WO2008086239A1 - Livre de code de précodage pour systèmes mimo - Google Patents

Livre de code de précodage pour systèmes mimo Download PDF

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Publication number
WO2008086239A1
WO2008086239A1 PCT/US2008/050319 US2008050319W WO2008086239A1 WO 2008086239 A1 WO2008086239 A1 WO 2008086239A1 US 2008050319 W US2008050319 W US 2008050319W WO 2008086239 A1 WO2008086239 A1 WO 2008086239A1
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Prior art keywords
matrix
codebook
rank
precoding
householder
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PCT/US2008/050319
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English (en)
Inventor
Badri Varadarajan
Eko N. Onggosanusi
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Texas Instruments Incorporated
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Publication of WO2008086239A1 publication Critical patent/WO2008086239A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0417—Feedback systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/0478—Special codebook structures directed to feedback optimisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/063—Parameters other than those covered in groups H04B7/0623 - H04B7/0634, e.g. channel matrix rank or transmit mode selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0632—Channel quality parameters, e.g. channel quality indicator [CQI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0636—Feedback format
    • H04B7/0639—Using selective indices, e.g. of a codebook, e.g. pre-distortion matrix index [PMI] or for beam selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/046—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account
    • H04B7/0465—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account taking power constraints at power amplifier or emission constraints, e.g. constant modulus, into account

