Method for channel information feedback by whitening information in mobile communication and apparatus therefor

Abstract

Various solutions for channel information feedback and whitening information with respect to user equipment and network devices in mobile communications are described herein. An apparatus may measure a reference signal (RS) from a network node to derive channel information. The apparatus may determine interference and noise information observed at its receiver. The apparatus may determine whitening information based on the interference and noise information. The apparatus may report the whitening information and the channel information to the network node.

Description

[0001] Cross-referencing This disclosure claims priority to U.S. Provisional Patent Application No. 63 / 580,398, filed on September 4, 2023, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0002] This disclosure generally relates to mobile communications, and more specifically, to channel information feedback and whitening information regarding user equipment (UE) and network devices in mobile communications. Background Technology

[0003] Unless otherwise stated herein, the methods described in this section are not prior art to the claims listed below, and are not recognized as prior art by virtue of being included in this section.

[0004] Channel State Information Reference Signal (CSI-RS) is a type of Reference signal (RS) used in the downlink (DL) direction in 5G NR, with the purpose of channel sounding and for measuring the characteristics of the wireless channel so that appropriate modulation, code rate, precoder, beamforming, etc. can be used. The UE will use these reference signals to measure the quality of the DL channel and report it in the uplink (UL) through a CSI report. The network node transmits CSI-RS to measure channel state information for mobility procedures, such as CSI-Reference Signal Receiving Power (RSRP), CSI-Reference Signal Receiving Quality (RSRQ), and CSI-Signal to Interference plus Noise Ratio (SINR). A specific instance of CSI-RS can be configured for time / frequency tracking and mobility measurements. CSI feedback is the method by which the UE indicates certain reports to the network to indicate channel parameters, for example, for dynamic scheduling purposes. CSI parameters are quantities related to the channel state. The UE reports CSI parameters as feedback to the network node (e.g., gNB). CSI feedback includes multiple parameters, such as Channel Quality Indicator (CQI), Precoding Matrix Indicator (PMI) with different codebook sets, and Rank Indicator (RI). CSI feedback can also include parameters to indicate the CSI-RS resource (or set of CSI-RS resources) based on which CQI, PMI, and RI are derived and reported. The UE uses CSI-RS to measure CSI feedback. After receiving the CSI parameters, the network node can schedule downlink data transmission accordingly (e.g., modulation scheme, code rate, number of transmission layers, and MIMO precoding).

[0005] In the current NR CSI framework, a UE feeds back a UE preferred precoder for CSI feedback. The current CSI reporting considers a single Transmission / Reception Point (TRP) - UE signal channel. Each UE reports a preferred precoder observed by the UE. The reported precoder can not reflect the true channel state and does not consider noise information and / or interference from other UE transmissions. This can be applicable for Single-User Multiple-Input Multiple-Output (SU-MIMO) scenarios where inter-user interference is not a major issue. However, this is not a preferred solution for Multiple-User Multiple-Input Multiple-Output (MU-MIMO) scenarios. The network node is not able to determine the appropriate precoder and modulation and coding scheme (MCS) and hence is not able to manage the noise and interference among multiple UEs. Although the network node can perform some procedures to make the signals among different UEs more orthogonal, these procedures can result in signal power loss and can degrade the signal performance.

[0006] Therefore, how to feed back the real / appropriate channel information and noise / interference information for channel and interference management becomes an important issue in newly developed wireless communication networks. Therefore, there is a need to provide appropriate solutions to perform CSI measurement and reporting. SUMMARY

[0007] The following summary is illustrative only and is not intended to be limiting in any way. In other words, the following summary is provided to introduce some concepts, aspects, benefits and advantages of the novel and non-obvious technology described herein. Selected implementations are described in further detail in the detailed description. As such, the following summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter in any way.

[0008] It is an object of the present disclosure to propose solutions or schemes to solve the above-mentioned problems related to channel information feedback and whitening information for user equipment and network apparatus in mobile communications.

[0009] In one aspect, a method can involve an apparatus measuring a reference signal from a network node to derive channel information. The method can also involve the apparatus determining interference and noise information observed at a receiver of the apparatus. The method can further involve the apparatus determining whitening information based on the interference and noise information. The method can further involve the apparatus reporting the whitening information and the channel information to the network node.

[0010] In one aspect, a method may involve a network node transmitting a reference signal to a UE. The method may also involve the network node receiving whitening information and channel information from the UE. The method may further involve the network node determining at least one of a precoder and a modulation and coding scheme based on the whitening information and the channel information. The method may further involve the network node performing downlink transmissions to the UE using the precoder and at least one of the modulation and coding schemes.

[0011] In one aspect, an apparatus may include a transceiver that wirelessly communicates with at least one network node on a network side during operation. The apparatus may also include a processor communicatively coupled to the transceiver. During operation, the processor may perform operations including measuring a reference signal from the network node via the transceiver to derive channel information. The processor may also perform operations including determining interference and noise information observed at a receiver of the apparatus. The processor may further perform operations including determining whitening information based on the interference and noise information. The processor may further perform operations including reporting the whitening information and the channel information to the network node via the transceiver.

[0012] It is worth noting that although the descriptions provided herein may be presented in the context of certain radio access technologies, networks, and network topologies such as Long-Term Evolution (LTE), LTE-Advanced, LTE-Advanced Pro, 5G, New Radio (NR), Internet-of-Things (IoT), Narrow Band Internet of Things (NB-IoT), Industrial Internet of Things (IIoT), and 6G, the proposed concepts, schemes, and any variations / derivatives thereof may be implemented, applied, and performed by other types of radio access technologies, networks, and network topologies. Therefore, the scope of this disclosure is not limited to the examples described herein. Attached Figure Description

[0013] The accompanying drawings are included to provide a further understanding of this disclosure and are incorporated in and constitute a part of this invention. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. It will be understood that the drawings are not necessarily to scale, as some components may be shown in a manner not proportional to actual dimensions in order to clearly illustrate the concepts of the invention.

[0014] Figure 1This is a schematic diagram illustrating an example scenario under an embodiment of the present disclosure.

[0015] Figure 2 This is a schematic diagram illustrating an example scenario under an embodiment of the present disclosure.

[0016] Figure 3 This is a schematic diagram illustrating an example scenario under an embodiment of the present disclosure.

[0017] Figure 4 This is a schematic diagram illustrating an example scenario under an embodiment of the present disclosure.

[0018] Figure 5 This is a block diagram of an example communication system according to an embodiment of the present disclosure.

