Optical Networks Research Articles

Enhanced Coexistence of Quantum Key Distribution and Classical Communication over Hollow-Core and Multi-Core Fibers.

In this paper, we investigate the impact of classical optical communications in quantum key distribution (QKD) over hollow-core fiber (HCF), multi-core fiber (MCF) and single-core fiber (SCF) and propose wavelength allocation schemes to enhance QKD performance. Firstly, we theoretically analyze noise interference in QKD over HCF, MCF and SCF, such as spontaneous Raman scattering (SpRS) and four-wave mixing (FWM). To mitigate these noise types and optimize QKD performance, we propose a joint noise suppression wavelength allocation (JSWA) scheme. FWM noise suppression wavelength allocation and Raman noise suppression wavelength allocation are also proposed for comparison. The JSWA scheme indicates a significant enhancement in extending the simultaneous transmission distance of classical signals and QKD, reaching approximately 100 km in HCF and 165 km in MCF under a classical power per channel of 10 dBm. Therefore, MCF offers a longer secure transmission distance compared with HCF when classical signals and QKD coexist in the C-band. However, when classical signals are in the C-band and QKD operates in the O-band, the performance of QKD in HCF surpasses that in MCF. This research establishes technical foundations for the design and deployment of QKD optical networks.

Anisotropic van der Waals Tellurene-Based Multifunctional, Polarization-Sensitive, In-Line Optical Device.

Polarization plays a paramount role in scaling the optical network capacity. Anisotropic two-dimensional (2D) materials offer opportunities to exploit optical polarization-sensitive responses in various photonic and optoelectronic applications. However, the exploration of optical anisotropy in fiber in-line devices, critical for ultrafast pulse generation and modulation, remains limited. In this study, we present a fiber-integrated device based on a single-crystalline tellurene nanosheet. Benefiting from the chiral-chain crystal lattice and distinct optical dichroism of tellurene, multifunctional optical devices possessing diverse excellent properties can be achieved. By inserting the in-line device into a 1.5 μm fiber laser cavity, we generated both linearly polarized and dual-wavelength mode-locking pulses with a degree of polarization of 98% and exceptional long-term stability. Through a twisted configuration of two tellurene nanosheets, we realized an all-optical switching operation with a fast response. The multifunctional device also serves as a broadband photodetector. Notably, bipolar polarization encoding communication at 1550 nm can be achieved without any external voltage. The device's multifunctionality and stability in ambient environments established a promising prototype for integrating polarization as an additional physical dimension in fiber optical networks, encompassing diverse applications in light generation, modulation, and detection.

Physical layer encryption-based secure slicing in 5G RAN with hybrid-trusted links

In a 5G radio access network (RAN), network slicing enables dividing a single RAN infrastructure into multiple logical networks, efficiently accommodating services with diverse requirements. Although RAN slicing can help improve resource efficiency and reduce network costs, it is accompanied by various security risks. One of the security threats in RAN slicing is potential eavesdropping, resulting in the leakage of sensitive data within slices. Encryption technologies have been developed to address the eavesdropping problem at different layers in optical networks. We focus on physical layer encryption since it has been demonstrated beneficial in line-speed processing, low latency, and small encryption overhead. The problem of utilizing physical layer encryption technologies to achieve secure RAN slices remains unexplored since physical layer encryption introduces additional hardware costs. In this paper, we study how to realize secure RAN slicing based on physical layer encryption in a metro aggregation network that consists of hybrid-trusted links (i.e., links with different risks for eavesdropping). We propose an integer linear programming (ILP) model and an auxiliary graph-based heuristic for small-scale and large-scale networks, respectively. The objective is to maximize the number of deployed slices and minimize the total cost of secure slice deployment, which includes the costs of servers, line cards (LCs), encryption cards (ECs), and bandwidth resources. To evaluate the benefit of encryption, we compare it with a detour solution, which protects slices by routing through trusted links (i.e., where no additional hardware for encryption is deployed). Simulation results show that the encryption-based solution exhibits a lower cost than the benchmark when the same number of slices are deployed, and it can reduce the blocking ratio by up to 8.5% as slice requests increase. In addition, the average latency of slices is also reduced by up to 14.6%.

