Agile Communication Architectures
Goals
Future wireless communication devices will need to dynamically learn their environment and opportunistically exploit spectrum. The goal of this project is to integrate machine learning algorithms into communication architectures to achieve the agility required for the task. The team will participate to the DARPA Spectrum Collaboration Challenge (SC2) and test its solutions against other competitors.
Issues Involved or Addressed
Machine learning, distributed optimization, and spectrum sharing.
Methods and Technologies
- Machine Learning
- Wireless Communications
- Networking
- Software Defined Radios
- Distributed Optimization
Majors Sought
Computing: Computer Science
Engineering: Aerospace Engineering, Biomedical Engineering, Computer Engineering, Electrical Engineering, Industrial Engineering, Mechanical Engineering
Sciences: Mathematics, Physics
Preferred Interests and Preparation
ISyE: Background/interest in machine learning and distributed optimization.
EE: Background/interest in machine learning and signal processing.
CompE: Background/interest in FPGA programming and wireless networking
CS: Background/interest in machine learning and wireless networking
Advisor
Matthieu Bloch
Matthieu Bloch
matthieu.bloch@ece.gatech.edu
Day, Time & Location
Full Team Meeting:
3:30-4:20 Friday
TSRB 523A
Subteam meetings scheduled after classes begin.