# Efficient filter weight computation for mimo system

FIELD: radio engineering, communication.

SUBSTANCE: invention relates to communication engineering and can be used in MIMO systems. Techniques to efficiently derive a spatial filter matrix are described. In a first scheme, a Hermitian matrix is iteratively derived based on a channel response matrix, and a matrix inversion is indirectly calculated by deriving the Hermitian matrix iteratively. The spatial filter matrix is derived based on the Hermitian matrix and the channel response matrix. In a second scheme, multiple rotations are performed to iteratively obtain first and second matrices for a pseudo-inverse matrix of the channel response matrix. The spatial filter matrix is derived based on the first and second matrices. In a third scheme, a matrix is formed based on the channel response matrix and decomposed to obtain a unitary matrix and a diagonal matrix. The spatial filter matrix is derived based on the unitary matrix, the diagonal matrix, and the channel response matrix.

EFFECT: high throughput of transmission channels.

13 cl, 4 dwg

The technical field to which the invention relates.

The invention in General relates to the field of communications and, more specifically, to methods of calculating the weights of the filters in the communication system.

The level of technology

In the communication system with multiple inputs and multiple outputs (MIMO MVPS) for data transmission using multiple (T) transmit antennas of a transmitting station, and many (R) receiving antennas of the receiving station. A MIMO channel formed by the T transmit antennas and R receiving antennas may be decomposed into S spatial channels, where S≤min {T, R}. S spatial channels may be used to transmit data in such a way to achieve greater overall throughput and/or higher reliability.

The transmitting station can simultaneously transmit T data flows through the T transmit antennas. In these data streams have distortion in accordance with the response of the MIMO channel, and their quality is additionally deteriorates due to exposure to noise and interference. The receiving station receives the transmitted data streams through R receiving antennas. The received signal from each receiving antenna contains a scaled version of the T data streams transmitted by a transmitting station. Transmitted data streams, thus dispersed among the R signals received through R receiving antennas. Reception with anzia then performs spatial processing receiver for R received signals, using the matrix spatial filter, to recover the transmitted data streams.

To determine the weights matrix spatial filter requires a lot of processing. This is because the matrix spatial filter is usually obtained on the basis of the function that contains the inverse of the matrix, and direct calculations of matrix inversion require volumetric calculations.

Thus, this technology requires the development of methods for efficient calculation of the weighting coefficients of the filter.

The invention

Here is described the method of calculating the effective weighting matrix spatial filter. These techniques allow to exclude a direct calculation of matrix inversion.

In the first variant embodiment for obtaining matrix__M__spatial filter Hermitian matrix P iteration is obtained on the basis of the matrix__H__response channel, and the inverse of the matrix indirectly calculated by iterative obtain a Hermitian matrix. Hermitian matrix can be initialized to the identity matrix. One iteration is then performed for each row of the matrix of the channel response, and effective sequence of calculations performed for each iteration. For the i-th iteration of the receive intermediate vector__a___{i}line-based vector__h__*r*_{i}get on the basis of the intermediate vector and row vector row of the channel response. Intermediate matrix__C___{i}also get on the basis of the intermediate vector line. Hermitian matrix, then update based on scalar values and the intermediate matrix. After all iterations, the gain matrix spatial filter based on the Hermitian matrix and the matrix of the channel response.

In the second variant embodiment perform many turns to iteratively obtain a first matrix__P__^{1/2}and the second matrix__B__for pseudouridines matrix of the channel response. One iteration is performed for each row of the matrix of the channel response. For each iteration form a matrix__Y__containing the first and second matrix from the previous iteration. Many turns of Givens then perform for the matrix__Y__to zero the elements in the first row of the matrix, to obtain the updated first and second matrix for the next iteration. After all iterations are completed, the receive matrix spatial filter based on the first and second matrices.

In the third variant embodiment form a matrix__X__based on the matrix of the channel response and decompose (for example, used the eat decomposition own values)
to obtain a unitary matrix__V__and a diagonal matrix__Λ__. The decomposition can be obtained in the iterative execution of rotations Jacobi matrix__X__. Matrix spatial filter is then obtained on the basis of a unitary matrix, a diagonal matrix and the matrix of the channel response.

Various aspects and embodiments of the invention are described in more detail below.

Brief description of drawings

Properties and essence of the present invention will be clearer from the detailed description below, which should be read in conjunction with the drawings in which the same numbers of reference positions indicated corresponding elements in all the drawings.

In figure 1, 2 and 3 shows the processing performed to calculate the matrix of spatial MMSE filter (ISCED, the minimum mean square error), based on the first, second and third variants of the embodiment, respectively.

Figure 4 shows the block diagram of the access point and user terminal.

Detailed description of the invention

The word "exemplary"as used here, means "used as an example, a case or illustration". Any variant execution or design described herein as "exemplary"is not necessarily should be considered as preferred or predominant compared to the other options run or designs.

Described here are methods for calculating weighting coefficients of the filter can be used for MIMO systems with single-carrier and MIMO systems with multiple carriers. Many of bearing can be obtained using multiplexing orthogonal frequency division signals (OFDM), multiple access frequency division with alternation (IFDMA), localized multiple access frequency division (LFDMA), or some other modulation techniques. OFDM, IFDMA and LFDMA effectively share the total bandwidth of the system into multiple (K) orthogonal frequency papolos, which are also called tones, subcarriers, the signal elements and frequency channels. Each podporou associated with the corresponding subcarrier, which can be modulated data. In the system of the OFDM symbols of the modulation transfer in the frequency domain for all or a subset K papolos. In IFDMA transmit the modulation symbols in the field of time popoloca which are evenly distributed on K popoloca. In LFDMA transmit the modulation symbols in the field of time and usually in the neighboring popoloca. For clarity, most of the following description is directed to a MIMO system with a single carrier, which uses one subcarriers.

A MIMO channel formed by multiple (T) transmit antennas at a transmitting station, and numerous ® receiving antennas in the reception of the article is ncii,
can be characterized by the matrix__H__response channel size RxT, which can be specified as:

Equation (1)

where h_{i,j}*,*for i=1,...,R and j=1,...,Tindicates the strengthening of links or complex gain of the channel between the transmit antenna jand receiving antenna i*;*and

__h___{i}is a vector of strings of the channel response 1×T to the receiving antenna i*,*which represents the i-th row of the matrix__H__.

