接收机算法
以下示例演示了可用于各种接收机算法的 AI 技术。
精选示例
Verify Performance of 6G AI-Native Receiver Using MATLAB and PyTorch Coexecution
Integrate a trained PyTorch® network with MATLAB®-based data generation to simulate an AI-native air interface.
(5G Toolbox)
- 自 R2025a 起
AI-Native Fully Convolutional Receiver
Use a convolutional neural network to replace conventional channel estimation, equalization, and symbol demodulation.
(5G Toolbox)
- 自 R2025a 起
Training and Testing a Neural Network for LLR Estimation
Generate signals and channel impairments to train a neural network, called LLRNet, to estimate exact log likelihood ratios (LLR).
(Communications Toolbox)
Deep Learning Data Synthesis for 5G Channel Estimation
Generate deep learning training data for channel estimation using 5G Toolbox™.
(5G Toolbox)
MATLAB Command
You clicked a link that corresponds to this MATLAB command:
Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.
选择网站
选择网站以获取翻译的可用内容,以及查看当地活动和优惠。根据您的位置,我们建议您选择:。
您也可以从以下列表中选择网站:
如何获得最佳网站性能
选择中国网站(中文或英文)以获得最佳网站性能。其他 MathWorks 国家/地区网站并未针对您所在位置的访问进行优化。
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)