[0019] Figure 6 This is a flowchart of an example process according to an embodiment of the present disclosure.

[0020] Figure 7 This is a flowchart of an example process according to an embodiment of the present disclosure. Detailed Implementation

[0021] This document discloses detailed embodiments and implementations of the claimed subject matter. However, it should be understood that the disclosed embodiments and implementations are merely illustrative of the claimed subject matter, which can be embodied in various forms. The invention can be practiced in many different forms and should not be construed as limited to the exemplary embodiments and implementations set forth herein. Rather, these exemplary embodiments and implementations are provided so that the description of the invention is thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In the following description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments and implementations.

[0022] Overview The implementations of this disclosure relate to various techniques, methods, schemes, and / or solutions for channel information feedback and whitening information related to user equipment and network devices in mobile communications. According to this disclosure, many possible solutions can be implemented individually or in combination. That is, although these possible solutions may be described individually below, two or more of these possible solutions may be implemented in one or another combination.

[0023] Figure 1An exemplary 5G NR network supporting CSI compression based on multidimensional MIMO radio frequency (RF) signatures is illustrated according to an embodiment of the present invention. The 5G NR network 100 includes a UE 110, which is communicatively connected to a gNB 121 of an access network 120. The access network 120 provides radio access using Radio Access Technology (RAT) (e.g., 5G NR technology). The access network 120 is connected to a 5G core network 130 via a Next Generation (NG) interface, more specifically to a User Plane Function (UPF) via the NG user-plane (NG-u) portion, and to an Access and Mobility Management Function (AMF) via the NG control plane (NG-c) portion. A gNB can connect to multiple UPFs / AMFs for load sharing and redundancy. The UE 110 can be a smartphone, wearable device, Internet of Things (IoT) device, tablet, etc. Alternatively, the UE 110 may be a laptop (NB) or personal computer (PC) with a modem and RF transceiver inserted or installed to provide wireless communication capabilities.

[0024] gNB 121 can provide communication coverage for a geographic coverage area, within which communication with UE 110 is supported via communication link 101. Communication link 101 shown in 5G NR network 100 may include uplink (UL) transmission from UE 110 to gNB 121 (e.g., on the Physical Uplink Control Channel (PUCCH) or Physical Uplink Shared Channel (PUSCH)) or downlink (DL) transmission from gNB 121 to UE 110 (e.g., on the Physical Downlink Control Channel (PDCCH) or Physical Downlink Shared Channel (PDSCH)).

[0025] In a novel aspect, the UE can estimate a multidimensional nonorthogonal basis at the receiver based on a set of reference signals (RS) transmitted by the transmitter, and feed back the multidimensional nonorthogonal basis (e.g., an N-dimensional sine matrix) with a first periodicity; and estimate linear combination coefficients of the multidimensional nonorthogonal basis based on the set of reference signals, and feed back the linear combination coefficients with a second periodicity. Specifically, the UE can receive reference signals, such as CSI-RS. The UE can obtain a feedback configuration (e.g., a CSI reporting configuration). In one embodiment, the feedback configuration is predefined. In another embodiment, the feedback configuration is dynamically updated. The UE can estimate the basis matrix and the coefficient matrix. Furthermore, the UE can compress the basis matrix and the coefficient matrix into compressed feedback. The UE then sends the compressed feedback to the network. While the multidimensional basis is generally nonorthogonal, in some embodiments, orthogonal bases are used as approximations.

[0026] Figure 2 An exemplary schematic diagram of a geometric model for a multidimensional MIMO channel and CSI feedback including a basis matrix and a coefficient matrix, according to an embodiment of the present invention, is shown. UE 210 has a MIMO transceiver / antenna 211 and can establish an RF link with gNB 220 having a transceiver / antenna array 221. The link between UE 210 and gNB 222 has 1 to 2... Multiple transmit / receive paths. Each path can be accessed via elevation angle. Azimuth ,Delay and Doppler To define. Elevation angle. and azimuth It can be further scaled to real numbers between 0 and 1. Figure 2 The first path is shown in the figure (e.g., )231, which is the line-of-sight path, and the second path (e.g., 232, it is a non-line-of-sight path. One receive (RX) antenna of gNB antenna array 221 and UE antenna 211. The channels between them can be determined by the number of paths. Parameters for each path q and complex channel gain To determine. It has the number of paths. Multipath channels can be modeled as matrices ,in A transmit (TX) antenna can include an antenna array. The number of TX antennas... The number of elements in the elevation angle Number of elements in azimuth angle and polarization quantity To determine. For example, suppose , and The total number of antennas can be To indicate the location of a single antenna, for Define index and (in as well as ), which can be used to indicate the position of antenna j in the vertical and horizontal planes, respectively.

[0027] In an exemplary scenario, gNB 220 can send at least one CSI-RS to UE 210. UE 210 can receive at least one CSI-RS from gNB 220. UE 210 can adjust the timing of the CSI-RS according to different times. and frequency At least one CSI-RS is used to estimate at least one covariance matrix and / or at least one downlink channel matrix of at least one downlink channel matrix. Specifically, after receiving CSI-RS at different times and frequencies, UE 110 can estimate the following: Downlink channel matrix of MIMO channel : .

[0028] This indicates the number of receiving antennas (i.e., antenna 211). This indicates the number of transmitting antennas (i.e., antenna 221). This indicates a time-domain index. This represents the frequency domain index. Assuming a path... RX antenna The complex channel gain is Then the path RX antenna The downlink channel matrix can be modeled as follows: .

[0029] It can be represented as: .

[0030] in ,as well as .against index and This is used to convert the antenna index to the position of antenna j. For planar antenna arrays, the index can be similar to... Figure 2 .

[0031] In a novel aspect, the channel matrix It can be modeled as a linear combination of multidimensional complex sine waves. In one embodiment, a time-frequency MIMO channel can be modeled as a linear combination of 4-dimensional (4-D) bases, expressed as: .

[0032] The dimension is Complex linear combination matrix: , And 4-D sine base The dimension is It can be represented as: .

[0033] in and It can be constant or slowly changing.

[0034] In a novel aspect, CSI feedback can be based on a multidimensional nonorthogonal basis matrix. and linear combination coefficient matrix The estimate is sent to the network. Feedback of the basis matrix can be obtained through the feedback matrix. To complete this. Basis matrix The matrix can be reconstructed according to the above formula. The basis matrix is ​​parameterized by a set of 4-dimensional parameters. Feedback of the basis matrix is ​​accomplished by feeding back a set of 4-dimensional parameters. In one embodiment, the CSI estimation matrix can be compressed before sending feedback. In one embodiment, periodicity can be configured for the compressed feedback CSI matrix.

