CN112236961B - Channel state information feedback - Google Patents

Abstract

Various communication systems can 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 a single set of transformation matrices at a user device. A single set of transformation matrices can be used for different layers. The method may further include constructing, at the user equipment, a channel state information report including the single set of transformation matrices. Additionally, the method may include transmitting a channel state information report from the user equipment to the network entity, the channel state information report comprising a single set of transformation matrices.

Description

Channel status information feedback

Technical field

Various communication systems can benefit from channel state information feedback. For example, it may be helpful to use spatial compression to improve channel state information feedback.

Background technique

In 3rd Generation Partnership Project (3GPP) technologies such as Long Term Evolution (LTE), fifth generation (5G) or new radio (NR) technologies, multiple input multiple output (MIMO) can be utilized to help facilitate signaling . MIMO is used to increase the overall bit rate by transmitting two or more different data streams on two or more different antennas - using the same resources in both frequency and time, separated only by the use of different reference signals - — to be received by two more antennas. In NR technology, the number of antennas and/or data streams will increase, thereby simultaneously increasing the importance of MIMO.

To allow the use of MIMO in NR technology, channel state information feedback and compression schemes are used. For example, time domain, frequency domain and spatial domain compression are used to compress signal transmission. This may allow multiple signals to be transmitted on multiple antennas using the same frequency and/or time resources.

Contents of the invention

According to certain embodiments, an apparatus may include at least one memory including computer program code and at least one processor. At least one memory and computer program code may be configured together with at least one processor to cause the apparatus to determine at least a single set of transformation matrices. A single set of transformation matrices can be used for different layers. The at least one memory and computer program code may also be configured with the at least one processor to cause the apparatus to construct at least a channel state information report that includes a single set of transformation matrices. Additionally, the at least one memory and computer program code may also be configured together with the at least one processor to cause the apparatus to transmit at least a channel state information report including a single set of transformation matrices to the network entity.

According to some embodiments, a method may include determining a single set of transformation matrices at a user device. A single set of transformation matrices can be used for different layers. The method may further include constructing, at the user equipment, a channel state information report that includes a single set of transformation matrices. Additionally, the method may include transmitting a channel state information report from the user equipment to the network entity, the channel state information report comprising a single set of transformation matrices.

In certain embodiments, an apparatus may include means for determining a single set of transformation matrices. A single set of transformation matrices can be used for different layers. The apparatus may further comprise means for constructing a channel state information report comprising a single set of transformation matrices. Additionally, the apparatus may comprise means for transmitting a channel state information report comprising a single set of transformation matrices to the 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 a single set of transformation matrices at the user device. A single set of transformation matrices can be used for different layers. The process may also include constructing, at the user equipment, a channel state information report that includes a single set of transformation matrices. Additionally, the process may include transmitting a channel state information report from the user equipment to the network entity, the channel state information including a single set including a transformation matrix.

According to certain other embodiments, a computer program product may encode instructions for performing a process. The process may include determining a single set of transformation matrices at the user device. A single set of transformation matrices can be used for different layers. The process may also include constructing, at the user equipment, a channel state information report that includes a single set of transformation matrices. Additionally, the process may include transmitting a channel state information report from the user equipment to the network entity, the channel state information report including a single set of transformation matrices.

According to certain embodiments, an apparatus may include circuitry for determining a single set of transformation matrices. A single set of transformation matrices can be used for different layers. The apparatus may also include circuitry for constructing a channel state information report that includes a single set of transformation matrices. Additionally, the apparatus may include circuitry for transmitting a channel state information report including a single set of transformation matrices from the user equipment to the network entity.

According to some embodiments, an apparatus may include at least one memory including computer program code and at least one processor. At least one memory and computer program code may be configured with at least one processor to cause the apparatus to receive at least a single set of transformation matrices from a user device. A single set of transformation matrices is used for different layers. The at least one memory and computer program code may also be configured with the at least one processor to cause the apparatus to construct channel state information based on at least 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 equipment. A single set of transformation matrices can be used for different layers. The method may also include constructing the channel state information based on a single set of transformation matrices at the network entity.

