optical link budgeting

Optical space–ground communication networks face high deployment costs, slow responsiveness, and limited flexibility. Method: This study systematically compares portable versus large optical ground stations (OGSs) in low Earth orbit (LEO) small-satellite constellations, integrating orbital dynamics, multi-scenario atmospheric channel fading models, link budget analysis, and network availability simulations. Contribution/Results: It provides the first quantitative assessment of low-cost portable terminals as viable replacements for traditional high-capacity OGSs. Results show that a portable OGS network maintains reliable optical links over >95% of operational time, reduces deployment cost by >60%, and cuts end-to-end latency by an order of magnitude. The paper proposes a novel “distributed lightweight OGS + dynamic scheduling” network architecture, which significantly enhances global coverage elasticity and rapid deployment capability while preserving robustness.

This work addresses the severe performance degradation in satellite-to-ground coherent optical communication caused by nonlinear distortions introduced by high-power optical amplifiers. To mitigate this issue, the paper proposes a low-complexity digital signal processing scheme that incorporates an efficient nonlinear compensation algorithm. The approach significantly enhances the link’s tolerance to channel loss with negligible increase in system complexity. Experimental results demonstrate that the proposed method improves the allowable link loss by 6 dB, effectively alleviating nonlinear impairments and offering a practical solution for high-power satellite-to-ground optical communication systems.

Traditional optical time-domain reflectometry (OTDR) suffers from low energy efficiency and poor scalability in optical network monitoring. Method: This work presents the first systematic cost and power consumption evaluation of power profile monitoring (PPM) in both opaque and all-optical IP-over-Wavelength-Division-Multiplexing (IPoWDM) architectures, benchmarked against OTDR. We propose a cross-layer analytical framework integrating optical-layer power distribution modeling with joint cost–power optimization, validated via an IPoWDM network simulation platform. Contribution/Results: Although PPM increases per-transceiver cost by 80% and power consumption by 50% relative to OTDR, it achieves superior deployment efficiency, significantly lower long-term operational energy consumption, and enhanced network scalability—thereby surpassing the energy-efficiency limits of conventional monitoring techniques. This study establishes a novel paradigm and practical foundation for green, scalable, intelligent monitoring in next-generation optical networks.

In mode-division multiplexing (MDM) systems based on multimode fiber, mode-dependent gain (MDG) induces stochastic fluctuations in channel capacity, substantially reducing the average capacity and hindering universal analytical characterization. To address this, we propose a statistical channel model and derive, for the first time, a closed-form expression for the probability distribution of channel capacity for arbitrary mode count $D > 2$, overcoming the prior limitation to $D = 2$. Our approach leverages Gaussian approximation and introduces a fitting parameter to capture inter-mode capacity correlations, ensuring both accuracy and broad applicability. Validated against multi-section Monte Carlo simulations across wide-ranging practical system parameters, the proposed analytical model achieves high fidelity with controllable error. This significantly enhances computational efficiency and theoretical interpretability in capacity assessment. The framework provides a foundational theoretical tool for design optimization and performance prediction of high-dimensional MDM systems.

To address the challenge of real-time synchronization between digital twins (DTs) and physical optical networks—limiting dynamic service adaptability throughout the network lifecycle—this paper proposes a dynamically updated DT framework for fiber channel performance prediction. Methodologically, it introduces the first DT dynamic update mechanism for optical networks, integrating physics-informed neural networks (PINNs), partial differential equation (PDE)-constrained hybrid modeling, real-time parameter identification, and a closed-loop feedback architecture. This enables synchronous, adaptive updates of multi-physical parameters—including Raman gain, amplifier frequency response, and connection loss—across C- and L-bands. Experimental results demonstrate a 100× speedup in prediction over conventional numerical methods; a 1.4 dB reduction in performance estimation error following device replacement; and validation of high accuracy (sub-dB), low latency (millisecond-level), and physical consistency in both large-scale simulations and live C+L-band field trials.

Accurately predicting channel power, optical signal-to-noise ratio (OSNR), and generalized signal-to-noise ratio (GSNR) in operational optical networks remains challenging. This work proposes a hybrid modeling paradigm anchored by a digital link model (DLM), which synergistically integrates physical principles with data-driven techniques to achieve high-accuracy prediction of these key performance metrics without requiring full-network model reconstruction. By leveraging the DLM to calibrate inter-span and inline amplifier (ILA) boundaries, the proposed approach achieves OSNR and GSNR prediction errors within 0.39 dB and 0.43 dB, respectively, in both single-channel and OSaaS deployment scenarios—significantly outperforming existing methods.

This study addresses the overestimated performance in existing LiFi link budgets caused by idealized assumptions by proposing a design space analysis framework for diffuse laser LiFi constrained by hardware feasibility. By coupling a holographic diffusion channel model with a comprehensive receiver noise budget incorporating laser RIN, this work evaluates PAM modulation, multipath effects, and eye safety constraints. Furthermore, an open-source ns-3 simulation module validated by prototyping is released. Experimental results demonstrate a data rate of 558 Mb/s at 5 meters, revealing that idealized models overestimate performance by 3.9 to 6.6 times. These findings confirm the effectiveness of the proposed framework in correcting prediction biases and guiding practical system design for realistic diffuse laser LiFi deployments.

本文针对光星间链路因指向抖动导致的可靠性问题，通过建立统计信道模型并采用高斯主瓣近似方法，分析了终端稳定性对链路性能的影响，并提出了设计指导。

This work addresses the limited generalization and low modeling efficiency of existing physical-layer approaches in ultra-wideband optical networks, which struggle to accurately estimate the generalized signal-to-noise ratio (GSNR) under stimulated Raman scattering. The authors propose a Link-Adaptive Digital Twin (LA-DT) framework that decomposes GSNR modeling into amplified spontaneous emission (ASE), nonlinear interference (NLI), and signal power components. Innovatively integrating a neural network architecture with a linear modulation layer and a domain discriminator, the method leverages domain-adversarial training and few-shot fine-tuning to explicitly model Raman amplifier insertion loss within the digital twin for the first time. Experiments demonstrate substantial improvements: across 35 scenarios, prediction errors are significantly reduced (RMSE of 0.151, 0.111, and 0.113 dBm for NLI, ASE, and signal power, respectively), outperforming baselines by over 52%. Moreover, on 12 unseen scenarios, it achieves a GSNR RMSE of 0.159 dB with only 20 samples, highlighting exceptional generalization and rapid adaptability.

This study addresses critical gaps in laser diode–based LiFi prototype research, including throughput mismeasurement, absent noise modeling, and unclear coverage–performance trade-offs, by presenting the first reproducible, closed-loop validation framework spanning hardware to full protocol stack simulation. The system integrates a 500-mW laser source, a holographic diffuser, an IM/DD receiver, and adaptive M-QAM modulation, coupled with the ns-3 network simulator and a Monte Carlo link-level error model to enable joint PHY/MAC/network-layer evaluation. Experimental results demonstrate 930 Mb/s at 14 m (16-QAM), 1.86 Gb/s at 5 m (256-QAM), and a maximum OOK range of 23.3 m; a 20° diffuser covers a 4.2-m radius area. ns-3 simulations confirm a saturated throughput reaching 93% of the physical-layer rate and a 99th-percentile latency below 0.11 ms under 70% load, quantifying for the first time the trade-off between beam width and coverage.