Method for transmission-reception of signal in multiuser system of radio communication with multiple transmitting and multiple receiving antennas

FIELD: radio engineering.

SUBSTANCE: invention applies new sequence of interrelated actions, including procedure of vector disturbance in combination of array basis reduction and multi-alternative quantisation. Invention makes it possible to simultaneously service group of several subscriber stations in one and the same physical channel. Invention advantage is possibility of quite simple realisation in transmitter and especially simple realisation in receiver of subscriber station. Invention advantage is possibility of realisation with only one receiving antenna available in each of subscriber stations.

EFFECT: increased throughput capacity of communication channel.

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The invention relates to the field of radio engineering, in particular to a method of transfer-acceptance signal in multi-user communication system with multiple transmitting and multiple receiving antennas.

Technology the use of multiple transmitting and multiple receiving antennas attracts attention as an effective way of increasing the bandwidth of the communication channel that does not require the additional cost of the radio frequency spectrum. In radio systems that use this technology, the communication channel between the transmitting and the receiving party has many inputs (multiple inputs) transmit antennas and multiple outputs (multiple outputs) - receiving antennas, resulting technology called MIMO (multiple-input-multiple-output).

The totality of channels of signal propagation between the transmitting and receiving antennas is called a MIMO channel. One way to increase throughput is the simultaneous transmission of different information flows at different spatial subchannel of the MIMO channel. This method is known as spatial multiplexing spatial multiplexing) [1] G.J.Foshini, G.D.Golden, R.A.Valenzuela, "Simplified processing for high spectral efficiency wireless communication employing multi-element arrays," IEEE Selected Areas Communication, vol.17, pp.1841-1852, November, 1999, [2] 802.16TM IEEE Standard for local and metropolitan area networks. Part 16: Air Interface for Fixed Broadband Wireless Access Systems, 1 October 2004.

PR is spatial multiplexing independent information streams pass through different transmit antennas. At the receiving side estimate transfer coefficients of the hj,iall spatial communication channels, each of which is formed of one transmitting and one receiving antenna, where the i,j - indices of the transmitting and receiving antennas, respectively. From these coefficients form the channel matrix H, which is used when receiving a signal.

Until recently, very intensively developed methods of transfer-acceptance for single-user MIMO channels, covering one receiver and one transmitter (in terms of foreign publications - point-to-point - point-to-point).

One of the most serious obstacles to the use of MIMO technology in the system "from point to point is the necessity of posting on the subscriber station (MSS) multiple antennas. It is quite difficult to implement, so as to subscriber stations, as a rule, the requirements of small size and low cost.

Another problem in the use of single-user MIMO is that the increase in throughput depends on the scattering properties of the medium of propagation. To obtain significant gains in throughput required to cause the signal propagation had objects scattering and antenna systems had antenna, remote from each other at a great distance.

Vari is NT the solution of these problems is the multi-user MIMO technology. In this technology as a MIMO channel is considered, the channel formed by multiple antennas of a base station (BS) on the one hand and antennas multiple subscriber stations (MSS) with the other hand. In addition, each subscriber station can have as few or only one antenna.

Multiplayer approaches enable the use of the additional benefits of MIMO technology.

First, you can increase throughput due to the spatial separation of the users, when multiple subscriber stations used to communicate with the BS one and the same physical channel.

Secondly, multi-user MIMO channel has a relatively low correlation between spatial subchannels, due to the fact that they belong to different subscriber terminals. This provides a gain in throughput even in an environment with low dispersion.

Thirdly, it becomes possible to implement the algorithms in MIMO case, when the user equipment has one or a small number of antennas.

To date, there is enough practical solution for multi-user MIMO algorithm in the reverse channel communication system (from subscriber stations to the base). This method of collaborative spatial multiplexing (collaborative spatial multiplexing, used for transmitting signals from multiple user terminals to the base station. This solution is provided by modern communication standards, such as [2] TM IEEE Standard for local and metropolitan area networks. Part 16: Air Interface for Fixed Broadband Wireless Access Systems, 1 October 2004.

However, the problem of increasing the capacity of the most pressing forward link from the base station to a subscriber terminal, which transmitted the most voluminous and high-speed data streams. At the same time has not yet developed a simple and efficient multi-user algorithm for the direct channel of the MIMO communication system. The implementation of multi-user MIMO approaches in the direct channel is faced with two major problems. First of all, it is a necessity to ensure the transmitter information about the communication channel. Another problem is that unlike single-user MIMO channel in a multi-user channel is practically impossible for joint processing of signals of different user terminals.

Thus, a very urgent task of developing a multi-user algorithm of transfer-acceptance signal in the forward channel of the MIMO communication system.

There are several multi-user MIMO approaches in the direct channel. These include the encoding of dirty pages" (dirty paper coding) [3] M.Airy, A.Forenza, R.W.Heath, Jr.S.Shakkottai, "Practical Costa precedng for the multiple antenna broadcast channel," IEEE Global Telecommunications Conference, GLOBECOM, 29 Nov.-3 Dec. 2004, Volume 6, Page(s): 3942-3946, block diagonalization (block diagonalization) [4] Q.H.Spencer, and M.Haardt, "Capacity and Downlink Transmission Algorithms for a Multi-user MIMO Channel," Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference, Volume 2, Issue, 3-6 Nov. 2002 Page(s): 1384-1388 vol.2, and various methods of linear multi-user pre-coding (multiuser precoding) [5] J.C.Mundarath, J.H.Kotecha, "Zero-Forcing Beamfbrming for Non-Collaborative Space Division Multiple Access," Proceedings of 2006 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 14-19 May 2006, Volume: 4, page(s): IV-IV. [6] A Wiesel, Y.C.Eldar, and Sh.Shamai, "Optimal Generalized Inverses for Zero Forcing Preceding," 41st Annual Conference on Information Sciences and Systems, CISS'07, 14-16 March 2007, pages: 130-134.

Most of these methods have high complexity and requires considerable research aimed at practical application.

Known, for example, the algorithm block diagonalization (block diagonalization), which theoretically is a very effective way of implementing multi-user MIMO [4] Q..Spencer, and M.Haardt, "Capacity and Downlink Transmission Algorithms for a Multi-user MIMO Channel," Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference, Volume 2, Issue, 3-6 Nov. 2002 Page(s): 1384-1388 vol.2. In this algorithm, multi-user pre-conversion (encoding) signal is performed so that the MIMO channel is transformed into orthogonal spatial subchannels corresponding to different user terminals. The data ka the materials do not create mutual interference. The reception-signal transmission for each user terminal to perform in the respective spatial sub-channel using any of the known single-user MIMO algorithms.

To implement this approach it is necessary to estimate the coefficients of the transfer of all spatial channels of communication and to form a channel matrix. Information about the channel matrix is an auxiliary control information, which in one way or another it is necessary to transmit to the base station. After that, the base station should perform a decomposition of the channel matrix singular values. The resulting information about the right singular vectors BS uses in the process of signal transmission. However, the information about the left singular vectors of the base station must transmit the subscriber terminal so that they could perform the signal reception.

This algorithm is difficult for practical implementation, as it requires two-way transfer of voluminous control data with high speed. Another drawback of this algorithm is that it is applicable only for the case when the user terminals have two or more receiving antennas.

Known more simple - linear methods multi-user pre-coding, which refers to the way a minimum of environments is kvadratichnoi errors (minimum mean squared error - MMSE) and the method of contacting the zero forcing - ZF) [5] J.C.Mundarath, J.H.Kotecha, "Zero-Forcing Beamforming for Non-Collaborative Space Division Multiple Access," Proceedings of 2006 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 14-19 May 2006, Volume: 4, page(s): IV-IV, [6] A Wiesel, Y.C.Eldar, and Sh.Shamai, "Optimal Generalized Inverses for Zero Forcing Preceding," 41st Annual Conference on Information Sciences and Systems, CISS'07, 14-16 March 2007, pages: 130-134.

