31 results about "Amplifier nonlinearity" patented technology

The invention discloses a power adaptive digital pre-distortion method, system and device based on sparse GRU and a medium. The method comprises the steps that input and output signals under different powers are collected, a composite feature vector is constructed through amplitude normalization and phase alignment, and a pre-distortion training target is generated in combination with indirect learning; constructing a sparse GRU neural network, introducing L1 regularization constraint, and obtaining a sparse pre-distortion model through joint optimization of mean square error and sparse constraint; partial weight updating is realized based on power grading, and weight fusion output is carried out during power interval switching so as to complete power adaptive optimization; pruning and compressing the sparse GRU model and then deploying the sparse GRU model in a pre-distortion module to compensate the nonlinearity of the power amplifier; according to the method, the model complexity is reduced through rarefaction, the dynamic working condition stability is improved through a power adaptive mechanism, pruning compression adapts to low-power-consumption hardware, high precision, low complexity and adaptive capacity are considered, and the method is suitable for the low-power-consumption and high-performance requirements of a broadband wireless communication 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 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.

A communication device comprises: a digital predistortion (DPD) circuit; a digital-to-analog converter (DAC) configured to convert output signals of the DPD circuit into analog signals; a power amplifier configured to amplify the analog signals; and an antenna configured to transmit the amplified analog signals, wherein the DPD circuit may be configured to: generate first predistortion signals by performing a convolution operation on digital signals of a reference time unit over a time interval including a first set of time units before the reference time unit and a second set of time units after the reference time unit; generate second predistortion signals by performing predistortion on the digital signals; and generate the output signals of the DPD circuit on the basis of the first predistortion signals and the second predistortion signals.

The invention discloses a multi-satellite large-scale MIMO (Multiple Input Multiple Output) downlink precoding method and a multi-satellite large-scale MIMO downlink precoding system considering power amplifier nonlinearity. According to the method, different time delays and Doppler frequency shifts of different satellite signals arriving at a user terminal are considered, and pre-compensation is carried out on each satellite sending signal; the input and output characteristics of the satellite side nonlinear power amplifier are modeled by using the polynomial model; establishing an optimization problem to jointly design a precoding vector and a receiving vector; the signal interference noise distortion ratio in the optimization problem considers interference and distortion from other satellites, interference and distortion in the satellite and a noise item; and converting a sum rate maximization problem into a weighted mean square error minimization problem for solving. And a traditional iteration updating step is further mapped into a learnable network layer structure through a deep expansion algorithm, so that the calculation complexity is reduced. Compared with the traditional method, the method provided by the invention is more in line with the actual transmission condition, can improve the system performance and reduce the online calculation overhead, and is suitable for the precoding design in a multi-satellite communication scene.

This invention discloses a pre-equalization compensation method for a terminal in a TDD-OFDM direct conversion system with known transmitter IQI and nonlinear parameters. The method includes: the base station cyclically sending P different training sequences to the terminal; the terminal using a sliding window least squares-based channel state information tracking algorithm to track and estimate the channel state information, where δ is a threshold representing the correlation of the channel within adjacent symbol periods; and pre-equalization compensation performed directly at the terminal. Using the pre-equalization compensation algorithm, a modified data sequence can be obtained and sent to the base station. This invention considers three factors in wireless communication systems: I-path and Q-path imbalance caused by the non-ideal nature of analog components in RF transceivers, power amplifier nonlinearity, and multipath channels. It enables distributed processing within the cell, effectively reducing the demodulation burden on the base station and has wider applicability than traditional compensation methods.

A method for wireless communication by a user equipment (UE) includes transmitting, to a network node, a first message indicating a capability of the UE to transmit a multiplexed low peak-to-average power ratio (PAPR) demodulation reference signal (DM-RS) and a high PAPR reference signal (RS) within a single slot. The method also includes multiplexing, associated with the capability, the low PAPR DM-RS with the high PAPR RS within the single slot. The method further includes transmitting, to the network node, the multiplexed low PAPR DM-RS and high PAPR RS within the single slot.

