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The current and official versions of the course specifications are available on the web at https://www.usq.edu.au/course/specification/current.
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ELE4607 Advanced Digital Communications

Semester 1, 2022 Toowoomba On-campus
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Engineering
Student contribution band : Band 2
Grading basis : Graded
Version produced : 2 July 2022

Staffing

Examiner: John Leis

Requisites

Pre-requisite: ELE1301 or Students must be enrolled in one of the following Programs: GCEN or METC or GCNS or GDNS or MENS or MEPR

Overview

Advanced digital encoding, compression and encryption are vital to modern telecommunications and networks. Engineers operating at the advanced level of telecommunications networks are required to understand, maintain and configure advanced telecommunications systems. Furthermore, they may be required to design new systems involving data compression and encryption.

This course examines the methods used for coding, transmitting and storing continuous signals such as speech, music, images and video. The course covers such topics as data compression, encryption, and error control in a digital transmission system.
The course also seeks to impart an understanding of current research problems in the digital communications field. It is thus suitable for students who may wish to undertake research and development work in this important field.

Course learning outcomes

The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:

  1. describe quantization techniques;
  2. to explain the operation of lossless coding algorithms, and in particular their relationship to data probabilities;
  3. implement transform-domain encoders and decoders;
  4. describe coding algorithms used in speech communications such as linear predictive coding and code-excited linear prediction;
  5. describe coding algorithms used in video communications such as the discrete cosine transform and intraframe predictors;
  6. analyse the computational complexity of coding algorithms and assess their suitability for real-time implementation on DSP systems;

Topics

Description Weighting(%)
1. Principles of quantization 20.00
2. Mathematical transformations 20.00
3. Audio signal modelling 20.00
4. Video signal modelling 20.00
5. Lossless coding algorithms 10.00
6. DSP systems implementation 10.00

Text and materials required to be purchased or accessed

Leis, JW 2018, Communication Systems Principles Using MATLAB, John Wiley, NY.
MATLAB (Student Edition).

Student workload expectations

To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.

Assessment details

Approach Type Description Group
Assessment
Weighting (%) Course learning outcomes
Assignments Design Model (theoretical) No 10 3,5,6
Assignments Written Problem Solving No 40 3,4,5
Examinations Non-invigilated Time limited online examinatn No 50 1,2,3,4,5,6
Date printed 2 July 2022