A transceiver is disclosed which includes a transmitter and a receiver. The transmitter provides an impairment measurement signal, which is substantially similar to a transmitted communication signal except for a possible difference in phase and/or a magnitude, to the receiver. An envelope detector within the receiver provides an envelope of the impairment measurement signal to the transmitter. The transmitter determines sets of one or more filtering coefficients using the envelope of the impairment measurement signal and adjusts phases or magnitudes and/or phases of a sequences of bits used to generate the transmitted communication signal in accordance with the sets of one or more filtering coefficients to compensate for the unwanted distortion and/or the unwanted interference present within the transmitted communication signal.

An amplification apparatus includes a separator configured to separate an input signal into a first signal and a second signal, a first and second amplifiers amplify the first and second signal, a storage, and a processor coupled to the storage and configured to adjust a phase of the second signal on the basis of a first phase value corresponding to a power value of the input signal or a second phase value set within a period in which the first phase value is updated, calculate a power value of an output signal that is synthesis of an output of the first amplifier and an output of the second amplifier, and update the first phase value to the second phase value after the change of the power value of the calculated output signal when the first phase value is the power value of the input signal.

Embodiments of the present disclosure provide an estimation apparatus and compensation apparatus for clipping distortion of multicarrier signals and a receiver. The estimation apparatus includes: a first calculating unit configured to multiply an error signal of each subcarrier in all or part of subcarriers in received multicarrier signals by a conjugation of an error signal of a subcarrier neighboring or spaced apart from each subcarrier; a second calculating unit configured to calculate an average value of all results of multiplication; a third calculating unit configured to calculate parameters of the clipping distortion of the multicarrier signals according to the average value; and an estimating unit configured to estimate the clipping distortion of the multicarrier signals according to the calculated parameters of the clipping distortion. By calculating the parameters of the clipping distortion of the multicarrier signals according to the error signals of the subcarriers, the clipping distortion of the multicarrier signals may be accurately estimated and compensated, with the method of calculation being simple and the bit error rate being low.

A signal transmission system for a satellite comprises means (31) for producing a signal to be transmitted; a first signal channel (37) which includes a first digital pre-distortion device (32) for applying pre-distortion to the signal; a second signal channel (38) for processing an envelope of the signal, which includes a second digital pre-distortion device (35) for applying pre-distortion to the envelope of the signal; and output means (34) for transmitting the signal.

Example embodiments relate to machine learning based digital pre-distortion for power amplifiers. A device may amplify a signal with a power amplifier and transmit the signal. The signal may be received by an internal feedback receiver of the device. The device may further comprise a first machine learning model configured to emulate an external feedback receiver and to generate an emulated feedback signal based on the internal feedback signal. The device may further comprise a second machine learning model configured to determine digital pre-distortion parameters for the power amplifier based on the emulated feedback signal. Apparatuses, methods, and computer programs are disclosed.

A method for dynamic event detection based on content from a set of social networking systems including receiving content from the set of social networking systems, identifying a plurality of content associated with a geofence, the content that was generated within a predetermined time period, determining feature values from the plurality of content for each of a set of features, determining an event probability for the geofence based on the feature values, and detecting an event within the geofence in response to the event probability exceeding a threshold event probability.

A RF-digital hybrid mode power amplifier system for achieving high efficiency and high linearity in wideband communication systems is disclosed. The present invention is based on the method of adaptive digital predistortion to linearize a power amplifier in the RF domain. The power amplifier characteristics such as variation of linearity and asymmetric distortion of the amplifier output signal are monitored by the narrowband feedback path and controlled by the adaptation algorithm in a digital module. Therefore, the present invention could compensate the nonlinearities as well as memory effects of the power amplifier systems and also improve performances, in terms of power added efficiency, adjacent channel leakage ratio and peak-to-average power ratio. The present disclosure enables a power amplifier system to be field reconfigurable and support multi-modulation schemes (modulation agnostic), multi-carriers and multi-channels. As a result, the digital hybrid mode power amplifier system is particularly suitable for wireless transmission systems, such as base-stations, repeaters, and indoor signal coverage systems, where baseband I-Q signal information is not readily available.

Example embodiments relate to machine learning based digital pre-distortion for power amplifiers. A device may amplify a signal with a power amplifier and transmit the signal. The signal may be received by an internal feedback receiver of the device. The device may further comprise a first machine learning model configured to emulate an external feedback receiver and to generate an emulated feedback signal based on the internal feedback signal. The device may further comprise a second machine learning model configured to determine digital pre-distortion parameters for the power amplifier based on the emulated feedback signal. Apparatuses, methods, and computer programs are disclosed.

Described examples provide for digital communication circuits and systems that implement digital pre-distortion (DPD). In an example, a system includes a DPD circuit configured to compensate an input signal for distortions resulting from an amplifier. The DPD circuit includes an infinite impulse response (IIR) filter configured to implement a transfer function. The IIR filter includes a selection circuit configured to selectively output a selected parameter. The transfer function is based on the selected parameter.

The invention relates to a device for linearising a power amplifier by employing digital predistortion, comprising: a digital predistortion module, configured to infer a polar domain predistortion to be applied to a signal, and comprising a first neural network and a second neural network respectively configured to correct amplitude and phase distortion produced by the amplifier; an optimisation module of each of said neural networks configured to implement meta-learning, using: a meta-initialisation providing a prior initialisation of the initial weights of each of said neural networks; a meta-matching of the initial weights into optimal weights of each of said neural networks.