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Communication Networks Modeling and Optimization

CIT4330006Examination Performance5 ECTSEnglishsummer semesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You will learn probabilistic models and optimization approaches for describing and controlling communication networks (wireless and wired). In the end you can apply Markov models and queueing theory as well as formulate optimization problems for network parameters and solve them with solver software.

What you will be able to do

  • Understand probabilistic and stochastic processes
  • Apply discrete and continuous Markov chains
  • Master fundamentals of queueing theory (including M/G/1, special cases, networks)
  • Analyze statistical multiplexing and buffer behavior
  • Formulate scheduling and network optimization problems
  • Implement optimization tasks with software (e.g., CVX, Gurobi)

What the module consists of

  • VorlesungConveying the theoretical foundations in a lecturer-centered form
  • Übung/TutorialSolving analytical problems for deepening
  • Homework/ProgrammieraufgabenPractical application with optimization software (6–7 tasks)

Teaching method

  • LehrvortragIntroduction and explanation of the theory
  • Übungsaufgaben auf Tafel/NotebookReinforcement and application of analytical methods
  • Software‑gestützte BeispieleTraining in handling optimization solvers and implementation
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Official page in TUMonline · Details are not binding.