EE/CSE - Comparative Analysis of Indoor CBRS vs. Wi-Fi

With the explosion of wireless devices, the radio spectrum has become a highly constrained resource. We bridge the gap between wireless engineering and public policy through real-world spectrum measurements. By analyzing actual usage patterns and performance limits, our lab provides the critical data that policymakers and industry leaders need to build a faster, more accessible wireless future.

We are seeking motivated students interested in real-world spectrum measurement and wireless networking. Our testbed comprises of Wi-Fi and CBRS system installed in the Fitzpatrick-Cushing building. This project compares the performance of both systems to serve indoor users, using smartphones and Meta VR headsets. Students will learn experimental protocol design and measurements tools such as QualiPoc and Wireshark, as well as data processing and analysis using Python-based framework such as Jupyter, Pandas, and NumPy.

Name of research group, project, or lab
GHOSH Lab
Why join this research group or lab?

This project gives students hands-on experience with wireless research and analysis using real-world Wi-Fi datasets. Students will gain experience with experimental and end-to-end data cycle: retrieving real-world data, processing it for analysis (cleaning, transforming, and engineering features), as well as data analysis and modeling. This project will also be published, giving students exposure to technical writing and academic publishing process.

Logistics Information:
Project categories
Computer Science & Engineering
Electrical Engineering
Student ranks applicable
Sophomore
Junior
Senior
Student qualifications
  • Strong interest in data science or technology policy.
  • Strong interest in hands-on smartphone and VR measurements.
  • Basic understanding in wireless technologies, particularly Wi-Fi. 
  • Proficiency with (or a strong willingness to learn) Python-based data analysis framework. Familiarity with other analytical frameworks (e.g., machine learning/AI) is also welcome.
  • Some mobility is required to participate in the experiments.
Hours per week
2 credits / 6-12 hours
Compensation
Research for Credit
Number of openings
1
Techniques learned
  • Python/Jupyter-based data processing and visualization.
  • Experience with experiment design utilizing end-user devices. 
  • Deeper understanding of real-world cellular and Wi-Fi implementations.
  • Technical writing and preparation of results for publication in a research conference or journal.
Project start
2026 Fall Semester
Contact Information:
Mentors
mrochman@nd.edu
Postdoc Researcher
mghosh3@nd.edu
mghosh3
ecase@nd.edu
Name of project director or principal investigator
Monisha Ghosh
Email address of project director or principal investigator
mghosh3@nd.edu
1 sp. | 0 appl.
Hours per week
2 credits / 6-12 hours
Project categories
Electrical Engineering (+1)
Computer Science & EngineeringElectrical Engineering