Abstract: A phased-array Doppler radar includes a two-way splitter, a transmit antenna, a receive antenna array, an ILO, a demodulation unit and a digital signal processing unit. A reference signal is split by the two-way splitter to the transmit antenna for transmission to targets and the ILO for injection locking. Signals reflected by the targets are received by the receive antenna array as received signals. An injection-locked signal generated by the ILO and the received signals received by the receive antenna array are delivered to the demodulation unit. The received signals are demodulated into baseband I/Q signals by the demodulation unit that uses the injection-locked signal as a local oscillator signal. The baseband I/Q signals are processed by the digital signal processing unit to obtain a digital beamforming pattern.

Abstract: A FCFMSIL radar includes a SILO, a frequency conversion unit, an antenna unit, a demodulation unit and a processing unit. The frequency conversion unit converts an oscillation signal of the SILO into a FMCW signal. The antenna unit transmits the FMCW signal to an area as a transmitted signal and receives a reflected signal from the area as a received signal. The frequency conversion unit converts the received signal into an injection signal and injects it into the SILO. The demodulation unit demodulates the oscillation signal into an in-phase demodulated signal and a quadrature demodulated signal. The processing unit processes the in-phase and the quadrature demodulated signals to obtain a baseband signal and thus acquire a phase and a frequency of a tone in the frequency-domain baseband signal, and determines the tone corresponding to one or multiple objects based on the phase and frequency of the tone.

Abstract: A method of parameter estimation for a multi-input multi-output system based on deep learning is executed. The method includes creating a connection between the base station and a user device entering a coverage of the base station, transmitting real-time channel information from the user device to the base station through the connection, optimizing a parameter for the user device based on the real-time channel information through a deep learning algorithm, transmitting the optimized parameter to the user device, and applying the optimized parameter in a signal detection for the multi-input multi-output system at the user device. The real-time channel information is a channel status of the user device upon the creation of the connection between the base station and the user device. Another method of parameter estimation for a multi-input multi-output system having a base station and a plurality of user devices is also disclosed.

Abstract: A non-contact method of physiological characteristic detection is provided to reduce the time consumption and complexity in calculation. The method includes transmitting a radar signal to at least one detected object through radar to obtain a reflected signal lasting for at least one time session, setting an estimated frequency for each of the at least one time session, obtaining a wave energy corresponding to the estimated frequency, and converging the wave energy with respect to the reflected signal through an optimized algorithm to obtain a physiological characteristic of the at least one detected object.

Abstract: A FCFMSIL radar includes a SILO, a frequency conversion unit, an antenna unit, a demodulation unit and a processing unit. The frequency conversion unit converts an oscillation signal of the SILO into a FMCW signal. The antenna unit transmits the FMCW signal to an area as a transmitted signal and receives a reflected signal from the area as a received signal. The frequency conversion unit converts the received signal into an injection signal and injects it into the SILO. The demodulation unit demodulates the oscillation signal into an in-phase demodulated signal and a quadrature demodulated signal. The processing unit processes the in-phase and the quadrature demodulated signals to obtain a baseband signal and thus acquire a phase and a frequency of a tone in the frequency-domain baseband signal, and determines the tone corresponding to one or multiple objects based on the phase and frequency of the tone.

Abstract: A method includes depositing a copper layer over a first substrate, annealing the copper layer, depositing a hexagonal boron nitride (hBN) film on the copper layer, and removing the hBN film from the copper layer. The hBN film may be transferred to a second substrate.

Abstract: A method of parameter estimation for a multi-input multi-output system based on deep learning is executed. The method includes creating a connection between the base station and a user device entering a coverage of the base station, transmitting real-time channel information from the user device to the base station through the connection, optimizing a parameter for the user device based on the real-time channel information through a deep learning algorithm, transmitting the optimized parameter to the user device, and applying the optimized parameter in a signal detection for the multi-input multi-output system at the user device. The real-time channel information is a channel status of the user device upon the creation of the connection between the base station and the user device. Another method of parameter estimation for a multi-input multi-output system having a base station and a plurality of user devices is also disclosed.

