CN112236961B - Channel state information feedback - Google Patents
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- CN112236961B CN112236961B CN201880093680.2A CN201880093680A CN112236961B CN 112236961 B CN112236961 B CN 112236961B CN 201880093680 A CN201880093680 A CN 201880093680A CN 112236961 B CN112236961 B CN 112236961B
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- 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
- H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
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Abstract
Various communication systems may benefit from channel state information feedback. For example, it may be helpful to use spatial compression to improve channel state information feedback. According to some embodiments, a method may include determining, at a user device, a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The method may also include constructing, at the user equipment, a channel state information report including the single set of transformation matrices. Additionally, the method may include transmitting, from the user equipment to the network entity, a channel state information report comprising a single set of transformation matrices.
Description
Technical Field
Various communication systems may benefit from channel state information feedback. For example, it may be helpful to use spatial compression to improve channel state information feedback.
Background
In third generation partnership project (3 GPP) technologies such as Long Term Evolution (LTE), fifth generation (5G), or New Radio (NR) technologies, multiple Input Multiple Output (MIMO) may be utilized to help facilitate signal transmission. MIMO is used to increase the total bit rate by transmitting two or more different data streams on two or more different antennas-both in frequency and time using the same resources-separated by using only different reference signals-for reception by the two more antennas. In NR technology, the number of antennas and/or data streams will increase, thereby increasing the importance of MIMO at the same time.
To allow MIMO to be used in NR technology, channel state information feedback and compression schemes are used. For example, time, frequency and spatial domain compression is used to compress signal transmissions. This may allow multiple signals to be transmitted on multiple antennas using the same frequency and/or time resources.
Disclosure of Invention
According to some embodiments, an apparatus may comprise at least one memory including computer program code and at least one processor. The at least one memory and the computer program code may be configured, with the at least one processor, to cause the apparatus at least to determine a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The at least one memory and the computer program code may also be configured, with the at least one processor, to cause the apparatus at least to construct a channel state information report comprising a single set of transformation matrices. In addition, the at least one memory and the computer program code may also be configured, with the at least one processor, to cause the apparatus at least to transmit a channel state information report comprising a single set of transformation matrices to a network entity.
According to some embodiments, a method may include determining, at a user device, a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The method may also include constructing, at the user equipment, a channel state information report comprising a single set of transformation matrices. Additionally, the method may include transmitting, from the user equipment to the network entity, a channel state information report comprising a single set of transformation matrices.
In some embodiments, an apparatus may include means for determining a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The apparatus may also include means for constructing a channel state information report comprising a single set of transformation matrices. Additionally, the apparatus may include means for transmitting a channel state information report comprising a single set of transformation matrices to a network entity.
According to some embodiments, a non-transitory computer readable medium encodes instructions that, when executed in hardware, perform a process. The process may include determining, at a user device, a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The process may also include constructing, at the user equipment, a channel state information report including a single set of transformation matrices. Additionally, the process may include transmitting, from the user equipment to the network entity, a channel state information report, the channel state information including a single set including the transformation matrix.
According to certain other embodiments, a computer program product may encode instructions for performing a process. The process may include determining, at a user device, a single set of transformation matrices. A single set of transformation matrices may be used for different layers. The process may also include constructing, at the user equipment, a channel state information report including a single set of transformation matrices. Additionally, the process may include transmitting, from the user equipment to the network entity, a channel state information report including a single set of transformation matrices.
According to some embodiments, an apparatus may include circuitry to determine a single set of transform matrices. A single set of transformation matrices may be used for different layers. The apparatus may also include circuitry to construct a channel state information report comprising a single set of transformation matrices. Additionally, the apparatus may include circuitry to transmit, from the user equipment to the network entity, a channel state information report comprising a single set of transformation matrices.
According to some embodiments, an apparatus may include at least one memory including computer program code and at least one processor. The at least one memory and the computer program code may be configured, with the at least one processor, to cause the apparatus at least to receive a single set of transformation matrices from a user equipment. A single set of transformation matrices is used for the different layers. The at least one memory and the computer program code may also be configured, with the at least one processor, to cause the apparatus at least to construct channel state information based on the single set of transformation matrices.
According to some embodiments, a method may include receiving, at a network entity, a single set of transformation matrices from a user device. A single set of transformation matrices may be used for different layers. The method may further include constructing, at the network entity, channel state information based on the single set of transformation matrices.
In some embodiments, an apparatus may include means for receiving a single set of transformation matrices from a user device. A single set of transformation matrices may be used for different layers. The method may further include constructing channel state information based on the single set of transformation matrices.
According to some embodiments, a non-transitory computer readable medium encodes instructions that, when executed in hardware, perform a process. The process may include receiving, at a network entity, a single set of transformation matrices from a user device. A single set of transformation matrices may be used for different layers. The process may also include constructing channel state information at the network entity based on the single set of transformation matrices.