Definitions

  • the present disclosure is directed, in general, to wireless communication systems and, more specifically, to Multiple-Input Multiple-Output (MIMO) communication employing a transmitter, a receiver and methods of operating a transmitter and a receiver.
  • MIMO Multiple-Input Multiple-Output
  • MIMO communication systems offer large increases in throughput due to their ability to support multiple parallel data streams that are each transmitted from different spatial transmission layers which are either real/physical or virtual antennas.
  • MIMO transmissions employ one or more parallel spatial streams that are independently FEC encoded, termed codeword. Each stream/codeword is then mapped to one or more transmission layers . Mapping of one encoded stream to multiple layers can be done by simply distributing the encoder stream output on all the layers, i.e., the serial stream from the FEC output is converted to parallel streams on different layers . The number of spatial transmission layers is termed the rank of transmission.
  • the number of transmission layers is typically less than or equal to the number of physical antennas.
  • the signal on the virtual antennas is converted to the signal on the real antennas, typically by linear precoding, i.e., linearly combining the virtual antenna signals to obtain the actual transmit signals.
  • linear precoding i.e., linearly combining the virtual antenna signals to obtain the actual transmit signals.
  • the effectiveness of MIMO communication depends on the set of possible precoders used, called the codebook. Although many current precoding codebooks exist, further improvements would prove beneficial in the art. BRIEF DESCRIPTION OF THE DRAWINGS
  • FIGURE 1 illustrates a system diagram of a transmitter as provided by one embodiment of the present disclosure
  • FIGURE 2 illustrate an embodiment of a method of operating a transmitter
  • FIGURE 3 illustrates a system diagram of a receiver as provided by one embodiment of the present disclosure
  • FIGURE 4 illustrates an embodiment of a method of operating a receiver
  • FIGURE 5 illustrates an embodiment of a method of computing preferred transmission ranks and precoder matrices in a receiver
  • Embodiments of the present invention below employ a transmitter (node-B) and a receiver (UE) equipped with multiple antennas.
  • the UE may feed back a channel quality indicator (CQI) report to assist the transmitter in selecting transmission parameters.
  • CQI channel quality indicator
  • the following parameters are adapted, often based on receiver feedback.
  • Rank Adaptation The rank R, namely, the number of spatial transmission. The rank cannot exceed the number of transmit antennas N T .
  • Link Adaptation The modulation and coding scheme (MCS) of each spatial stream. This is determined by the channel quality indicator (CQI) for each spatial stream.
  • MCS modulation and coding scheme
  • Precoder Adaptation The mapping from virtual-to- real antennas, called precoding, can be adapted to improve the channel quality indicator of different streams.
  • precoding can be based on receiver feedback, or it can be done in a feedback-independent way, by using a time-varying precoding pattern.
  • time-division duplex (TDD) system where the uplink and downlink channels are reciprocal.
  • TDD time-division duplex
  • Feedback-based adaptive precoding applies to any duplexing scheme including frequency-division duplex
  • FIGURE 1 illustrates a system diagram of a transmitter
  • FIGURE 2 illustrates a method of operating the exemplary transmitter.
  • the transmitter operates in an OFDM communication system (typically referred to as a node B) although the principles of the present disclosure may be employed in other communication systems.
  • the transmitter includes a transmit portion (101) and a feedback decoding portion
  • the transmit portion (101) includes a modulation, encoding, and layer mapping module (102), a precoding module
  • the feedback decoding portion (110) includes a receiver module (114) and a decoder module (112) .
  • the transmitter has at least two transmit antennas and is capable of transmitting at least one spatial codeword corresponding to a transmission rank grouping.
  • the feedback decoding portion (110) is configured to recover the CQI report from the UE, which is used to determine the precoding matrix index on each time-frequency resource block, as illustrated in (202) and (204) of FIGURE 2.
  • the transmit portion (101) is coupled to the multiple transmit antennas and provides a transmission. Data is generated and encoded for each of the symbol streams.
  • the encoded streams are grouped (102) by mapping one spatial stream to multiple spatial layers (in the form of virtual antennas) wherein the number of active virtual antennas is given by a transmission rank R. By performing encoding and layer mapping, the transmit signal on each transmission layer is assembled.
  • the precoding module (104) converts the signal on the R virtual antennas to the N T physical antennas .
  • Embodiments of the precoders presented are linear. That is, the signal on each of the physical antennas is some linear combination of the signals on the virtual antennas .
  • the mapping can be specified by an N T xR linear precoding matrix.
  • the precoder output contains signal to be transmitted on the physical antennas.
  • the signal is assembled in the frequency domain and converted to time domain using the OFDM modulator which can add a cyclic prefix to guard against channel distortion.
  • the specific OFDM modulation is just an example for the various kinds of modulation schemes that could be used to send the precoder output on the channel.
  • Some other examples include code-division multiple access (CDMA) and time- division multiple access (TDMA) transmissions where the signal is transmitted in the code and time domain, respectively.
  • CDMA code-division multiple access
  • TDMA time- division multiple access
  • FIGURE 3 A corresponding embodiment of a receiver 300 is shown in FIGURE 3, and an exemplary method of operating that receiver is shown in FIGURE 4.
  • the receiver includes a data decoding portion (301) and a feedback generation portion (310) .
  • the OFDM demodulation is followed by channel estimation (308) which enables control channel decoding (309).
  • the control channel decoder determines, among other things, the transmission rank and the precoder index used by the transmitter on each time-frequency resource.
