TELECOMMUNICATIONS SEMINAR Tietoliikennetekniikan seminaari

Code: TLTE3090


This time topic is ”Evolutionary algorithms in Communications and systems

Credits: 3–10 ECTS (3–10 op)

Prerequisites: related subject studies on telecommunica­tion engineering

Learning Outcomes: the aim of this course is to introduce research oriented topics in telecommunications and sys­tems, after completing this course successfully, the stu­dent will be able to seek scientific information and to pre­pare and give seminar presentations, moreover, they will be able to demonstrate the principles of the seminar topic

Content: this course has varying content, the current content is always indicated by the course subtitle pre­sented in the course website

Study Materials: 1. depend on the topic

Teaching Methods: depending on the topic

Modes of Study: attending seminar sessions (most of them), quizzes, preparing scientific report and giving at least one presen­tation (some guidelines in blow)

Languages: english

Grading: 1–5 or failed, or passed/failed (depends on the topic)

Responsible Person: Mohammed Elmusrati and Reino Virrankoski

Teacher(s): Mohammed Elmusrati, Reino Virrankoski

Responsible Unit: Department of Computer Science

Additional Information: annual course, website



Presentation lecture 3.3.2015 “What are Evolutionary algorithms

Presentation lecture 10.3.2015 “More about EAs


Those who are interested to learn more about EAs, can read the slides etc. Evolutionary algorithms course homepage.

A lot of information about EAs can be found from Wikipedia EA category:


Note, last year we originally thought that the topic of this seminar would be “MIMO Broadband Communication”, but we changed it later, but I will make a presentation about how EAs are used with MIMO systems planning and resource allocation, and will present that in later in the exercises.


EXERCISES from 17.3.

You should prepare presentation, about 20 min from some research paper related to the topic. You will find suitable research papers with keywords eg. “evolutionary algorithm” + Telecommunications e.g. from here:

·       ScienceDirect

·       IEEEXplore

Most of the pdfs are downloadable from the University accounts.


Exercise, Week 13, 14:

Matlabise these these java codes (do the same with Matlab)

Some programming examples of 1. exercise other version of binary GA

I will deliver example code later

Some programming examples of 2. exercise
DE class source, place in the same directory as

Some programming examples of 3. exercise version where numbers are drawn freely version that forces all lines to have all integers {1, 2, ..., 9} once on and only once all the time



EXERCISE, Week 16: F4104 from 14:30 to 17:00

Test these Matlab codes and try to understand what they are doing:


Some programming examples of 4. exercise

GAFIR1.m GA version of FIR designer. There were some problems in class, but b is what we want to find.

DEFIR1.m DE version of FIR designer.


CMA-ES code:


Pareto Front:



Other evolutionary optimization examples:
Note most of these codes in Mathworks require Global optimization toolbox which our classroom Matlab may not have.