Course Syllabus for

Stochastic Optimization for Communication Networks
Stokastisk optimering för kommunikationsnät

EIT135F, 7.5 credits

Valid from: Autumn 2016
Decided by: Rektor Viktor Öwall
Date of establishment: 2016-06-21

General Information

Division: Electrical and Information Technology
Course type: Third-cycle course
Teaching language: English


The aim of this course is to provide students with the tools and mentality of stochastic optimization. Communication networks in practice always contain a certain level of randomness and uncertainty. This random behavior naturally necessities the stochastic investigation and design of these networks, where the classical deterministic optimization tools fail to be applied. This course intents to present well-known stochastic optimization techniques with their applications to communication systems.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

Optimization tools for stochastic communication networks covering both classic results and current research. Sample application areas: queuing-theoretic problems, network flow problems, network resource allocation and utility maximization, wireless network power control, medium access control, routing. Sample optimization tools: KKT optimality condition, dynamic programming, stochastic approximation, Lyapunov optimization.

Course Literature

Instruction Details

Types of instruction: Lectures, exercises, self-study literature review

Examination Details

Examination formats: Written exam, written assignments, seminars given by participants. There will be one written exam. There will be also a final project which is closely related to student's research. The final project will be presented in the class. There will be 2-3 assignments and paper readings.
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: Basic engineering mathematics. Basic probability theory.

Further Information

Course Coordinator: Mehmet Karaca,

Course Occasion Information

Contact and Other Information

Course coordinators:

Complete view