48 results about "Channel parameter estimation" patented technology

Certain aspects of the present disclosure provide techniques for obtaining one or more reference signals specific to a communication channel; inputting at least one characteristic associated with the one or more reference signals into a machine learning model that is configured to predict one or more channel parameters associated with multipath propagation characteristics of the communication channel; outputting, from the machine learning model, one or more predicted channel parameters specific to the multipath propagation characteristics of the communication channel; and performing channel estimation to generate a characteristic of the communication channel based on the one or more predicted channel parameters.

The invention provides a Bayesian wireless channel estimation method and a Bayesian wireless channel estimation system suitable for same-frequency interference, and the method uses variational inference based on LSI to capture frequency points with large interference power in a considered frequency band, and can more effectively extract frequency points with real interference from an actual frequency selective fading channel. The method comprises the following steps: carrying out GI and LSI-based alternate variational inference for optimizing an algorithm model and reducing overfitting of the algorithm, introducing a hyper-parameter adaptive updating method of an interference level so as to introduce more prior information entropy during iteration, and completing position estimation through channel parameter estimation in a pilot frequency band of OFDM in combination with ToA / TDoA / AoA and other algorithms, so that the estimation accuracy is improved. Kalman / Particle Filter can also be combined to complete navigation prediction, and the communication quality of signal subcarriers can also be improved by using a related equalization algorithm.

The invention discloses an underwater sound double-expansion channel parameter estimation method based on Newton orthogonal matching pursuit. The method comprises the following steps: firstly, realizing frame synchronization by using a cross-correlation peak of an LFM signal and a received signal; a coarse estimation value of a Doppler coefficient is obtained on a discrete time frequency grid through an ambiguity function method by utilizing the self-correlation characteristic of m-sequence pilot frequency, multipath time delay of a channel is detected by utilizing a matched filtering peak value of a signal after frequency offset compensation, and a coarse estimation result of the channel is obtained; executing Newton iteration optimization in a continuous parameter space by adopting a Newton orthogonal matching pursuit algorithm to realize super-resolution off-grid estimation of the Doppler coefficient of the first data block; and finally, proposing an iterative block tracking strategy, initializing the compensation of the rear block through the estimated value of the front block, and updating the time-varying Doppler coefficient by using the balanced signal feedback to realize the dynamic tracking of the time-varying Doppler coefficient. According to the invention, the Doppler estimation root-mean-square error is obviously reduced, and the calculation efficiency is high.

The present application relates to a parameter estimation method, a positioning method, and an apparatus. The parameter estimation method includes: discretizing the incident angle in the channel steering vector on a grid to determine the coefficient matrix expression in the continuous-time signal representation model; performing baseband sampling on the received signal to obtain a discrete-time signal representation model of the received signal on M antennas after reflection from the reflector; using the coefficient matrix expression, the discrete-time signal representation model, and the transmit signal matrix to obtain a sparse representation model of the received signal based on the angle domain and the delay domain; based on the sparse representation model, obtaining a joint estimation problem for characterizing channel estimation and signal detection, and solving the joint estimation problem to obtain a channel estimation value and a transmit signal estimation value. The present application can reduce pilot overhead for channel parameter estimation.

The invention provides a positioning and speed measuring method and system based on an MIMO-OFDM communication architecture, and the method comprises the steps: enabling each base station to receive a communication signal of a target device, obtaining a plurality of received signals, and enabling each base station to carry out the communication based on the MIMO-OFDM communication architecture; performing time-frequency synchronization and channel estimation on the received receiving signals through each base station to obtain a time-frequency compensation amount and a channel parameter estimation value corresponding to each receiving signal; and inputting each channel parameter estimation value, each time-frequency compensation amount and a first positioning result into a preset positioning model, so that the positioning model performs a plurality of times of weighted iterative updating on the first positioning result based on an iterative optimization algorithm to generate a second positioning result of the target equipment, the first positioning result is obtained through calculation according to preset TDoA, AoA and FDoA positioning methods, so that the accuracy of positioning and speed measurement of the target equipment is improved.