[0035] In some implementations, the coefficient matrix one or more elements ( Elements can be removed based on one or more coefficient compression criteria. In one embodiment, one or more coefficient compression criteria may include removing elements with values ​​less than a predefined threshold, and / or selecting a predefined number of elements, and / or selecting a predefined percentage of elements. In one example, if an element... Elements that are "smaller" compared to other elements can be ignored in the feedback. In one embodiment, "smaller" is determined by comparing the element to a threshold. The threshold can be predefined or based on... The values ​​of all or some elements are derived. In another embodiment, "smaller" is determined by sorting. In one example, a fixed number of elements with the maximum value are selected. The fixed number of values ​​can be predefined, dynamically configured, or derived. In another example, a fixed proportion of all elements are selected. The values ​​of the fixed proportion can be predefined, dynamically configured, or derived.

[0036] In some implementations, one or more path columns can be removed based on one or more path-based compression criteria. One or more elements of the coefficient matrix can be removed based on all values ​​of all received antennas for each path, and one or more paths can be identified for compression. In one embodiment, one or more elements of the coefficient matrix can be removed based on all element values ​​in the first dimension representing the path, and elements in the second dimension of the coefficient matrix can be identified for compression. In one embodiment, the path-based compression criterion can be based on all values ​​of all RX antennas for a fixed path. In one embodiment, one or more values ​​of the path can be compared to a threshold, or one or more paths can be selected by sorting. For example, selection can be based on a fixed path. RX antenna All values ​​of , i.e. In one embodiment, if the path is determined If no feedback is provided, then its association No feedback is provided. Path determined. No feedback can be based on The function in which, In one embodiment, one or more paths can be selected for removal by comparing the path value with a path threshold. In one embodiment, the path threshold may be predefined. In another embodiment, the path threshold may be dynamically configured or derived. In yet another embodiment, one or more paths can be selected for removal by sorting. In one example, a fixed number of paths / columns with the maximum value can be selected. The fixed number of values ​​can be predefined or dynamically configured or derived. In another example, a fixed proportion of all paths / columns can be selected. The fixed proportion value can be predefined or dynamically configured or derived. It should be noted that when the path... Feedback is required when needed. It may be sufficient to derive its in The associated sinusoidal basis in the equation.

[0037] In a novel aspect, CSI feedback compression can be implemented in the RX antenna dimension according to embodiments of the invention. CSI feedback can be compressed by reducing one dimension of the coefficient matrix through compression of the decomposition matrix derived from the coefficient matrix. In some embodiments, CSI feedback can be compressed in the RX antenna dimension using eigenvalue decomposition (EVD) or singular value decomposition (SVD). CSI feedback matrix The dimension is If the RX antennas are correlated with each other (e.g., due to proximity), then The rank may be less than or at least The number of significant eigenvalues ​​may be less than Therefore, the UE can further compress the CSI feedback from the RX antenna dimension to a smaller rank dimension.

[0038] In one embodiment, compression can reduce the dimensionality of the receiving antenna through eigenvalue decomposition. The dimension is RX antenna The dimensions can be reduced to ,in Coefficient matrix Conjugate with its Hermite The product can be expressed as: .

[0039] yes diagonal matrix, where . It includes linear combination coefficients. A rank-decreasing matrix. The dimension is ,yes Hermetic conjugation.

[0040] The feedback can be further compressed and obtained through eigenvalue decomposition. (With an equal sign). In middle," This could mean that compression is already based on a diagonal matrix. Proceed. After that, you can proceed with... and related Compression is performed. In one embodiment, eigenvalue decomposition can facilitate the removal of one or more elements of the diagonal matrix of the coefficient matrix and the corresponding eigenvalues ​​according to one or more criteria, including removing elements smaller than a predefined threshold, selecting a predefined number of elements, and selecting a predefined percentage of elements. In one embodiment for compression, elements smaller than the threshold... The value can be ignored / removed from the feedback, and its associated feature vector is... The same applies to compression. In one embodiment, the threshold can be predefined. In another embodiment, the threshold can be dynamically configured or derived. In another embodiment for compression, a fixed number of feature values ​​and their associated feature vectors can be fed back. Other values ​​can be ignored / removed from the feedback. In one embodiment, the fixed number of values ​​can be predefined. In another embodiment, the fixed number of values ​​can be dynamically configured or derived. In another embodiment for compression, a fixed proportion of all feature values ​​and their associated feature vectors can be fed back. In the middle. Others can be ignored / removed from the feedback. In one embodiment, the value of the fixed ratio can be predefined. In another embodiment, the value of the fixed ratio can be dynamically configured or derived. In other embodiments for compression, only feature vectors associated with selected feedback feature values ​​can be fed back, while feature vectors associated with unselected feature values ​​can be removed from the feedback. After compression, the compressed and It can be sent as CSI feedback. Alternatively, only It can be sent as CSI feedback to further reduce overhead. In one embodiment, the feedback coefficient matrix can be derived by projecting the coefficient matrix onto at least one eigenvector matrix.

[0041] In one embodiment, compression can reduce the feedback of channel state information (CSI) at the receive antenna dimension through singular value decomposition (SVD). The dimension is Dimensions of the receiving antenna It can be reduced to ,in Coefficient matrix It can be represented as: .

[0042] yes A diagonal matrix has , . It contains left eigenvectors Reduced-rank matrix. It contains right eigenvectors. Reduced-rank matrix. The dimension is ,yes The conjugate transpose of .

