We demonstrate a novel scheduling approach for implementing QKD in optical access networks. By applying adaptive time-division coordination, we achieve 95% improvements in secret key rate while maintaining acceptable quality-of-service for classical data services.

To satisfy the stringent requirements of emerging broadband services in home networks, a novel Centralized optical and Wi-Fi Access Network (C-WAN) has been proposed within the context of Fiber-to-The-Room (FTTR). In C-WAN, centralized management and control of multiple Wi-Fi access points (APs) deployed in each room are facilitated by relocating portions of Wi-Fi protocols from the APs to a centralized entity. This approach significantly enhances network performance, including throughput and roaming capabilities. However, C-WAN also imposes strict demands on the fronthaul networks, specifically requiring high bandwidth and ultra-low latency. In this context, orthogonal frequency division multiplexing passive optical network (OFDM-PON) emerges as a promising solution to support the C-WAN fronthaul network by allocating dedicated subcarriers to each AP. In C-WAN over OFDM-PON, Wi-Fi stations still contend for access to the wireless channel based on existing Wi-Fi protocols, which may result in prolonged wireless access delays. Consequently, the Quality of Service (QoS) requirements for time-sensitive (TS) services may not be met. Additionally, the variation in maximum Wi-Fi throughput due to the contention-based access mechanism presents a significant challenge for the efficient allocation of optical network resources under stringent delay constraints. To address these issues, we propose a priority-based access mechanism that assigns higher priority to TS services for accessing Wi-Fi channels and obtaining wireless resources. Building on this mechanism, we further develop a Wi-Fi throughput prediction model, which is used to optimize the allocation of optical network resources. Simulation results demonstrate that the proposed scheme can effectively reduce wireless access delay and jitter for TS services, meeting their performance requirements while also improving the utilization of optical network resources.

As quantum computers scale, single-chip architectures face inherent limitations in qubit count. It drives the need for modular quantum computing and Quantum Data Centers (QDCs), where multiple quantum processor units (QPUs) are interconnected to enable the distributed execution of a quantum algorithm. However, evaluating distributed quantum computing (DQC) architectures is challenging. Classical simulation is limited by the growth of exponential state vector, limiting their ability to model large systems and realistically capture hardware noise and timing. Meanwhile, implementing QDC introduces interconnect noise challenges such as transduction inefficiency and optical fiber losses. In this work, we introduce a hardware-based emulation framework by partitioning a single quantum processor's qubit coupling map into multiple logical QPUs. We show how noise arising from transduction and optical fiber can be modeled by adding an ancilla qubit representing the environment based on quantum collisional dynamics. This model is then translated into a gate-based circuit, in which the couplings between each portion act as controllable noisy quantum communication channels. We demonstrate the framework on IBM quantum hardware by executing remote gates under controllable communication noise. To highlight the flexibility of the platform, we further replicate the implementation results of distributed Grover's search on an ion-trap system. Finally, we test a larger circuit, i.e., Grover's search algorithm and the Quantum Fourier Transform (QFT), achieving reasonable fidelity across logical QPUs. Overall, the framework enables hardware-level emulation beyond the limits of classical scaling, captures noise sources through physical qubits, and is compatible with any platform supporting the Qiskit SDK.

