38results about "Memory effect compensation" patented technology

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.

Systems and methods for compensating a transmit signal for charge trapping effects of a power amplifier are provided. In certain embodiments, a non-linear filter is trained based on time aligning a first set of observations taken from digital transmit data prior to conversion to a radio frequency transmit signal, and a second set of observations taken from an output of a power amplifier that amplifies the radio frequency transmit signal. In certain implementations, the first set of observations and the second set of observations are obtained without decimation. Rather, decimation is provided after timing alignment. By implementing the DPD system in this manner, signal data is not lost by decimation and more accurate timing alignment between the sets of observations is achieved.

A method carried out by an electronic device, according to the embodiments, may comprise a step for identifying a channel bandwidth. The method may comprise the steps of: on the basis of the channel bandwidth and a quantity of resources allocated in the channel bandwidth, identifying one or more active digital pre-distortion (DPD) units among a plurality of DPD units of a DPD circuit; generating a DPD output signal of the DPD circuit on the basis of the one or more active DPD units; and generating an amplifier output signal on the basis of 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 being generated, at least one DPD unit, among the plurality of DPD units of the DPD circuit, which is different from the one or more active DPD units may be deactivated.

A power amplification system (20) has the following features: a power amplifier (11) configured to amplify a first WLAN signal in a first frequency band; a power amplifier (12) configured to amplify a second WLAN signal in a second frequency band higher than the first frequency band; and a (DPD) circuit (311) configured to pre-distort the second WLAN signal without pre-distorting the first WLAN signal.

A digital pre-distortion circuit and technique for a signal being amplified. Digital pre-distortion is performed using a model-based pre-distortion function. Pre-distortion is further corrected using a data-driven pre-distortion function. The model-based pre-distortion function and the data-driven pre-distortion function are trained using training data including a digital loopback signal generated by sampling a loopback signal of an amplifier, the digital pre-distorted signal input to the amplifier for a time period, and an intermediate signal output from the model-based pre-distortion function driven by the digital loopback signal or an output of the data-driven pre-distortion function. Parameters may be continually updated in order to account for changes in characteristics of the amplifier.

A pre-compensation method for a pre-compensation circuit coupled to a power amplifier to compensate for nonlinearity of the power amplifier includes performing pre-distortion according to at least one parameter or at least one hyperparameter to convert a first input signal received by the pre-compensation circuit into a first pre-distortion output signal, updating the at least one parameter or the at least one hyperparameter according to Bayesian Optimization, Causal Bayesian Optimization, or Dynamic Causal Bayesian Optimization, and performing pre-distortion according to the at least one parameter updated or the at least one hyperparameter updated to convert a second input signal received by the pre-compensation circuit into a second pre-distortion output signal.

This electronic device comprises a power amplifier (PA), one or more processors connected to the PA, and a memory for storing instructions. When executed individually or collectively by the one or more processors, the instructions instruct the electronic device to: monitor input data of the PA and output data of the PA; identify a weighted value for a first digital pre-distortion (DPD); identify a hyperparameter for a second DPD on the basis of estimated input data of the PA estimated on the basis of the second DPD based on a neural network (NN) scheme, estimated input data of the PA estimated on the basis of a first DPD, and the input data of the PA; correct, on the basis of the weighted value and the first DPD, first nonlinear data included in the input data of the PA; and correct, on the basis of the hyperparameter and the second DPD, second nonlinear data included in the input data of the PA.

A device may include a first model implemented using a first processing circuit configured to implement a transformation function to generate an initial predistortion signal based on an input signal corresponding to an output of a power amplifier. The device may include a second model implemented using a second processing circuit configured to implement a modification function to modify the initial predistortion signal. A device may include a configurable multiplier configured to weight an output of the second model based at least in part on a weighting value to obtain a weighted output. A device may include a combiner configured to combine the initial predistortion signal that is output by the first model with the weighted output to generate a digital predistortion signal for the power amplifier in communication with the digital predistortion system.

A power amplifier system front end measures both forward and reverse power associated with an RF transmit signal. A processor is configured to use measurements derived from the measured forward and reverse power output to adjust the RF transmit signal in order to compensate for one or more memory effects of the power amplifier system.

Systems, devices, and methods are provided for using model architecture search for hardware configurations. The method includes receiving, by a computer-implemented system, information associated with a pool of processing units, receiving, by the computer-implemented system, a dataset associated with a data transformation operation, training a parameterized model associated with the data transformation operation based on the dataset and the information associated with the pool of processing units, where the training includes updating at least one parameter of the parameterized model associated with configuring at least a subset of the processing units in the pool, and outputting one or more configurations for at least a subset of the processing units in the pool based on the training.