This invention belongs to the field of wireless communication and signal processing technology, and relates to a digital predistortion method, system, and application for power amplifiers in shortwave communication systems. This invention can cover the wide dynamic range of the power amplifier's operating range in shortwave communication systems, maintaining excellent linearization compensation across the entire power range. It effectively improves modulation signal distortion, spectral broadening, and adjacent channel interference, significantly reducing the system bit error rate and improving the quality of the transmitted signal, thus meeting the requirements for spectral and linearity specifications. This invention eliminates the need for multiple predistortion models and complex switching logic, greatly reducing system implementation complexity and storage resource overhead. When power levels switch or the signal envelope changes rapidly, it avoids additional distortion introduced by abrupt changes in predistortion parameters, ensuring continuous and stable linearization. Furthermore, this invention supports online adaptive updates, enabling real-time adaptation to changes in the nonlinear characteristics of the power amplifier, improving system robustness and environmental adaptability.

The application discloses a gradient field nonlinearity compensation method and system in a low-field magnetic resonance imaging system, and belongs to the technical field of magnetic resonance imaging. The application aims at the gradient field distortion problem caused by the nonlinearity of a gradient power amplifier and the thermal memory effect in a low-field magnetic resonance system, and provides a real-time dynamic compensation scheme integrating feedforward calibration and thermal effect modeling. The application calibrates the nonlinearity error of a gradient current through a pre-scan sequence, generates an initial feedforward lookup table, establishes a thermal model representing the thermal dynamic behavior of the gradient power amplifier, dynamically corrects the feedforward table according to the influence factor of the thermal memory effect estimated in real time according to historical workloads, and iteratively corrects the feedforward table and the thermal model through adaptive filtering technology. The application greatly reduces the computing power requirement of the compensation algorithm, can track the dynamic thermal drift of the gradient field in real time, solves the gradient field nonlinearity problem from the signal source, and significantly improves the geometric fidelity of a low-field magnetic resonance image.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network entity, a reference signal. The UE may transmit, to the network entity and via a feedback channel, digital pre-distortion (DPD) information that is based at least in part on the reference signal, wherein the DPD information indicates an estimate of non-linearities of a power amplifier at the network entity based at least in part on the reference signal. Numerous other aspects are described.

The application discloses an anti-power amplifier nonlinearity original AI communication system, which comprises a transmitting end, a channel and a receiving end, wherein the transmitting end comprises a trained learnable back-off mapper LBOM, which maps an input coded bit stream into a power back-off symbol stream; the LBOM performs joint optimization on constellation distribution and input power back-off parameters through training; the channel transmits the sending symbol distorted by the power amplifier nonlinearity; when the computing power of the receiving end is limited, the receiving end adopts a neural network demapper ND to demap the symbol and signal-to-noise ratio information output by the channel into a log likelihood ratio, and information bits are obtained through BP decoding; when the computing power of the receiving end is sufficient, the receiving end adopts an IDD module to receive the symbol and signal-to-noise ratio information output by the channel, and joint iterative decoding is realized through mutual transmission of extrinsic information between submodules to obtain information bits; the IDD module comprises a neural network demapper iDemapper submodule and a BP decoder iDecoder submodule.

This application discloses a digital predistortion (DPD) implementation method, system, device, and storage medium, relating to the field of radio frequency communication technology. The method includes: when the soft core receives a calibration start command, it first sends a sinusoidal calibration signal to the FPGA platform, triggering its initial calibration of the transmission link; after receiving a calibration confirmation signal from the FPGA, the soft core reads the pre-stored initial training modulation signal from its internal memory and sends it to the FPGA platform as transmission data; subsequently, it reads the feedback data after nonlinear distortion by the power amplifier from the FPGA via a high-speed bus; based on this feedback data and the initial training signal, the soft core iteratively updates the digital predistortion compensation parameters and updates the transmission data; the FPGA performs stable compensation on the power amplifier (PA) based on the updated transmission data. This method, through the collaboration of the FPGA and the soft core, tightly couples calibration, acquisition, caching, and updating, utilizes on-chip high-speed storage to avoid external memory access, and combines pipelined processing to significantly improve DPD accuracy, iteration efficiency, and resource utilization.

Apparatuses and methods for negotiation and signaling for cooperative control of power amplifier nonlinearity are disclosed. At least some example embodiments may allow signaling to support the design and deployment of cooperative control of power amplifier nonlinearity for digital pre-distortion (DPD) applications in user equipment and digital post-distortion (DPoD) applications in network nodes, where digital pre-distortion may be used to control out-of-band transmissions (e.g., adjacent channel leakage ratio (ACLR)), and digital post-distortion (DPoD) applications in network nodes. And digital post-distortion may be used to control in-band transmission (e.g., error vector magnitude (EVM)).