According to certain other embodiments, a computer program product may encode instructions for performing a process. The process may include receiving, at a network entity, a single set of transformation matrices from a user device. A single set of transformation matrices may be used for different layers. The process may also include constructing channel state information at the network entity based on the single set of transformation matrices.
According to some embodiments, an apparatus may include circuitry to receive a single set of transformation matrices from a user device. A single set of transformation matrices may be used for different layers. The apparatus may also include circuitry to construct channel state information based on the single set of transformation matrices.
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For a proper understanding of the exemplary embodiments of the present invention, reference should be made to the accompanying drawings, in which:
FIG. 1 illustrates an example of a table according to some embodiments.
FIG. 2 illustrates an example of a graph in accordance with certain embodiments.
Fig. 3 illustrates an example of a table in accordance with certain embodiments.
FIG. 4 illustrates an example of a table according to the ABC scheme.
Fig. 5 illustrates an example of a table in accordance with certain embodiments.
Fig. 6 illustrates an example of a diagram in accordance with certain embodiments.
Fig. 7 illustrates an example of a method according to some embodiments.
Fig. 8 illustrates an example of a method according to some embodiments.
Fig. 9 illustrates an example of a system according to some embodiments.
Detailed Description
Some embodiments allow for overhead reduction by using enhanced channel state information feedback based on Principal Component Analysis (PCA). PCA may be a statistical process that uses an orthogonal transformation to convert a set of data points into a set of uncorrelated linear variables (called principal components). The first principal component of the PCA may have the greatest possible variance, while each subsequent component may in turn have the greatest possible variance under the constraint of being orthogonal to the previous component. In NR technology, PCA can improve accuracy of channel state information using a special channel compression technique while reducing feedback overhead.
As discussed above, PCA may be the use of quadrature transformation Q to convert the related variables of X intoStatistical process of uncorrelated variables of Φ. In other words, PCA can be expressed by the following formula: Φ=qx. The row of Q may be the principal component of X. In some embodiments, channel compression and feedback may be used. In certain embodiments, M x N c Can be used which includes the channel dominant eigenvector X (p) of M X1 in all subbands and layers (p=1, …, N c ). M may be the number of antenna ports, N may be the number of subbands, RI may be the number of layers or the reported rank index, and N c ＝N x RI。
The channel matrix may be expressed as follows:singular Value Decomposition (SVD) or Eigenvector Decomposition (ED) may be performed on the above channel matrix X to obtain one or more components. The one or more components may be, for example, principal components, singular vectors, or eigenvectors. The covariance matrix of X and its eigenvector decomposition can be calculated using the following formula: />Where U may be formed from eigenvectors and Σ may be composed of eigenvalues along the main diagonal. According to PCA, transform matrix->May include K principal components, which may be derived from R having a maximum of K eigenvalues x Is selected from the first K dominant feature vectors of (c). The following formula may be used: />To calculate the transformed matrix Φ.
User equipment may quantize and feedback the transform matrixAnd transformed matrix->One or more of the coefficients of (a). Feedback of one or more coefficients may mean transmitting the coefficients from the user equipment to a network entity, such as 5G or NR NodeB (gNB). In other words, feedback of the transformation matrix may mean that all coefficients of all components should be quantized and reported to the network entity. Quantization and feedback may be divided into two parts, one for the index of the strongest coefficient of one or more components and the other for the coefficients of all components except the strongest coefficient or coefficients. In some embodiments, matrix->M x K coefficients may be included, which are common to the different layers. The matrix Φ may include kx N coefficients for each layer. The total number of coefficients for feedback can be expressed as follows: (KXM) + (KXN RI), assuming rank RI. Thus, in some embodiments, only a single set of transformation matrices may be used +.>Rather than having to use multiple sets for different layers. Doing so may reduce the amount of network resources, thereby providing significant advantages to the network as well as to the user equipment itself. For example, use only a single set of transformation matrices +. >The channel state information payload may be reduced by K x M x (RI-1) coefficients.
Thus, some embodiments may provide channel state information feedback transmitted from a user equipment to a network entity such as 5G or NR nodeB (gNB). In other words, the user equipment constructs the channel state information report as part of the feedback provided by the user equipment to the network entity. Constructing the channel state information report may include determining at least one of: transformation matrixOr transformed matrix->Some embodiments may also utilize higher layer parameter configurations. For example, radio Resource Control (RRC) may be used to configure parameters at the user equipment. Higher layer parameter configurations may be used as the determination of the transformation matrix +.>Or transformed matrix->Is a part of the same.
Transformation matrixK principal components may be included that are common to the different layers. Using K principal components common to different layers may allow the use of only a single set of transformation matrices +.>Without having to use multiple sets for different layers. As discussed above, only a single set of transformation matrices is used +.>The channel state information payload may be reduced by K x M x (RI-1) coefficients.
