380 results about "Pre distortion" patented technology

The invention belongs to the technical field of semiconductor testing, and discloses a novel automatic detection system and method for the electrostatic protection performance of a power device. A distributed parasitic parameter network model is constructed by acquiring packaging structure parameters of a to-be-tested power device and physical layout data of a test fixture, key parasitic parameter distribution is identified in combination with a time domain reflection measurement technology, a waveform distortion coefficient is calculated, and a spatio-temporal evolution model of electrostatic pulse propagation is constructed. Based on the model, a compensatory predistortion waveform is generated to counteract the parasitic effect of a transmission path, a device port response signal is collected in real time, an energy dissipation characteristic spectrum is extracted through wavelet packet decomposition, and quantitative evaluation of the electrostatic protection performance is achieved. According to the invention, the test precision and repeatability are improved, and the method is suitable for electrostatic protection tests of various novel power devices, especially high-frequency wide-band gap devices.

The invention provides a communication method and device, which can be applied to the technical field of wireless communication, and can enable a compensation model to be matched with a power amplifier (PA) in actual work, thereby accurately compensating nonlinear distortion of a signal caused by the PA, and not needing to carry out approximate mathematical modeling on the PA. The method comprises: a first device receiving a first signal and first information; wherein the first signal is a signal which is amplified by the first PA through adoption of the first gain, and the first information is used for indicating the first gain. And the first device determines a first compensation model according to the first signal and the first gain. Wherein the first compensation model is used for compensating non-linear distortion, and the non-linear distortion comprises the non-linear distortion on the signal in the process that the first PA adopts the first gain to execute amplification processing. For example, the first compensation model is a digital pre-distortion (DPD) model.

The invention discloses a high-precision power supply output correction method based on a digital pre-distortion technology, and relates to the technical field of power electronics, and the method comprises the steps: integrating an electricity-heat-magnetism real-time combined observer, and inputting parameters including a power supply output voltage, a current, a power device junction temperature, a magnetic element surface temperature, an environment temperature, and an input voltage ripple; using a hierarchical memory depth pre-distortion compensator to generate an anti-phase pre-distortion signal containing long time domain thermal constant compensation and short time domain capacitance energy storage compensation based on modeling engine output; based on a double-ring adaptive updating module, an inner ring updates electrical parameters, including on resistance and dead time, by taking a switching period as a reference, and an outer ring updates thermomagnetic parameters, including thermal resistance and a magnetic core saturation point, in a minute-level period; and the DAC is connected in series with a pre-distortion signal output end through an anti-interference execution channel, and comprises a noise shaping DAC and a driving stage for delay matching. According to the invention, through an electric-thermal-magnetic three-field combined observation architecture, the limitation of traditional single physical field monitoring is broken through.

The invention discloses a digital pre-distortion method, system and device and a storage medium, and relates to the technical field of aerospace communication. The method comprises the following steps: acquiring a first input signal and a first actual output signal of the power amplifier, and acquiring a thermal state characteristic; constructing a three-dimensional dynamic baseline; superposing the detection sequence into the first input signal to obtain a second input signal, obtaining a corresponding second actual output signal, and predicting an ideal output signal of the second input signal; extracting a harmonic component generated after the detection sequence passes through a power amplifier, and determining a distortion early warning moment; recording a third input signal after the distortion early warning moment; constructing a virtual test signal according to the third input signal, and predicting to obtain a reference output signal; and comparing the difference between the distortion output signal and the reference output to obtain a distortion feature vector, constructing a dynamic increment compensation function, and correcting the signal processing flow of the power amplifier based on the dynamic increment compensation function. And the accuracy of digital pre-distortion is improved.

An adaptable, generalized digital predistortion system that can increase the accuracy of the distortion applied to a power amplifier input signal is disclosed. Further, the digital predistortion system can be implemented using a reduced circuit area by reducing a number of coefficients used by the models applied to generate the distortion compensation signal. Further, the system can implement an improved digital predistortion adaptation engine that can improve one or more of the following metrics of a complete radio frequency (RF) analog front-end radio signal chain: error vector magnitude (EVM), adjacent channel leakage ratio (ACLR), spectrum emission mask (SEM), and power consumption of the circuits and systems. An example of circuits and systems is a radio frequency power amplifier (PA).

