Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that can leverage a natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity. In particular, the disclosed systems can tokenize activity event vectors to generate a series of sequential tokens that correspond to recent user activity of one or more user accounts. In addition, the disclosed systems can, for each candidate (e.g., hypothetical) user activity, augment the series of sequential tokens to include a corresponding token. Based on respective probability scores for each of the augmented series of sequential tokens, the disclosed systems can identify as the predicted user activity, a candidate user activity corresponding to one of the augmented series of sequential tokens associated with a highest probability score. Based on the predicted user activity, the disclosed systems can surface one or more suggestions to a client device.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that can leverage a natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity. In particular, the disclosed systems can tokenize activity event vectors to generate a series of sequential tokens that correspond to recent user activity of one or more user accounts. In addition, the disclosed systems can, for each candidate (e.g., hypothetical) user activity, augment the series of sequential tokens to include a corresponding token. Based on respective probability scores for each of the augmented series of sequential tokens, the disclosed systems can identify as the predicted user activity, a candidate user activity corresponding to one of the augmented series of sequential tokens associated with a highest probability score. Based on the predicted user activity, the disclosed systems can surface one or more suggestions to a client device.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that can leverage a natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity. In particular, the disclosed systems can tokenize activity event vectors to generate a series of sequential tokens that correspond to recent user activity of one or more user accounts. In addition, the disclosed systems can, for each candidate (e.g., hypothetical) user activity, augment the series of sequential tokens to include a corresponding token. Based on respective probability scores for each of the augmented series of sequential tokens, the disclosed systems can identify as the predicted user activity, a candidate user activity corresponding to one of the augmented series of sequential tokens associated with a highest probability score. Based on the predicted user activity, the disclosed systems can surface one or more suggestions to a client device.

Abstract: Embodiments of the present disclosure provide a method, a device, and a storage medium for hybrid automatic gain control in a communication system. The method includes amplifying an input signal to generate an amplified signal which is converted into a plurality of output signals; obtaining a moving average amplitude of a plurality of output signals of a current input signal; and calculating a signal amplitude difference according to the moving average amplitude and a desired output signal amplitude level; calculating a signal amplitude ratio according to a plurality of output signals of two previous output signal blocks and AGC gains corresponding to the plurality of output signals of the two previous output signal blocks; obtaining a step size according to the signal amplitude difference and the signal amplitude ratio; and calculating an AGC gain of the current input signal according to the step size and a corresponding previous AGC gain.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.

Abstract: A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.