For simplicity, in the following description it is assumed that the MIMO channel has full rank and that the number of spatial channels (S) is defined as: S=T≤R

The transmitting station may transmit T modulation symbols simultaneously from the T transmit antennas in each symbol period. The transmitting station may perform or may perform spatial processing for the modulation symbols prior to transmission. For simplicity, the following description assumes that each modulation symbol is passed through the transmitting antenna without any spatial processing.

The receiving station receives R received symbols from the R receiving antennas in each symbol period. The received symbols can be expressed as:

Equation (2)

where__s__is a vector of size T×1, where T is the modulation symbols transmitted is erediauwa station;

__r__is a vector of size R×1, where R is the received characters receive in the receiving station R receiving antennas; and

__n__is the noise vector of size R×1.

For simplicity, we can assume that the noises are additive white Gaussian noise (AWGN) with zero mean vector and covariance matrix δ^{2}_{n}×__I__where δ^{2}_{n}isa noise variance, and__I__represents the identity matrix.

In the receiving station may use different methods of spatial processing for recovering modulation symbols transmitted by a transmitting station. For example, the receiving station may perform spatial processing of the receiver with minimum mean square error (MMSE), as follows:

Equation (3)

where__M__is a matrix of spatial MMSE filter of size T×R;

__P__represents the Hermitian covariance matrix of size T×T error estimates__s__-;

is a vector of size T×1, which is an estimate of s; and

*"*^{H}*"*denotes conjugate transposition.

Matrix__P__the covariance can be specified as__P__=E[(__s__-)×(__s__-
)^{H}], where E[] represents an operation of mathematical expectation.__P__also is a Hermitian matrix, the off-diagonal elements which have the following properties p_{i,j}=p*_{i,j}where "*" denotes a complex conjugate of a number.

As shown in equation (3), matrix__M__spatial MMSE filter is the calculation of the converted matrix. The direct calculation of the matrix inversion requires a large amount of computer operations. The matrix of spatial MMSE filter can be more effectively obtained on the basis of the embodiments, described below, which allow you to indirectly calculate the inverse of the matrix using an iterative process, instead of directly calculating the conversion matrix.

In the first variant embodiment of the calculation of the matrix__M__spatial MMSE filter count Hermitian matrix__P__based on the Riccati equation. Hermitian matrix P can be expressed as follows:

Equation (4)

Hermitian matrix__P___{i}the size of TxT can be defined as:

Equation (5)

Lemma matrix inversion can be applied to equation (5) to obtain the following:

Equation (6)

where*r*_{i}represents scalarmultiply value.
Equation (6) is called the Riccati equation. Matrix__P___{i}can be initialized as__P___{0}=•__I__. After the execution of R iterations of equation (6), for i*=*1,...,R are matrix__P___{R}as the matrix__P__or__P__=__P___{R}.

Equation (6) can be multiplied by certain coefficients to obtain the following:

Equation (7)

where matrix__P___{i}initialize as__P___{0}=__I__and the matrix__P__get as__P__=•__P___{R.}Equations (6) and (7) differ from the solutions of the equation (5). For simplicity used the same variables__P___{i}and r_{i}for both equations (6) and (7), even though these variables have different values in the two equations. The final results obtained by the equations (6) and (7), that is,__P___{R}for equations (6) and•__P___{R}for the equation_{}(7),_{}equivalent._{}However, calculations for the first iteration of equation (7) are simplified thanks to the use of__P___{0}as the identity matrix.

Each iteration of equation (7) can be performed as follows:

Equation (8a)

Equation (8b)

<> Equation (8c)Equation (8d)

where__a___{i}is a vector of intermediate rows 1×T elements with complex value; and

__C__represents an intermediate Hermitian matrix of size T×T.

In the system (8) equations sequence of operations is structured for efficient calculation using hardware. A scalar value r_{i}I hope before the matrix__C___{i}. Division by r_{i}in equation (7) is achieved by means of an inversion and multiplication. The treatment of r_{i}can be performed in parallel with the calculation of__C___{i}. The treatment of r_{i}is achieved with a shift for normalization of r_{i}and with the use of a reference table to obtain the converted values of r_{i}. The normalization of r_{i}can be compensated by multiplying by__C___{i}.

Matrix__P___{i}initialize as a Hermitian matrix, or__P___{0}=__I__and it remains Hermitian matrix in all following iterations. Therefore, only the upper (or lower) diagonal matrix need be calculated for each iteration. After R iterations are matrix__P__as__P__=•__P___{R.}The matrix of spatial MMSE filter can then be calculated as follows:

Equation (9)

Figure 1 shows a process 100 calculation of the matrix__M__spatial MMSE filter based on the first variant embodiment. Matrix__P___{i}initialized as__P___{0}=1 (block 112), and the index i is used to denote the number of iteration is initialized as i=1 (block 114). Then execute R iterations of the Riccati equation.

Each iteration of the Riccati equation is performed by block 120. For*i*iteration vector__a___{i}the intermediate line is calculated on the basis of the declared vector__h___{i}the channel response and Hermitian matrix__P___{i+1}the previous iteration, as shown in equation (8a) (block 122). A scalar value r_{i}count_{}based on the variance of*δ*^{2}_{n}noise vector__a___{i}intermediate string and vector__h___{i}prompt response of the channel, as shown in equation (8b) (block 124). Scalar*r*_{i}after that it is converted (block 126). Intermediate matrix__C___{i}calculated on the basis of__a___{i}intermediate line, as shown in equation (8c) (block 128). Matrix__P___{i}then update based on the inverted scalar value of*r*_{i}and the intermediate matrix__C___{i}as shown in equation (8d) (block 130).

Then determine whether you have performed all the R iterations (block).
If the answer is negative, perform a sequential increment index i(block 134), and the process returns to block 122 to perform another iteration. Otherwise, if all R iterations were performed, calculate the matrix M MMSE spatial filter based on the Hermitian matrix__P___{R}for the last iteration, matrix__H__response channels and dispersion*δ*^{2}_{n}noiseas shown in equation (9) (block 136). Matrix__M__you can then use for spatial processing of the receiver,_{}as shown in equation (3).