Abstract: A phased-array Doppler radar includes a two-way splitter, a transmit antenna, a receive antenna array, an ILO, a demodulation unit and a digital signal processing unit. A reference signal is split by the two-way splitter to the transmit antenna for transmission to targets and the ILO for injection locking. Signals reflected by the targets are received by the receive antenna array as received signals. An injection-locked signal generated by the ILO and the received signals received by the receive antenna array are delivered to the demodulation unit. The received signals are demodulated into baseband I/Q signals by the demodulation unit that uses the injection-locked signal as a local oscillator signal. The baseband I/Q signals are processed by the digital signal processing unit to obtain a digital beamforming pattern.

Abstract: A non-contact method of physiological characteristic detection is provided to reduce the time consumption and complexity in calculation. The method includes transmitting a radar signal to at least one detected object through radar to obtain a reflected signal lasting for at least one time session, setting an estimated frequency for each of the at least one time session, obtaining a wave energy corresponding to the estimated frequency, and converging the wave energy with respect to the reflected signal through an optimized algorithm to obtain a physiological characteristic of the at least one detected object.

Abstract: A method disclosed in the present invention utilizes an image captured by an image capture device to assist physiological signal paring. Multiple vital signs in the physiological signal detected by a radar are able to be paired with multiple subjects in the image one on one accurately to realize continuous tracking of vital signs of multiple subjects.

Abstract: A communication system and a codec method based on deep learning and known channel state information (CSI) are provided. The communication system includes: a first electronic apparatus including a known first link CSI and a CSI encoder having a deep learning function; and a second electronic apparatus including a known second link CSI and a CSI decoder having a deep learning function. The first and second link CSIs have a correlation or a similarity. The CSI encoder of the first electronic apparatus encodes or compresses the first link CSI into the first codeword, and feeds the first codeword back to the second electronic apparatus via a feedback link. The CSI decoder of the second electronic apparatus encodes or compresses the second link CSI into a second codeword, and decodes or restores the first link CSI of the first electronic apparatus based on the first codeword and the second codeword.

Abstract: A method includes depositing a copper layer over a first substrate, annealing the copper layer, depositing a hexagonal boron nitride (hBN) film on the copper layer, and removing the hBN film from the copper layer. The hBN film may be transferred to a second substrate.

Abstract: A switching method for multiple antenna arrays is disclosed which including: turning on a number of antenna arrays of an electronic device, and obtaining multiple received powers of a beam signal; turning off the antenna array(s) other than the antenna array having the largest received power, and calculating multiple first power ratio parameters according to the received powers; calculating a first channel information of the antenna array which is turned on; calculating a first virtual channel information of each of the antenna arrays which are turned off according to the first channel information, the first power ratio parameter corresponding to each of the antenna arrays which are turned off and an angle mapping table; and selecting one of the antenna arrays to turn on according to the first channel information and all the first virtual channel information, and turning off the rest antenna array(s).

Abstract: A communication system and a codec method based on deep learning and known channel state information (CSI) are provided. The communication system includes: a first electronic apparatus including a known first link CSI and a CSI encoder having a deep learning function; and a second electronic apparatus including a known second link CSI and a CSI decoder having a deep learning function. The first and second link CSIs have a correlation or a similarity. The CSI encoder of the first electronic apparatus encodes or compresses the first link CSI into the first codeword, and feeds the first codeword back to the second electronic apparatus via a feedback link. The CSI decoder of the second electronic apparatus encodes or compresses the second link CSI into a second codeword, and decodes or restores the first link CSI of the first electronic apparatus based on the first codeword and the second codeword.

