99 results about "Channel frequency response" patented technology

The invention relates to a channel estimation method based on frequency domain deviation compensation and dynamic DCT denoising, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a wireless channel model and an OFDM system model; estimating the frequency offset in the received signal by using the phase rotation characteristic of the pilot signal; calculating a preliminary channel frequency domain response # imgabs2 # at a pilot frequency position through a least square criterion based on the compensation signal # imgabs1 #; obtaining a receiving pilot frequency signal # imgabs4 # according to the sending pilot frequency Xp and the roughly estimated channel frequency response # imgabs3 #; estimating a current signal-to-noise ratio SNRest based on the pilot frequency signal # imgabs5 # and a noise power ratio; and establishing an adaptive DCT denoising strategy based on a signal-to-noise ratio threshold, and selecting different denoising strategies according to different signal-to-noise ratios to perform denoising processing on # imgabs6 # to obtain final channel estimation # imgabs7 #. The adaptive denoising strategy design of the invention effectively balances the relationship between noise suppression and channel structure fidelity, and improves the precision and stability of overall channel estimation.

The invention discloses a communication data transmission method and system for an intelligent charging pile, and relates to the technical field of intelligent charging pile communication, and the method comprises the steps: constructing a reverse power line transmission channel model based on an equivalent channel response matrix, extracting channel frequency response, generating a channel equalization configuration parameter set through a joint optimization equalization algorithm, and transmitting the channel equalization configuration parameter set to a communication module. Subcarrier modulation orders are dynamically allocated according to the signal-to-noise ratio parameter, and a pre-balanced OFDM time domain signal is generated; on the basis of the channel equalization configuration parameter set and the pre-equalization OFDM time domain signal, dynamically monitoring power frequency harmonic noise of the cable, and inhibiting interference through a filtering algorithm to generate a clean power line carrier signal; and generating a verified V2G communication control instruction through a cyclic redundancy check method based on the clean power line carrier signal in combination with the main polarization direction feature vector. According to the method, an accurate channel model is constructed by combining an equivalent channel response matrix and cable characteristics, and dynamic subcarrier distribution is realized based on signal-to-noise ratio parameters.

Methods and systems for communication and sensing systems. The disclosed method includes, among other things, responsive to receiving a plurality of channel frequency response (CFR) measurements from an antenna operating at a low-bandwidth range, generating a channel state information (CSI) across a high-bandwidth range based on the plurality of CFR measurements and determining, based on the CSI, a Doppler shift across the high-bandwidth range.

The present invention discloses a MIMO-OFDM channel estimation method and device based on natural interpolation. The method comprises: obtaining a channel coefficient at a pilot signal based on least squares channel estimation; assigning weights to the channel coefficients at several pilot signals near each interpolation point according to the size of the Voronoi diagram grid area based on the natural interpolation method, and obtaining an interpolation formula at the interpolation point by weighted summation; and performing natural interpolation on each interpolation point using the interpolation formula to obtain a MIMO-OFDM channel estimation result. The method applies natural interpolation to channel estimation, and obtains a channel frequency response estimate at the interpolation point by weighting the values ​​at several pilot signals near the interpolation point. This method can simultaneously utilize the time and frequency correlation of the channel, significantly improve the channel estimation accuracy, reduce the channel estimation error, and have a smoother interpolation effect and better interpolation performance.

The invention discloses a beam codebook generation method, a beam management method, a beam codebook generation device, a beam management method, a beam codebook generation device, a beam management device and communication equipment, relates to the technical field of communication, and aims to solve the problem of relatively high beam forming codebook complexity in an existing near-field beam forming scheme. The method comprises the following steps: respectively determining the channel frequency response of each antenna unit according to the position of each antenna unit in an antenna array and a preset incident path parameter; respectively converting the channel frequency response of each antenna unit into a phase mode response; and generating a beam codebook of each antenna unit according to the phase mode response of each antenna unit. According to the embodiment of the invention, the codebook complexity and the codebook number can be reduced, and the sensing speed is improved.

The invention provides a coding method and system of a Transform class model for channel state information prediction. The coding method comprises the following steps: S1, acquiring and processing channel state time sequence data; s2, inputting the processed data into an encoder to extract features; s3, CFR data needing to be predicted are embedded, and position codes of the model are added; decoding the relevant parameters using a decoder; s4, processing the output of the decoder, and predicting channel state information; and S5, taking the CFR data and the CSI data obtained in the actual scene as the input of the model, and predicting channel frequency response information. According to the method, the time sequence characteristics of the channel state information are calculated and coded, and the time information is brought into the model, so that the relative stability time of the channel at the future moment is considered, the problem of weak time sequence information embedding capability in a Transform model is solved, and the accuracy of channel state prediction is improved.