[0043] The feedback can be further obtained through SVD compression. (With an equal sign). In middle," This could mean that compression is already based on a diagonal matrix. Proceed. Then, you can... and related Compression is performed. In one embodiment, SVD can facilitate the removal of one or more elements from the diagonal matrix of the coefficient matrix according to one or more criteria, including removing elements smaller than a predefined threshold, selecting a predefined number of elements, and selecting a predefined percentage of elements. In one embodiment for compression, values ​​smaller than a threshold are... The relevant feature vectors can be ignored / removed from the feedback. The same applies to compression. In one embodiment, the threshold can be predefined. In another embodiment, the threshold can be dynamically configured or derived. In yet another embodiment for compression, a fixed number of feature values ​​and their associated feature vectors can be fed back. Other values ​​can be ignored / removed from the feedback. In one embodiment, the fixed number of values ​​can be predefined. In another embodiment, the fixed number of values ​​can be dynamically configured or derived. In another embodiment for compression, a fixed proportion of all feature values ​​and their associated feature vectors can be fed back. Other features can be ignored / removed from the feedback. In one embodiment, the fixed ratio value can be predefined. In another embodiment, the fixed ratio value can be dynamically configured or derived. In other embodiments for compression, only feature vectors related to selected feedback feature values ​​can be fed back. Selected non-feedback feature values ​​can be removed. After compression, the compressed... and It can be sent as CSI feedback. Alternatively, only It can be sent as CSI feedback to further reduce overhead.

[0044] It should be noted that, due to the formula... , ,in The above of Left eigenvector and Compress (and then report). Compress (and then report) For separate reconstruction and They are the same. From the perspective of the precoder derivation of network nodes, and Similar information is provided, and any compression alternative can be applied.

[0045] In some implementations, different CSI feedback options, including representation, periodicity, and other configurations, can be applied according to embodiments of the invention. In one embodiment, one or more feedback options can be configured. In one embodiment, different representations can be configured as different feedback options. The underlying matrix can be in 4D (four-dimensional), 3D (three-dimensional), or 2D (two-dimensional) format. MIMO channel model This can include time-domain indexes and frequency domain index .

[0046] In 4D basic representation and It can be represented as: , , as well as , where 𝜦 and 𝛀 can be constant or slowly changing.

[0047] In three-dimensional basis representation, time-domain index It can be absorbed into the linear combination coefficients Middle. Path downlink channel matrix of the receiving antenna It can be represented as ,in and The elevation angle, azimuth angle, delay, and Doppler for each path can be expressed as: , , , Dimensions The complex linear combination matrix can be represented as: , A three-dimensional nonorthogonal Fourier basis can be represented as: , A time-frequency MIMO channel, as a linear combination of three-dimensional bases, can be expressed as: , in It can be constant or slowly changing.

[0048] In two-dimensional basis representation, time-domain index and frequency domain index All can be absorbed into the linear combination coefficients Middle. Path downlink channel matrix of the receiving antenna It can be represented as ,in as well as The elevation angle, azimuth angle, delay, and Doppler for each path can be expressed as: , .

[0049] .

[0050] Dimensions The complex linear combination matrix can be represented as: .

[0051] A two-dimensional nonorthogonal Fourier basis can be represented as: .

[0052] A time-frequency MIMO channel, as a linear combination of two-dimensional bases, can be expressed as: , in It can be constant or slowly changing.

[0053] In some implementations, the feedback periodicity can be configured accordingly based on this representation. In one embodiment, the parameters used to derive the basis matrix can be constant or slowly varying, and its associated feedback can be provided with a first periodicity. In one embodiment, the coefficient matrix may not include time-varying components (i.e., no time-domain index). The coefficient matrix can be constant or slowly changing. The relevant feedback of the coefficient matrix can be transmitted in a second periodicity. In one embodiment, the second periodicity can be longer than or equal to the first periodicity. In another embodiment, the coefficient matrix can include a time-varying component, wherein the time-varying coefficient matrix can be transmitted in a third periodicity shorter than the first or second periodicity.

[0054] For example, The 4D / 3D / 2D basis matrices can be constant or slowly changing, and can be configured to provide feedback with a first periodicity. It can be constant or slowly changing, and can be configured to provide feedback with a second periodicity. The second periodicity can be equal to or longer than the first periodicity. Maybe more , The changes are faster and can be configured to provide feedback with a third periodicity. The third periodicity can be shorter than the first periodicity. The third periodicity can be shorter than the second periodicity. It should be noted that for CSI feedback purposes, one of the 2D / 3D / 4D representations can be used (e.g., through configuration). Compression details and periodicity settings can be adjusted accordingly based on the representations discussed above.

[0055] In some implementations, other feedback configurations are available. In one embodiment, , , It can be done without accompaniment , , In cases where feedback is used to acquire spatial domain channel characteristics, such as beam direction acquisition, only the basis matrix (or the parameters used to derive the basis matrix) can be transmitted as CSI feedback. In one embodiment, Feedback can be provided to acquire the spatial domain characteristics of the channel for (simulated) beamdirection acquisition. In one embodiment, Doppler information is not reported. and its index The relevant information may not be included in the corresponding 2D / 3D / 4D representation, and therefore may not be fed back.

[0056] However, channel information feedback based on 4D / 3D / 2D forms (e.g., The receiver does not provide noise information (which may or may not include interference) observed at the receiver side. In NR CSI feedback, in addition to precoder feedback (e.g., PMI), the channel quality indicator (CQI) can also be fed back to indicate the spectral efficiency that can be supported under certain assumptions about the rank and / or precoder. Without noise and / or interference information, the reported feedback may not reflect the true channel conditions. The precoder and / or modulation and coding scheme determined by the network side may not be optimal without considering noise and / or interference information. Therefore, the receiver needs to include noise and / or interference information so that the transmitter side can derive the modulation and coding scheme transmitted between the transmitter and receiver.

[0057] In view of the above, this disclosure proposes several schemes for channel information feedback with whitening information. The whitening information can reflect noise and / or interference observed at the receiver side. The whitening information can be reported together with the channel information to be fed back (e.g., channel parameters). The channel parameters to be fed back can be one of the following alternatives: , Furthermore, the compression scheme described above can also be applied to feedback whitening information and channel parameters. Therefore, the receiver can reconstruct comprehensive channel information / state based on the reported information, and the network can achieve interference / noise management capabilities.

[0058] Specifically, the UE can measure reference signals from network nodes to derive channel information (e.g., The UE can determine the interference and noise information observed at its receiver. The interference and noise information may include only interference information, only noise information, or both. The interference and noise information can be represented by a covariance matrix. The covariance matrix may include at least one of a square matrix representing the noise variance at the device receiver, a white noise matrix, or a covariance matrix of spatial color interference plus noise. The UE can determine the covariance matrix by measuring the interference measurement resource (IMR) from network nodes. The IMR may include at least one of a zero-power (ZP) downlink (DL) RS and a non-zero-power (NZP) DL RS. The UE can then determine whitening information based on the interference and noise information. For example, the UE can determine a pre-whitening matrix (i.e., whitening information) based on the covariance matrix. The pre-whitening matrix can be obtained / determined by a covariance matrix based on Cholesky decomposition or eigenvalue decomposition. The pre-whitening matrix may include a pre-whitening filter reflecting at least one spatial orientation or spatial layer with lower interference and noise. After determining the whitening information, the UE can report the whitening information and channel information to the network node. For example, the UE can report pre-whitened channel information, which includes channel information and the pre-whitening matrix, to the network node. Alternatively, the UE can report the channel information and the covariance matrix separately to the network node.