The invention relates to a digital pre-distortion method and system based on a hierarchical iterative neural network, and belongs to the field of digital pre-distortion of power amplifiers. According to the method, the pre-distortion process is decoupled into two stages of off-line generalization training and on-line specialization optimization. In the offline stage, a mixed data set containing multiple modulation modes and bandwidths is adopted to train an offline neural network, and a basic model with high generalization ability is constructed; in the online stage, aiming at a signal with a specific modulation mode and bandwidth, a single configuration data set is utilized to train an online neural network, and the accurate compensation capability of the model on a real-time input signal is enhanced. In practical application, a baseband signal is firstly subjected to targeted preprocessing through the online neural network, then is subjected to deep optimization through the offline neural network, and finally is input into the power amplifier PA. According to the method, through a generalization-specialization double-layer structure, the dynamic response capability and compensation precision of a digital pre-distortion system to a complex signal environment are remarkably improved.

The invention discloses a broadband noise generation method based on predistortion calibration, and relates to the technical field of communication, and the method comprises the steps: S1, setting a flatness threshold value, and screening out an original noise signal needing to be calibrated; s2, generating an inverse filter coefficient and a filter suppression coefficient for the original noise signal; s3, performing frequency response compensation by using an inverse filter coefficient, performing band-pass filtering by using a filter suppression coefficient, performing down-conversion to a baseband, and reducing a sampling rate; and S4, comparing the processed signal with a flatness threshold value, and if the processed signal does not exceed the flatness threshold value, indicating that signal calibration is completed, otherwise, entering calibration again. By introducing a pre-distortion calibration mechanism, the inverse filter coefficient is calculated in real time to compensate the system frequency response, the spectrum distortion caused by a fixed filter is effectively eliminated, and the method has the advantages of realizing dynamic and adaptive filter adjustment, effectively reducing the manual participation frequency and improving the continuous operation capability and the test efficiency of the system.

The invention belongs to the field of quantum computing, and particularly relates to a distortion correction optimization method and device for a quantum measurement and control link, and the method comprises the steps: applying a frequency control signal for loading a target pre-distortion waveform on a to-be-corrected quantum measurement and control Z link; setting a first logic gate for quantum state operation on an XY control line of the selected quantum bit; obtaining the fidelity of the quantum state output by the selected quantum bit; in response to the fact that the fidelity does not reach the preset standard, updating the pre-distortion waveform, and returning to execute a frequency control signal for applying and loading the target pre-distortion waveform signal on the quantum measurement and control Z link to be corrected; and setting a first logic gate for quantum state operation on an XY control line of the selected quantum bit until the fidelity reaches a preset standard. According to the invention, distortion correction can be rapidly and effectively carried out.

The invention provides a data acquisition method and device, and the method comprises the steps: carrying out the dynamic noise suppression of analog input signals of four input channels, and obtaining a primary purification signal; performing multi-stage nonlinear compensation on the primary purification signal based on a preset sensor type feature library to generate a standardized linear signal; performing time domain-space domain joint reconstruction on the standardized linear signal, and outputting a high-fidelity reconstruction signal; obtaining a parameter configuration library of a preset industrial scene mode, performing digital pre-distortion compensation on the high-fidelity reconstruction signal according to the parameter configuration library, and generating a scene adaptation signal; and performing edge feature extraction and data compression on the scene adaptation signal to generate an industrial data packet, and uploading the industrial data packet to the two output channels through a preset communication protocol.

