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.
METHODS & TECHNOLOGIES: Machine learning, Software defined radios, Wireless communications, Distributed optimization, Networking.
RESEARCH/DESIGN ISSUES: Machine learning, distributed optimization, and spectrum sharing.
MEETING TIME: Fri, 3:00-3:50
ADVISORS: Profs. Matthieu Bloch (ECE), Sebastian Pokutta (ISyE)
PARTNERS & SPONSORS: TBD
MAJORS, PREPARATION AND INTERESTS:
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
CONTACT: Dr. Matthieu Bloch, email@example.com