Next-generation Optical Networks Research Articles

Planning tools for next-generation DSP-based passive optical networks above 50G [Invited Tutorial

Next-generation optical access networks are evolving towards ultra-high bit rates (above 50 Gbps per wavelength) and extended fiber reach architectures. This trend will likely push the optoelectronics to their limits, thus requiring impairment compensation based on digital signal processing (DSP) techniques in the transceivers. In this paper, which is an invited follow-up of a tutorial given at ECOC 2023, we first present an overview of this evolving scenario and then propose a unified analytical model that is able to predict the performance of these new systems for both direct-detection and coherent transceiver types. We believe that this model can be useful for preliminary scalability studies of new access architectures (as it happens in international standardization bodies). Moreover, when they are deployed, it can be useful as a base for network planning tools, particularly if future transceivers will be, as expected, highly reconfigurable at the DSP level.

Alamouti-coded DSP algorithm with a simplified PTBC decoder for next-generation optical access networks

The use of Alamouti-coded polarization-time block code (A-PTBC) in combination with a simple single polarization coherent receiver enables phase-diverse coherent detection without any optical polarization tracking. However, applying this technique to high-speed single-carrier systems is not straightforward, as it requires specialized digital signal processing (DSP) algorithms for data recovery, which increases DSP complexity. In this paper, we propose a novel Alamouti-coded coherent algorithm designed to significantly reduce the complexity of the receiver DSP for data recovery. The proposed algorithm achieves the comparable performance to the conventional algorithm but requires only half the number of necessary equalizers for data recovery. We validate its performance through simulations and also experimentally demonstrate a 100 Gb/s 16-quadrature amplitude modulation (QAM) single-carrier coherent system employed the single-polarization coherent receiver over 20 km of standard single-mode fiber (SMF). Through the performance verification, the coherent system with the proposed algorithm exhibits performance comparable to that of the conventional Alamouti-coded coherent system and achieves a power budget of 34 dB when the transmit launch power is set to 7 dBm at a Bit Error Rate (BER) of 1 × 10−2 for 0-20 km fiber transmission.

Optical Add-Drop Multiplexers: Enhancing High Transmission Bit Rates in Next-Generation Communication Networks

The development of optical networks in the telecommunications sector is becoming much closer by considering the help of an Optical Add Drop Multiplexer (OADM) based on a novel technology called Wavelength Division Multiplexing (DWDM). The objective of the current study to examine high transmission bit rates for next-generation optical communication networks using the technology of OADM Based on DWDM. Artificial neural networks (ANNs) were developed via MATLAB software to predict three main parameters in this filed such as transmitted signal power (PT), transmitted signal bandwidth (B.Wsig), and transmission bit rate capacity (Bsh) at different fiber cable lengths, such as L=200, 250, and 300 km. The ANNs results showed that, standard error (SE) for predicting PT as a function of the number of transmitted channels (Nch) was 0.115 mW, 0.095 mW and 0.077 mW, for 200, 250 and 300 km, respectively. Additionally, the SE for predicting B.Wsig was 0.067 GHz, 0.051 GHz and 0.040 GHz for 200, 250 and 300 km, respectively. Lastly, the SE for predicting Bsh was 1.665, 1.311 Gbit/sec and 1.076Gbit/sec for 200, 250 and 300 km, respectively. The SE for predicting PT as a function of the Signal Wavelength (λ) was 0.116, 0.096 and 0.079 mW for 200, 250 and 300 km, respectively. Additionally, the SE for predicting B.Wsig was 0.067, 0.052 and 0.052 GHz for 200, 250 and 300 km, respectively. Lastly, the SE for predicting Bsh was 1.688, 1.417 and 1.110 Gbit/sec for 200, 250 and 300 km, respectively. The low SE in ANNs demonstrated the efficiency, motivating further advancements in optimizing network performance for high-bit-rate transmission.