Traditional standard single-mode fibers (SSMFs) are unable to satisfy the future long-distance and high-speed optical channel transmission requirement due to their relatively large signal losses. To address this issue, the ultra-low loss and large effective area (ULL) fibers are successfully manufactured and expected to deployed in the existing optical networks. For such ULL fiber deployment, network operators prefer adding ULL fibers to each link rather than replace existing SSMFs, resulting in a scenario where both of SSMF and ULL fiber coexist on the same link. In this paper, we investigated the routing, fiber, modulation format, and spectrum allocation (RFMSA) problem in the context of an elastic optical network (EON) where ULL fiber and SSMF coexisting on each link under both the static and dynamic traffic demands. We formulated this RFMSA problem as a node-arc based Mixed Integer Linear Programming (MILP) model and developed Spectrum Window Plane (SWP)-based heuristic algorithms based on different fiber selection strategies, including spectrum usage based (SU), optical signal-to-noise ratio (OSNR) aware, ULL fiber first (UFF), and random strategies. Simulation results show that in the static traffic demand situation, the RFMSA algorithm based on the OSNR-aware (OA) strategy exhibits optimal performance, attaining a performance similar to that of the MILP model regarding the maximum number of frequency slots (FSs) used in the entire network. Moreover, in the dynamic traffic demand scenario, the SU strategy remarkably surpasses the other strategies in terms of the lightpath blocking probability.

Wi-Fi retransmission mechanism brings stringent latency requirement in fiber in-premises network (G.fin) based centralized Wi-Fi access network (C-WAN) fronthaul. To solve this problem, this paper proposes a cross-layer dynamic bandwidth allocation mechanism, where physical layer information from Wi-Fi preamble can be used for bandwidth allocation in G.fin network. Simulation results show that the upstream latency can be reduced significantly. Under the latency constraints, more network units can also be supported in contrast to benchmarks.

To enhance system bandwidth efficiency while satisfying diverse latency demands in hybrid traffic scenarios, this paper proposes a hybrid bandwidth allocation scheme for 50G time-division multiplexing passive optical networks that integrates directed bandwidth allocation for time-sensitive services with contention-based dynamic allocation for others.

Communication noise from fiber-interconnected distributed quantum systems is quantified through monolithic processor simulations, with experimental results validating this approach as an effective method for evaluating the performance of distributed quantum algorithms. (c) 2025 The Author(s)

In higher-speed passive optical networks (HS-PONs), an upstream dedicated activation wavelength (DAW) is introduced to eliminate the latency caused by periodically creating quiet windows (i.e., time slots) for optical network unit (ONU) activation, thus supporting emerging time-sensitive services. As for the DAW, only part of the bandwidth is reserved for ONU activation, and the remaining bandwidth can still be used to transmit data frames of non-time-sensitive services. However, the existing dynamic bandwidth allocation mechanism tailored for PONs with a single wavelength cannot support cooperative bandwidth scheduling of working and activation wavelengths. In addition, even though transmitting data frames by the DAW can improve the performance in terms of latency and throughput, it brings high energy consumption, especially for the optical digital signal processing function being performed in ONUs. In this paper, we address the above problems by enhancing the existing scheduling protocols for HS-PONs with DAWs to enable bandwidth scheduling of two wavelengths in a unified way, based on which the maximum upstream latencies are further analyzed. Furthermore, we also propose an energy-efficient bandwidth and wavelength allocation scheme, in which the number of operating wavelengths can be reduced while meeting the services’ latency requirements. Simulation results show that the proposed scheme outperforms the benchmarks in terms of energy saving, without affecting the latency constraint, thus well satisfying services’ diverse requirements.

Reconfigurable intelligent surfaces (RISs) have emerged as a promising wireless technology for the 6th generation (6G) wireless systems. Herein, we investigate the joint passive- and hybrid- beamforming (JPHBF) optimization problem in RIS-aided millimeter-wave (mmWave) multi-user MISO (MU-MISO) systems. Furthermore, we introduced codebooks into analog- and passive- beamforming design for low training and feedback overheads. We proposed optical true time delay (OTTD)-based sub-connected hybrid beamforming (SC-HBF) with a low hardware cost and low channel estimation overheads. Compared to the traditional SC-HBF implementation, only about half of the optical true time delay pool based phase control units (OTTDP-PCUs) are required. We design the codebook-based passive- and analog- beamforming (PABF) under the constraints improved by the use of about half of the OTTDP-PCUs and the passive nature of RISs. The results show that the use of multiple RISs significantly improves the sum rate, specifically an improvement of approximately 284.5% at 25 dBm total transmit power. Although only about half of the OTTDP-PCUs are used, the proposed OTTD-based SC-HBF achieves near-optimal sum rates. Moreover, we presented a design example of the optical wavelength matrix used to map the OTTDP-PCUs.

