Change detection device incorporating quantum computing with game theoretic optimization and related methods

A cognitive radio device comprising:

• an RF receiver configured to receive interfering RF signals;
• an RF transmitter configured to be selectively operated;
• a quantum computing circuit configured to perform quantum subset summing;
• and
• a processor configured to
• generate a game theory reward matrix for a plurality of different deep learning models, the game theory reward matrix including rows corresponding to a union between at least some of frequency bins,
• waveform types, and data rates, and columns corresponding to predictive deep learning metrics for the different deep learning models,
• cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix,
• select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and
• process the received interfering RF signals using the selected deep learning model for selectively operating the RF transmitter.

A method for operating a cognitive radio device comprising an RF receiver configured to receive interfering RF signals, an RF transmitter configured to be selectively operated, and a quantum computing circuit configured to perform quantum subset summing, and a processor, the method comprising:

• using the processor for
• generating a game theory reward matrix for a plurality of different deep learning models;
• cooperating with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix;
• selecting a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix;
• and
• processing the received interfering RF signals using the selected deep learning model for selectively operating the RF transmitter.