Registration Information:

  • All graduate AND undergraduate courses must be registered on paper using an Academic Change Form and approved by your supervisor
  • When registering for a course, you must indicate whether the course will be primary or secondary to your program
  • All courses which are part of your required program must be listed as primary
  • All primary courses require a pass mark of B- or 2.7 or 70%
  • Courses taken outside the department and that are used to meet degree requirements should be in a related field to the student's research and must have course instructor's approval
  • Students who audit graduate courses may be required to participate in assignments but not final examinations; consult the instructor beforehand.
  • It is the student's responsibility to adhere to the guidelines for dropping and adding courses by the relevant deadlines.

Winter Timetable 2018-2019 (PDF document)

Courses offered at Royal Military College

RMC course descriptions

To register for a course at RMC, complete and submit the application form

ECE Graduate Courses

Fall 2018 Courses
Winter 2019 Courses
Not Currently Offered
ELEC 831 - Power Electronics


Power electronics plays a key role in our modern society. It is helping us in building modern infrastructures that are not only providing us a comfortable life but are also environmental friendly. This course presents some of the advanced work in the field of resonant and soft-switching converters. We will see how this field has evolved through the years in terms of power electronics converter topologies and control techniques. We will also see how this field has impacted many real-life applications such as space, telecommunications, information processing and renewable energy generation.


  • Variable Frequency Resonant Converters
  • Modeling of Resonant Converters
  • Phase-shift modulated resonant converters
  • Asymmetrical PWM resonant converters
  • Naturally commutated soft switching converters
  • Auxiliary Commutated Soft Switching Converters


There will be two independent projects for this class. Students will present their projects to the class. The course grade will be based on the class presentations and submissions of project reports.


ELEC 843 - Control of Discrete Event Systems

Course Website


In this course we will study discrete-event processes, such as computer systems and manufacturing systems, that require control to induce desirable behaviour. Informally, a discrete-event system (DES) is a process (or set of processes) that starts out in some initial state, and is transformed from state to state by the occurrence of discrete events. Such a system can be thought of as a set of sequences of events, each sequence describing a series of actions that occur within the system. Control amounts to inhibiting the behaviour of such processes by disabling events (or preventing certain actions from occurring). Standard models for the control of discrete-event systems are taken from computer science and mathematics and include automata or finite-state machines, directed graphs, Petri nets, modal logic (such as temporal logic) and algebras.

Topics covered in the course will include some of the following: basic automata and formal language theory; modeling of plants and supervisors for discrete-event control problems; centralized control problems; modular supervision; partial observation; nonblocking solutions; decentralized control problems; computational complexity of DES control problems; timed discrete-event systems; and control using a limited-lookahead approach. Small-scale examples will be used to motivate material. We will show how the course material can be used to model applications such as communication protocol verification, system secrecy , factory automation, concurrency control, and emergency response to medical outbreaks.

Much of the material that will be used in this course comes from automata theory and formal languages and the mathematics used is discrete mathematics and is closest in flavour to algebra, as opposed to calculus. Students are not expected to have any specific course prerequisites or formal background; however, students are expected to be competent at mathematical proofs (especially mathematical induction), formal reasoning and logical arguments. Some familiarity with automata theory, graph theory, or propositional logic is a bonus but is not essential.


