 5.5%. Thus, the proposed sensor is an interesting alternative for measuring displacements in 3-D applications, such as movement analysis and the instrumentation of novel soft robots.

Machine Learning for 100 Gb/s/ λ Passive Optical Network

Abstract: Responding to the growing bandwidth demand by emerging applications, such as fixed-mobile convergence for fifth generation (5G) and beyond 5G, 100 Gb/s/ λ access network becomes the next research focus of passive optical network (PON) roadmap. Intensity modulation and direct detection (IMDD) technology is still considered as a promising candidate for 100 Gb/s/ λ PON attributed to its low cost, low power consumption, and small footprint. In this paper, we achieve 100 Gb/s/ λ IMDD PON by using 20G-class optical and electrical devices due to its commercial availability. To mitigate the system linear and nonlinear distortions, neural network (NN) based equalizer is used and the performance is compared with feedforward equalizer (FFE) and Volterra nonlinear equalizer (VNE). We introduce the rules to train and test the data while using NN-based equalizer to guarantee a fair comparison with FFE and VNE. Random data have to be used for training, but for test, both random data and pseudorandom bit sequence are applicable. We found that the NN-based equalizer has the same performance with FFE and VNE in the case of linear distortion, but outperforms them in a strong nonlinearity case. In the experiment, to improve the loss budget, we increase the launch power to 18 dBm, achieving a 30-dB loss budget for 33 GBd/s PAM8 signal at the system frequency response of 16.2 GHz, attributed to the strong nonlinear equalization capability of NN.

Laser Frequency Combs for Coherent Optical Communications

Abstract: Laser frequency combs with repetition rates on the order of 10 GHz and higher can be used as multi-carrier sources in wavelength-division multiplexing (WDM). They allow replacing tens of tunable continuous-wave lasers by a single laser source. In addition, the comb's line spacing stability and broadband phase coherence enable signal processing beyond what is possible with an array of independent lasers. Modern WDM systems operate with advanced modulation formats and coherent receivers. This introduces stringent requirements in terms of signal-to-noise ratio, power per line, and optical linewidth which can be challenging to attain for frequency comb sources. Here, we set quantitative benchmarks for these characteristics and discuss tradeoffs in terms of transmission reach and achievable data rates. We also highlight recent achievements for comb-based superchannels, including >10 Tb/s transmission with extremely high spectral efficiency, and the possibility to significantly simplify the coherent receiver by realizing joint digital signal processing. We finally discuss advances with microresonator frequency combs and compare their performance in terms of flatness and conversion efficiency against state-of-the-art electro-optic frequency comb generators. This contribution provides guidelines for developing frequency comb sources in coherent fiber-optic communication systems.

Canceling Thermal Cross-Talk Effects in Photonic Integrated Circuits

Abstract: Thermal actuators are among the most consolidated and widespread devices for the active control of photonic integrated circuits (PICs). As a main drawback, mutual thermal crosstalk among actuated devices integrated onto the same photonic chip can affect the working point of the PIC and can reduce the efficiency of automated tuning and calibration procedures. In this paper, a strategy to cancel out the effects of the phase coupling induced by thermal crosstalk is presented. In our technique, we named thermal eigenmode decomposition (TED), all the actuators of the PIC are controlled simultaneously according to the eigensolution of the thermally coupled system. The effectiveness of the TED method is validated by numerical simulations and experiments carried out on coupled microring resonator and switch fabrics of Mach–Zehnder interferometers. With respect to individual control of phase actuators, where thermal crosstalk can hinder the convergence of automated tuning algorithms, with the TED technique convergence is always reached, requires a lower number of iterations, and is less sensitive to the initial state of the PIC. The proposed TED method can be applied to generic tuning and locking algorithm, can be employed in arbitrary PIC architectures and its validity can be extended to systems where phase coupling is induced by other physical effects, such as mutual mechanical stress and electromagnetic coupling among RF lines.

