15 results about "Power amplifier linearization" patented technology

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 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.

The present power amplifier linearizing module linearizes operation of a power amplifier and operates in parametrizing mode and operation mode. A processing module executes a feed-forward transfer functions set, which includes at least: a transfer function P and a summing function. The transfer function P derives a change signal ΔVa relative to the control signal component received and the summing function summing the incremental change signal ΔVa to an input signal to generate an adjusted input signal. A transfer function G uses the adjusted input signal to generate an RF signal representative of the amplifying of the adjusted input signal based on the control signal component. The processing module determines a linearizing control signal component based on the generated RF signal representative.

The utility model relates to the technical field of radio frequency and microwave, in particular to a linearization circuit of a power amplifier, which comprises the power amplifier used for amplifying an input signal and providing required output power; the bias circuit is used for providing bias voltage for the power amplifier and controlling the change characteristic of a quiescent operating point of the power amplifier along with the temperature and the power; the active feedback circuit comprises a first connection point P1, a second connection point P2 and a third connection point P3, the active feedback circuit effectively reduces nonlinear distortion of the power amplifier through a negative feedback mechanism, and the nonlinear distortion of the power amplifier is effectively reduced by adjusting a first resistor R5, a second resistor R4, a third resistor R1 and a fourth resistor R3. The feedback circuit can be controlled to work in a critical region of a saturation region and a linear region, so that the linearity of the power amplifier can be optimized.

The invention discloses a power amplifier linearization method based on a KAN network and a digital pre-distortion system, and belongs to the technical field of wireless communication, and the method comprises the steps: introducing Kolmogorov-Arnold Networks (KAN) in a digital pre-distortion processing process, and constructing a real value time delay KAN digital pre-distortion network and a real value time delay KAN digital pre-distortion network; for a real-value time delay KAN digital pre-distortion network, input signals at the current moment and the previous moment are considered in the input process of the network, and the memorability of a power amplifier can be correspondingly compensated; for a vector decomposition time delay KAN digital pre-distortion network, on the basis of a real value time delay KAN digital pre-distortion network, a phase recovery layer and a full connection layer are further introduced, and under the condition that the performance similar to that of a previous KAN model is kept, the complexity of the network can be simplified; compared with an original digital pre-distortion method based on a neural network, the KAN digital pre-distortion method used in the invention uses fewer network parameters and realizes higher linearization capability.

The application discloses a kind of based on KAN network's power amplifier linearization method and digital pre-distortion system, belong to wireless communication technical field, this method in digital pre-distortion processing process, introduced the Kolmogorov-Arnold Networks (KAN), constructs real time delay KAN digital pre-distortion network and real time delay KAN digital pre-distortion network;For real time delay KAN digital pre-distortion network, the input process of this network considers current time and previous time input signal, can correspond to the memory of power amplifier compensation;For vector decomposition time delay KAN digital pre-distortion network, on the basis of real time delay KAN digital pre-distortion network, further introduces phase recovery layer and fully connected layer, in the case where similar performance with previous KAN model is maintained, network complexity can also be simplified again;KAN digital pre-distortion method used in the application compared with original neural network-based digital pre-distortion method, use less network parameter, realize higher linearization capacity.

A wideband power amplifier (PA) linearization technique is proposed. A current interpolation technique is proposed to linearize power amplifiers over a wide bandwidth. The wideband power amplifier linearization technique employs a novel transconductance Gm linearizer using a current interpolation technique that achieves improvement in the third order intermodulation over wide bandwidth for a sub-micron CMOS differential power amplifier. By using a small amount of compensating bias into an opposite phase differential pair, linearization over wide bandwidth is achieved and can be optimized by adjusting the compensating bias.

The invention relates to a power amplifier predistortion method based on a KAN neural network, and belongs to the technical field of radio frequency power amplifier linearization. The problems that a traditional polynomial model is insufficient in precision and a traditional neural network is large in parameter quantity are solved. The technical scheme comprises: collecting and processing input and output signals of a power amplifier; constructing a KAN neural network or a KAN model improved based on a memory polynomial; training the model; and pre-distortion signals are generated and input into the power amplifier. The method has the technical effects that the linearization precision of the power amplifier is remarkably improved, the model complexity is greatly reduced, the training time of the improved model is shortened, the industrial deployment universality is enhanced, and the green communication development is promoted.

Method for identifying individual radiation sources under digital predistortion of power amplifiers. The present invention relates to a method for identifying individual radiation sources. The purpose of the present invention is to solve the problem that existing power amplifier linearization technologies weaken the nonlinear effect of power amplifiers while improving signal quality, resulting in a decline in the performance of individual radiation source identification. The process is as follows: First, obtain a trained digital predistortion trainer; Second, extract multi-domain features from the radiation source signals output by the labeled digital predistortion trainer. The process is as follows: 2.1 Extract contour integral bispectrum features; 2.2 Extract horizontal visibility graph features; 2.3 Extract individual features based on intrinsic time-scale decomposition; Third, obtain a trained SincNet network; Fourth, extract multi-domain features from the radiation source signals to be measured output by the digital predistortion trainer; Fifth, identify the category of the individual signal of the radiation source to be measured after predistortion. The present invention is used in the field of individual radiation source identification.

