Binquan Guo

Networks · Computing · Algorithms

Research

I received my Ph.D. from Xidian University in December 2025, following joint doctoral training with the Tianjin Artificial Intelligence Innovation Center.

I study how to make large, changing networks work efficiently, with a particular focus on low Earth orbit satellite systems.

I am interested in methods that remain useful as systems change. I value clear assumptions, reproducible results and practical implementation.

Selected work

Five contributions to networking in large LEO constellations. Years below follow first online publication.

  1. IEEE Transactions on Mobile Computing2026

    Lightweight Semantic Communication-Compliant Shortest Path Selection in Large-Scale LEO Satellite Networks

    An exact graph-based routing method for four combinations of user-side and satellite-side semantic encoding and decoding. It finds optimal paths for the formulated model in polynomial time and examines bandwidth–delay trade-offs and the sources of semantic gains.

    IEEE Accepted manuscript · PDF
    Authors & publication details

    Binquan Guo, Zehui Xiong, Zhou Zhang, Qianqian Yang, Baosheng Li, Dusit Niyato, Mohsen Guizani, and Zhu Han.

    DOI: 10.1109/TMC.2026.3675010

  2. IEEE Wireless Communications2025

    Enhancing Mega-Satellite Networks with Generative Semantic Communication: A Networking Perspective

    A temporal-graph framework for deploying semantic models and routing through them. With the hop count fixed, encoding nearer the source and decoding nearer the destination can reduce aggregate link bandwidth; detours can instead increase bandwidth use and delay.

    IEEE Preprint · PDF
    Authors & publication details

    Binquan Guo, Wanting Yang, Zehui Xiong, Zhou Zhang, Baosheng Li, Zhu Han, Rahim Tafazolli, and Tony Q. S. Quek.

    First published online in 2025; assigned to a 2026 issue.

    DOI: 10.1109/MWC.2025.3596938

  3. IEEE Transactions on Communications2025

    Resilience of Mega-Satellite Constellations: How Node Failures Impact Inter-Satellite Networking Over Time?

    A service-aware temporal betweenness metric measures how node failures affect connectivity over time. Simulations show that topology changes can partly restore service, while rerouting is important for faster recovery.

    IEEE Preprint · PDF
    Authors & publication details

    Binquan Guo, Zehui Xiong, Zhou Zhang, Baosheng Li, Dusit Niyato, Chau Yuen, and Zhu Han.

    DOI: 10.1109/TCOMM.2025.3610221

  4. IEEE Transactions on Vehicular Technology2025

    Enabling Real-time Computing and Transmission Services in Large-Scale LEO Satellite Networks

    Joint selection of a computing satellite and communication route for real-time services. The method exploits the structure of the formulated problem to find optimal solutions efficiently under computing and bandwidth constraints.

    IEEE Preprint · PDF Research news · Tech Xplore
    Authors & publication details

    Binquan Guo, Zhou Zhang, Saman Atapattu, Miao Pan, Ye Yan, Zehui Xiong, and Hongyan Li.

    DOI: 10.1109/TVT.2025.3550806

  5. IEEE Transactions on Vehicular Technology2024

    Lightweight Maximum-Capacity Path Selection for Delay-Sensitive Applications in Large-Scale LEO Satellite Networks

    An efficient graph-based method for selecting a maximum-capacity path subject to an end-to-end delay bound, combining capacity bounds, graph filtering and bisection.

    IEEE Accepted manuscript · PDF
    Authors & publication details

    Binquan Guo, Zehui Xiong, Zhu Han, Chau Yuen, and Sumei Sun.

    First published online in 2024; assigned to a 2025 issue.

    DOI: 10.1109/TVT.2024.3516779

For the wider publication list, visit Google Scholar .

Research interests

Mega-constellation networking

Main focus

Routing, resilience, semantic communication and joint computing–communication services in large LEO constellations.

Green computing for AI

Resource packing in data centers, workflow scheduling and the scheduling of multi-step language-model inference, with an interest in reducing wasted resources.

Scheduling and optimization

Exploratory

Exact and approximate methods for NP-hard scheduling problems, and how AI and mathematical optimization can help find useful solutions.

AI for cryptography

Exploratory

Exploring how learning-based methods can inform the analysis and design of cryptographic systems.

AI for biology and medicine

Exploratory

Earlier work on color vision motivates an interest in useful AI methods for biological and medical questions.

Background

Education

I received my bachelor’s and master’s degrees from Xidian University in 2017 and 2020. During my doctoral studies, I visited the Singapore University of Technology and Design and collaborated remotely with the University of Houston.

Research exchange

I have collaborated with colleagues at the Singapore University of Technology and Design, Nanyang Technological University, Queen’s University Belfast, the University of Surrey and the University of Houston, on questions across networking, communications and computing.

Earlier work on color vision

I am a co-inventor of a color-vision test chart synthesis method granted in China in 2023 (CN111429547B).

Research conversations

Students and researchers interested in these topics are welcome to discuss a concrete question or explore a small research project together.

I also welcome conversations with industry teams about networking and computing problems, practical constraints and opportunities for collaborative research.

bqguo@stu.xidian.edu.cn