1-Tb/s Millimeter-Wave Signal Wireless Delivery at D-Band

Abstract: We experimentally demonstrate the photonics-aided wireless transmission of 4 × 4 multiple-input multiple-output probabilistic shaping 64-ary quadrature-amplitude-modulation (PS 64QAM) millimeter-wave signals at D-band (110–170 GHz) over 3.1-m distance with a total bit rate of 1.056 Tb/s and a bit-error ratio under 4 × 10−2. The employment of advanced digital-signal-processing techniques, including probabilistic shaping, the Nyquist shaping, and look-up-table predistortion, significantly improves the transmission capacity and distance as well as the system performance. To the best of our knowledge, this is the first time to realize >1-Tb/s millimeter-wave signal wireless delivery.

Ultra-Sensitive Strain Sensor Based on Femtosecond Laser Inscribed In-Fiber Reflection Mirrors and Vernier Effect

Abstract: One of the efficient techniques to enhance the sensitivity of optical fiber sensor is to utilize Vernier effect. However, the complex system structure, precisely controlled device fabrication, or expensive materials required for implementing the technique creates the difficulties for practical applications. Here, we propose a highly sensitive optical fiber strain sensor based on two cascaded Fabry–Perot interferometers and Vernier effect. Of the two interferometers, one is for sensing and the other for referencing, and they are formed by two pairs of in-fiber reflection mirrors fabricated by femtosecond laser pulse illumination to induce refractive-index-modified area in the fiber core. A relatively large distance between the two Fabry–Perot interferometers needs to be used to ensure the independent operation of the two interferometers. The fabrication of the device is simple, and the cavity's length can be precisely controlled by a computer-controlled three-dimensional micromachining platform. Moreover, as the device is based on the inner structure inside the optical fiber, good robustness of the device can be guaranteed. The experimental results obtained show that the strain sensitivity of the device is ∼28.11 pm/μϵ, while the temperature sensitivity achieved is ∼278.48 pm/°C.

High-Sensitivity Fiber-Optic Strain Sensor Based on the Vernier Effect and Separated Fabry–Perot Interferometers

Abstract: A high-sensitivity fiber-optic strain sensor, based on the Vernier effect and separated Fabry–Perot interferometers (FPIs), is proposed and experimentally demonstrated. One air-cavity FPI is used as a sensing FPI (SFPI) and another is used as a matched FPI (MFPI) to generate the Vernier effect. The two FPIs are connected by a fiber link but separated by a long section of single-mode fiber (SMF). The SFPI is fabricated by splicing a section of microfiber between two SMFs with a large lateral offset, and the MFPI is formed by a section of hollow-core fiber sandwiched between two SMFs. By using the Vernier effect, the strain sensitivity of the proposed sensor reaches $\text{1.15 nm/}\mu \varepsilon $ , which is the highest strain sensitivity of an FPI-based sensor reported so far. Owing to the separated structure of the proposed sensor, the MFPI can be isolated from the SFPI and the detection environment. Therefore, the MFPI is not affected by external physical quantities (such as strain and temperature) and thus has a very low temperature cross-sensitivity. The experimental results show that a low-temperature cross-sensitivity of $\text{0.056 } \mu \varepsilon /^ {\circ }{\text{C}}$ can be obtained with the proposed sensor. With its advantages of simple fabrication, high strain sensitivity, and low-temperature cross-sensitivity, the proposed sensor has great application prospects in several fields.

Seamless Convergence of Fiber and Wireless Systems for 5G and Beyond Networks

Abstract: We propose different fronthaul systems for facilitating future mobile networks based on the seamless convergence of fiber-optic and wireless systems in the millimeter-wave (mmWave) bands. First, a flexible and high-performance wireless fronthaul system is proposed through an encapsulation of radio signals onto a converged fiber–mmWave system. A simultaneous transmission of three radio signals over the system is successfully demonstrated. Second, a high-performance optical self-heterodyne system is proposed and demonstrated for the generation and transmission of radio access signals in high-frequency bands. Third, a high-spectral-efficiency optical fronthaul system for the simultaneous transmission of multiple radio signals in different frequency bands is proposed using a subcarrier-multiplexing intermediate-frequency-over-fiber system. Satisfactory performance is experimentally confirmed for the transmission of three different radio signals in the microwave and low- and high-mmWave bands. The proposed systems can overcome the challenges and bottlenecks of the current mobile fronthaul systems and can be useful in different usage scenarios of 5G and beyond networks.