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.