Statistical Propagation Models

Statistical Propagation Models is a type of propagation model that characterizes signal attenuation in wireless communication environments through empirical data and probabilistic methods, distinguishing it from deterministic models by relying on statistical analysis of measurement campaigns rather than explicit physical or geometric representations of the propagation medium.

979

Publications

74.1K

Citations

2.3K

Authors

771

Institutions

Publications per year

2017–2026

181

Authors

2.3K

  1. AF
    Andreas F. Molisch

    University of Southern California, United States

    15 publications · 1.8K citations

    15

    h-index

  2. TS
    Theodore S. Rappaport

    Virginia Tech, United States

    14 publications · 5K citations

    13

    h-index

  3. BA
    Bo Ai

    Beijing Jiaotong University, China

    11 publications · 450 citations

    11

    h-index

  4. RH
    Ruisi He

    Beijing Jiaotong University, China

    11 publications · 511 citations

    11

    h-index

  5. SL
    Simon L. Cotton

    Queen's University Belfast, United Kingdom

    10 publications · 463 citations

    10

    h-index

1–5 of 2.3K

Venues

  1. IEEE Transactions on Vehicular Technology

    97 publications · 9.4K citations

    46

    h-index

  2. IEEE Transactions on Antennas and Propagation

    37 publications · 3.3K citations

    28

    h-index

  3. IEEE Transactions on Communications

    40 publications · 3.9K citations

    28

    h-index

  4. IEEE Transactions on Wireless Communications

    34 publications · 2.1K citations

    24

    h-index

  5. IEEE Journal on Selected Areas in Communications

    23 publications · 11.8K citations

    20

    h-index

1–5