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]