Aiming at the problem of signal nonlinear distortion caused by nonlinear characteristics of a power amplifier in satellite communication, the invention provides a generalized linear dual-mode switching blind equalization algorithm based on a third-order truncated Volterra structure, and the technical scheme and the application effect are expanded according to the following steps S1 to S3: S1: initializing parameters of a generalized linear blind equalizer based on the third-order Volterra structure; s2, taking a modified constant modulus algorithm and a decision-oriented least mean square algorithm in the linear blind equalization field as theoretical basis, combining signal processing characteristics of a third-order truncated Volterra nonlinear model, deriving to obtain two generalized linear equalizer tap updating formulas suitable for the nonlinear model, and providing algorithm support for a dual-mode equalization mechanism; s3, adopting a staged adaptive equalization strategy to construct a switching mechanism: in an equalization initial stage, using a generalized linear correction constant modulus algorithm of a nonlinear channel, and utilizing a rapid convergence characteristic of the algorithm to realize rapid reduction of a mean square error; and when the equalization process reaches a preset judgment condition, automatically switching to a generalized linear judgment guide algorithm of a nonlinear channel, further reducing the steady-state error through judgment feedback, and considering both the convergence speed and the equalization precision.

The application discloses a kind of based on two-stage attention neural network's down-sampling DPD method and device, method includes: using memory polynomial method determines rough estimate DPD parameter;Based on a plurality of input sample signals and each input sample signal corresponding rough estimate DPD signal constructs sample set;Wherein, each input sample signal corresponding rough estimate DPD signal is determined based on the input sample signal and rough estimate DPD parameter;Utilize sample set training DPD neural network model, and according to the model after training realizes down-sampling DPD signal estimation;Utilize sample set training model includes: input input sample signal into model, to make model output the input sample signal corresponding output DPD signal;According to the difference between the output DPD signal and rough estimate DPD signal corresponding to input sample signal, incremental training is carried out to DPD neural network model, reduce the calculation cost, improve the power amplifier nonlinear correction efficiency.

The invention discloses a power amplifier nonlinear compensation method and device combining amplitude-phase grouping modulation and data driving. At a transmitter side, bit information is borne by adopting a packet modulation technology with amplitude-phase constraints, and a frame structure sequence is constructed by using nonlinear compensation pilot symbols and data symbols. At a receiver side, a distorted data symbol is reconstructed through amplitude-phase constraint to obtain a preliminarily compensated signal sequence, and a power amplifier nonlinear distortion inverse model is trained offline to obtain a coarse estimation parameter. And carrying out parameter initialization on an online power amplifier nonlinear distortion inverse model by using the parameter through a transfer learning technology, carrying out online training by using a known nonlinear compensation pilot frequency sequence to obtain a fine estimation parameter of the inverse model, compensating a nonlinear distortion data signal through the inverse model, and demodulating to obtain emission information. According to the invention, more accurate power amplifier nonlinear compensation is realized, the resource overhead of the transmitting and receiving end is reduced, and the power efficiency and the information transmission performance of a wireless communication system are remarkably improved.

The application discloses a kind of amplitude-phase grouping modulation-oriented received signal reconstruction methods, it is applicable to communication system receiving end, the amplitude-phase grouping modulation signal of distortion caused by power amplifier nonlinear amplification is reconstructed.The method is first to the frequency domain equalization of received signal, and eliminate the influence of power amplifier linear amplification;Then, the phase of received signal is adjusted, and demodulates additional phase;Subsequently, the amplitude of received signal is revised;Then, based on least square criterion, signal reconstruction optimization problem model is constructed, and least square optimization reconstruction is executed.Afterwards, additional phase demodulation, amplitude adjustment and least square optimization reconstruction are iteratively executed until the preset iteration number is reached, so as to obtain high-quality reconstructed signal.The application can effectively deal with nonlinear distortion at the receiving end of the communication system, realize high-quality signal reconstruction, thereby significantly improving the overall performance and power efficiency of the communication system.

The disclosed signal nonlinear distortion compensation method, model, and communication system relate to the wireless communication technology field. In this disclosure, a preset nonlinear compensation fusion model is used to perform DPD processing, CFR processing, and error compensation processing on an initial OFDM signal to obtain a nonlinear distortion-compensated initial OFDM signal. In this nonlinear compensation fusion model, the BL-DPD module, BL-CFR module, and error compensation module are arranged in parallel, avoiding the technical drawbacks of the prior art, where the DPD module is applied after the CFR module, which increases the requirements for the ADC / DAC sampling rate and the requirements for hardware and algorithm convergence speed, thereby increasing the difficulty and cost of system implementation. This not only reduces the requirements for the ADC / DAC sampling rate, but also improves the DPD compensation ability for power amplifier nonlinearities, thereby improving the communication and sensing performance of the OFDM system.

