CN113508538B

CN113508538B - Channel State Information (CSI) feedback enhancement depicting per path angle and delay information

Info

Publication number: CN113508538B
Application number: CN202080004226.2A
Authority: CN
Inventors: 刘皓
Original assignee: Nokia Shanghai Bell Co Ltd; Nokia Solutions and Networks Oy
Current assignee: Nokia Shanghai Bell Co Ltd; Nokia Solutions and Networks Oy
Priority date: 2020-02-05
Filing date: 2020-02-05
Publication date: 2023-06-23
Anticipated expiration: 2040-02-05
Also published as: WO2021155514A1; CN113508538A

Abstract

Systems, methods, apparatuses, and computer program products described herein may provide CSI feedback enhancement that delineates per-path angle and delay information. For example, some embodiments may provide a new codebook design in which accurate angle and delay information may be obtained for each dominant channel path using Spatial Domain (SD) transform and Frequency Domain (FD) transform, respectively. In particular, certain embodiments may provide at least the following operations for CSI feedback design: 1) The UE may perform FD transformation on a subcarrier level using fourier transform operations according to a current channel measurement matrix to determine a dominant channel path and a corresponding delay; 2) The UE may determine angle information for each dominant channel path using an SD transform; and 3) after FD and SD transforms, the UE may reduce the channel matrix in its dimension and the UE may quantize the Linear Combination (LC) coefficients for feedback.

Description

Channel State Information (CSI) feedback enhancement depicting per path angle and delay information

Technical Field

Some example embodiments may relate generally to mobile or wireless telecommunication systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technology or New Radio (NR) access technology, or other communication systems. For example, certain embodiments may relate to systems and/or methods for Channel State Information (CSI) feedback enhancement that delineates per-path angle and delay information.

Background

Examples of mobile or wireless telecommunications systems may include Universal Mobile Telecommunications System (UMTS) terrestrial radio access network (UTRAN), evolved UTRAN for Long Term Evolution (LTE) (E-UTRAN), LTE-advanced (LTE-a), multeFire, LTE-a Pro, and/or fifth generation (5G) radio access technology or New Radio (NR) access technology. The 5G wireless system refers to the Next Generation (NG) radio system and network architecture. The 5G is built mainly on the New Radio (NR), but the 5G (or NG) network may also be built on the E-UTRA radio. It is estimated that NR can provide bit rates on the order of 10-20Gbit/s or higher and can support at least enhanced mobile broadband (emmbb) and ultra-reliable low latency communications (URLLC) as well as large-scale machine type communications (mctc). NR is expected to achieve extremely broadband and ultra-robust low latency connectivity as well as large-scale networking to support internet of things (IoT). As IoT and machine-to-machine (M2M) communications become more prevalent, there will be an increasing demand for networks that meet the demands of lower power, low data rates, and long battery life. Note that in 5G, a node that may provide radio access functionality to user equipment (i.e., similar to a node B in UTRAN or an eNB in LTE) may be named a gNB when built on an NR radio and a NG-eNB when built on an E-UTRA radio.

Disclosure of Invention

According to a first embodiment, a method may include: at least one Frequency Domain (FD) transformation is performed on the at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation. The method may include: one or more dominant channel paths and corresponding delays are determined based on the at least one first transformed channel matrix. The method may include: angle information is determined for each of the one or more dominant channel paths using at least one Spatial Domain (SD) transform of the at least one second transformed channel matrix. The method may include: at least one linear combination coefficient is calculated for at least one third transformed channel matrix.

In one variation, the method may include: at least one channel measurement matrix is acquired in at least one downlink channel state information reference signal (CSI-RS) measurement before performing at least one Frequency Domain (FD) transformation. In one variation, performing at least one Frequency Domain (FD) transform may further include: at least one channel measurement matrix is transformed into at least one Time Domain (TD) channel matrix to form at least one first transformed channel matrix. In one variation, determining one or more dominant channel paths may further comprise: one or more dominant channel paths are selected from the at least one first transformed channel matrix to form at least one second transformed channel matrix.

In one variation, the angle information may identify at least one departure angle. In a variation, determining the angle information may further include: at least one corresponding column vector of the at least one second transformed channel matrix is reshaped into at least one matrix for at least one of the one or more dominant channel paths, the at least one matrix having the size of the number of receive antenna ports multiplied by the number of transmit antenna ports. In a variation, determining the angle information may further include: in a second dimension of the at least one matrix, angle information is determined based on the at least one matrix. The angle information may be common to different receive antenna ports.

In one variation, determining the angle information may include: at least one discrete fourier transform vector is searched to match at least one matrix in a second dimension and to represent angle information, wherein the angle information is different for each of the one or more dominant channel paths or for each polarization of the dominant channel paths of the one or more dominant channel paths. In one variation, the method may further comprise: at least one of the following is provided for uplink Channel State Information (CSI) feedback: feedback of delay per path using at least one Frequency Domain (FD) transform, feedback of angle per path using at least one Spatial Domain (SD) transform, at least one bitmap of at least one linear combination coefficient, at least one indication of at least one particular linear combination coefficient, or at least one calculation of at least one non-zero linear combination coefficient.