Optimal path calculation method of optical network under complex constraints

AbstractTo address the optimal solution problem of loop‐free paths in software‐defined optical networks with multiple complex logical relationships, a unified constraint expression is utilized to describe the constraints. The logical relationships of complex constraints are dissected and simplified, differentiating between “AND” and “OR” constraints. An optimal path calculation method is proposed, involving the transformation of the network topology based on various constraints. This transformation includes layering the topology, removing specific links, and adding necessary links to portray the different complex constraints onto the original network structure. Following the topology transformation, an enhanced K‐shortest path algorithm is employed to compute the route satisfying the combination of multiple complex constraints, resulting in the global optimal solution. Experimental results demonstrate that this method can determine the optimal path under intricate constraints in a single computational iteration without requiring prior knowledge of the optimal constraint sequence. Therefore, it offers significant practical value compared to existing algorithms.

Multi-Scale Flow Estimation Within Stereoscopic PIV Processing Based On Deep Learning

Classical methods of particle-image velocimetry (PIV) based on state-of-the-art cross-correlation algorithms constitute a spatial filtering operation that leads to a loss of spatial resolution of the estimated velocity fields. This is associated with numerous limitations, e.g., when it comes to aligning high-fidelity numerical simulations, since the detection of small turbulent scales is often precluded. An optical flow neural network adapted for PIV processing, called RAFT-PIV, can overcome the drawback of reduced spatial resolution while maintaining the reliability and robustness of the classical approach. The present work aims to extend the application of the aforementioned deep learning based method by integrating it within a stereoscopic PIV processing workflow. Experimental data from an optically accessible single-cylinder combustion engine the flow field of which is characterized by complex, three-dimensional flow structures and a broad range turbulent scales are processed using RAFT-PIV. The 2D-3C vector fields obtained from stereoscopic reconstruction are compared against a classical cross-correlation based PIV evaluation, providing insight into instantaneous quantities and turbulent structures. A qualitative comparison of the instantaneous in-plane and out-of-plane velocity components reveals that the reconstructed flow obtained from the deep learning based estimation includes a wide range of resolved turbulent length scales. It outperforms the classical method. Furthermore, the findings of the present study demonstrate that the pixel accuracy has an effect on both physical quantities and turbulence characteristics. In particular, an increase in turbulent kinetic energy is observed across the engine cycles of the investigated engine flow states. Moreover, a higher fraction of three-dimensional isotropic turbulent structures is derived from RAFT-PIV compared to the results from the cross-correlation based technique.

Wafer-scale fabrication of single-crystalline calcium fluoride thin-film on insulator by ion-cutting

Developing bulk materials into thin-films not only enables multiple physical fields to interact strongly within a smaller volume but also enhances the stability, scalability, and integrability of the system. This transformation has been witnessed to lead to significant improvements in the performance of devices utilizing diverse materials across various fields. Calcium Fluoride (CaF2), with remarkable optical properties such as ultralow optical loss and strong nonlinear features, is a preferable material for building ultra-high-Q resonators and stimulating light-matter interaction with low threshold. However, the integration of CaF2 material has remained elusive due to its low hardness and high thermal expansion, which plagues the large-scale fabrication of CaF2 thin film. Here, an optimized ion-cutting technique is proposed for engineering CaF2 thin films theoretically and experimentally. Taking the thermal expansion into consideration, we employ the Lithium niobate (LN) as substrate, and utilize accessible ion implantation, wafer bonding and precisely designed annealing process to attain the CaF2-LN and the CaF2-on-insulator (CaFOI) with high film thickness uniformity and maintained crystalline quality. The perspectives of our work are also illustrated by numerical simulation for further verifying the potential of integrated photonic applications, which could be extended to monolithic optical network by means of large-scale manufacturing method.

DNN Distributed Inference Offloading Scheme Based on Transfer Reinforcement Learning in Metro Optical Networks

DNN Distributed Inference Offloading Scheme Based on Transfer Reinforcement Learning in Metro Optical Networks

Multi-objective optimization of asymmetric bit rate partitioning for multipath protection in elastic optical networks

In survivable elastic optical networks, multi-path protection combined with traffic squeezing has gained attention. Link-disjoint multipath routing (LD-MPR) and bandwidth squeezing protection (BSP) when applied to the routing, modulation level and spectrum assignment problem are efficient strategies to address the excessive bandwidth demanded by protected services, spectral fragmentation and link-load balancing. LD-MPR enables the division of service transmission bit rate into independent flows, whereas BSP tolerates traffic reduction under link failure. An open issue in the literature is how to efficiently divide demanded traffic among the link-disjoint routes under dynamic-traffic and BSP, while complying the service level agreement (SLA). We propose in this paper a multi-objective-optimization genetic algorithm that defines how service transmission bit rate should be partitioned among the candidate link-disjoint routes. A customized partitioning definition is made for each source–destination node pair in the network, aiming the simultaneous minimization of network blocking probability and average squeezing transmission bit rate experienced by the services during single-link failure. We also propose, a fixed-alternate routing using groups of disjoint paths (FARgdp). Complex dynamic-traffic network scenarios that simultaneously consider BSP, LD-MPR and FARgdp are addressed.

