Modellazione DPD e PA
Modellare un amplificatore di potenza (PA) utilizzando una rete neurale. Per compensare gli effetti delle non linearità in un PA, è possibile utilizzare una rete neurale per applicare la predistorsione digitale (DPD) al segnale di input.
Per una descrizione del workflow, vedere AI for Digital Predistortion Design (Communications Toolbox).
Argomenti
- AI for Digital Predistortion Design (Communications Toolbox)
Example workflows for training, compressing, and using a deep learning network for digital predistortion design. (Da R2024a)
- PASSAGGIO 1: Data Preparation for Neural Network Digital Predistortion Design (Communications Toolbox)
- PASSAGGIO 2: Neural Network for Digital Predistortion Design-Offline Training (Communications Toolbox)
- PASSAGGIO 3: Neural Network for Digital Predistortion Design - Online Training (Communications Toolbox)
- PASSAGGIO 4: Structurally Compress Neural Network DPD Using Projection (Communications Toolbox)
- Complex-Valued Neural Network for Digital Predistortion Design-Offline Training (Communications Toolbox)
Use a complex-valued neural network, that is trained offline, to apply digital predistortion to offset the effects of nonlinearities in a power amplifier. (Da R2026a)
- Power Amplifier Modeling Using Neural Networks (Communications Toolbox)
Model a power amplifier (PA) using several different neural network (NN) architectures. (Da R2024a)
Esempi in primo piano
Compare Residual Recurrent Neural Network Structures for Digital Predistortion Design
Compare residual RNN structures for a digital predistortion (DPD) design.