Abstract: The beamforming calibration system includes a transmitter, a receiver, and a computing device. The transmitter includes multiple transmitting antennas. The computing device provides multiple phase sets to the transmitter. When the computing device provides a first phase set among the phase sets to the transmitter: the transmitter uses the first phase set to set phases of the transmitting antennas, the receiver receives wireless transmission signal from the transmitting antennas to obtain a first radiation pattern corresponding to the first phase set, and the computing device is configured to compare the first radiation pattern with a predetermined pattern to calculate a pattern similarity score corresponding to the first phase set. The computing device selects a calibration phase set among the phase sets according to the pattern similarity score of each phase set, and provides the calibration phase set to the transmitter to calibrate beamforming.

Abstract: The disclosure is directed to an OFDM receiver with a low-resolution ADC and an electronic device thereof. According to one of the exemplary embodiments, the OFDM receiver may include not limited to: an ADC module which receives a transmission signal of a channel in an analog format and digitizes the transmission signal into a digital format to generate a quantized transmission signal; an error compensating and estimating module which is coupled to the ADC module, receives the quantized transmission signal and a feedback signal which is a first estimated time-domain transmission signal to generate an estimated error signal according to a turbo iterative updating technique; and a signal estimating module which is coupled to the error compensating and estimating module, receives the estimated error signal and a channel attenuation coefficient of the channel to generate an estimated transmission signal.

Abstract: The beamforming calibration system includes a transmitter, a receiver, and a computing device. The transmitter includes multiple transmitting antennas. The computing device provides multiple phase sets to the transmitter. When the computing device provides a first phase set among the phase sets to the transmitter: the transmitter uses the first phase set to set phases of the transmitting antennas, the receiver receives wireless transmission signal from the transmitting antennas to obtain a first radiation pattern corresponding to the first phase set, and the computing device is configured to compare the first radiation pattern with a predetermined pattern to calculate a pattern similarity score corresponding to the first phase set. The computing device selects a calibration phase set among the phase sets according to the pattern similarity score of each phase set, and provides the calibration phase set to the transmitter to calibrate beamforming.

Abstract: The disclosure is directed to an OFDM receiver with a low-resolution ADC and an electronic device thereof. According to one of the exemplary embodiments, the OFDM receiver may include not limited to: an ADC module which receives a transmission signal of a channel in an analog format and digitizes the transmission signal into a digital format to generate a quantized transmission signal; an error compensating and estimating module which is coupled to the ADC module, receives the quantized transmission signal and a feedback signal which is a first estimated time-domain transmission signal to generate an estimated error signal according to a turbo iterative updating technique; and a signal estimating module which is coupled to the error compensating and estimating module, receives the estimated error signal and a channel attenuation coefficient of the channel to generate an estimated transmission signal.

Abstract: The present disclosure discloses a receiver device, including receiving antennas, radio frequency receivers, a configurable precision analog-to-digital converter, a switch device, a baseband processor, and an analog-to-digital controller. The switch device converts a first number of baseband analog signals into a second number of baseband analog signals. The configurable precision analog-to-digital converter converts the second number of baseband analog signals into a third number of first baseband digital signals. The configurable precision analog-to-digital converter combines at least two of first analog-to-digital converters into at least one second analog-to-digital converter so that the total number of the rest of the first analog-to-digital converters and the at least one second analog-to-digital converters is equal to the third number. The resolution of each of the second analog-to-digital converters is higher than the resolution of each of the first analog-to-digital converters.

Abstract: The present disclosure discloses a receiver device, including receiving antennas, radio frequency receivers, a configurable precision analog-to-digital converter, a switch device, a baseband processor, and an analog-to-digital controller. The switch device converts a first number of baseband analog signals into a second number of baseband analog signals. The configurable precision analog-to-digital converter converts the second number of baseband analog signals into a third number of first baseband digital signals. The configurable precision analog-to-digital converter combines at least two of first analog-to-digital converters into at least one second analog-to-digital converter so that the total number of the rest of the first analog-to-digital converters and the at least one second analog-to-digital converters is equal to the third number. The resolution of each of the second analog-to-digital converters is higher than the resolution of each of the first analog-to-digital converters.