1. Introduction (1.3)
  • What are discrete-event systems (DESs)?
  • Why should we study how to control them?
  • What types of mathematical models are used to represent DESs?
  • Automata, finite-state machines, directed graphs (2.1-2.4)
  • Petri nets (4.1-4.2)
  • Mathematical Logic
  • Algebra
2. Automata Theory and the Theory of Formal Languages (2.1-2.4)
  • Formal languages (2.2.1)
  • Regular expressions (2.4.2)
  • Automata (2.2.2)
  • How can automata and languages be used to describe DESs?
  • The relationship between finite-state automata and regular languages (2.4)
  • Nondeterministic finite-state automaton (NFA); converting NFA to language-equivalent deterministic finite-state automation (DFA) (2.3.3)
3. DES Control Problems (3.1-3.3)
  • Basic Ramadge-Wonham concepts: how to model the process to be controlled (as an automaton), how to model "desired behaviour", how to formulate control problems (3.1-3.2)
  • Concept of legal language (3.3)
  • Concept of supervisor (3.2)
  • Generated versus marked behaviour (3.2.1)
  • Concept of nonblocking solutions (3.2.1)
  • Ways to combine several processes: shuffle, intersection, synchronous product (2.3.2)
4. Centralized DES Control Problems (3.4-3.5)
  • Motivating examples
  • Concept of controllability (3.4.1)
  • Concept of supremal controllable sublanguage (3.4.3)
  • Formulations of centralized DES problems and their solutions (3.4.4-3.4.5)
  • Computing supremal controllable sublanguage (3.5.3)
  • Cat and Mouse example
5. Modular Supervision (3.6)
  • Supervisor conjunction
  • Nonblocking solutions (3.6)
  • Small-scale manufacturing system example
6. Centralized DES Control Problems with Partial Observation (3.7)
  • Motivation, discussion of why it's harder to control system that cannot be fully observe
  • Concept of observability (3.7.1)
  • Formulations of centralized, partial observation DES problems and their solutions (3.7.4)
  • Suboptimal solutions: concept of "normality" (3.7.5)
  • Small example: trains on subway tracks
  • Failure diagnosis as an example of partial observation (2.5.3)
7. Decentralized DES Control Problems (3.8)
  • Local versus global specification
  • Motivating examples
  • Formulations of decentralized DES problems
  • Concepts of decomposability, co-observability (3.8.1)
  • How to solve decentralized DES problems
  • Communication protocol verification example
  • Computational complexity (3.8.5)
  • Using formal reasoning about knowledge and modal logic to model decentralized DES problems
8. Timed DESs
  • How to model DESs where events have time bounds (thus permitting real-time constraints to be realized)
  • Small-scale industrial automation problem
9. Limited Lookahead, Online Control and Dynamic DESs
  • What is limited lookahead?
  • What is online control?
  • What if plant being controlled changes over time?
  • How limited lookahead policies and online control can be applied to dynamic DESs
  • Truck company scheduling example
10. Other Applications of DES
  • Truck dispatching for mining industry
  • Emergency response protocols for epidemiological outbreaks
  • Concurrency control in software development
  • Supervisory control of biological pathways
  • Using DES to maintain secrecy
Student Accessibility

Queen’s University is committed to achieving full accessibility for persons with disabilities. Part of this commitment includes arranging academic accommodations for students with disabilities to ensure they have an equitable opportunity to participate in all of their academic activities. If you are a student with a disability and think you may need accommodations, you are strongly encouraged to contact Student Wellness Services (SWS) and register as early as possible. For more information, including important deadlines, please visit the Student Wellness website at:

Academic Integrity

It is your responsibility to adhere to academic integrity. Copying other people's work (in whole or in part) is plagiarism and is not allowed. Facilitating or allowing your work to be plagiarized is also an infringement of academic integrity. See the link to the SGS guidelines on academic integrity:

ELEC 852 - Broadband Integrated Circuits


Topics covered include S-parameter design method; filters, equalizers and amplifiers; broadband design applications of microwave integrated circuits (MIC) with emphasis on lightwave transmitters and receivers; broadband adaptive filtering for lightwave systems; monolithic microwave integrated circuits (MMIC) techniques; comparison between MIC and MMIC.


  • Understand limitations of electronic elements and their parasitics. Parasitic extraction.
  • RF, microwave and electromagnetic modelling and there limitations. Many examples in IC and PCB designs.
  • Getting the most out of your active devices. Increasing fT and fmax of FETs and BJTs.
  • Broadband amplifier design techniques. Dealing with Miller through unilaterlization and neutralization. Parasitic absorption. Applications to filters and mixers.
  • High speed digital topologies.


50% Assignments and 50% Project.

ELEC 864 - WDM Fibre Optic Communications Systems


The course will include the following topics:

      • Topic 1: Introduction: semi-conductor lasers, photodiodes, optical fibers
      • Topic 2: WDM transmission system, receiver performance, Q-factor, sensitivity
      • Topic 3: Modulators and transmitter chirp
      • Topic 4: Dispersion management and compensation, impact on WDM system performance
      • Topic 5: Fiber non-linear effects (scattering, Kerr)
      • Topic 6: Interplay between fiber nonlinearities, dispersion, and transmitter chirp.
      • Topic 7: Optical amplification (doped fiber amplifier, Raman, parametric amplification)
      • Topic 8: Polarization mode dispersion Project
        1. Students can select from a list of suggested topics or any topic in the area of optical communications (with instructor’s consent).
        2. The project will be evaluated by a number of criteria (specifics to be determined). Criteria include thoroughness of background literature search, novelty of proposed research, and quality of research (theory and/or simulation and/or experiment).
Marking Scheme

