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To enforce incumbent protection through a spectrum access system (SAS) or future centralized shared spectrum system, dynamic protection area (DPA) neighborhood distances are employed. These distances are distance radii, in which citizen broadband radio service devices (CBSDs) are considered as potential interferers for the incumbent spectrum users. The goal of this paper is to create an algorithm to define DPA neighborhood distances for radio astronomy (RA) facilities with the intent to incorporate those distances into existing SASs and to adopt for future frameworks to increase national spectrum sharing. This paper first describes an algorithm to calculate sufficient neighborhood distances. Verifying this algorithm by recalculating previously calculated and currently used neighborhood distances for existing DPAs then proves its viability for extension to radio astronomy facilities. Applying the algorithm to the Hat Creek Radio Observatory (HCRO) with customized parameters results in distance recommendations, 112 kilometers for category A (devices with 30 dBm/10 MHz max EIRP) and 144 kilometers for category B (devices with 47 dBm/10MHz max EIRP), for HCRO’s inclusion into a SAS and shows that the algorithm can be applied to RA facilities in general. Calculating these distances identifies currently used but likely out-of-date metrics and assumptions that should be revisited for the benefit of spectrum sharing. 

Abstract—Demand for wireless communication devices has been growing continuously since the advent of mobile communication. Even though spectral efficiency and throughput keep increasing, consumer demand continues to seemingly outpace that growth. Spectrum sharing is becoming a more attractive solution to solving various capacity constraints as the resulting perceived spectrum scarcity can mostly be attributed to inefficient spectrum management. However, increasingly complex sharing arrangements come with an increased risk of interference. This makes it necessary to address such events in a timely manner. At the same time, research into using machine learning for solving issues such as signal classification, decision-making processes, and anomaly detection in wireless communication has been growing. To support machine learning research in anomaly detection for wireless communications, this research uses IQ data to train two autoencoders for anomaly detection in shared spectrum: a Long Short-Term Memory (LSTM) and a Deep Autoencoder. These algorithms are used to successfully identify anomalies in the time and frequency domain of recorded IQ data in the form of unauthorized LTE transmissions on top of Wi-Fi communication. 

Under NASA’s Artemis program, NASA is planning to send astronauts back to the Moon in the next couple of years. Near term missions will be analogous but much more sophisticated versions of the last couple of Apollo missions. However, unlike Apollo, this time NASA intends to put the infrastructure in place to support long term human presence and eventual industrialization of the Moon. To make this vision a reality, NASA plans to collaborate with commercial and international partners as much as possible as opposed to developing, building, and operating equipment on its own. Lunar infrastructure will eventually be built over time by many organizations, public and private, to support sustained human exploration, science, and industrial activities. Obviously, this vision for the future will be impossible without a robust lunar communications and navigation system that can support many users with varying degrees of services. On Earth, most people are very familiar with the 3rd Generation Partnership Project (3GPP) 5G mobile telecommunications technology. NASA’s Space Technology Mission Directorate and NASA’s Space Communications and Navigation office would like to see a lunar communications and navigation network with similar capabilities to the cellular communication networks most of us enjoy today. Building such a network will require participation by many organizations. This paper will provide an overview of NASA’s interest in using 5G and beyond on the lunar surface; it will also describe current work based on 3GPP standards within NASA or funded by NASA, such as Nokia’s upcoming Tipping Point demonstration of 4G / LTE on the lunar surface. 

As radio spectrum becomes increasingly scarce, coexistence and bidirectional sharing between active and passive systems becomes a crucial target. In the past, spectrum regulations conferred radio astronomy a status on par with active services, thereby protecting their extreme sensitivity against any harmful interference. However, passive systems are likely to lose exclusive allocations as capacity constraints for active systems increase. The resulting increase in ambient radio frequency noise from various terrestrial and non-terrestrial emitters can only be mitigated with informed collaboration between active and passive users. While coexistence using time-division spectrum access has been proposed in the past, a more dynamic approach following the CBRS sharing principle promises greater spectral occupancy and efficiency, enabled by a spectrum access system capable of constantly monitoring the ambient RF environment. Instead of simply minimizing the potential for any ”harmful” interference to passive users, the goal is to use good engineering to enable sharing between active and passive users. To this end, this research created a Software Defined Radio (SDR)-based testbed at the the Hat Creek Radio Observatory to quantitatively characterize the radio-frequency environment, and flag potential sources of radio frequency interference in the vicinity of the Allen Telescope Array. Sensor validation was carried out via data analysis of I/Q data collected in well-characterized RF bands. Results so far from ground and drone-based surveys are consistent with the expected sources of interference, based on both the deployment of static RF transmitters in the Hat Creek/Redding area as well as the interference detected in telescope observations themselves.