Circuits and methods for achieving good amplifier AM-AM and AM-PM metrics while achieving good power, PAE, linearity, and EVM performance. Embodiments compensate for a non-linear distortion profile (e.g., an AM-PM and / or AM-AM profile) in an amplifier by pre-processing an input signal, such as a radio-frequency signal, to alter the non-linear distortion profile of the input signal so as to compensate for the non-linear distortion profile imposed by a coupled device, such as an amplifier. An inventive aspect includes linearizing an output from an amplifier having a first non-linear distortion profile, including passing an input signal having a second non-linear distortion profile through a reflective hybrid coupler to a non-linear termination circuit, and reflecting a modified input signal from the non-linear termination circuit back through the reflective hybrid coupler as an output signal, the output signal having a third non-linear distortion profile shaped to compensate for the first non-linear distortion profile.

The present application provides a power amplifier linearization method based on conditional generative adversarial network, which solves the technical problem that the modeling performance of digital pre-distortion model is difficult to improve in the existing power amplifier linearization technology. The method comprises the following steps: obtaining randomly generated input data X(n) and actual output data Y(n) of the power amplifier; constructing a CGAN-DPD model, which includes a nonlinear distortion degree extraction network C net , Generative Adversarial Network; Generative Adversarial Network includes Generator Network G net , Discriminator Network D net ; Train the nonlinear distortion extraction network C net , generator network G net and the discriminator network D net ; Randomly generate a transmission signal and input it into the trained CGAN-DPD model. The input data can obtain a linearized output after passing through a power amplifier. The application is applied to the field of communication technology.

The invention discloses a multistage power amplifier linearization system based on broadband communication, which relates to the technical field of broadband communication and comprises a signal receiving module, an alignment module, a frequency domain analysis module, a behavior modeling module, a coefficient generation module, an updating module and a closed-loop control module. A frequency domain analysis module analyzes the aligned predistortion signal copy and the feedback signal in a frequency domain, and extracts cross-multi-sub-band nonlinear distortion and memory effect features; the behavior modeling module constructs and updates a broadband behavior model according to the model, and represents the overall nonlinearity of the multi-stage amplifier; and the coefficient generation module reversely solves a new predistortion coefficient, and after the new predistortion coefficient is applied by the updating module, closed-loop control continuous iteration is performed to realize dynamic correction. According to the system, broadband distortion is accurately captured through frequency domain cross-sub-band features, compensation is optimized through an overall nonlinear model, and output signal distortion of the multi-stage amplifier is restrained. According to the invention, the output linearity of the multi-stage power amplifier in a broadband communication scene is improved, and the anti-interference and spectrum efficiency of the system are enhanced.

The present application provides an adaptive power amplifier nonlinearity correction system based on an independent architecture, which is composed of a digital processing unit, an analog-to-digital converter, and a first digital-to-analog converter, wherein the digital processing unit is configured with a gated dynamic neural network, which is composed of a gated network and a backbone network; the baseband signal in the communication device forms an initial analog signal after passing through the second digital-to-analog converter of the communication device itself, and the initial analog signal is converted into a digital signal by the analog-to-digital converter and transmitted to the digital processing unit, and data processing is performed through the gated network and the backbone network in the digital processing unit to form a corrected signal, which is then converted into a target analog signal by the first digital-to-analog converter, and the target analog signal is sent to the power amplifier of the communication device. The present application, combined with the gated dynamic neural network, can achieve efficient, flexible and adaptable dynamic configuration, and can meet the requirements of intelligent communication systems for power amplifier linearization performance.

FIELD: radio engineering.SUBSTANCE: device for digital linearization of a power amplifier is proposed, comprising a power amplifier, a linearizer, a digital-to-analogue converter connected to the first output of the linearizer, for converting a digital linearized signal for setting the power amplifier into an analogue signal for adjusting the gain of the power amplifier. A digital frequency synthesizer is introduced, the input of which is connected to the second output of the linearizer, and the output is connected to the input of a power amplifier, to the output of which an attenuator, a signal conversion device that converts a high-frequency signal into a low-frequency analogue signal, and an analogue-to-digital converter, the output of which is connected to the input of the linearizer, are connected in series, and the linearizer records the value corresponding to the specified power at the output of the power amplifier, which is then compared with the current values of the power of the power amplifier, supplied to the linearizer from the output of the analogue-to-digital converter.EFFECT: simplification of the digital linearization device of a power amplifier.3 cl, 2 dwg

The invention belongs to the technical field of data processing of the computer information disciplinary, and relates to a broadband power amplifier linearization method and system based on predistortion, and the method comprises the steps: collecting and preprocessing a radio frequency input baseband signal, an actual output baseband signal and tube core heat flow data of a broadband power amplifier, and obtaining an initial data set; calculating a transient heat dissipation gradient at each sampling moment based on the signal energy difference and the tube core temperature change rate; in combination with broadband distribution characteristics of radio frequency input baseband signals, broadband thermal teratogenesis factors at all sampling moments are obtained; performing dynamic tracking compensation on a cross term coefficient of a generalized memory polynomial based on the distortion factor to obtain an update coefficient; and the pre-distortion signal is reconstructed by utilizing the updating coefficient, so that high-linearity output of the broadband power amplifier is realized. The dynamic response speed of coefficient updating can be improved, thermally induced nonlinear distortion of a power amplifier is effectively offset, and the linearity and stability of a high-power broadband radio frequency test are improved.