Radio Frequency Noise Sensor

Frequent travelers or moviegoers know the moment when you’re asked to put your mobile phone into airplane or silent mode to keep it from interfering with the movie experience or the flight. While these devices actively accessing the radio spectrum are easier to address, passive users face additional challenges in an environment where access to the limited radio spectrum keeps increasing in value. 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 between active and passive 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 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 several concerns for radio astronomy. While optical astronomy is hampered by light pollution, radio astronomy is much more concerned about radio frequency interference (RFI) [1]. Since signals from astronomical observations are extremely weak and easily drowned out by human made transmissions, making Astro-physical observations becomes increasingly more difficult if the observed frequency band is shared with active users in time or frequency [1], [2]. 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 radio frequency interference (RFI) [3].

Still, as the Passive and Active Spectrum Sharing working group highlighted, spectrum sharing between passive and active systems will be crucial for future radio spectrum access [4]. To further improve efficient spectrum use, and to investigate the challenges of creating a dynamic radio spectrum environment for radio astronomy, this research sets out to create a 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.

It took more than 20 years from the first radio astronomical observation to recognize radio astronomy as an important use of the radio spectrum and to protect its observations on a regulatory basis from interference across multiple frequency bands [5]. Radio astronomy was not recognized as a “radio service” until the World Administrative Radio Conference (WARC) of 1959, where the first dedicated band from 1400 to 1427 MHz was allocated to radio astronomy, granting radio astronomy protection from interference on the hydrogen line [6], [7]. Over the next 20 years, recognition for radio astronomy’s contribution to major technical advances kept growing and additional spectrum allocations were finally made in 1963, 1971, and 1979. These national spectrum allocations did not only provide radio astronomy services with access to further molecular spectral lines, but furthermore for the first time aimed at promoting international coordination for radio astronomy protection. To this day, radio astronomical observations have resulted in the discovery of more than 550 spectral lines across the frequency range from 0.8 to 350 GHz, exoplanets, fast radio bursts, and the discovery of the cosmic microwave background [8], [9].

Internationally, the passive use of the electromagnetic spectrum is regulated by the Radiocommunication Sector of the International Telecommunications Union (ITU-R) with binding outcomes negotiated every three to five years by the World Radiocommunication Conference (WRC). These outcomes are then matched on a national level by domestic regulations, e.g., by the Federal Communications Commission (FCC) for non- federal and by the National Telecommunications and Information Administration (NTIA) for federal use within the United States [7]. While regulations attempt to give radio astronomers protection from interference in the most essential frequency bands, regulations struggle to protect radio astronomy from interference from adjacent channels and unintentional emitters. As a result, the vast majority of radio astronomy sites has historically been placed in remote locations or valleys in order to minimize interference from man-made sources or on higher elevations to avoid as much water vapor as possible when observing higher frequency bands while also using traditional RFI mitigation methods, including RF filters, post-processing of data, discarding corrupted data samples, and local RFI mitigation [7], [10], [11]. Most observatories can be found inside a Radio Quiet Zone (RQZ), which usually consists of an exclusion zone limiting the use of the radio spectrum and a coordination zone with limited transmit power requirements, in order to further increase protection from a variety of sources of interference [12]. One example can be found at the National Radio Astronomy Observatory (NRAO) in Green Bank, WV, where RFI suppression is achieved with the help of a National Radio Quiet Zone (NRQZ) established in 1958 by the FCC [13]. However, while the ITU emphasizes in its recommendation RA.769 (ITU-R RA.769) that radio astronomy services have been responsible for some of the most fundamental astronomical and major technical advances in the past five decades [14], [15] emphasizes that NRQZs are neither globally adopted, nor enough to protect radio astronomy sites from interference caused by satellite networks in many locations, nor sustainable as urbanization increases, making new protection mechanisms necessary.