  • the receiver uses the knowledge of the codebook, the receiver then determines the precoding matrix used. This knowledge is used by the MIMO detector (304) to generate soft information for each transmission layer, which is then subsequently processed to decode the various coded streams .
  • the receiver embodiment shown in FIGURE 3 also contains a feedback generation portion (310) , which uses channel and noise variance estimates to assemble the CQI report.
  • this includes selection of a recommended rank (316) , the preferred precoder index from the codebook corresponding to the preferred rank (312), CQI for the corresponding transmission layers / coded streams (314) . These are then fed back to the transmitted using the modulator (318) .
  • the precoding matrix in many communication systems is drawn from a finite codebook.
  • the codebook size increases the size allows better tuning of the precoder matrix to improve the signal-to-interference-noise ratio (SINR) seen by the transmission layers, and hence to increase downlink throughput.
  • SINR signal-to-interference-noise ratio
  • a larger codebook size also increases the amount of feedback and downlink control signaling to indicate the preferred / used precoder index.
  • the UE might need to compute the optimum precoding matrix based on channel and noise variance estimates, as shown in Block (312) in FIG 3. An exemplary procedure for doing so is shown in FIG 5.
  • the exemplary receiver first examines each rank, starting with rank 1 (500) .
  • the receiver computes the SINR of each layer (502), uses it to compute the sum throughput (504) .
  • the receiver picks the preferred precoding matrix for that rank (506) .
  • the receiver determines the preferred rank and the corresponding precoding matrix (514) .
  • Other throughput-based metrics can also be used.
  • other optimality criteria are also possible such as the maximizing the worst-case SINR, minimizing the worst-case block error rate.
  • This codebook size is signaled periodically either by broadcasting to the entire network or by signaling to individual sets of user(s).
  • each set of users comprises only a single user.
  • dedicated signaling is required to notify the change in codebook. Since the codebook changes slowly, higher layer signaling can be used for this purpose .
  • the actual codebook must be chosen to maximize performance (e.g. maximum throughput, minimum error rate, maximum SINR) , while at the same time minimizing the computational complexity of precoder feedback calculation.
  • Embodiments of the present invention describe a nested codebook structure which enables easy computation of throughput metrics for precoding matrices.
  • the precoding matrix for rank R transmission has dimensions N T X R.
  • the R columns are the matrix are mutually orthogonal N T x 1 complex vectors.
  • the rank-R codebook consists of N C matrices, it effectively contains a set of up to N C ⁇ R vectors. Note that some of these may be scaled versions of each other, and therefore should be counted together. Denote this set by S(R) .
  • the nested structure requires that if R 1 ⁇ R 2 , then S(R 1 ) ⁇ S (R 2 ) •
  • the advantages of the nested structure are as follows: First, it simplifies the codebook design. Second, it is simpler for the node-B to estimate the preferred precoding matrix and CQI when it has to override the UE's rank recommendation. More importantly, the nested structure simplifies precoder selection because it allows reuse of computations for precoder metric calculation with different codebooks . Specifically, the per-layer SINR calculation (502 in FIG 5) requires computation of the form V H PV where V is a matrix in the codebook and P is the effective channel at the whitened matched filter output.
  • V H denotes complex conjugate (Hermitian) transpose operation.
  • each of the elements of V H PV is a product of the form v 1 H Pv 2 where v 1 and v 2 are in the set S(R) . Because of the nested property it is sufficient to calculate these products for the highest rank S(N T ) and the remaining can be derived thence.
  • each matrix in the rank-R ( ⁇ N T ) codebook is a sub-matrix of a matrix in the rank-N T codebook.
  • a sub-matrix of W is defined as a matrix that is constructed from the column vectors of matrix W without any particular restriction on the column ordering or column permutation. That is, any column ordering or permutation is possible.
  • a 4x2 sub-matrix X can be constructed from columns ⁇ 1,2 ⁇ , ⁇ 2,1 ⁇ , ⁇ 1,3 ⁇ , ⁇ 3,1 ⁇ , ⁇ 1,4 ⁇ , ⁇ 4,1 ⁇ , ⁇ 2,3 ⁇ , ⁇ 3,2 ⁇ , ⁇ 2,4 ⁇ , ⁇ 4,2 ⁇ , ⁇ 3,4 ⁇ , or ⁇ 4,3 ⁇ .
  • an additional scalar multiplication can be applied to all the selected column vectors.
  • V H PV for a rank-R precoding matrix is a direct sub-matrix of W H PW for some rank-N T precoding matrix W.
  • each matrix in the rank-R ( ⁇ N T ) codebook is a sub-matrix of a matrix in the rank-(R+1) codebook. This is mostly beneficial when the node-B decides to override the rank report recommended by the node-B .
  • Embodiments of the present invention use the general nested codebook structure described above. Some illustrative examples are now presented. Those skilled in the art can recognize that the examples are preferred embodiments.
  • the rank-2 codebook consists of three matrices and the rank-1 codebook consists of the columns of the columns of those matrices.
  • EXEMPLARY METHOD 1 SUBMATRIX SELECTION FROM A FIXED PRECODING MATRIX Choose a fixed precoding matrix M of dimension N T X N T . Possible choices of this matrix include
  • the rank R codebook consists of N T X R submatrices obtained by choosing R columns from M. Note that one could either choose all C(N T , R) possible submatrices are some subset thereof.
  • the above codebook construction method can be viewed alternatively as follows:
  • the fixed precoder M transforms virtual antennas to real antennas.
  • precoding consists of virtual antenna selections alone.
  • FIG 7 contains one illustrative example for N T - 4, with M being the 4 X 4 Hadamard matrix.
  • Step 1 Choose Rank-One Codebook: The rank-one codebook consisting of some N unit-norm 4 x 1 complex vectors is chosen. Note that the codebook can be chosen to satisfy any metric. In one embodiment, the codebook is chosen so that each of its elements is drawn from a small finite alphabet set, such as ⁇ +1, ⁇ j ⁇ or ⁇ 1, ⁇ j, ( ⁇ 1 ⁇ j)/ 2 ⁇ . Other methods are described in the sequel .
  • Step 2 Obtain Householder vectors: From each vector in the rank-one codebook, obtain one Householder basis vector. This can be done as follows . Suppose x is a valid precoding vector. Then the corresponding Householder vector u is obtained
