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Over 5 Million Hours of RF Interference Data Enables Instant, Actionable Insights


May 23, 2022 – KIRKLAND, WA — Spectrum Effect® announced today that Spectrum-NET® has collected and labeled more than 200,000 samples of observed RF interference data from mobile operator networks around the world.

Spectrum-NET is the industry’s leading solution for the automated AI-driven analysis of RF interference, enabling operators to rapidly and effectively mitigate sources of RF interference.

The Spectrum Effect team works collaboratively with mobile operators to ensure their RF interference reduction and KPI improvement objectives are realized. With this close cooperation, Spectrum Effect has established a valuable pipeline of RF interference data from operator networks.

“The single largest obstacle for generating meaningful insights from network performance data with machine learning models is collecting a dataset large enough to deliver highly accurate classifications,“ commented Spectrum Effect CTO, Eamonn Gormley. “We have been successful in capturing vast quantities of labeled RF interference signatures that are used to train Spectrum-NET’s convolutional neural network (CNN) models.”

“Operators are hitting the ground running and immediately benefiting from Spectrum-NET’s automated CNN-driven classification,” remarked Spectrum Effect Director of Product Management, Jina Choi. “Our CNN models are continuously updated and refined with additional labeled data samples, which keeps operators better informed about their networks and helps them make faster, data-driven decisions.”


About Spectrum Effect

Spectrum Effect’s mission is to solve the most challenging and costly problems in the wireless industry through innovation and automation. With R&D located in Kirkland, Washington, USA, and Monterrey, Mexico, the Spectrum Effect team is passionate about creating disruptive technologies, engineering excellence, and enhancing the experience of mobile operators. Spectrum Effect has created Spectrum-NET, the industry’s leading solution for the automated analysis of RF interference. Protected by 27 issued patents, Spectrum-NET performs machine learning-driven analysis of RF interference across all RF bands and operates seamlessly across multi-vendor 5G NR, LTE and UMTS cells within mobile networks continually. With Spectrum-NET, operators across the globe are rapidly addressing RF interference, improving network KPIs, surgically deploying their field assets, gaining insights into spectral efficiency, and saving significant OPEX and CAPEX.


Cara Mormino
+1 847 243 3000