To ensure radio astronomy can continue operating in an environment that allows for major technological advances it is crucial to protect the service from interference. Interference for radio astronomy is defined in ITU-R RA.769 as the unwanted but detectable portion of a desired observation that has the potential to either degrade or inhibit the successful conduct of the observation” [14]. ITU-R RA.769 further describes harmful interference for radio astronomy as interference that causes a change in amplitude equal to 10% of the RMS noise or increases the uncertainty of the measurements by 10%. However, interference from terrestrial transmissions is no longer the only concern. Transmissions from aircrafts, spacecrafts, satellites, and the moon are increasingly becoming a concern for radio astronomy. ITU-R RA.1513 therefore dictates that harmful interference from a satellite network should affect less than 2% and from all systems less than 5% of the aggregate data [16].

Historically, many mechanisms have been put in place to protect radio astronomy from interference, but as the spread of devices accessing the radio spectrum increases - 13.1 billion wireless connected devices by 2023 [17]- and previous protection mechanism are proving insufficient and potentially unsustainable. While systems such as the Citizen Broadband Radio Service (CBRS) include provisions for protection zones, exclusive access to the radio spectrum and restrictive protection zones in the future might have to face a more dynamic mode of sharing as the demand for radio spectrum access by consumer devices continues to grow. As exclusive spectrum access (single use spectrum use licenses) is replaced by sharing arrangements, designing spectrum sharing models suited for sharing between radio astronomy and various active services will be very important to avoid harmful interference [18]. In fact, while spectrum sharing typically results in more efficient spectrum use, it also has the potential to negatively impact passive users such as radiometry and radio astronomy. Ac- cording to [19], coexistence with Radio Astronomy Services at 1 GHz with a transmit power as low as 1 nW would require transmitting at a distance of 1050 km from the passive service to avoid violating ITU Recommendation ITU-R RA.769-2. Still, a system such as the Spectrum Access System used for the Citizen Broadband Radio Spectrum for instance has considerable potential to solve the wide-ranging coordination issues and avoid unnecessary interference. Additionally, [18] assumes free-space path loss, which, given the general location of observatories, is not guaranteed, and often blocked by obstacles.

However, as the sensitivity of radio telescopes increases to achieve better results, transmissions from a variety of sources, inside and outside of the observed band, are increasingly being captured through the telescopes side lobes [1], [2], [12], [20]. Even though regulations by the Federal Communications Commission (FCC) and agreements by the International Telecommunications Union (ITU) can be effective at preventing some interference, research has shown that even transmitters at distances beyond 100 km can be problematic [3].

Additionally, signals from low-earth- orbit (LEO) satellites leaking into protected radio astronomy bands can be an issue even in remote locations [1]. Sharing spectrum with radio astronomy would not only have to consider a much larger protection area, but furthermore be adaptive enough to react to terrestrial and satellite signals. Several additional challenges need to be considered when sharing spectrum with radio astronomy and scheduling telescope observations, including logistical and environmental factors such as weather and ionospheric perturbations [11]. While scheduling observations dynamically in accordance with expected interference has been considered [21], considering all possible factor in dynamic observation windows can become highly complex.

In a first step of building out the testbed, 5 low-cost sensors have been deployed around HCRO that continuously sweep the frequencies from 400 to 1800 MHz (see Figure 1). To verify the efficiency of the HCRO’s remote location at protecting it from RFI, a drone was flown in 3 different locations at 4 different heights with an additional sensor attached to evaluate the RFI environment at elevated positions and compare it to ground level results. Tables I list the 5 main sensors located on the HCRO site with their exact location and height above ground, as well as the locations of the drone surveys and their distance to a known transmitter. The next section is organized as follows: it will begin with a description of the sensor hardware, followed by the software used to execute the RF surveys, and conclude with a description of the drone survey parameters.

