MXPA06007967A - Data transmission with spatial spreading in a mimo communication system - Google Patents

Abstract

For data transmission with spatial spreading, a transmitting entity (1) encodes and modulates each data packet to obtain a corresponding data symbol block, (2) multiplexes data symbol blocks onto Ns data symbol streams for transmission on Ns transmission channels of a MIMO channel, (3) spatially spreads the Ns data symbol streams with steering matrices, and (4) spatially processes Ns spread symbol streams for full-CSI transmission on Ns eigenmodes or partial-CSI transmission on Ns spatial channels of the MIMO channel. A receiving entity (1) obtains NR received symbol streams via NR receive antennas, (2) performs receiver spatial processing for full-CSI or partial-CSI transmission to obtain Ns detected symbol streams, (3) spatially despreads the Ns detected symbol streams with the same steering matrices used by the transmitting entity to obtain Ns recovered symbol streams, and (4) demodulates and decodes each recovered symbol block to obtain a corresponding decoded data packet.

Description

DATA TRANSMISSION WITH SPACE PROPAGATION EH A MIMO COMMUNICATION SYSTEM FIELD OF THE IHVEHCIÓM The present invention relates generally to communication, and more specifically to the techniques for transmitting data in a multiple output / multiple input (MIMO) communication system.

BACKGROUND OF THE INVENTION A MIMO system employs multiple transmit antennas (? t) in a transmitting entity and multiple receive antennas (? R) er. a receiving entity for data transmission. A MIMO channel formed by transmit antennas? T and receive antennas? R that can be decomposed into spatial channels? S, where? S = min. { ? T /? R} . Space channels can be used to transmit data in parallel to achieve higher performance and / or redundantly achieve greater reliability. The MIMO channel between the transmitting entity and the receiving entity may experience various harmful channel conditions such as, for example, fading, multiple path, and interference effects. Generally, a good performance can be achieved to transmit the data through the MIMO channel if the interference and noise observed in the receiving entity are spatially "white", which is the noise power and constant and flat interference through the spatial dimension. However, this can not be the case if the interference comes from sources of interference located in specific directions. If the interference is spatially "colored" (not white), then the receiving unit can establish spatial characteristics of the interference and place the light ray nulls in the direction of the interference sources. The receiving entity can also provide the transmitting entity with the channel status information (CSI). Subsequently, the transmitting entity may process the data spatially in a manner to maximize the ratio of the noise / interference signal (SNR) to the receiving entity. In this way, a good performance can be achieved when the receiving and transmitting entities perform the appropriate transmission and reception spatial procedure for the transmission of data in the presence of spatially colored interference. To perform the nullity of spatial interference, the receiving entity typically needs to determine the characteristics of the interference. If the interference characteristics change as time passes, then the receiving entity will need to obtain the continuously updated interference information to place exactly the light ray nulls. Possibly, the receiving entity also needs to continuously send the channel status information at a rate sufficient to allow the receiving entity to perform the appropriate spatial procedure. The need for accurate interference information and channel state information results in nullity of spatial interference that is impractical for most MIMO systems. Therefore, the techniques for transmitting the data in the presence of spatially colored noise and interference are necessary.

SUM II OF THE INVENTION In one embodiment, a method for transmitting data from a transmitting entity to a receiving entity in a multiple input / output communication system (MIMO) is described, in which the data is processed to obtain a plurality of data symbol streams to be transmitted in a plurality of transmission channels in a MIMO channel between the transmitting entity and the receiving entity. Spatial propagation is developed in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagation symbol streams, wherein the spatial propagation with the plurality of address matrices randomizes the plurality of channels of propagation. transmission for the plurality of data symbol flows. The spatial procedure is developed in the plurality of propagation symbol streams to obtain a plurality of transmission symbol streams to be transmitted from a plurality of relay antennas to the transmitting entity. In another modality, an apparatus is described in a multiple input / output communication (MIMO) system that includes a data processor to process the data to obtain a plurality of data symbol streams to be transmitted in a plurality of transmission channels in a channel MIMO between a transmitting entity and a receiving entity in the MIMO system; a spatial propagator for performing spatial propagation in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagation symbol streams, wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol flows; and a spatial processor that performs the spatial procedure on the plurality of propagation symbol streams to obtain a plurality of transmission symbol streams to be transmitted from a plurality of transmit antennas at the transmitting entity. In another embodiment, an apparatus is described in a multiple input / output communication (MIMO) system that includes the means for processing the data to obtain a plurality of data symbol streams to transmit on a plurality of transmission channels in a MIMO channel between a transmitting entity and a receiving entity in the MIMO system; means for performing spatial propagation in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagation symbol streams, wherein the spatial propagation with the plurality of address matrices randomizes the plurality of channels transmission for the plurality of data symbol flows; and means for performing the spatial procedure on the plurality of propagation symbol streams to obtain a plurality of transmission symbol streams to be transmitted from a plurality of transmit antennas in the transmitter unit. In another embodiment, a method for receiving a data transmission sent by a transmitting entity to a receiving entity in a multiple outgoing / incoming communication system (MIMO) is described, in which a plurality of received symbol streams are obtained for a plurality of data symbol streams transmitted through a plurality of transmission channels in a MIMO channel, wherein the plurality of data symbol flows with a plurality of address macrices is spatially propagated and further processed spatially before its transmission through the MIMO channel, and wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol streams. The receiving spatial procedure is performed in the plurality of received symbol streams to obtain a plurality of detected symbol streams. The spatial depropagation plays in the plurality of detected symbol streams with the plurality of address matrices to obtain a plurality of recovered symbol streams, which are calculated from the plurality of data symbol streams.

In another embodiment, an apparatus is described in a wireless multiple input / output (MIMO) communication system that includes a plurality of receiver units to obtain a plurality of received symbol flows for a plurality of data symbol flows transmitted through of a plurality of transmission channels in a MIMO channel from a transmitting entity to a receiving entity, wherein the plurality of data symbol flows with a plurality of address matrices is spatially propagated and further processed spatially before transmitting them through of the MIMO channel, and wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol flows; a spatial processor for performing the receiver spatial procedure on the plurality of received symbol streams to obtain a plurality of detected symbol streams; and a spatial despread to perform spatial despreading in the plurality of symbol streams detected with the plurality of address arrays to obtain a plurality of retrieved symbol streams, which are calculations of the plurality of data symbol streams. In another embodiment, an apparatus is described in a multiple input / output communication (MIMO) system that includes the means for obtaining a plurality of received symbol streams for a plurality of data symbol streams transmitted through a plurality of data streams. transmission channels in a MIMO channel from a transmitting entity to a receiving entity, wherein the plurality of data symbol streams are spatially propagated with a plurality of address matrices and further processed spatially before being transmitted through the MIMO channel , and where the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol streams; means for performing the receiver spatial procedure in the plurality of received symbol streams to obtain a plurality of streams . of detected symbols; and means for performing spatial despreading in the plurality of detected symbol streams with the plurality of address arrays to obtain a plurality of retrieved symbol streams, which are calculations of the plurality of streams of data symbols.

BRIEF DESCRIPTION OF THE FIGURES Figure 1 shows a MIMO system with a transmitting entity, a receiving entity, and two interference sources 25.

Figure 2 shows a model for data transmission with spatial propagation. Figure 3 shows the procedure developed by the transmitting entity. Figure 4 shows the procedure developed by the receiving entity. Figure 5 shows a block diagram of the entities, receiving and transmitting. Figure 6 shows a transmission data processor (TX) and a spatial processor TX in the transmitting entity. Figure 7 shows a receiver spatial processor (RX) and an RX data processor in the receiving entity. Figure 8 shows a spatial processor RX and an RX data processor implementing a successive interference cancellation technique (SIC).