The invention relates to the technical field of circuit fault processing, and discloses an automatic identification and remote isolation method for a fault section of a low-voltage distribution line, and the method comprises the steps: building a reference fingerprint database based on channel state information through a central coordination node; monitoring real-time channel frequency response and executing threshold comparison to judge suspected fault points; triggering an active impedance control unit of the terminal agent node to execute controlled perturbation; a transmission line network model is used for calculating a theoretical transmission function variable quantity, fitting analysis is carried out on the theoretical transmission function variable quantity and a measured value, and a physical fault is judged and load interference is stripped through a normalized residual coefficient; calculating a residual drift distance between adjacent nodes based on the topological mapping table to execute differential positioning so as to lock a fault physical interval; and issuing a tripping message, and driving the circuit breaker to execute physical isolation at the power frequency zero crossing point. According to the scheme, on-line fault identification and isolation are realized through active impedance perturbation and distributed residual analysis, and the robustness of fault judgment in a complex load environment is improved.

A time-interleaved ADC mismatch correction method and time-interleaved ADC relating to the technical field of integrated circuits are disclosed. The time-interleaved ADC mismatch correction method and time-interleaved ADC solve problems with high-order filter modules and signal overflow or saturation risks. The applied technical scheme uses time-interleaved ADC output signal(s) and a fitted signal to calculate a set of filtering coefficients, and uses this set of filtering coefficients to correct the ADC output signal in real time. The applied technical scheme compensates for differences in the frequency response of each channel, rather than the frequency response itself, and the filter order is smaller, the implementation is simpler, and the circuit design complexity and device cost are greatly reduced. The technical solution has a wide range of adaptability, can correct and improve broadband interleaving performance, and avoids the signal overflow / saturation risk because the compensation range is small.

The embodiment of the invention provides a high-order modulation signal group delay distortion compensation method and device based on sub-band decomposition, and the method comprises the steps: obtaining a received signal, extracting a target guide code, and calculating a signal-to-noise ratio estimation value; determining a signal sub-band decomposition number and a compensation filter length based on a predetermined signal decomposition parameter and a signal-to-noise ratio estimation value; decomposing the received signal based on the signal sub-band decomposition number to obtain at least four signal sub-bands; calculating a filter compensation coefficient of each signal sub-band based on the compensation filter length, and performing group delay compensation on each signal sub-band based on the compensation coefficient; according to the embodiment of the invention, fine compensation of different frequency components is carried out on group delay through sub-band decomposition, channel frequency response in the sub-bands is flatter, requirements for estimation errors and the length of a filter are reduced, and therefore the performance bottleneck of a global equalizer is avoided.

Disclosed are systems and methods that provide a decision-intelligence (DI)-based, computerized framework for advanced device naming and localization of Wi-Fi connected devices at a location. The disclosed framework operates to manage, control and / or manipulate devices on a Wi-Fi network, which provides intuitive mechanisms to select devices to name, group and / or locate in a WiFi app with WiFi motion and / or detected gesture(s) by leveraging voting and ranking mechanisms via a compiled cross-correlation matrix of channel frequency response (CFR) motion signatures and / or channel state information (CSI) motion signatures. Accordingly, motion signature information can be leveraged to control, enable and / or permit Wi-Fi connections among and / or between devices at a location.

The invention discloses a channel estimation method for a 5G-OFDM system based on deep learning, and the method comprises the steps: building an OFDM orthogonal frequency division multiplexing system, and forming a low-resolution channel matrix; establishing a deep learning neural network channel estimation model; the low-resolution channel matrix is input into a deep learning neural network channel estimation model to be processed, the deep learning neural network channel estimation model adopts an interpolation-free end-to-end learning framework, and feature extraction is directly conducted on channel response data which are not interpolated; and outputting a complete channel frequency response matrix through the deep learning neural network channel estimation model to realize channel estimation. Under a 3GPP TDL-A multipath channel, the model provided by the invention has excellent performance in a signal-to-noise ratio range of 1-30dB: compared with an existing deep learning model, the estimation precision has the advantage that the parameter quantity is reduced by 93% under similar precision; the reasoning time is only 12.44 ms, the speed is increased by 25.7% compared with that of an SRCNN, the model calculation amount is only 38.24 MMac, and the method is easy to deploy in a mobile terminal with limited resources.

Techniques are provide for neural network based positioning of a mobile device. An example method for measuring a channel in a wireless communication system includes: receiving reference signal information; determining one or more channel frequency responses based on the reference signal information and one or more timing hypotheses; determining one or more channel impulse responses comprising a channel impulse response for each of the one or more channel frequency responses; processing the one or more channel impulse responses with a neural network; and determining an output of the neural network.

