Network Planning

Vortragende/r (Mitwirkende/r)
Umfang3 SWS
SemesterWintersemester 2020/21
Stellung in StudienplänenSiehe TUMonline
TermineSiehe TUMonline




This course should enable students to: • Summarize the goals and issues in network planning • Describe the processes for network planning • Formulate linear optimization models for network problems • Explain the differences between the various modeling approaches • Discuss the pros and cons of solving approaches • Identify key parameters influential in modeling complexity, solving time, and computation results


Introduction: Motivation, Range of Tasks, Application Areas, Classification, Planning Process, Traffic Engineering; Related Optimization Fundamentals: Mathematical Formulation, Categories, Solution Methods (principles of exact and heuristic methods); Traffic and Demand Modeling: Traffic Types, Modeling, Forecasting Network Topology Design: Initial Planning, Extension Planning, Site Selection; Network Dimensioning: Approaches for Circuit and Packet Switched Networks, Optimization Problems, Representative Heuristics; Resilience Planning: Redundancy Concepts, Disjointness, Resource Sharing; Generalizations: Multilayer Planning, Multiperiod Planning; Access Networks Planning: Overview, Selected Problems; Mobile Networks Planning: Overview; Post-Planning Analysis: Network Simulation, Availability Analysis In Practice: Network Planning Tools, Economics Aspects; Additionally, students will practically model and solve planning problems with the student version of AMPL ("A Modeling Language for Mathematical Programming"), and potentially with network planning and simulation tools.

Inhaltliche Voraussetzungen

Basic Knowledge of Communication Networks The knowledge of the following modules is strongly recommended for this course: - Broadband Communication Networks

Lehr- und Lernmethoden

Learning method: In addition to the individual methods of the students further knowledge is gained by own lab experiments and reading of books and articles. Supportive programming: • Used to exemplify modeling and solving in software • Modeling: “A Modeling Language for Mathematical Programming (AMPL)” Web-Interface: Book: • Solving: LPSOLVE Teaching method: During the lectures students are instructed in a teacher-centered style. The exercises are a mixture of question-based exercises and lab experiments. Interaction between students and teacher is steadily performed. The students are guided to solve problems independently using a computer based network planning tool.

Studien-, Prüfungsleistung

The type of examination is adapted to the different learning outcomes: Knowledge-based learning results are examined during a written exam with 60 minutes duration. During the semester an optional mid term exam will be offered, which can be used to improve the final grade. The final grade is composed of the following elements: - 100% final exam If the mid term exam is passed, this leads to an improvement of the overall grade by a bonus of 0,3. The mid term exam evaluates the students knowledge of the lecture content, reading additional scientific articles and pratical experience with a network planning tool.

Empfohlene Literatur

The following literature is recommended: • M. Pióro and D. Medhi, “Routing, Flow, and Capacity Design in Communication and Computer Networks,” Morgan Kaufmann, 2004. • W. D. Grover, “Mesh-based Survivable Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking,” Prentice Hall, 2003. • T. G. Robertazzi, “Planning Telecommunication Networks,” IEEE Press, Piscataway, 1999. • J. L. Gross and J. Yellen, “Graph Theory and Its Applications,” CRC Press, 1998. • J. M. Simmons, “Optical Network Design and Planning,” Springer, 2014. • D. Schupke, O. González de Dios, D. Tipper, IEEE Communications Magazine, Feature Topic “Advances in Network Planning,” January and February 2014 • R. Fourer; D. M. Gay; D. W. Kernighan, “AMPL: A Modeling Language for Mathematical Programming,” Duxbury Press / Brooks/Cole Publishing Company, 2002. • R. Fourer; D. M. Gay; B. W. Kernighan, “A Modeling Language for Mathematical Programming,” Management Science 36 (1990) 519-554.