144 results about "Kronecker product" patented technology

A transmitter and a transmitting method in a code division multiplexing (CDM) wireless communication system are provided. The transmitter includes a DC offset unit, a Barker code generating unit, a multiplier, a unipolar code generating unit, a Kronecker product unit, and a modulator. The DC offset unit transforms digital transmitting data to bipolar data, and the Barker code generating unit generates a Barker code. The multiplier multiplies the bipolar data with the Barker code and outputting the multiplying result, and the unipolar code generating unit generates a predetermined unipolar code. The Kronecker product unit multiplies the multiplying result from the multiplier and the unipolar code based on the Kronecker product, and outputs the result thereof, and the modulator modulates the output of the Kronecker produce unit through the On-Off keying modulation scheme.

The invention discloses a multiband signal reconstruction method based on a clustering sparse regularization orthogonal matching tracking algorithm, relates to the technical field of information and communication, and aims at solving a problem of restoring an original multiband signal from an unknown-sparseness multi-observation-value vector in a Xampling frame after the conversion through a continuous-finite module and sampling through a modulation bandwidth converter. Because many simulation signals met a multiband signal model in a process of signal processing, the method plays an important role in enabling the compressed sensing theory to be used for simulation signals. The basic idea of the method is to convert an infinite observation value vector problem into a single-observation-value vector problem. The method comprises the following steps: carrying out the column vectorization of observation values; carrying out the extension of an observation matrix through a Kronecker product; estimating a support set of the original signal through employing the above two results and signal sparseness estimation; finally reconstructing the signal, wherein the regularization idea is used in an estimation process of the support set.

The invention relates to the technical field of wireless communication and particularly a method for transmitting coding indication information and a method for determining a pre-coding matrix, a system and equipment. The objective of the invention is to solve the problem of performance reduction caused by a situation in which a codebook is directly applied to three-dimensional wave beam shaping/pre-coding technologies at present. The method for transmitting the coding indication information comprises the step that user equipment determines and transmits first pre-coding indication information, second pre-coding indication information and third pre-coding indication information, wherein the indication information is corresponding to the pre-coding matrix, wherein the pre-coding matrix is equal to a function matrix of a first component pre-coding matrix, a second component pre-coding matrix and a third component pre-coding matrix, wherein the first component pre-coding matrix is a diagonal matrix, the second component pre-coding matrix is a diagonal matrix, the third component pre-coding matrix is composed of a wave beam rotating vector, wherein the beam rotation vector is equal to the Kronecker product of two vectors. With the method for transmitting the indication information, the method for determining the pre-coding matrix, the system and the equipment of the invention adopted, the performance of the three-dimensional wave beam shaping/pre-coding technologies can be improved.

The invention relates to a block encoder and an encoding method of a polarization code, and belongs to the technical field of encoding devices. According to the block encoder and the encoding method of the polarization code, the problems of high algorithm complexity and relatively low processing speed existing in the prior art are solved. The block encoder comprises an input encoding module, a generator matrix module and a multiplier module; and each module is provided with multiple exclusive-OR gates and multiple time delay units. The encoding method comprises the steps of grouping to-be-encoded input information sequences; constructing a generator matrix of the polarization codes; and generating an encoding result. The principle of the block encoder and the encoding method of the polarization code is that a matrix GN is compressed, a position containing F<Kronecker product k> is replaced by 1, a K*K zero matrix is replaced by zero, the compressed matrix is the generator matrix F< Kronecker product (n-k)> of the encoder; K information bits are input to the information sequences per each clock; and a result of corresponding encoding operation for a matrix GK is output after the result is subjected to selection and exclusive-OR operation. According to the block encoder and encoding method of the polarization code, K-bit data can be input at each clock, and N-bit data can be output after 1+N/K clocks, so that encoding delay is reduced, and the encoding efficiency is improved.