In the second variant embodiment of the calculation of the matrix__M__spatial MMSE filter define a Hermitian matrix__P__by obtaining the square root__P__that is a__P__^{1/2}on the basis of an iterative procedure. Spatial processing receiver in equation (3) can be expressed as follows:

Equation (10)

where__U__=represents the augmented channel matrix of size (R+T)×T;

__U__^{p}represents pseudouridine matrix of size T×(R+T)resulting from the operation of the treatment or pseudouridine Moore-Penrose for__U__or__U__^{p}=(__U__^{H}∙__U__)^{-1}∙__U__^{H};

__0___{Tx1}represents the t of a vector of size T×1,
containing zeroes; and

__H__^{p}_{δn}is Podiatric of size T×R containing the first R columns__U__^{p}.

The QR decomposition can be performed for a matrix with augmented channel as follows:

Equation (11)

where__Q__is a matrix of size (R+T)×T with orthonormal columns;

__R__is a matrix of size T×T, which is not the identity matrix;

__B__is a matrix of size R×T containing the first R rows of the matrix__Q__; and

__Q___{2}is a matrix of size T×T, containing the last T rows of the matrix__Q__.

QR (KO, quasiorder) the decomposition in equation (11) decomposes the matrix of the augmented channel orthogonal matrix__Q__and not a single matrix__R__. Orthogonal matrix__Q__has the following property:__Q__^{H}•__Q__=__I__that means that the columns of an orthogonal matrix are orthogonal relative to each other, and each column has a single degree. Not the identity matrix is a matrix which can be calculated converts the matrix.

Hermitian matrix__P__can then be expressed as:

Equation (12)

__R__represents decomposition Koleczkowo or Quadra is hydrated root matrix P^{
-1}. Therefore,__P__^{1/2}is__R__^{-1}and is called the square root matrix__P__.

Pseudobradya matrix in equation (10) can then be expressed as:

Equation (13)

Pediatrica__H__^{P}_{δn}that also is a matrix of spatial MMSE filter can then be expressed as:

Equation (14)

Equation (10) can then be expressed as:

Equation (15)

Matrix__P__^{1/2}and__B__can be calculated iteratively as follows:

or Equation (16)

Equation (17)

where__Y___{i}is a matrix of size (T+R+1)×(T+1), containing elements derived from__P__^{1/2}_{i-1},__B___{i-1}and__h___{i};

__θ___{i}is a unitary transformation matrix of size (T+1)×(T+1);

__Z___{i}is a transformed matrix of size (T+R+1)×(T+1)containing the elements for P_{i}^{1/2},__B___{i}and*r*_{i};

__e___{i}is a vector of size R×1 unit (1,0) as the i-th element and with the other zero elements; and

__k___{i}is a vector of size T×1 and__I/u>
_{i}is a vector R×1, and both of them are insignificant.__

__Matrix P^{1/2}andBinitialize asP_{0}^{1/2}=•IandB_{0}=0_{RxT}.__

__The transformation in equation (17) can be performed iteratively, as described below. For clarity, each iteration of equation (17) is called outer iteration. R external iterations of equation (17) is performed for the R vector h_{i}the channel response for i=1,...,R. For each outer iteration unitary matrixδ_{i}the transformation in equation (17) is converted into the transformed matrixZ_{i}containing all zeros in the first row, except the first element. The first column of the transformed matrixZ_{i}contains r_{i}^{1/2},k_{i}andI_{i}. The last T columnsZ_{i}contain updatedP_{i}^{1/2}andB_{i}. The first column isZ_{i}you do not need to count, because onlyP_{i}^{1/2}andB_{i}used in the next iteration.P_{i}^{1/2}is an upper triangular matrix. After R outer iterations getP_{R}^{1/2}asP^{1/2}andB_{R}get asB. MatrixMspatial MMSE filter can then be calculated n the basis
P^{1/2}andBas shown in equation (14).__

__For each outer iteration ithe transformation in equation (17) can be performed by successive zero one element in the first rowY_{i}at the same time with 2×2 Givens rotations. T inner iterations Givens rotation can be performed to reset the last T elements in the first rowY_{i}.__

__For each outer iteration i, matrix Y_{i,j}can be initialized asY_{i1}=Yi. For each inner iteration j for j=1,...,T, the outer iteration i, originally form PediatricoY'_{i,j}size (T+R+1)×2 containing the first and the (j+1)-th columnsY_{i,j}. Then perform the Givens rotation to pieces and usesY'_{i,j}to generate pieces and usesY"_{i,j}size (T+R+1)×2 containing zero in the second element in the first row. The Givens rotation can be expressed as:__

__Equation (18)__

__where G_{i,j}is a rotation matrix of the Givens of size 2×2 for the j-th inner iteration of the i-th outer iteration, which is described below. MatrixY_{i,j+1}then form first by settingY_{i,j+1}=Y_{i,j}then replace the first columnY_{i,j+1}the first columnY"_{i,j}and then replace the (j+1)-th column of the matrixY_{i,j+1}is that the column
Y"_{i,j}. The Givens rotation, thus, modifies only two columnsY_{i,j}j-th inner iteration to obtainY_{i,j+1}for the next inner iteration. The Givens rotation can be performed in place of the two columnsY_{i}for each inner iteration, resulting in an intermediate matrixY_{i,j},_{}Y'_{i,j},_{}Y"_{i,j}and_{}Y_{i,j+1}not needed and described above for clarity.__

__For the j-th inner iteration of the i-th outer iteration matrix G_{i,j}the Givens rotation is determined based on the first element (which is always a valid value) and (j+1)-th element in the first row of the matrixY_{i,j}. The first element may be denoted as α, and (j+1)-th element can be designated as b-e^{jθ}. MatrixG_{i,j}turn_{}The Givens can then be obtained in the following way:__

__Equation (19)__

__where c=and s=for equation (19).__

__Figure 2 shows a process 200 that is designed to calculate the matrix Mspatial MMSE filter based on the second variant embodiment. MatrixP_{i}^{1/2}initialize P_{0}^{1/2}=•Iand the matrixB_{i}initializer the Ute as
B_{0}=0(block 212). The index i to denote the number of external iterations are initialized as i=1 and the index j is used to denote the number of inner iteration, initialize j=1 (block 214). Then execute R outer iterations unitary transformation in accordance with equation (17) (block 220).__

