Table of contents

Problem statement

As an increasing number of government and industry services is asked to share the spectrum, radio astronomy will eventually have to face the potential of sharing with active users. Still only a concept in the regulatory domain, research in bi-directional sharing between radio astronomy and active services has the potential to not only address future spectrum scarcity challenges but furthermore provide a path forward for other passive service that will face the need to share radio spectrum with active services. Sharing spectrum raises a number of concerns for radio astronomy. Since signals from astronomical observations are extremely weak and easily drowned out by human made transmissions, making astrophysical observations becomes increasingly more difficult if the observed frequency band is shared with active users in time or frequency. Most radio telescopes in fact can be considered about 150 dB more sensitive than a cellular receiver, making radio telescopes highly susceptible to man-made RFI. Spectrum sharing between passive and active systems will be crucial for future radio spectrum access. To further improve efficient spectrum utilization and to investigate the challenges of creating a dynamic radio spectrum environment for radio astronomy, this document describes the software and hardware components of the RFI testbed at the Hat Creek Radio Observatory (HCRO) located in northeastern California. This testbed is used to assess the spectral environment at HCRO, to determine and measure sources of RFI, and ultimately to create a national radio dynamic zone (NRDZ) by extending a spectrum access system (SAS) to coordinate radio astronomy with active users.

Goals

1. IQ data recordings to conduct a RF Baseline Noise Survey:
   • Record the data in a binary format.
   • Record IQ data in locations with varying topography and RF environments.
   • Data are recorded in regular or random intervals for a predetermined amount of time or indefinitely.
   • Data are recorded from a single frequency band or from a sweep across a range of frequencies.
2. Data transfer and storage:
   • Since storage on the RF sensors is limited, all data are automatically transferred to a server for storage and processing.
   • Data are stored on the server until they are processed or/and delivered to a long-term storage provider.
   • Each IQ data file is accompanied by metadata and status information files in the JSON format.
3. Data Processing
   • On the server, data are organized and processed by an automated service.
   • This service provides statistical information such as average, maximum and median power, standard deviation, and spectral kurtosis across the entire sample.
   • Graphical interpretations of the processed data are provided via a dashboard utility.
   • Understand if and where the characteristics of the RF background in a given location are changing and quantify the change in these characteristics.
4. Open access IQ data
   • To improve the availability of IQ data for research, selected samples will be published using a long-term data storage provider.

Non-goals

1. Long-term IQ data retention:
   • It is out of scope to infinitely store the IQ data files on the HCRO or CU Boulder server. Due to the amounts of data generated by SDRs, it is unfeasible to store the data forever. A single day of 1 second, 20 MHz wide, 20 MS/s samples recorded every 10 seconds results in $80660*24=691,200$ or approximately 691 GB of data per day, multiplied by the number of sensors recording data simultaneously.
2. Creating visualizations for every frequency band supported by the underlying hardware:
   • While the USRP B200 series supports a frequency range from 70 MHz to 6 GHz, the supporting hardware, including amplifiers and antennas, is focused on specific frequency bands and is selected for specific surveys. As a result, it is not possible to record all supported frequency bands at the same quality without switching out hardware components to support the specific frequency bands. Additionally, due to storage and processing limitations, it is unfeasible to create spectrograms from every IQ data file. Such visualizations will be created in a more targeted fashion.

Proposed solution

To achieve these goals, RF surveys use commercial off-the-shelf (COTS) hardware to keep cost low and allow for the use of multiple sensors at the same time.

High level hardware architecture

High level software architecture