For each principal component, M coefficients may be quantized separately with respect to amplitude and phase. To reduce (streamline) the channel state information payload, the strongest coefficient may be selected first from the M coefficients, and the following formula may be used: To quantize the index of the strongest coefficient. The strongest coefficient may have the largest magnitude value. The other (M-1) coefficients of the principal component may be divided by the strongest coefficient and then quantized separately with respect to amplitude and phase. In some embodiments, for each principal component, it may be implemented from the user equipment to the networkVolume report transformation matrix->The index of the strongest coefficient of (c) and the amplitude/phase values of the other (M-1) coefficients. The report may be included as part of a channel state information report. The network entity may be, for example, a gNB. In some embodiments, the reporting may occur on a Physical Uplink Shared Channel (PUSCH).
Thus, the user equipment may determine that the user equipment is included in the transformation matrixAn index of each principal component of the model. The principal components of the transformation matrix may be common to the different layers. The index may represent the strongest coefficient for each principal component included in the transformation matrix, and the following formula may be used: />But is calculated. The index may be reported by the user equipment to the network entity.
As discussed above, the construction of the channel state information report may include determining a transformation matrixOr transformed matrix- >At least one of (a) and (b). Transformed matrix->There may be individual quantized coefficients for each layer. In each layer, the strongest coefficient may be selected first from the k×n coefficients, and the following formula may be used:the coefficients of the strongest coefficients are quantized. The transformed matrix is in the other (KXN-1) of the layersThe coefficients may be divided by the strongest coefficients and then quantized separately with respect to amplitude and phase. In some embodiments, for each layer, the index of the strongest coefficient in the transformed matrix Φ and the amplitude/phase values of the other (kxn-1) coefficients may be reported from the user device. The report may be included as part of a channel state information report. For example, the index may be reported on a physical uplink shared channel from the user equipment to a network entity such as the gNB.
In other embodiments, the user device may determine another index for the transformed matrix in one or more layers. The transformed matrix in each of the one or more layers may have separate quantization coefficients. The index of the transformed matrix may represent the strongest coefficient in each layer.
The channel state information feedback may include higher layer parameter configurations. In other words, some higher layer parameters may be statically or semi-statically configured. The network entity may determine higher layer parameters and transmit the parameters to the user equipment. For example, the user equipment may receive the parameters using Radio Resource Control (RRC) signaling. These parameters may be, for example, the number of principal components K. The quantized sets of amplitude and phase and the quantized bits may be directed to the transformation matrix by the network entity, respectively And a transformed matrix Φ.
In some embodiments, the channel state information may be constructed or reconstructed by the network entity using the received information included in the channel state information report. The report may include, for example, a single set of transformed matrices, and one or more sets of transformed matrices. The network entity may be based on being included in the transformation matrixAnd/or information in the transformed matrix Φ. By->The channel state matrix can be restored on the network entity side (e.g., gNB)>
Using a transform matrix, as compared to another channel state information approachThe above embodiments of at least one of the transformed matrix Φ and/or the higher layer parameter configuration may help reduce the channel state information payload by 35%. In addition, the channel state information feedback overhead may be reduced by 6% for 9 subbands, 18% for 13 subbands, and 28% for 20 subbands, as compared to other channel state information methods. In other words, certain embodiments may help reduce channel state information feedback overhead, thereby reducing network resources used for channel state information reporting and/or construction.
FIG. 1 illustrates an example of a table according to some embodiments. In particular, fig. 1 illustrates an example of channel state information feedback using subband bundling. In some embodiments of subband correlation, the correlated subbands may be selected together as part of channel state information feedback. In particular, the network entity may configure the user equipment with respect to which sub-bands are to be considered jointly or independently. In some embodiments reporting the selection of subband bundling, for example, the subband bundling may be reported on PUSCH together with channel state information feedback.
The user equipment may perform bundling and feedback or transmit such information to the base station together with the channel state information report. In some embodiments, the subbands may be bundled together, while in other embodiments, the subbands may be bundled into multiple groups based on their correlation, each group having a different subband bundling size. This may allow the network entity to flexibly reduce channel state information feedback overhead while maintaining satisfactory system performance. In some embodiments, the network entity may be able to plan for high feedback overhead in order to achieve better performance. The correlation of the subbands may be known by long-term knowledge or any other mechanism at the user equipment or network entity. In other words, for example, the network operator and/or provider may pre-configure the user equipment or network entity with the correlation of the subbands.
In some embodiments, the number of subbands may be represented by N, and the network entity may configure the subband bundling size(s) and the exact subband index to be bundled together during channel state information calculation. The channel state information feedback or report may have a bit field that is used by the user equipment to dynamically pass the bundled subbands to the network entity. Subband bundling may be combined with other PCA rules to further compress the channel state information to reduce the channel state information payload.
