Project Description
In connection with NTIA/ITS (National Telecommunications and Information Administration/Institute for Telecommunication Sciences) we are collecting LTE and 5G NR cell phone radio signals in the Boulder area and CBRS (Citizens Broadband Radio Service) signals in the Denver area. The purpose is to study spectrum usage and to devise strategies for using the radio spectrum (a limited natural resource) more efficiently. One of the goals is to apply machine learning (ML) to automatically classify short duration radio signals. In order to train and evaluate ML algorithms, we need labeled data sets with known properties. The main task of this project is to analyze and classify real-world radio signals that have been captured from cell phones and cell towers in terms of their signal properties (not in terms of their content and without violating any privacy rights). Programming skills (Python preferred) and knowledge of linear systems is required.
Special Requirements
- Programming skills (Python preferred, or Matlab)
- ECEN 3300 Linear Systems
Contact
- Peter Mathys (faculty)