Python 与 MATLAB
用于无线的 AI 直接从 MATLAB® 调用 Python® 库功能
与使用其他深度学习框架的同事协作，通过从 MATLAB 直接调用 Python 来训练和测试 PyTorch®、TensorFlow™ 或 ONNX™ 模型。您也可以导入和导出函数。
工作流步骤包括数据生成、数据准备、深度神经模型训练、模型压缩、模型测试和模型部署。
这些示例侧重于训练、测试和部署工作流步骤，以演示在 5G 无线通信系统中使用人工智能 (AI) 运行 PyTorch 模型执行信道状态信息 (CSI) 反馈压缩和 CSI 预测方法。
主题
简介
- Call Python from MATLAB for Wireless
AI for wireless workflows calling Python from MATLAB to run PyTorch or TensorFlow models. (自 R2025a 起) - PyTorch Wrapper Template
You can use your own PyTorch models in MATLAB by using the Python interface.
模型训练
- Train PyTorch Channel Prediction Models (5G Toolbox)
Train a PyTorch neural network for channel prediction by using data generated in MATLAB. (自 R2025a 起) - Train PyTorch Channel Prediction Models with Online Training (5G Toolbox)
Enable real‐time adaptation to time‐varying wireless channels by generating each training batch in MATLAB on-the-fly to train a PyTorch GRU channel prediction network online. (自 R2026a 起) - Offline Training and Testing of PyTorch Model for CSI Feedback Compression (5G Toolbox)
Train an autoencoder-based PyTorch neural network offline and test for CSI compression. (自 R2025a 起) - Online Training and Testing of PyTorch Model for CSI Feedback Compression (5G Toolbox)
Train an autoencoder-based PyTorch neural network online and test for CSI compression. (自 R2025a 起)
模型测试
- Test AI-based CSI Compression Techniques for Enhanced PDSCH Throughput (5G Toolbox)
Measure physical downlink shared channel (PDSCH) throughput in a 5G New Radio (NR) system, with a primary focus on AI-based compression methods for CSI feedback. (自 R2026a 起) - Apply Transfer Learning on PyTorch Model to Identify 5G and LTE Signals (5G Toolbox)
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. (自 R2025a 起) - Verify Performance of 6G AI-Native Receiver Using MATLAB and PyTorch Coexecution (5G Toolbox)
Integrate a trained PyTorch network with MATLAB-based data generation to simulate an AI-native air interface. (自 R2025a 起)
模型部署
- Import TensorFlow Channel Feedback Compression Network and Deploy to GPU (5G Toolbox)
Generate GPU specific C++ code for a pretrained TensorFlow channel state feedback autoencoder. (自 R2023b 起)
