Hybrid Wireless Processing Chains that Include Deep Neural Networks and Static Algorithm Modules

Techniques and apparatuses are described for hybrid wireless communications processing chains that include deep neural networks (DNNs) and static algorithm modules. In aspects, a first wireless communication device communicates with a second wireless device using a hybrid transmitter processing chain. The first wireless communication device selects a machine-learning configuration (ML configuration) that forms a modulation deep neural network (DNN) that generates a modulated signal using encoded bits as an input. The first wireless communication device forms, based on the modulation ML configuration, the modulation DNN as part of a hybrid transmitter processing chain that includes the modulation DNN and at least one static algorithm module. In response to forming the modulation DNN, the first wireless communication devices processes wireless communications associated with the second wireless communication device using the hybrid transmitter processing chain.