According to a second embodiment, a method may include: channel State Information (CSI) feedback is received for each of the one or more dominant channel paths. The method may include: at least one first recovered channel matrix is constructed based on Channel State Information (CSI) feedback. The method may include: at least one inverse Spatial Domain (SD) transform is performed on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD). The method may include: at least one inverse Frequency Domain (FD) transformation is performed on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD). The method may include: the third recovered channel matrix is used for one or more actions including scheduling or precoding for downlink transmissions.

In one variation, the Channel State Information (CSI) feedback may comprise at least one of: delay information for each of the one or more dominant paths, angle information for each of the one or more dominant paths, spatial beam information for each of the one or more dominant paths, or at least one linear combination coefficient. In a variation, constructing the at least one first recovered channel matrix may further comprise: at least one first recovered channel matrix is constructed for each of the one or more dominant paths based on the one or more linear combination coefficients. In one variation, performing at least one inverse Spatial Domain (SD) transform may further comprise: at least one reverse Spatial Domain (SD) transform from angular information to spatial information is performed on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant paths. In one variation, performing at least one inverse Frequency Domain (FD) transform may further include: at least one inverse Frequency Domain (FD) transformation from delay information to Frequency Domain (FD) information is performed on the at least one second recovered channel matrix using delay feedback for each of the one or more dominant paths.

A third embodiment may be directed to an apparatus comprising at least one processor and at least one memory including computer program code. The at least one memory and the computer program code may be configured to, with the at least one processor, cause the apparatus at least to perform the method according to the first embodiment or the second embodiment, or any of the variations discussed above.

The fourth embodiment may be directed to an apparatus, which may comprise circuitry configured to perform the method according to the first or second embodiment, or any of the variations discussed above.

The fifth embodiment may be directed to an apparatus, which may comprise means for performing the method according to the first or second embodiment, or any of the variations discussed above.

The sixth embodiment may be directed to a computer readable medium comprising program instructions stored thereon for performing at least the method according to the first embodiment or the second embodiment, or any of the variations discussed above.

The seventh embodiment may be directed to a computer program product encoded with instructions for performing at least the method according to the first embodiment or the second embodiment, or any of the variations discussed above.

Drawings

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

fig. 1 illustrates an example of Channel State Information (CSI) feedback enhancement depicting per-path angle and delay information, in accordance with some embodiments;

FIG. 2 illustrates an example flow chart of a method according to some embodiments;

FIG. 3 illustrates an example flow chart of a method according to some embodiments;

FIG. 4a illustrates an example block diagram of an apparatus according to some embodiments; and

fig. 4b illustrates an example block diagram of an apparatus according to some embodiments.

Detailed Description

It will be readily understood that the components of certain example embodiments, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Accordingly, the following detailed description of some example embodiments of systems, methods, apparatus, and computer program products for Channel State Information (CSI) feedback enhancement depicting per-path angle and delay information is not intended to limit the scope of certain embodiments, but is representative of selected example embodiments.

The features, structures, or characteristics of the example embodiments described throughout this specification may be combined in any suitable manner in one or more example embodiments. For example, the use of the phrases "certain embodiments," "some embodiments," or other similar language throughout this specification refers to the fact that: a particular feature, structure, or characteristic described in connection with the embodiments may be included within at least one embodiment. Thus, appearances of the phrases "in certain embodiments," "in some embodiments," "in other embodiments," or other similar language throughout this specification do not necessarily all refer to the same group of embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments. In addition, as used herein, the phrase "set of … …" refers to a set that includes one or more of the referenced items. Thus, the phrases "set of … …", "at least one of … …" and "one or more of … …" may be used interchangeably.

In addition, if desired, different functions or operations discussed below may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the described functions or operations may be optional or may be combined. As such, the following description should be considered as merely illustrative of the principles and teachings of certain exemplary embodiments, and not in limitation thereof.

One of the goals for CSI enhancement is described as evaluating (and if needed) a specified type II port selection codebook enhancement (based on rel.15/16 type II port selection), where information about angle(s) and delay(s) is estimated at the gNB based on Sounding Reference Signals (SRS) by exploiting the downlink/uplink (DL/UL) reciprocity of angle and delay. The remaining DL CSI is reported by the UE, mainly for Frequency Division Duplex (FDD) frequency range 1 (FR 1), to achieve a better tradeoff between UE complexity, performance and reporting overhead.

Due to its superior performance over Rel-14 LTE, a type II codebook design was introduced in rel.15 nr. In the rel.16nr phase, frequency Domain (FD) transform techniques are implemented and specified in a type II codebook to significantly reduce feedback overhead without performance loss. As NR is being commercialized, there may be a need for more attention to the real deployment scenario. For example, partial reciprocity on channel statistics (including angle and delay) may be used for FR1 FDD CSI enhancement to achieve a better tradeoff between UE complexity, performance, and reporting overhead.

For the rel.16 type II codebook, there are two types of transforms that use Discrete Fourier Transforms (DFT) to reduce the number of CSI feedback elements, including FD transforms and Spatial Domain (SD) transforms. In general, the channel matrix may be transformed from FD to Time Domain (TD) using FD transformation that determines the dominant channel path and corresponding delay. The rel.16 type II codebook is designed at the subband level and its FD transformation is performed between subbands. Therefore, it cannot acquire accurate delay information for each dominant path.