DETAILED DESCRIPTION OF THE INVENTION The word "exemplary" is used in the present invention to mean "which serves as an example, instance, or illustration." Any modality described in the present invention as "exemplary" is not necessarily mentioned as being preferable or advantageous over other modalities. The techniques for transmitting data with spatial propagation in MIMO systems of multiple carriers or single carrier are described in the present invention. Spatial propagation refers to the transmission of a data symbol (which is a modulation symbol for data) in spatial channels or multiple own modes (described below) of a MIMO channel simultaneously with an address vector. Spatial propagation randomizes a transmission channel observed by means of a flow of data symbols, which whitens the flow of the transmitted data symbol and can provide several benefits described below. For transmitting data with spatial propagation, a transmitting entity processes (eg, encodes, interleaves, and modulates) each data packet to obtain a corresponding block of data symbols and multiplexes the blocks of the data symbol into symbol streams. Ns data to transmit them in the Ns transmission channels in a MIMO channel. Subsequently, the transmitting entity spatially propagates the data symbol streams Ns with address matrices to obtain propagation symbol flows Ns. The transmitting entity further spatially processes the propagation symbol streams Ns for, either the total CSI transmission in the Ns own modes of the MIMO channel or the partial CSI transmission in the Ns spatial channels in the MIMO channel, as described below . A receiving entity obtains the received symbol flows NR and performs the receiving spatial procedure for the partial or complete CSI transmission to obtain the detected symbol flows Ns, which are calculations of the propagation symbol flows Ns. The receiving entity further spatially depresses the detected symbol flows Ns with the same address matrices used by the transmitting entity and obtains the recovered symbol flows Ns, which are calculations of the data symbol flows Ns. The spatial receiver and spatial despread procedure can be performed jointly or separately. Subsequently, the receiving entity processes (e.g., demodulates, deinterleaves, and decodes) each block of symbols received in the recovered symbol streams Ns to obtain a corresponding decoded data packet. The receiving entity may also calculate the noise / interference signal (SNR) ratio of each transmission channel used for data transmission and select an appropriate rate for the transmission channel based on its SNR. The same or different speeds can be selected for the transmission channels Ns. The transmitting entity encodes and modulates the data for each transmission channel based on its selected speed. Various aspects and embodiments of the invention are described in greater detail below. Figure 1 shows a MIMO system 100 with a transmitting entity 110, a receiving entity 150, and two interference sources 190a and 190b. The transmitting entity 110 transmits the data to the receiving entity 150 through line of sight trajectories (as shown in Figure 1) and / or reflected paths (not shown in Figure 1). The interference sources 190a and the transmission signals 190b which act as interference in the receiving entity 150. The interference observed by the receiving entity 150 from the interference sources 190a and 190b can be spatially colored. 1. Single Carrier MIMO System For a single carrier MIMO system, a MIMO channel formed by Nt transmission antennas in the transmitting entity and the NR receiving antennas in the receiving entity can be characterized by means of a NR x NT channel response matrix H which can be expressed as: where the input h ± j, for i = l ... NR and j = l ... Nt, denotes the complex channel coupling or gain between the retransmission antenna j and the receiving antenna i. The data can be transmitted in various ways in the MIMO system. For a total CSI transmission scheme, the data is transmitted in "own modes" of the MIMO channel (described below). For a partial CSI transmission scheme, the data is transmitted in spatial channels of the MIMO channel (also described below).

A. Total CSI transmission For the total CSI transmission scheme, the eigenvalue decomposition can be performed in a correlation matrix of H to obtain the proper Ns modes of H, as follows: R = H "-H = E- A - "Ec. 2 where R is a correlation matrix NT X T of H; E is a unitary matrix Nt x Nt whose columns are eigenvectors of R; ? is a diagonal matrix Nt x Nt of eigenvalues of R; and "H" denotes a conjugate transposition. A unitary matrix U is characterized by the property üH * 0 = I, where I_ is the identity matrix. The columns of a unitary matrix are orthogonal to each other. The transmitting entity can perform the spatial procedure with the eigenvectors of R to transmit the data in the proper modes Ns of H. Own modes can be visualized as orthogonal spatial channels obtained through decomposition. The diagonal entries of 2 are eigenvalues of R, which represent the power gains for the proper modes Ns. The transmitting entity performs the space procedure for the total CSI transmission as follows: ? = E-i Ec. 3 where js is a vector Nt xl with non-zero entries Ns for data symbols to be transmitted simultaneously in the spatial channels N £; and x is a vector Nt xl with transmission symbols to be sent from the transmission antennas Nt. The symbols received in the receiving entity such as: r = H-s-j Ec. 4 wherein r is a vector NR xl with received NR symbols obtained through the receiver antennas NR; and j_ is a vector NR xl of interference and noise observed in the receiving entity. The receiving entity performs the spatial procedure with a spatial filter matrix Nt x NR M =? -E -H for the total CSI transmission, as follows: =? "I-E * -E ^ -ÍH-E-s + j) Ec.5 = A-1 -E -E- A-E * -E-S + A ~ '-EH -Hff • j = § +] where s is a vector Nt xl with recovered symbols Ns or data symbol calculations, which are calculations of the data symbols N? in s; and jJ =? '-EJ? -HJÍ-j- is l, a i.nt, erfterenci? A and rui • d -Lo dje detection "after the spatial procedure in the receiving unit, a proper mode can be visualized as an effective channel between an element of s and a corresponding element of | with the receiving and transmitting entities performing the spatial procedure shown in equations (3) and (5) The receiving and transmitting entities only have calculations of the channel response matrix H, which can be obtained based on the pilot symbols A pilot symbol is a modulation symbol for the pilot, which is the data that is known previously for both transmitter and receiver entities For simplicity, the description in the present invention assumes no channel calculation error.The vector can be decomposed into an interference vector i and a noise vector n, as follows: j =? + a Ec.

The noise can be characterized by means of a self-covariance matrix NR x NR fnn = E [n 'nH), where E [x] is the expected value of x. If the noise is the additive soft Gaussian noise (A GN) with the zero medium and a variant of s2n, then the noise auto-covariance matrix can be expressed as: fnn = s 2n 'I. Similarly, interference can be characterized by a self-covariance matrix NR x NR f i = E [i 'iH]. The self-covariance matrix of j_ can be expressed as cpjj = L [j 'jH] = fnn + fii, assuming that interference and noise are not correlated. The interference and noise are considered spatially white if their self-covariance matrices are of the cr2'l_ form because they do not correlate noise and interference. For spatially white noise and interference, each receiving antenna observes the same amount of interference and noise, and the interference and noise observed at each receiving antenna does not correlate with the interference and noise observed on all other receiving antennas. For spatially colored interference and noise, self-covariance matrices have non-zero diagonal terms due to the correlation between interference and noise observed in different receiving antennas. In this case, each receiving antenna i can observe a different amount of interference and rough, which is equal to the sum of the elements NR in row i of the matrix? J3.

If the interference and noise are spatially colored, then the optimal eigenvectors for the total CSI transmission can be derived as: Eopt =? LH • f ^ = Eopt - A -Eoorpt Ec. 7 The eopt eigenvectors direct the data transmission in the direction of the receiver unit and also place the light ray nulls in the direction of the interference. However, the transmitting entity would need to be provided with the f-and self-covariance matrix to derive the EoPf eigenvectors. The matrix fjj is based on the interference and noise observed in the receiving entity and can be determined only by means of the receiving entity. To spatially cancel the interference, the receiving entity would need to send this matrix, or its equivalent, back to the transmitting entity, which can represent a large amount of channel state information to be sent back. Spatial propagation can be used to spatially bleach the interference and noise observed by the receiving entity and potentially improve performance. The transmitting entity performs spatial propagation with a set of address matrices in such a way that the complementary spatial propagation in the receiving entity spatially bleaches the interference and noise. For the total CSI transmission with spatial propagation, the transmitting entity performs the procedure as follows: ? fcsi (m) =? ¡(m) • V (m) • i (m) Ec. 8 where s_ (m) is a data symbol vector for the transmission output m; V (? N) is an address array Nt x Nt for the transmission output m; E is a matrix of eigenvectors for the transmission output m; Xfcsi (-ffl) is a transmission symbol vector for the transmission output m. A transmission output can cover frequency and / or time dimensions. For example, in a single-carrier MIMO system, a transmission output may correspond to a symbol period, which is the duration in time to transmit a data symbol. A transmission output can also cover multiple symbol periods. As shown in equation (8), each data symbol in s_ (m) is spatially propagated with a respective column of V (m) to obtain the propagated symbols Nt, which can be transmitted later in all E-modes proper. (m). The symbols received at the receiving entity can be expressed as: / csi (m) - B, (m) •? fcsi (m) + ¡(m) - Jm) • E (m) • Y (m) • s (m) + ¡(m) Ec.9 The receiving entity derives a spatial filter matrix fcsi (tf) as follows: The receiving entity performs the spatial receiving and spatial depropagation procedure using MfCSi (m) and VH (m), respectively, as follows: [physi (m) =? H (m) - Mfs, (m) • rc «(m) = YH (m) - A" 1 (m) -EH (m) - E, H (m) - [H (OT) • l (m) • V (m) • § () + j ()] Eq. 11 where j_fCSi (-? p) is the interference and noise of "post-detection" after the spatial procedure and spatial depropagation in the receiving entity, which } fcsl (m) = YH (m) -? - 1 (»?) - EffW-E" W "¡(m) Ec.12 As shown in equation (12), the noise and interference in ?) is transformed by the conjugate transpositions of V (m), E (? r <), and H (J?). E (m) is a matrix of eigenvectors that can not be optionally computed for spatially colored noise and interference if the self-covariance matrix </ i> is not known. gjj (m), which happens frequently. Transmitting and receiving entities can, by means of randomization, operate with an E (m) matrix that results in more interference and noise that the receiving entity will observe. This may be the case, for example, if an E () mode is correlated with the interference. If the MIMO channel is static, then the transmitting and receiving entities can operate continuously with an E (J?) Matrix that provides poor performance. Spatial depropagation with the direction matrix V (m) spatially blanks interference and noise. The effectiveness of the effect of whitening the interference and the noise depends on the characteristics of the response matrix of channel H (m) and the interference j_ (m). If there is a high degree of correlation between the desired signal and the interference, then this limits the amount of gain provided by the effect of bleaching the interference and noise.

The SNR of each mode can be expressed with the total CSI transmission as: 7fc k) for? = L K Ns Eq. 13 where P? (m) is the transmission power used by the transmission symbol sent in own mode? in the transmission output m; (m) is the eigenvalue for the own mode? in the transmission output m, which is the diagonal element? from ? (m); ss is the variant of the interference and received noises; and y-fca x (ia) is the SNR of the proper mode? in the transmission output m.