In certain embodiments, an apparatus may include means for receiving a single set of transformation matrices from a user equipment. A single set of transformation matrices can be used for different layers. The method may also include means for constructing channel state information based on a 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 the network entity, a single set of transformation matrices from the user equipment. A single set of transformation matrices can be used for different layers. The process may also include constructing channel state information at the network entity based on a 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 the network entity, a single set of transformation matrices from the user equipment. A single set of transformation matrices can be used for different layers. The process may also include constructing channel state information at the network entity based on a single set of transformation matrices.

According to certain embodiments, an apparatus may include circuitry for receiving a single set of transformation matrices from a user equipment. A single set of transformation matrices can be used for different layers. The apparatus may also include circuitry for constructing channel state information based on the single set of transformation matrices.

Description of the drawings

For a proper understanding of example embodiments of the present invention, reference should be made to the accompanying drawings, in which:

Figure 1 illustrates an example of a table in accordance with certain embodiments.

Figure 2 illustrates an example of a graph in accordance with certain embodiments.

Figure 3 illustrates an example of a table in accordance with certain embodiments.

Figure 4 illustrates an example of a table according to the ABC scheme.

Figure 5 illustrates an example of a table in accordance with certain embodiments.

Figure 6 illustrates an example of a graph in accordance with certain embodiments.

Figure 7 illustrates an example of a method in accordance with certain embodiments.

Figure 8 illustrates an example of a method in accordance with certain embodiments.

Figure 9 illustrates an example of a system in accordance with certain embodiments.

Detailed ways

Certain embodiments allow overhead to be reduced by using enhanced channel state information feedback based on principal component analysis (PCA). PCA can be a statistical process that uses orthogonal transformations to transform a set of data points into a set of uncorrelated linear variables, called principal components. The first principal component of PCA can have the maximum possible variance, and each subsequent component in turn can have the maximum possible variance subject to the constraint that it is orthogonal to the previous component. In NR technology, PCA can utilize special channel compression technology to improve the accuracy of channel state information while reducing feedback overhead.

As discussed above, PCA can be a statistical procedure that uses an orthogonal transformation Q to transform the correlated variables of X into the uncorrelated variables of Φ. In other words, PCA can be expressed by the following formula: Φ=QX. The rows of Q can be the principal components of X. In some embodiments, channel compression and feedback may be used. In some embodiments, a _channel matrix X of _M ). 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 can 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. 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 can be formed by eigenvectors, and Σ can be composed of eigenvalues along the main diagonal. According to PCA, the transformation matrix/> K principal components may be included, which may be selected from the top K dominant eigenvectors of R _x with the largest K eigenvalues. You can use the following formula:/> to calculate the transformed matrix Φ.

The user device can quantify and feedback the transformation matrix and the transformed matrix/> One or more of the coefficients. Feedback of one or more coefficients may mean transmitting the coefficients from the user equipment to a network entity, such as a 5G or NR NodeB (gNB). In other words, feedback of the transformation matrix can mean that all coefficients of all components should be quantized and reported to the network entity. Quantization and feedback can be divided into two parts, one for the index of the strongest coefficient of one or more components, and another for the coefficients of all but the strongest coefficient or components. In some embodiments, the matrix/> M x K coefficients may be included, which are common to different layers. The matrix Φ may include K x N coefficients for each layer. The total number of coefficients for feedback can be expressed as follows: (K×M)+(K×N×RI), assuming rank RI. Therefore, in some embodiments, only a single set of transformation matrices may be used/> Instead of having to use multiple collections for different layers. Doing so reduces the amount of network resources, providing significant advantages to the network as well as the user device itself. For example, using only a single collection of transformation matrices/> The channel state information payload can be reduced by K×M×(RI-1) coefficients.

Therefore, certain embodiments may provide channel state information feedback transmitted from the user equipment to a network entity such as a 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 a channel state information report may include determining at least one of the following: a transformation matrix or transformed matrix/> Some embodiments may also utilize higher layer parameter configuration. For example, Radio Resource Control (RRC) may be used to configure parameters at the user equipment. Higher level parameter configuration can be used to determine the transformation matrix/> or transformed matrix/> a part of.

transformation matrix K principal components common to different layers may be included. Using K principal components that are common to different layers allows using only a single set of transformation matrices/> Rather than having to use multiple collections for different layers. As discussed above, only a single set of transformation matrices are used/> The channel state information payload can be reduced by K×M×(RI-1) coefficients.