As shown in fig. 1, there may be ten subbands 110. The network entity and/or the user equipment may be configured with a subband configuration 120 and the user equipment may inform the network entity of the configuration. The subband configuration 120 may be any of four examples illustrated in the table. In example 1, subbands 1 and 2, subbands 3, 4, 5 and 6, and subbands 9 and 10 are bundled together, respectively, while subbands 7 and 8 remain independent. In example 2, subbands 1 and 2, subbands 3 and 4, subbands 5 and 6, subbands 7 and 8, and subbands 9 and 10, respectively, are bundled together. In example 3, subbands 1, 2, 3, 4, 5, and 6, subbands 7 and 8, and subbands 9 and 10, respectively, are bundled together. In example 4, subbands 1, 2, 5, and 6, subbands 3 and 4, and subbands 7, 8, 9, and 10 are bundled together, respectively.
Some embodiments may utilize unequal bit allocations for the singular vectors. For example, in some PCA schemes, the following formula may be used:represents bit allocation, where p=min (M, N) and σ 1 ＞σ 2 ＞…＞σ P . For some users, a good compression of the Channel Frequency Response (CFR) may be obtained and the first singular vector may carry most of the information. In such an embodiment, the first and second substrates,k of the P singular vectors may be fed back from the user equipment while the remaining P-K singular vectors may be discarded.
FIG. 2 illustrates an example of a graph in accordance with certain embodiments. In particular, fig. 2 illustrates the ratio of energy for CFR aggregation (CFR concentration) in the first singular vectors for user 1, user 2, and user 3, each user having two receiver antennas. The performance of user 1 receiver antenna 1210, user 1 receiver antenna 2 220, user 2 receiver antenna 1 230, user 2 receiver antenna 2 221, user 3 receiver antenna 1 230, and user 3 receiver antenna 2 231 are all shown in fig. 2. For example, user 2 has 87.5% of the CFR energy concentrated in the first singular vectors (left and right). In some embodiments, the first singular vector may be assigned to user 2 with a high quantization resolution.
In some embodiments, the user equipment may utilize a threshold T 1 To determine whether the first singular vector can be assigned a higher quantization resolution. For example, the first singular vector may be included within the transformation matrix. In some embodiments, the singular vectors, the principal components, or the feature vectors may all have similar meanings. If a certain measurement index is equal to or higher than T 1 The singular vectors may be assigned a higher quantization resolution. On the other hand, if the measurement index is lower than T 1 The singular vectors may be assigned a lower quantization resolution.
In some embodiments, it may be beneficial to assign different feedback overheads to different UEs, such that different UE assignments may be assigned different numbers of principal components K. Based on another threshold T 2 The UE may determine the desired value of K and may feed back or transmit the desired value to the network entity. For example, in fig. 2, user 1 may be assigned more singular vectors than user 3. As shown in fig. 2, the energy of CFR aggregation in the first singular vector may be higher in user 3 than in user 1.
As discussed above, the left singular vector may be a eigenvector of the frequency correlation matrixWhile the right singular vector may be the eigenvector of the spatial correlation matrix +. >The compression quality of the left singular vector may be different from the right singular vector depending on at least one of the frequency correlation and/or the spatial correlation. Thus, different quantization resolutions can be assigned to the left singular vector and the right singular vector.
Comprising a transformed matrix Φ transformation matrixBoth channel state information reports may have reduced feedback coefficients. For example, some embodiments may use a single set of transformation matrices>Rather than having to report multiple groups to different layers. Thus, some embodiments may save the channel state information payload by at least K M× (RI-1) coefficients.
Fig. 3 illustrates an example of a table in accordance with certain embodiments. In particular, FIG. 3 illustrates a transform matrix with channel state information scheme 310320. A transformed matrix Φ330 and a table of total payloads 340. The table shows two different channel state information schemes, one scheme according to some embodiments, and another scheme to compare XYZ channel state information. Transformation matrix->320 and transformed matrix Φ330 may include the strongest coefficients, magnitude, and phase. As shown in fig. 3, the payload of the transformed matrix Φ330 of the XYZ channel state information scheme may be similar to some embodiments of the channel state information scheme. However, transform matrix- >320 may be lower resulting in a total payload of 616 for the XYZ channel state information scheme and 398 for some embodiments described above.
The table of fig. 3 can assume that the number of antenna ports is m=16, the number of subbands is n=9, the number of layers is ri=2, and the number of principal components is k=2. Transformation matrixMay have 4-bit phase quantization and 3-bit amplitude quantization, and the transformed matrix Φ may have 3-bit phase quantization and 2-bit amplitude quantization. When performing a method or process according to some embodiments, the total payload of the XYZ channel state information scheme may be reduced by 35%.
FIG. 4 illustrates an example of an ABC scheme, while FIG. 5 illustrates an example of a table according to some embodiments. In particular, fig. 4 illustrates a payload according to an ABC scheme, while fig. 5 illustrates a payload according to some embodiments. The table shown in fig. 4 may include a number of subbands 410, beam selection 420, a non-zero amplitude indication 430, strongest coefficients 440, wideband (WB) amplitude 450, subband (SB) amplitude 460, SB phase 470, and total payload 480.