Homework Assignments - 0%
Class Project - 50% 
Final Exam - 50%

Course Material

Fiber-Optic Communication Systems, 4th Edition, Govind P. Agrawal, Wiley, 2010, ISBN 978-0-470-50511-3 
Lecture Notes 
Research Literature 

ELEC 867 - Data Communications

Course Website

ELEC867 Fall 2018

Course Instructor


Office: Walter Light Hall, Room 409
Tel: 533-6000, ext. 77672
Lab: Wireless Information Transmission Laboratory (WITL)

Time and location:

Wednesday 2:30 - 5:30 PM, WLH 620

Office Hours:


Course objectives:

  1. To provide the fundamental theories of modulation, demodulation, and detection in digital communications systems
  2. To provide the foundation for the power efficiency/bandwidth efficiency/complexity tradeoffs in digital communications systems.
  3. To provide the fundamentals of OFDM and wireless communications theories

Course topics:

  1. Introduction
  2. Baseband Demodulation/Detection
  3. Bandpass Modulation and Demodulation/Detection
  4. Baseband Representation of Bandpass Signals
  5. Bandlimited Channels and Inter-Symbol Interference (ISI)
  6. Power and Bandwidth Tradeoffs
  7. Trellis-Coded Modulation
  8. Wireless Digital Communications
  9. OFDM
  10. Adaptive Modulation
  11. Other Topics: Synchronization, CDMA, UWB, etc.


  • B. Sklar, Digital Communications, 2nd edition, Prentice Hall.

    The textbook has been placed on reserve for 1 day loans at the Engineering & Science Library.

    Other books:

    1. J. G. Proakis and M. Salehi, Communication systems engineering, 2nd edition, Prentice Hall
    2. J. G. Proakis and M. Salehi, Digital communications, 5th edition, McGrawHill
    3. M. K. Simon and M.-S. Alouini, Digital communication over fading channels, 2nd edition, Wiley
    4. A. Goldsmith, Wireless communications, Cambridge University Press
    5. D. Tse and P. Viswanath, Fundamentals of wireless communication, Cambridge University Press
  • All books have been placed on reserve for 1 day loans at the Engineering & Science Library.

    Grading policy:

    1. Homework: 10%
    2. Term project: 10%
    3. Midterm exam: 30%
    4. Final exam: 50%

    The responsibility to adhere to academic integrity:

    Please see the following FEAS guidelines:

    Disability accommodations:

    Queen’s University is committed to achieving full accessibility for persons with disabilities. Part of this commitment includes arranging academic accommodations for students with disabilities to ensure they have all equitable opportunity to participate in all of their academic activities. If you are a student with a disability and you think you may need accommodations, you are strongly encouraged to contact the Disability Services Office (DSO) and register as early as possible. For more information, including important deadlines, please visit the DSO website at:

ELEC 873 - Cluster Computing


This course covers topics related to high-performance computing (HPC) systems, from traditional to heterogeneous clusters, parallel programming models, high-performance networking and communication subsystems, and topology-aware and power-aware HPC. Research papers from literature, a term paper and presentation, project (optional), critique, and hands-on programming on clusters will play an important role in the learning process.

Text: Lecture notes, book chapters, journal and conference papers


  • Introduction to Cluster Computing
  • Parallel Programming Paradigms (MPI, OpenMP, PosixThreads, PGAS)
  • Scalability Analysis, Performance Metrics and Benchmarks
  • Interconnection Networks, High-speed Interconnects and Messaging Layers
  • Collective Communications, and One-sided Communications
  • Latency Tolerance and Overlapping Techniques
  • Heterogeneous (GPU, Xeon Phi) Computing
  • Topology-aware, and Power-aware High-Performance Computing
  • Parallel I/O, Support of Clustering, and Availability


There is no required textbook for this course. Course materials have been gathered from recent research papers and selected chapters of different textbooks.

Research Paper and Presentation

Each student will work on a research topic and will present his/her work in class. A wide range of research topics is available. Students may also propose their own topics, which must be acknowledged by the instructor. Your work may be a survey of the state-of-the-art in a particular research area, may include verification of a recent research work, or it may propose some new ideas with experimental results. Your research will be evaluated based on its importance, originality, technical quality, depth of analysis, completeness, and the final research paper and its presentation. Presentations will be typically in the last two weeks of classes; however, you are allowed to continue working on your research paper until mid-December (for the actual date, refer to the course website). Research paper is limited to 8 pages, and students are to write their papers using the standard two-column IEEE Computer Society conference paper template.