The invention discloses a data full-link dynamic anti-interference optimization transmission method. The method comprises the following steps: S1, constructing a data transmission system architecture comprising a sending end, a transmission link and a receiving end; the sending end detects environment disturbance characteristics in real time, and the receiving end collects receiving signals containing background noise and link distortion; s2, designing a self-adaptive waveform coding strategy at a sending end; s3, performing active channel compensation on a transmission link; channel characteristics are extracted, and channel interference is counteracted in real time through pre-distortion waveform adjustment; s4, deploying an intelligent noise reduction decoding algorithm at a receiving end; a depth feature separation network is constructed, and link residual interference is filtered out by analyzing the time-frequency domain difference between a target signal and a noise component. Through a three-level anti-interference mechanism of adaptive coding of the sending end, active compensation of a transmission link and intelligent noise reduction of the receiving end, the problem that the transmission reliability of signals is reduced due to environment disturbance, channel distortion and noise pollution in a complex environment is solved.

The invention relates to the technical field of data processing, and discloses a digital feedback dynamic adjustment method and system for a neutron generator control signal, and the method comprises the steps: calling a reconfigurable waveform parameter set corresponding to a target neutron from a mapping relation according to the yield and beam spot characteristic demands of the target neutron; generating a basic high-frequency pulse sequence of the neutron tube, and performing pre-distortion filtering on the basic high-frequency pulse sequence to obtain a high-frequency pulse sequence of the neutron tube; collecting an anode current and a target voltage signal of the neutron tube applied with the high-frequency pulse sequence during operation, and converting the anode current and the target voltage signal into a digital feedback current; comparing the digital feedback flow with a reference waveform in the reconfigurable waveform parameter set in real time to obtain an error correction amount of the high-frequency pulse sequence; dynamically adjusting the high-frequency pulse sequence according to the error correction; applying the dynamically adjusted high-frequency pulse sequence to a corresponding electrode in a neutron tube through power; the neutron tube control signal processing efficiency can be improved.

One or more aspects of the techniques and models described herein provide for bidirectional recurrent neural network (BiRNN)-based digital pre-distortion techniques for radio frequency (RF) power amplifiers (PAs). As an example, a digital pre-distorter (DPD) system may implement residual learning and long short-term memory (LSTM) projection layer features to reduce computational complexity and memory requirements. Implementing the described unconventional techniques of applying residual learning in RNN (e.g., in BiLSTM), using LSTM projection to develop a DPD structure, or both, may provide several advantages over preexisting techniques. For instance, the complexity in training and pre-distortion may be reduced and significantly less memory may be required to store the DPD neural network coefficients (e.g., while achieving similar or better linearization performance compared to other LSTM models). Further, faster training convergence speed may be achieved (e.g., compared to other LSTM models).

The invention relates to a voltage-mode high-speed transmitter fusing digital pre-distortion and serial driving. The voltage-mode high-speed transmitter comprises a time sequence control unit, a digital signal generation unit, a voltage modulation unit and an output matching unit, the digital signal generation unit is used for generating a pre-modulated digital signal in response to the first clock signal sent by the time sequence control unit; the voltage modulation unit is used for responding to a second clock signal sent by the time sequence control unit and sequentially performing low-speed serialization processing, retiming processing, differential processing and high-speed serialization-output driving processing on the pre-modulated digital signal to obtain a first high-speed level differential signal and a second high-speed level differential signal; and the output matching unit is used for performing impedance matching processing on the first high-speed level differential signal and the second high-speed level differential signal and outputting a corresponding first differential signal and a corresponding second differential signal. The device can be applied to high-order modulation and high-rate application scenes.

The invention discloses a power amplifier linearization thermal compensation method based on reinforcement learning, and the method comprises the steps: constructing a digital pre-distortion model, and obtaining a data set with a temperature label; building a neural network model based on reinforcement learning; constructing a state space and an action space of the neural network model, introducing the temperature into the state space and the action space, and adjusting a pre-distortion signal output by the digital pre-distortion model; defining parameters related to training of a neural network model, inputting the data set into the neural network model for training, and obtaining a loss function convergence reinforcement learning network model; and the reinforcement learning network model is cascaded with the digital pre-distortion model and the power amplifier, so that a temperature self-adaptive power amplifier linearization function is realized. By sensing the environment temperature and adjusting the pre-distortion signal output by the digital pre-distortion model, the pre-distortion signal can be matched with the behavior characteristics of the power amplifier more accurately, and the linearization performance of the pre-distorter is ensured.

