ELEC9505: Semester 1, 2021

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Units ELEC9505 Semester 1 2021 [Normal day]

Unit outline_

ELEC9505: Communications

Semester 1, 2021 [Normal day] - Remote

Overview

This is an intermediate unit of study in telecommunications following on the general concepts studied in earlier units such as Signal and Systems and leading on to more advanced units such as Digital Communication Systems. Student will learn how to critically design and evaluate digital communication systems including the elements of a digital transmission system, understand the limitations of communications channels, different analog and digital modulation schemes and reasons to use digital techniques instead of analog, and the effect of noise and interference in performance of the digital communication systems. On completion of this unit, studentss will have sufficient knowledge of the physical channel of a telecommunications network to approach the study of higher layers of the network stack. The following topics are covered. Introduction to communications systems, random signals and stochastic process, components, signals and channels, sampling, quantization, pulse amplitude modulation (PAM), pulse code modulation (PCM), quantization noise, time division multiplexing, delta modulation. Digital communications: baseband signals, digital PAM, eye diagram, equalization, correlative coding, error probabilities in baseband digital transmission, bandpass transmission, digital amplitude shift keying (ASK), frequency shift keying (FSK), phase shift keying (PSK) and quadrature shift keying (QPSK), error probabilities in bandpass digital transmission, a case study of digital communication systems. Introduction to information theory: fundamental limits in communications, channel capacity and channel coding, signal compression.

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	ELEC5739
Assumed knowledge ?	ELEC9302
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Abbas Jamalipour, abbas.jamalipour@sydney.edu.au
Demonstrator(s)	Forough Shirin Abkenar, forough.shirinabkenar@sydney.edu.au
Tutor(s)	Sarumathi Murali, sarumathi.murali@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Record+)	Final Exam Final Exam	55%	Formal exam period	2 hours
Outcomes assessed:
Participation	Tutorial assessment reports	10%	Multiple weeks	n/a
Outcomes assessed:
Assignment	Lab report - individual preparation & group final	35%	Multiple weeks	n/a
Outcomes assessed:
= group assignment ? = Type B final exam ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. Introduction to the unit of study; 2. Elements of communications systems, communication resources, source of information, and noise	Online class (2 hr)
Week 02	1. Communication networks, communications channels, modulation process, analog and digital communications, and Shannon’s information capacity theorem; 2. Examples	Online class (2 hr)
Week 03	1. Continuous-wave modulation; 2. Introduction to CWM, amplitude modulation, linear modulation, DSB-SC modulation, coherent detection, and quadrature carrier multiplexing	Online class (2 hr)
Week 04	Single-sideband modulation, vestigial sideband modulation, frequency translation, FDM, and angle modulation	Online class (2 hr)
Week 05	FM, narrowband and wideband FM, nonlinear effects in FM noise in CWM, and noise in AM and FM receivers	Online class (2 hr)
Week 06	Pulse modulation sampling process and sampling theorem, PAM, BW-noise trade-off, and quantization process.	Online class (2 hr)
Week 07	PCM, noise in PCM, TDM, and digital multiplexers	Online class (2 hr)
Week 08	Delta modulation, linear prediction, differential PCM, and adaptive differential PCM	Online class (2 hr)
Week 09	1. Baseband pulse transmission; 2. Matched filter, error rate due to noise, and inter-symbol interference	Online class (2 hr)
Week 10	Nyquist’s criterion, baseband M-ary PAM, DSL, optimum linear receiver, and adaptive equalization	Online class (2 hr)
Week 11	1. Signal-space analysis; 2. Geometric representation of signals, vector channel conversion, likelihood functions, coherent detection of signals in noise, correlation receiver, and probability of error	Online class (2 hr)
Week 12	1. Passband digital transmission; 2. Passband transmission model, coherent PSK, hybrid ASK/PSK, coherent FSK, unknown phase signal detection, non-coherent orthogonal modulation, and non-coherent binary FSK	Online class (2 hr)
Week 13	Differential PSK, comparison between different digital modulation schemes, voice-band modems, multi-channel modulation, and synchronization	Online class (2 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed on the Library eReserve link available on Canvas.

Communication Systems, Simon Haykin and Michael Moher, 5th edition, John Wiley, 2009.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. work in a team, demonstrating capacity to manage complex roles and responsibilities, drawing on and optimizing the contribution of others towards the timely delivery of specific engineering tasks in a laboratory environment
LO2. design digital communication systems by applying principles and techniques developed in the material presented
LO3. recognise the limitations of communications channels, as well as different analog and digital modulation schemes and explain the reasons to use digital techniques instead of analog
LO4. demonstrate an understanding of professional practice by differentiating between theory and real communication systems, identifying economic, social and sustainability standards employed
LO5. demonstrate an understanding of the effect of noise and interference in the performance of digital communication systems
LO6. evaluate digital communication systems including the elements of a digital transmission system using knowledge of concepts, principles and techniques developed throughout the course
LO7. demonstrate an understanding of the physical channel of telecommunications networks to the extent of the information presented throughout the course.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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