On the other hand, for uplink or downlink, different channel paths may have different angles of arrival (AoA) or angles of departure (AoD), respectively, on the gNB side. The SD transform in the rel.16 type II codebook selects L candidate SD beams for the polarization direction on the wideband level, so the candidate SD beams are common to all dominant channel paths and cannot reflect the exact AoA or AoD information for each dominant path in the Angle Domain (AD).

In summary, existing rel.16 type II codebooks cannot utilize SD transforms and FD transforms, respectively, to determine accurate angle and delay information for each dominant channel path. Therefore, the angle and delay FDD DL/UL reciprocity cannot be used properly in type II CSI to reduce the corresponding feedback overhead.

Some embodiments described herein may provide CSI feedback enhancement that delineates per-path angle and delay information. For example, some embodiments may provide a new codebook design in which accurate angle and delay information may be obtained for each dominant channel path using SD and FD transforms, respectively. In particular, certain embodiments may provide at least the following operations for CSI feedback design: 1) The UE may perform an FD transform at the subcarrier level using an inverse fast fourier transform (ift) operation according to the current channel measurement matrix to determine a dominant channel path and a corresponding delay; 2) The UE may determine angle information (e.g., aoA or AoD) for each dominant channel path using an SD transform; and 3) after FD and SD transforms, the UE may reduce the channel matrix in its dimension and the UE may quantize the Linear Combination (LC) coefficients for feedback.

In this way, certain embodiments related to the proposed CSI scheme may have, for example, system performance gain as compared to rel.16 type II CSI, while reducing feedback overhead. Since the payloads of SD and FD transforms in the new CSI scheme may be larger than in rel.16 type II CSI, it is expected that the payloads of CSI schemes according to some embodiments may be further reduced when FDD reciprocity is used for CSI feedback in rel.17. Certain embodiments utilizing the CSI designs described herein may more conveniently identify angle and delay information in CSI feedback items for future FDD reciprocity applications and may have the high potential for payload reduction capability.

Fig. 1 illustrates an example of Channel State Information (CSI) feedback enhancement depicting per-path angle and delay information, in accordance with some embodiments. Fig. 1 illustrates a UE and a network node (e.g., a gNB) in communication with each other.

Prior to the operation illustrated in fig. 1, the UE may acquire a channel measurement matrix. For example, the UE may obtain a channel measurement matrix in a downlink channel state information reference signal (CSI-RS) measurement. As illustrated at 100, the UE may use a fourier transform operation (e.g., an inverse fast fourier transform (ift) operation, a Discrete Fourier Transform (DFT) operation, or an Inverse Discrete Fourier Transform (iDFT) operation, etc.) at a frequency domain granularity (e.g., a subcarrier level for a channel matrix including a plurality of subcarriers, a resource block level for a channel matrix including a plurality of resource blocks, or a resource block level for a channel matrix including a plurality of resource blocksSub-band level of a channel matrix comprising a plurality of sub-bands, etc.), frequency Domain (FD) transformation is performed on the channel measurement matrix. For example, the UE may transform the channel measurement matrix into a Time Domain (TD) channel matrix to form a first transformed channel matrix (e.g., which may have the same size as the FD channel measurement matrix). Assuming, for example, FD channel measurement matrix H _FD In dimension N in downlink CSI-RS measurement _p ×N _f Is acquired, wherein N _f May be the number of active subcarriers, N _p ＝N _rx ×N _tx May be the number of channel pairs, each channel pair linking a transmit antenna port and a receive antenna port, N _tx May be the number of transmit antenna ports, and N _rx May be the number of receive antenna ports.

FD channel measurement matrix H _FD It is possible to use a matrix having N in the second dimension of the matrix _f The iFFT operation of the individual points is transformed into a first transformed channel matrix H ₁ 。H ₁ May have N _p ×N _f Is a dimension of (c).

As illustrated at 102, the UE may determine one or more dominant channel paths and corresponding delays based on the first transformed channel matrix. For example, the UE may select one or more dominant channel paths from the first transformed channel matrix (e.g., according to an Orthogonal Matching Pursuit (OMP) search rule) to form a second transformed channel matrix (e.g., that includes only dominant channel paths in the TD). Selection pair N taking into account dominant channel path _p The individual channel pairs may be common, N _path The dominant channel paths may be derived from the first transformed channel matrix H in its second dimension according to OMP search rules ₁ Is selected from the group consisting of a plurality of combinations of the above. In [1, N _f ]The position of each channel path within may represent the delay of the path to some extent. After FD transformation and selection of one or more dominant channel paths, a second transformed channel matrix H ₂ Can be shown as follows:

as illustrated at 104, the UE may determine angle information (e.g., angle of arrival (AoA), angle of departure (AoD), and/or the like on the gNB side) for each of the one or more dominant channel paths using a Spatial Domain (SD) transform of the second transformed channel matrix. For example, the UE may reshape, for a dominant channel path of the one or more dominant channel paths, a corresponding column vector of the second transformed channel matrix into a matrix having a size of a number of receive antenna ports multiplied by a number of transmit antenna ports. For channel path i, a second transformed channel matrix H ₂ May be reshaped to have N _rx ×N _tx Matrix H of the size of (2) ₂ (i) A. The invention relates to a method for producing a fibre-reinforced plastic composite The UE may determine angle information based on the matrix in a second dimension of the matrix (e.g., the angle information may be common to different receive antenna ports). For example, the AoA or AoD of channel path i may be in its second dimension according to matrix H ₂ (i) Is determined and may be common to different receive antenna ports.

