Generative Adversarial Learning for Spectrum Sensing

Understand

A novel approach of training data augmentation and domain adaptation is presented to support machine learning applications for cognitive radio.

• Machine learning provides effective tools to automate cognitive radio functionalities by reliably extracting and learning intrinsic spectrum dynamics.
• However, there are two important challenges to overcome, in order to fully utilize the machine learning benefits with cognitive radios.
• First, machine learning requires significant amount of truthed data to capture complex channel and emitter characteristics, and train the underlying algorithm (e.g., a classifier).