The present application relates to a kind of based on pilot enhancement live network channel parameter estimation method, device and storage medium, by utilizing the pilot information in the downlink signal of commercial mobile network, using high-precision estimation algorithm is preliminarily estimated to the transmission channel between signal from base station to the collection user, and based on the channel result of estimation, the data part in received signal is channel equalization, reconstruct the original data sent by symbol decision, then with the reconstructed data as original transmitting data, high-precision parameter estimation algorithm is applied again to carry out channel parameter estimation, compared with prior art, the present application has by the reconstruction and reuse of the data part of known transmission standard commercial signal, can reduce the data overhead for channel estimation, increase the air interface bandwidth that can be used for user data transmission, while transmission channel state still can obtain real reliable estimation result, with the advantages of accurate channel estimation, low data overhead and controllable calculation complexity.

The present invention belongs to the field of wireless communication technology, and specifically relates to a positioning method for a millimeter wave communication system using low-precision quantization. The present invention proposes an alternating iterative algorithm framework in the channel estimation stage. First, the unquantized channel is restored by the generalized Turbo algorithm, and the channel is roughly estimated using multi-task sparse Bayesian learning. Subsequently, the channel is finely estimated based on expectation maximization, and the above process is iterated to complete the channel parameter estimation. In the position estimation stage, the residual between the channel parameters obtained from the position information and the channel parameters estimated by the algorithm is used as an optimization function, and the Newton method is used to solve the optimization problem. Experiments show that the millimeter wave communication system positioning method proposed in the present invention can still achieve accurate user positioning under low-precision quantization conditions and reach the corresponding theoretical lower bound.

The application provides a near-field channel parameter estimation method considering spatial non-stationary characteristics, which comprises the following steps: obtaining a multipath parameter initial value by using a far-field SAGE algorithm; calculating propagation distances of array elements at a transmitting end and a receiving end to scattering points, constructing a near-field channel response, and performing refined estimation on angle and distance parameters, time delay parameters and complex gain parameters of the multipath. Correlation operation is performed on a current residual signal and the near-field channel response in a frequency domain to obtain an array element level correlation metric. Continuous spatial non-stationary coefficients with a value of 0 to 1 are updated based on the correlation metric, and weighting iteration is performed on residual construction and parameter updating until a stop criterion is met, and near-field geometric parameters, time delay parameters, complex gain parameters of each multipath and spatial non-stationary coefficients of both transmitting and receiving ends are output. The method solves the problem of inconsistent multipath visible domains under XL-MIMO arrays, can suppress the influence of invisible array elements on parameter estimation, and improves the estimation accuracy and stability of the SAGE algorithm under the condition of near-field spatial non-stationary channels.

The embodiments of the present application disclose a measurement method, device, baseband chip, terminal, and storage medium, belonging to the field of communication technology. The method includes: estimating channel parameters based on a reference signal to obtain a parameter estimation result; determining a target filter from at least two candidate filters based on the parameter estimation result; performing channel filtering processing on the reference signal using the target filter to obtain a reference signal filtering result, wherein the channel filtering processing is used to filter out interference and noise in the reference signal; and calculating a measurement item based on the reference signal and the reference signal filtering result. The method provided in the embodiments of the present application can improve the measurement accuracy on the terminal side.

The present invention provides a method, apparatus, electronic device, and storage medium for 5G shared channel parameter estimation, which relates to the field of communication technologies. The method includes: extracting received DMRS data from the received data of the shared channel, and extracting a preset number of DMRS values from the received DMRS data as the DMRS data to be processed; applying a first sequence to the DMRS data to be processed to obtain the processed DMRS data; calculating second sequences corresponding to respective configuration parameters within the range of channel generation configuration parameters corresponding to the shared channel in the current time slot; calculating correlation values between each of the second sequences and the processed DMRS data; using the configuration parameter corresponding to the second sequence with the largest correlation value as the target configuration parameter; and using the target configuration parameter to determine a DMRS symbol for channel estimation. By using this method, the efficiency of calculating the DMRS symbol can be improved.

This invention discloses a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions. The method includes: acquiring reference channel signals and echo signals and performing signal characterization preprocessing to obtain reference channel signal matrices and echo signal matrices; estimating channel parameters based on the reference channel signal matrices and echo signal matrices using the generalized likelihood ratio principle to construct a DPI-GRLT detector; solving the DPI-GRLT detector and calculating the detection statistics at each grid point to obtain the radar target information estimation result. This invention can maintain high localization accuracy and achieve rapid estimation and resolution of multiple targets even under weak signal conditions. As a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions, this invention can be widely applied in the field of radar target localization technology.

