Multi-User Information Theory

This course covers multi-user information theory, information theory for Gaussian channels (including fading and MIMO), and information theory for ad-hoc and sensor networks. The channels studied are primarily motivated by wireless communication systems and ad-hoc & sensor networks.

- Project presentations are Thursday, May 5, in EE/CS 6-212. Schedule of Presentations

- Instructor: Nihar Jindal, 6-119 EE/CS, nihar@ece.umn.edu, 625-6306
- Lecture: Tues & Thurs, 4:00 - 5:15, Ackerman 211
- Office Hours: Mon 11-12, Wed 1-2, 6-119 EE/CS
- Text: No required text, but a graduate level information theory textbook is highly recommended.
- Prerequisite: EE 5581 (or equivalent)
- Grading: 35% Homework, 25% Midterm, and 40% Project.
- Detailed Course Information & Syllabus
- Project Information

- A Random Beamforming Technique in MIMO Broadcast Channels, Younghwan Bae Presentation
- Feedback Capacity of Multiple Access & Broadcast Channels, Shahrokh Farahmand Presentation
- Distributed Source Coding, Vikrham Gowreesunker Presentation
- Survey on Capacity Results and Limits on MIMO Systems, Dimitrios Katselis Presentation
- Information Theoretic View on Capacity of Hybrid Wireless Networks, Mikalai Kisialiou Presentation
- Maximizing the Worst-User's Capacity for a Multi-User OFDM Uplink Channel, Juyul Lee Presentation
- Distortion-Rate for Non-Distributed and Distributed Estimation with WSNs, Iannois Schizas Presentation
- Achievable Rates of Transmit-Reference Ultra-Wideband Radio with PPM, Xiliang Luo Presentation
- Diversity-Multiplexing Tradeoff in the Rayleigh Fading Relay Channel, Alejandro Ribeiro Presentation
- On MIMO Fading Channels with Side Information at TX, Tairan Wang Presentation
- Linear Coding for Fading Channels, Jinjun Xiao Presentation
- Using Noncoherent Modulation for Training, Yingqun Yu Presentation

- Lecture Notes 1
- Lecture Notes 2
- Lecture Notes 3
- Lecture Notes 4-6
- Lecture Notes 7-8
- Lecture Notes 9-10
- Sensor Network Notes
- Network Coding Notes

- Homework Set 1 - Due Thursday, Jan 27
- Homework Set 2 - Due Thursday, Feb 3
- Homework Set 3 - Due Tuesday, Feb 15
- Homework Set 4 - Due Tuesday, Feb 22
- Homework Set 5 - Due Thursday, March 3
- Homework Set 6 - Due Tuesday, March 29

Tentative Dates |
Lectures |
Supplemental Reading |

1/18 | Course Introduction | |

1/20, 1/25 | Information Theory Basics: Entropy, Mutual Information, AEP | |

1/27, 2/1 | Single User Source and Channel Coding |
Shannon, 1948 A Mathematical Theory of Communication Shannon, 1956 The Zero Error Capacity of a Noisy Channel |

2/3, 2/8, 2/10 | Single-User Gaussian Channels: AWGN, Parallel, Fading |
Goldsmith & Varaiya, 1997
Capacity of Fading Channels with Channel Side Information Caire & Shamai, 1999 On the Capacity of Some Channels with Channel State Information (Section IV) |

2/15, 2/17, 2/22 | MIMO Channels |
Foschini & Gans, 1998
On Limits of Wireless Communication in a Fading Environment
when Using Multiple Antennas Telatar, 1995 Capacity of Multi-Antenna Gaussian Channels Jafar & Goldsmith, 2004 Transmitter Optimization and Optimality of Beamforming for Multiple Antenna Systems Venkatesan, Simon, & Valenzuela, 2003 Capacity of a Gaussian MIMO channel with Nonzero Mean Hosli & Lapidoth, 2004 The Capacity of a MIMO Ricean Channel is Monotonic in the Singular Values of the Mean Faycal, Trott & Shamai, 2001 The Capacity of Discrete-Time Memoryless Rayleigh-Fading Channels Marzetta & Hochwald, 1999 Capacity of a Mobile Multiple-Antenna Communication Link in Rayleigh Flat Fading Zheng & Tse, 2002 Communication on the Grassmann manifold: A Geometric Approach to the Noncoherent Multiple-Antenna Channel |