It is assumed that the configuration of a two-dimensional (2-D) antenna port, for example, on the gNB side can be defined in each polarization by (N _1, N ₂ ) Expression, where N ₁ And N ₂ The number of antenna ports in the horizontal and vertical dimensions, respectively, and they may be defined by N _tx ＝2×N ₁ ×N ₂ Satisfying the following conditions. The azimuth of channel path i in the horizontal dimension may be set to

And zenith angle in the vertical dimension may be set to θ _i . The AoA or AoD information may include azimuth and zenith angles. The two-dimensional transmit antenna vector may have the following:

for l=1, …, N ₁

For k=1, …, N ₂

Wherein:

and->

Is the transmit antenna vector for channel path i in the horizontal and vertical dimensions. Transmitting antenna vector w _i May be the Kronecker product between the vertical and horizontal vectors for channel path i, i.e.,

the antenna spacing may be defined by d in the horizontal and vertical dimensions, respectively _H And d _V Given. Lambda may be a wavelength.

According to the above, aoA or AoD may be included in the transmit antenna vector w _i It may also be represented as an oversampled DFT vector. The UE may search for a Discrete Fourier Transform (DFT) vector to match the matrix in the second dimension and represent angle information (e.g., where the angle information may be different for each of the one or more dominant channel paths and/or where the angle information may be different for each polarization of the dominant channel paths). For example, the UE may search for the best DFT vector w _i To communicate with the channel matrix H in a second dimension ₂ (i) The properties of AoA or AoD for channel path i are matched and plotted in one polarization. This may be an SD transform by which the third transformed channel matrix H ₃ May be formed from the second transformed channel matrix and may include the determined angle information in an angle domain. SD transform matrix W for channel path i _i Can be expressed by the following formula:

for channel path i, the third transformed channel matrix may be composed of H ₃ (i) Expressed and can be calculated as follows:

H ₃ (i)＝H ₂ (i)×W _i

the UE may calculate a set of linear combination coefficients for the third transformed channel matrix at 106. For example, the UE may quantize the linear combination coefficients. After the FD transform process and the SD transform process, the channel matrix H ₃ (i) There may be only N for each channel path _rx X 2 Linear Combination (LC) coefficients. The UE may provide for uplink Channel State Information (CSI) feedback at 108: feedback of delay per path (e.g., delay information) using at least one Frequency Domain (FD) transform, feedback of angle per path (e.g., angle information) using at least one Spatial Domain (SD) transform, at least one bitmap of a set of linear combination coefficients, at least one indication of at least one particular linear combination coefficient, at least one calculation of a set of non-zero linear combination coefficients, and/or the like. For feedback per path delay using FD transformation, assume the feedback at N _f After the point iFFT operation, N _path The individual dominant channel paths are selected according to OMP search rules. In this case, the indication of the delay per path may be costly

Bits are used for feedback.

For per-path angle feedback using SD transforms, aoA or AoD for each channel path may refer to azimuth and zenith angles of polarization in horizontal and vertical dimensions, respectively. This may be represented as an oversampled DFT vector. Feedback per path angle can be costly in total

Of bits, where N ₁ And N ₂ Can be respectivelyThe number of antenna ports in the horizontal and vertical dimensions, and O ₁ And O ₂ May be an oversampling rate in the corresponding dimension.

For bitmaps of sets of LC coefficients, after FD transform process and SD transform process, N _path The total of the individual dominant channel paths may have N _path ×N _rx X 2 LC coefficients. Maximum number of non-zero (NZ) LC coefficients K ₀ May be a parameter of a Radio Resource Control (RRC) configuration, where K ₀ ≤N _path ×N _rx X 2. The bitmap may utilize N _path ×N _rx X 2 bits, which may indicate a type for each of the LC coefficients. For example, "1" may represent an NZ coefficient, and "0" may represent a zero coefficient.

For the indication of the strongest LC coefficient, the index of the strongest LC coefficient may be used

A number of bits to signal. For quantization of NZ LC coefficients, there may be K in total ₀ The NZ LC coefficients, which may be signaled in terms of amplitude and phase quantization. The strongest LC coefficient may have a different quantization bit length and quantization set than the other LC coefficients.

As illustrated at 108, the network node may receive CSI feedback for each of the one or more dominant channel paths. CSI feedback may include delay information for each of the one or more dominant paths, angle information for each of the one or more dominant paths, at least one linear combination coefficient (e.g., a bitmap of a set of linear combination coefficients, an indication of a particular linear combination coefficient, calculation of a set of non-zero linear combination coefficients, etc.), and/or the like. As illustrated at 110, the network node may construct a first recovered channel matrix based on CSI feedback. For example, the network node may construct a first recovered channel matrix for each of the one or more dominant paths based on a set of linear combination coefficients.