Fig. 4 can assume that the number of antenna ports is m=16, (N 1 ，N 2 ) = (4, 2) and oversampling (O 1 ，O 2 ) = (4, 4), while the number of beams is l=4. Thus, it is possible to useBits to signal beam selection. The number of subbands shown in fig. 4 may be set to n=9, 13 or 20, and the number of layers may be 2, ri=2. Based on simulation statistics, the average of the non-zero WB magnitudes for each layer may be 6. The quantization bits of WB amplitude, SB differential amplitude and SB phase may be 3, 1, 3, respectively. The subband numbers 9, 13 and 20 may have total payloads of 425, 585 and 865, respectively.
On the other hand, FIG. 5 illustratesThe total payload according to some embodiments is shown. The embodiment of FIG. 5 illustrates a subband number 510, a transform matrix520. Transformed matrix Φ530 and total payload 540. In fig. 5, the number of antenna ports may be m=16, the number of subbands may be n=9, 13 or 20, the number of layers may be ri=2, and the number of principal components may be k=2. Transformation matrix->May have 4-bit phase quantization and 3-bit amplitude quantization, while the transformed matrix Φ may have 3-bit phase quantization and 2-bit amplitude quantization. According to some embodiments, the number of subbands of 9, 13, and 20 may have a total payload of 398, 478, and 620, respectively, which represents a significant reduction in overhead for channel state information feedback.
Fig. 6 illustrates a diagram in accordance with certain embodiments. In particular, FIG. 6 illustrates a payload 610 of ABC channel state information and a payload 620 of channel state information according to certain embodiments. Payload channel state information 610 may represent the payload shown in fig. 4, and payload channel state information 620 may represent the payload shown in fig. 5. As shown in fig. 6, the above embodiment may reduce the payload by 6% for 9 subbands, 18% for 13 subbands, and 28% for 20 subbands.
Fig. 7 illustrates an example of a method according to some embodiments. In particular, fig. 7 illustrates a method performed by a user equipment. In step 710, the user equipment may receive one or more higher layer parameters statically or semi-statically. The one or more higher layer parameters may include at least one of: the number of components and quantization configuration parameters. In other words, the quantized sets of amplitude and phase and the quantized bits may be configured for the transformed matrix and the transformed matrix, respectively. For example, the transformed matrix may have 4-bit phase quantization and 3-bit amplitude quantization, and the transformed matrix may have 3-bit phase quantization and 2-bit amplitude quantization. The components may be, for example, one or more principal components. The user equipment may then use one or more higher layer parameters to determine channel state information feedback. In step 720, the user device may determine a single set of transformation matrices. A single set of transformation matrices may be used for different layers. In some embodiments, one or more components of the transformation matrix may be common to different layers.
In some embodiments, the user device may determine an index for a component of the transformation matrix. The index of the transformation matrix may represent the strongest coefficient for, or each of, the one or more components, and the index may be included in the channel state information report. The strongest coefficient may be determined as a single index that considers all components, or may be selected as multiple indexes that each represent a different component. The user equipment may also determine the amplitude and phase of coefficients other than the strongest coefficients for one or more components, or each of the one or more components, included in the transformation matrix.
In step 730, the user device may assign a higher quantization to the components of the transformation matrix when the threshold is met. In step 740, the user device may determine a transformed matrix in one or more layers. The transformed matrix in each of the plurality of layers may include separate quantized coefficients. The channel state information report may include individual quantized coefficients of the transformed matrix. In step 750, the user equipment may select a group of subbands related to channel state information reporting. An example of a selected group of subbands is illustrated in fig. 1.
In step 760, the user equipment may construct a channel state information report comprising a single set of transformation matrices. The channel state information report may also include individual quantized coefficients of the transformed matrix. In step 770, the user equipment may transmit a channel state information report to the network entity. The channel state information report may be transmitted on a physical uplink shared channel.
Fig. 8 illustrates an example of a method according to some embodiments. In particular, fig. 8 illustrates a method performed by a network entity, such as a gNB. In step 810, the network entity may statically or semi-statically determine one or more higher layer parameters. The one or more higher layer parameters may include at least one of: the number of components and quantization configuration parameters. In step 820, the network entity may transmit one or more higher layer parameters to the user equipment.
In step 830, the network entity may receive a single set of transformation matrices from the user device. In some embodiments, the network entity may receive an index for one or more components of the transformation matrix from the user device. The index of the transformation matrix may represent the strongest coefficient for the component. In some embodiments, the index of one or more components may be received as part of a single set of transformation matrices. The feedback term of the transformation matrix may consist of the index of the strongest coefficient of each component and the amplitude and phase of the coefficients other than the strongest coefficient for each component. A single set of transformation matrices may be used for different layers. The components of the transformation matrix may be common to the different layers. In step 830, the network entity may alternatively or additionally receive individual quantization coefficients for one or more layers of the transformed matrix. The feedback term of the transformed matrix may consist of the index of the strongest coefficient for each layer and the amplitude and phase of the coefficients other than the strongest coefficient for each layer.
