EE194-16 Syllabus - Fall 2015

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  1. Review of basic information theory concepts (entropy, mutual information)

  2. Single-user channel capacity and coding (DMC, Gaussian, MIMO, random coding, typicality)

  3. Multiple access channel (capacity, successive interference cancellation, Gaussian)

  4. Broadcast channel (superposition coding, Marton binning, duality for Gaussian)

  5. Channels with state (causality, Gelfand-Pinsker coding, dirty-paper coding)

  6. Interference channel (rate splitting, Han-Kobayashi scheme, non-unique decoding)

  7. Relay channel (decode-forward, compress-forward, block Markov encoding, list coding, backward decoding, sliding window decoding)

  8. Multicast and interference networks (network coding, noisy network coding, interference alignment, as time permits)

Some of the advanced topics will be covered as time permits.



  • 50% homework

  • 50% project

We reserve the right to change these weights based on performance of the entire class.

  1. Homework: There will be approximately 5-6 bi-weekly homework sets. Homework is due in class on the due date. The homework is essential for learning the materials.

  1. Project: The project will focus on applying ideas and techniques introduced in the course to modern communication and network problems. We will provide a list of suggested topics, but students are also encouraged to propose their own topic that is related to their research. The project will involve a presentation to the class and a report. The presentation will be scheduled during the last two weeks of the semester, and the report will be due on the last day of the semester.

Text and References

  • Abbas El Gamal and Young-Han Kim, Network Information Theory, Cambridge University Press, 2012. (lecture notes available on arXiv)


  1. Thomas Cover and Joy Thomas, Element of Information Theory, 2nd ed., Wiley-Interscience, 2006.

  2. Imre Csiszar and Janos Korner, Information Theory: Coding Theorems for Discrete Memoryless Systems, 2nd ed., Cambridge University Press, 2011.

  3. Raymond W. Yeung, A First Course in Information Theory, Kluwer, 2001.

  4. Robert G. Gallager, Information Theory and Reliable Communication, John Wiley & Sons, Inc., 1968.


  • Working knowledge of Probability theory. If you are not sure, talk to the instructor.