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CECS Professional Skills Mapping

ENGN3226 — Digital Communications

code: ENGN3226
name: Digital Communications
unit value: 6
description: This course presents the principles and techniques fundamental to the analysis and design of digital communication systems. It focuses on the basic building blocks of a digital communication system (channel encoder/decoder, digital modulator/demodulator and channel characteristics). The emphasis is on mathematical underpinnings of communications theory along with practical applications. Specific topics include:

• Review of Probability and Random Processes and Modelling of Gaussian noise process.
• Digital Modulation Techniques: Signal space analysis, BPSK, QPSK, QAM.
• Digital Demodulation & Detection Techniques: Correlator-demodulator, Maximum likelihood detection (MLD) in additive white Gaussian noise (AWGN), bit error rate (BER) performance.
• Channel Encoder/Decoder: Linear block codes, Cyclic codes, Convolutional codes, Viterbi algorithm.
• Information Theory and Source Coding: Source Entropy, Huffman Coding, Channel Capacity.

Advanced topics in digital communications are briefly discussed if time allows. Matlab is used in the analysis and design.
P&C: https://programsandcourses.anu.edu.au/course/ENGN3226
course learning outcomes:
  1. Model digital communication signals and systems using appropriate mathematical techniques (e.g., probability, random process, signal-space analysis, constellation diagram, trellis diagram).
  2. Analyse the performance of digital modulation schemes over AWGN channels and choose appropriate modulation schemes according to design criteria.
  3. Characterise error-control codes and apply the encoding and decoding processes.
  4. Compute source entropy and channel capacity and apply the Huffman coding technique.
  5. Provide sound evaluation of practical digital communication systems in terms of their performance and complexity.
  6. Simulate digital communication systems in a proficient and confident manner.
  7. Apply engineering design practice in a laboratory setting, individually or in a small team, and communicate the results effectively.
assessment:
  1. Assignments (12%)
  2. Computer and Hardware Labs (15%)
  3. Mid-Term exam (20%)
  4. Final Exam (53%)

Mapped learning outcomes

learning outcome1. KNOWLEDGE AND SKILL BASE2. ENGINEERING APPLICATION ABILITY3. PROFESSIONAL AND PERSONAL ATTRIBUTESassessment tasks
1.11.21.31.41.51.62.12.22.32.43.13.23.33.43.53.61234
  1. Model digital communication signals and systems using appropriate mathematical techniques (e.g., probability, random process, signal-space analysis, constellation diagram, trellis diagram).
✓✓✓✓✓✓✓✓✓
  1. Analyse the performance of digital modulation schemes over AWGN channels and choose appropriate modulation schemes according to design criteria.
✓✓✓✓✓✓✓✓✓✓✓
  1. Characterise error-control codes and apply the encoding and decoding processes.
✓✓✓✓✓✓✓✓✓
  1. Compute source entropy and channel capacity and apply the Huffman coding technique.
✓✓✓✓✓✓✓
  1. Provide sound evaluation of practical digital communication systems in terms of their performance and complexity.
✓✓✓✓✓✓✓✓✓✓
  1. Simulate digital communication systems in a proficient and confident manner.
✓✓✓✓✓
  1. Apply engineering design practice in a laboratory setting, individually or in a small team, and communicate the results effectively.
✓✓✓✓✓

Course contribution towards the Engineers Australia Stage 1 Competency Standard

This table depicts the relative contribution of this course towards the Engineers Australia Stage 1 Competency Standard. Note that this illustration is indicative only, and may not take into account any recent changes to the course. You are advised to review the official course page on P&C for current information..

1. KNOWLEDGE AND SKILL BASE
1.1
 
1.2
 
1.3
 
1.4
 
1.5
1.6
2. ENGINEERING APPLICATION ABILITY
2.1
 
2.2
 
2.3
 
2.4
3. PROFESSIONAL AND PERSONAL ATTRIBUTES
3.1
3.2
 
3.3
 
3.4
3.5
 
3.6
 

Engineers Australia Stage 1 Competency Standard — summary

1. KNOWLEDGE AND SKILL BASE
✓1.1Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.
✓1.2Conceptual understanding of the, mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.
✓1.3In depth understanding of specialist bodies of knowledge within the engineering discipline.
✓1.4Discernment of knowledge development and research directions within the engineering discipline.
1.5Knowledge of contextual factors impacting the engineering discipline.
1.6Understanding of the scope, principles, norms, accountabilities and bounds of contemporary engineering practice in the engineering discipline.
2. ENGINEERING APPLICATION ABILITY
✓2.1Application of established engineering methods to complex engineering problem solving.
✓2.2Fluent application of engineering techniques, tools and resources.
✓2.3Application of systematic engineering synthesis and design processes.
2.4Application of systematic approaches to the conduct and management of engineering projects.
3. PROFESSIONAL AND PERSONAL ATTRIBUTES
3.1Ethical conduct and professional accountability.
✓3.2Effective oral and written communication in professional and lay domains.
✓3.3Creative, innovative and pro-active demeanour.
3.4Professional use and management of information.
✓3.5Orderly management of self, and professional conduct.
✓3.6Effective team membership and team leadership.

Updated:  18 February 2021/ Responsible Officer:  Dean, CECS/ Page Contact:  CECS Academic Education Services