Anritsu Jointly Verifies AI-Based Antenna Optimization with SK Telecom, POSTECH and Bluetest

ANRITSU CORPORATION announced that it has jointly verified AI-based antenna optimization technologies with SK Telecom, South Korea’s leading mobile network operator, Pohang University of Science and Technology (POSTECH), and Bluetest of Sweden.

In this verification, MIMO measurement data were acquired in a real user environment using Anritsu’s Radio Communication Test Station MT8000A and Universal Wireless Test Set MT8870A. Based on AI-based analysis and optimization technologies, the effectiveness of antenna performance optimization was confirmed.

Details of this joint verification were also presented at MWC Barcelona 2026 (MWC 2026), one of the world’s largest mobile communications exhibitions.

This verification analyzed antenna performance based on throughput and ECC (Error Correlation Coefficient) data collected from real user environments. It reflected practical usage conditions, including free-space scenarios, handheld operation, and head-proximate usage scenarios. By incorporating a variety of user grip conditions, it quantitatively evaluated performance variations under time-varying RF conditions.

Through AI-based analysis, RF performance differences according to antenna tuner states were modeled, and the optimal antenna switching configuration was automatically identified. This enabled dynamic optimization of antenna performance while maintaining communication quality in real user environments.

Based on measurement-driven evaluation results, significant throughput improvements were confirmed across various user scenarios in an 8Rx (eight-receive-antenna) configuration, while in a 4Tx (four-transmit-antenna) configuration, throughput improvement of up to more than two times was observed.

Verification Overview

This verification presented an AI-based antenna optimization workflow built on real measurement data collected in an Over-the-Air (OTA) test environment.

The verification covered the following processes:

• Analysis of RF performance variations according to user scenarios and tuner state changes
• Comparison of power and performance characteristics for each antenna path
• Derivation of optimal switching states based on throughput and ECC data
• Verification of performance improvement through AI analysis based on measurement data

This approach goes beyond conventional static antenna design-centric evaluation, enabling data-driven optimization verification that reflects real environmental conditions.

MT8000A (5G NR Test Platform)

MT8000A is an integrated RF and protocol-based test platform for 5G NR device validation. In this verification, it was used for MIMO performance analysis and throughput evaluation in an OTA environment.

Key features include:

• 4×4 / 8×8 MIMO signal generation and OTA data acquisition
• Multi-port synchronized measurement based on digital IQ capture
• Throughput evaluation under controlled 5G NR link conditions
• Provision of a repeatable and stable RF test environment

MT8000A provided high-precision signal generation and analysis capabilities for measurement-based performance verification, supporting the acquisition of highly reliable data required for AI modeling.

MT8870A (RF Measurement Platform)

MT8870A is a general-purpose wireless measurement platform supporting non-signaling RF measurements. In this verification, it was used for RF characteristic analysis by antenna path and comparative measurement of switching states.

Key features include:

• RF power measurement by antenna path under various tuner states
• TX/RX path control and RF characteristic measurement
• Collection of measurement data across antenna paths and switching states
• Support for multi-port RF measurement configurations

The path-specific RF characteristic data obtained through MT8870A is used as core input data for AI-based optimization analysis.

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