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

Optical Frequency Comb Generator Employing Two Cascaded Frequency Modulators and Mach–Zehnder Modulator

Optical frequency combs (OFCs) are extensively used in spectroscopy, range finding, metrology, and optical communications. In this paper, we propose a novel technique to achieve a flat OFC by serially cascading two frequency modulators (FMs) followed by a single-drive Mach–Zehnder modulator (MZM). The modulators are driven by a sinusoidal RF signal of frequencies fm, fm2, and 2 fm GHz, respectively. With our proposed approach (fm), an optical spectrum of 71 subcarriers spaced at 4 GHz is realized within a power fluctuation of ∼2 dB. The proposed method is also tested for fm = 16 GHz, showing that this approach can work in all scenarios with lower power fluctuations. In addition, we also studied the impact of the phase of the RF signal on the power variation of the OFC spectrum. A theoretical investigation of the ultra-flat spectrum generated by cascaded FMs and MZM is conducted, and the results of simulations support the findings. The simulation results demonstrate good performance, allowing for the application of our proposed approach in next-generation optical networks.

Dimensioning networks of ROADM cluster nodes

Next-generation optical networks require high-degree, high-capacity reconfigurable optical add-drop multiplexer (ROADM) nodes and intelligent network planning schemes. We propose a cluster ROADM node design and a network dimensioning method that optimizes the resource utilization of optical networks with cluster nodes. The proposed ROADM cluster node offers a flexible add-drop rate, scaling to 100s of degrees, and a cost per degree similar to today’s ROADM. It disaggregates the cluster’s line and add-drop functions into different chassis. The low-cost node architecture is complemented by an order-based connection management algorithm that achieves better than 10−4 blocking despite being equipped with less than 30% dilation in the cluster design. For an optical network with ROADM cluster nodes, we propose a network dimensioning scheme that proactively uses network knowledge to determine the optimum degree for ROADM nodes as demand increases. The results show a much-improved blocking rate, particularly at medium to high loading and an average of 3.1% increased utilization on each network’s fiber compared with reactive schemes.

Routing and Timeslot Scheduling for SPN Fine-Granularity Slices

The integration of 5G and vertical industries promotes the development of the energy Ethernet while putting forward fine granularity, flexibility, high reliability, and deterministic low-latency service requirements for the smart grid and the ubiquitous power Internet of Things (UPIoT). As the bearer architecture supporting the next-generation optical transmission network, the Slicing Packet Network (SPN) slice granularity decreases from 5 Gbps to 10 Mbps fine granularity and the frame period of 5 Gbps large-granularity slices is short, so the non-deterministic delay caused by timeslot conflicts has a negligible impact on the end-to-end delay, and the timeslot scheduling is unnecessary. However, due to the reduction in timeslot granularity and the change in frame structure in 10 Mbps slices, the scheduling of conflicting timeslots and the complex device computing management problems need to be solved urgently. In this paper, we establish a model of routing embedded timeslot scheduling for the routing of fine-granularity slices and timeslot scheduling problems in SPN-based FlexE interfaces, for which we propose a deterministic timeslot allocation mechanism supporting end-to-end low-latency transmission. According to the timeslot symmetry, the mechanism can reduce the space of feasible solutions through ant colony optimization and unidirectional neighborhood search (ACO-UNS), so as to efficiently solve the scheduling of conflicting timeslots and provide end-to-end delay guarantee for delay-sensitive services. Finally, we make a comparison between the ACO-UNS algorithm and the timeslot random dispatching algorithm (ACO-RD); the results show that, relative to the ACO-RD, the reduction in the proposed ACO-UNS is 98.721% for the end-to-end delay of fine-granularity slices.

Machine learning enhanced next-generation optical access networks—challenges and emerging solutions [Invited Tutorial

Optical access networks are envisioned to become increasingly complex as they support more and more diverse and immersive services, each with a different capacity, latency, and reliability need. While machine learning has been touted as a silver bullet that will intelligently manage network operations and resources to meet these demands, as it had been anticipated for core and metro networks, there exist various challenges that need to be addressed to progress machine learning models from research to production. In this tutorial, we first aim to motivate the continued push to advance optical access networks and rationalize the use of machine learning in these networks. We then highlight the challenges that are especially amplified due to the traffic dynamicity and heterogeneity, data scarcity, and computation-resource constraints of optical access networks. We discuss emerging machine learning approaches that are being explored to address these challenges. Finally, we consider a fast and self-adaptive machine learning enhanced dynamic bandwidth allocation scheme in an illustrative future use case of supporting immersive human-to-machine communications over the mobile fronthaul of next-generation mobile networks.

