AI 功能

支持无线应用深度学习工作流的函数和对象

借助 Communications Toolbox™ 和 Deep Learning Toolbox™，您可以训练包含神经网络的无线通信系统。

使用 AI 功能来分析和优化无线信道，以实现更好的信号处理、信道估计和资源管理。
训练无线神经网络需要支持 dlarray (Deep Learning Toolbox) 数据对象的 Communications Toolbox 函数和对象。有关支持 dlarray 对象的无线通信领域特定函数集，请参阅Wireless Communications (Deep Learning Toolbox)。

函数

`awgn`	向信号添加高斯白噪声
`bit2int`	Convert bits to integers (自 R2021b 起)
`genqammod`	General quadrature amplitude modulation (QAM)
`ofdmmod`	Modulate signals using OFDM method
`ofdmdemod`	Demodulate signals using OFDM method
`ofdmChannelResponse`	Calculate OFDM channel response (自 R2023a 起)
`ofdmEqualize`	Equalize OFDM signals (自 R2022b 起)

`comm.ChannelFilter`	Filter signal using multipath gains at specified path delays
`comm.MIMOChannel`	Filter input signal through MIMO multipath fading channel

`dpdPreprocessor`	Digital predistortion (DPD) data input preprocessor for AI algorithms (自 R2024b 起)
`signalDatastore`	Datastore for collection of signals

Background Data Generation
Generate simulation input data in the background while running your simulation loop on parameterized conditions rather than generating the data in advance and recalling the stored data and run time. (自 R2026a 起)
Cosine Similarity As a Channel Estimate Quality Metric
Use the cosine similarity metric to compare two vectors. (自 R2024b 起)
Normalized Mean Squared Error as a Distance Measure
Use the normalized mean squared error (NMSE) as a loss function for training a neural network in a wireless communications application. (自 R2025a 起)