arXiv subjects

Shengfeng Wang

Publications and source records attributed to Shengfeng Wang.

4 recordsLinked to original sources

arXiv2026

Toward Generalized LEO Channel Prediction: A Rapid Adaptation Time-Frequency Mamba Framework

Accurate channel state information (CSI) prediction is pivotal for enhancing system capacity in low Earth orbit (LEO) satellite-terrestrial communications within the sixth-generation vision of global ubiquitous connectivity. However, the extreme mobility of LEO satellites, coupled with significant propagation delays, induces severe channel aging. Existing deep learning (DL) methods often struggle with non-stationary dynamics or generalize poorly across diverse global geographies. To address these challenges, we design the Evo-TFMamba, which is an evolutionary framework integrating time-frequency selective Mamba blocks with meta-learning for generalized CSI prediction. Experimental results demonstrate that the proposed Evo-TFMamba performs adaptive prediction according to the geographic coverage of LEO satellites. Meanwhile, it significantly enhances the model's generalization ability, particularly when faced with unseen channel environments in LEO satellite communication.

eess.SP↗

arXiv2026

A Hierarchical Space-Ground Collaborative Network: Architecture Design and Deployment

The sixth-generation (6G) landscape demands a profound architectural evolution toward a unified, collaborative ecosystem that integrates satellite and terrestrial segments to provide ubiquitous global connectivity. Nevertheless, conventional independent management paradigms are increasingly challenged by the profound spatiotemporal nonstationarity of low-Earth orbit (LEO) channels and the volatile demands of massive heterogeneous services. To address these challenges, this study focuses on the architectural design of space-ground integrated networks (SGINs) and investigates elastic deployment strategies tailored to heterogeneous 6G service requirements. We first review the development trends in SGIN and then summarize typical application scenarios into two categories, along with their associated challenges and constraints. After that, a hierarchical space-ground collaborative network (SGCN) architecture is proposed to support achieving larger network capability, extensive continuous coverage, and enhanced spectral efficiency, which is evaluated through three representative scenarios with progressive baselines. Subsequently, a service-aware deployment strategy is introduced to further establish the engineering feasibility of the proposed architecture.

eess.SP↗

arXiv2025

Optimal error estimates of a second-order temporally finite element method for electrohydrodynamic equations

In this work, we mainly present the optimal convergence rates of the temporally second-order finite element scheme for solving the electrohydrodynamic equation. Suffering from the highly coupled nonlinearity, the convergence analysis of the numerical schemes for such a system is rather rare, not to mention the optimal error estimates for the high-order temporally scheme. To this end, we abandon the traditional error analysis method following the process of energy estimate, which may lead to the loss of accuracy. Instead, we note that the charge density also possesses the "energy" decaying property directly derived by its governing equation, although it does not appear in the energy stability analysis. This fact allows us to control the error terms of the charge density more conveniently, which finally leads to the optimal convergence rates. Several numerical examples are provided to demonstrate the theoretical results, including the energy stability, mass conservation, and convergence rates.

math.NA↗

arXiv2023

Modeling and Design of the Communication Sensing and Control Coupled Closed-Loop Industrial System

With the advent of 5G era, factories are transitioning towards wireless networks to break free from the limitations of wired networks. In 5G-enabled factories, unmanned automatic devices such as automated guided vehicles and robotic arms complete production tasks cooperatively through the periodic control loops. In such loops, the sensing data is generated by sensors, and transmitted to the control center through uplink wireless communications. The corresponding control commands are generated and sent back to the devices through downlink wireless communications. Since wireless communications, sensing and control are tightly coupled, there are big challenges on the modeling and design of such closed-loop systems. In particular, existing theoretical tools of these functionalities have different modelings and underlying assumptions, which make it difficult for them to collaborate with each other. Therefore, in this paper, an analytical closed-loop model is proposed, where the performances and resources of communication, sensing and control are deeply related. To achieve the optimal control performance, a co-design of communication resource allocation and control method is proposed, inspired by the model predictive control algorithm. Numerical results are provided to demonstrate the relationships between the resources and control performances.

cs.PF↗