The invention discloses a broadband digital pre-distortion method and system based on an external attention mechanism, and the method comprises the steps: constructing an external attention intensive gated loop network model which comprises a feature extraction layer, an input layer, a GRU layer, a hidden full-connection layer, an external attention layer and an output full-connection layer; based on the baseband IQ signal after feature extraction and preprocessing and an IQ signal output by a power amplifier, constructing input data of an external attention intensive gated loop network model; training an external attention intensive gating loop network model; and inputting data to the trained external attention intensive gated loop network model to obtain a predicted value output by the network model to the power amplifier. The invention provides a novel broadband digital pre-distortion architecture of an external attention intensive gated loop network. An external attention mechanism is combined with an intensive connection layer, so that the network better compensates the nonlinear characteristic of a power amplifier.

Apparatus for causing a power amplifier (PA) to act as an idealized power amplifier (iPA). The apparatus comprises: a fixed digital predistortion (DPD) circuit; a PA coupled to the DPD circuit; at least one sensor adapted to determine at least one condition related to of the power amplifier; and a neural network adapted control a level of amplification provided by the power amplifier based on a measurement of the at least one condition as measured by the at least one sensor.

The invention discloses an adaptive power amplifier linearization method and device based on deep learning. The method comprises the following steps: acquiring a to-be-processed input signal; processing the input signal to be processed by adopting a trained hybrid network model to obtain a processed pre-distortion signal; wherein the trained hybrid network model takes data of a preset category as a training data set, samples in the training data set are selected, the selected samples and the unselected samples are endowed with different weights, the initial hybrid network model is trained, and in different stages of training, the selected samples and the unselected samples are subjected to different weights. Dynamically adjusting the weight of the samples in the training data set, wherein the data of the preset category comprises an input signal, an envelope related item, a lead item and a time delay item of the input signal, and a lead item and a time delay item of the envelope related item; and inputting the processed pre-distortion signal to a power amplifier for amplification to obtain a linearized output signal. The linearity of the power amplifier can be improved.

Methods, systems, and apparatus for microwave pulse distortion compensation using reflection parameters from error amplification pulse sequences. In one aspect, a method includes generating a pre-distorted control signal that implements a single qubit rotation operation and applying the pre-distorted control signal to a qubit to perform the rotation operation on the qubit. The pre-distorted control signal comprises an inverted transfer function, where the inverted transfer function comprises values of parameters obtained through fitting measured qubit parasitic rotation angles per gate to a reflection model that models pulse distortion in the quantum computing device; and the qubit parasitic rotation angles per gate are measured using a first pulse sequence that amplifies out-of-phase pulse distortion in the quantum computing device and a second pulse sequence that amplifies in-phase pulse distortion in the quantum computing device.

Certain aspects of the present disclosure provide techniques for pre-distortion training feedback via inductive coupling. An example apparatus includes a receive path; a transmit path comprising an amplifier having a first output that is inductively coupled to the receive path; a memory; and a processor coupled to the memory. The processor is configured to cause the apparatus to obtain a first signal, based on a second signal output by the amplifier, via the receive path being inductively coupled to the first output of the amplifier; determine a parameter for pre-distortion associated with the amplifier based at least in part on the first signal; pre-distort a third signal based at least in part on the parameter; amplify the pre-distorted third signal via the amplifier; and transmit the amplified third signal.

The invention relates to a digital pre-distortion high-precision phase interpolator with a constant input load. The digital pre-distortion high-precision phase interpolator comprises a multi-phase clock generation circuit, an input buffer circuit, two pre-filter circuits, a phase interpolation core circuit, a CML2CMOS circuit and a control code decoder circuit. The two pre-filter circuits are used for converting the two full-swing square wave signals into two sine clocks; and the phase interpolation core circuit is used for carrying out nonlinear interpolation on the two paths of sine clocks according to the two paths of weight control codes by using a constant input load, and outputting a small-swing signal. According to the phase interpolator, the interpolation precision is greatly improved, digital pre-distortion of the interpolation weight can be realized by adjusting the control code decoder, the precision of the phase interpolator is further improved, a high-speed and high-precision output clock is realized, and the phase interpolator is suitable for clock generation modules such as a clock data recovery circuit and a phase-locked loop in a high-speed SerDes system.