As described in Section II, current implementations of dedicated RFI monitoring equipment at various Radio Astronomy facilities are based on the use of spectrum analyzers. The cost of this approach does not lend itself to the deployment of multiple sensors and is subject to several drawbacks. A single (or low numbers of) sensor(s) severely constrains the spatial diversity of RF Baseline sampling, and provides - at best, an average estimate of the background RFI (assuming a uniform distribution), and in the worst case, can provide a noise estimate that is below the RFI incident on the RA telescope antennas themselves (if the sensor is in a more favorable location than the telescope). Additionally, such a system is usually also constrained to operate in a single contiguous slice of the frequency spectrum of interest, and therefore is not suited to track frequency-variant transient signals. Given that RFI monitoring is not the main remit of the RA facilities, it is also oftentimes outside project scope to develop custom RFI monitoring systems, and the engineering trade-off which picks a reliable, commercial solution is employed. Spectrum analyzers have, until recently, been the only instruments that qualify through this trade-off, despite their expensive overabundance of capability which is not leveraged by their use as dedicated RFI monitors. However, with the advent of Commercial, Off- The-Shelf Software Defined Radios, this is no longer the case. Neither spectrum analyzers, nor SDRs can approach the sensitivity limits of the radio telescope receiver themselves. Even spectrum analyzer based RFI monitors require RF components in a dedicated front end, to perform signal conditioning as well as signal detection at levels that are in the vicinity of the sensitivity of the RA telescope itself. The availability of a range of connectorized RF components, would - therefore - allow the design of a dedicated RFI monitoring system based on an SDR. With only a little more incremental work, the instrument may be designed to meet exactly those performance metrics desired, especially if it’s a bulk of the signal.

A broadband omnidirectional antenna is chosen to ensure the node’s sensitivity to RFI emanating from all relative azimuth and elevation angles. We preserve the ability to perform rogue source localization despite having omnidirectional antennas, by deploying multiple sensor nodes - each of which can establish the magnitude of a detected interferer. This is susceptible to errors due to propagation effects (such as multipath reflections, and ducting) that deviate from the ideal inverse square dependence, however, and we have designed the nodes to be able to perform phase synchronized sampling to address this. Initially, the Keysight N6850A antenna was down selected for use due to its uniform radiation pattern, which was largely frequency independent across a wide bandwidth (VSWR < 2.5 over 450 MHz - 6 GHz, average gain over all space of -1 dBi). The wide bandwidth operation would allow the antenna to remain a constant part of multiple configurations targeting different frequency bands. However, availability issues with the antenna resulted in only two of these antennae being procured. These are installed at the CHIME and Gate locations. The other locations were catered to by an Aaronia OmniLog 30800 antenna which, while not possessing as much gain, or uniformity as the N6850A (VSWR < 3 over 700 MHz - 8 GHz, average gain approximately -5 dBi), was far less expensive, and in stock. Both the N6850A and the OmniLog 30800 are linearly polarized and are mounted with their axis of polarization collinear with the local vertical.

Following along the signal chain, the transduced RFI signal encounters the pre-amplifier. The pre-amplifier comprises a low noise figure LNA, a bias-tee, and a low drop-out linear voltage regulator PCB all housed in a 4” cube weather-proof junction box. The antenna is mounted atop the pre-amplifier box to ensure that there is as little of a signal path (and hence as little attenuation) between the antenna and the LNA. The objective of the pre-amplifier is to be able to amplify the signal as quickly as possible, prior to the addition of losses due to attenuation and noise. Two factors make the pre-amplifier especially critical for the RFI monitoring. First, given our use of the omnidirectional antenna, the gain available from the antenna itself is quite small. Since the noise figure of the entire system, and therefore the sensitivity is largely determined by the noise-figure of the first stage (with subsequent stages’ contributions weighted in descending order), the choice of the LNA has a large impact on the overall system temperature. Given the limits of the gain-bandwidth product, as well as the tradeoff between the noise-figure and the gain of the LNA, it was decided to split the overall system gain between two amplifiers, with the priority on selecting a low-noise figure amplifier for the first stage. Additionally, it was also decided to use two different LNAs to monitor different regions of the target spectrum. The LNAs chosen were the MiniCircuits ZKL-33ULN-S+ for the 400 MHz - 1.8 GHz, and the ZX60- 63 GLN+ for 1.8 GHz - 6 GHz, with noise figures of < 0.5dB and < 1.5 dB, and gains of 47 dB - 24 dB, and 31.5 dB - 24 dB respectively. Note that the gain varies significantly over the frequency range of operation - even for a single LNA, and therefore a flattening is required to have a flat response across the passband. This is achieved by incorporating a slope- compensator with a similarly frequency dependent attenuation. However, for ease of assembly, and volume reasons, this attenuator is not placed in the pre-amplifier box, but placed (at the same position in the signal chain) inside the EMI enclosure. The output of the pre-amplifier is then connected via an RF cable to the input of the EMI enclosure.