  • the resulting u is unique up to a phase rotation, and is unit-norm.
  • N T - 4 another notable feature of such construction is the preservation of constant modulus property across different ranks for each of the matrix/vector elements. That is, if all the elements of x have the same magnitude, the same holds for u as well as H(u) .
  • Step 3 Obtain rank-4 codebook: From the set of Householder vectors u, construct the 4x4 Householder matrices
  • rank-4 codebook forms the rank-4 codebook.
  • applying column permutation i.e. rearranging the column order
  • the rank-4 codebook can also be constructed from such set of Householder matrices with column permutation applied to at least one the matrices.
  • there are 4! ( 24) possible column permutations or rearrangements.
  • Some examples are ⁇ 1,2,3,4 ⁇ , ⁇ 1,3,2,4 ⁇ , ⁇ 4,1,2,3 ⁇ .
  • Step 4 Obtain rank-2 and rank-3 codebooks by column selection: Codebooks for rank two and three are obtained by selecting sub-matrices of the rank-4 codebook.
  • more sophisticated construction techniques would pick the sub-matrices in order to optimize the chordal or Fubini-Study distance or some other performance-related criterion. Methods for doing so are described in the sequel .
  • rank-one codebooks are designed to maximize inter-element distance based on a metric like chordal or Fubini-Study distance. While such "Grassmanian" codebooks work well for uncorrelated fading channels, they do not necessarily achieve good performance for correlated fading. The reason for this is that antenna correlation distorts the space of the dominant right singular vector and makes it more concentrated along a specific direction. Two methods can be used to derive rank-one codebooks for correlated fading channels.
  • the first method uses matched filtering criterion of Grassmanian codebooks.
  • a Grassmanian codebook ⁇ If the transmit antenna correlation matrix is R ⁇ , then the codebook for rank-one transmission can be ⁇ y /
  • , where y R T x, x ⁇ ⁇ .
  • the second method applies selection from a finite mother set: Instead of the heuristic method of matched filtering, a precise search algorithm can be used to find high-performance codebook.
  • a finite set ⁇ containing (N T X 1) vectors of norm N T .
  • the elements of ⁇ could be drawn from a small finite-alphabet set like ⁇ 1, ⁇ j ⁇ , or ⁇ 1, ⁇ j, ( ⁇ 1 ⁇ j) / 2 ⁇ .
  • the vectors in ⁇ are scaled so that the first element is zero-phase.
  • codebook design is stated as a problem of selecting a subset ⁇ of vectors from the larger "mother set" ⁇ . Many methods can be used for selecting the subset:
  • the subset can be searched by trial and error (i.e. random search) to maximize chordal distance.
  • a set of random channel matrices are generated according to the desired distribution.
  • the effective SINR is calculated for each matrix and each candidate vector in ⁇ .
  • the effective SINR for each channel matrix is the maximum effective SINR across all candidate vectors in the codebook.
  • this maximum effective SINR S max ( ⁇ , H) is a random variable whose specific value depends on the channel matrix H but whose distribution is determined by the codebook ⁇ .
  • the numerical search can be implemented exhaustively for all possible selections ⁇ ..
  • a greedy approach can be implemented as follows. Choose the first element such that it minimized Pr(S max ( ⁇ , H) ⁇ s 0 ) . Then remove from consideration all values of H for which the chosen element is the best (max- SINR) element in ⁇ . Now, from among the remaining values of H, choose the second element to minimize Pr (S max ( ⁇ , H) ⁇ s 0 ) and so on.
  • the numerical search method for rank-one codebooks can be extended. Two modifications are necessary. Firstly, the cost function for selecting a rank-R codebook needs to be changed because up to R SINRs are generated, so the SINR itself cannot be used as a cost function since it is multi-dimensional. Instead the sum throughput can be used as cost function, assuming some nominal noise variance. Alternatively, the Frobenius norm (energy) of the matrix (HV) can be used instead of SINR as the cost function for a precoding matrix V ⁇ ⁇ . Once the cost function is chosen, any search method can be used to determine the codebook, exhaustive and greedy search being exemplary methods .
  • the second, and crucial change needed for higher rank codebooks is the choice of the mother codebook from which the subset is selected.
  • One possible choice is the set of all (N T x R) matrices with elements drawn from a finite codebook.
  • An alternative embodiment is to use Householder matrices obtained from the rank-one codebook as discussed earlier.
  • FIG 8 presents an example of a Householder-based nested codebook construction.
  • the householder vectors ⁇ u i ⁇ are tabulated.
  • the rank-4 codebook consists of Householder matrices.
  • the rank-1 and rank-3 codebook contain respectively the first one and three columns of the Householder matrices.
  • the rank-2 codebook is obtained by sub-matrix selection, as shown.
  • FIG 9 presents another example of a Householder-based nested codebook construction. Compared to the previous example, this exemplary design conforms to the strongest nested condition. In addition, column permutation is applied to some of the matrices in the rank-4 codebook.
  • codebooks of some (but not all) ranks are generated using the Householder structure.
  • the codebooks for rank-1 and 2 can be generated based on the structures given above.
  • the codebooks for rank-3 and 4 can be designed based on some other constructions such as ordering, grouping, and/or antenna selection.
  • the ordering, grouping, and/or antenna selection can be based on physical antennas or virtual antennas.
  • the finite- alphabet Householder codebook (for all ranks) can be combined with physical or virtual antenna selection codebook (for all ranks) to form a larger codebook.
  • Another possible combination is with the grouping codebook (for all ranks) .
  • Other combinations are also possible for one skilled in the art.
  • Yet another possible variation is to remove at least one matrix from at least one of the N T codebooks from the original construction. For instance, it is possible to remove at least one of the 4x4 matrices in the rank-4 codebook given in FIG 8 or 9. This can be done to reduce feedback overhead without significant impact on the performance. While this does not fully conform with the prescribed definition of nested structure, it is still within the scope of the invention.

