Theory of Signals and Communication Systems

The details
Computer Science and Electronic Engineering (School of)
Colchester Campus
Postgraduate: Level 7
Thursday 03 October 2024
Friday 13 December 2024
24 July 2023


Requisites for this module



Key module for

MSC H61012 Electronic Engineering,
MSC H610CH Electronic Engineering,
MSC H64112 5G and Emerging Communication Systems,
MSC GH64N1 Computer Systems Engineering,
MENGH613 Electronic Engineering,
MENGH614 Electronic Engineering (Integrated Masters, Including Placement Year)

Module description

This module provides the key concepts for the study of communication systems and understanding their operation. It starts with an introduction to signal processing: classification of signals, Fourier transforms, random processes, and analog to digital conversion.

It then uses these tools to examine the operation of modern communication systems, such as analog and digital modulation, including amplitude modulation, frequency modulation, phase modulation, and multisymbol phase and quadrature amplitude modulation techniques. Various sources of random signals and noise, including quantisation noise, thermal Nyquist-Johnson noise, and additive white-Gaussian noise (AWGN) and their contributions to bit error rate (BER) in digital systems are studied. Practical example of communication systems will be studied and simulated during the lab classes. The course finishes with a discussion of basics of information theory, concepts of self-information and information entropy and their applications to source coding and evaluation of performance bounds (Shannon-Hartley law), and identifies how close commercially important systems are to these bounds.

Module aims

The module aims to provide a mathematical foundation for the study of communication systems and their operation.

Module learning outcomes

On completion of the course, the student is expected to:

1. Classify signals with respect to their properties.
2. Demonstrate a critical understanding of the key concepts of spectral analysis.
3. Classify and analyse a LTI system in the time and frequency domains.
4. Describe a random process and characterize its spectral properties.
5. Demonstrate a critical understanding of the effect of noise in communications.
6. Describe analog and digital signal modulation techniques and analog to digital conversion.
7. Explain the principles of baseband and band-pass digital transmission.
8. Apply concepts of information theory to design Huffman codes to compress data.
9. Describe digital communication systems and apply the Shannon-Hartley bound.

Module information

Outline Syllabus

Signal analysis fundamentals:
Signal representation and classification; energy and power;

Transform theory:
Fourier series; Definition of Fourier transforms; Energy and power signals and spectra; Energy and power spectral density; Modulation.

System analysis:
Linear Time Invariant (LTI) systems, impulse response and transfer function; Discrete time systems;
Filters theory.

Digital to Analog conversion: Sampling; Quantization.

Probability methods in communications:
Sample space, discrete and continuous random variables; Conditional probability and statistical independence, Probability models and their application in communications; Random processes; Gaussian model;

Noise in digital communication systems:
Sources of noise, quantisation noise, thermal Nyquist-Johnson noise, additive white Gaussian noise (AWGN) in communication systems, Signal-to-noise ratio (SNR).

Analog Modulations:
Amplitude modulation; baseband and bandpass signals; Frequency modulation; Types of linear CW modulation, DSBTC and DSBSC modulation schemes.

Digital Modulations:
Digital transmission; Signal space and signal constellations; ASK, FSK and PSK modulation schemes, Multisymbol signalling, phase modulation and quadrature amplitude modulation (QAM) techniques.
Transmission in optical-fibre communication systems and in satellite systems.

Information theory and coding:
Introduction to information theory, information measure, self-information, information entropy, redundancy of message; Information coding, code performance; Discrete memoryless sources (DMSs), message statistics, digital source coding, the Huffman algorithm, code efficiency estimate; Shannon coding theorem and Shannon-Hartley bound.

The exam in this module will take the form of an oral examination.

Learning and teaching methods

A combination of lectures and classes. The final assessment will include an oral examination of 30 minutes duration.


This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Progress Test 1 (In person, MCQ Moodle Based Test, Closed Book)    15% 
Coursework   Progress Test 2 (In person, MCQ Moodle Based Test, Closed Book)    15% 
Coursework   Oral Exam (30 Mins)    50% 
Coursework   Assignment 1 - Report on Practical Exercises and Essays     20% 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Yuli Yang, email: yuli.yang@essex.ac.uk.
Dr Yuli Yang, Dr De Feo
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770



External examiner

Dr Anthony Olufemi Tesimi Adeyemi-Ejeye
Available via Moodle
Of 39 hours, 28 (71.8%) hours available to students:
11 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).


Further information

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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