The invention discloses a large-scale MIMO system limiting feedback method based on compressive sensing. In a large-scale MIMO limiting feedback system, an Nh*Nv-dimensional uniform planar array (UPA) is adopted at a base station, and a linear array is adopted at a user terminal. The large-scale MIMO system limiting feedback method comprises the following steps: firstly, seeking a sparse base matched with a large-scale MIMO horizontal-dimensional channel and a vertical-dimensional channel by using a compressive sensing (CS) theory, thereby furthermore obtaining a two-dimensional united sparse base matched with a large-scale MIMO channel according to a Kronecker product; secondly, projecting an observation matrix irrelevant to the sparse base to a low-dimensional space, thereby obtaining an observation signal, quantifying the signal, and feeding the quantified signal back to the base station; finally, reconstructing channel state information at the base station by using an orthogonal matching pursuit (OMP) algorithm. The utility model provides a simple and efficient implementation method for the large-scale MIMO limiting feedback system.

The invention provides a low-complexity two-dimensional angle and polarization parameter joint estimation method. Cross electric dipoles are adopted to form a uniform plane square matrix in an XOY coordinate system to receive signals. Firstly, an array manifold matrix of an X axis is solved from a covariance matrix of received data by fully utilizing the rotation invariant characteristic of a receiving array. Then, an array manifold matrix and a polarization-sensitive matrix of a Y axis are gradually solved by utilizing the characteristic of a Kronecker product between vectors. Finally, a DOA parameter and a polarization parameter are solved by comprehensively considering relationships between internal elements of the three matrixes. In a parameter solution process, the parameters can be automatically paired by utilizing the characteristic of the Kronecker product between the vectors, and an additional algorithm is not needed; since the computation process only relates to the multiply-add operation between the matrixes, relative to other automatic pairing algorithms, the complex operation such as matrix SVD is avoided, the computation complexity is effectively reduced and the quick realization is facilitated.

The invention discloses a sparse model of a multi-directional model, wherein the sparse model can ensure remarkable improvement on algorithm complexity and storage space without Kronecker product. The sparse model of the multi-directional model is represented by a formula x=B*1D1*2*D2...NDN, wherein ||B||<=K. In the formula, tension x represents a tension product between an N-directional sparse tension B which belongs to R<M1*M2*...*MN and a series of sparse dictionary Dn which belongs to R<In*Mn>, wherein In<=Mn, Dn is defined as the dictionary in an n-th direction, K is sparsity and is used for representing the number of non-zero elements in a sparse coefficient B. The invention furthermore provides a reconstruction method of the sparse model and a dictionary training method of the reconstruction method.

The invention belongs to the technical field of communications, and discloses a beam-forming method for NLOS scenarios in massive MIMO, comprising: obtaining a channel estimation matrix at the base station side; performing autocorrelation on the channel estimation matrix to obtain a spatial correlation matrix; constructing an optimization problem according to a maximum received signal-to-noise ratio criterion; performing equivalent minimization on the optimization problem; solving the optimal weight vector; performing maximum naturalization; performing Crohneck product with vertical antenna weight; and multiplying by transmission data. The invention has the advantages of low sensitivity to channel time-varying characteristics, strong anti-non-line-of-sight NLOS capability, low algorithm complexity and simple implementation, and finally improves the receiving power of the desired user. The invention solves the problems that the beam-forming method of the prior art has weak resistance tochannel time-varying, and cannot effectively improve the received power of the desired user in the case of multipath, and the algorithm has high complexity.

Digital files are compressed using a process including Schmidt decompositions of matrices using an algorithm, termed ‘BSD’ herein, which is based on an algebraic method generalizing QR decomposition. Software analyzes an input file and initially identifies a matrix M, with entries within a predefined set of integers, within the file. Next, essential entries are defined, extracted from M, that contain sufficient information to recover Musing BSD. The compressed file includes the essential entries and their positions within M. To achieve an encryption process, software encrypts the pattern matrix that includes the positions of the essential entries of M. To achieve a lossy compression, software identifies essential entries that contain sufficient information to recover an approximation to M for which the quality is determined by an error threshold. For a more efficient lossy compression, software uses singular value decomposition, BSD, and other signal processing of M.

