Class Restriction And Registration Summary 
EE 87027  Section 01: Network Info Theory (CRN 28963)
Long Title: Network Information Theory  

Course Description: Network information theory deals with the fundamental limits of information transmission over networks and optimal coding techniques that achieve these limits. It extends Shannon's pointtopoint information theory to networks with multiple sources and destinations. The course aims to present key results and techniques in the theory. Topics include pointtopoint systems (Shannon's channel coding theorem and rate distortion theory), singlehop networks (multiple access channels, broadcast channels, interference channels, channels with state, Gaussian fading channels, distributed lossless source coding, multiple description coding, joint sourcechannel coding), and multihop networks (FordFulkerson maxflow mincut theorem, noiseless networks and network coding, relay channels, capacity of large Gaussian networks, source coding over noiseless networks).Students should have taken a graduate level class in probability theory/stochastic processes (e.g., EE 60563/EE 60573). Prior exposure to information theory is recommended although not necessary. Associated Term: Spring Semester 2013 Campus: Main Credits: 3 Grade Mode: Standard Letter Course may not be repeated Restrictions: Must be enrolled in one of the following Levels: Employee NonDegree (EM) , Graduate Architecture (GA) , Graduate NonDegree (GD) , Graduate (GR) Must be enrolled in one of the following Campuses: Main (M) Course Attributes: ZTST  Final exam

Enrollment over the last three years 

Course was recently taught in SP11 
Average number of students: 9 
Composition of Students  First Year  Soph  Junior  Senior/5th  Grad/Prof 

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