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Machine Learning for 6G CSI-RS Processing

Developed novel machine learning-based methods for CSI-RS (Channel State Information Reference Signal) processing for 6G standards, achieving NMSE in the order of 1e-3 using UNet-inspired architectures.

ML Deep Learning 6G Signal Processing Research Industry

Tech Stack

Python PyTorch Deep Learning 6G Communications Signal Processing UNet
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Results

Designed and implemented UNet-inspired deep learning architectures achieving Normalized Mean Squared Error (NMSE) in the order of 1e-3. Work under patent filing process for potential impact on future 6G physical layer standards.

Key Ideas

  • Collaborated with 6G Standards Team at Samsung R&D Institute India
  • Designed UNet-inspired architectures for CSI-RS processing
  • Achieved state-of-the-art performance with NMSE ~1e-3
  • Patent filing in process for 6G physical layer standards

Overview

This project involved developing innovative machine learning-based solutions for Channel State Information Reference Signal (CSI-RS) processing in 6G communication systems. The work was conducted in collaboration with the 6G Standards Team at Samsung R&D Institute India.

Problem Statement

CSI-RS processing is critical for 6G communication systems. Traditional signal processing methods face challenges in accuracy and efficiency. This project aimed to leverage deep learning to improve CSI-RS processing performance.

Architecture

The solution uses UNet-inspired deep learning architectures, which are well-suited for signal processing tasks:

  • Encoder-decoder structure for feature extraction and reconstruction
  • Skip connections for preserving fine-grained details
  • Optimized for signal processing domain

Results

Achieved exceptional performance:

  • NMSE in the order of 1e-3 - significantly better than traditional methods
  • Efficient processing suitable for real-time applications
  • Patent filing in process due to potential impact on 6G physical layer standards

Impact

This work has significant implications for future 6G communication systems, potentially influencing physical layer standards. The patent filing process reflects the innovative nature and commercial potential of the solution.