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September 10, 2025Open Access

Machine Learning in Near-Field Communication for 6G: A Survey

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This survey discusses machine learning applications for enhancing near-field communication channels and system performance.

Machine learning enhances system performance in near-field communication, addressing challenges in channel modeling and beamforming design.
Key areas of application include channel estimation and security enhancement, highlighting the integration of machine learning in 6G networks.
Near-field communication utilizes extremely large-scale antenna arrays, fundamentally changing wave characteristics for improved connectivity.
Challenges remain, such as data privacy and computational complexity, underscoring the need for advanced machine learning techniques.

Iqbal et al. (2025) studied this question.

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September 10, 2025Open Access

View Full Paper

Ask AI

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Authors

This survey discusses machine learning applications for enhancing near-field communication channels and system performance.

Machine learning enhances system performance in near-field communication, addressing challenges in channel modeling and beamforming design.
Key areas of application include channel estimation and security enhancement, highlighting the integration of machine learning in 6G networks.
Near-field communication utilizes extremely large-scale antenna arrays, fundamentally changing wave characteristics for improved connectivity.
Challenges remain, such as data privacy and computational complexity, underscoring the need for advanced machine learning techniques.

Iqbal et al. (2025) studied this question.

View Full Paper

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