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Elisa Boosts RF Performance with ML-based Spectrum Analytics Solution

Elisa Boosts RF Performance with ML-based Spectrum Analytics Solution Image Credit: Spectrum Effect

Spectrum Effect announced a successful milestone in the trial of its Spectrum-NET machine learning solution with Elisa Estonia.

Spectrum Effect, founded by the wireless industry veterans behind SON Leader Eden Rock Communications, claims that it has pioneered the application of new machine learning algorithms for mobile network data designed to detect, characterize, and localize RF interference. 

Spectrum-NET automatically detects, characterizes, locates and assesses the impact of external and unintended internal RF interference in mobile networks. Spectrum-NET operates throughout multi-vendor LTE and UMTS networks on a continual basis without service interruption or dependency on external probes.

Kristo Kork, Head of Radio Access Networks and Infrastructure, Elisa
The successful trial utilizing Spectrum-NET to analyze Elisa’s mobile network uncovered numerous instances of external and unintended internal RF interference, including previously undetectable passive intermodulation (PIM) interference.

Frank J. DeJoy, CEO, Spectrum Effect 
Elisa is a very innovative operator and it’s been a great experience collaborating with their team. We are pleased to have achieved exceptional results in this trial and we are now fully focused on providing measurable benefits to mobile operators with our full-scale, global launch of Spectrum-NET later this year.

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Author

Ray is a news editor at The Fast Mode, bringing with him more than 10 years of experience in the wireless industry.

For tips and feedback, email Ray at ray.sharma(at)thefastmode.com, or reach him on LinkedIn @raysharma10, Facebook @1RaySharma

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