[0059] From the network's perspective, network nodes can send reference signals to the UE. Additionally, network nodes can send IMR to the UE for measurement. IMR includes at least one of ZP DL RS and NZP DL RS. Network nodes can receive whitening information and channel information from the UE. Whitening information may include only interference information, only noise information, or both. Whitening information can be represented by a pre-whitening matrix. For example, a network node can receive pre-whitened channel information from the UE that includes channel information and the pre-whitening matrix. Alternatively, a network node can receive channel information and a covariance matrix from the UE separately. The network node can determine the pre-whitening matrix based on the covariance matrix and determine the pre-whitened channel information that includes the channel information and the pre-whitening matrix. The pre-whitening matrix may include a pre-whitening filter reflecting at least one spatial orientation or spatial layer with low interference and noise. The pre-whitening matrix can be obtained / determined using a covariance matrix based on Cholesky decomposition or eigenvalue decomposition. The network node can then determine at least one of a pre-encoder and a modulation / coding scheme based on the whitening information and channel information. Network nodes can use at least one of the precoder and modulation coding scheme to perform downlink transmissions to the UE.

[0060] Figure 3 An example scenario 300 is illustrated under an embodiment of the present invention. Scenario 300 involves at least one UE and at least one network node, which may be part of a wireless communication network (e.g., an LTE network, a 5G / NR network, an IoT network, or a 6G network). Scenario 300 illustrates a novel channel information feedback scheme. The UE may connect to the network side. The network side may include one or more network nodes. The network node can... Each antenna transmits DL RS (e.g., CSI-RS) to the UE. The UE can then... Each antenna measures the CSI-RS to obtain channel information between itself and network nodes. The UE can perform measurements to derive the channel information (e.g., ).

[0061] Furthermore, network nodes can send IMRs to the UE. IMRs may include ZP DL RS. The UE can perform interference measurements to derive the interference variance (e.g., covariance matrix). The network node can also send another IMR to the UE. The IMR may include NZP DL RS. The UE can perform interference measurements to derive the interference variance (e.g., covariance matrix). After determining the interference variance, the UE can base its decisions on... and At least one derived prewhitening matrix in Then, the UE can determine the pre-whitening channel based on the pre-whitening matrix and channel information. The network then sends a pre-whitened channel back to the network side. This feedback can be done during the compression process. Upon receiving the pre-whitened channel, the network side can determine an appropriate / optimal precoder and / or modulation / coding scheme for subsequent communication.

[0062] In a novel aspect, the information / channel parameters to be fed back can be derived based on an equivalent channel (e.g., a pre-whitened channel). The equivalent channel can include channel information and whitening information. The pre-whitened channel can be defined as: .

[0063] Represents the pre-whitening matrix (i.e., whitening information), which can be based on the covariance matrix on the receiver side. Export. This represents the channel information as described above. Extraction , or The operation can be applied to by Defined pre-whitened channel.

[0064] In some implementations, the covariance matrix may include a square matrix representing the receiver-side noise variance. In some implementations, the covariance matrix may be measured from (pre-)configured resources, such as an IMR for interference measurements. This interference measurement resource may include ZP DLRS and / or NZP DLRS. The covariance matrix may be based on measurements of the ZP DLRS and NZP DLRS. The covariance matrix may include a colored noise matrix. In some implementations, the covariance matrix may be based on the receiver's noise level. Determined in the receiving branch. The covariance matrix may include white noise. In some implementations, The matrix can be derived from the Cholesky decomposition (e.g., and The matrix derived from ).

[0065] For pre-whitening channels Compression can follow the above-mentioned principles for... The operation. In some implementations, amplitude information may be preserved. For example, (or or The linear combination coefficients in the model may not be normalized based on the strongest coefficient, meaning the strongest coefficient is not magnitude 1. In some implementations, magnitude information may not be preserved. For example, (or or The linear combination coefficients in the data may be normalized based on the strongest coefficient. Amplitude information about the strongest coefficient may be additionally fed back to the receiver.

[0066] Figure 4 An example scenario 400 is illustrated under a scheme according to an embodiment of the present invention. Scenario 400 involves at least one UE and at least one network node, which may be part of a wireless communication network (e.g., an LTE network, a 5G / NR network, an IoT network, or a 6G network). Scenario 400 illustrates a novel aspect of a channel information feedback scheme. In this embodiment, channel information... Covariance Matrix This can be reported / reported independently by the UE. Specifically, the pre-whitened channel can be... Sure. As described above, the covariance matrix can be used to... Export. Feedback can also follow a similar procedure / operation as described above. The UE can report in one report or separately in different reports. and To the receiver side. Upon receiving... and Afterwards, network nodes can be based on Export and through Determine the pre-whitened channel. The UE may not need to know about... Information. The pre-whitened channel can be derived on the network side.

[0067] In some implementations... and The amplitude information can be retained separately. In some implementations, and The relative amplitude information can be preserved. (or or The linear combination coefficients in () can be normalized based on the strongest coefficients. The entries in the matrix can be normalized based on the strongest coefficients mentioned above. In some implementations, the covariance matrix... It can be compressed into noise variance values. In one example, the covariance matrix... It is whitened, therefore it is a diagonal matrix with the same noise variance values. Only the noise variance values ​​are reported. In one example, the covariance matrix... It is whitened, therefore it is a diagonal matrix with individual noise variance values. Only the noise variance values ​​are reported. The noise variance values ​​to be fed back can be based on... (or or The strongest coefficient in the ) is normalized.

[0068] In a novel aspect, the pre-whitened channel Feedback can be provided through the compression process. The pre-whitening matrix may include a pre-whitening filter reflecting at least one spatial orientation or layer with low interference and noise. In this case, the pre-whitening filter... It can be incorporated into the channel, so a separate report is not required. Specifically, the UE can perform interference measurements to derive the covariance matrix. Assuming It is spatial colored interference plus noise The covariance matrix. It includes feature vectors and can reflect the spatial orientation of interference and noise. It can reflect the amplitude. The UE can determine the pre-whitening filter as... Compression operations can be performed through... Performed on the pre-whitened channel, not on the measured physical channel. This process is performed on the network nodes. The interference plus noise term is then normalized to an identity matrix, i.e., independently and identically distributed (iid) across the RX antennas with unit variance. The feedback may include a scaler that appropriately scales the parameterized direct channel feedback of the pre-whitened channel (and thus the unit variance of the whitened interference plus noise term) to minimize quantization error.

