47 results about "Channel quantization" patented technology

The invention discloses a channel quantization method of a multiuser MIMO system based on a limited feedback and a device thereof belonging to the wireless transmission technology field. The method comprises the following steps: firstly choosing a code word having a minimal included angle with a codebook from the codebook according to the channel state information, and calculating the quantized error; secondly choosing a code word vector having a minimal included angle with the quantized error from the codebook; projecting the channel vector to the space formed by the chosen two code word vectors and calculating to obtain a compound proportion factor; quantizing the compound proportion factor using a pre-generated quantization step set. A receiving terminal device comprises a channel condition information acquisition unit, a channel vector quantization unit and a quantization information feedback unit. The transmission terminal device comprises a feedback information reconstruction unit and a precoding unit. The channel quantization method of the invention can reduce the quantization error, improve the system capacity performance and have advantages of small used codebook and low complexity when the speed and capacity are the same.

The present invention relates to a transmission beamforming method and apparatus in an orthogonal frequency division multiplexing (OFDM)-based MIMO wireless system. In particular, the present invention relates to a transmission beamforming method in an OFDM-based MIMO wireless system and an apparatus therefor, wherein the transmission beamforming method comprises: estimating a channel from a received pilot signal and obtaining time for the estimating channel and 2D channel correlation information of a frequency band; obtaining estimated channel information based on the channel correlation information; obtaining differential information that represents a difference between the current channel and the estimated channel and quantizing the differential information; and generating a transmission beam weight by using a predefined code book from the quantized differential information. The present invention may also provide a method and apparatus for reducing the channel quantization error and feedback load by employing the OFDM-based MIMO in a wireless communication system using a transmission beamforming scheme, wherein a receiver estimates current channel information by using time and 2D channel correlation information of a frequency based on the previous channel information, compares the estimated current channel information with an actual channel and then feeds back the differential channel information, i.e., the difference between the estimated channel and the actual channel, to a transmitter.

A method and system for channel quantization for multiuser diversity are provided. A quantizer may utilize quantization levels determined based on an objective function J that corresponds to a performance metric for a finite-rate feedback multiuser downlink communication system. The quantization levels may be obtained based on the results of maximizing the objective function J by means of an optimization algorithm. The optimization algorithm may be a multivariate optimization algorithm that may be implemented utilizing an iterative approach. The quantizer may utilize the quantization levels to quantize channel state information (CSI) to achieve multiuser diversity in the finite-rate feedback multiuser system. The performance metric may be based on signal-to-noise ratio (SNR), bit error rate (BER), and / or system capacity. The quantization levels may be utilized in a multiuser system where distributed quantization is needed for optimal selection.

Aspects of a method and system for an efficient channel quantization method or MIMO pre-coding systems may include quantizing channel state information in a MIMO pre-coding system onto a codebook, which comprises one or more unitary matrices, using a cost function; selecting a quantization function that enables the quantizing based on a number of receive antennas and a number of transmit antennas associated with the MIMO pre-coding system; and selecting the cost function from a set of cost functions based on the number of receive antennas and the number of transmit antennas. The channel state information may be a matrix Ĥ. The set of cost functions may comprise function f(A), which may be defined by the following relationships:f⁡(A)=∑i=1N⁢⁢∑j=1,j≠iN⁢⁢ai,j2⁢⁢and / or⁢⁢f⁡(A)=∑i=1N⁢⁢∑j=1,j≠iN⁢⁢ai,j2-∑i=1N⁢⁢ai,iwhere A is a matrix of size N by N and aij is element (i,j) of matrix A.

Embodiments of the present invention provide a method and device for reducing complexity of channel quantization. The method comprises: determining, on the basis of whether a measurement feedback parameter configured by a channel state information (CSI) process satisfies a predetermined condition, a CSI report time-domain position and a time interval requirement parameter Nrpt-ref for a CSI reference resource time-domain position, or determining a CSI trigger time-domain position and a time interval requirement parameter Nrpt-ref for a CSI reference resource time-domain position; determining, according to the determined time interval requirement parameter Nrpt-ref and the CSI report time-domain position, the CSI reference resource time-domain position, or determining, according to the determined time interval requirement parameter Nrpt-ref and the CSI trigger time-domain position, the CSI reference resource time-domain position; and performing CSI quantization according to the determined CSI reference resource time-domain position.