B. Partial CSI transmission For partial CSI transmission with spatial propagation, the transmitting entity performs the procedure as follows: ? pcs? . { i) = Y (m) - s (m) Ec. 14 where pCSi (m.) Is the transmission data vector for the transmission output m. As shown in equation (14), each data symbol is spatially propagated in s_ (m) with a respective column of V_ (m) to obtain propagated symbols Nt, which can be transmitted subsequently from all the transmit antennas Nt. The symbols received at the receiving entity can be expressed as: rpcs (m) = K (m) - Y (m) - § m) + j () = He (m) -s () + j (m) Eq. 15 where rpcsi (m) is the symbol vector received for the transmission output m; and Heff (m) is an effective channel response matrix, which is: The receiving entity can derive the calculations of the data symbols transmitted in s_ using various receiver procedure techniques. These techniques include a channel correlation matrix inversion technique (CCMI) (which is also commonly referred to as a zero force technique), a minimum mean square error (MMSE) technique, a technique for canceling successive interference (SIC), et cetera. The receiving entity may perform the spatial receiving and spatial propagation procedure jointly or separately, as described below. In the following description, a data symbol stream is sent for each element of the data symbol vector _s. For the CCMI technique, the receiving entity can derive a spatial filter matrix Mccmi (m), as follows: Mean, M = ñ "ff (m) • He (m) Yl • Meff (m) = T¿ (m) • He ^ (m) Eq. 17 The receiving entity may subsequently perform the spatial procedure and depropagation together, as follows: , - (m) ~ Mccm¡ (m) • r pcs¡ (m) n) + j (w)] Ec. H where j_ccmi (^) is the filtered CCMI and propagates the interference and noise, which is: m) = R ^ WH W-jW = fíW-R-1 () -H // () -j () Ec. 19 As shown in equation (19), the interference and the noise j_ are bleached ( m) by means of V (m). However, due to the structure of R (m), the CCMI technique can amplify interference and noise. The receiving entity can also perform the spatial procedure CCMI and spatial despropagation separately, as follows: ccmi () = YH (m) - ci (/ «) • Zpcs, (w) = V // () -R_1 () -Hí () - [H (ffí) -V (7? 2) -s ( m) + j ()] Ec. 20 where? Cm Cm = R_1 (m) aHH (m). In any case, a spatial channel can be visualized as an effective channel between an element of _s and a corresponding element of § with the transmitting entity performing the spatial procedure with the identification matrix I and the receiving entity performing the appropriate spatial receiver procedure to calculate s_. The SNR for the CCMI technique can be expressed as: rcad) = -T) for? = 1 K NS Ec 21 r ~ xavWs) where, P ?? (m) is the power used for the data symbol flow. { s ?} in the transmission output m; r ?? (m) is the diagonal element? of R-1 < (m); sj2 is the variant of the interference and noise received; and? ccmix (m) is the SNR of the data symbol stream. { s ?} in the transmission output m; The amount P? (m) / sj2 is the SNR of the data symbol flow. { s ?} in the receiving entity before the receiving spatial procedure and is commonly referred to as the received SNR. The quantity? Ccmi (m) is the SNR of the flow of the data symbol. { s ?} after the receiver spatial procedure and is also referred to as the post-detection SNR. In the following description, "SNR" refers to the post-detection SNR unless noted otherwise. For the MMSE technique, the receiving entity can derive a spatial filter matrix Mmmse (m), as follows: Mmmse (m) = (m) Ec. 22 The spatial filter matrix M ^ se (m) minimizes the error of the mean square between the symbol calculations from the spatial filter and the data symbols. If the self-covariance matrix (> jj (m), which is the case frequently, is not known, then the spatial filter matrix Mmmse (m) can approximate to: The receiving entity can perform the MMSE spatial procedure and depropagation together, as follows: j (m)] Eq. 2 < = o. { m) -Q (m) - $. { m) + mmse (m) where Q (m) = ^ se (m) ß Hef f (); DQ (m) is a diagonal matrix whose diagonal elements are diagonal elements of Q'1 (m), or DQ (m) = [diag IQ (m)]] - 1; and jtimse (m) is the filtered MMSE and propagates noise and interference, which is: "? mseM = From (m) -Mmmse (m) - mmse (m) The spatial filter matrix symbol calculations Mmmse (ni) are non-normalized calculations of the data symbols. Multiplication with OQ (m) provides the standardized calculations of the data symbols. The receiving entity can also perform the spatial MMSE procedure and separate spatial despread, similar to those described for the CCMI technique. The SNR for the MMSE technique can be expressed as: rmmse, Ák - q ?? ,) for? = l K N Eq. 26 where q ?? (m) is the diagonal element? of Q (m); Y Ymmse (m) is ^ to SNf 'of the data symbol flow. { s ?} in the transmission output m. For the SIC technique, the receiving entity processes the received symbol flows NR in the successive steps Ns to recover the data symbol flows Ns. For each stage?, The receiving entity performs the depropagation and spatial procedure on either the received NR symbol streams or the modified NR symbol streams from the previous step (eg, using CCMI, MMSE, or any other technique) to obtain a symbol flow recovered ís ?} .

Subsequently, the receiving entity processes (e.g., demodulates, deinterleaves, and decodes) this recovered symbol stream to obtain a corresponding decoded data stream. { 3 ? } . The receiving entity then calculates the interference that this flow causes to other data symbol flows not yet recovered. To calculate the interference, the receiving entity re-encodes, collates and traces the symbols of the decoded data stream in the same way as it did in the transmitting entity for this stream and obtains a stream of "re-oped" symbols. { s ?} , which is a calculation of the data symbol flow that has just been recovered. Subsequently, the receiving entity spatially propagates the deregulated symbol flow with the address array Y () and further multiplies the result with the R (m) channel response matrix for each transmission output of interest to obtain the NR interference components caused by this flow. Subsequently, the NR interference components of the received or modified symbol streams NR for the current stage are subtracted to obtain the modified symbol streams NR for the next step. The receiving entity then repeats the same procedure in the modified symbol streams NR to retrieve another data stream.

For the SIC technique, the SNR of each data symbol flow is dependent on (1) the spatial procedure technique (eg, CCMI or MMSE) used for each stage, (2) the specific spate in which the data symbol flow, and (3) the amount of interference due to data symbol flows that were not recovered yet. Generally, the SNR progressively improves data symbol flows recovered in later stages since interference is canceled of the data symbol flows recovered in previous stages.

C. System model Figure 2 shows a model for data transmission with spatial propagation. The transmitting entity 110 performs spatial propagation (block 220) and spatial procedure for partial CSI transmission or Total CSI (block 230). The receiving entity 150 performs the receiving spatial procedure for partial CSI transmission or total CSI (block 260) and spatial despreading (block 270). Next, the description refers to the vectors shown in Figure 2. Figure 3 shows a method 300 developed by the transmitting entity to transmit the data with spatial propagation in the MIMO system. The transmitting entity processes (eg, encodes and interleaves) each data packet to obtain a corresponding block of encoded data, which is also called a code block or an encoded data packet (block 312). Each block of code is encoded separately in the transmitting entity and is decoded separately in the receiving entity. The transmitting entity further maps the symbol to each code block to obtain a corresponding block of data symbols (also block 312). The transmitting entity multiplexes all data symbol blocks generated for all data packets in the data symbol streams N? (denoted by the vector s) (block 314). Each transmitting entity spatially propagates the data symbol streams Ns with address matrices and obtains the propagated symbol streams Ns (denoted by a vector w in Figure 2) (block 316). The spatial propagation is such that each data symbol block is spatially propagated with multiple address matrices (NM) to randomize the transmission channel observed by the block. The randomization of the transmission channel results from the use of different address matrices and not necessarily from the randomization in the elements of the address matrices. The transmitting entity further develops the spatial procedure in propagated symbol flows i Ns for the partial CSI or full CSI transmission, as described above, and obtain the transmit symbol flows N5 (denoted by the vector x) (block 318). The transmitting entity then conditions and sends the transmit symbol flows Nt through the transmit antennas Nt to the receiving entity (block 320). Figure 4 shows a method 400 developed by the receiving entity to receive the transmitted data with spatial propagation in the MIMO system. The receiving entity obtains the received symbol flows NR (denoted by the vector r) through the receiving antennas NR (block 412). The receiving entity calculates the response of the MIMO channel (block 414), develops the spatial procedure for the total CSI transmission or partial CSI based on the MIMO channel calculation, and obtains the detected symbology streams Ns (denoted by an ftf vector in the 2) (block 416). The receiving entity further spatially depresses the detected symbol flows Ns with the same address matrices used by the transmitting entity and obtains the recovered symbol flows Ns (denoted by the vector §) (block 418). The spatial receiver and spatial propagation procedure may be developed jointly or separately, as described above. The receiving entity then processes (e.g., demodulates, deinterleaves, and decodes) each block of symbols recovered in the recovered symbol streams Ns to obtain a corresponding decoded data packet (block 420). The receiving entity may also calculate the SNR of each transmission channel used for data transmission and select an appropriate rate for the transmission channel based on its SNR (block 422). The same or different speed can be selected for the transmission channels Ns. With reference again to figure 2, the data symbol streams Ns are sent in the transmission channels Ns of the MIMO channel. Each transmission channel is an effective channel observed by a data symbol stream between an element of the vector _s in the transmitting entity and a corresponding element of the vector § in the receiving entity (eg, the transmission channel i is the effective channel between the element i of s_ and the element i of §). The spatial propagation randomizes the transmission channels Ns. 3e send the propagated symbol streams Ns in either the Ns own mode of the MIMO channel for the total CSI transmission or the spatial channels Ns of the MIMO channel for the partial CSI transmission.