This invention relates to distortion compensation devices and methods, computer-readable storage media, and communication devices. One provided is a distortion compensation device that uses a distortion compensation model to compensate for distortion in a signal to be amplified by an amplifier, wherein internal states affecting distortion characteristics in the amplifier change, and the distortion compensation model includes: a plurality of computational models having corresponding distortion compensation characteristics for the amplifier in different internal states; and a combiner that combines the plurality of computational models with a combination ratio corresponding to the changed internal states.

A device may include a first model implemented using a first processing circuit configured to implement a transformation function to generate an initial predistortion signal based on an input signal corresponding to an output of a power amplifier. The device may include a second model implemented using a second processing circuit configured to implement a modification function to modify the initial predistortion signal. A device may include a configurable multiplier configured to weight an output of the second model based at least in part on a weighting value to obtain a weighted output. A device may include a combiner configured to combine the initial predistortion signal that is output by the first model with the weighted output to generate a digital predistortion signal for the power amplifier in communication with the digital predistortion system.

A power amplification system is provided that includes a power amplifier configured to amplify a first WLAN signal in a first frequency band, a power amplifier configured to amplify a second WLAN signal in a second frequency band higher than the first frequency band, and a circuit configured to pre-distort the second WLAN signal and to not pre-distort the first WLAN signal.

Aspects of this disclosure relate to Neural Volterra actuators. In an embodiment, a Neural Volterra actuator includes a first processing block that includes an artificial neural network, a second processing block that includes non-linear gain blocks, multipliers, a connection circuit configured to adjust an electrical connection to an input of a multiplier of the multipliers, and a combiner that generates a combined output signal based on output signals from the multipliers. The combined output signal can be a digitally predistorted version of an input signal received by the Neural Volterra actuator. Related methods and systems are also disclosed.

The present disclosure is a novel utility of a software defined radio (SDR) based Distributed Antenna System (DAS) that is field reconfigurable and support multi-modulation schemes (modulation-independent), multi-carriers, multi-frequency bands and multi-channels. The present invention enables a high degree of flexibility to manage, control, enhance, facilitate the usage and performance of a distributed wireless network such as Flexible Simulcast, automatic traffic load-balancing, network and radio resource optimization, network calibration, autonomous / assisted commissioning, carrier pooling, automatic frequency selection, frequency carrier placement, traffic monitoring, traffic tagging, pilot beacon, etc. As a result, a DAS in accordance with the present invention can increase the efficiency and traffic capacity of the operators' wireless network.

An apparatus may be configured to receive a signal to be transmitted via an array of antennas by a zero-forcing precoder, wherein the signal is processed by the linear precoder based on one or more input power criteria for power amplifiers of the array of antennas; apply a distortion reducing matrix to the processed signal, wherein the distortion reducing matrix is trained to reduce the distortion at each output of the power amplifiers based on minimizing an error signal corresponding to a difference between measured and calculated outputs of the power amplifiers after a coupling effect between the power amplifiers based on the applied matrices; and provide an output of the distortion reducing matrix to be used in digital pre-distortion processing of an input signal for the power amplifiers.

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.

Embodiments of the present disclosure provide digital predistortion method and digital predistortion apparatus. The digital predistortion method for power amplifier, PA, comprises: in accordance with a predicted traffic condition associated with a future time, determining PA related parameters for the future time; and applying the determined PA related parameters when the future time comes.

A method for determining a plurality of digital predistortion, DPD, models. The method comprising obtaining test data indicating a set of test cases. The method further comprising dividing the set of test cases into subsets of test cases. The method further comprising determining a DPD model for each subset of test cases, thereby determining the plurality of DPD models.

Systems, methods and apparatus for processing signals are described. The method includes determining a predistortion signal corresponding to an input signal by processing the input signal through a multi-stage predistortion model that is based on neural network processing and generating a transmission waveform by processing the predistortion signal through transmission electronics.

The invention relates to a neural worthland system for digital pre-distortion. Aspects of the present disclosure relate to a neural wolfram actuator. In an embodiment, a neural Wollaston actuator comprises: a first processing block comprising an artificial neural network; a second processing block including a nonlinear gain block; a multiplier; a connection circuit configured to adjust an electrical connection to an input of a multiplier of the multipliers; and a combiner that generates a combined output signal based on the output signal from the multiplier. The combined output signal may be a digitally pre-distorted version of the input signal received by the Neural Wollaston actuator. Related methods and systems are also disclosed.