In these algorithms, a pre-transmission signal processing (pre-encoding) is performed by a linear transformation matrix which is based on the inversion or pseudoinverse channel matrix H. As a result of such pre-treatment in each reception antenna of each of the speakers is formed only designed the antenna signal without interference from the other signals of the receiving antennas. Ways ZF and MMSE applicable for terminals equipped with one or multiple antennas.

One of the most simple methods multi-user pre-coding is a method of inversion channel or treatment in the zero (ZF).

According to the method of the inversion channel of the modulation symbols α1, ..., αMdesigned for simultaneous transmission To the subscriber terminal, to form a package or a vector of modulation symbols a=[α1, ... αM]Tin which the number of symbols transmitted from each speaker is equal to the number of receiving antennas is given as, where M is with Marnie the number of receiving antennas of the subscriber stations. From this vector form vector of transmitted signals s by multiplying the vector and the inverse of the channel matrix or pseudoinverse, if the matrix H is not square. Further, for simplicity, we will consider the case M=N, when the matrix H is square. Then

Many of the signals received subscriber stations, can be represented as vector elements, which, in turn, can be expressed as

where n is the noise vector components of the receiving antennas, which are well approximated as independent Gaussian random variables, x is the normalized vector of transmitted signals, obtained by the following transformation vector s:

- power signal, E[γ] is the expected value of γ.

Substituting (1) and (3) in (2) can be obtained, that

where n is the noise vector components of the receivers AC, IM- singular diagonal matrix with dimension M×M

From the formula (4) shows that the received signals of the users are mutually independent and do not create mutual interference. However, the normalization (3) leads to the fact that the ratio of the transmission signal is equal to

The value ofin the denominator of this expression is avisit from the inversion of the channel matrix H and can be quite significant, especially when ill-conditioned channel matrix. The presence of this factor is the main reason for the decline in the relative productive capacity at the point of reception and, with it, the noise immunity of the reception.

Thus, a significant increase in signal power s due to multi-user pre-processing is the main disadvantage of methods ZF and MMSE. As in the communication system, there is a limit on the transmit power, the signal amplitude is linearly reduced (in accordance with (3)), but this leads to a significant reduction of the useful signal power relative to the noise at the point of reception. As a result, the robustness of reception becomes poor.

There is another way of limiting power transmission, which avoids significant reduction in the relative productive capacity at the point of reception. The basis of this method is the nonlinear operation of the modular reduction, which applies, for example, in [7] R.F.H.Fischer, C.Windpassinger, A.Lampe, J.B.Huber, "Space-Time Transmission using Tomlinson-Harashima Preceding," In Proc. 4th Int. ITG Conf., pp.139-147, Berlin, Jan. 2002.

Input values for this operation is a complex number, reflecting the converted signal. Operation modular reduction (reducing modulo) is added to the real and imaginary part of the input number multiples of the actual measurements is A, called by the module.

Added values are chosen such that the total complex number is in the Central region of the complex plane, which are all complex characters used constellation modulation. Unit known as the transmitting and the receiving side that allows you to restore the reduced signal in the admission process.

The most effective way to use non-linear modular reduction is a vector of disturbance (perturbation vector) [8] Christoph Windpassinger, Robert F.H.Fischer, and Johannes B.Huber, "Lattice-Reduction-Aided Broadcast Precoding," IEEE TRANSACTIONS ON COMMUNICATIONS, VOL.52, NO.12, DECEMBER 2004, pp.2057-2060.

Vector perturbation is that the vector of information symbols and add some perturbation vector R. as a result, the signal after multiplayer transformation can be represented as

Real and imaginary parts of the elements of the vector p determines multiples of the unit And chosen so that

where Reα, Imα is valid and, accordingly, the imaginary part of any complex symbol used constellation modulation.

The signal γ, received in the channel of each receive antenna for each subscriber station, subjected to the nonlinear operation of the modular reduced the I

where

[x] is a maximum integer not exceeding X.

The main property of this operation is that it is invariant to adding multiples of A:

where r is any integer.

In virtue of this property, after performing a modular reduction of the signal receiving antennas for all speakers can be represented by a vector

where IM- singular diagonal matrix with dimension M×M

This equality shows that the vectors of transmitted and received signals are related linearly by using the diagonal matrix IM. That is, in the preceding transmission multiplayer conversion in each of the receiving antennas formed corresponding transmitted signal without interference from the signals transmitted to other receiving antennas.

Equality (10) is obtained under the assumption that distorted noise symbols of the constellation of modulation beyond the boundaries of the square of the complex plane bounded by the values

that is:

where Ren, Imn is valid and, accordingly, the imaginary part of the noise component of the signal receiving antenna.

In cases when the condition (11) not vypolnjaete is, nonlinear modular reduction (10) causes distortion of the signal, which in turn leads to loss of noise immunity and accordingly the capacity of the communication channel. Therefore, preferably the maximum extent possible to reduce the power of the transmitted signal x=N-1·(a+R). For this purpose it is necessary to determine the optimal vector of perturbations poptso that adding it to the vector of information symbols and will provide a minimum signal power after the preliminary multiplayer encoding:

where- the set of M-dimensional vectors whose elements are integer real and imaginary part.

The solution of the optimization problem (12) is complicated by the fact that the set of integers is not limited, which is why manyinfinitely. Therefore, the search for solutions by brute force all values of manyimpossible. Even if you limit the question of integers, some of the most close-to-zero values, for example{-2, -1, 0, 1, 2}, and in this case, the set of search can be very large. For example, this set consists of (52)M=625 vectors with M=2, and (52)M=390625 vectors with M=4.

Therefore, the brute force method for solving (12) leads to a significant increase is the complexity of implementation.

One approach to the solution of the optimization problem (12) is to use the reduced basis of the lattice [8] Christoph Windpassinger, Robert F.H.Fischer, and Johannes B.Huber, "Lattice-Reduction-Aided Broadcast Preceding," IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO.12, DECEMBER 2004, pp.2057-2060. This method is the closest to the method of the claimed invention. Prototype method is as follows.

The method of transfer-acceptance signal in a communication system including a transmitting station equipped with N transmitting antennas and receiving stations, where K≥2, and each receiving station is equipped with at least one receiving antenna, and the total number of receiving antennas of the receiving stations M satises 1<M≤N, namely, that

to estimate the parameters of the aggregate spatial communication channels, each of which is formed of one transmitting antenna of the transmitting station and one receiving antenna of the receiving station,

the quality of the estimated parameters using the coefficients of the transmission channel;

transfer-receiving signals between a transmitting station and a receiving station, for which:

on the transmitting station To form sets of modulation symbols intended for transmission To the receiving stations, respectively,

- formed from sets of modulation symbols to form packages of M modulation symbols in each one character package for each of the receiving antennas of the receiving stations,

- package symbol modulation present in the form of a vector of transmitted modulation symbols a=[α1... αM]T,

- perform multi-user transformation of the vector of transmitted modulation symbols in the vector of transmitted signals x so that the transmitted signals did not create interference in the M receiving antennas of the receiving stations, for what

form the channel matrix H using the transfer coefficients of the spatial channels of communication

from the vector of transmitted modulation symbols and the channel matrix H form a real-valued vector arand the matrix Hrin accordance with the formula

where ReY, ImY - matrix composed of the real and imaginary parts, respectively of the respective elements of the matrix Y,

of real-valued channel matrix Hrform the matrix Wrpre-signal conversion,

by the reduction of the basis of the lattice of the matrix Wrform of an integer matrix with determinant equal to ±1, the multiplication which converts the matrix preliminary transformations in the matrix Z=WrT with a low condition number,

using the matrix T, define the perturbation vector by the formula

where Q(is) - the vector obtained from the vector x by rounding its elements to the nearest whole number,

And is a real number, such that the actual Reα and imaginary Imα of any modulation symbol for absolute value is strictly less than A/2:

form a perturbed real-valued vector of transmitted modulation symbols by adding real-valued vector of transmitted modulation symbols and the perturbation vector ar+p0and perform a preliminary linear transformation of the received perturbed real-valued vector of modulation symbols forming, thus, a real-valued vector of transmitted signals:

from the obtained real-valued vector of transmitted signals xrform the vector of transmitted signals

where j is the imaginary unit, as in xr(n:m) denotes a vector composed of a sequence of elements of vector xrfrom n-th to m-th;

- a set of signals corresponding to the elements of the vector of transmitted signals x, pass through all transmitting antennas - one signal through the antenna;

- accept signals at each of the receiving stations, and reception is carried out in the channel of each receive antenna, and receiving

form the signal, as the comp is exee number with the module and argument, reflecting respectively the amplitude and phase of the signal received by this channel antennas;

determine the real and imaginary parts of the normalized signal y

with the received signals z and perform the operation modular reduction with module equal to:

where [x] is the integer part of x, that is, the maximum integer not exceeding x,

from signalsandform an integrated signal

using the values of the complex signalthus formed in each physical channel of each receive antenna, performs demodulation and decoding of a received signal.

