Network Information Theory
Mumbai , India
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Start Date
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Medium of studying
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Duration
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Details
Program Details
Degree
Masters
Major
Electrical Engineering | Computer Science | Information Technology
Area of study
Information and Communication Technologies | Engineering
Course Language
English
About Program
Program Overview
Electrical Engineering
The Indian Institute of Technology Bombay offers a comprehensive Electrical Engineering program.
About the Department
IIT Bombay was established in the year 1957, and the department of Electrical Engineering (EE) has been one of its major departments since its inception.
Academics
The department offers various academic programs, including:
- PhD
- MTech
- Dual Degree
- BTech
- Courses
- Faculty Advisors
- Teaching Labs
- Wadhwani Lab
- TI DSP Lab
- ePGD
- Calendar
- Timetable
- Placements
- Co-curricular
Admissions
The department admits students to its programs through:
- PhD admissions
- Postgraduation admissions
- Undergraduation admissions
Research
The department conducts research in various areas, including:
- Communication and Signal Processing
- Control and Computing
- Power Electronics and Power Systems
- Electronic Systems
- Integrated Circuit and Systems
- Solid State Devices
People
The department consists of:
- Faculty
- Post Doc
- Students
- Staff
- Committees
EE 756 - Network Information Theory
Course Description
Introduction: Entropy, Notions of Typicality, Discrete Memoryless Channels (DMCs), Shannon's Theorem, Feedback.
Course Topics
- Multiple-Access Channels (MACs): System Models of MAC and Applications, Capacity Region of Discrete Memoryless MACs, Gaussian MAC models.
- Broadcast Channels (BC): System Model, Super Position Coding, Marton's Inner Bound, Outer-bounds on BC Capacity, Capacity-region of Degraded BCs, Multi-antenna (MIMO) BC, Dirty Paper Coding.
- Interference Channels: Han Kobayashi region, Outer bounds to the Capacity-region, Gaussian Interference Channel, Interference Alignment and Degrees of Freedom.
- Multi-terminal Source Coding: Lossless and Lossy Distributed Data Compression -- models and Techniques, Multiple Descriptions, Successive Refinement.
- Network Information Flow: Relay Networks, Routing and multicast, Capacity region for linear deterministic networks, Capacity approximation for Gaussian relay networks. Network Coding and applications.
- Optional Contents: Joint Source Channel Coding, Separation Theorem, Role of Feedback in Networks.
Latest Semester
2019-Spring
Programs
PG
Latest Instructor
Sibi Raj B Pillai
Substitutions
Not Applicable
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