A method and system for channel quantization for multiuser diversity are provided. A quantizer may utilize quantization levels determined based on an objective function J that corresponds to a performance metric for a finite-rate feedback multiuser downlink communication system. The quantization levels may be obtained based on the results of maximizing the objective function J by means of an optimization algorithm. The optimization algorithm may be a multivariate optimization algorithm that may be implemented utilizing an iterative approach. The quantizer may utilize the quantization levels to quantize channel state information (CSI) to achieve multiuser diversity in the finite-rate feedback multiuser system. The performance metric may be based on signal-to-noise ratio (SNR), bit error rate (BER), and / or system capacity. The quantization levels may be utilized in a multiuser system where distributed quantization is needed for optimal selection.

Provided are, among other things, systems, methods and techniques for quantizing a joint-channel-encoded audio signal, e.g., by: identifying a target quantization unit for reduction of quantization step size based on quantization errors; determining whether the target quantization unit has been jointly sum / difference encoded with another quantization unit; if the target quantization unit has been jointly sum / difference encoded with another quantization unit, then (i) designating the sum or difference channel quantization unit as a target S / D quantization unit in based on which has a greater quantization error and (ii) re-quantizing the target S / D channel quantization using a decreased quantization step size; recalculating the quantization error for the target quantization unit; and repeating the process until a specified criterion is satisfied.

The embodiment of the invention provides a quantization processing method and device, and a quantization processing chip, and the method comprises the steps: firstly, determining the initial quantization parameter of each channel based on the distribution characteristics of the network parameters of each channel, and enabling the initial quantization parameter of one channel to be the optimal quantization parameter theoretically meeting the distribution characteristics of the network parameters of the channel; however, the initial quantization parameter may not satisfy a layer quantization hardware deployment condition; therefore, the optimized quantization parameter corresponding to each channel is searched in the search space determined on the basis of the initial quantization parameter, the quantization performance of the searched optimized quantization parameter is close to that of the initial quantization parameter, and a layer quantization hardware deployment condition can be met, so that the method can be applied to a general quantization processing chip, and the quantization performance of the universal quantization processing chip is close to that of a channel quantization mode.

The invention discloses a deep learning model reasoning method, system and device, and a computer medium. The method comprises the following steps: determining channel quantization parameters of each channel in a target deep learning model; determining a branch quantization parameter of the model branch based on the channel quantization parameter according to a relationship between a channel in the target deep learning model and the model branch; quantizing the target deep learning model based on the branch quantization parameters to obtain a quantized deep learning model; and reasoning based on the quantized deep learning model to obtain a reasoning result. In the application, the channel quantization parameter of each channel in the target deep learning module is determined, fine-grained quantization parameter determination is realized, the branch quantization parameter of the model branch is determined based on the channel quantization parameter, reasoning is performed based on the quantized deep learning model, and the reasoning result is obtained. The deep learning model reasoning based on the fine-grained channel quantization parameters is realized, and the reasoning precision of the deep learning model is improved.

The invention discloses a power distribution method and equipment, which are used for solving the problem that the application range of an RS transmission strategy is limited. The method comprises thefollowing steps of: a network device obtains K channel quantization error mean values, wherein the K channel quantization error mean values are in one-to-one correspondence with the K terminal devices, and the ith channel quantization error mean value in the K channel quantization error mean values is determined according to an estimation channel vector and a quantization channel vector corresponding to a signal transmitted between the ith terminal device and the network device; and the network device determines a power distribution parameter value, wherein the power distribution parameter value is determined according to the K channel quantization error mean values. By adopting the method, the RS transmission strategy does not depend on an RVQ codebook, and the method is suitable for more codebooks.