IQ-channel multiplexed DP-4ASK signal using power loading for downlink coherent PON system with access-span length difference

This study explores the integration of dual-polarized (DP) four-level amplitude shift keying (4ASK) signals within an intensity and quadrature division multiplexing framework, mainly focusing on coherent passive optical network (PON) systems. The primary objective is to address the challenges associated with distance disparities in downstream transmissions, which are prevalent in coherent PON architectures. We introduce a novel approach that significantly reduces the power consumption of digital-to-analog converters by implementing power loading strategies tailored explicitly for IQ channel division multiplexing (IQDM)-DP-4ASK signals. Our simulations confirm that ASK standard frequency offset compensation is adaptable to these signals, providing a robust method for managing frequency offsets in a dynamic network environment. Moreover, we propose and empirically validate an energy-efficient adaptive downlink solution capable of supporting 128 Gb/s per optical network unit (ONU), utilizing IQ-imbalanced DP-4ASK signals. This solution is particularly advantageous for systems where the transmission conditions include a 10 km variance in access span lengths between ONUs. Results from our experimental setup demonstrate that reducing the digital-to-analog converter output current for the Q channel by 137 mA is feasible without compromising signal integrity or system performance. Additionally, the research verifies the effectiveness of the automatic bias controller on the transmitter side, ensuring stable operation across varying conditions. Equally, the receiver-side digital signal processing effectively handles polarization separation, illustrating the system's capability to maintain high data integrity and reliability under diverse operational scenarios. These findings highlight the technical feasibility and operational benefits of using IQDM-DP-4ASK signals in coherent PON systems and underscore the potential for significant power savings and enhanced system efficiency in optical networks. The study paves the way for future research into scalable, energy-efficient solutions suitable for high-capacity optical access networks striving for increased sustainability and reduced operational costs.

Design of a tunable metal–insulator-metal power splitter and wavelength demultiplexer for optical interconnect networks

Design of a tunable metal–insulator-metal power splitter and wavelength demultiplexer for optical interconnect networks

Brillouin-based fiber loss measurement for PON using ERA-BOTDA with differential width pairs of frequency-swept pump pulses

We demonstrate Brillouin-based loss distribution measurement for passive optical networks with differential width pairs of frequency-swept pump pulses that can suppress the spatial resolution degradation, especially those created by large loss events typical of an 8-branch splitter. Based on the acoustic wave simulation of a frequency-swept pump pulse, we investigate the arrangement of the modulation frequency within the optical pulse. A preliminary experiment is conducted on a 5-dB loss event near an 8-branch splitter. The results show that the proposed technique can accurately measure loss events with a spatial resolution of better than 3 m.

Optical network noise fluctuation analysis using Markov Reinforcement Attention Fuzzy model

Optical network noise fluctuation analysis using Markov Reinforcement Attention Fuzzy model

Multimode interference coupler based on general interference for integrated optical and quantum optic devices: a review

Integrated optics play important role in the development for optical network devices, optical processing, instrumentation and quantum information device. Here, multimode interference (MMI) coupler is one of basic component preferred for these integrated optic devices in which MMI coupler based on general interference (GIMMI) has been focused for large scale integrated optic devices because of compact size in comparison to MMI coupler based restricted interference (RIMMI). In this paper, we have reviewed different GIMMI structures reported previously. Different waveguide materials are mentioned and compared for fabrication of GIMMI device. The coupling behaviors and modal analysis of GIMMI couplers and their different tapered structures are estimated by using simple model based on sinusoidal modes showing reduced coupling lengths in down tapered structures in comparison to other structures. The excess loss, polarization dependence loss and crosstalk versus fabrication tolerances are obtained to compare their performances revealing almost same losses and fabrication tolerance. The paper reports the use of the GIMMI coupler in wavelength multiplexing, power splitting, switching, optical processing. Finally, Quantum optic application of GIMMI coupler is shown indicating high quantum fidelity of 50:50 coupling ratio.

