- Code ENGN6626
- Unit Value 6 units
- Offered by Research School of Engineering
- ANU College ANU College of Engineering and Computer Science
- Course subject Engineering
- Academic career PGRD
- AsPr Parastoo Sadeghi
- Dr Xiangyun Zhou
- Mode of delivery In Person
- Co-taught Course
First Semester 2016
See Future Offerings
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:
- Probability and Random Processes: Probability distributions, Random variables, Random processes, Statistical averages, Correlation.
- 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: Source Entropy, Huffman Coding, Channel Capacity.
Advanced topics in digital communications are briefly discussed if time allows. Matlab is used extensively in the analysis and design.
Upon successful completion, students will have the knowledge and skills to:
1. Describe random variables and random processes in terms of their mean, variance, and correlation functions and characterize important random variables and processes.
2. Identify and analyse methods of digital modulation and compare their performance using signal-space analysis.
3. Explain receiver techniques for detection of a signal in AWGN channels.
4. Characterize error-control coding techniques and explain the working of Viterbi algorithm.
5. Compute source entropy and channel capacity and apply Huffman coding technique.
6. Develop an intuitive grasp of random variables and notion of random process and their characteristics.
7. Explain in simple words the working principles of basic building blocks of a digital communication systems.
8. Model digital communication systems using appropriate mathematical techniques (probability distributions, signal-space analysis, constellation diagrams, trellis graphs).
9. Provide sound evaluation of digital communication systems in terms of their performance and complexity.
10. Use Matlab for simulation of digital communication systems in a knowledgeable and confident manner.
Mid-semester Exam 20%
Final Exam 53%
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9-10 hours per week workload is expected. This includes
36-39 hours of formal lectures,
2 three-hour computer labs,
3 three-hour hardware labs,
4-6 one-hour formal tutorials,
plus adequate self study, assignments, lab reports and exam preparations.
Requisite and Incompatibility
Preliminary ReadingRecommended reading:
- Proakis, John G., Digital Communications, 4th ed, McGraw Hill, 2001
- Sklar, Bernard, Digital Communications: Fundamentals and Applications, 2nd edition, Prentice Hall
- Rappaport, Theodore S. Wireless Communications Principles & Practice, 2nd edition, Prentice Hall, 2002.
- Haykin, Simon, Communication Systems, 4th edition, John Wiley, 2001.
- Goldsmith, Andrea Wireless Communications, Cambridge University Press, 2005.
- Proakis, J.G. & Salehi, M., Communications Systems Engineering, 2nd edition, Pearson/Prentice Hall, 2002
Assumed knowledge of electronics and communications enigneering
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|3174||15 Feb 2016||26 Feb 2016||31 Mar 2016||27 May 2016||In Person||N/A|