Transfer learning for modulation generalization in neural net transmitters/receivers

A transfer learning (TL)-based method for training a target neural net demodulator, comprising:

• training a fixed neural net demodulator model for a fixed modulation order 2q for q∈θ={2, 4, . . . , M}, wherein the fixed neural net demodulator model comprises a plurality of base layers starting at an input and at least one output layer at an output;
• generating a set of neural net demodulator models for modulation orders 2z, where ∀ z≠q∈θ={2, 4, . . . , M}, wherein each of the set of neural net demodulator models comprises a plurality of base layers starting at an input and one or more training output layers at an output;
• transferring the plurality of base layers of the fixed neural net demodulator model to the target neural net demodulator;
• transferring each of the one or more training output layers of each of the set of neural net demodulator models to the target neural net demodulator;
• training, by the target neural net demodulator, for a set of desired modulation orders by, for each of the set of one or more training output layers:
• combining the transferred plurality of base layers of the fixed neural net demodulator model and each of the transferred one or more training output layers into a combination;
• and
• training each combination to generate a trained set of the one or more training output layers, wherein each of the trained set matches one of the set of desired modulation orders;
• and
• storing the plurality of transferred base layers and the trained set of the one or more training output layers at the target neural net demodulator.

A transfer learning (TL)-based system for training a target neural net demodulator, comprising:

• at least one source processor with a non-transitory computer-readable memory storing instructions executable by the at least one source processor to:
• train a neural net demodulator model for a fixed modulation order, wherein the trained neural net demodulator model comprises a plurality of base layers starting at an input and at least one output layer at an output;
• and
• transfer the plurality of base layers to the target neural net demodulator;
• and
• at least one target processor in the target neural net demodulator with a non-transitory computer-readable memory storing instructions executable by the at least one target processor to:
• train a set of one or more training output layers matching each of a set of desired modulation orders by receiving the plurality of base layers transferred from the at least one source processor, and, for each of the set of one or more training output layers:
• combining the received plurality of base layers and each of the set of one or more training output layers into a combination;
• and
• training each combination to generate a trained set of the one or more training output layers, wherein each of the trained set matches one of the set of desired modulation orders;
• and
• store the plurality of transferred base layers and the trained set of the one or more training output layers at the target neural net demodulator.