A predistortion system for linearizing the output of a power amplifier includes a first signal representative of an RF modulated signal and a feedback signal representative of nonlinear characteristics of a power amplifier. The system also includes a predistortion controller, comprising at least one lookup table, adapted to receive the first signal and the feedback signal and to generate a correction factor for correcting the nonlinear characteristics of the power amplifier and combining logic which combines the RF modulated signal with a signal corresponding to the correction factor and supplies it to the power amplifier to linearize the output of the power amplifier.

An analog predistorter (APD) core module including a radio frequency delay module, an envelope module, and a contact matrix module. The radio frequency delay module is configured to receive a feed-forward radio frequency signal, generate multiple radio frequency delay signals with different delays according to the feed-forward radio frequency signal, and output each radio frequency delay signal to the contact matrix module. The envelope module is configured to receive the feed-forward radio frequency signal, perform envelope detection on the feed-forward radio frequency signal to obtain multiple envelope signals with different delays, and output each envelope signal to the contact matrix module. The contact matrix module is configured to receive each radio frequency delay signal, each envelope signal, and a predistortion coefficient from an exterior source, and generate a predistortion signal according to the predistortion coefficient, each radio frequency delay signal, and each envelope signal.

Aspects of this disclosure relate to a receiver for digital predistortion (DPD). The receiver includes an analog-to-digital converter (ADC) having a sampling rate that is lower than a signal bandwidth of an output of a circuit having an input that is predistorted by DPD. DPD can be updated based on feedback from the receiver. According to certain embodiments, the receiver can be a narrowband receiver configured to observe sub-bands of the signal bandwidth. In some other embodiments, the receiver can include a sub-Nyquist ADC.

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.

An amplifier may include control circuitry that may track a first input signal parameter and, in response, adjust a value of a second input parameter. Input parameter tracking and adjustment may facilitate control of output parameters for the amplifier. For example, an envelope-tracking amplifier may track input signal amplitude and adjust other input parameters in response. The adjustments may facilitate control of output parameters, such as gain or efficiency. The amplifier may further include calibration circuitry to determine adjustment responses to various tracked input parameters.

A radio apparatus includes an amplifier that amplifies electrical power of a signal that is wirelessly transmitted, and a processor that executes a process including: performing, by using a distortion compensation coefficient that compensates distortion generated in the amplifier, distortion compensation of an input signal; reading, from a predetermined memory, a threshold that varies in accordance with the electrical power of the input signal; and comparing the read threshold with a monitoring target which includes the distortion compensation coefficient used with respect to the input signal to monitor whether an abnormality is present in the distortion compensation of the input signal.

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.

A device configured to perform wireless communication includes: a pre-distortion circuit configured to generate a pre-distorted input signal by performing pre-distortion on an input signal based on a parameter set comprising a plurality of coefficients; a power amplifier configured to generate an output signal by amplifying an RF signal based on the pre-distorted input signal; and a parameter obtaining circuit configured to obtain second memory polynomial modeling information corresponding to an operating frequency band based on first memory polynomial modeling information corresponding to each of a plurality of frequency sections and obtain a parameter set according to an indirect learning structure by using the second memory polynomial modeling information.

A predistortion processing apparatus: an auxiliary feedback module, configured to: extract a nonlinear distortion signal from an analog signal, and input an obtained feedback signal corresponding to the nonlinear distortion signal into an auxiliary model coefficient training module; the auxiliary model coefficient training module, configured to: train an auxiliary coefficient according to the feedback signal and a predistortion signal, and transmit a first auxiliary coefficient obtained through training to a predistortion processing module; a radio frequency signal feedback module, configured to extract a fundamental wave feedback signal; a predistortion model coefficient training module, configured to: train a predistortion coefficient according to the predistortion signal and the fundamental wave feedback signal, and transmit an obtained predistortion coefficient to the predistortion processing module; the predistortion processing module, configured to: perform predistortion processing on an input intermediate frequency signal by performing nonlinear modeling according to the first auxiliary coefficient and the predistortion coefficient.

In an embodiment, an apparatus includes: a modulator to modulate a first signal; a distortion circuit coupled to the modulator to digitally pre-distort the first signal to compensate for a distortion of an amplifier; a distortion characterization circuit coupled to the distortion circuit to determine the distortion of the amplifier and configure the distortion circuit based on the determined distortion; a mixer coupled to the distortion circuit to upconvert the pre-distorted first signal to a pre-distorted radio frequency (RF) signal; and the amplifier coupled to the mixer to amplify the pre-distorted RF signal and output an amplified RF signal.