The invention discloses an effective capacity optimization method of multi-antenna transmission under feedback limitation. Firstly, a source node pre-codes the information, and then performs data transmission with a destination node in a beam forming manner. In the precoding of the source node, channel state information needs to be obtained, so that the destination node performs channel estimationat first, and feeds back the estimated channel state information to the source node after quantifying the same. As the accuracy of channel quantization is higher, the precoding performance of the source node is better, but this also increases the feedback cost. By application of the effective capacity optimization method of multi-antenna transmission under feedback limitation disclosed by the invention, the optimal channel feedback quantization bit is sought, and the effectiveness and the reliability of wireless transmission are improved under the condition of limited feedback cost, and the effective capacity of the multi-antenna transmission is significantly improved at the same time.

The invention discloses a method for channel state information feedback and receiving. The method is used for realizing informing an opposite terminal of a precoding matrix to be adopted through channel state information feedback, so that the indicated precoding matrix can be used for carrying out signal processing, and the spatial channel quantization precision can be further improved. The method comprises the following steps: selecting the precoding matrix according to estimated channel information, wherein the precoding matrix is a 4-antenna precoding matrix composed of partial elements in a 8-antenna precoding matrix; and sending index information corresponding to the selected precoding matrix. The invention also discloses a device which is used for realizing the method.

The present invention relates to a transmission beamforming method and apparatus in an orthogonal frequency division multiplexing (OFDM)-based MIMO wireless system. In particular, the present invention relates to a transmission beamforming method in an OFDM-based MIMO wireless system and an apparatus therefor, wherein the transmission beamforming method comprises: estimating a channel from a received pilot signal and obtaining time for the estimating channel and 2D channel correlation information of a frequency band; obtaining estimated channel information based on the channel correlation information; obtaining differential information that represents a difference between the current channel and the estimated channel and quantizing the differential information; and generating a transmission beam weight by using a predefined code book from the quantized differential information. The present invention may also provide a method and apparatus for reducing the channel quantization error and feedback load by employing the OFDM-based MIMO in a wireless communication system using a transmission beamforming scheme, wherein a receiver estimates current channel information by using time and 2D channel correlation information of a frequency based on the previous channel information, compares the estimated current channel information with an actual channel and then feeds back the differential channel information, i.e., the difference between the estimated channel and the actual channel, to a transmitter.

The invention provides a channel randomization circuit and method based on a time-interleaved ADC, and the circuit comprises a channel selection module which is used for outputting M clock receiving control signals and N coded data receiving control signals according to a main clock and a generated random number; the multi-phase clock distribution module is used for generating N multi-phase clocks according to a sampling main clock, redistributing the multi-phase clocks according to the clock receiving control signal, and outputting M redistributed clock signals; the time-interleaved ADC module is used for outputting M pieces of output data and a corresponding number of channel quantization completion signals according to the redistribution clock signal; the adjustable delay module is used for setting the delay size of the data receiving control signal; and the time sequence distribution control module is used for controlling the output data to be sequentially arranged and output according to a time sequence according to the delayed data receiving control signal and the channel quantization completion signal.

This application relates to the method and network of time-frequency channel attention weight calculation and vectorization, including: using spherical embedding normalization to preprocess the logarithmic Fourier magnitude spectrum; segmenting the logarithmic Fourier magnitude spectrum preprocessing Process data into short-term spectral segments to generate multi-channel tensors; use the attention mechanism to calculate the attention weight of each channel in the time direction and frequency direction; obtain time-frequency attention by matrix multiplication of the attention weights in the time direction and frequency direction Weight coefficient tensor; use the attention mechanism to calculate the attention weight tensor of each channel in the time-frequency attention weight coefficient tensor; use the attention weight tensor of each channel to obtain vectorization in the time and frequency directions through one-dimensional convolution Results; concatenate the vectorized results of the time direction and frequency direction of at least one channel, and use one-dimensional convolution to obtain the channel vectorized results; calculate the average value of the channel vectorized results of the short-term spectrum segment and use it as the entire long-term The results of the time-to-speech correspondence.