The invention discloses a channel parameter estimation and positioning method and device for a double-end super-large-scale array, and relates to the technical field of wireless communication and signal processing, and the method comprises the steps: obtaining the observation data of a receiving end; determining a current scene based on the target distance and the Rayleigh distance, the current scene being any one of a near-field scene and a far-field scene; determining a target channel parameter estimation strategy based on the current scene; based on a target channel parameter estimation strategy, processing observation data of a receiving end to obtain a path time delay estimation value; determining a direct path and a non-direct path based on the path time delay estimation value; and positioning a target position based on the direct path and the non-direct path. Through the above mode, the observation signals received by the large-scale array of the receiving end are processed in the combined dimension of the spatial domain and the frequency domain, the angle, the time delay, the gain and the distance information of each path are accurately estimated, and the position of the target is accurately positioned according to the estimated path parameters of the direct path.

The present application provides a channel parameter estimation method, apparatus, electronic device, and storage medium. The method utilizes a transmission signal, a target estimation channel parameter, a noise parameter, and a preset target smart reflector phase to perform processing through a sampling inference algorithm. The method obtains the target estimation channel parameter after t-1 rounds of processing. If the t-1 rounds of processing do not reach a preset processing threshold, the channel parameters after t-1 rounds of processing are used as the target estimation channel parameters. An iterative inference process is performed based on the transmission signal, the channel parameters after t-1 rounds of processing, and the target smart reflector phase, such that the smart reflector phase continuously approaches the true phase. Accurate inference can be performed based on this process. When the channel parameters after the latest processing round are obtained and the latest processing round reaches the preset processing threshold, the channel parameters after the latest processing round are used as the target channel parameters for the smart reflector, thereby ensuring the accuracy of channel parameter estimation.

The application discloses a method for estimating parameters of a water acoustic double-spreading channel based on Newton orthogonal matching pursuit, which comprises the following steps: first, frame synchronization is realized by using the cross-correlation peak of an LFM signal and a received signal; second, the coarse estimation value of a Doppler coefficient is obtained on a discrete time-frequency grid by using the autocorrelation characteristics of an m sequence pilot and a blurring function method, the multipath time delay of a channel is detected by using the matching filter peak value of a frequency offset compensated signal, and a coarse estimation result of the channel is obtained; third, the Newton orthogonal matching pursuit algorithm is used to perform Newton iteration optimization in a continuous parameter space, and the super-resolution off-grid estimation of the Doppler coefficient of a first data block is realized; and finally, an iterative block tracking strategy is proposed, the compensation of a latter block is initialized by using the estimation value of a former block, the time-varying Doppler coefficient is updated by using the feedback of an equalized signal, and the dynamic tracking of the time-varying Doppler coefficient is realized. The application significantly reduces the root mean square error of Doppler estimation and has high calculation efficiency.

The invention belongs to the technical field of wireless communication, and particularly relates to a fractional order adaptive optimization short wave channel parameter estimation method. Aiming at the time-frequency double-color dispersion characteristic caused by short-wave channel multipath and Doppler spread, firstly, the fractional order Fourier transform energy focusing degree is constructed as a self-adaption degree function, and the fractional order is mapped into the individual position of a sparrow; then, a sparrow search algorithm is utilized to adaptively search a global optimal fractional order in a given order interval, so that high calculation overhead of traditional traversal search is avoided, and meanwhile, the problem that single-peak search is easy to fall into local optimum due to low signal-to-noise ratio and multipath superposition is solved; and finally, peak information is extracted under the optimal fractional order, and joint estimation of multipath time delay, Doppler frequency shift and signal-to-noise ratio is completed. According to the method, the calculation complexity of order search is remarkably reduced while the parameter estimation precision is ensured, the estimation robustness in a low signal-to-noise ratio environment is improved, and good engineering realizability is achieved.