In flexible-rate passive optical networks (PONs), optical network units (ONUs) with different channel conditions can achieve different data rates by implementing flexible transmission parameters, e.g., modulation format, thereby enhancing system capacity. Correspondingly, the downstream frame is divided into multiple subframes, each being received and processed only by ONUs in its targeted group. However, for downstream multicast services, the data need to be duplicated and encapsulated into multiple subframes for ONUs belonging to different groups, resulting in data redundancy and degradation of effective throughput (i.e., throughput without redundant data). To improve resource utilization, ONU grouping should be dynamically adjusted according to both channel conditions and time-varying network factors, e.g., traffic loads and multicast memberships. For this, we first enhance the current downstream scheduling protocol to support dynamic ONU grouping in a multicast scenario and propose a traffic-aware ONU grouping (TAOG) algorithm to improve effective throughput, which optimizes ONU grouping by considering time-varying network conditions. As ONUs belonging to different groups have different data rates, we further propose a group-based downstream time slot allocation (GBDTA) algorithm to adjust time slots for each service by considering their demands and ONU data rates. Exhaustive simulation results show that the integrated TAOG-GBDTA scheme adapts effectively to dynamic network conditions and, compared to conventional schemes, it effectively improves effective throughput, reduces redundancy, and achieves lower packet latency under various multicast scenarios.

This paper proposes a synchronized scheduling mechanism for PON and Wi-Fi, leveraging Wi-Fi 6 deterministic channel access. The mechanism supports centralized Wi-Fi access in FTTR and enables the MFU to allocate air interface resources, thereby significantly reducing STA uplink delay.

With the rapid growth of Internet traffic and new services, demands on access network bandwidth and latency have intensified. Fiber-to-the-Room (FTTR) has emerged as a new architecture for indoor networks, extending fiber directly to users via optical edge gateways. Despite FTTR’s performance benefits, concerns about its equipment’s power consumption have been overlooked. This study investigates FTTR-based home networks, developing models for device power consumption and energy use over time. Results indicate higher power consumption required by FTTR-based networks compared to traditional Wi-Fi networks. To mitigate this, we propose leveraging FTTR’s centralized control for an innovative energy-saving mechanism, enhancing network efficiency and reducing overall energy consumption. Additionally, we explore integrating millimeter-wave technology to further boost energy efficiency through increased transmission capacity.

We propose a service-oriented hybrid fairness scheduling algorithm for downlink visible light communication networks. By incorporating actual service requirements into fairness considerations, it achieves a Jain’s fairness index approaching 1 and effectively reduces average delay.

This paper introduced a unified optical access network that integrates 50G passive optical network (PON) and G.fin, as well as a unified scheduling protocol. The PON bandwidth can be reserved by using scheduling information of G.fin to reduce upstream latency.

Federated Learning (FL) has attracted extensive attention in facilitating emerging edge intelligence applications for its inherent advantages of ensuring data security and privacy. Especially in the edge computing networks connected by Passive Optical Network (PON) system, FL is introduced to enable applications like autonomous driving, intelligent manufacturing, and precision medicine. However, in this system, the FL deployment over PON inevitably faces challenges induced by the conflict between a large volume of model data with the restrict latency limitation and the confined bandwidth resource of PON, especially for the multiple FL tasks. To address these issues, a novel scheme is proposed for tackling the client distribution and bandwidth allocation problems under the scenario of multiple simultaneous FL tasks supported by the multiple interconnected PON systems, which is consisted of the client scheduling and bandwidth slicing processes. To be specific, an easy-to-implement heuristic algorithm is first performed to assign the client numbers to PONs based on iterative method, with which certain operations are repetitively executed to achieve optimal solutions. And then, the serial bandwidth slicing which adapts the traditional policy, i.e., one-task-per-cycle, to the situation with multiple FL tasks, and parallel slicing with the multi-task-per-cycle, are designed for the investigated system. Furthermore, the simulation system is constructed to verify our method. The corresponding results exhibit that, the largest 43.2% round time reduction is achieved by client scheduling compared to benchmark without the scheduling. Compared to the benchmark with serial slicing, our scheme can achieve a maximum 50.11% of the round time decrease. It's also validated that, our proposed client scheduling and parallel bandwidth slicing method can improve the learning efficiency by reducing communication delay, especially for the situation with less client number and smaller FL threshold.