As illustrated at 112, the network node may perform a reverse Spatial Domain (SD) transform on the first recovered channel matrix to form a second recovered channel matrix in Spatial Domain (SD). For example, the network node may perform a reverse Spatial Domain (SD) transform from angle information to spatial information on the first recovered channel matrix using angle feedback for each of the one or more dominant paths. As illustrated at 114, the network node may perform an inverse Frequency Domain (FD) transform on the second recovered channel matrix to form a third recovered channel matrix in the Frequency Domain (FD). For example, the network node may perform an inverse Frequency Domain (FD) transformation from delay information to Frequency Domain (FD) information on the at least one second recovered channel matrix using delay feedback for each of the one or more dominant paths. As illustrated at 116, the network node may use the third recovered channel matrix for one or more actions including, for example, scheduling or precoding for downlink transmissions.

As described above, according to some embodiments, in each feedback instance, the UE may first perform FD transformation on a subcarrier level, according to a current channel measurement matrix, using an ift operation to determine a dominant channel path and corresponding delay. The UE may then determine angle information (e.g., aoA or AoD) for each dominant channel path using an SD transform. After FD and SD transforms, the channel matrix may be reduced in its dimension and its LC coefficients may be quantized for feedback.

According to some embodiments, CSI may use some payloads for feedback of SD transforms and FD transforms. When FDD reciprocity is used for CSI feedback and reporting of SD transforms and FD transforms is not required, the payload of some embodiments may be reduced compared to rel.16 type II CSI. In addition, certain embodiments may provide a system performance gain as compared to rel.16 type II CSI, while adjusting the number of NZ LC coefficients K ₀ When it can further reduce the feedback overhead. Since the payloads of SD and FD transforms in Rel.17CSI may be greater than in Rel.16 type II CSI, certain embodiments may further reduce the payload of CSI when FDD reciprocity is used for CSI feedback And (5) loading. CSI designs according to some embodiments may more conveniently identify angle and delay information in CSI feedback items for future FDD reciprocity applications and may have high potential for payload reduction.

As described above, fig. 1 is provided as an example. Other examples are possible according to some embodiments.

FIG. 2 illustrates an example flow chart of a method according to some embodiments. For example, fig. 2 illustrates example operations of a UE (e.g., apparatus 20). Some of the operations illustrated in fig. 2 may be similar to some of the operations shown in fig. 1 and described with respect to fig. 1.

In one embodiment, the method may include: at 200, at least one Frequency Domain (FD) transformation is performed or performed on at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation. In one embodiment, the method may include: at 202, one or more dominant channel paths and corresponding delays are determined based on at least one first transformed channel matrix. In one embodiment, the method may include: at 204, angle information is determined for each of the one or more dominant channel paths using at least one Spatial Domain (SD) transform of the at least one second transformed channel matrix. In one embodiment, the method may include: at 206, at least one linear combination coefficient is calculated for the at least one third transformed channel matrix.

In some embodiments, the method may include: at least one channel measurement matrix is acquired in at least one downlink channel state information reference signal (CSI-RS) measurement before performing at least one Frequency Domain (FD) transformation. In some embodiments, performing at least one Frequency Domain (FD) transform may further include: at least one channel measurement matrix is transformed into at least one Time Domain (TD) channel matrix to form at least one first transformed channel matrix. In some embodiments, determining one or more dominant channel paths may further comprise: one or more dominant channel paths are selected from the at least one first transformed channel matrix to form at least one second transformed channel matrix.

In some embodiments, the angle information may identify at least one departure angle. In some embodiments, determining the angle information may further include: at least one corresponding column vector of the at least one second transformed channel matrix is reshaped into at least one matrix for at least one of the one or more dominant channel paths, the at least one matrix having the size of the number of receive antenna ports multiplied by the number of transmit antenna ports. In some embodiments, determining the angle information may further include: in a second dimension of the at least one matrix, angle information is determined based on the at least one matrix. The angle information may be common to different receive antenna ports.

In some embodiments, determining the angle information may include: at least one discrete fourier transform vector is searched to match at least one matrix in a second dimension and to represent angle information. The angle information may be different for each of the one or more dominant channel paths, or for each polarization of the dominant channel paths of the one or more dominant channel paths. In some embodiments, the method may further comprise: for uplink Channel State Information (CSI) feedback, at least one of: feedback of delay per path using at least one Frequency Domain (FD) transform, feedback of angle per path using at least one Spatial Domain (SD) transform, at least one bitmap of at least one linear combination coefficient, at least one indication of at least one particular linear combination coefficient, or at least one calculation of at least one non-zero linear combination coefficient.

As described above, fig. 2 is provided as an example. Other examples are possible according to some embodiments.

FIG. 3 illustrates an example flow chart of a method according to some embodiments. For example, fig. 3 illustrates example operations of a network node (e.g., apparatus 10). Some of the operations illustrated in fig. 3 may be similar to some of the operations shown in fig. 1 and described with respect to fig. 1.

In one embodiment, the method may include: at 300, channel State Information (CSI) feedback is received for each of one or more dominant channel paths. In one embodiment, the method may include: at 302, at least one first recovered channel matrix is constructed based on Channel State Information (CSI) feedback. In one embodiment, the method may include: at 304, at least one inverse Spatial Domain (SD) transform is performed or performed on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD). In one embodiment, the method may include: at 306, at least one inverse Frequency Domain (FD) transform is performed or performed on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD). In one embodiment, the method may include: at 308, the third recovered channel matrix is used for one or more actions, the one or more actions including scheduling or precoding for downlink transmissions.