The final piece of the sensor node is the EMI enclosure. All the components up until this point have been analog, and there have been no independent signal sources. However, the SDR, as well as the computing host that interfaces with the SDR are digital components, which are necessarily driven by clock signals and have transients. In addition, the SDR also has a local oscillator, and all these are sources of EMI. As a result, to fulfill the third requirement, we are required to house all these noisy components inside an Electro- Magnetic Interference enclosure, which prevents RFI from leaking out (as well as into) the enclosed volume. This is especially necessary, because the sensor nodes are placed in close proximity to the dishes of the ATA, and any inadvertent EMI leakage from the monitoring nodes themselves could pose problems to the highly sensitive amplifiers in the telescope itself. A Ramsey Test solutions’ STE2300M EMI enclosure was procured and modified to serve as the EMI enclosure for our sensor nodes.

The inside of the EMI enclosure was divided into two parts. The lower half contained a switched mode power supply (MeanWell LRS-35-5), that provides DC voltage for the operation of the computing host (Raspberry Pi), and the networking-cum-timing node (White-Rabbit LEN), as well as an extremely stable linear power supply (Bel Power Solutions HB12-1.7-AG) for the provisioning of the DC voltage for the analog components (i.e. the wideband amplifier and the bias- tee, which - in turn - powers the pre-amplifier). Complete separation between the analog components, and the digital components - such that they shared different local, physical ground planes, is usually pursued as a design feature, to avoid the crosstalk between ground-planes. The power supplies are in immediate electrical and thermal contact with a metallic mounting plate, which in turn is in contact with the bottom of the box, and which is connected to the local Earth potential via the power cable. This bottom section also contains the WR-LEN (White Rabbit) terminal node, which provides both the timing reference signal (10 MHz sinusoidal clock signal) as well as network connectivity (via CAT-6e cable) to the Raspberry Pi. The input to the WR-LEN is a single-mode optical fiber cable, via an SFP connector. The WR-LEN terminal module receives a copy of the Temperature Controlled Oscillator HCRO Station Clock (used for the synchronized sampling across the ATA itself). This section also contains AC mains fuses, to provide fault protection. The Ethernet, power and clock outputs from this section are drawn through the mounting plate of the top-section. This top section comprises all the remaining analog components, as well as the Raspberry Pi and the Ettus Research B200-mini-i which is the Software Defined Radio that we use in the sensor nodes. The analog components comprise the slope compensator (Minicircuits VEQY-6-63+), a wide-band gain-block (Minicircuits ZX60- 14012L-S+), and an identical bias-tee as in the pre-amplifier (Minicircuits ZX85-12G-S+). The RF signals are connected by high-quality, low-loss RF cables from AtlantecRF, and the power signals are all conveyed through twisted pair wires, to terminal blocks.

The STE2300M has conductive gaskets lining the opening, which forms a tight, compressive seal when the box is closed.

This leaves the pass-throughs (for power) as the primary route through which EMI may leave the box, but the pass-through provided is appropriately filtered. Additionally, while the original EMI box came with RF-absorber on all the six internal faces, it was revealed during operation that this led to poor thermal conductivity between the active components in the enclosure, and led to an increase in the operational temperature inside the box, reaching about 70 C during periods when the ambient external temperature was about 35 C. As a result, this RF-absorber was removed from all sides, except for the top lid. The system noise temperature from this system (calculated at 3 frequencies) were: 557 K (400 MHz), 186 K (1800 MHz), and 330 K (at 5000 MHz).