A Secure Protocol Authentication Method Based on the Strand Space Model for Blockchain-Based Industrial Internet of Things

The rapid development of the Industrial Internet of Things (IIoT) and its application across various sectors has led to increased interconnectivity and data sharing between devices and sensors. While this has brought convenience to users, it has also raised concerns about information security, including data security and identity authentication. IIoT devices are particularly vulnerable to attacks due to their lack of robust key management systems, efficient authentication processes, high fault tolerance, and other issues. To address these challenges, technologies such as blockchain and the formal analysis of security protocols can be utilized. And blockchain-based Industrial Internet of Things (BIIoT) is the new direction. These technologies leverage the strengths of cryptography and logical reasoning to provide secure data communication and ensure reliable identity authentication and verification, thereby becoming a crucial support for maintaining the security of the Industrial Internet. In this paper, based on the theory of the strand space attack model, we improved the Fiber Channel Password Authentication Protocol (FACP) security protocol in the network environment based on symmetric cryptography and asymmetric cryptography. Specifically, in view of the problem that the challenge value cannot reach a consensus under the symmetric cryptography system, and the subject identity cannot reach a consensus under the asymmetric cryptography system, an improved protocol is designed and implemented to meet the authentication requirements, and the corresponding attack examples are shown. Finally, the effectiveness and security of the protocol were verified by simulating different networking environments. The improved protocol has shown an increase in efficiency compared with the original protocol across three different network configurations. There was a 6.43% increase in efficiency when centralized devices were connected to centralized devices, a 5.81% increase in efficiency when centralized devices were connected to distributed devices, and a 6.32% increase in efficiency when distributed devices were connected to distributed devices. Experimental results show that this protocol can enhance the security and efficiency of communication between devices and between devices and nodes (servers, disks) in commonly used Ethernet passive optical network (EPON) environments without affecting the identity authentication function.

Multiplexed All‐Optical Permutation Operations Using a Reconfigurable Diffractive Optical Network

AbstractLarge‐scale and high‐dimensional permutation operations are important for various applications in, for example, telecommunications and encryption. Here, all‐optical diffractive computing is used to execute a set of high‐dimensional permutation operations between an input and output field‐of‐view through layer rotations in a diffractive optical network. In this reconfigurable multiplexed design , every diffractive layer has four orientations: , , , and . Each unique combination of these layers represents a distinct rotation state, tailored for a specific permutation operation. Therefore, a K‐layer rotatable diffractive design can all‐optically perform up to independent permutation operations. The original input information can be decrypted by applying the specific inverse permutation matrix to output patterns. The feasibility of this reconfigurable multiplexed diffractive design is demonstrated by approximating 256 randomly selected permutation matrices using = 4 rotatable diffractive layers. To further enhance its multiplexing capability, input polarization diversity is also utilized. Additionally, this reconfigurable diffractive design is experimentally validated using terahertz radiation and 3D‐printed diffractive layers, providing a decent match to numerical results. The presented rotation‐multiplexed diffractive processor is particularly useful due to its mechanical reconfigurability, offering multifunctional representation through a single fabrication process.

Penerepan Analisis Optical Line Terminal (OLT) Dengan Rasio Spliter dan Pasif Spliter Pada 8 Optical Distribution Point (ODP)

This service aims to analyze the application of Optical Line Terminal (OLT) with splitter and passive splitter ratios at eight Optical Distribution Points (ODP) in the Fiber To The Home (FTTH) network. Through distance measurements, observations, and analysis of the power link budget and rise time budget, this research evaluates the performance of the FTTH network and determines the optimal configuration for the OLT and splitter. The results show that proper OLT settings and splitter ratios can significantly improve optical network performance. These findings provide practical guidance for internet service providers in designing efficient and reliable FTTH networks.

Phase-locking-free all-optical matching system for 100 Gbaud QPSK optical signal

Photonic firewall is a monitoring protection device that will directly detect and locate optical network attacks at the optical layer, which can effectively ensure the security of optical networks. An all-optical matching system is the core part of photonic firewall, which determines the performance of a photonic firewall, so it is of great significance to research and develop all-optical matching system for high-speed and high-order modulation formats signals. At present, an all-optical matching system for binary modulation formats is relatively mature, but the all-optical matching system for high-order phase modulation format signals is still limited by how to solve the problem of phase synchronization. In this paper, a new all-optical matching system based on self-interference matching is proposed for quadrature phase shift keying (QPSK) optical signal, which avoids the introduction of local target sequence optical signals and phase-locking circuits. The theoretical analysis and simulation verification are conducted for the designed system. The results demonstrate that the system can accurately identify and locate 4-symbol or 8-symbol target sequences in the input QPSK optical signals with 16-symbol and 32-symbol data sequences at a data rate of 100 Gbaud.

