Lehrinhalte
This lecture course introduces the fundamentals of information and network information theory.
Outline:
information, uncertainty, entropy, mutual information, capacity, differential entropy, typical sequences, Gaussian channels, basics of source and channel coding, linear block codes, Shannons source coding theorem, Shannons channel coding theorem, capacity of Gaussian channels, capacity of bandlimited channels, Shannons bound, bandwidth efficiency, capacity of multiple parallel channels and waterfilling, Gaussian vector channel, Multiple Access Channel, Broadcast Channel, rate region..
Literature
1. T.M. Cover and J.A. Thomas, Elements of Information Theory, Wiley & Sons, 1991.
2. Abbas El Gamal and Young-Han Kim, Network Information Theory, Cambrige, 2011.
3. S. Haykin, Communication Systems, Wiley & Sons, 2001.
Voraussetzungen
Knowledge of basic communication theory und probability theory
This lecture course introduces the fundamentals of information and network information theory.
Outline:
information, uncertainty, entropy, mutual information, capacity, differential entropy, typical sequences, Gaussian channels, basics of source and channel coding, linear block codes, Shannons source coding theorem, Shannons channel coding theorem, capacity of Gaussian channels, capacity of bandlimited channels, Shannons bound, bandwidth efficiency, capacity of multiple parallel channels and waterfilling, Gaussian vector channel, Multiple Access Channel, Broadcast Channel, rate region..
Literature
1. T.M. Cover and J.A. Thomas, Elements of Information Theory, Wiley & Sons, 1991.
2. Abbas El Gamal and Young-Han Kim, Network Information Theory, Cambrige, 2011.
3. S. Haykin, Communication Systems, Wiley & Sons, 2001.
Voraussetzungen
Knowledge of basic communication theory und probability theory
- Lehrende: Heinz Köppl
- Lehrende: Matthias Schultheis
- Lehrende: Mark Sinzger-D'Angelo
- Lehrende: Anam Tahir
Semester: WT 2021/22