Wireless Network Models

Wireless Network Models is a class of stochastic models that formally represent the spatial configuration, random connectivity, and dynamic behavior of wireless communication systems by integrating probabilistic methods to capture interference, channel randomness, and node mobility inherent in such networks.

3.9K

Publications

219K

Citations

7.3K

Authors

1.7K

Institutions

Publications per year

2017–2026

782

Authors

7.3K

  1. MH
    Martin Haenggi

    University of Notre Dame, United States

    75 publications · 10.1K citations

    42

    h-index

  2. JG
    Jeffrey G. Andrews

    The University of Texas at Austin, United States

    53 publications · 10K citations

    29

    h-index

  3. MA
    Mohamed‐Slim Alouini

    King Abdullah University of Science and Technology, Saudi Arabia

    29 publications · 2.1K citations

    22

    h-index

  4. RW
    Robert W. Heath

    The University of Texas at Austin, United States

    35 publications · 2.7K citations

    21

    h-index

  5. FB
    François Baccelli

    Institut national de recherche en sciences et technologies du numérique, France

    26 publications · 4.2K citations

    21

    h-index

1–5 of 7.3K

Venues

  1. IEEE Transactions on Wireless Communications

    244 publications · 17.2K citations

    62

    h-index

  2. IEEE Transactions on Communications

    143 publications · 12.6K citations

    51

    h-index

  3. IEEE Transactions on Vehicular Technology

    147 publications · 7.9K citations

    49

    h-index

  4. IEEE Transactions on Information Theory

    83 publications · 9.5K citations

    47

    h-index

  5. IEEE Journal on Selected Areas in Communications

    81 publications · 9.7K citations

    44

    h-index

1–5