Search Results (199)

Faster-than-Nyquist (FTN) tight filtering introduces serious inter-symbol interference (ISI) impairment, leading to an insufficient compensation range for conventional IQ imbalance compensation algorithms. Furthermore, receiver (Rx) IQ imbalance and ISI impairments significantly increase the convergence cost required by the squared Gardner phase detector (SGPD) timing recovery algorithm to establish a timing synchronization loop. This paper proposes a joint Rx IQ compensation and timing recovery scheme. By embedding a two-stage IQ imbalance compensation algorithm into the timing recovery feedback loop, the proposed scheme could effectively estimate and compensate for Rx IQ imbalance. Meanwhile, thanks to the innovative scheme, which equalizes Rx IQ imbalance and ISI during the timing feedback loop, the convergence cost of timing recovery could be reduced compared with the conventional blind frequency domain (BFD) scheme. The simulation results of 128 GBaud polarization multiplexing (PM) 16-quadrature amplitude modulation (QAM) FTN wavelength division multiplexing (WDM) transmission systems demonstrate that the proposed scheme could bring about 14%, 12.5%, and 16.6% improvements in the compensation range for Rx IQ amplitude imbalance, phase imbalance, and skew, respectively, compared with the conventional one. Meanwhile, the convergence cost is reduced by at least 31% with a 0.9 acceleration factor. In addition, 40 GBaud PM-16QAM FTN experiment results show that the proposed scheme could bring about a 0.8 dB improvement in the optical signal noise ratio (OSNR) compared with the conventional BFD scheme. Full article

Waterline extraction is a key step in applying the Waterline Detection Method (WDM) to Digital Elevation Model (DEM) generation. Cloud interference remains a major challenge for achieving high-quality extraction of waterlines. This study developed an image filtering method termed “Cloud Coverage in Region of Interest” (CCROI). By integrating the CCROI method with the Otsu algorithm and noise smoothing techniques, this study enabled high-quality batch and automated extraction of waterlines within the Google Earth Engine (GEE) platform. Using the WDM, DEMs were established to evaluate recent geomorphological changes in the estuarine tidal flats of the abandoned Diaokou Course (ETFADC). The results confirm that the erosional trend of the ETFADC has persisted throughout nearly 50 years of natural adjustment. In areas distant from oil extraction zones, erosion dominates the high-tide zone, while accretion prevails in the low-tide zone, indicating a slope-flattening process. However, in areas near the oil extraction zone, tree-shaped embankments have acted to inhibit erosion rather than exacerbate it, with strong accretion even occurring in wave-sheltered areas. By enhancing the quality of the selected images and reducing the waterline false detection rate, the CCROI method demonstrates significant potential for time-series studies of small regions. Full article

Retinal vessel segmentation in fundus images is critical for diagnosing microvascular and ophthalmologic diseases. However, the task remains challenging due to significant vessel width variation and low vessel-to-background contrast. To address these limitations, we propose WDM-UNet, a novel spatial-wavelet dual-domain fusion architecture that integrates spatial and wavelet-domain representations to simultaneously enhance the local detail and global context. The encoder combines a Deformable Convolution Encoder (DCE), which adaptively models complex vascular structures through dynamic receptive fields, and a Wavelet Convolution Encoder (WCE), which captures the semantic and structural contexts through low-frequency components and hierarchical wavelet convolution. These features are further refined by a Gated Fusion Transformer (GFT), which employs gated attention to enhance multi-scale feature integration. In the decoder, depthwise separable convolutions are used to reduce the computational overhead without compromising the representational capacity. To preserve fine structural details and facilitate contextual information flow across layers, the model incorporates skip connections with a hierarchical fusion strategy, enabling the effective integration of shallow and deep features. We evaluated WDM-UNet in three public datasets: DRIVE, STARE, and CHASE_DB1. The quantitative evaluations demonstrate that WDM-UNet consistently outperforms state-of-the-art methods, achieving 96.92% accuracy, 83.61% sensitivity, and an 82.87% F1-score in the DRIVE dataset, with superior performance across all the benchmark datasets in both segmentation accuracy and robustness, particularly in complex vascular scenarios. Full article