__For the i-th outer iteration first form a matrix Y_{i}with vectorh_{i}prompt response of the channel matrixP_{i-1}^{1/2}andB_{i-1}as shown in equation (17) (block 222). MatrixY_{i}then referred to as matrixY_{i,j}for the inner iterations (block 224). T inner iterations of the Givens rotation is then performed for the matrixY_{i,j}(block 230).__

__For the j-th inner iteration gain matrix G_{i,j}the Givens rotation based on the first and (j+1)-th elements in the first rowY_{i,j}as shown in equation (19) (block 232). MatrixG_{i,j}the Givens rotation is then applied to the first and the (j+1)-th columnsY_{i,j}to getY_{i,j+1}as shown in equation (18) (block 234). Then determine whether you have performed all the T inner iteration (block 236). If the answer is "No", then the index j is increased by one unit (block 238), and processing returns to block 232 to perform other internal iteration.__

__If all T inner iteration b is performed for the current outer iteration,
and the answer is "Yes" to block 236, then the last Y_{i,j+1}equalZ_{i}in equation (17). An updated matrixP_{i}^{1/2}andB_{i}get out the lastY_{i,j+1}(block 240). Then determine whether you have performed all the R outer iterations (block 242). If the answer is "No", then the index i is increased by one unit, and the index j re-initialize j=1 (block 244). Processing then returns to block 222 to perform other external iteration withP_{i}^{1/2}andB_{i.}Otherwise, if all R outer iterations were performed, and the answer is "Yes" to block 242, then calculate the matrixMspatial MMSE filter based onP_{i}^{1/2}andB_{i}as shown in equation (14) (block 246). The matrix M can then be used for spatial processing of the receiver as shown in equation (15).__

__In the third variant embodiment of the calculation of the matrix M MMSE spatial filter performs the decomposition on their own values P^{-1}as follows:__

__Equation (20)__

__where Vis a unitary matrix T×T eigenvectors; and__

__Λ__is a diagonal matrix of size T×T with a valideigenvalues along the diagonal.

__RA is a suggestion for eigenvalues Hermitian matrix
X_{2x2}2×2 can be obtained using different techniques. In a variant embodiment decomposition own valuesX_{2x2}receive by performing complex Jacobi rotation forX_{2x2}to obtain matrixV_{2x2}2×2 eigenvectorsX_{2x2}. X_{2x2}andV_{2x2}can be specified as:__

__Equation (21)__

__V___{2x2}can be calculated directly from__X___{2x2}as follows:

__Equation (22a)__

__Equation (22b)__

__Equation (22c)__

__Equation (22d)__

__Equation (22e)__

__Equation (22f)__

__Equation(22g)__

__Equation (22h)__

__Equation (22i)__

__Equation (22j)__

__Equation (22k)__

__Expansion eigenvalues Hermitian matrix Xof size T×T, which is greater than 2×2, can be performed in an iterative process. In this iterative process, repeatedly use what is the Jacobi rotation to zero the off-diagonal elements in
X. For the iterative process, the index i denotes the iteration number and is initialized as i=1.Xis a Hermitian matrix of size T×T, which must be decomposed, and is installed asX=P^{-1}. MatrixD_{i}is an approximation of a diagonal matrixΛin equation (20) and is initialized asD_{0}=X. MatrixVis an approximation of the unitary matrixVin equation (20) and is initialized asV_{0}=I.__

__A single iteration of the Jacobi rotation to update matrix D_{i}andV_{i}can be performed as follows. First Hermitian matrixD_{pq}2×2 is formed on the basis of the current matrixD_{i}as follows:__

__Equation (23)__

__where d _{p,q}represents the element at location (p,q) matrixD_{i}, p{1,...,T}, g{1,...,T} and p≠q.D_{pq}is_{}PediatricoD_{i}2×2, and four elements of D_{pq}represent the four elements at locations (p, p), (p, q), (q, p) and (q, q) matrixD_{i.}The indices p and q may be selected, as described below.__

__Then perform the decomposition on their own values D_{pq}as shown in equation (22), obtained for the I of the unitary matrix
V_{pq}2×2 eigenvectorsD_{pq}. To decompose on their own valuesD_{pq,}X_{2x2}in equation (21) is replaced byD_{pq}andV_{2x2}from equation (22j) or (22k) are asV_{pq}.__

__The matrix of T _{pq}complex Jacobi rotation TxT size is then formed withV_{pq,}T_{pq}and represents the identity matrix with four elements at locations (p, p), (p, q), (q, p) and (q, q), which are replaced by the elements of v_{1,1}v_{1,2}v_{2,1}and v_{2,2}accordingly , matrixY_{pq}.__

__Matrix D_{i}then updated as follows:__

__Equation (24)__

__Equation (24) two zeroes off-diagonal element at locations (p, q) and (q, p)in the matrix D_{i}. The calculation can change the values of the other off-diagonal elements inD_{i}.__

__Matrix V_{i}also update as follows:__

__Equation (25)__

__V___{i}can be viewed as a matrix of cumulative transformations, which contains all matrix__T___{pq}turn Jacobi used for__D___{i}.

__Each iteration of the Jacobi rotation resets the two off-diagonal matrix element Di. The number of iterations of Jacobi rotation can be performed for different testing the response of the indices p and q,
to reset all off-diagonal elementsD_{i}. One pass through all possible values of the indices p and q may be performed as follows. The index p is sequentially changes from 1 up to T-1 in increments of the unit. For each value of p, the index q is sequentially changed from p+1 to T in increments of the unit. The Jacobi rotation performed for each different combination of values of p and q. Many passages can be made up untilD_{i}andV_{i}will not provide reasonably accurate estimatesΛandVrespectively.__

__Equation (20) can be rewritten as follows:__

__Equation (26)__

__where Λ^{-1}is a diagonal matrix whose elements represent the converted values of the corresponding elements ofΛ. Decomposition own valuesX=P^{-1}is evaluationΛandV.Λcan be inverted to obtainΛ^{-1}.__

__The matrix of spatial MMSE filter can then be calculated as follows:__

__Equation (27)__

__3 shows a process 300 that is designed to calculate the matrix Mspatial MMSE filter, on the basis of the third variant embodiment. Hermitian matrixP^{-1}initially get on the basis of the matrix
Hresponse of the channel, as shown in equation (20) (block 312). Then perform the decomposition on their own valuesP^{-1}to obtain a unitary matrixVand a diagonal matrixΛas also shown in equation (20) (block 314). Decomposition own values can be performed iterative with multiple twists Jacobi, as described above. MatrixMspatial MMSE filter is then obtained on the basis of a unitary matrixVdiagonal matrixΛand matrixHresponse of the channel, as shown in equation (27) (block 316).__