D. Spatial propagation Address matrices used for spatial propagation can be generated in various ways, as described below. In one embodiment, a set of address matrices L is generated and denoted as. { V.}. , or V (i) for i = l ... L, where L can be an integer greater than one. These address matrices are unit matrices that have orthogonal columns. The address matrices of this set are selected and used for spatial propagation. Spatial propagation can develop in several ways. Generally, it is desired to use as many different address matrices as possible for each data symbol block in such a way that interference and noise is randomized through the block. Each data symbol block is transmitted at the NM transmission outputs, where NM > 1, and NM is also referred to as the block length. An address array in the set can be used for each transmission output. The transmitting and receiving entities can be synchronized in such a way that both entities know which address matrix to use for each transmission output. With spatial propagation, the receiving entity observes an interference and noise distribution through each data symbol block even if the MIMO channel is constant across the entire block. This avoids the case in which high levels of interference and noise are received because the transmitter and receiver entities continuously use a bad array of eigenvectors or the receiving entity continuously observes the colored interference. The address matrices L in the set can be selected to be used in various ways. In one embodiment, the address arrays of the set are selected in a determinant manner. For example, the address matrices L can be programmed and selected in sequential order, starting with the first address matrix V (l), subsequently the second address matrix V (2), and so on, and subsequently the last address matrix V (L) In another embodiment, the address arrays of the set are selected in a pseudo-random manner. For example, the address matrix to be used for each transmission output m can be selected based on a function j (m) that selects in a pseudo-random form one of the address matrices L, or the address array V (f (m)). In still another embodiment, the address arrays of the set are selected in a "permuted" form. For example, the address matrices L can be programmed and selected in a pseudo-random manner, instead of always being the first address matrix V (l). Address matrices L of other forms may also be selected, and this is within the scope of the invention. The selection of the address matrix may also depend on the number of address matrices (L) in the set and the block length (NM). Generally, the number of address matrices can be May a, equal to, or smaller than the block length. The selection of the address matrix can be developed for these three cases, as described below. If L = NM, then the number of address matrices matches the block length. In this case, a different address array may be selected for each of the NM transmission outputs used to send each data symbol block. The address arrays NM for the transmit outputs NM can be selected in a determinant, pseudo-random, or permuted manner, as described above. If L < NM, then the block length is greater than the number of address matrices in the set. In this case, the address matrices are again used for each data symbol block and can be selected as described above. If L > NM, then a subset of address matrices is used for each data symbol block. The selection of the specific subset to be used for each data symbol block can be determinant or pseudo-random. For example, the first address array to be used for the current data symbol block can be the address array after the last one used for a previous data symbol block. As noted above, a transmission output can cover one or multiple symbol periods and / or one or multiple subbands. To improve performance, we want to select the transmission output to be as short as possible, so that (1) more address matrices can be used for each datum symbol block and (2) each receiving entity can obtain as many "visualizations" of the MIMO channel as possible for each data symbol block. The transmission output should be shorter also than the MIMO channel coherence time, which is the duration over which it can be assumed that the MIMO channel is approximately static. Similarly, the transmission output should be shorter than the coherence bandwidth of the MIMO channel for a broadband system (eg, an OFDM system).

E. Applications for spatial propagation Spatial propagation can be used to randomize and bleach spatially colored noise and interference for both transmissions, total CS1 and partial CSI, as described above. This can improve the performance of certain channel conditions. Spatial propagation can also be used to reduce the likelihood of power outages under certain operating scenarios. As an example, a block of data symbols for a block of code can be divided into sub-blocks of data symbol Nt. Each data symbol sub-block can be encoded and modulated in accordance with the expected SNR for the sub-block. Each data symbol sub-block can be transmitted as an element of the data symbol vector s_, and the data symbol sub-blocks Nt can be transmitted in parallel. Subsequently, a power outage may occur in the event that one of the data symbol sub-blocks Nt can not be decoded free of errors by means of the receiving entity. In case the partial CSI transmission without spatial propagation is used for the data symbol sub-blocks Nt, then each sub-block is transmitted from a respective transmit antenna. Subsequently, each data symbol sub-block would observe the SNR achieved for the corresponding spatial channel for its transmitting antenna. The receiving entity can calculate the SNR of each space channel, select an appropriate speed for each space channel based on its SNR, and provide the speeds for all the spatial channels Nt for the transmitting entity. The transmitting entity can then code and modulate the data symbol sub-blocks Nt based on their selected rates. The MIMO channel can change between time n when the velocities are selected in time n + t when velocities are used. This may be the case, for example, if the receiving entity has moved to a new location, if the MIMO channel changes faster than the feedback speed, and so on continuously. The new response matrix of channel Hi at time n + t can have the same capacity as the response matrix of channel H0 at time n, which can be expressed as: where ? (n) is the SNR of space channel i at time n and log2 (l +? (n)) is the capacity of space channel i at time n. Even if the capacities of Ho and Hi are the same, the capacities of the individual spatial channels between time n and time n + t may have changed, so that? _ (n) possibly not equal to x (n + t). Without spatial propagation, the probability of a light cut is increased if y ± (n) < and ± (n + t) for any spatial channel i. This is because a data symbol sub-block sent in a spatial channel with a lower SNR is less likely to be decoded error-free, and any decoded data symbol sub-block in error corrupts the symbol block of complete data under the previous assumption. In case the partial CSI transmission with spatial propagation is used for the data symbol sub-blocks Nt, then each sub-block is propagated and spatially transmitted from all the transmit antennas Nt. Subsequently, each data symbol sub-block would be transmitted on a transmission channel formed by a combination of spatial channels Nt of the MIMO channel and observed by an effective SNR which is a combination of the SNRs for these spatial channels. The transmission channel for each data symbol sub-block is determined by means of the address matrices used for spatial propagation. In case a sufficient number of address matrices is used to spatially propagate the NT data symbol sub-blocks; then the effective SNR observed by each data symbol sub-block will be approximately equal to the average SNR for all spatial channels when a powerful error correction code is employed. With the spatial propagation, the light cutoff probability of the average SNR of the spatial channels can then be dependent instead of the SNRs of the individual spatial channels. Thus, if the average SNR at time n + t is approximately equal to the average SNR at time n, then the probability of light outage may be approximately the same, even though the SNRs of individual spatial channels may have changed between times n and n + t. Thus, the performance of spatial propagation can be improved for the case in which the inaccurate partial CSI is available in the transmitting entity and / or receiving entity. Inaccurate partial CSI can result in mobility, inadequate feedback speed, and so on. 2. MIMO system of multiple carriers The spatial propagation for a MIMO system of multiple carriers can also be used. Multiple carriers can be provided by means of orthogonal frequency division multiplexing (OFDM) or some other structures. OFDM effectively divides the entire broadband of the system into sub-bands by multiple orthogonal frequency (NF), which are referred to as tones, sub-carriers, bins, and frequency channels. With OFDM, each subband is associated with a respective sub-carrier that can be modulated with the data. For an OFDM-based system, spatial propagation can be developed in each of the sub-bands used for data transmission. For a MIMO system using OFDM (i.e., an OFDM-MIMO system can be formed), a data symbol vector s_ (k, n) for each subband k in each symbol period n OFDM. The vector s (k, n) contains up data symbols Ns to be sent through own modes Ns or sub-band spatial channels k in the symbol period n OFDM. They can currently be transmitted to vectors NF, s (k, n) for k = 1 ... NF, in the NF subbands in an OFDM symbol period. For the OFDM-MIMO system, a transmission output can cover both dimensions, by frequency and by time. Thus, the index m for the transmission output can be substituted with k, n for the subband k and the symbol period n OFDM. A transmission output may cover a subband in an OFDM symbol period or multiple OFDM symbol periods and / or multiple subbands.