A multi-objective genetic algorithm is tailored to optimize the design of a wavelength interleaver/deinterleaver device. An interleaver combines data streams from two physical channels into one. The deinterleaver does the opposite job. The WDM requirements for this device include channel spacing of 50 GHz, channel bandwidth of 20 GHz, free spectral range of 100 GHz, maximum channel dispersion of 30 ps/nm, and maximum crosstalk of −23 dB. The challenges for the optimization process include the lack of a closed-form expression for the device performance and the trade-off between the conflicting performance parameters. So, for this multi-objective problem, the proposed approach maneuvers to find a compromise between the performance parameters within a few minutes, saving the designer the laborious design process previously proposed in the literature, which relies on visually inspecting the Z-plane for the dynamics of the transmission poles and zeros. Designs of better performance are achieved, with fewer ring resonators, a channel dispersion as low as 1.6 ps/nm, and crosstalk as low as −30 dB. Full article

We developed the Global–Local Integrated Topology inverse design algorithm (denoted as the GLINT algorithm), which employs a trajectory-based optimization strategy with waveguide–substrate material-flipping structural modifications, enabling the direct optimization of discrete waveguide–substrate binary structures. Compared to the conventional Direct Binary Search (DBS), the GLINT algorithm not only significantly enhances computational efficiency through its global search–local refinement framework but also achieves a superior 20 nm × 20 nm optimization resolution while maintaining its optimization speed—substantially advancing the design capability. Utilizing this algorithm, we designed and experimentally demonstrated a 3.5 µm × 3.5 µm dual-port wavelength division multiplexer (WDM), achieving a minimum crosstalk of −11.3 dB and a 2 µm × 2 µm 90-degree bending waveguide exhibiting a 0.31–0.52 dB insertion loss over the 1528–1600 nm wavelength range, both fabricated on silicon-on-insulator (SOI) wafers. Additionally, a 4.5 µm × 4.5 µm three-port WDM structure was also designed and simulated, demonstrating crosstalk as low as −36.5 dB. Full article

Integrated photonics is a transformative technology for enhancing communication and computation in Cloud and Fog computing networks. Photonic integrated circuits (PICs) enable significant improvements in data-processing speed, energy-efficiency, scalability, and latency. In Cloud infrastructures, PICs support high-speed optical interconnects, energy-efficient switching, and compact wavelength division multiplexing (WDM), addressing growing data demands. Fog computing, with its edge-focused processing and analytics, benefits from the compactness and low latency of integrated photonics for real-time signal processing, sensing, and secure data transmission near IoT devices. PICs also facilitate the low-loss, high-speed modulation, transmission, and detection of RF signals in scalable Radio-over-Fiber (RoF) links, enabling seamless IoT integration with Cloud and Fog networks. This results in centralized processing, reduced latency, and efficient bandwidth use across distributed infrastructures. Overall, integrating photonic technologies into RoF, Fog and Cloud computing networks paves the way for ultra-efficient, flexible, and scalable next-generation network architectures capable of supporting diverse real-time and high-bandwidth applications. This paper provides a comprehensive review of the current state and emerging trends in integrated photonics for IoT sensors, RoF, Fog and Cloud computing systems. It also outlines open research opportunities in photonic devices and system-level integration, aimed at advancing performance, energy-efficiency, and scalability in next-generation distributed computing networks. Full article

Leveraging the human brain as a paradigm of energy-efficient computation, considerable attention has been paid to photonic neurons and neural networks to achieve higher computing efficiency and lower energy consumption. This study experimentally demonstrates on-chip silicon photonic neurons and neural networks based on thermally tunable microring resonators (MRRs) implement weighting and nonlinear operations. The weight component consists of eight cascaded MRRs thermally tuned within wavelength division multiplexing (WDM) architecture. The nonlinear response depends on the MRR’s nonlinear transmission spectrum, which is analogous to the rectified linear unit (ReLU) function. The matrix multiplication and recognition task of digits 2, 3, and 5 represented by seven-segment digital tube are successfully completed by using the photonic neural networks constructed by the photonic neurons based on the on-chip thermally tunable MRR as the nonlinear units. The power consumption of the nonlinear unit was about 5.65 mW, with an extinction ratio of about 25 dB between different digits. The proposed photonic neural network is CMOS-compatible, which makes it easy to construct scalable and large-scale multilayer neural networks. These findings reveal that there is great potential for highly integrated and scalable neuromorphic photonic chips. Full article