This method of transfer-acceptance signal in a multi-user MIMO communication system uses advanced linear conversion signal based on inversion (or pseudoinverse) channel matrix.

This is a very effective way multi-user pre-coding, because, firstly, as a result of this linear transformation is suppressed interference signals at the receiving antennas. Secondly, the receiving side does not require any additional service information for demodulation of the signal, resulting in possible regarding the compulsory implementation of a simple receiver.

However, due to the multiplication of the signal inversion (or pseudoinverse) channel matrix significantly increases the signal strength. As in the claimed method, and the method prototype for power reduction procedure vector perturbations. This procedure consists in the fact that the signal add some perturbation vector.

The elements of the disturbance vector is a multiple of the value of A, which is known to both transmitter and receiver. Value And determine depending on the type of modulation, so that you can restore the original signal in the receiver using the operation modular reduction.

The optimal perturbing vector is chosen from the set of vectors p=A·Z2Mwhere Z2Ma discrete set of integer vectors of dimension 2M. Moreover, the optimal perturbing vector is defined as the vector that minimizes the value ofThe smaller the value ofthe less transmission power and at the same time, the less the degree of signal distortion due to modular reduction in the receiver.

The easiest way to determine the optimal vector perturbations is to first determine not quantized perturbation vector puthe closest to ar

and then execute the ü its quantization

where Q(x) - atomic rounding to the nearest integer.

However, in the presence of even a small noise distortion in the vector arthe operation of rounding leads to an even greater distortion of the vector Wr·R. This phenomenon is called the amplification of noise due to quantization. This noise depends on the degree of orthogonality of the columns of the matrix Wr. The higher the degree of orthogonality of the columns of the matrix Wrthe less noise distortion vector Wr·R.

Therefore, to reduce distortion use the method of reduction of the basis of the lattice. In this case, the matrix a preliminary linear transformation Wrtransform the matrix Z, which has a low condition number, and, consequently, a higher degree of orthogonality of the columns. This conversion is accomplished by reduction of the basis of the lattice, so that between the original and the transformed matrix is the ratio Z=WrT, where T is an integer matrix with determinant equal to ±1.

Then do not quantized vector perturbations is determined in the space of the reduced matrix Z, that is,

where

The optimal perturbing vector is found by quantization

and the subsequent conversion of the Finance, reverse the reduction of the basis of the lattice

This perturbation vector provides less valuethan the vector obtained without reduction of the basis of the grating (22).

However, despite the fact that the conversion of reduced basis of the lattice on average reduces the condition number of the matrix and increases the degree of orthogonality of columns, it does not guarantee perfect orthogonality of the columns of the matrix a preliminary linear transformation. Consequently, the selected perturbation vector does not always ensure at leastThis leads, firstly, the increase in the value range of the transmitted signal power and, secondly, the increase in distortion of the signal in the receiver in the process of nonlinear modular reduction. The first of these aspects leads to the fact that increasing the ratio of the peak signal power to average, which increases the demands on the linearity of the amplifier and complicates the implementation of the method in the communication equipment. The second aspect causes a decrease in throughput of the channel.

The task solved by the invention is the improvement of the capacity of the communication channel, which is achieved by the claimed method by using the new sequence of interrelated dei is of textbooks, including the procedure vector perturbations in combination with a reduction of the basis of the lattice and multi quantization.

The method of transfer-acceptance signal in multi-user communication system with multiple transmitting and multiple receiving antennas, which use a transmitting station equipped with N transmitting antennas and receiving stations, where K≥2, and each receiving station is equipped with at least one receiving antenna, and the total number of receiving antennas of the receiving stations M satises 1<M≤N, and the transmission-reception of signals between transmitting and receiving stations through F physical communication channels, where F≥1, namely, that

for each F physical channels to estimate the parameters of the aggregate spatial communication channels, each of which is formed of one transmitting antenna of the transmitting station and one receiving antenna of the receiving station;

transfer-receiving signals between a transmitting station and receiving stations, using F physical channels, for which:

on the transmitting station To form sets of modulation symbols intended for transmission To the receiving stations, respectively,

- from the generated sets of characters modulation form F packages M modulation symbols in each, on the tea package for M kthe modulation symbols for each k-th receiving station, where Mk- the number of receiving antennas of the kth receiving station,

- transfer of each of the F symbol packages modulation corresponding physical channel, while

package modulation symbols are in the form of a vector of transmitted modulation symbols a=[α1, ..., αM]Twhich each element is a complex number, modulus and argument, reflecting the amplitude, and accordingly the phase of the corresponding modulation symbol,

perform multi-user transformation of the vector of transmitted modulation symbols in the vector of transmitted signals x so that the transmitted signals did not create interference in the M receiving antennas of the receiving stations, for what

form a channel matrix H for a given physical channel using transfer coefficients of the spatial channels of communication

from the vector of transmitted modulation symbols and the channel matrix H form a real-valued vector arand the matrix Hrin accordance with the formula

where ReY, ImY - matrix composed of the real and imaginary parts, respectively of the respective elements of the matrix Y,

of real-valued channel matrix Hrform the matrix WrPR is dwarfling linear signal conversion,

by the reduction of the basis of the lattice of the matrix W form of an integer matrix with determinant equal to ±1, the multiplication which converts the matrix preliminary linear transformations in the matrix Z=WrT with a low condition number,

using the matrix T, and the real-valued vector of transmitted modulation symbols ardetermine not quantized vector perturbations as

where a is a real number, such that real and imaginary part of any modulation symbol for absolute value is less than A/2,

perform rounding each element of the received vector z to the nearest largest integer that identifies, therefore, the first quantized vector z1define the vector of the corresponding values of the quantization errors are:

where Q(z) is the vector obtained elementwise rounding vector z to the nearest integer,

form the second quantized vector z2by determining for each element of the vector z of the second nearest largest integer with the opposite value of the quantization error, and a second vector corresponding values of the quantization error,

element of the first z1and the second z2the quantized vectors of the form R quantized vector is in u, with the lowest values of total quantization error vector,

each of the R quantized vectors u transform by the formula

forming, thus, many candidate perturbation vectors

determine the optimal perturbing vector R0as the vector from the set of candidate perturbation vectors for which the key functionminimal

form a perturbed real-valued vector of transmitted modulation symbols by adding real-valued vector of transmitted modulation symbols and the optimal perturbing vector, and perform a preliminary linear transformation of the received perturbed real-valued vector of modulation symbols forming, thus, a real-valued vector of transmitted signals:

from the obtained real-valued vector of transmitted signals xrform a non-normalized vector of transmitted signals

where j is the imaginary unit,

and after xr(n:m) denotes a vector composed of a sequence of elements of vector xrfrom n-th to m-th;

form the vector of transmitted signals x, multiplying the vector of the non-normalized transmitted signals by a factor of regulation CT,

the set of signals corresponding to the elements of the received vector x, is passed in the corresponding physical channel through all transmitting antennas - one signal through the antenna;

- accept signals at each of the receiving stations, and in each physical channel of each receive antenna reception is carried out in such a way that

form the signal as a complex number with modulus and argument, the corresponding amplitude and phase RX data physical channel signal;

normalized the signal by multiplying it by a factor of regulation CRforming, thus, the normalized signal

factor rating CRset, for example, equal to the inverse value of the ratio of normalized transmission:

determine the real and imaginary parts of the normalized signal ynorm

with the received signals z and perform the operation modular reduction modulo:

where [x] is the integer part of x, that is, the maximum integer less than x,

from signalsandform an integrated signal

using the values of the complex signal

Thus, for example, for each F physical channels in the quality of the estimated parameters using the transfer rate of the communication channel and the signal-to-noise ratio in the channel.