In one aspect, a method includes receiving, in a first wireless device, a data transmission including at least one orthogonal frequency division multiplexing (OFDM) packet from a second wireless device; processing the at least one OFDM packet to recover data and providing the data to a host processor of the first wireless device; encoding, in the first wireless device, at least one decoded symbol of the at least one OFDM packet using forward error correction coding; processing the encoded at least one decoded symbol to recover at least one corresponding transmission symbol of the at least one OFDM packet; and determining a distance estimate between the first wireless device and the second wireless device based at least in part on the corresponding transmitted symbols.

Aspects presented herein may improve the efficiency and performance of artificial intelligence (AI) / machine learning (ML) (AI / ML) positioning by enabling a network node (e.g., a base station, transmit receive point (TRP), etc.) to compress uplink (UL) reference signal measurements to reduce reporting overhead for UL reference signal measurements. In one aspect, a network node performs at least one channel impulse response (CIR) measurement or at least one channel frequency response (CFR) measurement for a sounding reference signal (SRS) set. The network node compresses at least one CIR measurement or at least one CFR measurement for the SRS set. The network node reports, for the network entity, one or more of the at least one compressed CIR measurement or the at least one compressed CFR measurement for the SRS set.

A channel feedback method, apparatus and system. The method comprises: acquiring multipath component information of a communication channel between a first device and a second device; on the basis of a self-supervised neural network, performing processing on the multipath component information and second channel information, so as to obtain intermediate information; and sending the intermediate information, wherein the second channel information is determined on the basis of first channel information and multipath delay information, the second channel information comprises a variable channel impulse response (CIR), the first channel information comprises a channel frequency response (CFR), which is obtained by means of a measurement, and the intermediate information and the multipath component information are used for determining a reconstructed CIR. By means of the solution, channel feedback is performed in combination with multipath component information and a self-supervised neural network, thereby reducing measurement overheads and feedback overheads.

This application provides a behavior recognition method, apparatus, electronic device, and storage medium based on exponential fitting, comprising: determining the corresponding power delay spectrum for the channel frequency response of a Wi-Fi signal at each observation time; fitting an exponential probability density function based on the power distribution of each sampling point in the power delay spectrum; performing a Fourier transform on the probability density function to obtain a frequency domain correlation function; determining filter coefficients based on the frequency domain correlation function and a preset frequency domain signal-to-noise ratio; filtering the channel frequency response based on the filter coefficients to obtain a denoised channel frequency response; and performing behavior recognition of passive targets based on the denoised channel frequency response at multiple observation times. This application's solution effectively denoises the channel frequency response of a Wi-Fi signal using exponential fitting, thereby enabling accurate behavior recognition based on the denoised channel frequency response.

The invention discloses a low-voltage power distribution network fault monitoring method and system based on a sensor network technology, and relates to the technical field of power distribution network fault monitoring, and the method comprises the steps: collecting sensor data in real time, and obtaining the frequency response of a power distribution network channel; comparing and analyzing change amplitudes of frequency responses of different power receiving equipment channels, and determining a branch where a fault is located; and calculating the impedance amplitude of the fault branch, and determining the accurate position of the fault point according to the relevance between the impedance and the distance. A fault branch is positioned by comparing the channel frequency response variation amplitudes of different power receiving devices, the impedance amplitude of the fault branch is calculated, and the accurate positioning of a fault point is further realized by combining the relation between impedance and distance. The method is accurate and stable, and can effectively monitor the grounding fault in the low-voltage power distribution network. Under the condition that signal interference is not considered or interference is small, fault branch detection accuracy is high.

The invention provides a power line carrier communication method and device based on adaptive bit power allocation, and the method comprises the steps: determining the channel frequency response and noise power of each OFDM subcarrier according to a preset signal transmitted to a target electric energy meter and a receiving signal received by the target electric energy meter on each OFDM subcarrier, and transmitting the channel frequency response and noise power to the target electric energy meter; according to the method, the optimal activation subcarrier number with a good communication effect and the most appropriate optimal power allocation reference value are screened out through channel frequency response and noise power, and then target power and bit number are configured for each optimal activation subcarrier. According to the method, the OFDM subcarriers with better communication performance can be selected from the plurality of OFDM subcarriers, and then proper power and bit number are configured for each OFDM subcarrier, so that the data to be transmitted can be modulated to each optimal activation subcarrier to communicate with the target electric energy meter according to the target power and bit number. Therefore, the communication quality of the intelligent acquisition terminal is improved, and the probability of communication interruption is reduced.