In step 840, the network entity may receive a report related to subband bundling from the user device. In step 850, the network entity may construct channel state information. Channel state information may be constructed based on at least one of the transformed matrix, and/or the single set of reports of the subband bundling.
Fig. 9 illustrates a system according to some embodiments. It is to be understood that each of the signals or blocks of fig. 1-8 may be implemented in various ways, such as hardware, software, firmware, one or more processors and/or circuitry, or combinations thereof. In one embodiment, the system may include several devices, such as, for example, a network entity 920 or a User Equipment (UE) 910. A system may include more than one UE 910 and more than one network entity 920. The network entity 920 may be a network node, a base station, an access point, an access node, a gNB, an eNodeB (eNB), a server, a host, or any other network entity that may communicate with a UE.
Each of these devices may include at least one processor or control unit or module, indicated at 911 and 921, respectively. At least one memory may be provided in each device, indicated as 912 and 922, respectively. The memory may include computer program instructions or computer code embodied therein. One or more transceivers 913 and 923 may be provided and each device may also include an antenna, illustrated as 914 and 924, respectively. Although only one antenna is shown per device, many antennas and multiple antenna elements may be provided per device. For example, other configurations of these devices may be provided. For example, network entity 920 and UE 910 may additionally be configured for wired communication in addition to wireless communication, and in such a case antennas 914 and 924 may illustrate any form of communication hardware and are not limited to antennas.
Transceivers 913 and 923 may each independently be a transmitter, a receiver, or both a transmitter and a receiver, or may be units or devices that may be configured for transmission and reception. The transmitter and/or receiver (in terms of radio parts) may also be implemented as a remote radio head, which is not located in the device itself, but for example in a mast. Operations and functionality may be performed in a flexible manner in different entities such as nodes, hosts, or servers. In other words, the division of labor may vary from case to case. One possible use is for a network entity to deliver local content. One or more of the functionalities may also be implemented as virtual application(s) in software that may run on a server.
The user equipment or UE 910 may be a Mobile Station (MS) such as a mobile phone or a smart phone or a multimedia device, an IoT cellular device, a computer such as a tablet computer provided with wireless communication capabilities or a Personal Digital Assistant (PDA) provided with wireless communication capabilities, a portable media player, a digital camera, a camcorder, a navigation unit provided with wireless communication capabilities, or any combination thereof. In other embodiments, the user device may be replaced by a machine communication device that does not require any human interaction, such as a sensor, meter, or robot.
In some embodiments, an apparatus, such as a user equipment or a network entity, may include means for performing the embodiments described above with respect to fig. 1-8. In some embodiments, at least one memory including computer program code may be configured to, with at least one processor, cause the apparatus at least to perform any of the processes described herein.
The processors 911 and 921 may be embodied by any computing or data processing device, such as a Central Processing Unit (CPU), digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), programmable Logic Device (PLD), field Programmable Gate Array (FPGA), digital enhancement circuit, or analog device, or a combination thereof. A processor may be implemented as a single controller or as multiple controllers or processors.
For firmware or software, the implementation may include modules or units (e.g., procedures, functions, etc.) of at least one chipset. Memories 912 and 922 may independently be any suitable storage device such as a non-transitory computer readable medium. A Hard Disk Drive (HDD), random Access Memory (RAM), flash memory, or other suitable memory may be used. The memory may be combined with the processor on a single integrated circuit or may be separate therefrom. Furthermore, the computer program instructions may be stored in a memory and they may be processed by a processor, and may be in any suitable form of computer program code, for example, a compiled or interpreted computer program written in any suitable programming language. The memory or data storage entity is typically internal, but may also be external or a combination thereof, such as where additional memory capacity is obtained from a service provider. The memory may be fixed or removable.
The memory and computer program instructions may be configured, with a processor for a particular device, to cause a hardware apparatus, such as the network entity 920 or the UE 910, to perform any of the processes described above (see, e.g., fig. 1-8). Thus, in certain embodiments, a non-transitory computer-readable medium may be encoded with computer instructions or one or more computer programs (such as added or updated software routines, applets, or macros) that, when executed in hardware, may perform a process, such as one of the processes described herein. The computer program may be encoded by a programming language, which may be a high-level programming language such as objected-C, C, C ++, c#, java, etc., or may be a low-level programming language, such as a machine language or assembler. Alternatively, some embodiments may be implemented entirely in hardware.
In some embodiments, an apparatus may include circuitry configured to perform any of the processes or functions illustrated in fig. 1-8. In one example, the circuitry may be a purely hardware circuit implementation, such as analog and/or digital circuitry. In another example, the circuitry may be a combination of hardware circuitry and software, such as a combination of: analog and/or digital hardware circuit(s) with software or firmware, and/or any portion of hardware processor(s) with software, including digital signal processor(s), software, and at least one memory, which work together to cause the apparatus to perform various processes or functions. In yet another example, the circuitry may be hardware circuit(s) and/or processor(s), such as microprocessor(s) or portion of microprocessor(s), including software such as operating firmware. Software in the circuitry may not be present when hardware operation is not required.