Infrastructures of access networks that mostly exploit the optical fiber medium effectively utilizing wavelength division multiplexing techniques play a key role in advanced F5G fixed networks. The orbital angular momentum technique is highly promising for use within passive optical networks to further increase transmission capacities. So, the utilization of common network resources in wavelength and optical domains will be more important. The main purpose of this paper is to present an analysis of resource efficiencies for various allocation methods applied in the proposed OAM&WDM-PON architecture with a conventional point-to-multipoint topology. This contribution introduces novel static, dynamic and dynamic customized allocation methods for a proposed network design with the utilization of only passive optical splitters in remote nodes. These WDM and OAM channel allocation methods are oriented towards minimizing the number of working wavelengths and OAM channels that will be used for compliance with customers’ requests for data transmitting in the proposed point-to-multipoint OAM&WDM-PON architecture. For analyzing and evaluating the considered allocation methods, a simulation model related to the proposed P2MP OAM&WDM-PON design realized in the MATLAB (R2022A) programming environment is presented with acquired simulation results. Finally, resource efficiencies of the presented novel allocation methods are evaluated from the viewpoint of application in future OAM&WDM-PONs. Full article

In future hybrid fiber and radio access networks, wavelength division multiplexing passive optical networks (WDM-PON) based fifth-generation (5G) fronthaul systems are anticipated to coexist with current protocols, potentially leading to non-linearity impairment due to stimulated Raman scattering (SRS). To meet the loss budget requirements of 5G fronthaul networks, this paper investigates the power changes induced by SRS in WDM-PON based 5G fronthaul systems. The study examines wavelength allocation schemes utilizing both the C-band and O-band, with modulation formats including non-return-to-zero (NRZ), optical double-binary (ODB), and four-level pulse amplitude modulation (PAM4). Simulation results indicate that SRS non-linearity impairment causes a power depletion of 1.3 dB in the 20 km C-band link scenario, regardless of whether the modulation formats are 25 Gb/s or 50 Gb/s NRZ, ODB, and PAM4, indicating that the SRS-induced power changes are largely independent of both modulation formats and modulation rates. This effect occurs when only the upstream and downstream wavelengths of the 5G fronthaul are broadcast. However, when the 5G fronthaul wavelengths coexist with previous protocols, the maximum power depletion increases significantly to 10.1 dB. In the O-band scenario, the SRS-induced maximum power depletion reaches 1.5 dB with NRZ, ODB, and PAM4 modulation formats at both 25 Gb/s and 50 Gb/s. Based on these analyses, the SRS non-linearity impairment shall be fully considered when planning the wavelengths for 5G fronthaul transmission. Full article

On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a set of sensitivity numerical experiments. The control simulation followed the operational configuration used daily by the Center for Weather and Climate Forecasting Studies of Minas Gerais (CEPreMG). Additional experiments tested the use of different microphysics schemes (WSM3, WSM6, WDM6), initial and boundary conditions (GFS, GDAS, ERA5), and surface datasets (sea surface temperature and soil moisture from ERA5 and GDAS). The model’s performance was evaluated by comparing the simulated variables with those from various datasets. We primarily focused on the representation of the spatial precipitation pattern, statistical metrics (bias, Pearson correlation, and Kling–Gupta Efficiency), and atmospheric instability indices (CAPE, K, and TT). The results showed that none of the simulations accurately captured the amount and spatial distribution of precipitation over the region, likely due to the complex topography and convective nature of the studied event. However, the WSM3 microphysics scheme and the use of ERA5 SST data provided slightly better representation of instability indices, although these configurations still underperformed in simulating the rainfall intensity. All simulations overestimated the instability indices compared to ERA5, although ERA5 itself may underestimate the convective environments. Despite some performance limitations, the sensitivity experiments provided valuable insights into the model’s behavior under different configurations for southeastern Brazil—particularly in a convective environment within mountainous terrain. However, further evaluation across multiple events is recommended. Full article

Free space optics (FSOs) is an emerging technology offering solutions for secure and high data rate transmission in dense urban areas, back haul link in telecommunication networks, and last mile access applications. It is important to investigate the performance of the FSO link as a result of aggregate attenuation caused by different weather conditions in a region. In the present work, empirical models have been derived in terms of visibility, considering fog, haze, and cloud conditions of diverse geographical regions of Delhi, Washington, London, and Cape Town. Mean square error (MSE) and goodness of fit (R squared) have been employed as measures for estimating model performance. The dual polarization-quadrature phase shift keying (DP-QPSK) modulation technique has been employed with hybrid mode and the wave division multiplexing (MDM-WDM) scheme for analyzing the performance of the FSO link with two Laguerre Gaussian modes (LG00 and LG 01) at 5 different wavelengths from 1550 nm to 1554 nm. The performance of the system has been analyzed in terms of received power and signal to noise ratio with respect to the transmission range of the link. Minimum received power and SNR values of −52 dBm and −33 dB have been obtained over the observed transmission range as a result of multiple impairments. Random forest (RF), k-nearest neighbors (KNN), multi-layer perceptron (MLP), gradient boosting (GB), and machine learning (ML) techniques have also been employed for estimating the SNR of the received signal. The maximum R squared (0.99) and minimum MSE (0.11), MAE (0.25), and RMSE (0.33) values have been reported in the case of the GB model, compared to other ML techniques, resulting in the best fit model. Full article