The present disclosure provides a channel optimization method and device, system, electronic equipment and program product. The method comprises: obtaining a channel frequency response value of a target channel based on current state information of a feedforward equalizer of a receiving end of the target channel in a serial system, the channel frequency response value being used to represent transmission quality of different frequency band signals in the target channel; generating an adjustment instruction of a target parameter based on the channel frequency response value, the target parameter being a parameter in a channel before the feedforward equalizer in the target channel; and adjusting the target parameter based on the adjustment instruction of the target parameter, so that the target channel transmits serial signals with the adjusted target parameter. The embodiments of the present disclosure can reduce the time and cost of channel optimization, and help to reduce the bit error rate of the channel and improve the stability of the channel.

A system and method for determining the distance between two wireless network devices is disclosed. The present system utilizes an algorithm that leverages additional information contained in the pseudo-spectrum generated the MUSIC algorithm. Specifically, since the MUSIC algorithm operates using the square of the channel frequency response, additional peaks are created in the pseudo-spectrum, which can be used to verify the correctness of the distance measurement. The algorithm verifies that the first peak is correct by identifying a second peak and looking for an additional peak located within a search region that is determined based on the first two peaks.

The invention provides a digital twin channel modeling method based on a generative adversarial network and transfer learning, which relates to the technical field of wireless communication, and comprises the following steps: firstly, constructing a semi-physical digital twin channel simulation platform, generating a baseband signal by using the semi-physical digital twin channel simulation platform, and processing the baseband signal; the channel frequency response data is obtained, and the cost of collecting the real channel data is effectively reduced while the precision of the channel data is kept; the channel frequency response data is utilized to train the generative adversarial network, the transfer learning strategy is utilized to accelerate the training process of the generative adversarial network, and parameters obtained by training at the semi-physical digital twin channel simulation platform are transferred to the target task, so that the time for updating each parameter again is shortened, the training efficiency is improved, and the training efficiency of the semi-physical digital twin channel simulation platform is improved. And finally, the trained generative adversarial network is utilized to generate channel data, so that the feature extraction capability of the model is enhanced.

The present invention discloses a transmitter calibration method, system, and medium based on an IQ modulator, belonging to the field of optical communications. The method includes: controlling the transmitter to transmit two multi-tone signals according to a pre-designed number of scanning frequency points, scanning frequency intervals, and multiple beat frequency intervals, so that the IQ modulator modulates the multi-tone signals and outputs corresponding optical signals; performing square detection and DC isolation processing on the optical signals in sequence to obtain low-frequency electrical signals, and separating the I-channel frequency response correlation signal, the Q-channel frequency response correlation signal, and the IQ delay difference correlation signal from the low-frequency electrical signals; using the cosine signal and sine signal of the beat frequency interval, performing calculation processing on the I-channel frequency response correlation signal, the Q-channel frequency response correlation signal, and the IQ delay difference correlation signal, respectively, to obtain the I-channel frequency response, the Q-channel frequency response, and the IQ two-channel delay difference to calibrate the transmitter. This greatly reduces measurement costs and broadens applicable scenarios.

The present invention provides a method for identifying visibility regions (VRs (140)) on the ELAA (100) by detecting the information related with VRs (140). The method comprises the steps of omnidirectionally transmitting a pilot signal from the user device (120) to the communication device (200) for channel estimation; omnidirectionally receiving the pilot signal by the ELAA (100) of the communication device transmitted from the user device (120) (210); measuring, by the communication device, the received power across the array element (110) in ELAA (100) from the received signal (220) and obtaining power distribution of the measured powers that are above a predefined threshold power in power domain; estimating the channel frequency response by the communication device from the received pilot signal (230); transforming the estimated channel frequency response to the beamspace domain (240); extracting the VR-related information from the beamspace domain representation of the estimated and transformed channel (250); identifying the VRs (140) by using the information obtained from beamspace domain and from the power domain (260).

A system and method for determining the distance between two wireless network devices is disclosed. The present system utilizes an algorithm that relies on the power ratio between the trial signal power and the remaining signal power. Remaining signal power is defined as the power that is left after subtracting the trial signal power from the total signal power. This algorithm computes the channel frequency response and uses the phase signal at each frequency and distance to calculate the line of sight distance between two wireless network devices. This approach does not rely on eigenvectors or any prior estimate of the number of signals, and can therefore be computed quickly and efficiently.