Methods and systems for NN-based digital pre-distortion for digital envelope tracking power amplifiers. A computer-implemented method includes receiving a measure of a digital envelope at a digital pre-distortion module having a neural network (NN)-based digital pre-distortion structure for digital envelope tracking (DET), receiving a transmit signal at the digital pre-distortion module, inputting the measure of the digital envelope and the transmit signal into the NN-based digital pre-distortion structure to produce a pre-distorted transmit signal, adjusting nonlinearity compensation of a power amplifier based on the measure of the digital envelope, and using the adjusted nonlinearity compensation of the power amplifier to produce an output signal.

The invention relates to the field of intelligent frequency spectrum control, and particularly discloses a frequency spectrum control method for a pulse modulation waveform of an all-solid-state transmitter, which comprises the following steps: generating an ideal waveform, performing pre-distortion processing, and performing depth and fine-grained semantic feature comparison on an actual output frequency spectrum of a power amplifier and a target frequency spectrum template; a spectrum sensing and difference reasoning method is adopted, spectrum deviation is accurately quantified, and a spectrum leakage index with rich information is formed. Based on the index, the system dynamically optimizes the DPD coefficient and adjusts the output frequency spectrum in a closed loop mode, precise suppression of frequency spectrum leakage is achieved, it is ensured that signals strictly meet the requirement of a frequency spectrum template, and therefore the performance and compatibility of a transmitter are remarkably improved.

The invention belongs to the technical field of magnetic variable measurement, and particularly relates to a power driving compensation method and system for magnetostrictive load characteristic monitoring, and the method comprises the steps: obtaining a reference zero point of magnetic performance evolution in a cold state environment of an electromagnetic system according to the center frequency of the electromagnetic system; calculating a current main frequency impedance module value and a phase difference through an electrical parameter characterization method, and obtaining a thermal drift index reflecting a hysteresis loop distortion degree in combination with a reference zero point; obtaining correction factors of all orders based on the thermal drift index and the average output power at the current moment, and dynamically updating a coefficient vector of the inverse model; and constructing a pre-distortion driving voltage signal capable of counteracting nonlinear interference by using the new coefficient and the ideal guided wave voltage sequence, and inputting the pre-distortion driving voltage signal to a power amplifier to drive the magnetostrictive transducer. According to the invention, the problem of predistortion failure under a variable-temperature working condition in the prior art is solved, and the signal-to-noise ratio of high-power long-distance guided wave detection is remarkably improved.

Systems and techniques are provided for power amplifier gain error compensation for a Digital Power Amplifier (DPA). In some aspects, a compensation method includes obtaining in-phase (I) and quadrature-phase (Q) components of a baseband sample corresponding to in-phase input amplitude codes and quadrature-phase input amplitude codes. The in-phase input amplitude codes can be distorted based on first gain pre-compensation information corresponding to an in-phase signal branch of the DPA, to generate pre-distorted output amplitude codes of the I component. The quadrature-phase input amplitude codes can be distorted based on second gain pre-compensation information corresponding to a quadrature-phase signal branch of the DPA, to generate pre-distorted output amplitude codes of the Q component. The DPA can be driven using the pre-distorted output amplitude codes of the I and Q components to generate a Radio Frequency (RF) output.

Aspects relate to signaling relating to a non-linearity model for power amplifier circuitry of a transmitting device. The power amplifier circuitry may apply digital pre-distortion (DPD) to a signal prior to amplification and transmission of the signal. A receiving device may apply digital post-distortion (DPoD) to a signal received from the transmitting device where the DPoD is based on the non-linearity model. The transmitting device may send to the receiving device non-linearity parameters for the non-linearity model.

