Agile Communication Architectures

2018 ~ Present

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
  • Software Defined Radios
  • Wireless Communications
  • Distributed Optimization
  • Networking

Academic Majors of Interest

  • Algorithms, Combinatorics, and Optimization
  • College of Computing
  • Computational Science and Engineering
  • Computer Engineering
  • Computer Science
  • Electrical Engineering
  • Industrial Design
  • Industrial Engineering

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

Meeting Schedule & Location

Time: 

4:00-4:50

Meeting Location: 

TSRB 530

Meeting Day: 

Friday

Team Advisors

Dr. Matthieu Bloch (ECE)
Dr. Sebastian Pokutta (ISyE)

Related Sites