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Optimization and Game Theory in Communications
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Optimization and Game Theory in Communications

Contents:

The course will allow students to identify, classify and formulate common optimization problems in communications.The students learn a variety of algorithms to rigorously solve those optimization problems. 

Furthermore, basic mathematical tools from game theory will be presented and applied in cooperative and non-cooperative communication systems.

Specifically, the following topics will be covered. 

  • Linear programming and resource allocation
  • Convex optimization and power control
  • Global optimizations and interference networks
  • Non-cooperative games and distributed resource allocation
  • Cooperative Games and transmit strategies in interference networks
  • Coalition games and ad-hoc networks

Course with Credit Points: 5

Lecturer: Prof. Eduard Jorswieck
Assistenten: Siddarth Marwaha and Zheng Ge​​​​​​​


Lecture (ET-NT-117)
Contact hours (SWS): 2h
Start: 8th April, 2025 (first lecture 10.04.2025)
Time: Tuesday 09:45 - 11:15
Location: SN 22.2
Language: German or English
StudIP Link

Exercise (ET-NT-119)
Contact hours (SWS): 1h
Start: 17th April, 2025
Time: Thu 08:00 - 9:30 / 14-täglich
Location: SN 22.2
Language: German and English
StudIP Link

Accompanying material

Lecture notes are available at StudIP. The password will be announced in the first lecture. 

Latest Information

When applicable, current announcements can be found in Stud-IP.

Examination

Examination type: in presence
Duration: 120 min.
Date: 04 August 2025
Time: 8:30 - 10:30
Entry admission: 8:00
Location: SN 23.1
Consultation hour: by agreement with Siddarth Marwaha. 

Please register as usual in TUConnect. 

Literature
  • Stephen Boyd and Vandenberghe: Convex Opimization, Cambridge University Press, 2004. Online: https://web.stanford.edu/~boyd/cvxbook/
  • M.J. Holler und G. Illing: Einführung in die Spieltheorie, Springer, 4. Auflage, 2000. Online: https://link.springer.com/book/10.1007/978-3-642-31963-1

Optional Literature

  • Dimitri P. Bertsekas: Convex Analysis and Optimization Cambridge University Press, 2003.
  • Hoang Tuy: Convex Analysis and Global Optimization, Kluwer Academic (2016).
  • M.J. Osborne und A. Rubinstein: A Course in Game Theory , The MIT Press, 1994
  • D. Fudenberg und J. Tirole: Game Theory, The MIT Press, 1991.
  • A. B. MacKenzie und L. A. DaSilva: Game Theory for Wireless Engineers (Synthesis Lectures on Communications), Morgan & Claypool Publishers, 2006.
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