For the total CSI transmission scheme, the channel response matrix E (k) for each subband k can be decomposed to obtain the proper Ns modes of that subband. The eigenvalues in each diagonal matrix h (k), for k = l ... NF, can be arranged in such a way that the first column contains the largest eigenvalue, the second column contains the next largest eigenvalue, and thus continuously, or? ? (k) > ? 2 (k) = ...? s (k), where? ? (k) is the eigenvalue in column f of? (k) after the sequence. When the eigenvalues are ordered for each matrix H (k), the eigenvectors (or columns) of the associated matrix E (k) are also ordered for that sub-band to the same extent. An own "broadband" mode can be defined as the set of own modes of the same order of all the NF sub-bands after the sequence (for example, the own mode of broadband í includes the proper mode of all the sub -bands). Each proprietary broadband mode is associated with a respective set of eigenvectors NF for the NF subbands. The basic broadband proper mode is the one associated with the largest eigenvalue of each matrix A (k) after the sequence. The data can be transmitted in the own broadband modes Ns. For the partial CSI transmission scheme, the transmitting entity may develop the propagation and spatial procedure for each subband, and the receiving entity may develop the despreading and receiving spatial procedure for each subband. Each data symbol block can be transmitted in various ways in the OFDM-MIMO system. For example, each data symbol block may be transmitted as one input of the vector s (k, n) for each of the NF subbands. In this case, each data symbol block is sent in all NF subbands and achieves frequency diversity in combination with the spatial diversity provided by means of spatial propagation. Each data symbol block may also encompass one or multiple OFDM symbol periods. In this way, each data symbol block can encompass the dimensions by time and / or frequency (by means of the system design) plus the spatial dimension (with spatial propagation). Address matrices can also be selected in various ways for the OFDM-MIMO system. Steering matrices for the sub-bands can be selected in a decisive way, pseudo-random, or permuted, as described previously. For example, the address matrices L in the set can be programmed and selected in sequential order for subbands 1 through T in the symbol period n OFDM, then subbands 1 through NF in the period of symbol n + l OFDM, and so on continuously. The number of address matrices in the set can be less than, equal to, or greater than the number of subbands. The three cases described above for L = NM, L <; NM, and L > NM can also be applied for subbands, with NM being replaced with NF. 3. MIMO System Figure 5 shows a block diagram of the transmitting entity 110 and receiving entity 150. In the transmitting entity 110, a data processor TX 520 receives and processes (eg, encodes, interleaves, and modulates) the data and provides the data symbols. A spatial processor TX 530 receives the data symbols, develops the spatial propagation and spatial procedure for the partial CSI transmission or total CSI, multiplexes the pilot symbols, and provides the transmit symbol flows Nt for the transmitter units Nt (TMTR) 532a at 532t. Each transmitter unit 532 develops the OFDM modulation (if applicable) and further conditions (eg, converts to analog, filters, amplifies, and over-converts the frequency) a respective transmit symbol stream to generate a modulated signal. The transmitter units Nt 532a to 532t provide the modulated signals Nt for transmission from the antennas Nt 534a to 534t, respectively. In the receiving unit 150, the antennas NR 552a to 552r receive the transmitted signals N, and each antenna 552 provides a signal received for a respective receiving unit (RCVR) 554. Each receiving unit 554 develops the complementary procedure to that developed by the unit transmitter 532 (including OFDM demodulation, if applicable) and provides (1) the received data symbols for a RX 560 spatial processor and (2) received pilot symbols for a 584 channel calculator within a 580 controller. The RX spatial processor 560 develops the spatial receiver and spatial depropagation procedure in the received NR symbol flows from the NR 554 receiver units with spatial filter matrices and address arrays, respectively, from the 580 controller and provides the recovered symbol flows Ns. Subsequently, the RX 570 data processor processes (for example, it does not trace, deinterface, and decode) the recovered symbols and provide the decoded data. The channel calculator 584 can derive fí (m), which is a calculation of the channel response matrix ñ (m), based on the transmitted pilot symbols without spatial propagation. Alternatively, the channel calculator 584 can directly derive B &tt (M), which is a calculation of the effective channel response matrix Heff (m), based on the pilot symbols transmitted with spatial propagation. In any case, fí (m), or fí eff (m) can be used to derive the spatial filter matrix. The channel calculator 584 further calculates the SNR of each transmission channel based on the received pilot symbols and / or received data symbols. The MIMO channel includes the Ns transmission channels for each subband, but these transmission channels may be different depending on (1) if the partial CSI transmission or total CSI is used, (2) whether the spatial propagation was developed or not , and (3) the specific technique of spatial procedure used by the receiving entity. The controller 580 selects an appropriate speed for the transmission channel based on its SNR. Each selected rate is associated with a particular coding scheme and a particular modulation scheme, which collectively determines a data rate. The same or different speeds can be selected for the transmission channels Ns. Speeds are processed for all transmission channels, other information, and traffic data (for example, encoded and modulated) by means of a TX 590 data processor, are spatially processed (if necessary) by means of a spatial processor TX 592, are conditioned by means of transmitter units 554a to 554r, and sent through antennas 552a to 552r. In the transmitting entity 110, the NR signals sent by the receiving unit 150 are received by means of the antennas 534a to 534t, are conditioned by means of the receiving units 532a to 532t ,, are spatially processed by means of a spatial processor RX 544, and are further processed (e.g., demodulated and decoded) by means of an RX 546 data processor to recover the selected rates. The controller 540 can then direct the data processor TX 520 to process the data for each transmission channel based on the speed selected for that transmission channel. The controllers 540 and 580 also control the operation of several processing units in the transmitter unit 110 and receiver unit 150, respectively. The memory units 542 and 582 store the data and / or program code used by the controllers 540 and 580, respectively. Figure 6 shows a block diagram of a mode of the data processor TX 520 and spatial processor TX 530 in the transmitting entity 110. For this mode, the data processor TX 520 includes the data flow processors TX ND 620a to 620nd for data flows ND. { d \), for 1 = 1 ... ND, where ND = 1 generally.

In each data stream processor TX 620, an encoder 622 receives and encodes its data stream. { d \) based on a coding scheme and provides the bits of the code. Each data packet is encoded in the data stream separately to obtain a corresponding code block or encoded data packet. Coding increases the reliability of data transmission. The coding scheme may include the generation of cyclic redundancy check (CRC), convolutional coding, Turbo coding, low density parity verification encoding (LDPC), block coding, other encodings, or a combination thereof. With spatial propagation, the SNR can vary through a block of code, even if the MIMO channel is static in the code block. A coding scheme powerful enough to combat SNR variation through the code block can be used, so that the encoded performance is proportional to the average SNR through the code block. Some exemplary coding schemes that can provide good performance for spatial propagation include the Turbo code (for example, the one defined by means of IS-856), LDPC code, and convolutional code.

A channel interleaver 624 interleaves (i.e., rearranges) the code bits based on an interleaving scheme to achieve frequency, time and / or spatial diversity. Intercalation can be developed through a block of code, a block of partial code, multiple blocks of code, and so on. A symbol tracing unit 626 traces the interleaved bits based on a modulation scheme and provides a flow of the data symbols. { s (j) Unit 626 groups each set of interleaved bits B to form a bit value B, where B = l, and also traces each bit value B to a specific modulation symbol based on the modulation scheme (eg. example, QPSK, M-PSK, or M-QAM, where M = 2B.) Unit 626 provides a block of data symbols for each block of code In Figure 6, the data flow processors TX 620 ND ND data streams are processed A data stream processor TX 620 can also process the ND data streams, for example, in a time division multiplex (TDM) form.The data can be transmitted in various ways in the system For example, if ND = 1, then it is processed, de-multiplexed, and transmits a data stream on all the transmission channels Ns of the MIMO channel.If ND = Ns, then a data stream can be processed and transmitted on each transmission channel In any case, the data that is going away can be encoded and modulated to send on each transmission channel based on the speed selected for that transmission channel. A multiplexer (Mux / Demux) 628 receives and ultiplexes / demultiplexes the data symbols for the data streams ND in data symbol streams Ns, a data symbol stream for each transmission channel. If ND = 1, then Mux / Demux 628 demultiplexes the data symbols for a data stream in the data symbol streams Ns. If ND = Ns, then Mux / Demux 628 can simply provide the data symbols for each data stream as a respective data symbol stream. The spatial processor TX 530 receives and spatially processes the data symbol streams Ns. In the spatial processor TX 530, a spatial propagator 632 receives the data symbol flows Ns, develops the spatial propagation for each transmission output m with the address matrix V (m) selected for that transmission output, and provides the flows of propagated symbols Ns. Address arrays can be retrieved from address array (SM) storage 642 in memory unit 542 or generated by means of controller 540, as needed. Subsequently, a spatial processor 634 spatially processes the propagated symbol streams Ns with the identity matrix I for the total CSI transmission or with the own vector matrices E (m) for the total CSI transmission. A multiplexer 636 multiplexes the transmission symbols from the spatial processor 634 with pilot symbols (e.g., in a time division multiplexed form) and provides the transmission symbol flows Nt for the transmission antennas Nt. Figure 7 shows a block diagram of a spatial processor RX 560a and a data processor RX 570a, which is a modality of the spatial processor RX 560 and data processor RX 570, respectively, in the receiving unit 150. The receiving units 554a at 554r NR provide the pilot symbols received. { JCÍ} for i = 1 ... NR, to the channel calculator 584. The channel calculator 584 calculates the response matrix of the R (m) channel based on the received pilot symbols and further calculates the SNR of each transmission channel. The controller 580 derives a spatial filter matrix M (m) and possibly a diagonal matrix O (m) for each transmission output m based on the response matrix of the R channel (m) and possibly the address array V (m) ). The receiving entity 150 is synchronized with the transmitting entity 110 such that both entities use the same address matrix V_ (m) for each transmission output m. The matrix M (m) can be derived as shown by equation (10) for the total CSI transmission and as shown in equations (17) and (23) for the partial CSI transmission with the MMSE and CCMI techniques, respectively. The matrix M (m) may or may not include the address matrix V (m) depending on whether the spatial procedure receitor and spatial despropagation is developed jointly or separately. Figure 7 shows the propagation and spatial propagation that will be developed separately. The spatial processor RX 560 obtains the received data symbols, (rdi) for i = 1 ... NR, from the receiving units 554a to 554r and the matrices M (m) and Y_ (m) from the 580 controller. RX 560 spatial processor, a spatial processor 764 develops the receiver spatial procedure on the data symbols received for each transmission output with the matrices M (m). Subsequently, a spatial depropagator 764 develops the spatial depropagation with the matrix V (m) and provides the recovered symbols for the RX 570 data processor. The spatial receiver and spatial depropagation procedure can also be developed jointly using the effective MIMO channel calculation, such as described previously. For the embodiment shown in Figure 7, the RX data processor 570a includes a multiplexer / demultiplexer (Mux / Demux) 768 and RX data stream processors ND 770a to 770nd for the data streams ND. The Mux / Demux 768 receives and multiplexes / demultiplexes the recovered symbol flows Ns for the transmission channels N? in the recovered symbol flows ND for the data streams ND. In each RX 770 data stream processor, a symbol non-tracer unit 772 demodulates the recovered symbols for their data stream according to the modulation scheme used for that stream and provides the demodulated data. A channel deinterleaver 774 deinterleaves the demodulated data in a complementary fashion for the interleaving developed in that stream by means of the transmitting entity 110. A decoder 776 decodes the deinterleaved data in a form complementary to the coding developed by means of the transmitting entity 110. in that flow. For example, a Turbo decoder or a Viterbi decoder can be used for the decoder 776, in case the convolutional or Turbo coding is developed, respectively by means of the transmitting entity 110. The decoder 776 provides a decoded data stream, which includes a data packet decoded for each data symbol block.

