|
課程概述 |
1. Measures of Information: entropy, differential entropy, mutual information, typical sequences.
2. Point-to-Point Communication: channel coding theorem, polar coding, lossless and lossy source coding, source-channel separation, Gaussian channel.
3. Channel with States: compound channel, channel with random state, dirty-paper coding, fading channel capacity.
4. Multiple Access Channel (MAC): successive interference cancellation, time-sharing, joint decoding, capacity of MAC.
5. Broadcast Channel (BC): superposition coding, capacity of degraded BC, Marton’s coding scheme, capacity of deterministic BC, MIMO Gaussian BC.
6. Interference Channel (IC): Han-Kobayashi coding scheme, capacity of Gaussian IC to within 1 bit, capacity of deterministic IC, interference alignment.
7. Relay Channel (RC): decode-and-forward, compress-and-forward, Gaussian relay channel, amplify-and-forward.
8. Distributed Source Coding: Slepian-Wolf theorem, Wyner-Ziv theorem.
9. Network Information Flow: Cut-set bound, network coding, noisy network coding.
10. Feedback: Schalkwijk-Kailath scheme, feedback in Gaussian IC.
11. Non-Asymptotic Information Theory |
|
參考書目 |
Textbook： Lectures will be based on lecture notes and slides.
Reference： 1. A. El Gamal and Y.-H. Kim, Network Information Theory, Cambridge University Press, 2011.
2. T. Cover and J. Thomas, Elements of Information Theory, Second Edition, Wiley-Interscience, 2006.
3. R. Yeung, Information Theory and Network Coding, Springer, 2008. |