For each principal component, the M coefficients can be quantized individually with respect to amplitude and phase. In order to streamline the channel state information payload, the strongest coefficient can be first selected from M coefficients, and the following formula can be used: to quantify the index of the strongest coefficient. The strongest coefficient can have the largest amplitude value. The other (M-1) coefficients of the principal component can be divided by the strongest coefficient and then individually quantized with respect to amplitude and phase. In some embodiments, for each principal component, a transformation matrix may be reported from the user equipment to the network entity/> The index of the strongest coefficient in and the amplitude/phase values of the other (M-1) coefficients. This report may be included as part of the channel status information report. The network entity may be a gNB, for example. In some embodiments, this reporting may occur on the Physical Uplink Shared Channel (PUSCH).

Therefore, the user equipment can determine the target value included in the transformation matrix The index of each principal component in . The principal components of the transformation matrix can be common to different layers. This index can represent the strongest coefficient for each principal component included in the transformation matrix, and can use the following formula: /> And be calculated. This index may be reported by the user device to the network entity.

As discussed above, construction of the channel state information report may include determining a transformation matrix or transformed matrix/> at least one of them. Transformed matrix/> There can be separate quantized coefficients for each layer. In each layer, the strongest coefficient can be first selected from K × N coefficients, and the following formula can be used: Quantize the coefficient of the strongest coefficient. The other (K×N-1) coefficients of the transformed matrix in this layer can be divided by the strongest coefficient and then quantized individually 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 (K×N-1) coefficients may be reported from the user equipment. This report may be included as part of the channel status information report. For example, the index may be reported on the physical uplink shared channel from the user equipment to a network entity such as a 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 can represent the strongest coefficient in each layer.

Channel state information feedback may include higher layer parameter configuration. In other words, some higher layer parameters can be configured statically or semi-statically. The network entity can 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 K of principal components. The quantization set and quantization bits for amplitude and phase can be specified by the network entity separately for the transformation matrix and the transformed matrix Φ to configure.

In some embodiments, channel state information may be constructed or reconstructed by a network entity using received information included in a channel state information report. The report may include, for example, a single set of transformation matrices, and one or more sets of transformed matrices. Network entities can be based on transformation matrices that are included in and/or the information in the transformed matrix Φ to construct channel state information. Utilize/> The channel state matrix can be recovered on the network entity side (e.g., gNB)/>

Compared with another channel state information method, using the transformation matrix The above embodiments of at least one of the transformed matrix Φ and/or higher layer parameter configuration can help reduce channel state information payload by 35%. In addition, compared with other channel state information methods, the channel state information feedback overhead can be reduced by 6% for 9 subbands, 18% for 13 subbands, and 28% for 20 subbands. 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.

Figure 1 illustrates an example of a table in accordance with certain embodiments. In particular, Figure 1 illustrates an example of channel state information feedback utilizing subband bundling. In some embodiments where subbands are related, related subbands may be selected together as part of the channel state information feedback. In particular, the network entity may configure the user equipment as to which subbands are to be considered jointly or independently. In some embodiments where the selection of subband bundling is reported, for example, the subband bundling may be reported on the PUSCH along with channel state information feedback.

User equipment may perform bundling and feedback or transmit such information to the base station along with channel status information reports. In some embodiments, subbands may be bundled together, while in other embodiments, subbands may be bundled into multiple groups based on correlation of the subbands, each group having a different subband bundle size. This may allow network entities to flexibly reduce channel state information feedback overhead while maintaining satisfactory system performance. In some embodiments, network entities may be able to plan for high feedback overhead in order to obtain better performance. The correlation of subbands may be known through long-term knowledge or any other mechanism at the user equipment or network entity. In other words, for example, network operators and/or providers may pre-configure user equipment or network entities with correlations of subbands.

In some embodiments, the number of subbands may be represented by N, and the network entity may configure the bundle size(s) and precise subband index of the subband(s) to be bundled together during channel state information calculation. The channel state information feedback or report may have a bit field used by the user equipment to dynamically notify the network entity of the bundled subbands. Subband bundling can be combined with other PCA rules to further compress channel state information to reduce channel state information payload.