[0069] Pre-whitening filter This means that spatial directions (or layers) with smaller interference-plus-noise variance (e.g., less than a threshold) will be amplified because more transmission energy should be directed to these spatial directions (or layers) to maximize throughput, while layers with strong interference-plus-noise variance will be reduced. Therefore, feedback overhead can be further reduced, especially in channels with highly colored interference.

[0070] In a new aspect, feedback from the pre-whitening channel This can be done through a compression process. Compression process It can include two steps. In the first step, the UE can... Project onto a feature subspace and select a (feature) subspace with a strong projection value (e.g., greater than a threshold), and reconstruct the reduced-rank channel based on the selected (feature) subspace. For example, a UE can... Perform eigenvalue decomposition, select the subset of eigenvectors with the strongest eigenvalues, and construct a new eigenvector matrix based on this subset and the eigenvalues. Smaller or weaker (feature) subspaces (e.g., less than a threshold) can be omitted from the report to reduce signaling overhead. In the second step, the UE can further optimize the report based on the compression scheme described above. Compress it.

[0071] Illustrative Implementation Figure 5 An example communication system 500 with an example communication device 510 and an example network device 520 according to an embodiment of the present disclosure is shown. Each of the communication device 510 and the network device 520 can perform various functions to implement the schemes, techniques, processes, and methods described herein for channel information feedback and whitening information related to network devices in user equipment and mobile communications, including the scenarios / schemes described above and processes 600 and 700 described below.

[0072] Communication device 510 may be part of an electronic device, which may be a UE (User Equipment), such as a portable or mobile device, a wearable device, a wireless communication device, or a computing device. For example, communication device 510 may be implemented in a smartphone, smartwatch, personal digital assistant, digital camera, or computing device such as a tablet, laptop, or notebook computer. Communication device 510 may also be part of a machine-type device, which may be an IoT, NB-IoT, or IIoT device, such as a fixed or stationary device, a home device, a wired communication device, or a computing device. For example, communication device 510 may be implemented in a smart thermostat, smart refrigerator, smart door lock, wireless speaker, or home control center. Alternatively, communication device 510 may be implemented in the form of one or more integrated circuit (IC) chips, such as, but not limited to, one or more single-core processors, one or more multi-core processors, one or more reduced-instruction-set computing (RISC) processors, or one or more complex-instruction-set computing (CISC) processors. Communication device 910 may include... Figure 5 At least some of the components shown, such as processor 512. Communication device 510 may also include one or more other components unrelated to the proposed solutions of this disclosure (e.g., internal power supply, display device, and / or user interface device), therefore, these components of communication device 510 are not... Figure 5 The text shown is not described below to keep things concise.

[0073] Network device 520 may be part of a network device, which may be a network node such as a satellite, base station, small cell, router, or gateway. For example, network device 520 may be implemented in an eNodeB in an LTE network, a gNB in ​​a 5G / NR, IoT, NB-IoT, or IIoT network, or a satellite or base station in a 6G network. Alternatively, network device 520 may be implemented in the form of one or more IC chips, such as, but not limited to, one or more single-core processors, one or more multi-core processors, or one or more RISC or CISC processors. Network device 520 may include... Figure 5 At least some of the components shown are included, for example, processor 522. Network device 520 may also include one or more other components unrelated to the proposed solutions of this disclosure (e.g., internal power supply, display device, and / or user interface device), therefore, these components of network device 520 are not... Figure 5 The text shown is not described below to keep things concise.

[0074] In one aspect, each of processors 512 and 522 may be implemented as one or more single-core processors, one or more multi-core processors, or one or more CISC processors. That is, although the singular term "processor" is used herein to refer to processors 512 and 522, each of processors 512 and 522 may include multiple processors in some embodiments and a single processor in other embodiments, according to this disclosure. In another aspect, each of processors 512 and 522 may be implemented as hardware (and optionally firmware) comprising, for example, but not limited to, one or more transistors, one or more diodes, one or more capacitors, one or more resistors, one or more inductors, one or more memristors, and / or one or more transformers, these components being configured and arranged to perform a specific purpose according to this disclosure. In other words, in at least some embodiments, each of processors 512 and 522 is a dedicated machine specifically designed, arranged, and configured to perform a specific task, including channel information feedback and whitening information in devices (e.g., represented by communication device 510) and networks (e.g., represented by network device 520) according to various embodiments of this disclosure.

[0075] In some embodiments, the communication device 510 may further include a transceiver 516 coupled to the processor 512 and capable of wirelessly transmitting and receiving data. In some embodiments, the transceiver 516 is capable of wireless communication with wireless networks of different types of UEs and / or different RATs. In some embodiments, the transceiver 516 may be equipped with multiple antenna ports (not shown), for example, four antenna ports. That is, the transceiver 516 may be equipped with multiple transmit antennas and multiple receive antennas for multiple-input multiple-output (MIMO) wireless communication. In some embodiments, the network device 520 may further include a transceiver 526 coupled to the processor 522. The transceiver 526 may include a transceiver capable of wirelessly transmitting and receiving data. In some embodiments, the transceiver 526 is capable of wireless communication with different types of UEs of different RATs. In some embodiments, the transceiver 526 may be equipped with multiple antenna ports (not shown), for example, four antenna ports. That is, the transceiver 526 may be equipped with multiple transmit antennas and multiple receive antennas for MIMO wireless communication.

[0076] In some embodiments, the communication device 510 may further include a memory 514 coupled to the processor 512, which can be accessed by the processor 512 and stores data. In some embodiments, the network device 520 may further include a memory 524 coupled to the processor 522, which can be accessed by the processor 522 and stores data. Each of the memories 514 and 524 may include a random-access memory (RAM), such as dynamic RAM (DRAM), static RAM (SRAM), thyristor RAM (T-RAM), and / or zero-capacitance RAM (Z-RAM). Alternatively, or additionally, each of the memories 514 and 524 may include a read-only memory (ROM), such as a mask ROM, a programmable ROM (PROM), an erasable programmable ROM (EPROM), and / or an electrically erasable programmable ROM (EEPROM). Alternatively or additionally, each of memories 514 and 524 may include a non-volatile random-access memory (NVRAM), such as flash memory, solid-state memory, ferroelectric RAM (FeRAM), magnetoresistive RAM (MRAM), and / or phase-change memory.

