ELEC 537: Intelligent Mobile Systems

Instructor: Nakul Garg ()

Lectures: Tu - Th, 4:00pm - 5:15pm

Location: James Baker Hall, 116

TA's:

Eric Yang ()
Office: Wed 11AM-12PM, Duncan Sym II Lab (Room 1020)

Bin Zhao ()
Office: Tue 2PM-3PM, Brockman Hall for Physics (Room B09)

Course Description. This course focuses on building intelligent mobile systems that sense, communicate, and make decisions under tight resource constraints like limited energy, compute, and bandwidth. We will explore wireless communication, embedded sensing, and machine learning techniques for mobile applications. Topics include wireless localization, sensor fusion, on-device AI, energy harvesting, wireless imaging, and emerging techniques like 3D mapping and neural radiance fields.

Prerequisites: The course is open for graduate (PhD/Master's) and senior undergraduate students. Prior experience in embedded systems, wireless communication, and machine learning is recommended but not required.

Topics.

Grading Breakdown.

Schedule.
# DATE TOPIC ASSIGNMENT READING
FOUNDATIONS OF SIGNALS AND SYSTEMS
1 Aug 26 Introduction to Intelligent Mobile Systems -
2 Aug 28 Sensors and Signals -
3 Sep 2 Signal Processing and Fourier Analysis -  
4 Sep 4 Signal Processing and Fourier Analysis Homework 1 Released  
5 Sep 9 Aliasing and Freq Shifting -
SPATIAL SENSING AND COMPUTING
6 Sep 11 Wave Propagation & Ranging -
7 Sep 16 Wave Equation and Spatial Sensing -
8 Sep 18 Arrays, Beamforming, Spatial Sensing Homework 1 & Project Proposal Due
9 Sep 23 Arrays, Beamforming, Spatial Sensing (cont.) Homework 2 Released
WIRELESS COMMUNICATION AND PERCEPTION
10 Sep 25 Wireless Communication -
11 Sep 30 Modulation -
12 Oct 2 Wireless Channel -
13 Oct 7 Wireless Channel (cont.) Homework 2 Due
14 Oct 9 OFDM and Synchronization -
Oct 14 Fall Recess No class — Holiday  
Oct 16 Midterm Exam (In-Class) Midterm Exam   Assessment  
15 Oct 21 Localization -
16 Oct 23 Guest Lecture -
17 Oct 28 Wireless Imaging – NeRF -
ON-DEVICE INTELLIGENCE
18 Oct 30 Structure Assisted Imaging Homework 3 Released (Oct 31)
19 Nov 4 Hidden Markov Models - Predicting the Future -
20 Nov 6 Hidden Markov Models (cont.) -
Nov 11 Project Progress Discussion -  
21 Nov 13 On-Device AI: TinyML & Optimization -
APPLICATIONS AND INTELLIGENT MOBILE SYSTEMS
22 Nov 18 Quantization and Pruning Homework 3 Due
23 Nov 20 Security and Privacy -  
24 Nov 25 Security and Privacy (cont.) -  
Nov 27 Thanksgiving Break No class — Holiday  
FINAL PROJECTS
Dec 2 Final Project Presentations I Final Presentations  
Dec 4 Final Project Presentations II Final Presentations  

Course Policies and Resources.

Rice Honor Code

All students must uphold the Rice Honor Code standards established when you matriculated at Rice. If you need clarification on academic integrity expectations, procedures, or student rights, consult the Honor System Handbook.

Disability Resource Center

Any student with a documented disability needing academic accommodations should: 1) visit the Disabilities Resource Center (DRC) to ensure required documentation is on file, and 2) speak with the instructor as soon as possible. The DRC is located in Allen Center, Room 111 / adarice@rice.edu / x5841.

Mental Health Statement

Student wellbeing and mental health are important. If personal challenges are interfering with your ability to complete coursework, please contact the Wellbeing and Counseling Center for support. 24/7 support: 713-348-3311.

Updates to the Course

Information in this syllabus may be subject to change with reasonable advance notice as appropriate.