Flexible and adaptive coherent PON for next-generation optical access network [Invited

With the official adoption of the single-wavelength 50G PON standard at the International Telecommunication Union Study Group 15 (ITU-T SG15) meeting, both industry and academia have started extensive research on the next-generation optical access network beyond 50G. It is envisioned that 100G and 200G per wavelength and even beyond will be required in the next-generation optical access network to support the continuously growing bandwidth demands. Coherent passive optical network (C-PON), which is based on multi-access coherent optics and digital signal processing (DSP), appears to be a promising candidate for future 100/200G and even beyond single-wavelength PON, thanks to its superior sensitivity compared with current direct-detection based PONs. Actually, multi-access coherent optics brings many benefits to the optical access network beyond the improvement of sensitivity. In this invited paper, we review recent studies and progress on the flexible C-PON for optical access network in terms of access speed, multiple-access architecture, and deployment scenarios. Rate-adaptive coherent access is first introduced in this paper as a promising solution to achieve flexible C-PON. Adaptive modulation formats based on constellation shaping is highlighted to realize fine granularity of information rate and wide flexibility. We have also discussed the flexible multiplexing schemes beyond TDM, to take the full advantages of coherent access. Finally, we analyze the flexible deployment scenarios under the large power budgets thanks to coherent detection. All these flexibilities provided by coherent access would be interesting and beneficial in the next generation optical access network.

Heterogeneous silicon-on-lithium niobate electro-optic modulator for 100-Gbaud modulation

Integrated lithium niobate (LN) electro-optic (EO) modulators are emerging for applications in next-generation optical fiber communication networks. To date, LN crystal waveguides have led the technology for high-speed modulators. On the other hand, on-chip LN modulators are expected to realize scalable signaling devices with mature complementary metal–oxide–semiconductor technology. In this study, a silicon-loaded LN modulator on the insulator substrate featuring a small footprint, a low driving voltage, and high-speed EO modulation is designed and fabricated. No etching or patterning of the LN is required. The measured halfwave-voltage length product is 1.9 V cm with a static modulation extinction ratio of 17.9 dB. The fabricated LN modulator has a modulation bandwidth of 60 GHz and supports high-speed signaling at a data rate up to 200 Gbit/s.

Si Photonic-Integrated Chip Assembly With Waveguide Ge Avalanche Photodiode for 10 Gbps L-Band Optical Access Networks

The receiving characteristics of the silicon photonic-integrated chip assembly consisting of transimpedance amplifiers and butt-joint waveguide germanium avalanche photodiodes with lateral separated absorption and multiplication (SAM) structures were demonstrated based on conventional complementary metal-oxide-semiconductor processes. We experimentally verified a clear open eye diagram at 10 Gbps with a reverse bias of 17 V. Receiving sensitivities of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$-$</tex-math></inline-formula> 22.8 dBm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$-$</tex-math></inline-formula> 22.0 dBm were obtained for the best and worst polarizations, respectively, with optical signals that had wavelengths longer than those of the absorption edges of Ge at a bit rate of 10 Gbps and a wavelength of 1600 nm. The proposed waveguide butt-joint germanium avalanche photodiodes with lateral SAM structures can be used to receive long wavelengths of downstream signals with low polarization dependence in next-generation optical access network systems.

Degradation Prediction of Semiconductor Lasers Using Conditional Variational Autoencoder

