Systems and methods are disclosed herein for providing efficient Digital Predistortion (DPD). In some embodiments, a system comprises a DPD system comprising a DPD actuator. The DPD actuator comprises a Look-Up Table (LUT), selection circuitry, and an approximate multiplication function. Each LUT entry comprises information that represents a first set of values {p.sub.1, p.sub.2, . . . , p.sub.k} and a second set of values {s.sub.1, s.sub.2, . . . , s.sub.k} that represent a LUT value of s.sub.1.Math.2.sup.p.sup.1+s.sub.2.Math.2.sup.p.sup.2+ . . . +s.sub.k.Math.2.sup.p.sup.k where each value s.sub.iϵ{+1,−1} where k≥2. The selection circuitry is operable to, for each input sample of an input signal, select a LUT entry based on a value derived from the input sample that is indicative of a power of the input signal. The approximate multiplication function comprises shifting and combining circuitry that operates to, for each input sample, shift and combine bits that form a binary representation of the input sample in accordance with {p.sub.1, p.sub.2, . . . , p.sub.k} and {s.sub.1, s.sub.2, . . . , s.sub.k} to provide an output sample.

Envelope tracking power supply circuitry includes a look up table (LUT) configured to provide a target supply voltage based on a power envelope measurement. The target supply voltage is dynamically adjusted based on a delay between the power envelope of an RF signal and a provided envelope tracking supply voltage. The envelope tracking supply voltage is generated from the adjusted target supply voltage in order to synchronize the envelope tracking supply voltage with the power envelope of the RF signal.

Systems and methods for compensating for non-linearity of a non-linear subsystem using predistortion are disclosed. In one embodiment, a system includes a non-linear subsystem and a predistorter configured to effect predistortion of an input signal of the non-linear subsystem such that the predistortion compensates for a non-linear characteristic of the non-linear subsystem. In addition, the system includes a narrowband filter that filters a feedback signal that is representative of an output signal of the non-linear subsystem to provide a filtered feedback signal, and an adaptor that adaptively configures the predistorter based on the filtered feedback signal and a reference signal that is representative of an input signal of the non-linear subsystem. By utilizing the filtered feedback signal, rather than the feedback signal, a complexity, and therefore, cost of the adaptor is substantially reduced.

A circuit includes a reference voltage circuit, a filter circuit configured to receive an output of the reference voltage circuit, and a voltage follower configured to receive an output of the filter circuit and generate a bias voltage. The filter circuit is configured to combine signals on a reference ground with the output of the reference voltage circuit. A method of providing a bias voltage includes generating a reference voltage using a reference voltage circuit, filtering the reference voltage to generate a second voltage using a filter circuit, and generating the bias voltage according to the second voltage using a voltage follower circuit. Filtering the reference voltage includes combining a fluctuation of the reference ground with the reference voltage.

The non-linear behavior of power amplifier is linearized using a pre-distorter that is adaptive to changes in the behavior of the power amplifier and uses an artificial neural network. According to embodiments presented here, the pre-distorter's artificial neural network is model-trained from time to time to learn the inverse of the transfer function of the power amplifier by using a second pre-distorter modeling system. The second modeling system determines the parameters of the inverse of the transfer function of the power amplifier using a least square method by using the (un-distorted) output signal samples of the power amplifier. Using the output of the second system as output to train the neural network enables the neural network to more successfully linearize the power amplifier's behavior. Furthermore, the trained artificial neural network as the pre-distorter can be implemented in hardware and presents a small form factor.

Systems and methods are disclosed herein for providing efficient Digital Predistortion (DPD). In some embodiments, a system comprises a DPD system comprising a DPD actuator. The DPD actuator comprises a Look-Up Table (LUT), selection circuitry, and an approximate multiplication function. Each LUT entry comprises information that represents a first set of values {p.sub.1, p.sub.2, . . . , p.sub.k} and a second set of values {s.sub.1, s.sub.2, . . . , s.sub.k} that represent a LUT value of s.sub.1.Math.2.sup.p.sup.1+s.sub.2.Math.2.sup.p.sup.2+ . . . +s.sub.k.Math.2.sup.p.sup.k where each value s.sub.i ∈{+1 , −1} where k≥2. The selection circuitry is operable to, for each input sample of an input signal, select a LUT entry based on a value derived from the input sample that is indicative of a power of the input signal. The approximate multiplication function comprises shifting and combining circuitry that operates to, for each input sample, shift and combine bits that form a binary representation of the input sample in accordance with {p.sub.1, p.sub.2, . . . , p.sub.k} and {s.sub.1, s.sub.2, . . . , s.sub.k} to provide an output sample.

A method for modelling a power amplifier, including memory effect modelling, for general input waveforms and power levels involves generating an extraction waveform having a plurality of tones each having a different frequency, a difference between the frequencies of two adjacent tones of the plurality of tones not being an integer multiple of a difference in frequency between any two other adjacent tones of the plurality of tones. The method further involves providing the extraction waveform to the power amplifier, receiving output from the power amplifier generated in response to the extraction waveform, and generating a model of the power amplifier based on the output.

A distortion compensation device includes: a first distortion compensation circuit having a first distortion compensation characteristic for compensating for a first distortion occurring in an output of an amplifier, the first distortion compensation circuit being configured to compensate for the first distortion; a second distortion compensation circuit having a second distortion compensation characteristic for compensating for a second distortion occurring in the output of the amplifier, the second distortion compensation circuit being configured to compensate for the second distortion; and an update unit configured to update the second distortion compensation characteristic. The first distortion includes a non-linear distortion and a memory effect distortion, the second distortion is a distortion whose temporal change is quicker than the first distortion, and the update unit updates the second distortion compensation characteristic at a higher frequency than an update frequency of the first distortion compensation characteristic.

A method for modelling a power amplifier, including memory effect modelling, for general input waveforms and power levels involves generating an extraction waveform having a plurality of tones each having a different frequency, a difference between the frequencies of two adjacent tones of the plurality of tones not being an integer multiple of a difference in frequency between any two other adjacent tones of the plurality of tones. The method further involves providing the extraction waveform to the power amplifier, receiving output from the power amplifier generated in response to the extraction waveform, and generating a model of the power amplifier based on the output.

Systems and methods are disclosed herein that provide low-complexity Digital Predistortion (DPD) for a transceiver system that uses an Advanced Antenna System (AAS) to provide analog or hybrid beamforming.