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Module

EEE2009 : Signals and Communications II

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Martin Johnston
  • Lecturer: Dr Mohsen Naqvi
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 2 Credit Value: 20
ECTS Credits: 10.0

Aims

To provide knowledge and understanding of the fundamentals of linear systems theory and its application to the analysis of signals and system behaviour.
To provide understanding of the basic design principles of communication systems.
To enhance understanding of communications concepts and systems.
To enable the student to appreciate the vital role of analogue and digital communications in the modern world.
To understand basic concepts of information theory and channel coding.

Outline Of Syllabus

Signals and Systems Overview
Introduction to continuous and discrete signals and systems, classifications of signals, operations of signals, convolution.

Laplace Transform
The definition of Laplace transforms and their properties and applications, inverse Laplace transform, continuous time poles and zeros concepts, circuit analysis by applying Laplace transforms.

Fourier transform
The impulse response, transfer function, Fourier transforms for systems and signals and their applications, inverse Fourier transform, Fourier transform properties, Discrete Fourier transforms, Fast Fourier transform and their application to beyond 3G mobile communication systems.

Z-Transform
Z transform and its applications, sampling, discrete time pole/zero concepts, description of transfer matrices, analysis of discrete time systems.


Communication system overview
Introduction to elements of communication systems, coding, modulation, channels.

Analogue modulation
Amplitude modulation, frequency modulation, narrow and wide band FM systems.

Digital Communication Schemes
Amplitude shift keying (ASK), Frequency shift keying (FSK), Phase shift keying (PSK), Quadrature amplitude modulation (QAM), spectrum efficiency and system demands, performance in noisy channels.

Information Theory
Entropy and mutual information, conditional entropy and mutual information, relationship between entropy and mutual information, channel capacity and Shannon theorems,

Error detection and correction coding
Introduction to channel coding and its benefits, the importance of the minimum Hamming distance and its effect on error detection and correction, a study of two coding schemes: parity check and repetition codes, simple decoding algorithms.

Teaching Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Assessment Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Reading Lists

Timetable