Course Project and Report

Course project is optional, but it is recommended for students in the field and those who would like to have a deeper knowledge about the design and implementation of ideas/projects in cluster computing. If you opt for the course project, the weight of the final exam will be adjusted accordingly. A wide range of project topics is available. Students may also propose their own project topics, which must be acknowledged by the instructor. Projects must be distinct from the research paper component of the course. They will be evaluated based on their technical quality, completeness, and the final report. You are allowed to continue working on your project report until mid December (for the actual date, refer to the course website).

Course Website


  • Dr. Ahmad Afsahi, P.Eng.
  • Professor and Chair of Graduate Studies
  • Department of Electrical and Computer Engineering
  • Queen's University
  • Office: Walter Light Hall, Rm 403
  • Tel: 613-533-3068
  • E-mail: ahmad.afsahi[AT]
ELEC 876 - Software Re-engineering


This course covers software re-engineering techniques and tools that facilitate the evolution of legacy systems. This course is broken into three major parts. In the first part, the course discusses the terminology and the processes pertaining to software evolution. In the second part, the course provides the fundamental re-engineering techniques to modernize legacy systems. These techniques include source code analysis, architecture recovery, and code restructuring. The last part of the course focuses on specific topics in software re-engineering research. The topics include software refactoring strategies, migration to Object Oriented platforms, quality issues in re-engineering processes, migration to network-centric environments, and software integration.

Text: Lecture notes, book chapters, journal and conference papers


  1. Introduction to software re-engineering
  2. Program comprehension
  3. Software re-engineering techniques in source code transformation and refactoring strategies
  4. Software metrics & quality
  5. Re-engineering economics
  6. Techniques for the migration of legacy systems into network centric environments
  7. Software integration issues and enabling technologies in web-enabled and distributed environments.

Course Material Info

The course will be consisted of lectures and student presentations. There are about 6 weeks of lectures. The other 6 weeks will be seminar format where students will present assigned research papers. Students will also do a project singly or in pairs, including a class presentation of the project. The marking scheme is: 

Paper Critiques (2 papers per student 10%
Paper Presentation 10%
Project Proposal 10%
Project Progress Reports  10%
Final Report 50%
Class discussion 10%

Resources for Lectures

Software Reengineering Tools

ELEC 879 - Wearable IoT Computing


This course focuses on recent advances and computing trends in wearable technologies, mobile devices, the Internet of Things (IoT), smart homes, and smart vehicles. The history, background, and applications of these systems are reviewed, followed by the description of common sensing technologies often utilized in these devices. Signal/time-series analysis techniques, machine learning algorithms, and computing methods that are often utilized in such applications will be covered in detail. The course is highly applied and students will complete a project and present their results.

The course is an option for graduate students and the delivery will be primarily in the form of lectures, as well as student-led seminars and presentations. It is anticipated that this course will appeal to students from the Department of Electrical and Computer Engineering, as well as students from other departments such as Computing, Mechanical Engineering, and Mining.

Evaluation Criteria:

  • Project and presentation: 50%
  • Seminar: 20%
  • Final Exam: 30%

Covered Topics:

  1. Introduction, background, and applications:
    • Mobile devices
    • Wearables for activity monitoring, health, entertainment, and rehabilitation
    • Virtual reality (VR) and augmented reality (AR)
    • IoT devices, smart homes, and smart vehicles
  2. Common sensors available in mobile, wearable, and IoT devices:
    • Inertial measurement unit (IMU): accelerometer, gyroscope, and magnetometer
    • Photoplethysmography (PPG)
    • Electrocardiography (ECG), electromyography (EMG), and electroencephalography (EEG)
    • Electrical bio-impedance (EBI) and galvanic skin response (GSR)
    • Textile sensors
    • Stretch and pressure sensors
  3. State of the art algorithms used in wearables and IoT devices:
    • Pre-processing: de-noising, feature extraction, dimensionality reduction, etc.
    • Machine learning (supervised and unsupervised)
  4. Other computing-related concepts in wearables and IoT:
    • Resource-constrained computing
    • Cloud computing
    • HCI
    • Case-studies

Fourth Year Courses

Fourth year courses listed below may be taken by graduate students for credit, subject to the regulations set forth in the departmental prescription and those of the School of graduate Studies and Research. 

External Course List