Figure 8 shows a block diagram of a spatial processor RX 560b and a data processor RX 570b, which implement the SIC technique for the receiving entity 150. For simplicity, ND = Ng and the spatial processor RX 560b and data processor RX 570b implement the steps of the receiver procedure in married Ns for the data symbol flows Ns. Each of the stages 1 for Ns -1 includes a spatial processor 860, an interference canceller 862, a data flow processor RX 870, and a data flow processor TX 880. The last stage includes only a spatial processor 860ns and a RX 870ns data stream processor. Each RX 870 data stream processor includes a non-tracer symbol unit, a channel deinterleaver, and a decoder, as shown in FIG. 7. Each TX 880 data stream processor includes an encoder, a channel interleaver. , a symbol tracer unit, as shown in figure 6. For step 1 - the spatial processor 860a develops the receiver spatial procedure in the received symbol flows NR and provides a recovered symbol stream. { sj. } . The RX 870a data stream processor demodulates, deinterleaves, and decodes the recovered symbol flow. { §? } and provides a corresponding decoded data stream. { gave) . The TX 880a data stream processor encodes, interleaves, and modulates the decoded data stream. { cl i} in the same way as the transmitting entity 110 develops it for that flow and provides a remodulated symbol flow. { yes} . The interference canceller 862a spatially propagates the remodulated symbol flow. { § ?} with the matrix V (m) and further multiply the results with the channel response matrix f (m) to obtain the NR interference components due to the data symbol flow. { sj} . The NR interference components of the received symbol flows NR are subtracted to obtain the modified symbol flows NR, which are provided for stage 2. Each of the stages 2 through Ns-1 carries out the same procedure as the stage 1, although it is true, in the modified symbol flows NR of the previous stage instead of the received symbol flows NR. The last stage develops the spatial procedure and decoding in the NR modified symbol flows from the Ns-1 stage and does not develop the interference and cancellation calculation. The spatial processors 860a to 860ns can each implement CCMI, MMSE, or any other technique. Each spatial processor 860 multiplies an input symbol vector r € SiC (m) (received or modified) with a spatial filter matrix M ^ ic (m) and the address array V (m) to obtain a recovered symbol vector . { s sc} and provides the recovered symbol flow for that stage. The matrix is derived. { M s¡c} based on a reduced channel response matrix fí (m) for the stage. The matrix fí (m) is equal to fí (m) with the columns for all the data symbol flows already recovered in previous removed stages. 4. Control and speed selection For both transmissions, partial CSI and total CSI, the receiving entity can calculate the SNR of each transmission channel. The calculation of SNR depends on (1) whether partial CSI or total CSI transmission is used, (2) whether spatial propagation is developed or not, and (3) the particular spatial procedure receiver technique (for example, CCMI, MMSE or SIC) used for the receiving entity in the case of partial CSI transmission. For a MIMO-OFDM system, the SNR can be calculated and averaged for each subband of each transmission channel to obtain the SNR of the transmission channel. In any case, you can calculate an operational SNR,? O (r for each transmission channel based on the SNR of the transmission channel, Y? I r, and a SNR derivation, fopOS) »- as follows: ríP (?) = R / (?) + R" í (?) EC. 28 where the units are in decibels (dB). The SNR derivation can be used to justify the calculation error, the variability in the channel, and other factors. An appropriate speed is selected for each transmission channel based on the operating SNR of the transmission channel. The MIMO system can support a specific set of speeds. One of the supported speeds can be for a null speed, which is a data rate of zero. Each of the remaining speeds is associated with a particular non-zero data rate, a particular coding scheme or code rate, a particular modulation scheme, and a particular minimum SNR required to achieve a desired level of performance , for example 1% packet error rate (PER) for an AWGN channel without fading. For each non-zero velocity supported, the required SNR can be obtained based on the specific system design (such as the particular code rate, the interleaving scheme, and the modulation scheme used by the system for that speed) and for a channel AWGN The required SNR can be obtained by computer simulation, empirical measurements, etc., as is known in the art. The set of supported speeds and their required SNRs can be stored in a look-up table. The operational SNR, Yopifyr of each transmission channel can be provided for the lookup table, which subsequently returns the speed q (í) for that transmission channel. This velocity is the highest velocity supported with a required SNR, yteq () r that is less than or equal to the operational SNR, or / req (£) = ^ op (í). In this way, the receiving entity selects the highest possible speed for each transmission channel based on its operational SNR.

. Generation of the address matrix Address matrices used for spatial propagation can be generated in various ways, and some exemplary schemes are described below. A set of address matrices L can be previously calculated and stored in the receiving and transmitting entities, and subsequently retrieved for use as needed. The address matrices must be unitary matrices and satisfy the following condition: YH (i) - Y (i) = l for ¡= 1K L Ec. 29 Equation (28) indicates that each column of V_ (i) must have unity energy and the Hermitian internal product of any of the two columns of Y_ (i) must be zero. This condition ensures that the data symbols Ns sent simultaneously using the address array Vf) have the same power and are orthogonal to each other before transmission. Similarly, some of the address matrices may not be correlated, so that the correlation between any of the two uncorrelated address matrices is zero or a minor value.

This condition can be expressed as: L, y = lK L, and i? j Ec.30 where (if) is the correlation matrix for Y (i) and V (j) and _0 is a matrix of all zeros. The condition in equation (30) can improve performance for some applications but not necessarily for most applications. The set of address matrices L can be generated. { V.}. using several schemes. In a first scheme, the address matrices L are generated based on the matrices of random variables. Initially, a G Ns x Nt matrix is generated with elements that are complex Gaussian random variables independently distributed identically, where each has a variant of unit and value of zero. A correlation matrix of G Ns x Nt is calculated and decomposed using the decomposition of the eigenvalue as follows: The matrix EG is used as an address array Y_ (i) and is added to the set. The procedure is repeated until all the address matrices L are generated. In a second scheme, the address matrices L are generated based on a set of unitary matrices (IID) distributed isotropically independently (log2 + L) + l, as follows: ? (?,? 2K? Q) = OI * -Q22 -K - O - YO for? 15? 2 > K,? Q =. { ? l} , Ec. 32 where Vo is a unitary matrix isotropically distributed independently Nt x Ns; i = t? t 2-l < 2r where Q = log2L and f-¡is the j bit of the index i; and O ^ j, for j = 1 ... Q, is a unitary IID matrix Nt x Nt.

The second scheme is described by T.L. Marzetta et al. in "Constellations of Time-Space Auto-coding Structured Units "(" Structural Unitary Space-Time Autocoding Constellations "), IEEE Transaction in Theory of Information (IEEE Transaction on Information Theory), Vol. 48, No. 4, April 2002.

