Deconflicting Commercial and Military 5G Signals

The Challenge: Expanded Commercial 5G Can Disrupt Military Communications

Most commercial 5G cellular services currently operate at 3.3–4.2 gigahertz (GHz). In anticipation of increased demand for 5G, industry is looking to expand into the 3.1–3.3 GHz range, where the U.S. military operates its communications, control, and other systems. These 5G signals have the potential to disrupt military radar and other communications.

To address this challenge, under the auspices of its 5G to Next G program, the Office of the Undersecretary of Defense for Research and Engineering (OUSD(R&E)) is funding the prototyping of various spectrum-sharing solutions. As part of that effort, in early 2021 ĢƵ Allen was selected as one of the awardees to develop and deploy a rapid prototype of such a system—in this case, one that would allow commercial 5G and military airborne radar systems to share the same spectrum.

The Approach: Applying Artificial Intelligence to Signal Processing

ĢƵ Allen’s prototype system first digitizes the signals on the shared spectrum then uses artificial intelligence (AI) to identify potential conflicts. The system then determines what measures are needed to deconflict the signals and sends those to the commercial 5G station to implement.

At the heart of the solution is ĢƵ Allen’s patented R.AI.DIO® capability that brings AI to radio signal processing. R.AI.DIO® signal processing capability—which ĢƵ Allen developed as an internal technology investment and has leveraged for other government clients—has a wide range of applications. These include making communications more secure and resilient, detecting rogue communication signals, and providing early warning of adversary jamming efforts. R.AI.DIO® processing can also be used on large unprocessed radio frequency (RF) datasets to quickly triage regions of interest and enable faster signal discovery.

ĢƵ Allen’s approach substantially accelerates the decision analytics involved in spectrum sharing and coexistence solutions.

Here are the four basic steps in ĢƵ Allen’s AI-enabled spectrum sharing and coexistence solution:

  • A high-dynamic-range software-defined radio continuously digitizes all of the signals on the shared channel and removes any noise.
  • ĢƵ Allen’s R.AI.DIO® neural networks use AI to rapidly identify the commercial 5G signals and military airborne radar signals that might conflict.
  • Potentially conflicting 5G and military signals are passed to a “command word generator,” which decides which, if any, interference-mitigation measures should be taken. These measures can include shifting the 5G signals to another frequency, lowering their power level, or applying other mitigation measures in the 5G system.
  • The system interfaces with the relevant commercial 5G base station, which can then automatically execute any mitigation measures needed to protect the radar.

ĢƵ Allen began the project in February 2021 and is implementing a 15-month proof-of-concept phase. This includes developing, testing, and optimizing the software and hardware components and then testing the system as a whole in ĢƵ Allen’s RF laboratories.

The testing takes place in a mixed-signal environment that simulates the effects of terrain, land clutter, buildings, atmospheric obstructions, and other real-world conditions that might affect RF performance.

Following the proof of concept, ĢƵ Allen will conduct incremental testing and improvements to the system for 1 year at its own labs and at an Air Force electromagnetic compatibility facility. This lab testing will be followed by at least 1 year of field testing at Hill Air Force Base in Utah, where the airborne radars involved in the project are based.

The Solution: Allowing Military and Commercial Users to Share 5G Spectrum

Modeling and simulation efforts in Phase 1 of ĢƵ Allen’s prototype system have successfully demonstrated that Air Force AWACS can dynamically share the same spectrum as 5G cellular services. One way it does this is by substantially shortening the time it takes to discriminate, identify, and deconflict signals.

The system performs signal detection and generates response significantly faster than traditional systems. This capability makes it possible for the system to achieve one of the DOD’s primary goals for the project—the ability to initiate interference mitigation measures before a commercial 5G system can cause harmful interference to military communications.

In addition, ĢƵ Allen was able to train and test the prototype’s ability to identify 5G and military airborne radar signals with nearly 100% accuracy, using a synthetic data generator and modeling software in a testbed environment.

The project’s success also demonstrated the feasibility of applying the same AI-enabled approach to 5G signal sharing for numerous other military, intelligence, commercial, and homeland security-related use cases. The system may eventually enable military and commercial signal sharing across an array of cellular and noncellular wireless communication systems.

ĢƵ Allen’s spectrum coexistence and sharing system highlights ĢƵ Allen’s multidisciplinary approach, highlighting our deep expertise in AI, RF communications engineering, and systems integration. In doing so, it demonstrates the company’s ability to rapidly develop cutting-edge capabilities that leverage its robust independent research and development investments.

This effort was sponsored by the U.S. government under Other Transaction Number W15QKN-21-9-5599 between the National Spectrum Consortium (NSC) and the government. The U.S. government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation herein. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. government.

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