The invention discloses a novel channel estimation method for a multi-user 3D MIMO system, and the method comprises the steps: carrying out the modeling through employing an included angle between a direction of arrival and an x axis and an included angle between the direction of arrival and a y axis of a planar array antenna, and projecting a 3D MIMO channel to the x axis and the y axis; in the uplink preamble stage, allocating an orthogonal pilot frequency sequence to each user, and obtaining paired spatial features and optimal rotation angles of channels projected to the x axis and the y axis by each user; grouping the obtained paired spatial features, distributing the same pilot frequency information in the groups, and distributing orthogonal pilot frequency sequences among the groups;carrying out channel estimation through the spatial feature and the optimal rotation angle of the (n-1)th coherence time in the group of the nth coherence time after the leader stage, and then dynamically updating the spatial feature and the optimal rotation angle of the user; and repeating the intra-group channel estimation method to obtain spatial features and optimal rotation angles of all users in the cell, reconstructing channels of an x axis and a y axis of all users in the cell, and generating a 3D MIMO channel through a Kronecker product.

The invention discloses a radar robust space-time adaption processing method based on an iterative subspace tracking algorithm. The method comprises the following steps of (1) according to a space-time data matrix X received by a known radar, acquiring P space-time data matrixes of a distance unit; (2) according to the space-time data matrix X received by the radar, writing a corresponding space-time adaptive weight matrix W as the following equation: W=uvT, and giving an optimization problem which is used to solve a space weight vector u and a time weight vector v, wherein the optimization problem is defined in the description; (3) using the iterative subspace tracking algorithm to solve and acquire the space weight vector u and the time weight vector v and calculating a robust space-time steering vector s; (4) carrying out Kronecker product on the robust space-time steering vector s and the space-time data matrix X received by the radar so as to obtain a radar space-time data matrix after adaptive space-time processing so that a target signal after the adaptive space-time processing is obtained.

The invention discloses an MIMO (Multiple-Input Multiple-Output) wireless channel modeling method fusing a smart antenna, and belongs to the technical field of wireless communication. The method comprises the following steps: firstly, constructing a transmitting end antenna correlation matrix and a receiving end wave beam correlation matrix, and taking a Kronecker product of the transmitting end antenna correlation matrix and the receiving end wave beam correlation matrix as an integral correlation matrix; taking a matrix obtained through Cholesky decomposition of the integral correlation matrix as a spatial correlation forming matrix; generating a spatial independent MIMO channel fading coefficient; allocating power to different delay paths according to power delay distribution of a channel; calculating a channel coefficient matrix of all delay paths according to a time-frequency fading characteristic of an MIMO channel and the spatial correlation forming matrix; and lastly, building an MIMO wireless channel matrix fusing the smart antenna according to the channel coefficient matrix and path delays of all the delay paths according to a tapped delay line structure of a frequency selective channel. Through implementation of the method, a propagation channel of an actual MIMO-smart antenna fusion system can be approximated well.

The invention belongs to the technical field of geophysical exploration signal processing, and relates to a three-dimensional seismic data multiple suppression method based on a local similarity coefficient. The method is based on a conventional three-dimensional surface related multiple wave pressing technology. The method comprises: calculating a local similarity coefficient spectrum of the multiple contribution gather of the contact survey line and the Radon transformation result; constructing a weighted threshold operator according to the similarity coefficient difference; using the Kronecker product of the original data and a weighted threshold operator, determining stationary phase overlay space, replacing a direct summation process of multiple wave connection measuring lines by superposition of Fresnel spaces, and the high-resolution multiple wave prediction method for the three-dimensional ocean seismic data is realized. The spatial false frequency generated by a conventional method is effectively suppressed, so that multiple wave prediction is more accurate, the precision and accuracy of multiple wave suppression are improved, and much convenience is brought to subsequentprocessing and explanation of seismic data processing.