Semiconductor lasers have been rapidly evolving to meet the demands of next-generation optical networks. This imposes much more stringent requirements on the laser reliability, which are dominated by degradation mechanisms (e.g., sudden degradation) limiting the semiconductor laser lifetime. Physics-based approaches are often used to characterize the degradation behavior analytically, yet explicit domain knowledge and accurate mathematical models are required. Building such models can be very challenging due to a lack of a full understanding of the complex physical processes inducing the degradation under various operating conditions. To overcome the aforementioned limitations, we propose a new data-driven approach, extracting useful insights from the operational monitored data to predict the degradation trend without requiring any specific knowledge or using any physical model. The proposed approach is based on an unsupervised technique, a conditional variational autoencoder, and validated using vertical-cavity surface-emitting laser (VCSEL) and tunable edge emitting laser reliability data. The experimental results confirm that our model (i) achieves a good degradation prediction and generalization performance by yielding an F1 score of 95.3%, (ii) outperforms several baseline ML based anomaly detection techniques, and (iii) helps to shorten the aging tests by early predicting the failed devices before the end of the test and thereby saving costs

Characterization, Monitoring, and Mitigation of the I/Q Imbalance in Standard C-Band Transceivers in Multi-Band Systems

Next-generation optical communication networks aim to vastly increase capacity by exploiting a larger optical transmission window covering the S-C-L-band. Simultaneously, the clear market trend is to maximize capacity per wavelength to reduce operational costs. This approach requires an increase in spectral efficiency, resulting in stringent requirements on the transceivers, which may not be satisfied in a multi-band (MB) scenario by current commercial components designed for operation in C-band. Transceiver specifications for MB operation can be relaxed through additional digital signal processing (DSP), at the cost of additional complexity, and by more resource-intensive calibration procedures. In this context, we experimentally characterize the wavelength-dependent frequency-resolved in-phase/quadrature (I/Q) imbalance of a standard C-band IQ-modulator and coherent receiver operating in an S-C-L-band system utilizing receiver-side DSP. This operation allows us to understand the nature of the wavelength-dependency of I/Q imbalance in MB systems. In the considered scenario, we validate the effectiveness of a cost-effective strategy for transceiver impairments mitigation and monitoring based on standard wavelength-independent calibration and reduced-complexity DSP.

Intelligent equally weighted multi-task learning for joint OSNR monitoring and modulation format identification

A novel scheme for combining modulation format identification (MFI) and optical performance monitoring (OPM) in elastic optical networks using convolutional-neural-network-based and equally weighted multi-task learning is proposed. In this scheme, shared features of optical signal-to-noise ratio (OSNR) and modulation formats (10 GBaud QPSK, QAM8, QAM16, QAM64) are extracted from constellation maps and used for multi-label classification. Simulation results demonstrate that the accuracies of MFI and OSNR can reach 100% stably and continuously. Moreover, we evaluated the robustness of this model in a system with fixed physical parameters and concluded that it is tolerant to chromatic dispersion and transmission distance. This technology predicts an image in ∼0.51 ms. Compared with the general multi-task learning (MTL) scheme, the proposed approach massively saves execution time (∼107 h) by removing weight selection. It is time-efficient and intelligent for OPM equipment that will perform multiple monitoring tasks in next-generation optical networks.

Dynamic Subcarrier Assignment in OFDMA-PONs Based on Deep Reinforcement Learning

Orthogonal Frequency Division Multiplexing Access Passive Optical Networks (OFDMA-PONs), a solution for the next-generation optical access network, allows multiple optical network units (ONUs) to dynamically share subcarriers (SCs) to support efficient bandwidth allocation. In uplink transmission, multiple ONUs can share orthogonal low bit rate SCs to transmit data at different time slots (TSs) during the transmission cycle. In this paper, the dynamic subcarrier allocation (DSA) scheme based on deep reinforcement learning (DRL) is proposed for various ONU bandwidth requests. The novel scheme jointly allocates time slots, subcarriers, and modulation formats in a dynamic and flexible manner. The ONU can save transmit power by using a lower order modulation format while meeting the delay requirement. The simulation part demonstrates how the proposed DRL-based DSA scheme can be adapted to various situations, including 1) variation in the size of ONU bandwidth requests, and 2) variation in the weight of different indicators. The extensive simulation results show that, for the first time, the proposed DRL-based DSA algorithm achieves optimal traffic latency with substantial power saving, compared with the traditional two-dimensional DSA algorithms.

Measurement of the Spectral Efficiency of a Heterogeneous Network Architecture of the NG-PON Type for a Quasilinear Propagation Regime.