At the transmitting station To each of the information messages destined for transmission To the receiving stations, for example, are respectively in the form of a sequence of binary symbols, and then perform the coding, interleaving and modulation of binary symbols of the sequence.

Matrix Wrpreliminary linear transformation of the signal form, for example, as

where Hris real-valued channel matrix for a given physical channel.

The second quantized vector z2and a second vector corresponding values of the quantization errors are formed by the formulas:

where through sign(a) denotes the vector obtained from the vector and, by applying to each element of the operation:

The total quantization error vector is determined, for example, as the sum or the sum of squares of absolute quantization errors of all elements of the vector.

When forming vectorparameter signal factor rating C Tis chosen so that the average transmit power of the signals generated vector x equal power signals that are transmitted to the receiving stations without multiplayer conversion. This can be, for example, pilot signals used for channel estimation at the receiving side.

The inventive method of transfer-acceptance signal in multi-user communication system with multiple transmitting and multiple receiving antennas in comparison with the prior art has novelty. Distinctive features of the invention are the following characteristics:

the transmission-reception of signals between transmitting and receiving stations through F physical communication channels, where F≥1,

for each F physical channels to estimate the parameters of the aggregate spatial communication channels

transfer-receiving signals between a transmitting station and receiving stations, using F physical channels

from the generated sets of characters modulation form F packages M modulation symbols in each,

transfer each of the F symbol packages modulation corresponding physical channel,

determining not quantized vector perturbations. use real-valued vector of transmitted modulation symbols arwhile

not quantized ve the tor perturbations defined as

where a is a real number, such that real and imaginary part of any modulation symbol for absolute value is less than A/2,

perform rounding each element of the received vector z to the nearest largest integer that identifies, therefore, the first quantized vector z1define the vector of the corresponding values of the quantization errors are:

where Q(z) is the vector obtained elementwise rounding vector z to the nearest integer,

form the second quantized vector z2by determining for each element of the vector z of the second nearest largest integer with the opposite value of the quantization error, and a second vector corresponding values of the quantization error,

element of the first z1and the second z2the quantized vectors of the form R quantized vectors u, with the lowest values of total quantization error vector,

the total quantization error vector is determined, for example, as the sum or the sum of squares of absolute quantization errors of all the elements of the vector

each of the R quantized vectors u transform by the formula

forming, thus, many candidate perturbation vectors

definition what are the optimal perturbing vector R 0as the vector from the set of candidate perturbation vectors for which the key functionminimal

form a perturbed real-valued vector of transmitted modulation symbols by adding real-valued vector of transmitted modulation symbols and the optimal perturbing vector, and perform a preliminary linear transformation of the received perturbed real-valued vector of modulation symbols forming, thus, a real-valued vector of transmitted signals,

form the vector of transmitted signals, multiplying the vector of the non-normalized transmitted signals by a factor of regulation CT,

taking the signals To each of the receiving stations, each physical channel of each receive antenna reception is carried out in such a way that the generated signal is normalized by multiplying it by a factor of regulation CRforming, thus, the normalized signal

factor rating CRset, for example, equal to the inverse value of the ratio of normalized transmission:

Listed above are the essential distinguishing features allow you to get the best technical effect, namely:

- significantly improve the throughput of multiuser MIMO communication system, as the simultaneous handling of several subscriber stations in the same physical channel;

to outperform the noise immunity of the known multi-user MIMO algorithms [4] Q.H.Spencer, and M.Haardt, "Capacity and Downlink Transmission Algorithms for a Multi-user MIMO Channel," Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference, Volume 2, Issue, 3-6 Nov. 2002 Page(s): 1384-1388 vol.2, [5] J.C.Mundarath, J.H.Kotecha, "Zero-Forcing Beamforming for Non-Collaborative Space Division Multiple Access," Proceedings of 2006 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 14-19 May 2006, Volume: 4, page(s): IV-IV, [6] A Wiesel, Y.C.Eldar, and Sh.Shamai, "Optimal Generalized Inverses for Zero Forcing Preceding," 41st Annual Conference on Information Sciences and Systems, CISS '07, 14-16 March 2007, pages: 130-134, as well as the algorithm, which served as the prototype of the proposed method [8] Christoph Windpassinger, Robert F.H.Fischer, and Johannes B.Huber, "Lattice-Reduction-Aided Broadcast Preceding," IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO.12, DECEMBER 2004, pp.2057-2060.

This advantage of the proposed method is achieved by using the new sequence of interrelated activities, including the procedure for vector perturbations in combination with a reduction of the basis of the lattice and multi quantization.

Moreover, an advantage of the method according to the present invention is relatively simple in its implementation at the transmitter and, especially, a simple implementation in the receiver the e subscriber stations.

A significant advantage of this invention is that it is possible to implement if there is only one receiving antenna at each of the subscriber stations of the communication system.

Another important advantage of the invention is the possibility of its implementation in almost any environment distribution. Explain that for the implementation of traditional stand-alone methods MIMO required distribution environment with a large number of scattering objects, which is not always realized in practice. At the same time, the method according to the claimed invention provides a gain in throughput even in an environment with relatively low scattering, since the antenna of the receiving parties belong to different subscriber terminals, so that their signals have a low correlation, regardless of the medium of propagation.

Further description of the invention is illustrated by examples and drawings.

Figure 1 is performed structural diagram of a multiuser communication systems with multiple transmitting and multiple receiving antennas, in which the inventive method.

Figure 2 performed structural diagram of the transmitter multiuser communication systems MIMO-OFDM.

Figure 3 - block diagram of the shaper signal group AC joint service, use isoimage in the transmitter.

Figure 4 - block diagram of the node forming an information packet used in the shaper signal group AC joint service.

Figure 5 - block diagram of the host of a multiplayer processing used in the shaper signal group AC joint service.

Figure 6 - block diagram of the receiver speakers.

Figure 7 - block diagram of the processing unit of the signal receiving antenna used in the receiver speakers.

On Fig - noise immunity characteristics of multi-user MIMO algorithms.

The structural scheme of the device and its component units, is made to figure 1-7, are given as examples for the implementation of the proposed method. However, the use of the claimed invention is not limited to implementing only by the above devices.

The method of transmission and reception of signals in multi-user communication system with multiple transmitting and multiple receiving antennas according to the present invention is realized in a system that includes a base station (BS) and at least two subscriber stations (MSS). The structure of such radio system, consisting of one BS 1 and L subscriber stations 6.1-6.L shown in figure 1. Part of the equipment of the base station 1 includes at least a transmitter 2, a receiver 3 and the control unit 4, and first the e input and output control unit 4 are connected respectively with the output and input of the transmitter 2, second input and output control unit 4 are connected respectively with the output and the input of the receiver 3. Part of the equipment of each subscriber station 6.1-6.L also includes at least a receiver, respectively, 8.1-8.L, the transmitter 9.1-9.L and the control unit 10.1-10.L, with the first input and output control units 10.1-10.L connected respectively with the output and the input of the receivers 8.1 - 8.L, the second input and output control units 10.1-10.L connected respectively with the output and input transmitters 9.1-9.L.

