Communications project
COM-304 / 8 credits
Teacher(s): Al Hassanieh Haitham, Roshan Zamir Amir
Language: English
Withdrawal: It is not allowed to withdraw from this subject after the registration deadline.
Summary
The course teaches the development of systems that solve real-world challenges in communications, signal processing, AI, and robotics. Students will work in teams, construct their ideas, and either program available hardware prototypes or build their hardware.
Content
The course will teach students both technical and project management skills which are essential in developing, designing, and prototyping practical systems where the underlying challenges fall in on or multiple areas with a focus on communication, signal processing, AI, and Robotics.
The primary goal of this course is to give students hands-on experience with solving real-world challenges by working in teams to program different hardware platforms and ultimately build their own projects. The overall structure of the course will consist of a few introductory lectures at the beginning to introduce the project and research areas in wireless radar sensing, communication, computer vision, robotics, and reinforcement learning. The students will have time to go through the background material needed for the course and get familiar with the hardware and sensor platforms. Students will then organize into groups of 3 or 4 and propose their project using one or more of the provided hardware platforms, with the aid of the course staff. Finally, students will design and build their own project.
This class has two types of lectures.
(1) In person lectures which are limited to three lectures at the beginning of the semester. After which the lecture time will be used as office hours to help students with their projects.
- Lecture 1: Class Introduction
- Lecture 2: Introduction to Wireless Communications & Sensing
- Lecture 3: Introduction to Reinforcement Learning & Robotics
(2)Online lectures on background material.
- Wireless Communication
- Radar Signal Processing
- Reinforcement Learning
The class will support 3 hardware platforms which students can work with.
- Millimeter Wave TI AWR1443BOOST Radars
- BladeRF 2.0 micro xA4 Software Defined Radios
- Turtlebot 4 Lite
We have two additional robots which students can use. However, we do not provide support for these robots and we only have one available from each type.
Learning Prerequisites
Recommended courses
COM-202 Signal Processing (BA3)
CS-233 Introduction to Machine Learning (BA4)
COM-302 Principles of Digital Communications (BA6) (To be taken concurrently)
CS-202 Computer System (BA4)
COM-102 Advanced Information, Computation, Communications II (BA2)
Important concepts to start the course
Basic programming skills.
Teaching methods
- Video lecture on background material.
- Tutorials on the hardware prototypes.
- Continuous supervision and tutoring
- Extensive team work and team feedback
Expected student activities
- Take an entrepreneurial approach to create and develop a practical system under the given hardware constraints.
- Work with team members to complete a large practical project
- Independently research solutions, learn new concepts and apply them in practice.
- Debug software/hardware systems.
- Discuss project progress in class
- Provide constructive criticism and feedback to other groups
- Present project outcome in a public forum
Assessment methods
35% Individual activities grade
65% Team project grade
Supervision
Office hours | Yes |
Assistants | Yes |
Forum | Yes |
In the programs
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Communications project
- Lecture: 2 Hour(s) per week x 14 weeks
- Project: 10 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Communications project
- Lecture: 2 Hour(s) per week x 14 weeks
- Project: 10 Hour(s) per week x 14 weeks
- Type: optional
Reference week
Mo | Tu | We | Th | Fr | |
8-9 | |||||
9-10 | |||||
10-11 | |||||
11-12 | |||||
12-13 | |||||
13-14 | |||||
14-15 | |||||
15-16 | |||||
16-17 | |||||
17-18 | |||||
18-19 | |||||
19-20 | |||||
20-21 | |||||
21-22 |
Légendes:
Lecture
Exercise, TP
Project, labs, other