Modern cellular systems rely on high-capacity and low-latency optical networks to meet ever-increasing data demands. Centralized Radio Access Network (C-RAN) architectures offer a cost-effective approach for deploying mobile infrastructures. In this work, we propose a flexible and cost-efficient fronthaul topology that combines Wavelength Division Multiplexing (WDM) passive optical networks (PONs) with free-space optical (FSO) links. To enhance overall system performance, we introduce Low-Density Parity Check (LDPC) decoding, which provides robust error-correction capabilities against atmospheric turbulence and noise. Our system transmits 20 Gbps, 16-QAM intensity-modulated orthogonal frequency-division multiplexing (OFDM) signals, achieving a substantial reduction in bit error rate (BER). Numerical results show that the proposed WDM-PON-FSO architecture, augmented with LDPC decoding, maintains reliable transmission over 2 km under strong turbulence conditions. Full article

In this paper, we present recent advancements in transmitter and receiver technologies for Optical Wireless Communication (OWC). OWC offers very wide license-free optical spectrum which enables very high capacity transmission. Additionally, beam-steered OWC is more power-efficient and more secure due to low divergence of light. One of the main challenges of OWC is wide angle transmission and reception because law of conservation of etendue restricts maximization of both aperture and field of view (FoV). On the transmitter side, we use Micro Electro-Mechanical System cantilevers activated by piezoelectric actuators together with silicon micro-lenses for narrow laser beam steering. Such design allowed us to experimentally demonstrate at least 10 Gbps transmission over 100° full angle FoV. On the receiver side, we show the use of photodiode array, and Indium-Phosphide Membrane on Silicon (IMOS) Photonic Integrated Circuit (PIC) with surface grating coupler (SGC) and array of SGC. We demonstrate FoV greater than 32° and 16 Gbps reception with photodiode array. PIC receiver allowed to receive 100 Gbps WDM with single SGC, and 10 Gbps with an array of SGC which had 8° FoV in the vertical angle and full FoV in the horizontal angle. Our results suggest that solutions presented here are scalable in throughputs and can be adopted for future indoor high-capacity OWC systems. Full article

This work presents a cost-effective optical frequency comb generator (CEOFCG) solution for generating multiple, equally spaced carriers in wavelength-division-multiplexing coherent optical fiber communication systems (WDM-COFCS). It enables the replacement of multiple laser sources with a single continuous-wave laser, eliminating the need for additional amplification and filtering setups. The CEOFCG provides stable multicarrier spacing, broad phase coherence, and compatibility with advanced modulation formats, enhancing the performance of WDM-COFCS. Digital signal processing (DSP) techniques, including digital filtering, detection, and impairment compensation, contribute to high transmission and spectral efficiency (SE). The results demonstrate the potential of CEOFCG in achieving cost reduction, complexity reduction, high SE, and optimal utilization of optical fiber bandwidth, particularly in higher-order QAM-based COFCS. Full article

Underwater image enhancement (UIE) is inherently challenging due to complex degradation effects such as light absorption and scattering, which result in color distortion and a loss of fine details. Most existing methods focus on spatial-domain processing, often neglecting the frequency-domain characteristics that are crucial for effectively restoring textures and edges. In this paper, we propose a novel UIE framework, the Wavelet-based Enhancement Diffusion Model (WEDM), which integrates frequency-domain decomposition with diffusion models. The WEDM consists of two main modules: the Wavelet Color Compensation Module (WCCM) for color correction in the LAB space using discrete wavelet transform, and the Wavelet Diffusion Module (WDM), which replaces traditional convolutions with wavelet-based operations to preserve multi-scale frequency features. By combining residual denoising diffusion with frequency-specific processing, the WEDM effectively reduces noise amplification and high-frequency blurring. Ablation studies further demonstrate the essential roles of the WCCM and WDM in improving color fidelity and texture details. Our framework offers a robust solution for underwater visual tasks, with promising applications in marine exploration and ecological monitoring. Full article