In some embodiments, channel State Information (CSI) feedback may comprise at least one of: delay information for each of the one or more dominant paths, angle information for each of the one or more dominant paths, or at least one linear combination coefficient. In some embodiments, constructing the at least one first recovered channel matrix may further comprise: at least one first recovered channel matrix is constructed for each of the one or more dominant paths based on the one or more linear combination coefficients. In some embodiments, performing at least one inverse Spatial Domain (SD) transform may further comprise: at least one reverse Spatial Domain (SD) transform from angular information to spatial information is performed on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant paths. In some embodiments, performing at least one inverse Frequency Domain (FD) transform may further include: at least one inverse Frequency Domain (FD) transformation from delay information to Frequency Domain (FD) information is performed on the at least one second recovered channel matrix using delay feedback for each of the one or more dominant paths.

As described above, fig. 3 is provided as an example. Other examples are possible according to some embodiments.

Fig. 4a illustrates an example of an apparatus 10 according to one embodiment. In one embodiment, the apparatus 10 may be a node, host, or server in a communication network or serving such a network. For example, the apparatus 10 may be a network node (e.g., including a RAN node, an AMF node, an AUSF node, a UDM node, a UDR node, a captive portal, an HSS, and/or the like), a satellite, a base station, a node B, an evolved node B (eNB), a 5G node B or access point, a next generation node B (NG-NB or gNB), and/or a WLAN access point) associated with a radio access network such as an LTE network, 5G, or NR. In an example embodiment, the apparatus 10 may be an eNB in LTE or a gNB in 5G.

It should be appreciated that in some example embodiments, the apparatus 10 may comprise an edge cloud server as a distributed computing system in which the server and radio node may be separate devices that communicate with each other via a radio path or via a wired connection, or they may be located in the same entity that communicates via a wired connection. For example, in some example embodiments where apparatus 10 represents a gNB, it may be configured with a Central Unit (CU) and Distributed Unit (DU) architecture that partitions gNB functions. In such an architecture, a CU may be a logical node including gNB functions such as transmission of user data, mobility control, radio access network sharing, positioning, and/or session management, etc. The CU may control the operation of the DU(s) through the forwarding interface. Depending on the function tear down option, the DU may be a logical node that includes a subset of the gNB functions. It should be noted that one of ordinary skill in the art will appreciate that the apparatus 10 may include components or features not shown in fig. 4 a.

As illustrated in the example of fig. 4a, the apparatus 10 may include a processor 12 for processing information and executing instructions or operations. The processor 12 may be any type of general purpose or special purpose processor. In practice, the processor 12 may include one or more of a general purpose computer, a special purpose computer, a microprocessor, a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), and a processor based on a multi-core processor architecture, as examples. Although a single processor 12 is shown in fig. 4a, multiple processors may be utilized according to other embodiments. For example, it should be understood that in some embodiments, apparatus 10 may include two or more processors, which may form a multiprocessor system (e.g., processor 12 may represent multiple processors in this case), which may support multiple processing. In some embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

Processor 12 may perform functions associated with the operation of apparatus 10, which may include, for example, precoding of antenna gain/phase parameters, encoding and decoding of the various bits forming the communication message, formatting of information, and overall control of apparatus 10, including processes related to management of communication resources.

The apparatus 10 may also include or be coupled to a memory 14 (internal or external), the memory 14 may be coupled to the processor 12 for storing information and instructions executable by the processor 12. Memory 14 may be one or more memories and of any type suitable to the local application environment and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and/or removable memory. For example, memory 14 may include any combination of Random Access Memory (RAM), read Only Memory (ROM), static memory (such as a magnetic or optical disk), a Hard Disk Drive (HDD), or any other type of non-transitory machine or computer readable medium. The instructions stored in the memory 14 may include program instructions or computer program code that, when executed by the processor 12, enable the apparatus 10 to perform tasks as described herein.

In one embodiment, the apparatus 10 may also include or be coupled to a (internal or external) drive or port configured to accept and read external computer-readable storage media, such as an optical disk, USB drive, flash drive, or any other storage medium. For example, an external computer readable storage medium may store computer programs or software for execution by processor 12 and/or apparatus 10.

In some embodiments, the apparatus 10 may also include or be coupled to one or more antennas 15 for transmitting signals and/or data to the apparatus 10 and receiving signals and/or data from the apparatus 10. The apparatus 10 may also include or be coupled to a transceiver 18 configured to transmit and receive information. The transceiver 18 may include a plurality of radio interfaces that may be coupled to the antenna(s) 15, for example. The radio interface may correspond to a plurality of radio access technologies, including one or more of the following: GSM, NB-IoT, LTE, 5G, WLAN, bluetooth, BT-LE, NFC, radio Frequency Identifier (RFID), ultra Wideband (UWB), multewire, etc. The radio interface may include components such as filters, converters (e.g., digital-to-analog converters, etc.), mappers, fast Fourier Transform (FFT) modules, etc., to generate symbols for transmission via one or more downlinks and to receive symbols (e.g., via an uplink).

As such, transceiver 18 may be configured to modulate information onto a carrier waveform for transmission by antenna(s) 15, and demodulate information received via antenna(s) 15 for further processing by other elements of apparatus 10. In other embodiments, the transceiver 18 may be capable of directly transmitting and receiving signals or data. Additionally or alternatively, in some embodiments, the apparatus 10 may include input and/or output devices (I/O devices).

