A device for OOK modulating an input signal, comprising at least: an injection-locked oscillator comprising a power supply input, an injection signal input and an output to which the OOK modulated signal is to be delivered; a first controlled switch comprising a control input to which the input signal is to be applied, and configured to couple or not a power supply source to the power supply input of the injection-locked oscillator in dependence on the value of the input signal; a periodic signal providing device configured to deliver, on an output which is electrically coupled to the injection signal input of the injection-locked oscillator, a periodic injection signal whose frequency and amplitude trigger locking of the injection-locked oscillator at the frequency of the injection signal or a multiple of this frequency.

A device for OOK modulating an input signal, comprising at least: an injection-locked oscillator comprising a power supply input, an injection signal input and an output to which the OOK modulated signal is to be delivered; a first controlled switch comprising a control input to which the input signal is to be applied, and configured to couple or not a power supply source to the power supply input of the injection-locked oscillator in dependence on the value of the input signal; a periodic signal providing device configured to deliver, on an output which is electrically coupled to the injection signal input of the injection-locked oscillator, a periodic injection signal whose frequency and amplitude trigger locking of the injection-locked oscillator at the frequency of the injection signal or a multiple of this frequency.

Disclosed by the present invention is a sub-band selection activation-based multi-band hyperbolic frequency modulation spread spectrum underwater acoustic communication method. The present invention discloses: dividing the available bandwidth of an underwater acoustic system into a plurality of sub-bands, performing hyperbolic frequency modulation on each of the sub-bands respectively, and performing spread spectrum modulation on the plurality of sub-bands within the same frequency modulation period, thus implementing multi-band parallel transmission. Hence, within each frequency modulation period, the divided plurality of sub-bands is grouped, and each sub-band group activates different sub-bands for transmission according to different options for transmitting data. Compared to other underwater acoustic hyperbolic frequency modulation communication solutions, the present invention further improves the frequency band utilization of the system, and the energy efficiency is also improved.

The present disclosure provides a frequency-converting super-regenerative transceiver with a frequency mixer coupled to a resonator and a feedback element having a controllable gain. The frequency-converting super-regenerative transceiver utilizes the frequency mixer to shift the incoming frequencies, based on a controlled oscillator, to match the frequency of operation of the super-regenerative transceiver. The frequency-converting super-regenerative transceivers described herein permit signal data capture over a broad range of frequencies and for a range of communication protocols. The frequency-converting super-regenerative transceivers described herein are tunable, consume very little power for operation and maintenance, and permit long term operation even when powered by very small power sources (e.g., coin batteries).

Electronic device and method for driving electronic device. The electronic device includes battery, power management integrated circuit (PMIC) configured to control charging status of battery, coil, wireless power circuit electrically connected to coil, communication circuit electrically connected to coil, and processor, wherein processor is configured to, when the wireless power circuit is in a transmission (Tx) mode, transmit a wireless power signal through the coil by using the wireless power circuit, and transmit a signal obtained by frequency shift keying (FSK)-modulating a transmission device parameter by using the communication circuit, to an external electronic device through the coil, and when the wireless power circuit is in a reception (Rx) mode, receive wireless power by using the wireless power circuit to charge the battery, and transmit a signal obtained by amplitude shift keying (ASK)-modulating a reception device parameter by using the communication circuit, to the external electronic device through the coil.

Electronic device and method for driving electronic device. The electronic device includes battery, power management integrated circuit (PMIC) configured to control charging status of battery, coil, wireless power circuit electrically connected to coil, communication circuit electrically connected to coil, and processor, wherein processor is configured to, when the wireless power circuit is in a transmission (Tx) mode, transmit a wireless power signal through the coil by using the wireless power circuit, and transmit a signal obtained by frequency shift keying (FSK)-modulating a transmission device parameter by using the communication circuit, to an external electronic device through the coil, and when the wireless power circuit is in a reception (Rx) mode, receive wireless power by using the wireless power circuit to charge the battery, and transmit a signal obtained by amplitude shift keying (ASK)-modulating a reception device parameter by using the communication circuit, to the external electronic device through the coil.

Systems and methods for classifying radio frequency signal modulations include receiving, at a consolidated neural network, a complex quadrature vector of interest representative of a baseband signal derived from a radio frequency signal, generating multiple data representations of the vector of interest, providing each data representation to one of multiple parallel neural networks in the consolidated neural network, and receiving, from the consolidated neural network, a classification result for the baseband signal. The consolidated neural network may be trained to classify baseband signals with respect to known modulation types by receiving complex quadrature training vectors, each including samples of a baseband signal derived from a radio frequency signal of known modulation type, comparing a classification result for the training vector to the known modulation type to determine modulation classification performance, and modifying a configuration parameter of the consolidated neural network dependent on the determined modulation classification performance.

Systems and methods for classifying radio frequency signal modulations include receiving, at a consolidated neural network, a complex quadrature vector of interest representative of a baseband signal derived from a radio frequency signal, generating multiple data representations of the vector of interest, providing each data representation to one of multiple parallel neural networks in the consolidated neural network, and receiving, from the consolidated neural network, a classification result for the baseband signal. The consolidated neural network may be trained to classify baseband signals with respect to known modulation types by receiving complex quadrature training vectors, each including samples of a baseband signal derived from a radio frequency signal of known modulation type, comparing a classification result for the training vector to the known modulation type to determine modulation classification performance, and modifying a configuration parameter of the consolidated neural network dependent on the determined modulation classification performance.

Systems and methods for classifying baseband signals with respect to modulation type include receiving, at a consolidated neural network whose objective is modulation classification performance, a complex quadrature vector of interest including multiple samples of a baseband signal derived from a radio frequency signal of unknown modulation type, generating multiple data representations of the vector of interest, providing each data representation to one of multiple parallel neural networks in the consolidated neural network, and receiving a classification result for the baseband signal based on combined outputs of the parallel neural networks. The consolidated neural network may be trained to classify baseband signals with respect to known modulation types by receiving complex quadrature training vectors, each including samples of a baseband signal derived from a radio frequency signal of known modulation type, and comparing a classification result for the training vector to the known modulation type to determine modulation classification performance.

Systems and methods for classifying baseband signals with respect to modulation type include receiving, at a consolidated neural network whose objective is modulation classification performance, a complex quadrature vector of interest including multiple samples of a baseband signal derived from a radio frequency signal of unknown modulation type, generating multiple data representations of the vector of interest, providing each data representation to one of multiple parallel neural networks in the consolidated neural network, and receiving a classification result for the baseband signal based on combined outputs of the parallel neural networks. The consolidated neural network may be trained to classify baseband signals with respect to known modulation types by receiving complex quadrature training vectors, each including samples of a baseband signal derived from a radio frequency signal of known modulation type, and comparing a classification result for the training vector to the known modulation type to determine modulation classification performance.