The communication channel from the transmitter 2 BS 1 to the receivers 8.1-8.L AC 6.1-6.L usually called direct channel communication system and a communication channel from a transmitter 8.1-8.L AC 6.1-6.L to the receiver 3 BS 1 - otherwise.

BS 1 is equipped with N antennas 5.1-5.N, the inputs and outputs of which are connected with the inputs and outputs of the transmitter 2 and receiver 3, and which are used for signal transmission in the direct channel. These N antennas 5.1-5.N can be used for reception of a signal return path, with N>1.

Each i-I AC (i=1, ... L) from L AC 6.1-6.L-equipped transceiver antennas 7.1 to 7.Mithe outputs and inputs which are connected respectively to the inputs and outputs of their corresponding transmitters 9.1-9.L and receiver 8.1-8.L. the Number of antennas Midifferent speakers (i=1,..., L) can be different. Thus the system can include speakers, equipped with one antenna, and speakers, equipped not is how many antennas, i.e., N≥Mi≥1. In the particular case of all subscriber stations can have one antenna.

The invention is carried out, for example, in the direct channel is represented in figure 1 communications systems to increase bandwidth.

In systems with high data transfer speed, as a rule, use a very wide band of frequencies. Under these conditions, the MIMO channel is experiencing distortion frequency selectivity, which in the time domain shown as megalocephaly. An effective method of combating megalocephaly is orthogonal frequency division multiplexing - orthogonal frequency division multiplexing - (OFDM), which is equivalent to the representation of a single frequency-selective channel multiple frequency subchannels, in which the frequency selectivity is missing. This fact is reflected in developing standards of modern communication systems such as IEEE 802.16, 802.20, which will include all the basic mechanisms using MIMO-OFDM.

The implementation of the method of the invention consider the following example of a communication system MIMO-OFDM.

In OFDM systems, the transmission-reception of signals between transmitting and receiving stations through many physical links. As data physical channels using orthogonal frequency subchannels corresponding to different lifting the existence of the OFDM signal.

Increasing the capacity of the method of the invention is implemented through joint service multiple subscriber stations through the same physical channel.

In order that the signals did not create mutual interference in the reception points, on the BS immediately before the transfer perform joint processing of data signals to the speakers. While using the information on the communication channel.

To implement this method, it is necessary that the total number of antennas of the subscriber stations did not exceed the number of base station antennas. If, for example, the BS is equipped with 4 antennas, N=4, at the same time you can maintain 4 ° C with one antenna and 2 speakers, each of which has two antennas, one or speakers with one and one AC - with three antennas.

This requirement limits the number of concurrent subscribers. However, in the communication system can be quite a large number of users. Therefore, in the control unit 4 of the base station 1 performs the organization AC 6.1-6.L, by combining them into groups. In the process to determine the AC joint and individual service. In each group, joint service, all speakers serve together in the frequency sub-total for speakers of this group. In the group of speakers of individual service each speaker system is t individually by means of frequency subchannels, dedicated only to this AC. In the process groups use different parameters, such as the number of antennas, the load on the base station long-term information about the communication channel quality indicator channel for each speaker and other

The method of the invention can be used in group shared services SA, as well as for individual use those speakers who have more than one antenna.

Let us consider the implementation of the claimed invention with reference to figure 2-7.

In the structural diagrams (Fig.2-7) not shown of the device and the synchronization signals, although it is implied that they are needed and are always present when implementing blocks included in structural diagrams of devices, which carry out the inventive method. The synchronization signals in the devices is performed by any known method (traditionally) for data communication systems and does not change with respect to the algorithm according to the present method, therefore, for simplicity the description of the synchronization signals and, accordingly, devices that perform these functions are omitted.

Also for simplicity, all connections (links) in structural diagrams are shown by the lines the same thickness (tires), although some compounds reflect the transfer of single digital and analog signals, and the other shows the arrays of signals matrices, since all of these signals have a complex structure.

Figure 2 performed structural diagram of the transmitter 2 communication system MIMO-OFDM, in which the method according to the claimed invention.

The transmitter 2 (figure 2) contains:

shapers signal groups AC joint maintenance 11.1-11.U, where U is the maximum number of groups of the AC joint service

the driver signals for speakers of personal service 12,

driver utility signals 13,

the OFDM modulators 14.1-14.N.

The first To inputs of each of the formers 11.1-11.U receive informational messages intended for transmission to subscriber stations of the respective group. On the second F of the inputs of each of the formers 11.1-11.U come estimation channel matrix for those subcarriers that are used for maintenance of the speakers of the respective group. On each of the N outputs of each of the U forming signals are formed F subcarriers intended for transmission through the corresponding transmitting antenna.

Number and number of used subcarriers act as control signals from the control unit BS via the control inputs of the formers 11.1-11.U.

For reasons of readability in the structural diagrams (Fig.2-5) does not show the control signals, although it is implied that they come from the unit control the Oia BS on the control inputs of blocks, included in structural diagrams of devices, which carry out the inventive method.

Designed for transmission of signals generated at the outputs of the formers 11.1-11.U arrive at the inputs of the OFDM modulators 14.1-14.N.

Signals for speakers of personal service form in the imaging unit 12. In the control unit BS 4 determine the frequency channels (subcarriers) to communicate with each of the speakers in this group. When forming the signal distribution of data subcarriers and modulation schemes, coding techniques and methods of transfer-acceptance, provided the used communication standard (see, for example, [2]) and defined in the system for subscriber stations personal service.

Signals intended for transmission to the MSS personalized service, formed from the outputs of the shaper 12, proceed to the other inputs of the OFDM modulators 14.1-14.N.

The former official signals 13 form service signals required for the implementation of the communication system, MIMO-OFDM, such as pilot signals (pilot signals), the signals of the zero carrier (carrier null), protective strips (guard bands)carrying direct current (DC carrier), [2] TM IEEE Standard for tocal and metropolitan area networks. Part 16: Air Interface for Fixed Broadband Wireless Access Systems, 1 October 2004.

The signals generated in the shaper 12 and 13, are received at the other input of the OFDM modulators. Thus, to the inputs of each is from the OFDM modulators 14.1-14.N receives signals of all frequency subchannels, used in the system intended for transmission via the transmitting antenna connected to the output of this modulator OFDM. In the OFDM modulators 14.1-14.N perform standard operations on the formation of the OFDM signal (inverse discrete Fourier transform, add cyclic prefix - see, for example, [9] John G.Proakis, "Digital Communication," McGrow-Hill, Third Edition), and the conversion to analog form, the transfer in the field of radio frequency and signal processing for radio frequency. After that, the generated radio signals pass through the transmitting antennas 15.1-15.N.

For a better understanding of the invention will consider in detail the operation of the shaper signal group AC joint maintenance 11.1-11.U, block diagram, one of which is made in figure 3 and is shown as an example implementation. Each driver signal group AC joint maintenance 11.1-11.U consists of a node forming an information packet 16 and F nodes multiplayer processing 17.1-17.F, where F is the maximum number of frequency subchannels allocated for communication with subscribers of the AC joint service.

From the first To the input of the shaper signal group AC joint service 11 to the inputs of node formation information packages 16 receive information messages intended for transmission respectively To the subscriber stations of the Anna group of subscribers. Node 16 of these messages form F sequences of packets of modulation symbols. The sequence formed on a single output node 16, is intended for transmission in the corresponding frequency sub-channel.

With each of the F output node of development of information packages 16 sequence of packets of modulation symbols is supplied to the first input of the corresponding node multiplayer processing 17.1-17.F. To the second input of each node multiplayer processing enters the estimation channel matrix corresponding frequency subchannel from the second input of the shaper signal group AC joint service 11.

At each n-th output (n=1, ... N) of each f-number (f=1, ... F) multi-user processing, a signal is generated that is designed to pass through n-th transmitting antenna in the f-th frequency subchannel.