In one embodiment, memory 14 may store software modules that provide functionality when executed by processor 12. These modules may, for example, include an operating system that provides operating system functionality for the device 10. The memory may also store one or more functional modules, such as applications or programs, that provide additional functionality for the apparatus 10. The components of apparatus 10 may be implemented in hardware, or as any suitable combination of hardware and software.

According to some embodiments, the processor 12 and the memory 14 may be included in, or form part of, processing circuitry or control circuitry. Additionally, in some embodiments, transceiver 18 may be included in, or form part of, transceiver circuitry.

As used herein, the term "circuitry" may refer to a hardware-only circuitry implementation (e.g., analog and/or digital circuitry), a combination of hardware circuitry and software, a combination of analog and/or digital hardware circuitry and software, any portion of a hardware processor(s) (including digital signal processors) with software that works together to cause a device (e.g., device 10) to perform various functions, and/or a hardware circuit(s) and/or processor(s), or portions thereof, that use software for operation, but software may not be present when software is not required for operation. As a further example, as used herein, the term "circuitry" may also cover an implementation of only a hardware circuit or processor (or processors), or a portion of a hardware circuit or processor, and its accompanying software and/or firmware. The term circuitry may also cover, for example, a baseband integrated circuit in a server, a cellular network node or device, or other computing or network device.

As introduced above, in some embodiments, the apparatus 10 may be a network node or RAN node, such as a base station, an access point, a node B, eNB, gNB, WLAN access point, or the like.

According to some embodiments, the apparatus 10 may be controlled by the memory 14 and the processor 12 to perform functions associated with any of the embodiments described herein, such as some operations of the flowcharts or signaling diagrams illustrated in fig. 1-3.

For example, in one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to: channel State Information (CSI) feedback is received for each of the one or more dominant channel paths. In one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to: at least one first recovered channel matrix is constructed based on Channel State Information (CSI) feedback. In one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to: at least one inverse Spatial Domain (SD) transform is performed or performed on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD). In one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to: at least one inverse Frequency Domain (FD) transformation is performed or performed on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD). In one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to: the third recovered channel matrix is used for one or more actions including scheduling or precoding for downlink transmissions.

Fig. 4b illustrates an example of an apparatus 20 according to another embodiment. In one embodiment, the apparatus 20 may be a node or element in or associated with a communication network, such as a UE, mobile Equipment (ME), mobile station, mobile device, fixed device, ioT device, or other device. As described herein, a UE may alternatively be referred to as, for example, a mobile station, mobile equipment, mobile unit, mobile device, user equipment, subscriber station, wireless terminal, tablet, smart phone, ioT device, sensor, NB-IoT device, or the like. As one example, the apparatus 20 may be implemented in, for example, a wireless handheld device, a wireless plug-in accessory, or the like.

In some example embodiments, the apparatus 20 may include one or more processors, one or more computer-readable storage media (e.g., memory, storage, etc.), one or more radio access components (e.g., modem, transceiver, etc.), and/or a user interface. In some embodiments, apparatus 20 may be configured to operate using one or more radio access technologies, such as GSM, LTE, LTE-A, NR, 5G, WLAN, wiFi, NB-IoT, bluetooth, NFC, multeFire, and/or any other radio access technology. It should be noted that one of ordinary skill in the art will appreciate that the apparatus 20 may include components or features not shown in fig. 4 b.

As illustrated in the example of fig. 4b, the apparatus 20 may include or be coupled to a processor 22 for processing information and performing instructions or operations. The processor 22 may be any type of general purpose or special purpose processor. In practice, the processor 22 may include one or more of a general purpose computer, a special purpose computer, a microprocessor, a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), and a processor based on a multi-core processor architecture, as examples. Although a single processor 22 is shown in fig. 4b, multiple processors may be utilized according to other embodiments. For example, it should be understood that in some embodiments, apparatus 20 may comprise two or more processors, which may form a multiprocessor system (e.g., processor 22 may represent a multiprocessor in this case), which may support multiprocessing. In some embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

Processor 22 may perform functions associated with the operation of apparatus 20 including, as some examples, precoding of antenna gain/phase parameters, encoding and decoding of the various bits forming the communication message, formatting of information, and overall control of apparatus 20 including processes related to management of communication resources.

The apparatus 20 may also include or be coupled to a memory 24 (internal or external), the memory 24 may be coupled to the processor 22 for storing information and instructions executable by the processor 22. Memory 24 may be one or more memories and of any type suitable to the local application environment and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and/or removable memory. For example, the memory 24 may include any combination of Random Access Memory (RAM), read Only Memory (ROM), static memory (such as a magnetic or optical disk), a Hard Disk Drive (HDD), or any other type of non-transitory machine or computer readable medium. The instructions stored in the memory 24 may include program instructions or computer program code that, when executed by the processor 22, enable the apparatus 20 to perform the tasks described herein.

In one embodiment, the apparatus 20 may also include or be coupled to a (internal or external) drive or port configured to accept and read external computer-readable storage media, such as an optical disk, USB drive, flash drive, or any other storage medium. For example, an external computer readable storage medium may store computer programs or software for execution by processor 22 and/or apparatus 20.

