2017/18 Taught Postgraduate Module Catalogue

ELEC5420M Communication Network Design

15 creditsClass Size: 60

Module manager: Prof. Jaafar Elmirghani
Email: j.m.h.elmirghani@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

This module is not approved as an Elective

Objectives

To teach the student the basic models, algorithms and theories of communication networks design;
- To understand linear programing and meta heuristics as tools for communication networks design and analyse case studies and implementation scenarios;
- To understand dynamic network design by covering topics such as dynamic programming, game theory, Markov chains and queuing theory.

Learning outcomes
On completion of this module, students should be able to:
- understand the underlying principles of communication network design and optimisation;
- construct basic network optimisation formulations with cost functions and constraints and solve these formulations;
- appreciate future developments and design requirements (e.g. core of the Internet, wireless networks, access networks).
- understand the need for meta heuristics and be able to explain a selection (e.g. Tabu search vs genetic algorithms);
- understand the basic principles of dynamic network designs, for example queuing performance and hence perform delay and packet loss evaluations and compare and contrast network designs and performance;
- perform dynamic programming analysis and construct game theory network optimisation formulations;
- use the theoretical and technical content of the module to assess the limitations and possibilities of communication networks

Syllabus

1. Network optimization
- Linear programming
- Linear programming solutions using simplex algorithm
- Duality and sensitivity analysis
- Network optimization models: shortest path, minimum spanning tree, maximum flow, minimum cost
- Example in communication networks

2. Meta heuristics and programming
- Integer programming: branch-and-bound technique
- Nonlinear programming
- Tabu search
- Genetic algorithms
- Use of meta heuristics in network design

3. Dynamic network design
- Dynamic programming
- Game theory: two-person, zero-sum game, games with mixed strategies, graphical solution procedure, solving by linear programing
- Markov chains: stochastic Processes, Chapman-Kolmogorov equations, states of a Markov chain
- Queuing theory: birth-and-death, priority-discipline queuing models, queuing networks, model with non-exponential distributions
- Evaluation of dynamic performance of typical communication networks

Teaching methods

Delivery type	Number	Length hours	Student hours
Example Class	4	1.00	4.00
Class tests, exams and assessment	1	4.00	4.00
Lecture	10	2.00	20.00
Private study hours			122.00
Total Contact hours			28.00
Total hours (100hr per 10 credits)			150.00

Private study

Directed reading, working through set problems, performing software simulations provided by lecturer and developing his/her own.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	In-semester assignment	20.00
Total percentage (Assessment Coursework)		20.00

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Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	3 hr 00 mins	80.00
Total percentage (Assessment Exams)		80.00

Re-sits for ELEC modules are subject to the rules in the School’s Code of Practice on Assessment. Students should be aware that, for some modules, a re-sit may only be conducted on an internal basis (with tuition) in the next academic session.

Reading list

There is no reading list for this module

Last updated: 08/05/2017

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