Graph-based Interference Models

Graph-Based Interference Models is a formal framework that represents interference effects through graph structures, where nodes denote entities or variables and edges encode potential causal or statistical dependencies that mediate interference, distinguishing it from traditional, non-network-based interference models by explicitly leveraging graph-theoretic representations to capture complex, structured interference patterns.

50

Publications

2.3K

Citations

150

Authors

82

Institutions

Publications per year

2017–2026

8

Authors

150

  1. XG
    Xin Guan

    Heilongjiang University of Science and Technology, China

    2 publications · 47 citations

    2

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  2. XC
    Xiang Cheng

    Peking University, China

    2 publications · 140 citations

    2

    h-index

  3. ZC
    Zhipeng Cai

    Georgia State University, United States

    2 publications · 47 citations

    2

    h-index

  4. RZ
    Rongqing Zhang

    Peking University, China

    2 publications · 140 citations

    2

    h-index

  5. ES
    Edward S. Davidson

    University of Michigan, United States

    2 publications · 47 citations

    2

    h-index

1–5 of 150

Venues

  1. IEEE Transactions on Vehicular Technology

    4 publications · 243 citations

    4

    h-index

  2. IEEE/ACM Transactions on Networking

    TON · 3 publications · 107 citations

    3

    h-index

  3. IEEE Transactions on Wireless Communications

    2 publications · 179 citations

    2

    h-index

  4. 2015 IEEE Global Communications Conference (GLOBECOM)

    Conference · 2 publications · 47 citations

    2

    h-index

  5. 1

    h-index

1–5