Investigating pseudo parabolic dynamics through phase portraits, sensitivity, chaos and soliton behavior

This research examines pseudoparabolic nonlinear Oskolkov-Benjamin-Bona-Mahony-Burgers (OBBMB) equation, widely applicable in fields like optical fiber, soil consolidation, thermodynamics, nonlinear networks, wave propagation, and fluid flow in rock discontinuities. Wave transformation and the generalized Kudryashov method is utilized to derive ordinary differential equations (ODE) and obtain analytical solutions, including bright, anti-kink, dark, and kink solitons. The system of ODE, has been then examined by means of bifurcation analysis at the equilibrium points taking parameter variation into account. Furthermore, in order to get insight into the influence of some external force perturbation theory has been employed. For this purpose, a variety of chaos detecting techniques, for instance poincaré diagram, time series profile, 3D phase portraits, multistability investigation, lyapounov exponents and bifurcation diagram are implemented to identify the quasi periodic and chaotic motions of the perturbed dynamical model. These techniques enabled to analyze how perturbed dynamical system behaves chaotically and departs from regular patterns. Moreover, it is observed that the underlying model is quite sensitivity, as it changing dramatically even with slight changes to the initial condition. The findings are intriguing, novel and theoretically useful in mathematical and physical models. These provide a valuable mechanism to scientists and researchers to investigate how these perturbations influence the system’s behavior and the extent to which it deviates from the unperturbed case.

An architecture to improve performance of software-defined optical networks

The software-defined optical network (SDON) is a revolutionary approach in the field of optical networks. The separation of the control plane and data plane in software-defined networking (SDN) provides enhanced security and simplified network administration. Nevertheless, performance and control plane scalability are significant issues in SDN. SDN performance can be evaluated using parameters such as burst loss, delay, channel occupancy, packet loss, throughput, and average response time. The number of messages exchanged between the data plane and the control plane is used as a metric to determine controller scalability. As the network load increases, the controller experiences a higher flow of messages. It causes delay and burst loss in transmitting the burst. Occasionally, bursts exceed the capacity of the fixed-sized burstifier and are discarded because it takes a long time to identify a suitable route for the burst. Hence, it is essential to minimize the volume of messages exchanged between the control plane and the data plane to improve performance and controller scalability. In this paper, we propose a scalable SDN optical network architecture that minimizes the number of messages exchanged between the data plane and the control plane. We proposed mechanisms like channel reservation, transmission cycles, and guard time between cycles to enhance both the speed and the quality of burst transmission. Prior to transmission, resources or channels are allocated to bursts to minimize the possibility of burst collision and loss. The data plane comprises an optical burst switching (OBS) network, and the flow table entries are periodically updated to minimize inter-plane communication. We perform simulations to evaluate and compare the performance of the proposed architecture with the existing state-of-the-art architecture reported in the literature. The proposed architecture performs better than the existing state-of-the-art in terms of metrics including burst loss, delay, channel occupancy, packet loss, throughput, average response time, and reduction in the number of messages exchanged between the data plane and the control plane. Experimental results indicate a 41% reduction in mean burst loss probability and a 40.5% reduction in mean burst sending delay compared to existing architectures. Additionally, 42.1% fewer messages are exchanged between the control plane and the data plane compared to the number of exchanged messages in existing architectures.

End-to-End Data Flows Management in the Decentralized 5G/6G Mobile Networks

The evolution of 5G and the anticipated emergence of 6G networks demand significant enhancements in optical backhaul infrastructure to support higher bandwidth, low latency, and increased reliability. Considering a wide range of feasible applications with different quality requirements, the key challenge for the underlying backhaul and optical transport network is in the high load variance in the optical switching nodes and complicated data flows management. In this paper, a novel approach is proposed for end-to-end data flows management in decentralized 5G/6G mobile networks, which are interconnected by the optical burst switching transport infrastructure. The key idea is to train a deep recurrent neural network over a real network statistic obtain at the different network segments and service slices. Then, predictions made by deep neural network are used for predictive resource allocation in each node of the optical burst switching network to ensure a target quality of service for each end-to-end data flow. The experimental results show that proposed approach provides 90% accuracy of predictions and allows to effectively utilize the resources of optical network.