[0077] Each of the communication device 510 and the network device 520 may be a communication entity capable of communicating with each other using various proposed schemes according to this disclosure. For illustrative purposes and without limitation, the capabilities of the communication device 510 as a UE and the network device 520 as a network node (e.g., TRP) are described below in conjunction with processes 600 and 700.

[0078] Exemplary process Figure 6 An example flow 600 according to an embodiment of the present disclosure is shown. Flow 600 may be an example implementation of the above scenario / solution, whether partially or completely, involving channel information feedback of whitening information of the present disclosure. Flow 600 may represent one aspect of a characteristic embodiment of communication device 510. Flow 600 may include one or more operations, actions, or functions, as shown in blocks 610, 620, 630, and 640. Although shown as discrete blocks, the individual blocks of flow 600 may be divided into more blocks, merged into fewer blocks, or eliminated according to the desired implementation. Furthermore, the blocks of flow 600 may be arranged according to... Figure 6 The process 600 may be executed in the order shown in the diagram, or in a different order. Process 600 may be implemented by communication device 510 or any suitable UE or machine type device. For illustrative purposes only and without limitation, process 600 is described below in the context of communication device 510. Process 600 may begin at block 610.

[0079] In block 610, process 600 may involve the processor 512 of communication device 510 measuring reference signals from network nodes via transceiver 516 to derive channel information. Process 600 can proceed from block 610 to block 620.

[0080] In block 620, process 600 may involve processor 512 determining interference and noise information observed at receiver 516 of communication device 510. Process 600 may proceed from block 620 to block 630.

[0081] In block 630, process 600 may involve processor 512 determining whitening information based on interference and noise information. Process 600 can proceed from block 630 to block 640.

[0082] In block 640, process 600 may involve processor 512 reporting whitening information and channel information to network nodes via transceiver 516.

[0083] In some implementations, process 600 may further involve processor 512 determining a pre-whitening matrix based on a covariance matrix. The covariance matrix may include at least one of a square matrix representing the noise variance at the device receiver, a covariance matrix of white noise, and a covariance matrix of spatially colored interference plus noise. Processor 512 may obtain / determine the pre-whitening matrix using a covariance matrix based on Cholesky decomposition or eigenvalue decomposition.

[0084] In some implementations, process 600 may further involve processor 512 reporting pre-whitened channel information, including channel information and a pre-whitening matrix, to network nodes via transceiver 516.

[0085] In some implementations, process 600 may further involve processor 512 reporting channel information and covariance matrix to network nodes via transceiver 516.

[0086] In some implementations, process 600 may further involve processor 512 determining a covariance matrix by measuring the IMR. The IMR may include at least one of ZP DL RS and NZP DL RS.

[0087] In some implementations, the pre-whitening matrix may include a pre-whitening filter that reflects at least one spatial orientation or spatial layer with low interference and noise.

[0088] In some implementations, the interference and noise information may include only interference information or only noise information.

[0089] Figure 7 An example flow 700 according to an embodiment of the present disclosure is shown. Flow 700 may be an example implementation of the above-described scenario / scheme, whether partially or completely, involving channel information feedback of whitening information of the present disclosure. Flow 700 may represent one aspect of a characteristic embodiment of network device 520. Flow 700 may include one or more operations, actions, or functions, as shown in blocks 710, 720, 730, and 740. Although shown as discrete blocks, the individual blocks of flow 700 may be divided into more blocks, merged into fewer blocks, or eliminated according to the desired implementation. Furthermore, the blocks of flow 700 may be arranged according to... Figure 7 The process 700 may be executed in the order shown, or in a different order. Process 700 may be implemented by network device 520 or any suitable base station or network node. For illustrative purposes only and without limitation, process 700 is described below in the context of network device 520. Process 700 may begin at block 710.

[0090] In block 710, process 700 may involve the processor 522 of network device 520 sending a reference signal to the UE via transceiver 526. Process 700 can proceed from block 710 to block 720.

[0091] In block 720, process 700 may involve processor 522 receiving whitening information and channel information from UE via transceiver 526. Process 700 can proceed from block 720 to block 730.

[0092] In block 730, process 700 may involve processor 522 determining at least one of a precoder and a modulation / coding scheme based on whitening information and channel information. Process 700 may proceed from block 730 to block 740.

[0093] In block 740, process 700 may involve processor 522 performing downlink transmission to UE using at least one of precoder and modulation coding scheme.

[0094] In some implementations, the whitening information may include a pre-whitening matrix. The pre-whitening matrix may include a pre-whitening filter that reflects at least one spatial orientation or spatial layer with low interference and noise.

[0095] In some implementations, process 700 may further involve processor 522 receiving pre-whitened channel information, including channel information and a pre-whitening matrix, from UE via transceiver 526.

[0096] In some implementations, process 700 may further involve processor 522 receiving channel information and covariance matrix from UE via transceiver 526.

[0097] In some implementations, process 700 may further involve processor 522 determining a pre-whitening matrix based on the covariance matrix. Processor 522 may obtain / determine the pre-whitening matrix using a covariance matrix based on Cholesky decomposition or eigenvalue decomposition. Process 700 may further involve processor 522 determining pre-whitening channel information, including channel information and the pre-whitening matrix.

[0098] In some implementations, process 700 may further involve processor 522 transmitting IMR to the UE via transceiver 526. This interference measurement resource may include at least one of ZP DL RS and NZP DL RS.

[0099] In some implementations, the whitening information may include only interference information or only noise information.

[0100] Additional Notes The topics described herein sometimes illustrate different components contained within or connected to different other components. It should be understood that the architectures described are merely examples, and many other architectures with the same functionality can actually be implemented. In a conceptual sense, any arrangement of components that achieve the same functionality is effectively “associated” to achieve the desired functionality. Therefore, any two components combined in this document to achieve a particular function can be considered “associated” with each other to achieve the desired functionality, regardless of the architecture or intermediate components. Similarly, any two components so associated can also be considered “operationally connected” or “operationally linked” to each other to achieve the desired functionality, and any two components that can be so associated can also be considered “operationally linked” to each other to achieve the desired functionality. Specific examples of operable connections include, but are not limited to, physically matchable and / or physically interacting components and / or wirelessly interactable and / or logically interacting and / or logically interactable components.