According to an aspect, an apparatus may comprise a digital pre-distorter, DPD, circuitry including at least one first-order infinite impulse response, IIR, filter and at least one second-order IIR filter. The apparatus may further comprise a power amplifier, at least one processor and at least one memory comprising instructions which, when executed by the at least one processor, cause the apparatus at least to compensate for non-linearities in the power amplifier by using the at least one first-order IIR filter and the at least one second-order IIR filter.

The application discloses a cross-domain physical layer security authentication method and system based on physical priori and meta learning, and comprises the following steps: S1, receiving an antenna array of a baseband complex signal of a high dynamic node to be authenticated; S2, synchronizing the received data packet preamble or pilot sequence, extracting the channel state information matrix and the radio frequency fingerprint sequence at the current time; S3, inputting the extracted high-dimensional baseband complex signal into a physical embedded meta authentication network PEMA-Net after offline multi-task meta training and online cross-scene authentication; S4, decoupling the previous stage based on the deterministic communication physical operator and the power amplifier nonlinear inverse mapping operator, obtaining pure hardware eigenfeatures; S5, the hardware eigenfeatures pass through the deep residual feature mapping middle stage, and output a field-independent embedded feature vector; and S6, the feature vector is linearly projected to the final decision space through the posterior probability judgment classification final stage.

This invention discloses a precoding method for power amplifier distortion-resistant multi-antenna systems, belonging to the field of wireless communication and radar sensing fusion technology. This invention is mainly applied to integrated sensing systems. Compared with traditional integrated sensing systems that do not consider power amplifier nonlinearity, this invention incorporates the power amplifier nonlinearity into the system performance, providing a received signal model and sensing and rate indices under power amplifier distortion conditions. Compared with classical precoding algorithms, this invention considers the impact of power amplifier distortion, resulting in superior performance in practical systems. Furthermore, this invention uses alternating optimization and manifold optimization to solve the non-convex problem of rate maximization, and employs a two-stage solution, enabling its application to hybrid beamforming arrays and making it suitable for real-time applications.

The present invention discloses a signal receiver and signal receiving method involving nonlinear detection method for mmWave OTFS systems in high mobility scenarios with non-ideal power amplifier, which is applicable in the fifth generation (5G) and beyond networks. The millimeter wave (mmWave) system is envisioned to be a promising candidate of 5G. However, the high frequency and large bandwidth operation in mmWaves result in nonlinear distortions from the power amplifier in the system. The nonlinearly distorted signals from non-ideal power amplifier when propagate through a wideband high mobility channel tremendously degrades the systems performance. Attributed to the non-ideal power amplifier, the nonlinear distortions induce multiplicative distortions and inter symbol interference (ISI) in the OTFS system. It further causes the posterior probability of the transmitted signal non-Gaussian and analytically intractable. The present signal receiver and signal receiving method proposes an amalgamation of maximal ratio combining (MRC) and particle filter in the delay-Doppler domain to retrieve the desired signal from the nonlinearly impaired observations.

The invention discloses a non-reflection distortion cancellation amplifier architecture, and belongs to the technical field of amplifiers. The framework aims to solve the problems of non-reflection of an input port and design of a high-linearity amplifier in a conventional integrated circuit process, multiple paths of distortion offset auxiliary paths are arranged, each auxiliary path comprises an auxiliary amplifier, and the input / output end of each auxiliary path is provided with a signal scaling factor corresponding to a nonlinear coefficient of a main amplifier; superposing or subtracting the generated nonlinear current / voltage to realize high-order nonlinear synchronous offset of the main amplifier; meanwhile, an out-of-band signal absorption network is combined to absorb out-of-band signals to avoid reflection; simulation and embodiments show that the architecture can suppress out-of-band signal reflection in a broadband, improve stop-band suppression and reflection coefficient performance, also can realize small-signal third-order intermodulation IIP3 improvement, has the advantages of low power consumption, high integration level and the like, and is suitable for various scenes such as high-data-rate communication and the like.