The above embodiments may relate to computer-related techniques that provide significant improvements to the functionality of a network and/or the functionality of a network entity within a network or a user device in communication with a network. For example, the above embodiments may help reduce the payload for transmitting channel state information or for channel state information feedback. In other words, the channel state information may help reduce channel state information feedback overhead. Thus, such embodiments may help reduce network resource usage and/or resource usage at the user device.
The particular features, structures, or characteristics of some embodiments described throughout the specification may be combined in any suitable manner in one or more embodiments. For example, the use of the phrases "certain embodiments," "some embodiments," "other embodiments," or other similar language throughout this specification refers to the fact that: the particular features, structures, or characteristics described in connection with this embodiment may be included in at least one embodiment of the invention. Thus, appearances of the phrases "in certain embodiments," "in some embodiments," "in other embodiments," or other similar language throughout this specification do not necessarily refer to the same group of embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Those of ordinary skill in the art will readily appreciate that the example embodiments of the invention discussed above may be practiced with steps in a different order and/or with hardware elements in a different configuration than that disclosed. Thus, while examples of the present invention have been described based upon these preferred embodiments, it would be apparent to those of ordinary skill in the art that certain modifications, variations, and alternative constructions would be apparent without departing from the spirit and scope of the invention. Although the above embodiments refer to 5G NR, the above embodiments may also be applied to any other current or future 3GPP technology, such as LTE, LTE-advanced, ioT technology, fourth generation (4G) technology, or any non-3 GPP technology.
Partial vocabulary
CFR channel frequency response
CSI channel state information
LTE long term evolution
MIMO multiple input multiple output
MU-MIMO multi-user MIMO
NR new radio
PCA principal component analysis
PUSCH physical uplink shared channel
RRC radio resource control
SB sub-band
WB wideband
FDMA frequency division multiple Access
FFT fast Fourier transform
gNB 5G or NR base station
HARQ hybrid automatic repeat request
Auxiliary access to LAA permissions
LBT listen before talk
LTE long term evolution
MCS modulation and coding scheme
Claims (40)
1. An apparatus for communication, comprising:
at least one memory including computer program code; and
at least one processor;
wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
determining a single set of transformation matrices based on a channel matrix, wherein the single set of transformation matrices includes one or more principal components and the one or more principal components are selected from feature vectors of the channel matrix, wherein the single set of transformation matrices is common to different layers;
constructing a channel state information report including the single set of the transformation matrix; and
transmitting the channel state information report comprising the single set of the transformation matrix to a network entity.
2. The apparatus of claim 1, wherein one or more components of the transformation matrix are common to the different layers.
3. The apparatus of claim 1, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
Determining transformed matrices in one or more layers, wherein the transformed matrices in the one or more layers comprise individual quantized coefficients, and wherein the channel state information report comprises the individual quantized coefficients of the transformed matrices in all the layers.
4. The apparatus of claim 1, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
receiving, statically or semi-statically, one or more higher layer parameters, wherein the one or more higher layer parameters comprise at least one of: the number of components of the transformation matrix or a quantization configuration parameter.
5. The apparatus of claim 1, wherein the channel state information report is transmitted on a physical uplink shared channel.
6. The apparatus of claim 1, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
an index for a component of the transform matrix is determined, wherein the index of the transform matrix represents a strongest coefficient for the component, and wherein the index is included in the channel state information report.
7. The apparatus of claim 1, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
the magnitude and phase of coefficients other than the strongest coefficients are determined for one or more components included in the transformation matrix.
8. The apparatus of claim 1, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
a set of subbands associated with the channel state information report is selected.
9. The apparatus of claim 2, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
when a threshold is met, a higher quantization is assigned to the components of the transformation matrix.
10. The apparatus of claim 2, wherein the one or more components comprise one or more principal components.
11. An apparatus for communication, comprising:
at least one memory including computer program code; and
at least one processor;
Wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
receiving a single set of transformation matrices from a user device, wherein the single set of transformation matrices is common to different layers, wherein the single set of transformation matrices is determined based on a channel matrix, wherein the single set of transformation matrices comprises one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix; and
channel state information is constructed based on the single set of the transformation matrices.
12. The apparatus of claim 11, wherein one or more components of the transformation matrix are common to the different layers.
13. The apparatus of claim 11, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
individual quantized coefficients are received for one or more layers of the transformed matrix.
14. The apparatus of claim 13, wherein the single set of the transformation matrices and the transformed matrices are included in a channel state information report received from the user equipment.
15. The apparatus of claim 14, wherein the channel state information report is received on a physical uplink shared channel.
16. The apparatus of claim 11, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
a subband bundling report is received from the user device, wherein the subband bundling report is used to construct the channel state information.
17. The apparatus of claim 12, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
determining, statically or semi-statically, one or more higher layer parameters, wherein the one or more higher layer parameters comprise at least one of: the number of the one or more components and a quantization configuration parameter; and
the one or more higher layer parameters are transmitted to the user equipment.