The set of signals thus formed from the outputs of the nodes multiplayer processing 17.1-17.F, is supplied to the output driver signal group AC joint service 11. From the outputs of the formers 11.1-11.U this combination of signals fed to corresponding inputs of a corresponding OFDM modulators 14.1-14.N (figure 2).

Let us consider the procedure of creating information packages. Figure 4 as an example of the proposed pic the BA presents a block diagram of the execution site of development of information packages 16. The site of formation of the information package consists of parallel channels of signal processing. Each channel performs signal processing of one To subscriber stations AC joint service. Channel signal processing individual speakers is formed by series-connected subnode coding 18, the modulator 19 and the sub-node distribution subchannels 20.

Inputs subnodes encoding 18.1-K are To the input node of the formation of data packets 16.

On To the input node of the formation of information packages 16 are received respectively To sequences of binary symbols. Sequence data received from the control unit BS 4 (figure 1), which are formed of the messages intended for transmission To subscriber stations, respectively.

In the sub-node encoding 18 of each of the channels To handle coding and interleaving of the input sequence of binary symbols. In the modulator 19 performs the modulation of the received coded sequence of binary symbols. The operation of the encode, interleave, and modulate perform in accordance with the selected types of coding and modulation, as well as algorithms interleave, provided the used communication standard (see, for example, [2] TM IEEE Standard for local and metropolitan area networks. Part 16: Air Interface for Fixed Broadband Wireless access Systems, 1 October 2004).

The sequence of modulation symbols generated at the output of modulator 19, to the input of the sub-node distribution subchannels 20, where this sequence is distributed between F frequency subchannels. Thus, F outputs of the sub-node 20 are formed subsequences of the symbol modulation, intended for transmission in the respective frequency sub-channels.

From the outputs of the subnodes 20.1-C formed subsequence arrive at the inputs of F shapers packages of frequency subchannels 21.1-21.F, so that a subsequence of different subscribers intended for transmission in the same frequency subchannel, proceed to the inputs of the former (21.1-21.F the respective frequency sub-channel.

In each of the F shapers 21.1-21.F form a sequence of packets of modulation symbols intended for transmission to subscriber stations served by the group in the corresponding frequency sub-channel.

The data packets are formed so that each package contains M modulation symbols, where M is the total number of receiving antennas of this group of subscriber stations. Moreover, the number of symbols allocated for transmission of each speaker, corresponds to the number of receiving antennas. Each packet generated at the output of one of the shapers 21.1-21.F, the process further processing are represented as M-dimensional vector of transmitted modulation symbols a=[a 1, ... aM]T.

Formed packet sequence of modulation symbols, intended for transmission to subscriber stations served groups in the respective frequency sub-channels with outputs F shapers 21.1-21.F arrive at the output node of the formation of data packets 16.

Let us consider the procedure multiuser processing, which is done by nodes 17.1-17.F. block diagram of the node 17 as an example implementation presented on figure 5. Each of the nodes multiplayer processing 17.1-17.F consists of a sub-node transformation vector signal 22, the sub-node processing channel matrix 23, subnode summation 24, subnode of the formation of the perturbation vector 25, sub-node linear transformation 26 and subnode regulation 27 while the first input node multiplayer handle 17 is the input node of the transformation vector signal 22, and the second input is the input node of the formation of the channel matrix 23, the output sub-node transformation vector signal 22 is connected with the first inputs of sub-node summation 24 and the sub-node of the formation of the perturbation vector 25, the first output sub-node processing channel matrix 23 is connected with the second input node the formation of the perturbation vector 25, the third input is combined with the second input of the sub-node linear transformation 26 isodine with the second output sub-node processing channel matrix 23, the output node of the formation of the perturbation vector 25 is connected with the second input node summation 24, the output of which is connected to the first input of the sub-node linear transformation 26, N outputs which are connected to N inputs of the sub-node of regulation 27, N outputs which are output node multiplayer processing 17.

The host of a multiplayer processing 17 operates as follows.

From the first input node 17 to the input of the sub-node transformation vector signal 22 is fed the sequence vector of transmitted modulation symbols and one of the frequency subchannels formed on the respective output node of the formation of data packets. In the sub-node 22 M-dimensional vector of transmitted modulation symbols and transform in 2M-dimensional real-valued vector of transmitted modulation symbols arin accordance with the formula

where Rea, Ima - vectors composed of the real and imaginary parts, respectively the corresponding elements of the vector A. Thus formed is real-valued vector arfrom the output of the sub-node 22 is supplied simultaneously to the first inputs of sub-nodes summation 24 and forming the perturbation vector 25.

To the input of the sub-node processing channel matrix 23 from the second input node 17 receives the channel matrix H corresponding often the th subchannel.

Each element of hj,ithe channel matrix is an estimate of the coefficient of transmission of the signal in the spatial channel, formed by the i-th transmitting antenna BS and j-th receiving antenna of this group of subscriber stations. This ratio is usually represented as a complex number module which reflects the change in amplitude and argument - changing the phase of the signal passing through the corresponding spatial channel.

There are different methods to obtain estimates of these coefficients. For example, if the communication system uses time division forward and reverse channel, the data evaluation form at the base station on the back channel signals received from subscriber stations. If the communication system uses frequency division forward and reverse channels, estimates of the elements of the channel matrix form in the receivers of the subscriber stations 8.1-8.L and pass on the BS 1 according to the feedback channel. Methods of estimating the channel in the system MIMO-OFDM known from the literature, for example, [12] Z.Jane Wang, Zhu Han, and K.J.Ray Liu, "A MIMO-OFDM Channel Estimation Approach Using Time of Arrivals," IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 4, NO.3, MAY 2005, pp.1207-1213.

In the sub-node conversion channel matrix 23 implement the following algorithm.

1. Channel matrix H of dimension M×N transform the real-valued matrix Hrrazmer the STI 2M×2N in accordance with the formula

where ReH, ImH - matrix composed of the real and imaginary parts, respectively of the respective elements of the matrix N.

2. Of real-valued channel matrix Hrform the matrix a preliminary linear transformation of the signal by the formula

where (.)Hthe symbol of transposition and complex conjugation,

(.)-1symbol inversion of the matrix.

Thus formed matrix Wrrouted to the first output node 23 and the second input sub-node linear transformation 26 and the third input node of the formation of the perturbation vector 25.

3. By the reduction of the basis of the lattice of the matrix Wrform of an integer matrix with determinant equal to ±1, the multiplication which converts the matrix preliminary linear transformations in the matrix Z=WrT with a low condition number.

When this is used, for example, a well-known algorithm of reduced basis of the lattice, named after the abbreviation of the names of the authors of the LLL (Lenstra-Lenstra-Lovasz) and presented in [10] Dirk Wubben, Ronald Böhnke, Volker Kühn, and Karl-Dirk Kammeyer, "Near-Maximum-Likelihood Detection of MIMO Systems using MMSE-Based Lattice Reduction", IEEE Proc. International Conference on Communications (ICC), Paris, France, June 2004 [11] A.K.Lenstra, H.W.Lenstra, and L.Lovasz, "Factoring potynomials with rational coefficients", Mathematische Annaten, vol. 261, pp.515-534, 1982.

Formed so about what atom, the matrix T from the output of the node 23 is supplied to the second input node of the formation of the perturbation vector 25.

Sub-node of the formation of the perturbation vector 25 operates in accordance with the following algorithm.

