Fiber-based quantum key distribution (QKD) systems are mature and commercialized, but their integration into existing optical networks is crucial for their widespread use, in particular in passive optical networks (PONs) if end-to-end quantum-secured communications are to be addressed. While discrete-variable QKD coexistence with classical channels is well-studied in point-to-point links, its performance in point-to-multipoint topologies like PONs has received less attention. We thus developed a numerical tool to estimate quantum-available bandwidth and maximum link lengths for QKD systems in single-fiber PON architectures in coexistence with GPON, XG-PON, NG-PON2, and HS-PON standards. The QKD channel performance is obtained by setting thresholds on the quantum bit error rate and the secret key rate, ultimately limited by spontaneous Raman scattering noise and high optical distribution network losses. We perform a comparison between the performance obtained assuming the asymptotic infinite-key generation rate or taking into account actual implementations in the finite-key regime. We evidence that proper design rules can be obtained as a function of both classical and quantum system parameters to support end-to-end quantum security services in existing optical networks.

Effective management of end-to-end 6G network services is crucial, with peak capacity requirements for 6G transport connections expected to exceed 1 Tb/s. As demand for high bandwidth rises, there is a growing necessity for high-capacity optical fiber links, including ultra-wideband (UWB) and multiple fiber links within the network. Scaling up to accommodate these demands, designing wavelength-selective switches (WSSs) for such networks significantly increases the port count. To tackle this issue, we propose various multi-granular optical node (MG-ON) architectures utilizing heterogeneous wavelength, waveband, and spatial switching. We evaluate these architectures’ performance against high-capacity wavelength division multiplexed (WDM) networks through various simulation parameters.

Quality of transmission (QoT) prediction is a fundamental function in optical networks. It is typically embedded within a digital twin and used for operational tasks, including service establishment, service rerouting, and (per-channel or per-amplifier) power management to optimize the working point of services and hence to maximize their capacity. Inaccuracy in QoT prediction results in additional, unwanted design margins. A key contributor to QoT inaccuracy is the uncertain knowledge of fiber insertion loss, e.g., the attenuation due to connector losses at the beginning or at the end of each fiber span, as such loss cannot be directly monitored. Indeed, insertion losses drive the choice of the launch power in fiber spans, which in turn drive key physical effects, including the Kerr and stimulated Raman scattering (SRS) effects, which affect services’ QoT. It is thus important to estimate (and detect possibly anomalous) fiber insertion losses at each span. We thereby propose a novel active input refinement (AIR) technique using active probing to estimate insertion losses in C and C + L systems. Here, active probing consists of adjusting amplifier gains span by span to slightly alter SRS. The amount of adjustment must be sufficient to be measurable (such that insertion losses can be inferred from the measures) but small enough to have a negligible impact on running services in a live network. The method is validated by simulations on a European network with 30 optical multiplex sections (OMSs) in C and C + L configurations and by lab experiments on a C-band network, demonstrating that AIR significantly improves insertion loss estimation, network QoT optimization, and QoT prediction compared with other state-of-the-art monitoring techniques. This work underscores the critical role of accurate estimation of QoT inputs in enhancing optical network performance.

In this work, we experimentally demonstrate a 100Gb/s/λ downstream transmission link for coherent passive optical networks (PONs) up to 50 km, achieving an optical power budget of 29 dB through polarization multiplexing (PolMux) of two 50 Gb/s channels using multiband carrierless amplitude phase modulation (multiCAP) and optical single side band (OSSB) modulation. Additionally, we introduce a separate PolMux 50 Gb/s link that presents an optical power budget of 38.7 dB. Both links have been achieved using a simplified polarization-demultiplexing heterodyne coherent receiver. The robustness of the system is experimentally evaluated by analyzing its response to various input states of polarization. The transmission has been accomplished using 10 GHz electrical bandwidth devices at both the transmission and receiving ends, thereby paving the way for low-cost 100G links suitable for applications such as PONs.

The non-orthogonal multiple access-passive optical network (NOMA-PON) is facing the dual security threats of primary user interference and unauthorized third-party user eavesdropping, so efficient data security enhancement techniques are crucial. To solve these problems, we propose a fixed-point extended (FE)-logistic chaotic mapping to reduce the computational complexity while employing a two-dimensional (2D) cellular automata (CA) and Turing pattern (TP) cascading scramble (CA-TPCS) encryption algorithm to further improve the sensitivity of the NOMA-PON system. The CA-TPCS consists of 2D-CA dynamic bit encryption and Turing symbol substitution (TSS). By using FE chaos to construct 2D-CA and adopting index sort to extract the TSS matrix, dynamic diffusion of bits and scrambling of a 2D symbol matrix are achieved. To ensure the key privacy, we employ a dual key mechanism, and uplink data is introduced as the private key. To verify the feasibility of the proposed method, a simulation validation is built on a 17.6 Gb/s power division multiplexing-orthogonal frequency division multiplexing (PDM-OFDM) NOMA-PON system transmitted over 25 km standard single mode fiber (SSMF). The results show that the proposed scheme has no effect on the optimal power allocation rate (PAR) values and the values are all 3. Meanwhile, the receiver sensitivity gains of 0.2 and 0.3 dB are obtained for high-power and low-power users after encryption. The ciphertext has good diffusion and statistical properties, and the key space is flexibly controlled by the FE precision f, the length l of the transmitted bit, and the size T of the TP, with the value of 22f+l+T×T. The results show that the proposed scheme is not only very compatible with PDM technology but also can realize the dual defense of internal aggression and external aggression. It has a good application prospect in the future NOMA-PON.

