Broader Impact Activity

 

Open source tutorials on POWDER (transmitter source localization, received power measurements, channel modeling, spectrum database lookup)

 

We created a tutorial for an over-the-air experiment on the localization of a jammer using the POWDER testbed.  We first performed this demonstration at Mobile & Wireless Week 2019 (Sept 2019), and then again for an REU Site (May 2020).  The instructions are public (https://gitlab.flux.utah.edu/powderrenewpublic/mww2019/-/blob/master/basic_localization.md), linked from the powderwireless.net website.  Anyone with an account can operate the tutorial, as described, or alter it to test out other localization algorithms, change transmit signal parameters, or receiver measurements.

 

This is largely in line with our proposed broader impact activity of building a jammer localization tutorial that would go in a museum; however, we believe that building it on POWDER has higher impact. It is accessible to any researcher with Internet access, and providing it with open source code gives others the opportunity to modify and improve the methods.  Further, POWDER’s repeatability allows it to serve as a benchmark of sorts for new algorithms.

 

We have also created tutorials on spectrum license lookup, channel path loss modeling, and received power measurements that are located on the Mobile & Wireless Week 2020 website: https://gitlab.flux.utah.edu/powderrenewpublic/mww2019/.  We are currently improving these tools and will continue to update these tools to make them more and more useful to other researchers. 

We have provided code on github, and tutorials for performing spectrum measurement and localization.

·      Channel impulse monitor: https://gitlab.flux.utah.edu/caleb/signal_power_monitor

·      Localization from impulse response: https://gitlab.flux.utah.edu/caleb/cir_localization

We have presented the spectrum monitoring work to students at Washington University in St. Louis, including in the presentation: ``Measurements, Networks, and People'', in the CSE 591 Seminar Series, 16 October 2020.

 

Special Scan Statistics

 

We have integrated elements of spatial scan statistics into the open source python library developed by our project team, called pyscan: https://mmath.dev/pyscan/.

 

Curriculum Development

 

Co-PI Patwari taught a graduate course in Fall 2018 on “RF Sensing”.  The course includes received power modeling and source localization, as used in this project. In this Fall 2018 version, he added modules on Bayesian recursive inference, including extended Kalman filtering, for localization and tracking.  These new modules parallel tools being developed in this project for tracking sources via Doppler information.

 

A new module on blockchain and another on spectrum security has been added to the Network Security class taught by PI Kasera.

 

Diversity

 

Our project team includes both undergraduate and graduate students. Our project team comprises of several women students as well as students from underrepresented minorities.

 

Dissemination of Results

 

We have published several papers as a part of this project. Additionally, several theses and dissertations have been completed on topics related to this project. The list of papers as well as theses and dissertations can be found here.