The invention discloses a channel parameter estimation method based on a multi-segment unique code frame structure and used for expanding a frequency offset estimation range. The method mainly comprises the following steps: sliding correlation estimation time delay; compensating time delay; accumulating and calculating phase angles; compensating phase jump; and estimating frequency offset and phase offset. According to the method, for a signal containing a multi-segment UW sequence frame structure, UW detection is carried out on a sequence to estimate symbol-level time delay, after compensation, a frequency offset estimation value and a phase offset estimation value are solved in a phase angle accumulation mode, the phase angle change trend of a multi-segment related sequence is utilized, effective deviation correction can be carried out through phase jump compensation correction based on conditional judgment, and the accuracy of the phase jump compensation correction is improved. Therefore, the frequency offset estimation range is expanded.

The present disclosure provides a method for estimating multipath channel parameters in a RIS system using structured tensor decomposition. The method first constructs a multipath signal tensor by designing a pilot sequence, a RIS reflection coefficient matrix, and a base station receive combining matrix. The baseband received signals for each subcarrier and time slot are collected and reconstructed into a fifth-order signal tensor whose expression contains a Vandermonde matrix as a mode 1 factor matrix A1. Vandermonde structured tensor decomposition is then performed: the Vandermonde structure of matrix A1 is used to multiplex the received signals, augmenting the fifth-order signal tensor into a sixth-order signal tensor. The factor matrix A1 is recovered using the ESPRIT algorithm, and then other factor matrices are recovered to recover the fifth-order signal tensor. Finally, the recovered fifth-order signal tensor is used to estimate the multipath channel parameters. The present invention enables multipath channel parameter estimation for a RIS system in a full multipath environment.

The invention discloses a hybrid non-line-of-sight path channel estimation method. According to the method, four non-line-of-sight paths, namely a line-of-sight path and symmetric distribution and asymmetric distribution of cascaded scatterers, are comprehensively considered, a current mixed field is updated and modeled, so that the model is more adaptive to general conditions in an actual scene, then an HF-OMP algorithm is improved to be adaptive to a new model, and finally, on the basis of a traversal residual error minimization thought, a new mixed field is obtained. According to a criterion of firstly determining a proportion value and then obtaining a corresponding estimated channel component, an adaptive proportional mixed NLoS algorithm based on OMP is provided, and a step-by-step optimization strategy is adopted to realize the determination of a mixed field path proportion and the estimation of channel parameters. According to the method, the problem of estimation deviation caused by loss of path proportion prior information under asymmetric distribution is solved. The experimental result verifies the adaptability of the improved HF-OMP algorithm to the asymmetric channel model and the superiority of the adaptive proportional algorithm in the aspect of reducing the NMSE (Non-Mean Square Error).

The invention provides a 5G shared channel parameter estimation method and device, electronic equipment and a storage medium, and relates to the technical field of communication. The method comprises the following steps: extracting received DMRS data from received data of a shared channel, and extracting a preset number of DMRS values from the received DMRS data as DMRS data to be processed; acting on the DMRS data to be processed by using a first sequence to obtain processed DMRS data; calculating a second sequence corresponding to each configuration parameter in a channel generation configuration parameter range corresponding to the shared channel under the current time slot; a correlation value between each second sequence and the processed DMRS data is calculated; taking the configuration parameter corresponding to the second sequence with the maximum correlation value as a target configuration parameter; the target configuration parameters are used for determining DMRS symbols for channel estimation. By adopting the method, the DMRS symbol calculation efficiency can be improved.

The invention provides a movable antenna system channel angle estimation method based on Bayesian tensor decomposition aiming at the problems of large pilot frequency overhead and channel sparsity in movable antenna system channel estimation, and joint estimation of a departure angle and an arrival angle is realized by constructing a five-dimensional complex number tensor model. The method specifically comprises the following steps: reconstructing channel responses at different positions through a movable antenna, and establishing a five-dimensional complex tensor model for receiving signals; converting the complex number tensor into a real value tensor by using the array structure characteristics; a five-dimensional tensor decomposition model is constructed based on Bayesian recommendation, and angle parameters are extracted through an approximate factor matrix obtained through decomposition; and deriving a Cramer-Ra theory lower bound of angle estimation, and establishing a parameter estimation model based on a limited channel measurement value. According to the method, high-precision estimation can still be kept when the number of transmission paths is unknown, the stability and calculation efficiency of angle estimation are improved, and a high-precision channel parameter estimation solution is provided for a movable antenna system.

