Active Spectrum Management with Passive Bands

In recent years the trend toward more broadband applications in commercial, terrestrial, and satellite-based systems and networks, either fixed or mobile, has accelerated. The most imminent examples are IMT-2020/5G, the currently under development 6G, satellite mega-constellations, and ultrawideband (UWB). The necessary bandwidth to meet the data rates needed for such broadband applications requires these systems to use much higher frequencies. Unfortunately, these radio frequency (RF) spectrum regions are also used by passive microwave sensors, which rely on specific natural emissions produced by elements of the Earth’s surface and its atmosphere that cannot be changed and are critical for meteorological observations.

Accommodating broadband systems in, or adjacent to, frequency bands used by passive sensors may also include compatibility issues and potential for radio frequency interference (RFI) to passive sensors. Even though regulatory requirements are established at both national and international (ITU) levels to protect passive sensors, more services are squeezed into an already crowded spectrum, and problems arise when largely incompatible services find themselves allocated to adjacent radio frequency bands. General regulations and mitigation techniques applied uniformly across the spectrum are likely to be inefficient, potentially leading to a steadily increasing level of RFI over time. This kind of interference, which slowly grows with the level of deployment of such networks, is especially difficult to detect and monitor.

RFI in passive microwave remote sensing occurs when anthropogenic (man-made) sourced signals/noise (non-Gaussian) contaminate calibrated radiometric brightness temperature measurements of naturally occurring thermal radiation (Gaussian noise), thus introducing an error in the geophysical variable being observed which in the end leads to erroneous sensor performance and corrupted data. Most insidious in this context is RFI that is small enough to be realistic (not automatically rejected because the measured data are considered obviously wrong), but large enough to affect the data. This is often considered to be insidious contamination. Currently, passive band sensors are not equipped or designed to differentiate noise between natural and anthropogenic sources leading to an inability to detect insidious RFI.

The most important mechanism for mitigating RFI is to prevent RFI from happening before it starts. This is at the point where the frequencies of potential future RFI sources are determined, and regulatory conditions are established at national, regional, and international (ITU) levels. Only at that point can conditions/limits be established to protect passive bands from RFI. Once these large-scale systems are deployed, it will be very difficult, costly, and lengthy to modify the equipment causing RFI.