2/24, 3/1 | Multiple-Access Channel | Dueck, 1978 Maximal Error Capacity Region are Smaller than Average Error Capacity Regions for Multi-User Channels |

3/3, 3/8 | Slepian-Wolf & MAC with Correlated Sources |
Slepian & Wolf, 1973
Noiseless Coding of Correlated Information Sources Cover, El Gamal, & Salehi, 1980 Multiple access channels with arbitrarily correlated sources Dueck, 1981 A Note on the Multiple Access Channel with Correlated Sources |

3/10 | Midterm (4-6 PM) | |

3/22, 3/24 | Broadcast Channel |
Cover, 1972
Broadcast Channels Bergmans, 1974 A Simple Converse for Broadcast Channels with Additive White Gaussian Noise Marton, 1979 A Coding Theorem for the Discrete Memoryless Broadcast Channel El Gamal & Van der Meulen, 1981 A Proof of Marton's Coding Theorem for the Discrete Memoryless Broadcast Channel El Gamal, 1979 The Capacity of a Class of Broadcast Channels Korner & Marton, 1977 General Broadcast Channels with Degraded Message Sets |

3/29, 3/31 | MAC-Broadcast Duality & MIMO Broadcast Channel |
Jindal, Vishwanath & Goldsmith, 2003
On the Duality of Gaussian Multiple-Access and Broadcast Channels Caire & Shamai, 2003 On the Achievable Throughput of a Multiantenna Gaussian Broadcast Channel Vishwanath, Jindal, & Goldsmith, 2003 Duality, Achievable Rates, and Sum Rate Capacity of Gaussian MIMO Broadcast Channels Viswanath & Tse, 2003 Sum Capacity of the Vector Gaussian Broadcast Channel and Uplink/Downlink Duality Yu & Cioffi, 2004 Sum Capacity of Gaussian Vector Broadcast Channels Weingarten, Steinberg, & Shamai, 2004 The Capacity Region of the Gaussian MIMO Broadcast Channel |

4/5 | Interference Channel |
Carleial, 1978
Interference Channels Han & Kobayashi, 1981 A New Achievable Rate Region for the Interference Channel El Gamal & Costa, 1982 The Capacity Region of a Class of Deterministic Interference Channels Carleial, 1983 Outer Bounds on the Capacity of Interference Channels Costa, 1985 On the Gaussian Interference Channel Costa & El Gamal, 1987 The Capacity Region of the Discrete Memoryless Interference Channel with Strong Interference Kramer, 2004 Outer Bounds on the Capacity of Gaussian Interference Channels Sason, 2004 On Achievable Rate Regions for the Gaussian Interference Channel |

4/7, 4/12 | Relay Channel |
Cover & El Gamal, 1979
Capacity Theorems for the Relay Channel Kramer, Gastpar, & Gupta, 2005 Cooperative Strategies and Capacity Theorems for Relay Networks |

4/14, 19 | Rate Distortion Theory | |

4/21, 4/26 | Sensor Networks |
Berger, Zhang, & Viswanathan, 1996
The CEO Problem Viswanathan & Berger, 1997 The Quadratic Gaussian CEO Problem Oohama, 1998 The Rate-Distortion Function for the Quadratic Gaussian CEO Problem Chen, Zhang, Berger, & Wicker, 2004 An Upper Bound on the Sum-Rate Distortion Function and Its Corresponding Rate Allocation Schemes for the CEO Problem Prabhakaran, Tse, & Ramchandran Rate Region of the Quadratic Gaussian CEO Problem |

4/28 | Ad-Hoc Network Capacity |
Gupta & Kumar, 2000
The Capacity of Wireless Networks Xie & Kumar, 2004 A Network Information Theory for Wireless Communication: Scaling Laws and Optimal Operation Leveque & Telatar, 2005 Information-Theoretic Upper Bounds on the Capacity of Large Extended Ad Hoc Wireless Networks |

5/3, 5/5 | Network Coding |
Ahlswede, Cai, Li, & Yeung, 2000
Network Information Flow Li, Yeung, & Cai, 2003 Linear Network Coding Koetter & Medard, 2003 An Algebraic Approach to Network Coding |