A SOA arrangement (100) including a first polarization-diversity SOA pair (102) and a second polarization-diversity SOA pair (104) arranged on a common optical path with a correlation reducing optical arrangement 106 The correlation reducing optical element is configured to receive a first and a second input component from the first SOA pair and to mix the first and second input components into a first and second output components. The first output component is a combination of the first and second input component from the first polarization-diversity SOA pair. The second output component is a combination of the first and second input component from the first polarization-diversity SOA pair. The SOA arrangement thereby being arranged to reduce the correlation between the nonlinear noise generated by the first SOA and the second SOA.

The invention discloses a power amplifier digital pre-distortion method and system based on a minimum gating network, and relates to the technical field of gating networks, and the method comprises the steps: firstly, obtaining a baseband input signal, and constructing a multi-dimensional feature vector containing current and historical real part imaginary parts and first-order and third-order instantaneous envelopes; time sequence processing is carried out through a scalar minimum gating unit layer, a stable state and a normalized forgetting mechanism are introduced, and the modeling capability of long-time nonlinear dynamics is enhanced. Then attention weighting is carried out on the hidden state, and instantaneous phase sine and cosine features extracted from the input signal are fused to form a comprehensive feature; and generating a complex field pre-distortion signal through output layer mapping. According to the method, a time sequence modeling structure based on a scalar minimum gating single is introduced, and delay enhancement feature construction, an attention weighting mechanism and instantaneous phase feature fusion are combined, so that high-precision and low-complexity digital pre-distortion of nonlinear distortion of the power amplifier is realized.

Embodiments herein disclose a method for controlling a non-linear effect of a power amplifier by an apparatus. The method includes acquiring an input data of the power amplifier of the apparatus and an output data of the power amplifier. Further, the method includes determining an inverse function using a neural network. The inverse function maps normalized output data of the PA to the input data of the PA, where the neural network comprises at least one sub-network for at least one memory tap from a plurality of memory taps in the neural network. Further, the method includes modifying the input data based on the determined inverse function value by dynamically changing a usage of the at least one memory tap from the plurality of memory taps. Further, the method includes compensating the non-linear effect in the output data of the power amplifier.

The invention discloses a power amplifier nonlinear compensation method based on a multilayer memory depth BiLSTM, and the method comprises the steps: firstly obtaining the original data of a radar transmitting end and the output data of a radar power amplifier, constructing a multilayer memory depth BiLSTM neural network model, taking the original data of the radar transmitting end and the output data of the radar power amplifier as a data set, training the BiLSTM neural network model, and carrying out the nonlinear compensation of the radar power amplifier. And obtaining a trained multilayer memory depth BiLSTM neural network model, collecting data after radar power amplifier non-linear and Gaussian channel interference at a radar receiving end, and sending the data to the trained multilayer memory depth BiLSTM neural network model to complete radar power amplifier non-linear receiving end compensation. According to the scheme, the communication error rate can be effectively reduced, and compared with a traditional algorithm, the method has more excellent compensation performance under the conditions of low signal-to-noise ratio and strong radar power amplifier nonlinearity, and has better applicability.

A method for wireless communication by a user equipment (UE) includes transmitting, to a network node, a first message indicating a capability of the UE to transmit a multiplexed low peak-to-average power ratio (PAPR) demodulation reference signal (DM-RS) and a high PAPR reference signal (RS) within a single slot, the low PAPR DM-RS having a first waveform and the high PAPR RS having a second waveform. The method also includes multiplexing, associated with the capability, the low PAPR DM-RS with the high PAPR RS within the single slot. The method further includes transmitting, to the network node, the multiplexed low PAPR DM-RS and high PAPR RS within the single slot.

The present application relates to the technical field of power amplifier characteristic simulation, and discloses a power amplifier operating characteristic simulation method, device, computer equipment and medium, the method comprises the following steps: obtaining a plurality of different input data of a power amplifier, intercepting time sequence data of different lengths of continuous time periods, and dividing the time sequence data into training data and test data; training a neural network based on an attention mechanism based on the training data to obtain a power amplifier nonlinear characteristic model; testing the power amplifier nonlinear characteristic model based on the test data to obtain a power amplifier operating characteristic simulation model; obtaining real-time input data of the power amplifier, and obtaining a power amplifier operating characteristic simulation output result based on the real-time input data and the power amplifier operating characteristic simulation model, the present application significantly improves the analytical ability of the complex relationship between the input signal and the output signal, greatly improving the precision and efficiency of the power amplifier simulation.