The present disclosure is a novel utility of a software defined radio (SDR) based Distributed Antenna System (DAS) that is field reconfigurable and support multi-modulation schemes (modulation-independent), multi-carriers, multi-frequency bands and multi-channels. The present disclosure enables a high degree of flexibility to manage, control, enhance, facilitate the usage and performance of a distributed wireless network such as flexible simulcast, automatic traffic load-balancing, network and radio resource optimization, network calibration, autonomous / assisted commissioning, carrier pooling, automatic frequency selection, frequency carrier placement, traffic monitoring, traffic tagging, pilot beacon, etc.

There is provided techniques for operating a DPD for a non-linear electronic device. The DPD is using coefficients and basis functions defined by an input signal and tap delays. The method is performed by the DPD. The method comprises receiving the input signal as destined to be input to a non-linear electronic device. The method comprises determining the coefficients and the tap delays for one of the basis functions for the DPD as a function of the input signal. The DPD implements a first control loop configured to determine the tap delays and a second control loop, different from the first control loop, configured to determine the coefficients. The method comprises obtaining an output signal. The output signal is obtained by the DPD pre-distorting the input signal using the determined coefficients and tap delays. The method comprises providing the output signal as input to the non-linear electronic device.

A pre-compensation method for a pre-compensation circuit coupled to a power amplifier to compensate for nonlinearity of the power amplifier includes performing pre-distortion according to at least one parameter or at least one hyperparameter to convert a first input signal received by the pre-compensation circuit into a first pre-distortion output signal, updating the at least one parameter or the at least one hyperparameter according to Bayesian Optimization, Causal Bayesian Optimization, or Dynamic Causal Bayesian Optimization, and performing pre-distortion according to the at least one parameter updated or the at least one hyperparameter updated to convert a second input signal received by the pre-compensation circuit into a second pre-distortion output signal.

A digital pre-distortion achieving near ideal spectral regrowth suppression with a bandlimited loopback. To eliminate mismatch between the bandwidth of the pre-distortion model terms and the bandwidth of the signal used to determine the model a band limiting operation may be applied to both the loopback signal and the input to the power amplifier used for estimating the pre-distortion coefficients. In addition, oversampling may be performed in the digital domain to avoid aliasing in the nonlinear terms of the pre-distortion model.

The present disclosure is a novel utility of a software defined radio (SDR) based Distributed Antenna System (DAS) that is field reconfigurable and support multi-modulation schemes (modulation-independent), multi-carriers, multi-frequency bands and multi-channels. The present invention enables a high degree of flexibility to manage, control, enhance, facilitate the usage and performance of a distributed wireless network such as Flexible Simulcast, automatic traffic load-balancing, network and radio resource optimization, network calibration, autonomous / assisted commissioning, carrier pooling, automatic frequency selection, frequency carrier placement, traffic monitoring, traffic tagging, pilot beacon, etc. As a result, a DAS in accordance with the present invention can increase the efficiency and traffic capacity of the operators' wireless network.

A digital pre-distortion achieving near ideal spectral regrowth suppression with a bandlimited loopback. To eliminate mismatch between the bandwidth of the pre-distortion model terms and the bandwidth of the signal used to determine the model a band limiting operation may be applied to both the loopback signal and the input to the power amplifier used for estimating the pre-distortion coefficients. In addition, oversampling may be performed in the digital domain to avoid aliasing in the nonlinear terms of the pre-distortion model.

An electronic device includes a power amplifier (PA), one or more processors coupled with the PA, and memory storing instructions. The instructions cause the electronic device to monitor input data of the PA and output data of the PA, identify a weight value for a first digital pre-distortion (DPD) scheme, identify a hyperparameter for the second DPD scheme, based on estimated input data of the PA estimated based on a second DPD scheme which is based on a neural network (NN) scheme and estimated input data of the PA estimated based on the first DPD scheme, and the input data of the PA, correct first non-linear data included in the input data of the PA based on the weight value and the first DPD scheme, and correct second non-linear data included in the input data of the PA based on the hyperparameter and the second DPD scheme.

Embodiments of the present disclosure provide digital predistortion method and digital predistortion apparatus. The digital predistortion method for power amplifier, PA, comprises: in accordance with a predicted traffic condition associated with a future time, determining PA related parameters for the future time; and applying the determined PA related parameters when the future time comes.

A system and method are provided for compensating a transmit signal for charge trapping effects in a power amplifier. In a particular embodiment, a nonlinear filter is trained based on time to align a first set of observations obtained from digital transmit data and a second set of observations obtained from an output of a power amplifier that amplifies the radio frequency transmit signal prior to conversion to a radio frequency transmit signal. In a particular implementation, the first set of observations and the second set of observations are obtained without decimation. Rather, decimation is provided after timing alignment. By implementing the DPD system in this manner, no signal data is lost due to decimation and more precise timing alignment between the sets of observations is achieved.