1. Using the matrix T, and the real-valued vector of transmitted modulation symbols ardetermine not quantized vector perturbations as

where a is a real number such that real and imaginary part of any modulation symbol α in absolute value strictly less than A/2, that is,

2) perform the rounding of each of the elements of the received vector z to the nearest largest integer that identifies, therefore, the first quantized vector z1and, however, define the vector of d1the corresponding values of the quantization errors in formulas

where Q(z) is the elementwise operation of the rounding vector z to the nearest integer,

3) form the second quantized vector z2by determining for each element of the vector z of the second nearest largest integer with the opposite value of the quantization error, and a second vector corresponding values of the quantization error d2according to the formula

where through sign(a) denotes the vector polucen the th of vector and applying to each element of the operation

4) of the elements of the first z1and the second z2the quantized vectors of the form R quantized vectors u, with the lowest values of total quantization error vector, and the total quantization error vector is defined as a sum (or sum of squares) of the absolute quantization errors of all the elements of the vector

5) each of the R quantized vectors u transform by the formula

forming, thus, many candidate perturbation vectors

6) determine the optimal perturbing vector of p0as the vector from the set of candidate perturbation vectors for which the key functionminimum.

Formed thus the optimal perturbing vector R0from the output of the sub-node 25 is supplied to the second input of the sub-node summation 24, where the sum is real-valued vector of transmitted symbols and the optimal perturbing vector, forming, thus, perturbed real-valued vector of transmitted symbols (ar+p0).

Perturbed real-valued vector of transmitted symbols (ar+p0with the output node 24 is supplied to the first input of the sub-node linear transformation 26.

In the subnode 26 perform a preliminary linear transformation of the received indignantly what about the real-valued vector of modulation symbols, forming a real-valued vector of transmitted signals in accordance with the formula:

From the obtained real-valued vector of transmitted signals xrin the subnode 26 form a non-normalized vector of transmitted signals

where j is the imaginary unit, as in xr(n:m) denotes a vector composed of a sequence of elements of vector xrfrom n-th to m-th.

Thus, the N outputs of the sub-node linear transformation 26 respectively form N elements of the non-normalized vector of transmitted signals x0. From the outputs of the sub-node 26 data signals to the corresponding inputs of the sub-node of regulation 27, where they form the vector of transmitted signals of a given frequency subchannel by multiplying the non-normalized transmitted signals by a factor of regulation CT,

Factor rating CTis a real number, which is chosen so that the average transmit power of the signals generated vector x was equal power signals receiving stations without multiplayer conversion.

The set of signals corresponding to the elements of the received vector x, is supplied to the output node of regulation 27 and respectively in the passages host a multiplayer processing 17. The set of signals corresponding to the elements of the received vector x, is passed in the corresponding frequency subchannel through all transmitting antennas - one signal through the antenna. To this end, the signals intended for simultaneous transmission through each of the n-th antenna (n=1, ... N) in the frequency subchannels allocated for transmission of the signal groups AC joint service, proceed to the appropriate inputs of the n-th OFDM modulator.

The functions of the OFDM modulators 14.1-14.N presented above in the description of operation of the transmitter 2.

Let us consider the implementation of the claimed invention in the receiver SA block diagram is executed on 6.

The receiver of the subscriber station has Mkreceiving antennas 7.1 to 7.Mkand the same number of the signal processing units receiving antennas 28.1-28.Mkand the block decoding 29, where k is the index of the subscriber stations.

The signal from each receiving antenna 7.1 to 7.Mkarrives at the input of the corresponding block signal processing 28.1-28.Mk. In each of the blocks 28.1-28.Mkperform the signal processing, which results in F sequences of binary symbols adopted by the respective receiving antenna in F frequency subchannels.

Each processing unit of the signal receiving antenna 28.1-28.Mk(structural scheme as an example of the implementation is made on Fig) contains the OFDM demodulator 30, F nodes regulation 31.1-31.F and the same number of nodes modular reduction 32.1-32.F and demodulators 33.1-33.F.

The OFDM demodulator input is the input of the processing unit of the signal receiving antenna 28.F. Outputs F demodulators 33.1-33.F are both F outputs of the processing unit of the signal receiving antenna.

In the OFDM demodulator 30 performs signal processing on a radio signal, the synchronization of the OFDM signal, removing the cyclic prefix and the discrete Fourier transform, the result of which are the signals F of frequency subchannels. Operations demodulation of the OFDM signal is represented, for example, in [9] John G.Proakis, "Digital Communication", McGrow-Hill, Third Edition.

Thus, each of the F output of the OFDM demodulator 30 form the y signal, which is a complex number with modulus and the argument corresponding to the amplitude and phase of the signal in this frequency subchannel.

The signal of each of the F frequency subchannels are treated independently in the corresponding subchannel processing formed by series-connected node of regulation 31, the node modular reduction demodulator 32 and 33.

Each subchannel processing each receiving antenna perform the following operations.

Under regulation 31 normalized signal y by multiplying it by a factor of regulation CRforming, thus, normer the cell signal

where the factor rating CRset, for example, equal to the inverse value of the ratio of normalized transmission:

Node modular reduction 32 define the real and imaginary parts of the normalized signal ynorm

With the received signals z and node 32 performs the operation of nonlinear modular reduction modulo:

where [x] is the integer part of x, that is, the maximum integer less than X.

From signalsandform an integrated signalwhich goes to the output node of the modular reduction 32 and further to the input of the demodulator 33.

In the demodulator 33 performs demodulation of the complex signalin the usual way, forming a sequence of estimates the received binary symbols.

The resulting sequence of estimates of binary symbols adopted in the F frequency subchannels, with the outputs of the demodulators 33.1-33.F come to the outputs of the processing unit of the signal receiving antenna 28 and then to the corresponding inputs of the block decoding 29.

Thus (see Fig.6), the generated sequence with F outputs of each block 28.1-28.M karrive at the corresponding inputs of the block decoding 29, where F is a sequence of estimates of the binary symbols unite and perform deteremine and decoding, inverse to those used in one of the subnodes encoding 18.1-C transmitter BS (figure 4)corresponding to a given k-th subscriber stations.

Thus, the output of block decoding 29 of the receiver of the subscriber station 8 form a sequence of binary symbols in the received message.

To characterize the noise immunity of the algorithm of transfer-acceptance signal developed in accordance with the method according to the claimed invention, was performed computer simulation.

For the simulation was developed a software model of the transmitter with N=4 antennas and 4 receivers subscriber stations, each equipped with a single receiving antenna.

The developed model corresponds to one group of the AC joint service. The structure of such models described above and shown in figure 1-7.

For simplicity in the programming model was used only one physical (frequency) channel for transmission and reception of a signal in a multi-user MIMO communication system.

The simulation results of multi-user MIMO algorithms when the total spectral efficiency of 8 bits/s/Hz is given n Fig. The curves on this drawing reflect the dependence of the BER on EB/N0where BER is the bit error rate, the error probability of receiving a bit signal, averaged over all subscriber stations, EB/N0- average ratio of bit energy signal EBthe spectral density of noise power, N0at the point of reception. It is assumed that the conditions of reception and transmission speed is the same for all speakers.

When modeling algorithms were used convolutional coding with rate 1/2 and the size of the original block is not coded binary symbols 192 bits. Used channel model with block fading and additive Gaussian noise.

Modeling algorithms

preliminary coding MMSE,

algorithm prototype and

algorithm of the proposed solutions

made for 4 subscriber stations, each of which has 1 reception antenna. For a signal to each speaker were used modulation 16QAM.

The simulation algorithm of precoding block diagonalizable performed for 2 subscriber stations, each of which has 2 receiving antennas. Transmission and reception in the generated orthogonal MIMO channels each speaker was performed according to the method of their own subchannels. We used 2 own subchannel with 64QAM modulation and BPSK, respectively.

Presents characteristics confirmed listout about what in the workspace values of BER (BER<=0.05) algorithm that implements the inventive method has a maximum noise immunity relative to the other considered algorithms.

Thus, the inventive method of transfer-acceptance signal in multi-user communication system with multiple transmitting and multiple receiving antennas can significantly improve the throughput of multiuser MIMO communication system, as does the simultaneous maintenance of a group of subscriber stations in the same physical channel.