The main software components used for the testbed surveys are located on the Raspberry Pi 4 Model-b single board computers (SBC). Each SBC is equipped with a 64 GB SanDisk Ultra MicroSD card hosting a 32-bit version of Raspberry Pi OS Lite version 10 (name “Buster”, dated 2021-05-07). The same USB connection that powers the USRP is used to control the SDR and transfer data from the SDR to the host. Data collections on the SDRs are controlled from the host using the USRP Hardware Drivers (UHD) Python 3 API. To minimize unwanted emissions coming from the SBC, Wi-Fi and Bluetooth are permanently disabled by blacklisting the modules via rfkill and disabling wpa_supplicant as well as Bluetooth. Since this only leaves the Ethernet connection for communication, several additional Python libraries and Linux packages are required to make the sensor system more plug-and-play. The UHD API is complemented by msmtp, mmtp-mta, and mailutils to enable the SBC to automatically report its IP address as well as its remaining capacity, CPU use, and temperature. This makes possible to receive the devices IP address, as long as an Internet connection is given.

The rsync utility is used to automatically backup data, as long as the SBC is connected to a local network and has a route to a remote server. If no connection to any remote storage location is available, rsync is used to manually offload data between data collections. Git is used to ensure version control and maintain the same codebase version on all sensors. The codebase consists of a Python 3 application that accesses the UHD Python API to start the I/Q data stream and schedule in what intervals I/Q samples are recorded on the host. The application is configured to use an external clock source, if given. Data are transferred from the SDR to the host in a 16-bit signed integer format and stored in the same format. As a result, each I/Q data sample requires 4 Bytes of storage. 1 A one-second-long sample of 20 MHz bandwidth and a matching sampling rate of 20 million (complex) samples per second for instance results in 80 million Bytes or 76.2939 MB. Due to the large amounts of data generated this way, the Python application will be configured in the future to calculate the current environment’s noise floor and only store samples above a specified threshold.

The data collection Python application can be launched using a single command-line command or using a graphical user interface (GUI) written with the Python tkinter library. Using this GUI, multiple SBCs can be controlled remotely at the same time. This also makes it possible to launch data collections on multiple sensors or schedule them to start at a common start time in the future and end together at the same time. In the interest of test configuration management, test initiation is under most circumstances controlled from this central GUI running on an on-site computer on the same subnet as the field sensors. Using the central GUI minimizes potential complications from user input error and enables computer- generated scheduling of tests based on human-readable date and time inputs. Without the GUI, tests need to be instantiated manually on six different remote hosts, and test delays would need to be calculated manually. This is especially important when sweeping across frequencies as a delay would cause individual sensors to record the same frequency at different times. When using the GUI’s delay parameter, each SBC’s Python application waits for a set delay time before initiating the survey. Once the delay is over, data collection begins on the host at the scheduled intervals and continues until the final sample is collected.

Several steps are taken to maintain proper documentation during a RF survey. The survey Python application maintains a log file that is regularly updated as files are created, stored, moved or if any errors occur. Logs are written both to syslog and local files that are rotated and synched daily. A script loaded via a cron job regularly checks the most current log files for errors and reports back to the administrator using the mailing utilities. To ensure all data can be properly identified and recovered, each file is labeled with the SBC’s hostname, the SDR’s serial number and a timestamp that consists of full date and time with 6 decimal points. Additionally, each file is accompanied with a JSON file recording the most important parameters, including hostname, serial number, location, co- ordinates, center frequency, interval, length of the recording, the SDR’s gain setting, sampling rate, and bit depth of the I/Q data file. Finally, if a remote storage location with rsync is used, the remote storage is manually checked for arriving I/Q data files after initiating a new survey.

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