Spectrum Coexistence of Satellite-borne Passive Radiometry and Terrestrial Next-G Networks

Spectrum coexistence between terrestrial Next-G cellular networks and space-borne remote sensing (RS) is now gaining attention. One major question is how this would impact RS equipment. In this study, we develop a framework based on stochastic geometry to evaluate the statistical characteristics of radio frequency interference (RFI) originating from a large-scale terrestrial Next-G network operating in the same frequency band as an RS satellite. For illustration, we consider a network operating in the restricted L-band (1400-1427 MHz) with NASA's Soil Moisture Active Passive (SMAP) satellite, which is one of the latest RS satellites active in this band. We use the Thomas Cluster Process (TCP) to model RFI from clusters of cellular base stations on SMAP's antenna's main- and side-lobes. We show that a large number of active clusters can operate in the restricted L-band without compromising SMAP's mission if they avoid interfering with the main-lobe of its antenna. This is possible thanks to SMAP's extremely low side-lobe antenna gains.

Coexistence of Satellite-borne Passive Radiometry and Terrestrial NextG Wireless Networks in the 1400-1427 MHz Restricted L-Band

The rapid growth of wireless technologies has fostered research on spectrum coexistence worldwide. One idea that is gaining attention is using frequency bands solely devoted to passive applications, such as passive remote sensing. One such option is the 27 MHz L-band spectrum from 1.400 GHz to 1.427 GHz. Active wireless transmissions are prohibited in this passive band due to radio regulations aimed at preventing Radio Frequency Interference (RFI) on highly sensitive passive radiometry instruments. The Soil Moisture Active Passive (SMAP) satellite, launched by the National Aeronautics and Space Administration (NASA), is a recent space-based remote sensing mission that passively scans the Earth's electromagnetic emissions in this 27 MHz band to assess soil moisture on a global scale periodically. This paper evaluates using the restricted L-band for active terrestrial wireless communications through two means. First, we investigate an opportunistic temporal use of this passive band within a terrestrial wireless network, such as a cluster of cells, during periods when there is no Line of Sight (LoS) between SMAP and the terrestrial network. Second, leveraging stochastic geometry, we assess the feasibility of using this passive band within a large-scale network in LoS of SMAP while ensuring that the error induced on SMAP's measurements due to RFI is below a given threshold. The methodology established here, although based on SMAP's specifications, is adaptable for utilization with various passive sensing satellites regardless of their orbits or operating frequencies.

minimizing estimation error variance using a weighted sum of samples from the soil moisture active passive (SMAP) satellite

The National Aeronautics and Space Administration's (NASA) Soil Moisture Active Passive (SMAP) is the latest passive remote sensing satellite operating in the protected L-band spectrum from 1.400 to 1.427 GHz. SMAP provides global-scale soil moisture images with point-wise passive scanning of the earth's thermal radiations. SMAP takes multiple samples in frequency and time from each antenna footprint to increase the likelihood of capturing RFI-free samples. SMAP's current RFI detection and mitigation algorithm excludes samples detected to be RFI-contaminated and averages the remaining samples. But this approach can be less effective for harsh RFI environments, where RFI contamination is present in all or a large number of samples. In this paper, we investigate a bias-free weighted sum of samples estimator, where the weights can be computed based on the RFI's statistical properties.