The present invention belongs to the field of underwater acoustics, and in particular relates to a method for estimating parameters of an acoustic Doppler velocity measurement channel. Current methods for measuring sound attenuation and sound scattering coefficients are greatly affected by changes in water scatterers and bottom changes, resulting in strong uncertainty, which leads to the problem of low accuracy in the measured sound attenuation and sound scattering coefficients. The present invention corrects the echo level measured by a transducer based on the equivalent plane wave reverberation level formula for volume reverberation and seabed reverberation, combined with known sound expansion attenuation and pure water absorption attenuation, to obtain volume backscattering correction curves and bottom backscattering correction curves, then derivates the distance to obtain the sound absorption coefficient, and then obtains the volume and bottom scattering coefficients, thereby solving the problem of low accuracy in the measured sound attenuation and sound scattering coefficients.

The invention discloses a channel and sensing self-adaption-oriented underwater acoustic communication integrated signal design method, and belongs to the technical field of underwater acoustic communication and positioning. The invention solves the problem that when the frequency band resource is limited, the traditional method is difficult to balance between the improvement of the positioning refresh rate and the improvement of the information transmission rate. The water surface end sends an instruction signal to wake up the underwater end, then the underwater end sends a channel measurement signal, the water surface end carries out channel parameter estimation by using a received signal, and then the optimal fixed-communication integrated signal frame structure design is completed according to a channel parameter estimation result and a user demand; according to the method, the design parameters of the optimal fixed-communication integrated signal are granted to the underwater end in a robust communication mode, and finally, the underwater end performs signal emission according to the designed fixed-communication integrated signal frame structure, so that channel parameter dynamic sensing and real-time optimization of the fixed-communication integrated signal frame structure can be realized; the static contradiction between the training sequence and the information symbol resource allocation is solved. The method can be applied to underwater acoustic communication integrated signal design.

The invention belongs to the technical field of wireless communication and signal processing, and particularly relates to a vibration fast fading parameter estimation method of a vehicle-mounted permanent magnet mechanical antenna (PMMA) communication system based on dynamic vibration characteristics. Comprising the following steps: step 1, antenna vibration amplitude modeling; step 2, channel modeling; step 3, channel parameter estimation; and step 4, adjusting the transmission rate according to the estimated channel parameters. According to the method, in the dynamic unmanned vehicle PMMA communication, the probability prior distribution of the vehicle is innovatively designed, and the distributed parameters are estimated through the EM algorithm, so that the quantitative evaluation of the vibration condition of the vehicle is realized, the vibration condition can be evaluated by a receiver, corresponding processing is performed, and the communication stability can be improved by using further measures.

The application provides a signal modulation parameter estimation method, comprising: dividing a modulation signal into two equivalent to-be-detected signals, and inputting the two to-be-detected signals into a main sampling channel and a feedback sampling channel respectively; performing main channel sampling on the to-be-detected signal input into the main sampling channel to obtain a sample group, performing main channel parameter estimation based on the sample group to obtain an estimation value of an interrupt point position and an estimation value of an amplitude factor of the to-be-detected signal, and obtaining an amplitude estimation value of the to-be-detected signal based on the amplitude factor estimation value; constructing a feedback signal based on the interrupt point position estimation value and the amplitude estimation value, and inputting the feedback signal into the feedback sampling channel; performing frequency mixing on the to-be-detected signal input into the feedback sampling channel and the feedback signal to obtain a carrier signal of the to-be-detected signal, performing direct sampling and delay sampling on the carrier signal to obtain an undelayed sample group and a delayed sample group respectively, and performing feedback channel parameter estimation based on the undelayed sample group and the delayed sample group to obtain a frequency modulation rate estimation value and an initial carrier frequency estimation value of the to-be-detected signal.

A channel parameter estimation method based on multi-segment unique code frame structure for extending frequency offset estimation range mainly includes the following steps: sliding correlation estimation time delay; compensating time delay; accumulating phase angle; compensating phase jump; estimating frequency offset and phase offset. The method is used for signals containing multi-segment UW sequence frame structure, estimates symbol level time delay of the sequence through UW detection, and obtains frequency offset estimation value and phase offset estimation value through the way of accumulating phase angle after compensation. The phase jump compensation correction based on conditional judgment can effectively correct the deviation by using the phase angle change trend of the multi-segment correlation sequence, so as to achieve the purpose of improving the frequency offset estimation range.

