# Multi-User Information Theory

## Lecture Notes

Lecture 1-3: Method of types, Sanov Theorem. [pdf] [source]

Lecture 4: Relay channel, definition and upper bound [pdf] [source]

Lecture 5: Relay channel, decode and forward, partial decode and forward [pdf] [source]

Lecture 6: Cut-set bounds, decode and forward via binning [pdf]

----------------------Convex optimization-----------------

Lecture 7: Introduction to convex optimization, definitions and convex sets analisys [pdf]

Lecture 8: Convex sets (cont), convex functions [pdf]

Lecture 9: Convex functions (cont), operations that preserve convexity [pdf]

Lecture
10: Conjugate function, convex optimization problems, such as inear
programming, linear fraction, Quadratic, second order cone, Geometric
programming, semi-definite programming. [pdf]

Lecture 11: Lagrange Duality [pdf]