Random Coding Bounds

Random Coding Bounds is a theoretical framework in finite blocklength information theory that characterizes the fundamental limits of reliable communication over noisy channels by deriving upper and lower bounds on the achievable error probability using randomly generated codes under specific decoding rules.

111

Publications

6.7K

Citations

164

Authors

94

Institutions

Publications per year

2017–2026

14

Authors

164

  1. AG
    Albert Guillén i Fàbregas

    University of Cambridge, United Kingdom

    11 publications · 369 citations

    10

    h-index

  2. AG
    Alfonso García Martínez

    University of Cambridge, United Kingdom

    10 publications · 354 citations

    10

    h-index

  3. NM
    Neri Merhav

    Technion – Israel Institute of Technology, Israel

    10 publications · 241 citations

    10

    h-index

  4. JS
    Jonathan Scarlett

    École Polytechnique Fédérale de Lausanne, Switzerland

    7 publications · 214 citations

    7

    h-index

  5. AL
    Amos Lapidoth

    ETH Zurich, Switzerland

    3 publications · 222 citations

    3

    h-index

1–5 of 164

Venues

  1. IEEE Transactions on Information Theory

    55 publications · 4.5K citations

    34

    h-index

  2. IEEE Transactions on Communications

    3 publications · 253 citations

    3

    h-index

  3. 3

    h-index

  4. arXiv (Cornell University)

    Repository · 2 publications · 23 citations

    2

    h-index

  5. Journal of Mathematical Physics

    1 publications · 24 citations

    1

    h-index

1–5