As shown in Figure 1, there may be ten sub-bands 110. The network entity and/or the user equipment may be configured with the subband configuration 120, and the user equipment may notify the network entity of the configuration. Subband configuration 120 may be any of the 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 respectively bundled together, 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 are bundled together respectively. In Example 3, subbands 1, 2, 3, 4, 5, and 6, subbands 7 and 8, and subbands 9 and 10 are bundled together respectively. In Example 4, subbands 1, 2, 5, and 6, subbands 3 and 4, and subbands 7, 8, 9, and 10 are bundled together respectively.

Certain embodiments may utilize unequal bit allocation for singular vectors. For example, in some PCA schemes, the following formula can be used: represents bit allocation, where P=min(M,N) and σ ₁ >σ ₂ >…>σ _P . For some users, good compression of the channel frequency response (CFR) can be obtained, and the first singular vector can carry most of the information. In such an embodiment, K of the P singular vectors may be fed back from the user equipment, while the remaining PK singular vectors may be discarded.

Figure 2 illustrates an example of a graph in accordance with certain embodiments. In particular, Figure 2 graphically illustrates the ratio of energy in the CFR concentration in the first singular vector 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 in is shown in Figure 2. For example, user 2 has 87.5% of the CFR energy concentrated in the first singular vector (left and right). In some embodiments, the first singular vector may be assigned to user 2 with high quantization resolution.

In some embodiments, the user equipment may utilize the threshold T ₁ to determine whether the first singular vector may be assigned a higher quantization resolution. For example, the first singular vector may be included within the transformation matrix. In some embodiments, singular vectors, principal components or eigenvectors may all have similar meanings. If a certain measurement index is equal to or higher than T ₁ , then the singular vectors can be assigned a higher quantization resolution. On the other hand, if the measurement index is lower than T ₁ , then the singular vectors can 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 a different number K of primary components. Based on another threshold T ₂ , the UE may determine the expected value of K and may feed back or transmit the expected value to the network entity. For example, in Figure 2, user 1 may be assigned more singular vectors than user 3. As shown in Figure 2, the energy accumulated by CFR in the first singular vector may be higher in user 3 than in user 1.

As discussed above, the left singular vector can be the eigenvector of the frequency correlation matrix The right singular vector can be the eigenvector of the spatial correlation matrix/> Depending on at least one of frequency dependence and/or spatial dependence, the compression quality of the left singular vector may be different from the right singular vector. Therefore, different quantization resolutions can be assigned to the left and right singular vectors.

Contains the transformed matrix Φ transformation matrix Both channel state information reports may have reduced feedback coefficients. For example, some embodiments may use a single set of transformation matrices/> Instead of having to report multiple groups to different layers. Therefore, some embodiments may save the channel state information payload by at least K×M×(RI-1) coefficients.

Figure 3 illustrates an example of a table in accordance with certain embodiments. Specifically, FIG. 3 illustrates a scheme 310 with channel state information, transformation matrix 320. Table of transformed matrix Φ 330 and total payload 340. This table shows two different channel state information schemes, one scheme according to certain embodiments, and another scheme comparing XYZ channel state information. Transformation matrix/> 320 and the transformed matrix Φ 330 may include the strongest coefficients, amplitude and phase. As shown in Figure 3, the payload of the transformed matrix Φ 330 of the XYZ channel state information scheme may be similar to certain embodiments of the channel state information scheme. However, the transformation matrix/> The payload of 320 may be lower, resulting in a total payload of 616 for the XYZ channel state information scheme, compared to 398 for some of the embodiments described above.

The table of Figure 3 may 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 matrix There may be 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 methods or processes according to certain embodiments, the total payload of the XYZ channel state information scheme may be reduced by 35%.

Figure 4 illustrates an example of an ABC scheme, and Figure 5 illustrates an example of a table according to certain embodiments. In particular, Figure 4 illustrates a payload according to the ABC scheme, while Figure 5 illustrates a payload according to certain embodiments. The table shown in Figure 4 may include number of subbands 410, beam selection 420, non-zero amplitude indication 430, strongest coefficient 440, wideband (WB) amplitude 450, subband (SB) amplitude 460, SB phase 470, and total validity Load 480.

