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ML Optimizes 5G UE mmWave 3D EIS Scan Test Time

This long test time is greatly shortened by using machine learning, which is expected to optimize the test efficiency for mmWave UE become commonplace.

ML-OptimizationAnritsu Company has introduced new “EIS-CDF Optimization using Machine Learning” MX800010A-026 software option for the “Radio Communication Test Station” MT8000A, which uses machine learning to optimize 5G mmWave 3D EIS Scan (EIS-CDF) test times.

Development Background

Rollout of fast connection 5G mmWave (FR2) services is gathering pace in advanced economies, such as N. America and Japan. Consequently, R&D and conformance tests of mmWave UE are expected to become active markets in future.

The 3GPP standard specifies tests of mmWave UE antenna properties in 3D in an Over-the-Air (OTA) test environment. The 3D testing needs to take long test time due to large number or measurement points.

This long test time is greatly shortened by using machine learning, which is expected to optimize the test efficiency for mmWave UE become commonplace.

Product Features

The MX800010A-026 software option supports 3D EIS Scan tests using Anritsu’s CATR Anechoic Chamber MA8172A by automatically learning the UE antenna properties to facilitate test efficiency. Multiple repetitions of the 3D EIS Scan with the same UE optimizes the test efficiency.

The machine learning optimized the tests times of two mmWave UE models by about 35% to 60%* from subsequent learning repetitions.

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Nitisha Dubey

I am a Journalist with a post graduate degree in Journalism & Mass Communication. I love reading non-fiction books, exploring different destinations and varieties of cuisines. Biographies and historical movies are few favourites.

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