**Instructor**

Srikrishna Bhashyam

Office: ESB 212D

Phone: 2257 4439

**Pre-requisites**

Information Theory

**Course Content**

- Review of Information measures: Entropy, differential entropy, some inequalities
- Typical sequences: robust typicality, strong typicality, and weak typicality, properties of robustly typical sequences, joint typicality lemma
- Review of point-to-point information theory: Discrete memoryless (DM) channels, packing lemma, capacity with input cost, Gaussian channel, Lossless and lossy source coding, covering lemma
- Multiple access channels (MAC): DM-MAC, Gaussian MAC
- Degraded Broadcast channels (BCs): DM-BC, Less noisy and More capable BCs
- Interference channels (IC): DM-IC, Gaussian IC, Han-Kobayashi inner bound, Approximate capacity of Gaussian IC
- Channels with state: Dirty paper coding
- Gaussian vector channels: Gaussian vector point-to-point channel, Gaussian vector MAC, Gaussian vector BC, Dirty paper coding
- Distributed lossless compression: Slepian-Wolf theorem

**References**

[1] A. El Gamal, Y-H. Kim, Network Information Theory, Cambridge University Press, 2011.

[2] G. Kramer, Topics in Multi-user information theory, Foundations and Trends in Communications and Information Theory, Now Publications, 2008.

**Problem Sets**

Problem Set 1

**Evaluation**

Quiz 1 (20%) -- Sep 5, 2014, Solutions

Final (40%) -- Nov 27, 2014

Project (40%)