__Matrix Mspatial MMSE filter based on each of the options above embodiment, represents the biased MMSE solution. Offset matrixMthe spatial filter can be scaled using a diagonal matrixD_{mmse}for_{}obtain unbiased MMSE matrixM_{mmse}spatial filter.MatrixD_{mmse}can be obtained as D_{mmse}=[diag[M•H]]^{-1}where diag[M•H] represents a diagonal matrix containing the diagonal elements ofM•H.__

__The above calculations can also be used to obtain spatial filter matrices for methods with zero significant coefficients (ZF) (also called methods the IR conversion matrix with correlation of the channel (CCMI,
OMCC)), methods of combining maximum ratio (MRC, ERC) and so on. For example, the receiving station may perform spatial processing receiver with zero significant coefficients and MRC, as follows:__

__Equation (28)__

__Equation (29)__

__where M_{zf}is a matrix spatial filter of size T×R were converted to zero is not significant factors;__

__M___{mrc}is a matrix of spatial MRC filter size T×R;

__P___{zf}=(H^{H}•H)^{-1}is a Hermitian matrix of size T×T; and

__[diag( P_{zf})] is a diagonal matrix of size T×T, containing the diagonal elements ofP_{zf}.__

__The inverse of the matrix is necessary for the direct calculation of P_{zf}.P_{zf}can be calculated using variants of the embodiments described above for the matrix of spatial MMSE filter.__

__In the above description, it is assumed that the T modulation symbols to transmit simultaneously from the T transmit antennas, without any spatial processing. The transmitting station may perform spatial processing before transmission as follows:__

__Equation (30)__

__the de
xis a vector of size T×1 T symbols of the transmission, which must be passed through the T transmit antennas; and__

__W__is the transfer matrix of size T×s Matrix__W__transmission can be either (1) the matrix of right singular vectors obtained by performing a decomposition of the singular values of__H__, (2) the matrix of eigenvectors obtained by performing a decomposition on their own values__H__^{H}__H__or (3) the control matrix selected for the spatial distribution of modulation symbols S spatial channels of the MIMO channel. Matrix__H___{eff}effective channel response observed by symbols of the modulation can then be specified as__H___{eff}=_{}__H__•__W__. The above combination can be based on the__H___{eff}instead of__H__.

__For clarity, the above description, it shows a MIMO system with a single carrier, with one podoloski. For MIMO systems with multiple load-bearing matrix H(k) the channel response can be obtained for each podology k of interest. MatrixM(k) the spatial filter can then be obtained for each podology k based on the matrixH(k) of the channel response for this podology.__

__The above calculations for the matrix spatial filter can be within the s by using a different processor type,
such as the floating-point processor, a processor with a fixed decimal point, processor, digital computer, rotate the coordinates (CORDIC), lookup table, and so forth, or combinations thereof. The CORDIC processor embodies an iterative algorithm that enables quick calculation using hardware trigonometric functions such as sine, cosine, magnitude and phase, using a simple hardware shift and addition/subtraction. The CORDIC processor may iteratively calculate each of the variables r, c _{1}and s_{1}system (22) equations with a large number of iterations, which allows to achieve a higher accuracy for the variable.__

__Figure 4 shows the block diagram of the point 410 access and terminal 450 of the user in the system 400 MIMO. Point 410 access equipped with N _{ap}antennas_{,}and the terminal 450 user is equipped with N_{ut}antennas, where N_{ap}>1 and N_{ut}>1. The top-down transmission channel, at the point 410 access processor 414 transmit (TX) data receives data traffic from source 412 data and other data from a controller/processor 430. The processor 414 TX data formats, encodes, performs interleaving, modulating the data and generates data symbols, which are modulation symbols for data. The spatial processor 420 TX multiplex the imagers and the data symbols with pilot symbols,
performs spatial processing matrixWtransfer, if applicable, and provides N_{ap}streams of transmitted symbols. Each module 422 transmitters (TMTR) processes corresponding to the stream of transmitted symbols and generates a modulated signal to a downstream transmission channel. The modulated signals to a downstream transmission channel N_{ap}modules 422a-422ap transmitter transmits via antenna 424a-424ap, respectively.__

__In the terminal 450 user N _{ut}antennas 452a-452ut receive the transmitted modulated signals downstream of the transmission channel, and each antenna transmits the received signal to the corresponding module (RCVR) 454 receiver. Each module 454 receiver performs processing complementary to the processing performed by the modules 422 transmission, and provides received pilot symbols and received data symbols. Block/processor 478 channel estimation processes the received pilot symbols and provides an assessment of the response of H_{dn}channel downstream of the transmission channel. The processor 480 receives the matrixM_{dn}spatial filter downstream of the transmission channel on the basis ofH_{dn}and using any of the variants of the embodiment described above. The spatial processor 460 receiver (RX) performs spatial processing of the receiver (or spatial coherent Phi is Tracey) for the received data symbols from all N_{
ut}modules_{}454a-454ut receiver_{}matrixM_{dn}spatial filter downstream of the transmission channel and provides detected data symbols, which are estimates of the data symbols transmitted by the point 410 access. The processor 470 receiver processes (for example, performs the inverse mapping of the symbol, removes the interleaving and decodes) the detected data symbols and provides decoded data to a receiver 472 of data and/or the controller 480.__

__Treatment for upstream transmission channel may be the same or may be different from the processing for the downward transmission channel. Data from 486 source data and signals from the controller 480 is processed (e.g., encode, perform interleaving and modulate) using a processor 488 TX data, multiplexed with pilot symbols and possibly spatially processed by a spatial processor 490 TX. The characters pass from the spatial processor 490 TX further treated using modules 454a-454ut transmitter for generating N _{ut}modulated signals upstream transmission channel, which is transmitted via antenna 452a-452ut.__