For noise immunity, the algorithm that implements the inventive method, than the known multi-user MIMO algorithms [4] Q.H.Spencer, and M.Haardt, "Capacity and Downlink Transmission Algorithms for a Multi-user MIMO Channel", Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference, Volume 2, Issue, 3-6 Nov. 2002 Page(s): 1384-1388 vol.2, [5] J.C.Mundarath, J.H.Kotecha, "Zero-Forcing Beamforming for Non-Collaborative Space Division Multiple Access", Proceedings of 2006 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 14-19 May 2006, Volume: 4, page(s): IV-IV, [6] A Wicsel, Y.C.Etdar, and Sh.Shamai, "Optimal Generalized Inverses for Zero Forcing Preceding", 41st Annual Conference on Information Sciences and Systems, CISS' 07, 14-16 March 2007, pages: 130-134, as well as the algorithm, which served as the prototype of the proposed method [8] Christoph Windpassinger, Robert F.H.Fischer, and Johannes B.Huber, "Lattice-Reduction-Aided Broadcast Preceding", IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO.12, DECEMBER 2004, pp.2057-2060.

This advantage of the proposed method is achieved PU is eaten using the new sequence of interrelated actions, including the procedure vector perturbations in combination with a reduction of the basis of the lattice and multi quantization.

Moreover, an advantage of the method according to the present invention is a relatively simple implementation of the transmitter and, especially, a simple implementation of a receiver of the subscriber station. When this receiver speakers sell them as independent channels of processing signals of different receiving antennas.

A significant advantage of this invention is that it is possible to implement if there is only one receiving antenna at each of the subscriber stations of the communication system.

Another important advantage of the invention is the possibility of its implementation in almost any environment distribution. Explain that for the implementation of traditional stand-alone methods MIMO required distribution environment with a large number of scattering objects, which is not always realized in practice. At the same time, the method according to the claimed invention provides a gain in throughput even in an environment with relatively low scattering, since the antenna of the receiving parties belong to different subscriber terminals, so that their signals have a low correlation, regardless of the medium of propagation.

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11. A.K.Lenstra, H.W.Lenstra, and L.Lovasz, "Factoring potynomials with rational coefficients", Mathematische Annalen, vol. 261, pp.515-534, 1982.

12. Z. Jane Wang, Zhu Han, and K.J.Ray Liu, "A MIMO-OFDM Channel Estimation Approach Using Time of Arrivals", IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VO. 4, NO.3, MAY 2005, pp.1207-1213.

1. The method of transfer-acceptance signal in multi-user communication system with multiple transmitting and multiple receiving antennas, which use a transmitting station equipped with N transmitting antennas and receiving stations, where K≥2, and each receiving station is equipped with at least one receiving antenna, and the total number of receiving antennas of the receiving stations M satises 1<M≤N, and the transmission-reception of signals between transmitting and receiving stations through F physical communication channels, where F≥1, namely, that for each of F physical channels to estimate the parameters of the aggregate spatial communication channels, each of which is formed of one transmitting antenna of the transmitting station and one receiving antenna of the receiving station; transfer-receiving signals between a transmitting station and receiving stations, using F physical channels, which at the transmitting station To form sets of modulation symbols intended for transmission To the receiving stations, respectively, To the generated sets of characters modulation form F packages M modulation symbols each including in a package of Mkthe modulation symbols for each k-th receiving station, where Mk- the number of receiving antennas of the k-th is zemnoi station; transfer each of the F symbol packages modulation corresponding physical channel, and the symbol package modulation present in the form of a vector of transmitted modulation symbols a=[α1...αM]Twhich each element is a complex number, modulus and argument, reflecting the amplitude, and accordingly the phase of the corresponding symbol modulation, perform multi-user transformation of the vector of transmitted modulation symbols in the vector of transmitted signals x so that the transmitted signals did not create interference in the M receiving antennas of the receiving stations, which form a channel matrix H for a given physical channel using transfer coefficients of the spatial channels of communication, from the vector of transmitted modulation symbols and the channel matrix H form a real-valued vector arand the matrix Hrin accordance with formulas

where ReY, ImY - matrix composed of the real and imaginary parts, respectively of the respective elements of the matrix Y,
of real-valued channel matrix Hrform the matrix Wrpreliminary linear transformation of the signal by the reduction of the basis of the lattice of the matrix Wrform of an integer matrix T with Opredelitel is m, equal to ±1, the multiplication which converts the matrix preliminary linear transformations in the matrix Z=WrT with a false low condition number using the matrix T, and the real-valued vector of transmitted modulation symbols ardetermine not quantized vector perturbations, as

where a is a real number, such that real and imaginary part of any modulation symbol for absolute value is less than A/2, perform the rounding of each of the elements of the received vector z to the nearest largest integer that identifies, therefore, the first quantized vector z1define the vector of the corresponding values of the quantization errors
z1=Q(z), d1=z1-z
where Q(z) is the vector obtained elementwise rounding vector z to the nearest integer,
form the second quantized vector z2by determining for each element of the vector z of the second nearest largest integer with the opposite value of the quantization error, and a second vector corresponding values of the quantization errors of the elements of the first z1and the second z2quantized vectors To form quantized vectors and lowest values of total quantization error vector, the total quantization error vector is predelut, for example, as the sum or the sum of squares of absolute quantization errors of the vector elements, each of the R quantized vectors u transform according to the formula
p=-A·T·u,
forming, thus, many candidate perturbation vectors, determine the optimal perturbing vector of p0as the vector from the set of candidate perturbation vectors, for which the crucial function F(p)=||Wr·ar-p||2minimum, form a perturbed real-valued vector of transmitted modulation symbols by adding real-valued vector of transmitted modulation symbols and the optimal perturbing vector and perform a preliminary linear transformation of the received perturbed real-valued vector of modulation symbols forming, thus, a real-valued vector of transmitted signals,
xr=Wr(ar+p0),
from the obtained real-valued vector of transmitted signals xrform a non-normalized vector of transmitted signals
x0=xr(1:N)+j·xr(N+1:2N),
where j is the imaginary unit,
and after xr(n:m) denotes a vector composed of a sequence of elements of vector xrfrom n-th to m-th;
form the vector of transmitted signals, multiplying the vector of the non-normalized transmitted signals by a factor of regulation CT,
x=x ·CT
the set of signals corresponding to the elements of the received vector x, is passed in the corresponding physical channel through all transmitting antennas - one signal through the antenna; receive signals on each of the receiving stations, and in each physical channel of each receive antenna reception is carried out in such a way that form the signal as a complex number with modulus and the argument corresponding to the amplitude and phase of the received physical data channel signal, the normalized signal by multiplying it by a factor of regulation CRforming, thus, the normalized signal
thenorm=y·CR,
determine the real and imaginary parts of the normalized signalnorm
z=Reynormc=Imynormreceived signals z and c perform the operation modular reduction modulo:

where- the integer part of x, that is, the maximum integer less than x,
from signalsandform an integrated signal

using the values of the complex signalformed this way in each physical channel of each receive antenna, performs demodulation and decoding of a received signal.

2. The method according to claim 1, distinguished by the different topics that for each F physical channels in the quality of the estimated parameters using the transfer rate of the communication channel and the signal-to-noise ratio in the channel.

3. The method according to claim 1, characterized in that at the transmitting station To each of the information messages destined for transmission To the receiving stations are respectively in the form of a sequence of binary symbols, and then perform the coding, interleaving and modulation of binary symbols of the sequence.

4. The method according to claim 1, characterized in that the matrix Wrpreliminary linear transformation of the signal form as

where Hris real-valued channel matrix for a given physical channel.

5. The method according to claim 1, characterized in that the second quantized vector z2and a second vector corresponding values of the quantization errors are formed by formulas
z2=z1-sign(d1), d2=z2-z
where through sign(a) denotes the vector obtained from the vector a,

applying to each element of the operation.

6. The method according to claim 1, characterized in that when forming the vector of transmitted signals coefficient normalization CTis chosen so that the average transmit power of the signals generated vector x equal power signal is fishing, transmitted to receiving stations without multiplayer conversion.



 

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