In a third scheme, the matrices of direction L by successively rotating an address array initial unit V (l) in a complex dimensional space Nt, as follows: V (¿+ l) = T'-V (l) for ¿= 1 K L-1, Ec.33 where TJ is a diagonal unitary matrix Nt x Nt with elements that are roots of unit L. The third is described scheme by B.M. Hoch ald et al. in "Systematic Design of Unitary Time-Space Constellations" ("Systematic Design of Unitary Space-Time Constellations "), IEEE Transaction in Information Theory (IEEE Transaction on Information Theory), Vol. 46, No. 4, September 2000. In a fourth scheme, the set of address matrices L with a base matrix B and different scalars. The base matrix can be a Walsh matrix, a Fourier matrix, or some other matrix. You can express yourself 1 1 Walsh matrix 2x2 as W2x2 = A larger Walsh W2x2 matrix can be formed from a Walsh W2x2 matrix of a smaller size, as follows: The matrices have dimensions that are powers of two. A D Fourier matrix Nt x Nt has the element wn; m in row n of column m, which can be expressed as: (»-l) (m-l) -j2p- w rn", m, = ~ e & 5 for »=. { l K Nt} and m =. { l K Nt} , Ec. 35 where n is a row index and m is a column index. Fourier matrices of any square dimension can be formed (eg, 2, 3, 4, 5, etc.). A W Walsh Nt x Nt t matrix, D Fourier matrix, or some other matrices such as the base matrix B can be used to form other address matrices. Each of the rows 2 can be independently multiplied by Nt of the base matrix with one of the different possible scalars M, where M > 1. Different address matrices MNt_1 of different permutations MNt_1 of the escars for rows Nt -1 can be obtained. By . example, you can independently multiply each of rows 2 through through Nt with a scalar of +1, -1, + j, or -j, where j = y-1. For Nt = 4 and M = 4, different address matrices can be generated from the base matrix B with the four different scalars. Additional address matrices can be generated with other scalars, for example e ± j37r / 4; e ± :} p / 4, e ±: j3 p / s, and so on continuously. Generally, each row of the base matrix can be multiplied with any scalar that has the form of ér ^? , where ? it can be any phase value. The address matrices TX NT / i) * B (i) can be generated, where gyyr = 1 JNT and B (?) Is the matrix i generated with the base matrix B. The scaling by means of g ^ t ensures that each column of / i) has the unit power. Other schemes may also be used to generate the set of address matrices L, and this is within the scope of the invention. Generally, the address matrices may be generated in a pseudo-random form (eg, such as the first scheme) or in a determinant fashion (eg, such as the second, third, and fourth schemes). The spatial propagation techniques described in the present invention can be implemented in several ways. For example, these techniques can be implemented in hardware, software, or a combination thereof. For a hardware implementation, processing units for spatial propagation in the transmitter unit and spatial despreading in the receiver unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), processors digital signal (DSPDs), programmable logic devices (Plus), field programmable gate networks (FPGAs), processors, controllers, icro-controllers, microprocessors, other electronic units designed to perform the functions described in the present invention, or a combination of them. For a software implementation, spatial propagation techniques can be implemented with modules (e.g., procedures, functions, etc.) that perform the functions described in the present invention. The software codes can be stored in the memory units (for example, the memory units 542 and 582 in FIG. 5) and executed by means of a processor (for example, controllers 540 and 580 in FIG. 5). The memory unit may be implemented in the processor or external to the processor, in which case it may be communicatively coupled to the processor through various means as is known in the art.

• The headers in the present invention are included for reference and to help locate certain sections. These headings are not intended to limit the scope of the concepts described in the present invention, and these concepts may be applied in other sections throughout the entire specification. The above description of the described embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined in the present invention can be applied to other embodiments without departing from the spirit and scope of the invention. Thus, the present invention is not intended to limit the embodiments shown in the present invention, but they are in accordance with the broad scope consistent with the principles and novel features described in the present invention.

Claims (59)

NEW D? THE INVENTION Having described the present invention, it is considered as a novelty and, therefore, the content of the following is claimed as a priority: CLAIMS

1. - A method for transmitting data from a transmitting entity to a receiving unit in a wireless multiple input / output (MIMO) communication system, comprises: processing the data to obtain a plurality of data symbol streams to transmit in a plurality of transmission channels in a MIMO channel between the transmitting entity and the receiving entity; developing the spatial propagation in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagated symbol streams, wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol flows; and developing the spatial procedure in the plurality of propagated symbol streams to obtain a plurality of transmitted symbol streams to be transmitted from a plurality of transmit antennas in the transmitting entity.

2. - The method according to claim 1, characterized in that developing the spatial process comprises: multiplying the plurality of propagation symbol flows with the arrays of eigenvectors to transmit the plurality of symbols flows propagated in a plurality of modes of the MIMO channel.

3. - The method according to claim 1, characterized in that developing the spatial procedure comprises: providing each of the pluralities of propagated symbol flows as one of the pluralities of streams of transmission symbols.

4. - The method according to claim 1, characterized in that processing the data comprises: coding and modulating the data for each of the plurality of data symbol flows based on a selected speed for the flow of data symbols.

5. The method according to claim 4, further comprises: obtaining the speed of each data symbol stream, the speed to be selected based on a noise / interference signal (SNR) ratio of a transmission channel for the flow of data symbols.

6. The method according to claim 1, characterized in that processing the data comprises: coding and modulating each of the plurality of data packets to obtain a block of data symbols, and multiplexing a plurality of blocks of data symbols generated for the plurality of data packets in the plurality of data symbol flows.

7. - The method according to claim 6, characterized in that the coding and modulation comprise: coding each data packet based on a Turbo code, a convolutional code, or a code of verification of low density pairings (LDPC) for obtain a block of encoded data, and trace the symbol of each block of code data based on a modulation scheme to obtain a block of data symbols.

8. The method according to claim 6, characterized in that multiplexing the plurality of blocks of data symbols comprises: multiplexing each block of data symbols in one of the plurality of data symbol flows.

9. - The method according to claim 6, characterized in that multiplexing the plurality of blocks of data symbols comprises: multiplexing each block of data symbols in all pluralities of data symbol flows.

10. The method according to claim 6, characterized in that developing the spatial propagation comprises: developing the spatial procedure in each block of data symbols in the plurality of data symbol flows with at least two address matrices.

11. The method according to claim 1, characterized in that developing spatial propagation comprises: developing the spatial procedure in the plurality of data symbol streams using a set of address matrices L, where L is an integer greater than one.

12. The method according to claim 11, further comprising: generating the address matrices L as unit matrices that have orthogonal columns.

13. The method according to claim 11, further comprising: selecting an address matrix from among the address matrices L for each interval, and characterized in that the spatial propagation for each interval is developed with the address matrix selected for the interval.

14. - The method according to claim 11, further comprising: selecting an address array from among the address matrices L for each group of at least one frequency sub-band, and characterized in that the spatial propagation for each group is developed of at least one frequency sub-band with the address matrix selected for the group.

15. The method according to claim 11, further comprising: processing each of the plurality of streams of transmission symbols for division multiplexing by orthogonal frequency (OFDM).

16. The method according to claim 1, characterized in that developing the spatial propagation comprises: developing the spatial procedure with at least two different address matrices for a plurality of sub-bands in each symbol period with the data transmission.

17. An apparatus in a multiple input / output communication (MIMO) system, comprises: a data processor for processing the data to obtain a plurality of data symbol streams to be transmitted in a plurality of transmission channels in a MIMO channel between a transmitting entity and a receiving entity in the MIMO system; a spatial propagator for developing the spatial propagation in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagation symbol streams, wherein the spatial propagation with the plurality of matrices or direction randomizes the plurality of transmission channels for the plurality of data symbol flows; and a spatial processor for developing the spatial procedure in the plurality of propagation symbol streams to obtain a plurality of transmission symbol streams to be transmitted from a plurality of transmit antennas in the transmitting entity.

18. The apparatus according to claim 17, characterized in that the spatial processor multiplies the plurality of propagation symbol streams with arrays of eigenvectors to transmit the plurality of propagation symbol streams in a plurality of modes proper to the MIMO channel. .

19. The apparatus according to claim 17, characterized in that the spatial processor provides each of the plurality of propagation symbol flows as one of the plurality of transmission symbol flows.

20. - The apparatus according to claim 17, characterized in that the data processor encodes and modulates the data for each of the plurality of data symbol streams according to a selected speed based on a signal / noise ratio. interference (SNR) of a transmission channel used for the flow of data symbols.

21. The aparate according to claim 17, characterized in that the data processor encodes and modulates each of the plurality of data packets to obtain a block of data symbols, and multiplexes a plurality of blocks of data symbols generated for the plurality of data packets in the plurality of data symbol flows.

22. The apparatus according to claim 21, characterized in that the spatial propagator spatially propagates each block of data symbols in the plurality of data symbol flows with at least two address matrices.

23. The aparate according to claim 17, further comprising: a controller for selecting an address array from among the address matrices L for each interval, wherein L is an integer greater than one, and characterized in that the propagator Spatial develops the spatial propagation for each interim with the address matrix selected for the interval.

24.- The aparate according to claim 17, characterized in that the MIMO system uses orthogonal frequency division multiplexing (OFDM), and characterized in that for each symbol period with the data transmission, the spatial propagator develops the spatial propagation with at least two different address matrices for a plurality of sub-bands used for data transmission.

25. The aparate according to claim 17, characterized in that the spatial propagation by means of the spatial propagator results in bleached noise and interference observed by means of the receiving entity for the plurality of data symbol flows after the receiving entity performs the spatial depropagation.

26. The apparatus according to claim 17, characterized in that the MIMO channel includes the plurality of spatial channels, and wherein the spatial propagation by means of the spatial propagator results in each of the pluralities of transmission channels achieving a ratio of noise / interference signal (SNR) which is an average of the CNRS of the plurality of spatial channels.

27.- An apparatus in a multiple input / output communication system (MIMO), comprises: means for processing the data to obtain a plurality of data symbol streams to transmit in a plurality of transmission channels in a MIMO channel between the transmitting entity and the receiving entity in the MIMO system; means for developing spatial propagation in the plurality of data symbol streams with a plurality of address matrices to obtain a plurality of propagated symbol streams, wherein the spatial propagation with the plurality of address matrices randomizes the plurality of streams of transmission for the plurality of data symbol flows; and means for developing the spatial procedure in the plurality of propagated symbol streams to obtain a plurality of transmitted symbol streams to be transmitted from a plurality of transmit antennas in the transmitting entity.