18. The apparatus of claim 12, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to:
An index for the one or more components of the transformation matrix is received from the user device, wherein the index of the transformation matrix represents the strongest coefficient for the components.
19. A method of communication, comprising:
determining, at a user device, a single set of transformation matrices based on a channel matrix, wherein the single set of transformation matrices includes one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix, wherein the single set of transformation matrices is common to different layers;
constructing, at the user equipment, a channel state information report comprising the single set of the transformation matrices; and
transmitting the channel state information report from the user equipment to a network entity, the channel state information report comprising the single set of the transformation matrices.
20. The method of claim 19, wherein one or more components of the transformation matrix are common to the different layers.
21. The method of claim 19, further comprising:
determining transformed matrices in one or more layers, wherein the transformed matrices in the one or more layers comprise individual quantized coefficients, and wherein the channel state information report comprises the individual quantized coefficients of the transformed matrices in all the layers.
22. The method of claim 19, further comprising:
receiving, statically or semi-statically, one or more higher layer parameters, wherein the one or more higher layer parameters comprise at least one of: the number of components of the transformation matrix or a quantization configuration parameter.
23. The method of claim 19, wherein the channel state information report is transmitted on a physical uplink shared channel.
24. The method of claim 19, further comprising:
an index for a component of the transform matrix is determined, wherein the index of the transform matrix represents a strongest coefficient for the component, and wherein the index is included in the channel state information report.
25. The method of claim 19, further comprising:
the magnitude and phase of coefficients other than the strongest coefficients are determined for one or more components included in the transformation matrix.
26. The method of claim 19, further comprising:
a set of subbands associated with the channel state information report is selected.
27. The method of claim 20, further comprising:
when a threshold is met, a higher quantization is assigned to the components of the transformation matrix.
28. The method of claim 20, wherein the one or more components comprise one or more principal components.
29. An apparatus for communication, comprising:
means for determining a single set of transformation matrices based on a channel matrix, wherein the single set of transformation matrices comprises one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix, wherein the single set of transformation matrices is common to different layers;
means for constructing a channel state information report comprising said single set of said transformation matrices; and
means for transmitting the channel state information report comprising the single set of the transformation matrices to a network entity.
30. A computer readable storage medium having stored thereon program code configured to, when executed, cause an apparatus to:
determining, at a user device, a single set of transformation matrices based on a channel matrix, wherein the single set of transformation matrices includes one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix, wherein the single set of transformation matrices is common to different layers;
Constructing, at the user equipment, a channel state information report comprising the single set of the transformation matrices; and
transmitting the channel state information report from the user equipment to a network entity, the channel state information comprising the single set of the transformation matrices.
31. A method of communication, comprising:
receiving a single set of transformation matrices from a user device, wherein the single set of transformation matrices is common to different layers, wherein the single set of transformation matrices is determined based on a channel matrix, wherein the single set of transformation matrices comprises one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix; and
channel state information is constructed based on the single set of the transformation matrices.
32. The method of claim 31, wherein one or more components of the transformation matrix are common to the different layers.
33. The method of claim 31, further comprising:
individual quantized coefficients are received for one or more layers of the transformed matrix.
34. The method of claim 33, wherein the transformed matrix and the single set of transform matrices are included in a channel state information report received from the user equipment.
35. The method of claim 34, wherein the channel state information report is received on a physical uplink shared channel.
36. The method of claim 31, further comprising:
a subband bundling report is received from the user device, wherein the subband bundling report is used to construct the channel state information.
37. The method of claim 32, further comprising:
determining, statically or semi-statically, one or more higher layer parameters, wherein the one or more higher layer parameters comprise at least one of: the number of the one or more components and a quantization configuration parameter; and
the one or more higher layer parameters are transmitted to the user equipment.
38. The method of claim 32, further comprising:
an index for the one or more components of the transformation matrix is received from the user device, wherein the index of the transformation matrix represents the strongest coefficient for the components.
39. An apparatus for communication, comprising:
means for receiving a single set of transformation matrices from a user device, wherein the single set of transformation matrices is common to different layers, wherein the single set of transformation matrices is determined based on a channel matrix, wherein the single set of transformation matrices comprises one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix; and
Means for constructing channel state information based on the single set of the transformation matrices.
40. A computer readable storage medium having stored thereon program code configured to, when executed, cause an apparatus to:
receiving a single set of transformation matrices from a user device, wherein the single set of transformation matrices is common to different layers, wherein the single set of transformation matrices is determined based on a channel matrix, wherein the single set of transformation matrices comprises one or more principal components and the one or more principal components are selected from eigenvectors of the channel matrix; and
channel state information is constructed based on the single set of the transformation matrices.
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| CN117097477B (en) * | 2023-10-20 | 2024-04-05 | 网络通信与安全紫金山实验室 | Channel key generation method, device, communication equipment and storage medium |
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