Integrated sensing and communication (ISAC) systems traditionally presuppose that sensing and communication (S&C) channels remain approximately constant during their coherence time. However, a "DISCO" reconfigurable intelligent surface (DRIS), i.e., an illegitimate RIS with random, time-varying reflection properties that acts like a "disco ball," introduces a paradigm shift that enables active channel aging more rapidly during the channel coherence time. In this letter, we investigate the impact of DISCO jamming attacks launched by a DRISbased fully-passive jammer (FPJ) on an ISAC system. Specifically, an ISAC problem formulation and a corresponding waveform optimization are presented in which the ISAC waveform design considers the trade-off between the S&C performance and is formulated as a Pareto optimization problem. Moreover, a theoretical analysis is conducted to quantify the impact of DISCO jamming attacks. Numerical results are presented to evaluate the S&C performance under DISCO jamming attacks and to validate the derived theoretical analysis.

Time Division Multiplexing-Passive Optical Networks (TDM-PONs) play a vital role in Fiber-to-the-Home (FTTH) deployments. To improve the service quality of home networks, FTTH is expanding to the Fiber-to-the-Room (FTTR) scenario, where fibers are deployed to connect individual rooms (i.e., Fiber In-premises Network (FIN) in the ITU-T G.9940 standard). In this scenario, a point-to-multipoint (P2MP) fiber network is deployed as FTTR FIN to offer gigabit access to each room, which forms a two-tier cascaded network together with the FTTH segment. To optimize the capacity utilization of the cascaded network and reduce the overall system cost, a centralized architecture, known as Centralized Fixed Access Network (C-FAN), has been introduced. C-FAN centralizes the medium access control (MAC) modules of both the FTTH and FTTR networks at the FTTH's Optical Line Terminal (OLT) for unified control and management of the cascaded network. We develop a unified bandwidth scheduling protocol by extending the ITU-T PON standard for both the upstream and downstream directions of C-FAN. We also propose a unified dynamic bandwidth allocation (UDBA) algorithm for efficient bandwidth allocation for multiple traffic flows in the two-tier cascaded network. Simulations are conducted to evaluate the performance of the proposed control protocol and the UDBA algorithm. The results show that, in comparison to the conventional DBA algorithm, the UDBA algorithm can utilize upstream bandwidth more efficiently to reduce packet delay and loss, without adversely impacting downstream transmission performance.

In this paper, an STC-SnF approach is presented to schedule bulk data transfers across the CPON. Studies show it can ensure the coordinated space-time relation of bandwidth fragments and hence benefit the SnF scheduling process.

In order to support time-sensitive (TS) services with low latency requirements, this paper proposes a dynamic subcarrier and bandwidth allocation scheme based on transmission containers (T-CONTs) granularity in Time-Frequency Division Multiplexing (TFDM) coherent passive optical network. Simulation results show that the proposed scheme can meet low latency requirements of TS services without sacrificing that of other services and resource utilization.

A SnF scheduling method is presented to schedule data transfers in the HFL aggregation process across the ECPON. Studies demonstrate that the proposed method outperforms conventional methods in terms of network performance and training accuracy.