Abstract

L'invention concerne un procédé de transmission dans lequel une matrice de précodage est sélectionnée parmi des livres de code NT et chaque livre de code correspond à un rang de transmission et NT correspond au nombre d'antennes de transmission. Le signal de données est précodé en réponse à la matrice de précodage sélectionnée, puis transmis. Chaque matrice NTXR du livre de code correspondant à un rang de transmission R, R étant inférieur à NT, est une sous-matrice d'une matrice de précodage NTXNT correspondant au livre de code de rang NT. En variante, chaque matrice NTXR du livre de code correspondant à un rang de transmission R, R étant inférieur à NT, est une sous-matrice d'une matrice de précodage NTX (R+1) correspondant au livre de code de rang (R+1). Un mode de réalisation donné à titre d'exemple basé sur Householder construction est également donné.
PCT/US2008/050319 2007-01-04 2008-01-04 Livre de code de précodage pour systèmes mimo WO2008086239A1 (fr)

Applications Claiming Priority (12)

Application Number Priority Date Filing Date Title
US88343507P 2007-01-04 2007-01-04
US60/883,435 2007-01-04
US88822907P 2007-02-05 2007-02-05
US60/888,229 2007-02-05
US89012507P 2007-02-15 2007-02-15
US60/890,125 2007-02-15
US89329107P 2007-03-06 2007-03-06
US60/893,291 2007-03-06
US91346107P 2007-03-16 2007-03-16
US89535407P 2007-03-16 2007-03-16
US60/913,461 2007-03-16
US60/895,354 2007-03-16

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WO2010009640A1 (fr) * 2008-07-21 2010-01-28 华为技术有限公司 Procédé, dispositif et système destinés à sélectionner une matrice de précodage dans un système mimo
EP2209220A1 (fr) * 2009-01-19 2010-07-21 ST-Ericsson (France) SAS Procédé de formation de faisceau de données devant être transmises par une station de base dans un système MU-MIMO et appareil de réalisation de celui-ci
WO2010105670A1 (fr) * 2009-03-17 2010-09-23 Nokia Siemens Networks Oy Procédé et appareil pour un pré-codage basé sur une liste de codage dans des systèmes mimo
WO2011032365A1 (fr) 2009-09-18 2011-03-24 富士通株式会社 Procédé et dispositif de génération de livre de codes de matrice de précodage
WO2011035481A1 (fr) 2009-09-25 2011-03-31 富士通株式会社 Procédé et dispositif de génération de livre de codes de matrice de précodage
EP2316173A2 (fr) * 2008-08-06 2011-05-04 Samsung Electronics Co., Ltd. Procédé et appareil permettant de générer le livre de codes de précodage d'une émission d'antennes multiples
CN102088340A (zh) * 2010-01-11 2011-06-08 大唐移动通信设备有限公司 一种多天线系统发送、接收信息的方法及装置
EP2368331A1 (fr) * 2008-12-15 2011-09-28 Huawei Technologies Co., Ltd. Procédé d'utilisation de répertoires de rang 1 et 2 sur six bits pour quatre antennes émettrices
EP2396938A2 (fr) * 2009-03-17 2011-12-21 Huawei Technologies Co., Ltd. Livre de codes de précodage et représentation en rétroaction
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