Growing capacity requirements are leading to the deployment of multiple fibers in each optical network link. Even though deploying state-of-the-art multi-fiber network architectures with stacked and independent fiber layers simplifies network design and control, spectrum can be used more efficiently if the optical-network nodes allow fiber layers to be interconnected, i.e., if the so-called lane change is enabled. Unfortunately, lane change in high-degree optical nodes requires wavelength selective switches (WSSs) with a high number of ports, which is prohibitively costly or even unfeasible with current WSS technology. Instead, lane change in low-degree optical nodes can be enabled at no extra cost, using WSS ports that are otherwise left empty. In this study, we describe our proposal for a multi-fiber network with partial lane-change capabilities and perform a simulative study to identify the advantages of this architecture, as well as discuss the emerging resource allocation challenges associated with it. We demonstrate that, by enabling lane change in degree-2 nodes, we can increase network throughput by 3% and restore 5%–8% more traffic in the case of single- and double-link failures at no additional equipment cost.

Accurate quality-of-transmission (QoT) estimation tools are crucial to building digital twins (DTs) for optical networks. However, the input-parameter inaccuracy deteriorates the estimation accuracy of the physical models. To address this problem, an input-parameter refinement (IR) paradigm aiming at finding the mappings from uncertain parameters to their corresponding true values is proposed. The primary advantage of the IR paradigm, as demonstrated in this study for Raman amplifiers (RAs), lies in its applicability to dynamic optical networks, where system parameters such as loading conditions and optical device configurations are subject to frequent variations. The use of the proposed paradigm to refine the model of RAs is discussed in detail, while its applicability to other types of devices requires further investigation. The inaccuracy of fiber parameters, signal power, and pump power are taken into account. The particle swarm optimization (PSO) algorithm is utilized to address the problem of the coupling of these parameter inaccuracies. Experiments over a C + L band are conducted. In a single-span scenario, results show the proposed IR scheme can lower the physics-based RA model’s mean prediction error from ∼0.92dB to ∼0.20dB and lower the maximum absolute error (MAE) from ∼3.09dB to ∼1.12dB. The proposed IR scheme also exhibits high precision when applied in a two-span scenario, indicating its scalability to multi-span optical multiplexing section (OMS) scenarios. Furthermore, we demonstrate that the proposed IR scheme can also effectively enhance the accuracy of machine learning (ML) models. An IR-aided ML-based model training scheme is proposed. It offers significant advantages in scenarios where data collection from real systems is limited. With the proposed IR paradigm, the practical application of both physics-based models and ML-based models can be facilitated in future dynamic multiband optical networks.

There is a strong demand for creating primary/backup optical path pairs between a source and a destination node in order to continue a service when the primary path has some disorder. We also have to consider SRLG (shared risk link group)-disjoint primary/backup path settings for achieving robust path protection against possible network problems on primary paths. To deal with these issues, in this study, we use the k-SPF (shortest path first) algorithm to determine primary/backup path routes between a specified source/destination node pair. We demonstrate that the proposed algorithm can find k SRLG-disjoint primary/backup route pairs with much higher probability and with faster speed compared with other algorithms. In addition, the proposed algorithm can find primary/backup routes with nearly minimum route costs.

The advent of 6G is expected to transform connectivity by necessitating robust and scalable transport networks, capable of managing the escalating demands for enhanced bandwidth, negligible latency, and heightened network automation. The progression towards centralized radio access networks and the cloudification of network functions introduce additional requirements to the transport network. Addressing these demands, the integration of packet and optical systems combines packet flexibility with the high bandwidth and low latency of optical systems, aiming for a balance between performance, efficiency, and functionality. This process considers cost and the reuse of existing infrastructure towards a seamless transition to 6G. The concept of a Mini-ROADM, a cost-effective, energy-efficient optical switch created using silicon photonics, is presented and demonstrated in a ring network application. The role of a transport-aware end-to-end orchestrator in coordinating resources across radio, transport, and cloud domains to ensure a diverse range of quality-of-service levels is also discussed. A system demonstrator that highlights the integration of packet and optical layers and the concrete application of these concepts in a network environment is presented.

The proposed architecture advances the concept of network slicing, crucial for beyond 5G services, by enabling dynamic resource allocation and customized partitioning in managed network infrastructures. This architecture addresses the challenges of provisioning end-to-end (E2E) slices across diverse network domains, which is complicated by technological heterogeneity and the variety of vendor solutions. By introducing a standardized transport network solution, we ensure seamless integration, equitable treatment of service requests, and the ability to meet diverse demands. The architecture is centered around a multi-layer transport network slicing architecture, which allows for the division of transport networks into virtual autonomous segments, each tailored for specific services or applications. This segmentation is essential for providing differentiated and personalized 5G services, optimizing network performance, and maximizing resource application. A key component of this architecture is the transport slice controller (TSC), which controls the provision and life-cycle management of transport slices, ensuring a standardized approach in the industry for the definition and realization of slices.