__At the point 410 access modulated signals upstream transmission channel is taken with the help of antennas 424a-424ap and process using modules 422a-422ap receiver generated for the I received pilot symbols and received data symbols,
for transmission upstream transmission channel. Block/processor 428 channel estimation processes the received pilot symbols and provides an assessment of response H_{up}channel ascending transmission. The processor 430 receives the matrixM_{up}spatial filter upstream transmission channel, and using one of the embodiments described above. The spatial processor 440 RX performs spatial processing receiver for the received data symbols with a matrixM_{up}spatial filter upstream transmission channel and provides detected data symbols. The processor 442 data RX advanced processes the detected data symbols and provides decoded data to a receiver 444 data and/or the controller 430.__

__Controllers 430 and 480 controls the operations at the point 410 access and terminal 450 of the user, respectively. In modules 432 and 482 stores data and program codes used by the controllers 430 and 480, respectively.__

__The blocks shown in figure 1-4 represent functional blocks, which can be embodied in the form of hardware (one or more devices), built-in programs (one or more devices), software (one or more modules), or combinations thereof. For example, the described methods of calculating the weights is ultra can be embodied as hardware,
firmware, software or combinations thereof. When executed in the form of hardware processing modules used to calculate the weighting coefficients of the filter can be embodied in one or more specific integrated circuits (ASIC), digital signal processors (DSP)devices, digital signal processing (DSPD), programmable logic devices (PLD), programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic modules designed to perform the functions described here, or combinations thereof. Different processors at the point 410 access figure 4 can also be embodied using one or more hardware processors. Similarly, the various processors in the terminal 450 of the user can be embodied with one or more hardware processors.__

__For the variant embodiment using firmware or software, the methods of calculating the weighting factor of the filter can be implemented with modules (e.g., procedures, functions, and so on)that perform the functions described here. Software codes may be stored in the memory module (e.g. module 432 or 482 memory figure 4) and can execute the process is the PR (e.g.,
the processor 430 or 480). The memory module may be implemented within the processor or external to your processor.__

__The above description of the disclosed embodiments is provided to enable a person skilled in the art to use the present invention. Various modifications of these options embodiments will be clear to a person skilled in the art, and the General principles defined herein may be applied to other embodiments without going beyond the essence or scope of the invention. Thus, the present invention is not intended to limit the variations of the embodiments described herein, but it should be understood in its broadest scope, which corresponds to the disclosed principles here and new properties.__

__1. A device for obtaining matrix spatial filter that contains:the first processor which during operation receives the response matrix of the channel; anda second processor which during operation receives the first iteration matrix based on the matrix of the channel response and displays the matrix spatial filter based on the first matrix and the matrix of the channel response, the second processor calculates the inverse of the matrix for the matrix obtained from the matrix of the channel response by iterative receipt of the first matrix.__

__2. The device according to claim 1, which which the second processor during operation initializes the first matrix to the identity matrix.__

3. The device according to claim 1, in which the second processor during operation, for each of multiple iterations receives the intermediate vector line based on the first matrix and the vector line of the channel response corresponding to the row of the matrix of the channel response, to obtain a scalar value based on the intermediate vector and row vector row of the channel response to obtain an intermediate matrix based on the intermediate vector line and to update the first matrix on the basis of a scalar value and the intermediate matrix.

4. The device according to claim 1, wherein the first matrix is used to obtain the matrix spatial filter with minimum mean square error (MMSE).

5. The device according to claim 1, in which the second processor during operation receives the first matrix on the basis of the following equation:

where__P___{i}represents the first matrix for the i-th iteration,__h___{i}represents the i-th row of the matrix of the channel response, r_{i}represents a scalar value derived from__h___{i}and__P___{i-1}and "^{H}" represents conjugate transposition.

6. The device according to claim 1, in which the second processor during operation receives the first matrix on the basis of the following equations:

where__P___{i}represents the first matrix for the i-th iteration,__h___{i}represents the i-th row of the matrix of the channel response,__a___{i}represents an intermediate vector line for the i-th iteration,__C___{i}represents an intermediate matrix for the i-th iteration,*r*_{i}represents a scalar value for the i-th iteration, δ^{2}_{n}represents the noise variance, and^{H}*"*represents conjugate transposition.

7. The device according to claim 1, in which the second processor during operation receives the matrix spatial filter based on the following equation:

where__M__is a matrix spatial filter,__P__represents the first matrix, H is a matrix of the channel response, and*"*^{H}*"*represents conjugate transposition.

8. A method of obtaining a matrix spatial filter containing phases in which:

iterative get the first matrix based on the matrix of the channel response, and the inverse of the matrix for the matrix obtained from the matrix of the channel response, calculated by iterative obtain a first matrix; and

get the matrix spatial filter based on the first matrix and the matrix of the channel response.

9. The method of claim 8, comprising the step ofwhich initialize the first matrix to the identity matrix.

10. The method according to claim 8, in which the first matrix contains, for each of multiple iterations of stages, which

receive an intermediate vector of strings based on the first matrix and the vector line of the channel response corresponding to the row of the matrix of the channel response,

get a scalar value based on the intermediate vector and row vector row of the channel response,

receive the intermediate matrix based on the intermediate vector line, and

updating the first matrix on the basis of a scalar value and the intermediate matrix.

11. A device for obtaining matrix spatial filter that contains:

the tool iteratively obtain a first matrix based on the matrix of the channel response, and the inverse of the matrix for the matrix obtained from the matrix of the channel response, calculated by iterative obtain a first matrix; and

means for obtaining matrix spatial filter based on the first matrix and the matrix of the channel response.

12. The device according to claim 11, which also contains means for initializing the first matrix to the identity matrix.

13. The device according to claim 11 in which the means for obtaining the first matrix contains, for each of multiple iterations:

means for obtaining an intermediate vector of strings based on the first matrix and the vector line of the channel response corresponding to the row of the matrix on the cliques of the channel

means for obtaining a scalar value based on the intermediate vector and row vector row of the channel response,

means for obtaining an intermediate matrix based on the intermediate vector line and

the update tool of the first matrix on the basis of a scalar value and the intermediate matrix.

__
Transmitter and signal transmission method // 2479927
Base station, user terminal and communication control method in mobile communication system // 2467480
Base station and mobile station // 2444862
Base station and mobile station // 2444862
Base station, user terminal and communication control method in mobile communication system // 2467480
Transmitter and signal transmission method // 2479927
__

**Same patents:**

FIELD: radio engineering, communication.

