ELEC5508: Semester 2, 2021

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Units ELEC5508 Semester 2 2021 [Normal day]

Unit outline_

ELEC5508: Wireless Engineering

Semester 2, 2021 [Normal day] - Remote

Overview

This unit will introduce the key ideas in modern wireless telecommunications networks. It will address both physical layer issues such as propagation and modulation, plus network layer issues such as capacity, radio resource management and mobility management issues. The following topics are covered. Wireless channel: Multipath fading, frequency selective fading, Doppler spread, statistical models, diversity, GSM, OFDM. Capacity and Interference: Cell types, coverage, frequency reuse, interference management, SIMO, MISO, multiuser diversity, CDMA, OFDMA, beamforming, superposition coding. MIMO: SVD, waterfilling, beamforming, V-BLAST, SIC, MMSE, Power Allocation. LTE/LTE-Advanced: Uplink-downlink channels, control signals, data transmission, spatial multiplexing, CoMP, spectrum reuse, heterogeneous networks, inter-cell interference coordination, carrier aggregation. Queueing theory: basic models, queueing systems, waiting time, delay, queue length, priority queues, wireless network virtualization (WNV) queues.

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Basic knowledge in probability and statistics, analog and digital communications, error probability calculation in communications channels, and telecommunications network.
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Wibowo Hardjawana, wibowo.hardjawana@sydney.edu.au
Laboratory supervisor(s)	Thomas Huang, thomas.huang@sydney.edu.au
Tutor(s)	Alva Kosasih, alva.kosasih@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Open book)	Final Quiz	30%	Formal exam period	1 hour
Outcomes assessed:
Assignment	Lab projects	40%	Multiple weeks	5 lab projects
Outcomes assessed:
Small test	Mid-semester quiz	30%	Week 08	n/a
Outcomes assessed:
= group assignment ? = Type C final exam ?

Assessment summary

Lab projects: carried out during the semester to assess students’ understanding of the simulations and experimental results for basic wireless systems.
Mid-semester quiz: will assess student’ understanding of basic knowledge in wireless system performance.
Final exam: will assess students’ understanding of basic knowledge in wireless system performance as well as the ability to apply fundamental knowledge and theory in network design.

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	Introduction and Overview on Wireless Communications	Lecture and tutorial (5 hr)
Week 02	Wireless channel	Lecture and tutorial (5 hr)
Week 03	Diversity and OFDM	Lecture and tutorial (5 hr)
Week 04	Capacity and interference	Lecture and tutorial (5 hr)
Week 05	Multiuser diversity	Lecture and tutorial (5 hr)
Week 06	MIMO: model	Lecture and tutorial (5 hr)
Week 07	MIMO: architecture	Lecture and tutorial (5 hr)
Week 09	5G NR Architecture	Lecture and tutorial (5 hr)
Week 10	5G NR Physical Layer	Lecture and tutorial (5 hr)
Week 11	5G NR Higher Layers	Lecture and tutorial (5 hr)
Week 12	Traffic analysis: queuing theory	Lecture and tutorial (5 hr)
Week 13	Advance Topic/Guest Lecture	Lecture and tutorial (5 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

Fundamental of Wireless Communications
Mobile Communications
Wireless Communications Principles and Practice
Other references as directed during the course

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

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. instigate inquiry and knowledge development on the technical advancements of various wireless technologies using varied media formats such as open literature and the internet
LO2. write reports and make presentations delivering technical and often complex material in a language and form commensurate with the expected level of understanding of stakeholders on the subject of wireless systems
LO3. design wireless networks on a system level such as WLAN and WiMAX using a clearly defined approach based on the specifications of an industrial customer
LO4. demonstrate an understanding of various wireless networks in terms of application scenarios, performance indicators, and design methodology
LO5. evaluate the performance of a wireless system in fading channels using probability and statistical theory to the extent of the material presented.

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 significant 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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