The invention discloses a power amplifier digital pre-distortion optimization method based on a complex convolutional neural network, and the method comprises the following steps: S1, collecting a plurality of groups of digital signals before and after passing through a power amplifier PA, and forming a sample set; s2, preprocessing the data in the sample set; s3, constructing a complex number time delay convolutional neural network containing a linear auxiliary branch and a nonlinear model as a digital pre-distortion model of the power amplifier; s4, training the digital pre-distortion model of the power amplifier by using the preprocessed data in the sample set to obtain maturely trained digital pre-distortion model parameters; and S5, when the digital pre-distortion of the power amplifier is actually carried out, sending a to-be-sent digital signal to the maturely trained digital pre-distortion model for processing. According to the method, the linearization capability is remarkably improved by introducing complex field processing and auxiliary linear branches while the low complexity characteristic is kept.

The invention discloses a high-linearity low-noise amplifier based on harmonic suppression, relates to the field of communication and the technical field of electronic devices, and is used for solving the problem that the noise coefficient of an existing Darlington structure is large. Comprising a noise matching and input matching network, a linearity enhancement structure, a negative feedback structure and a pre-distortion structure. Wherein the linearity enhancement structure at least comprises a first amplification transistor and a second amplification transistor which are arranged in parallel, and is used for improving the linearity of the circuit through harmonic cancellation; the negative feedback structure is connected with the noise matching and input matching network and the pre-distortion structure and is used for expanding circuit bandwidth and optimizing output matching; the pre-distortion structure is used for stabilizing the bias voltage of the third amplification transistor. According to the invention, the linearity of the whole circuit is effectively improved, and the source microstrip lines of the two circuits are utilized to improve the minimum noise matching and improve the noise performance. Noise is reduced, linearity is improved, low-frequency gain is suppressed, and bandwidth of the whole circuit is improved.

According to embodiments, a method performed by an electronic device includes: identifying a channel bandwidth; identifying one or more active DPD units among a plurality of DPD units of a digital pre-distortion (DPD) circuit based on the channel bandwidth and amount of resource allocated within the channel bandwidth; generating a DPD output signal of the DPD circuit based on the one or more active DPD units; generating an amplifier output signal based on the DPD output signal of the DPD circuit, a digital-to-analog converter (DAC), and a power amplifier (PA). While the DPD output signal is generated, at least one DPD unit different from the one or more active DPD units among the plurality of DPD units of the DPD circuit is deactivated.

The invention belongs to the field of quantum computing, and particularly relates to a distortion correction optimization method and device for a quantum measurement and control link. The method comprises the following steps: determining a digital filter for distortion correction or a pre-distortion waveform output by the digital filter and used for compensating distortion based on a target parameter value of a target system function fusing quantum measurement and control link signal response characteristics; acquiring an output signal of the quantum measurement and control link provided with the digital filter; and in response to the condition that the output signal does not reach the preset standard, updating the target parameter value or the pre-distortion waveform, and returning to execute the step of acquiring the output signal of the quantum measurement and control link provided with the digital filter until the output signal reaches the preset standard. According to the invention, distortion correction of the quantum measurement and control link can be effectively realized.

The invention discloses a pre-distortion calibration method and system based on a single chip microcomputer, a medium and a product, and relates to the field of radio frequency front ends. The method comprises the following steps: extracting an instantaneous amplitude value of an input signal sequence to obtain a first envelope to represent instantaneous nonlinearity; the periodic average power of the input signal is calculated and filtered through timer interruption, and a second envelope representing the heat effect is obtained. According to the method, the first envelope and the second envelope serve as double indexes, the preset two-dimensional lookup table is inquired, so that the pre-distortion calibration coefficient capable of being matched with the instantaneous nonlinearity and the thermal memory effect of the power amplifier at the same time is determined, and the input signal is calibrated. In addition, a feedback signal output by the power amplifier is obtained to calculate a distortion calibration error, and the two-dimensional lookup table is adaptively updated according to the error. According to the scheme, a composite calibration model is constructed on a low-cost single-chip microcomputer platform, and the accuracy and stability of nonlinear pre-distortion calibration of the power amplifier are guaranteed.