Figure 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. Therefore, one can use bits to signal beam selection. The number of subbands shown in Figure 4 can be set to N=9, 13 or 20, while the number of layers can be 2, RI=2. According to simulation statistics, the average number of non-zero WB amplitudes can be 6 for each layer. The quantization bits of WB amplitude, SB differential amplitude and SB phase can be 3, 1, and 3 respectively. Subband numbers 9, 13 and 20 may have total payloads of 425, 585 and 865 respectively.

Figure 5, on the other hand, illustrates the total payload in accordance with certain embodiments. The embodiment diagram of FIG. 5 shows the number of subbands 510, the transformation matrix 520. Transformed matrix Φ 530 and total payload 540. In Figure 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 main components may be K=2. Transformation matrix/> There may be 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, subband numbers of 9, 13 and 20 may have a total payload of 398, 478 and 620 respectively, which represents a significant reduction in the overhead of channel state information feedback.

Figure 6 illustrates a diagram in accordance with certain embodiments. In particular, Figure 6 illustrates a payload 610 of ABC channel state information and a payload 620 of channel state information in accordance with 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 Figure 6, the above-described embodiment can reduce the payload by 6% for 9 subbands, 18% for 13 subbands, and 28% for 20 subbands.

Figure 7 illustrates an example of a method in accordance with certain embodiments. In particular, Figure 7 illustrates a method performed by a user device. 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 following: a number of components and a quantization configuration parameter. In other words, the quantization set and the quantization bits of the amplitude and phase may be configured for the transformation matrix and the transformed matrix, respectively. For example, the transformation 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. A component 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 can 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 equipment may determine an index for a component of the transformation matrix. The index of the transformation matrix may represent the strongest coefficient for one or more components, or for each component of the one or more components, and the index may be included in a channel state information report. The strongest coefficient may be determined as a single index taking into account all components, or may be selected as multiple indices each representing different components. The user equipment may also determine the amplitude and phase of coefficients other than the strongest coefficient for one or more components, or for each component of the one or more components, included in the transformation matrix.

In step 730, when the threshold is met, the user equipment may assign higher quantization to the components of the transformation matrix. In step 740, the user equipment may determine transformed matrices 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 relevant to channel state information reporting. An example of selected groups of subbands is illustrated in Figure 1.

In step 760, the user equipment may construct a channel state information report including 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 the channel status information report to the network entity. Channel status information reports may be transmitted on the physical uplink shared channel.

Figure 8 illustrates an example of a method in accordance with certain embodiments. In particular, Figure 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: a number of components and a quantization configuration parameter. 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 equipment. In some embodiments, the network entity may receive an index to one or more components of the transformation matrix from the user equipment. The index of the transformation matrix can represent the strongest coefficient for a 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 can be used for different layers. Components of the transformation matrix can be common to different layers. In step 830, the network entity may alternatively or additionally receive individual quantized 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 coefficients other than the strongest coefficient for each layer.

In step 840, the network entity may receive reports related to subband bundling from the user equipment. In step 850, the network entity may construct channel state information. The channel state information may be constructed based on at least one of a transformation matrix, a transformed matrix, and/or a single set of reports of subband bundling.

Figure 9 illustrates a system in accordance with certain embodiments. It should be understood that each signal or block in FIGS. 1-8 may be implemented by various means, such as hardware, software, firmware, one or more processors and/or circuitry, or a combination thereof. In one embodiment, the system may include several devices, such as, for example, a network entity 920 or a user equipment (UE) 910. The system may include more than one UE 910 and more than one network entity 920. Network entity 920 may be a network node, base station, access point, access node, gNB, eNodeB (eNB), server, host, or any other network entity that can communicate with the UE.

Each of these devices may include at least one processor or control unit or module, designated 911 and 921 respectively. At least one memory may be provided in each device, indicated as 912 and 922 respectively. Memory may include computer program instructions or computer code contained 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 each, 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 communications in addition to wireless communications, and in this case, antennas 914 and 924 may illustrate any form of communications hardware, not just antennas.

