Artificial Intelligence and Machine Learning (AI-ML) for CSI Compression and Reconstruction in 5G Networks

• CSI Compression and Reconstruction using CSINet for TDD Massive MIMO 5G Networks
  • Import Libraries
    • Import Python Libraries
    • Import 5G Toolkit Libraries
  • Simulation Parameters
  • Wireless Channel Generation: CDL-A
  • Reconstrunction Performance of CSI-Net
  • PDSCH Parameters
  • PDSCH: Transmitter
  • SVD Based Beamforming: Perfect CSI
  • Pass through Channel
  • Link Level Simulation: SVD based Beamforming using Perfect CSI
  • SVD Based Beamforming: CSI Reconstructed using CSINet
  • Pass through Wireless Channel
  • Link Level Simulation: SVD based Beamforming using Imperfect CSI
• Performance Evaluations
  • Throughput Evaluations
  • BLER Evaluations
  • References
• Wireless Channel Dataset Generation for Training the AI based Models
  • Import Python Libraries
    • Import Basic Python LIbraries
    • Import 5G Toolkit Libraries
  • Simulation Parameters
  • Set Channel Parameters and Generate Common Parameters
  • Generate the Wireless Channels Databases and Preprocess it before storage.
  • Aggregate all the Datasets into a single Dataset
  • Display Sparsity of Wireless Channels
• Training the CSINet
  • Import Libraries
    • Import Python Libraries
  • Important AI-ML Libraries
  • Load Datasets
  • Set Training Parameters