The objective of future optical fiber networks is to provide an efficient infrastructure capable of supporting an increasing and variable number of data traffic generated by the diversification of applications with different speed requirements that the current legacy Line Speed networks Single Line Rate (SLR), with predefined modulation formats, cannot supply, because they do not offer enough flexibility to meet the requirements of the demands with such a wide range of granularities. Therefore, next-generation optical networks will be highly heterogeneous in nature, incorporating mixed modulation formats and Mixed Line Rates (MLR). In this work, an analysis of the measurement of the spectral efficiency of a heterogeneous network architecture of the next-generation passive optical network (NG-PON) type is reported for a quasilinear propagation regime through the use of the equation adapted from Shannon’s information theory and developed by the group from the GNTT Research of the University of Cauca, where it was found that it is better to transmit channels of 10 Gbps and 40 Gbps with robust modulations in MLR networks to make an improvement in the spectral efficiency of the network, achieving the same amount of information in a smaller bandwidth or more information in the same bandwidth.

Outright fit resource allocation approach for advance reservation requests in elastic optical networks

Elastic optical networks (EONs) are a promising technology for the next-generation optical network, and advanced reservation (AR) applications have been growing expeditiously over the past few years. Thus, the routing and spectrum allocation problem for AR requests has become a significant concern. This paper proposes an approach named outright fit advanced resource reservation to improve the spectral resource allocation efficiency for AR connection requests. Our proposed approach works in two stages: The proposed resource reservation strategy first uses an outright fit resource allocation strategy to reserve the spectral resource for a connection request within the absolute best service window and leaves adequate spectral resources for subsequent requests. If a connection request cannot get resources in the first stage, the proposed optimal rescheduling technique then is applied to serve the request. Our proposed optimal rescheduling technique uses spectrum shifting and reallocation without altering the routing paths, and its optimal characteristic decreases the number of rescheduling operations, thereby decreasing the rescheduling computational complexity and cost, which improves the network’s quality of service. Moreover, this rescheduling approach increases the opportunities for successful rescheduling of the requests without inducing many spectrum fragments, significantly reducing the blocking probability. The simulation results illustrate that the proposed approach can considerably enhance the blocking performance and obtains high spectrum utilization.

Guest Editorial: Next-Generation Optical Access Networks to Support Super-Broadband Services and 5G/6G Mobile Networks

We are pleased to introduce to our readers the following Special Issue (SI) on Next-Generation Optical Access networks to support Super-Broadband Services and 5G/6G Mobile Networks in IEEE Network. In recent years, optical access networks have been playing a growing role in mobile networks and will become even more prominent with 5G/6G due to the demand for extreme bandwidth, coverage, synchronization, and low latency. The success of future mobile networks will not just be about new radio access technologies. The deployment of future wireless technologies will be dependent on the ability of optical access networks to seamlessly connect to radio access networks (RANs) and edge/cloud computing resources. Many technologies are currently being developed for optical networks for convergence and access to increase throughput, improve energy efficiency, and simplify network design, deployment, and operation. This SI is intended to provide recent advances in optical networking technologies, concentrating on optical access networks and the convergence of integrated fiber and wireless access technologies.

Modulation format identification using the Calinski-Harabasz index.

Modulation format identification (MFI) is a key technology in optical performance monitoring for the next-generation optical network, such as the intelligent cognitive optical network. An MFI scheme based on the Calinski-Harabasz index for a polarization-division multiplexing (PDM) optical fiber communication system is proposed. The numerical simulations were carried out on a 28 Gbaud PDM communication system. The results show that the required minimum optical signal-to-noise ratio values of each modulation format to achieve 100% identification accuracy are all equal to or lower than their corresponding 7% forward error correction thresholds, and the proposed scheme is robust to residual chromatic dispersion. Meanwhile, the proposed scheme was further verified by 20 Gbaud PDM-QPSK/16QAM/32QAM long-haul fiber transmission experiments. The results show that the scheme has a good reliability when fiber non-linear impairments exist. In addition, the complexity of the scheme is significantly lower than that of other clustering-based MFI schemes.

Applications of machine learning techniques in next-generation optical WDM networks

Applications of machine learning techniques in next-generation optical WDM networks