AI를 사용한 5G NR

5G NR을 위한 딥러닝 워크플로

5G NR 통신 시스템에 Deep Learning Toolbox™ 기능을 통합한 딥러닝 워크플로를 살펴봅니다.

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추천 예제

5G 채널 추정을 위한 딥러닝 데이터 합성

5G 채널 추정을 위한 딥러닝 데이터 합성

5G Toolbox™를 사용하여 채널 추정을 위한 딥러닝 훈련 데이터를 생성합니다.

Import TensorFlow Channel Feedback Compression Network and Deploy to GPU

Import TensorFlow Channel Feedback Compression Network and Deploy to GPU

Generate GPU specific C++ code for a pretrained TensorFlow™ channel state feedback autoencoder.

AI for Positioning Accuracy Enhancement

AI for Positioning Accuracy Enhancement

Use AI to estimate the position of user equipment and compare performance with traditional TDoA techniques.

Neural Network for Beam Selection

Neural Network for Beam Selection

Use a neural network to reduce overhead in the beam selection task by using the location of the receiver rather than knowledge of the communication channels.

Train DQN Agent for Beam Selection

Train DQN Agent for Beam Selection

Train a deep Q-network (DQN) reinforcement learning agent for beam selection in a 5G new radio communications system.

Spectrum Sensing with Deep Learning to Identify 5G, LTE, and WLAN Signals

Spectrum Sensing with Deep Learning to Identify 5G, LTE, and WLAN Signals

Train a semantic segmentation network using deep learning for spectrum monitoring.

  • R2021b 이후
Apply Transfer Learning on PyTorch Model to Identify 5G and LTE Signals

Apply Transfer Learning on PyTorch Model to Identify 5G and LTE Signals

Coexecution with Python to identify 5G NR and LTE signals by using the transfer learning technique on a pre-trained PyTorch™ semantic segmentation network for spectrum sensing.

Train PyTorch Channel Prediction Models

Train PyTorch Channel Prediction Models

Train a PyTorch® neural network for channel prediction by using data generated in MATLAB.