This disclosure relates to the field of wireless communication technology, and in particular provides a CQI determination method, device, medium, program, and product. The method includes: receiving a downlink reference signal transmitted by a base station, and performing channel estimation based on the downlink reference signal to obtain channel state information, the channel state information including channel parameter estimation information, precoding matrix identifier (PMI) estimation information, channel estimation information, and noise estimation information; determining channel scenario parameter values ​​based on the channel parameter estimation information, and determining a target channel quality information lookup table corresponding to the channel scenario parameter values ​​and the current modulation and coding scheme from a candidate channel quality information lookup table of multiple channel scenarios; determining the signal-to-noise ratio (SNR) based on the PMI estimation information, channel estimation information, and noise estimation information, and determining the wM (Wide Information Mining) corresponding to each CQI based on the SNR and a mapping model of SNR and mutual information (MI); determining a target CQI based on the wM corresponding to each CQI and the wM threshold associated with each CQI in the target channel quality information lookup table. This disclosure improves the efficiency and accuracy of CQI determination.

This invention relates to a method for simultaneous localization and mapping (SLAM) assisted by a UAV equipped with a reconfigurable smart surface (UAV-RIS), addressing the problems of parameter decoupling difficulties caused by cascaded channels and large amplitude-based localization and mapping errors due to signal strength distortion. The method includes: 1) constructing a nested parallel factor model of the received signal and performing tensor decomposition using a bilinear alternating least squares method to achieve joint channel parameter estimation and signal detection; 2) initializing and removing outliers using an amplitude-independent geometric inference method based on the estimated geometric parameters; and 3) optimizing the model using a weighted least squares method to determine user state and environmental characteristic parameters. This method reduces the impact of amplitude model mismatch and improves parameter estimation accuracy in complex channel environments, making it suitable for autonomous localization and mapping in low-altitude wireless networks.

A wireless transmit / receive unit (WTRU) may sample a latent vector from a pre-defined channel distribution. The WTRU may input the latent vector to a trained generative artificial intelligence (AI) / machine learning (ML) model. The trained generative AI / ML model may be trained to output channel-related parameters associated with each path of a plurality of paths of an over-the-air (OTA) communication channel based on the latent vector. The WTRU may input the channel related parameters associated with each path of the plurality of paths of the OTA communication channel to a non-AI / ML model. The non-AI / ML model may be configured to produce a channel matrix. The WTRU may use the channel matrix to perform one or more of a channel state information (CSI) compression, CSI prediction, beamforming, positioning, and / or performance monitoring.

The present invention relates to a method for constructing a hybrid wavefront signal model for 5G signals and a channel estimation method based on passive measurement of the hybrid wavefront signal model. In the 5G receiving signal model, according to the distance #imgabs0# from the receiving end antenna to the previous scattering point and the Rayleigh distance d Rayleigh Different wavefront signal models #imgabs1# are used to fit the propagation of 5G signals in space based on the size comparison. The hybrid wavefront signal model is used to iteratively update the signal state information (CSI) of the receiving end using the spatial alternating generalized expectation maximization algorithm (SAGE) until the channel characteristic parameters #imgabs2# converge, thereby realizing channel parameter estimation. The present invention uses a hybrid of the plane wavefront model and the spherical wavefront model for estimation, which can better adapt to the indoor environment under the 5G environment, improve the accuracy of channel modeling in the indoor environment, and better describe the propagation of electromagnetic waves in the indoor environment.

The embodiment of the invention discloses a measurement method and device, a baseband chip, a terminal and a storage medium, and belongs to the technical field of communication. The method comprises the following steps: performing channel parameter estimation based on a reference signal to obtain a parameter estimation result; determining a target filter from the at least two candidate filters based on a parameter estimation result; performing channel filtering processing on the reference signal through a target filter to obtain a reference signal filtering result, the channel filtering processing being used for filtering interference and noise in the reference signal; a measurement term is calculated based on a reference signal and the reference signal filtering result. By adopting the method provided by the embodiment of the invention, the measurement accuracy of the terminal side can be improved.