SUBSTANCE: in the device and the method, BS and MS share a table correlating a basic TF as a combination of parameters such as TB size used for transmitting only user data, an allocation RB quantity, a modulation method and an encoding ratio, with a derived TF having user data of different TB size by combining L1/L2 control information. Even when multiplexing L1/L2 control information, the index corresponding to the basic TF is reported from BS to MS.

EFFECT: high downlink and uplink throughput even when performing dynamic symbol allocation.

14 cl, 20 dwg

FIELD: radio engineering, communication.

SUBSTANCE: transmitter includes multiple transmitting antennae; a conversion unit configured to generate multiple signal sequences corresponding to a predefined frequency bandwidth from one or more transmission streams associated with any of the transmitting antennae; a precoding unit configured to set the weight the signal sequences using a precoding matrix selected from a code module including multiple predefined precoding matrices; and a transmitting unit configured to convert an output signal from the precoding unit into a number of signals corresponding to the number of transmitting antennae and transmit the converted signals from the transmitting antennae. The precoding unit applies different precoding matrices to different signal sequences, and the relationship between the different precoding matrices and the different signal sequences is determined through open-loop control which is independent of feedback from a receiver.

EFFECT: high capacity.

24 cl, 18 dwg

FIELD: physics, communications.

SUBSTANCE: invention relates to wireless communication. The base station is configured to communicate with a user terminal in a mobile communication system using a multiple input/multiple output (MIMO) scheme via precoding. The base station includes a receiving module which receives a precoding matrix index (PMI), which indicates a given precoding matrix, a determination module which determines the value of a flag indicator which indicates whether to use the precoding matrix given in the PMI for communication over a downlink, a control signal generating module which generates a downlink control signal which includes a flag indicator, and a transmitting module which transmits a signal, including a downlink control signal, over a downlink.

EFFECT: efficient utilisation of resources while simultaneously reducing the volume of downlink overhead.

18 cl, 11 dwg

FIELD: information technologies.

SUBSTANCE: in a device and a method BS and MS jointly use a table correlating the main TF as a combination of such parameters as a size of TB used only for user data transfer, quantity of RB for distribution, a method of modulation and a coding coefficient, with a TF derivative, having user data with other size of TB, by means of combining control information of L1/L2. Even during multiplexing of control information of L1/L2 an index complying with the main TF is communicated from BS to MS.

EFFECT: increased efficiency of a top-down communication link and a bottom-up communication link during dynamic distribution of symbols.

10 cl, 20 dwg

FIELD: information technology.

SUBSTANCE: disclosed invention relates to a transmitting apparatus, a receiving apparatus and a data transmitting method. To this end, measurement of communication quality using a broadband signal and transmitting and receiving data using a predetermined frequency band is carried out at approximately the same time. The transmitting apparatus (1) can transmit data at a first frequency and a second frequency to the receiving apparatus (2). The transmitter (1a) of the transmitting apparatus (1) transmits a predetermined broadband signal in a first period of time in a frequency band which does not include the first frequency, and in a second period of time in a frequency band which does not include the second frequency. The quality measuring unit (2a) of the receiving apparatus (2) measures quality of communication with the transmitting apparatus (1) based on the broadband signal received in the first and second period of time.

EFFECT: invention helps prevent quality deterioration when transmitting and receiving data.

14 cl, 21 dwg

FIELD: information technology.

SUBSTANCE: disclosed is a base station in which mobile stations are allocated either resource blocks obtained by dividing the system frequency band into blocks of successive subcarrier frequencies or distributed resource blocks consisting of subcarrier frequencies which are discretely distributed on the system frequency band, and obtained via segmentation of resource blocks into several resource blocks. The base station has a scheduling device configured to allocate resource blocks or distributed resource blocks for mobile stations with a predetermined allocation cycle based on the state of corresponding downlink channels transmitted from the mobile stations.

EFFECT: capacity to periodically allocate predetermined radio resources for traffic with periodic occurrence of data.

4 cl, 14 dwg

FIELD: information technologies.

SUBSTANCE: transmitting device is equipped with facilities of radio communication resources provision, which provide radio communication resources to each physical channel according to the physical channel type; and transmission facilities, which transmit information to be sent by each physical channel, with application of proposed radio communication resources.

EFFECT: presence of optimal provision of radio communication resources to physical channels in the descending channel for transmission of various information types.

11 cl, 59 dwg

FIELD: information technology.

SUBSTANCE: in a first scheme, a Hermitian matrix is iteratively derived based on a channel response matrix, and a matrix inversion is indirectly calculated by deriving the Hermitian matrix iteratively. The spatial filter matrix is derived based on the Hermitian matrix and the channel response matrix. In a second scheme, multiple rotations are performed to iteratively obtain first and second matrices for a pseudo-inverse matrix of the channel response matrix. The spatial filter matrix is derived based on the first and second matrices. In a third scheme, a matrix is formed based on the channel response matrix and decomposed to obtain a unitary matrix and a diagonal matrix. The spatial filter matrix is derived based on the unitary matrix, the diagonal matrix, and the channel response matrix.

EFFECT: efficient derivation of a spatial filter matrix.

24 cl, 4 dwg

FIELD: methods for identification of changed in repeatedly broadcasted database.

SUBSTANCE: in accordance to the method data is produced in fragments, document is received which contains information about fragments, information is analyzed, and fragments are received repeatedly in accordance to aforementioned information.

EFFECT: possible listening of repeated broadcasting with minimal processing of data, detection of change of any data element and determining of location where the change is described.

4 cl, 2 dwg

FIELD: engineering of systems for providing access to multimedia products for consumer through connections of digital client line xDSL.

SUBSTANCE: method includes usage of at least one multiplexer of access to digital client line DSLAM with permitted broadcasting, made for authentication of at least one user locally, and for permitting access to at least one channel in base network, while client information of each user is recorded in DSLAM, which maintains xDSL connection, leading to house of client and each DSLAM supports broadcasting protocols, request is received in DSLAM with permitting of broadcasting at least to one channel from client, where receiving DSLAM locally services xDSL connection for client, information stored in receiving DSLAM is used to determine whether access of client to channel being requested is sanctioned, and if client has sanctioned access to channel being requested, then DSLAM is used to provide such access.

EFFECT: increased speed of switching between channels of audio-visual information through xDSL connection with confirmation in access unit.

5 cl, 9 dwg

FIELD: engineering of systems for providing access to multimedia products for consumer through connections of digital client line xDSL.