The invention discloses a photon terahertz OFDM (Orthogonal Frequency Division Multiplexing) system phase noise self-adaptive compensation method based on a double-branch Transform, and belongs to the field of terahertz communication. The method specifically comprises the following steps: a transmitting end performs constellation mapping on a bit stream to generate a complex symbol, performs OFDM coding, maps the complex symbol to a frequency domain subcarrier, adjusts the signal amplitude and outputs a transmitting signal to a receiving end; a receiving end performs channel estimation on the terahertz OFDM signal to obtain a channel frequency response; on the basis, OFDM decoding is carried out on the received signal, and a signal after preliminary phase correction is obtained; then, the signals are input into a phase noise neural network decoder, features of phase noise are extracted and input into a double-branch processing network for parallel processing, phase noise compensated signals output by a Transform phase estimation branch and enhanced signals output by a CNN signal enhancement branch are obtained, and self-adaptive fusion processing is carried out based on confidence score; and finally, demapping to obtain a final result. According to the invention, the influence of phase noise on the system performance is relieved, and the bit error rate performance is improved.

An example apparatus includes: channel frequency response (CFR) circuitry configured to: receive communication signals; and determine magnitudes of the communication signals; and quality metric circuitry coupled to the CFR circuitry and configured to: determine a quality metric using the magnitudes of the communication signals; select one of a first distance estimation model or a second distance estimation model using the quality metric; and estimate a distance using characteristics of the communication signals and the selected distance estimation model.

This application discloses an acceleration determination method, apparatus, device, and storage medium, relating to the field of communication technology, for improving the efficiency and accuracy of determining the acceleration of a target object. It includes: acquiring a first channel frequency response (CFR) corresponding to a first channel, and multiple second CFRs corresponding to multiple second channels, wherein the first channel is used to transmit direct signals, and the multiple second channels are used to transmit multipath signals, the multipath signals being reflected signals; determining a target model based on the first CFR and any one of the multiple second CFRs, the target model being used to determine the CFR corresponding to each time moment; determining the CFRs corresponding to multiple time moments based on the target model, and determining the target velocity and target acceleration of the target object based on the CFRs corresponding to the multiple time moments. This application is applied to scenarios involving determining the acceleration of a target object.

A method for determining an angle of arrival at a first communication device having a first antenna and a second antenna aligned along a direction and defining a normal thereto. The method comprises performing a respective signal exchange through each of a plurality of channels between the first communication device and a second communication device, storing a first plurality of in-phase and quadrature (I / Q) samples; estimating channel frequency responses for the first antenna and the second antenna respectively; measuring a respective distance; creating respective standard channel frequency response components corresponding to the respective distances; for each propagation path, selecting a first respective weight and a second respective weight; selecting a weight w1(1) and an other weight w2(1);determining, based on the weight w1(1) and the other weight w2(1), the angle of arrival, relative to the normal, of signals direct from the second communication device.

This invention discloses a method for cascading electricity meter reading, belonging to the field of smart meter reading technology. Specifically, it includes: acquiring the channel frequency response sequence and message response timing of each preset frequency point, constructing a dynamic transmission map for each frequency point; analyzing the signal correlation between nodes in the map, restoring the physical layer connectivity state at each frequency point, and extracting data forwarding reachability relationships; acquiring the power supply ripple sequence and crystal oscillator frequency deviation value of each node to form a node operating state feature set and establishing a joint parameter correlation matrix; training and generating a frequency-node joint optimization strategy mapping model; updating the joint parameter correlation matrix, inputting the model to output the optimal operating frequency point and corresponding relay node sequence, and executing the frequency point configuration and node allocation of the cascaded meter reading path. This invention, through dynamic sensing of the standing wave state at each frequency point and real-time frequency switching, achieves active adaptation to the time-varying filter effect of the power line channel, improving the communication effectiveness of the cascaded meter reading path under complex load environments.

This invention discloses an adaptive phase noise compensation method for a photonic terahertz OFDM system based on a dual-branch Transformer, belonging to the field of terahertz communication. Specifically, the transmitter performs constellation mapping on the bitstream, generates complex symbols, performs OFDM encoding, maps them onto frequency domain subcarriers, and adjusts the signal amplitude to output the transmitted signal to the receiver. The receiver performs channel estimation on the terahertz OFDM signal to obtain the channel frequency response. Based on this, it performs OFDM decoding on the received signal to obtain a signal with preliminary phase correction. Then, it inputs the signal to a phase noise neural network decoder to extract phase noise features, which are then input into a dual-branch processing network for parallel processing. This yields the phase noise-compensated signal output from the Transformer phase estimation branch and the enhanced signal output from the CNN signal enhancement branch. Adaptive fusion processing is then performed based on confidence scores. Finally, demapping is performed to obtain the final result. This invention mitigates the impact of phase noise on system performance and improves bit error rate performance.