28. The apparatus according to claim 27, characterized in that the means for developing the spatial process comprises: means for multiplying the plurality of propagation symbol flows in a plurality of modes proper to the MIMO channel.

29. The apparatus according to claim 27, characterized in that the means for developing the spatial process comprises: means for providing each of the pluralities of propagation symbol flows as one of the plurality of transmission symbol flows.

30. The aparate according to claim 27, characterized in that the means for processing the data comprises: means for encoding and modulating the data for each of the plurality of data symbol flows according to a selected speed based on a noise / interference signal (SNR) ratio of a transmission channel for the flow of data symbols.

31. The apparatus according to claim 27, characterized in that the means for processing the data comprises: means for coding and modulating each of the plurality of data packets to obtain a block of data symbols, and means for multiplexing a data block. plurality of blocks of data symbols generated for the plurality of data packets in the plurality of data symbol flows.

32. - The apparatus according to claim 27, further comprising: means for selecting an address array from among the address matrices L for each interval, wherein L is an integer greater than one, and characterized in that the spatial propagation for each interval is developed with the address matrix selected for the interval.

33. The apparatus according to claim 27, characterized in that the MIMO system uses orthogonal frequency division multiplexing (OFDM), and characterized in that the means for developing spatial propagation comprises: means for developing spatial propagation with minus two different address matrices for a plurality of subbands in each symbol period with data transmission. 34.- A method for receiving a data transmission sent by means of a transmitting entity for a receiving entity in a wireless multiple input / output communication (MIMO) system, comprises: obtaining a plurality of received symbol flows for a plurality of data symbol streams transmitted through a plurality of transmission channels in a MIMO channel, wherein the plurality of data symbol streams propagate spatially with a plurality of address matrices and are further processed spatially prior to transmission through the MIMO channel, and wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol streams; developing the receiver spatial procedure in the plurality of received symbol streams to obtain a plurality of detected symbol streams; and developing spatial depropagation in the plurality of symbol flows detected with the. plurality of address matrices to obtain a plurality of retrieved symbol streams, which are calculations of the plurality of data symbol streams. The method according to claim 34, further comprising: obtaining an effective MIMO channel calculation including a channel response calculation for the MIMO channel and the plurality of address matrices used for spatial propagation; and developing the spatial receiver procedure and spatial despropagation together based on the calculation of the effective MIMO channel. 36.- The method according to claim 34, characterized in that developing the spatial propagation comprises: developing the spatial propagation in each of the blocks of symbols detected in the plurality of detected symbol flows with at least two address matrices used by means of the transmitting entity in a corresponding block of data symbols. 37.- The method according to claim 34, characterized in that developing spatial despreading comprises: developing spatial despreading in the plurality of symbol streams detected using a set of address matrices L, where L is a whole number greater than one, and characterized in that the address matrices L are unit matrices. 38.- The method according to claim 34, characterized in that developing the receiver spatial procedure comprises: multiplying the plurality of received symbol flows with arrays of eigenvectors for a plurality of modes proper to the MIMO channel to obtain the plurality of streams of detected symbols. 39.- The method according to claim 34, characterized in that developing the receiver spatial procedure comprises: deriving a matching filter based on a channel response calculation for the MIMO channel, and multiplying the plurality of symbol flows received with the matching filter to obtain the plurality of streams of detected symbols. The method according to claim 34, characterized in that developing the receiver spatial procedure comprises: developing the receiver spatial procedure in the plurality of symbol flows received based on a channel correlation matrix inversion technique (CCMI) . 41.- The method according to claim 34, characterized in that developing the receiver spatial procedure comprises: developing the receiver spatial procedure in the plurality of symbol flows received based on a minimum square-average error (MMSE) technique. 42. The method according to claim 34, characterized in that developing the receiver spatial procedure comprises: developing the receiver spatial procedure in the plurality of symbol flows received based on a successive interference cancellation technique (SIC). 43.- The method according to claim 34, further comprising: calculating a noise / interference signal (SNR) ratio of each of the pluralities of the transmission channels for the plurality of data streams.; and selecting a speed for each of the pluralities of data symbol flows based on an SNR calculation for the transmission channel for the data symbol stream. The method according to claim 34, further comprising: sending to the transmitting entity at least one speed for the plurality of data symbol streams, characterized by the plurality of data symbol streams being encoded and modulated in base to at least one speed. 45. The method according to claim 34, further comprising: calculating a noise / interference signal (SNR) ratio of each of the plurality of retransmission channels for the plurality of data symbol flows; and selecting a single rate for the plurality of data symbol flows based on the SNR calculations for the plurality of transmission channels. 46. The method according to claim 34, further comprising: demodulating and decoding each of the pluralities of symbols flows recovered based on a speed selected for the flow to obtain the decoded data. 47. The method according to claim 34, characterized in that developing spatial despreading comprises: developing spatial despreading in the plurality of symbol streams detected with at least two address matrices for a plurality of subbands of each period of symbol used for data transmission. 48. An apparatus in a wireless multiple input / output (MIMO) communication system, comprises: a plurality of receiver units for obtaining a plurality of symbol flows received for a plurality of data symbol flows transmitted through a plurality of transmission channels in a MIMO channel from a transmitting entity for a receiving entity, wherein the plurality of data symbol streams are spatially propagated with a plurality of address matrices and further spatially processed before transmitting them through the channel MIMO, and wherein the spatial propagation with the plurality of address matrices randomizes the plurality of transmission channels for the plurality of data symbol flows; a spatial processor for developing the receotor spatial procedure in the plurality of received symbol streams to obtain a plurality of detected symbol streams; and a spatial despread to develop spatial despreading in the plurality of symbol streams detected with the plurality of address arrays to obtain a plurality of retrieved symbol streams, which are computed from the plurality of data symbol streams. 49. The apparatus according to claim 48, further comprises: a channel calculator for obtaining an effective MIMO channel calculation including a channel response calculation for the MIMO channel and the plurality of address matrices used for the propagation space, and characterized in that the spatial processor and the spatial depropagator develop the spatial receiver and spatial despread method together based on the calculation of the effective MIMO channel. 50. The apparatus according to claim 48, characterized in that the spatial processor multiplies the plurality of symbol flows received with arrays of eigenvectors for a plurality of modes proper to the MIMO channel to obtain the plurality of streams of detected symbols. 51. The aparate according to claim 48, characterized in that the spatial processor multiplies the plurality of symbol flows received with a matching filter, derived in case of a channel response calculation for the MIMO channel, to obtain the plurality of flows of detected symbols. 52. The apparatus according to claim 48, characterized in that the spatial processor develops the receiver spatial procedure based on a channel correlation matrix inversion (CCMI) technique, a minimum square-average error technique (MMSE), or a successive interference cancellation technique (SIC). 53. The apparatus according to claim 48, further comprises: a channel calculator for calculating a noise / interference signal ratio (SNR) of each of the plurality of transmission channels for the plurality of data symbol flows; and a controller for selecting a speed for each of the plurality of data symbol streams based on an SNR calculation for a transmission channel for the data symbol stream, and characterized in that each data symbol stream is encoded and modulates by means of the transmitting entity based on the speed selected for the flow of data symbols. 54. An apparatus according to claim 48, further comprising: a data processor for demodulating and decoding each of the plurality of symbol streams recovered based on a speed selected for flow to obtain the decoded data. 55.- An apparatus according to claim 48, characterized in that the MIMO system uses orthogonal frequency division multiplexing (), and characterized in that the spatial depropagator develops spatial depropagation with at least two different address matrices for a plurality of sub-bands in each symbol period with the transmission of data. 56.- An apparatus in a multiple input / output communication system (MIMO), comprises: means for obtaining a plurality of symbol flows received for a plurality of data symbol flows transmitted through a plurality of transmission channels in a MIMO channel, wherein the plurality of data symbol streams are spatially propagated with a plurality of address matrices and further processed spatially before transmission through the MIMO channel, and wherein the spatial propagation with the plurality of address arrays randomize the plurality of transmission channels for the plurality of data symbol flows; means for developing the receiver spatial procedure in the plurality of received symbol streams to obtain a plurality of detected symbol streams; and means for developing spatial despreading in the plurality of detected symbol streams with the plurality of address arrays to obtain a plurality of retrieved symbol streams, which are calculations of the plurality of data symbol streams. The apparatus according to claim 56, characterized in that the means for developing the receiver spatial procedure comprises: means for multiplying the plurality of received symbol streams with eigenvector matrices for a plurality of modes proper to the MIMO channel to obtain the plurality of streams of detected symbols. 58. The aparate according to claim 56, characterized in that the means for developing the receiver spatial procedure comprises: means for multiplying the plurality of symbol flows received with a matching filter, derived on the basis of a channel response calculation for the MIMO channel, to obtain the plurality of detected symbol flows. 59. The aparate according to claim 56, further comprising: means for calculating a noise / interference signal (SNR) ratio of each of the plurality of transmission channels for the plurality of data symbol flows; and means for selecting a speed for each of the plurality of data symbol streams based on an SNR calculation for a transmission channel for the data symbol stream, and characterized in that each stream of signal symbols is encoded and modulated by means of the transmitting entity based on the speed selected for the flow of data symbols.