SUBSTANCE: method includes usage of at least one multiplexer of access to digital client line DSLAM with permitted broadcasting, made for authentication of at least one user locally, and for permitting access to at least one channel in base network, while client information of each user is recorded in DSLAM, which maintains xDSL connection, leading to house of client and each DSLAM supports broadcasting protocols, request is received in DSLAM with permitting of broadcasting at least to one channel from client, where receiving DSLAM locally services xDSL connection for client, information stored in receiving DSLAM is used to determine whether access of client to channel being requested is sanctioned, and if client has sanctioned access to channel being requested, then DSLAM is used to provide such access.

EFFECT: increased speed of switching between channels of audio-visual information through xDSL connection with confirmation in access unit.

5 cl, 9 dwg

FIELD: methods for identification of changed in repeatedly broadcasted database.

SUBSTANCE: in accordance to the method data is produced in fragments, document is received which contains information about fragments, information is analyzed, and fragments are received repeatedly in accordance to aforementioned information.

EFFECT: possible listening of repeated broadcasting with minimal processing of data, detection of change of any data element and determining of location where the change is described.

4 cl, 2 dwg

FIELD: information technology.

SUBSTANCE: in a first scheme, a Hermitian matrix is iteratively derived based on a channel response matrix, and a matrix inversion is indirectly calculated by deriving the Hermitian matrix iteratively. The spatial filter matrix is derived based on the Hermitian matrix and the channel response matrix. In a second scheme, multiple rotations are performed to iteratively obtain first and second matrices for a pseudo-inverse matrix of the channel response matrix. The spatial filter matrix is derived based on the first and second matrices. In a third scheme, a matrix is formed based on the channel response matrix and decomposed to obtain a unitary matrix and a diagonal matrix. The spatial filter matrix is derived based on the unitary matrix, the diagonal matrix, and the channel response matrix.

EFFECT: efficient derivation of a spatial filter matrix.

24 cl, 4 dwg

FIELD: information technologies.

SUBSTANCE: transmitting device is equipped with facilities of radio communication resources provision, which provide radio communication resources to each physical channel according to the physical channel type; and transmission facilities, which transmit information to be sent by each physical channel, with application of proposed radio communication resources.

EFFECT: presence of optimal provision of radio communication resources to physical channels in the descending channel for transmission of various information types.

11 cl, 59 dwg

FIELD: information technology.

SUBSTANCE: disclosed is a base station in which mobile stations are allocated either resource blocks obtained by dividing the system frequency band into blocks of successive subcarrier frequencies or distributed resource blocks consisting of subcarrier frequencies which are discretely distributed on the system frequency band, and obtained via segmentation of resource blocks into several resource blocks. The base station has a scheduling device configured to allocate resource blocks or distributed resource blocks for mobile stations with a predetermined allocation cycle based on the state of corresponding downlink channels transmitted from the mobile stations.

EFFECT: capacity to periodically allocate predetermined radio resources for traffic with periodic occurrence of data.

4 cl, 14 dwg

FIELD: information technology.

SUBSTANCE: disclosed invention relates to a transmitting apparatus, a receiving apparatus and a data transmitting method. To this end, measurement of communication quality using a broadband signal and transmitting and receiving data using a predetermined frequency band is carried out at approximately the same time. The transmitting apparatus (1) can transmit data at a first frequency and a second frequency to the receiving apparatus (2). The transmitter (1a) of the transmitting apparatus (1) transmits a predetermined broadband signal in a first period of time in a frequency band which does not include the first frequency, and in a second period of time in a frequency band which does not include the second frequency. The quality measuring unit (2a) of the receiving apparatus (2) measures quality of communication with the transmitting apparatus (1) based on the broadband signal received in the first and second period of time.

EFFECT: invention helps prevent quality deterioration when transmitting and receiving data.

14 cl, 21 dwg

FIELD: information technologies.

SUBSTANCE: in a device and a method BS and MS jointly use a table correlating the main TF as a combination of such parameters as a size of TB used only for user data transfer, quantity of RB for distribution, a method of modulation and a coding coefficient, with a TF derivative, having user data with other size of TB, by means of combining control information of L1/L2. Even during multiplexing of control information of L1/L2 an index complying with the main TF is communicated from BS to MS.

EFFECT: increased efficiency of a top-down communication link and a bottom-up communication link during dynamic distribution of symbols.

10 cl, 20 dwg

FIELD: physics, communications.

SUBSTANCE: invention relates to wireless communication. The base station is configured to communicate with a user terminal in a mobile communication system using a multiple input/multiple output (MIMO) scheme via precoding. The base station includes a receiving module which receives a precoding matrix index (PMI), which indicates a given precoding matrix, a determination module which determines the value of a flag indicator which indicates whether to use the precoding matrix given in the PMI for communication over a downlink, a control signal generating module which generates a downlink control signal which includes a flag indicator, and a transmitting module which transmits a signal, including a downlink control signal, over a downlink.

EFFECT: efficient utilisation of resources while simultaneously reducing the volume of downlink overhead.

18 cl, 11 dwg

FIELD: radio engineering, communication.

SUBSTANCE: transmitter includes multiple transmitting antennae; a conversion unit configured to generate multiple signal sequences corresponding to a predefined frequency bandwidth from one or more transmission streams associated with any of the transmitting antennae; a precoding unit configured to set the weight the signal sequences using a precoding matrix selected from a code module including multiple predefined precoding matrices; and a transmitting unit configured to convert an output signal from the precoding unit into a number of signals corresponding to the number of transmitting antennae and transmit the converted signals from the transmitting antennae. The precoding unit applies different precoding matrices to different signal sequences, and the relationship between the different precoding matrices and the different signal sequences is determined through open-loop control which is independent of feedback from a receiver.

EFFECT: high capacity.

24 cl, 18 dwg

FIELD: radio engineering, communication.

SUBSTANCE: in the device and the method, BS and MS share a table correlating a basic TF as a combination of parameters such as TB size used for transmitting only user data, an allocation RB quantity, a modulation method and an encoding ratio, with a derived TF having user data of different TB size by combining L1/L2 control information. Even when multiplexing L1/L2 control information, the index corresponding to the basic TF is reported from BS to MS.

EFFECT: high downlink and uplink throughput even when performing dynamic symbol allocation.

14 cl, 20 dwg