[0101] Furthermore, regarding the use of virtually any plural and / or singular terms in this document, those skilled in the art can appropriately convert from plural to singular and / or from singular to plural depending on the context and / or application. For clarity, various singular / plural permutations may be explicitly described herein.

[0102] Furthermore, those skilled in the art will understand that, in general, the terms used herein, particularly those used in the appended claims, such as the body of the appended claims, are typically intended as “open-ended” terms; for example, the term “comprising” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “at least having,” and the term “comprising” should be interpreted as “including but not limited to.” Those skilled in the art will further understand that if a specific number of introduced claim statements are desired, such an intent will be explicitly stated in the claims, and without such a statement, such an intent does not exist. For example, to aid understanding, the following appended claims may contain the use of the introductory phrases “at least one” and “one or more” to introduce claim statements. However, the use of such phrases should not be construed as implying that a claim statement introduced by the indefinite article "a" or "an" limits any particular claim containing such a claim statement to an embodiment containing only one such statement, even when the same claim includes the introductory phrase "one or more" or "at least one," and indefinite articles such as "a" or "an," e.g., "an" and / or "an," should be interpreted as meaning "at least one" or "one or more." This also applies to the use of explicit texts introducing claim statements. Furthermore, even if a specific number of the introduced claims is explicitly listed, those skilled in the art will recognize that such a list should be interpreted as meaning at least the number listed; for example, a bare list of "two lists" without other modifiers means at least two lists, or two or more lists. Moreover, in those cases, the convention is similar to "at least one of A, B, and C, etc." Generally, in the conventional sense understood by those skilled in the art, the use of such a construct, such as "a system having at least one of A, B, and C," will include, but is not limited to, systems having a single A, a single B, a single C, A and B together, A and C together, B and C together, and / or A, B, and C together, etc., in those cases where the convention is similar to "at least one of A, B, or C." Generally, this construct is intended for use in the conventional sense understood by those skilled in the art; for example, "a system having at least one of A, B, or C" will include, but is not limited to, systems having a single A, a single B, a single C, A and B together, A and C together, B and C together, and / or A, B, and C together. Those skilled in the art will further understand that any extractive words and / or phrases that actually present two or more alternative terms, whether in the specification, claims, or drawings, should be understood to cover the possibility of including one, any, or both of the terms. For example, the phrase "A or B" will be understood to include the possibility of "A" or "B" or "A and B."

[0103] As will be understood from the foregoing, various embodiments of the invention have been described herein for illustrative purposes, and various modifications may be made without departing from the scope and spirit of the invention. Therefore, the various embodiments disclosed herein are not intended to be limiting, and their true scope and spirit are indicated by the appended claims.

Claims

1. A method comprising: The device's processor measures reference signals from network nodes to derive channel information; The processor determines the interference and noise information observed at the receiver of the device; The processor determines whitening information based on the interference and noise information. as well as The processor reports the whitening information and the channel information to the network node.

2. The method as described in claim 1, wherein, Determining this whitening information further includes: The processor determines the pre-whitening matrix based on the covariance matrix.

3. The method as described in claim 2, wherein, The pre-whitening matrix is ​​obtained by using the covariance matrix based on Cholesky decomposition or eigenvalue decomposition.

4. The method of claim 2, wherein, The report on the whitening information and the interference and noise information further includes: The processor reports the pre-whitened channel information, including the channel information and the pre-whitening matrix, to the network node.

5. The method of claim 2, wherein, The report on the whitening information and the interference and noise information further includes: The processor reports the channel information and the covariance matrix to the network node, respectively.

6. The method of claim 2, wherein, Further includes: The processor determines the covariance matrix by measuring interference measurement resources. The interference measurement resource includes at least one of a zero-power downlink reference signal and a non-zero-power downlink reference signal.

7. The method of claim 2, wherein, The pre-whitening matrix includes a pre-whitening filter that reflects at least one spatial orientation or spatial layer with low interference and noise.

8. The method of claim 1, wherein, The interference and noise information includes either interference information or noise information only.

9. A method comprising: The network node's processor sends a reference signal to the user equipment; The processor receives whitening information and channel information from the user equipment. The processor determines at least one of the precoder and modulation / coding scheme based on the whitening information and the channel information. as well as The processor uses at least one of the precoder and the modulation and coding scheme to perform downlink transmissions to the UE.

10. The method of claim 9, wherein, The whitening information includes the pre-whitening matrix.

11. The method of claim 10, wherein, The pre-whitening matrix includes a pre-whitening filter that reflects at least one spatial orientation or spatial layer with low interference and noise.

12. The method of claim 10, wherein, Receiving the whitening information and the channel information further includes: The processor receives pre-whitened channel information, including the channel information and the pre-whitening matrix, from the UE.

13. The method of claim 10, wherein, Receiving the whitening information and the channel information further includes: The processor receives the channel information and covariance matrix from the user equipment, respectively.

14. The method of claim 13, wherein, Further includes: The processor determines the pre-whitening matrix based on the covariance matrix; and The processor determines the pre-whitened channel information, including the channel information and the pre-whitening matrix.

15. The method of claim 9, further comprising: The processor sends interference measurement resources to the user equipment. The interference measurement resource includes at least one of a zero-power downlink reference signal and a non-zero-power downlink reference signal.

16. The method of claim 9, wherein, The whitening information includes only interference information or only noise information.

17. An apparatus comprising: A transceiver that communicates wirelessly with at least one network node during operation; as well as The processor is communicatively connected to the transceiver so that during operation, the processor performs the following operations: The transceiver measures reference signals from network nodes to derive channel information; Determine the interference and noise information observed at the receiver of the device; Whitening information is determined based on this interference and noise information; as well as The transceiver reports the whitening information and the channel information to the network node.

18. The apparatus of claim 17, wherein, In determining this whitening information, the processor further performs the following operations: The pre-whitening matrix is ​​determined based on the covariance matrix.

19. The apparatus of claim 18, wherein, In reporting the whitening information and the interference and noise information, the processor further performs the following operations: The transceiver reports the pre-whitened channel information, including the channel information and the pre-whitened matrix, to the network node.

20. The apparatus as claimed in claim 18, wherein, In reporting the whitening information and the interference and noise information, the processor further performs the following operations: reporting the channel information and the covariance matrix to the network node via the transceiver.

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