Transceivers 913 and 923 may each independently be a transmitter, a receiver, or both a transmitter and a receiver, or may be a unit or device configured for both transmission and reception. The transmitter and/or receiver (in terms of the radio part) can also be implemented as a remote radio head, which is not located in the device itself, but instead is located, for example, in a mast. Operations and functionality can be performed in a flexible manner in different entities such as nodes, hosts or servers. In other words, the division of labor may vary depending on the situation. One possible use is to enable network entities to deliver local content. One or more functionality may also be implemented as virtual application(s) in software that may run on the server.

The user equipment or UE 910 may be a mobile station (MS) such as a mobile phone or smartphone or a multimedia device, an IoT cellular device, a computer such as a tablet provided with wireless communication capabilities, or a person provided with wireless communication capabilities Digital assistant (PDA), portable media player, digital camera, camcorder, navigation unit providing wireless communication capabilities, or any combination thereof. In other embodiments, user devices may be replaced by machine communication devices that do not require any human interaction, such as sensors, meters, or robots.

In some embodiments, an apparatus, such as a user equipment or network entity, may include means for performing the embodiments described above with respect to Figures 1-8. In certain embodiments, at least one memory including computer program code may be configured to, together with at least one processor, cause the apparatus to perform at least any of the processes described herein.

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 Arrays (FPGAs), digital enhancement circuits, or comparable devices, or combinations thereof. A processor may be implemented as a single controller or as multiple controllers or processors.

For firmware or software, the implementation may include at least one module or unit of the chipset (eg, a process, a function, etc.). Memories 912 and 922 may independently be any suitable storage device, such as non-transitory computer-readable media. 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, computer program instructions may be stored in memory, and may be processed by the processor, as computer program code in any suitable form, e.g., a compiled or interpreted computer program written in any suitable programming language. The memory or data storage entity is typically internal, but may be external or a combination thereof, such as where additional memory capacity is obtained from a service provider. Storage can be fixed or removable.

Memory and computer program instructions may be configured using a processor for a particular device to cause a hardware device, such as network entity 920 or UE 910, to perform any of the processes described above (eg, see Figures 1-8). Accordingly, 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. Or one or more computer programs, when executed in hardware, may perform a process, such as one of the processes described herein. A computer program may be encoded in a programming language, which may be a high-level programming language such as Objective-C, C, C++, C#, Java, etc., or a low-level programming language such as machine language or assembler. Alternatively, some embodiments may be implemented entirely in hardware.

In certain embodiments, an apparatus may include circuitry configured to perform any of the processes or functions illustrated in Figures 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 (one or more) with software Any portion of a plurality of hardware processors (including digital signal processor(s)), software, and at least one memory that work together to cause an 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 microprocessor(s) part of the system, which includes software such as operating firmware. When hardware operation is not required, software in the circuit system may not exist.

The above embodiments may relate to computer-related technologies that provide significant improvements to the functionality of a network and/or the functionality of network entities within the network or user equipment communicating with the network. For example, the above embodiments can help reduce the payload for transmitting channel state information or for channel state information feedback. In other words, channel state information can help reduce channel state information feedback overhead. Accordingly, such embodiments may help reduce network resource usage and/or resource usage at the user device.

The features, structures, or characteristics of certain embodiments described throughout this specification may be combined in any suitable manner in one or more embodiments. For example, use of the phrase "certain embodiments," "some embodiments," "other embodiments," or other similar language throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with the embodiment may is included in at least one embodiment of the invention. Thus, throughout this specification, appearances of the phrases "in certain embodiments," "in some embodiments," "in other embodiments," or other similar language are not necessarily referring to the same group of embodiments, and the described The features, structures or characteristics of may be combined in any suitable manner in one or more embodiments.

Those of ordinary skill in the art will readily appreciate that example embodiments of the invention as discussed above may be practiced with steps in a different order and/or with hardware elements in different configurations than those disclosed. Accordingly, although examples of the invention have been described based on the preferred embodiments, it will be apparent to those skilled in the art that certain modifications, variations and alternative constructions will be made without departing from the spirit and scope of the invention. It is obvious. 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-3GPP technology.

partial glossary

CFR channel frequency response

CSI channel status 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 subband

WB Broadband

FDMA frequency division multiple access

FFT Fast Fourier Transform

gNB 5G or NR base station

HARQ hybrid automatic repeat request

Assisted Access Licensed by LAA

LBT pre-talk listening

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.