In some embodiments, apparatus 20 may further comprise or be coupled to one or more antennas 25 for receiving downlink signals and for transmission from apparatus 20 via the uplink. The apparatus 20 may also include a transceiver 28 configured to transmit and receive information. Transceiver 28 may also include a radio interface (e.g., a modem) coupled to antenna 25. The radio interface may correspond to a plurality of radio access technologies, including one or more of the following: GSM, LTE, LTE-A, 5G, NR, WLAN, NB-IoT, bluetooth, BT-LE, NFC, RFID, UWB, etc. The radio interface may include other components such as filters, converters (e.g., digital-to-analog converters, etc.), symbol demappers, signal shaping components, inverse Fast Fourier Transform (IFFT) modules, etc., to process symbols carried by the downlink or uplink, such as OFDMA symbols.

For example, transceiver 28 may be configured to modulate information onto a carrier wave for transmission by antenna(s) 25, and demodulate information received via antenna(s) 25 for further processing by other elements of apparatus 20. In other embodiments, transceiver 28 may be capable of directly transmitting and receiving signals or data. Additionally or alternatively, in some embodiments, apparatus 20 may include input and/or output devices (I/O devices). In some embodiments, the apparatus 20 may also include a user interface, such as a graphical user interface or a touch screen.

In one embodiment, memory 24 stores software modules that provide functionality when executed by processor 22. These modules may include, for example, an operating system that provides operating system functionality for device 20. The memory may also store one or more functional modules, such as applications or programs, that provide additional functionality for apparatus 20. The components of apparatus 20 may be implemented in hardware, or as any suitable combination of hardware and software. According to an example embodiment, apparatus 20 may optionally be configured to communicate with apparatus 10 via a wireless or wired communication link 70 according to any radio access technology (such as NR).

According to some embodiments, the processor 22 and the memory 24 may be included in, or form part of, processing circuitry or control circuitry. Additionally, in some embodiments, transceiver 28 may be included in, or may form part of, transceiver circuitry.

As discussed above, according to some embodiments, the apparatus 20 may be, for example, a UE, a mobile device, a mobile station, an ME, an IoT device, and/or an NB-IoT device. According to some embodiments, the apparatus 20 may be controlled by the memory 24 and the processor 22 to perform the functions associated with the example embodiments described herein. For example, in some embodiments, apparatus 20 may be configured to perform one or more of the processes depicted in any of the flowcharts or signaling diagrams described herein (such as those illustrated in fig. 1-3).

For example, in one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to: at least one Frequency Domain (FD) transformation is performed or performed on at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation. In one embodiment, the apparatus 20 may be controlled by the memory 24 and the processor 22 to: one or more dominant channel paths and corresponding delays are determined based on the at least one first transformed channel matrix. In one embodiment, the apparatus 20 may be controlled by the memory 24 and the processor 22 to: angle information is determined for each of the one or more dominant channel paths using at least one Spatial Domain (SD) transform of the at least one second transformed channel matrix. In one embodiment, the apparatus 20 may be controlled by the memory 24 and the processor 22 to: at least one linear combination coefficient is calculated for at least one third transformed channel matrix.

Accordingly, certain example embodiments provide several technical improvements, enhancements, and/or advantages over existing technical processes. For example, one benefit of some example embodiments is system performance gain and reduced feedback overhead. Thus, the use of some example embodiments results in improved functionality of the communication networks and their nodes, and thus constitutes, among other things, at least an improvement in the art of UE-network node feedback signaling.

In some example embodiments, the functionality of any of the methods, processes, signaling diagrams, algorithms, or flowcharts described herein may be implemented by software and/or computer program code or portions of code stored in a memory or other computer-readable or tangible medium and executed by a processor.

In some example embodiments, an apparatus may be included in or associated with at least one software application, module, unit, or entity configured to perform arithmetic operation(s), or a program or portion thereof (including added or updated software routines), by at least one operating processor. Programs (also referred to as program products or computer programs, including software routines, applets, and macros) may be stored in any apparatus-readable data storage medium and may include program instructions to perform particular tasks.

The computer program product may include one or more computer-executable components configured to perform some example embodiments when the program is run. One or more of the computer-executable components may be at least one software code or code portion. The modifications and configurations required to implement the functionality of the example embodiments may be performed as routine(s), which may be implemented as added or updated software routine(s). In one example, the software routine(s) may be downloaded into the device.

By way of example, software or computer program code or code portions may be in source code form, object code form, or in some intermediate form, and it may be stored in some carrier, distribution medium, or computer readable medium, which may be any entity or device capable of carrying the program. Such carriers may include, for example, recording media, computer memory, read-only memory, electro-optical and/or electronic carrier signals, telecommunications signals, and/or software distribution packages. Depending on the processing power required, the computer program may be executed in a single electronic digital computer or it may be distributed among multiple computers. The computer readable medium or computer readable storage medium may be a non-transitory medium.

In other example embodiments, the functions may be performed by hardware or circuitry included in an apparatus (e.g., apparatus 10 or apparatus 20), such as through the use of an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or any other combination of hardware and software. In yet another example embodiment, the functionality may be implemented as a signal, such as an intangible means that may be carried by an electromagnetic signal downloaded from the internet or other network.

According to example embodiments, an apparatus (such as a node, device, or corresponding component) may be configured as circuitry, a computer, or a microprocessor (such as a single-chip computer element), or as a chipset, which may include at least memory to provide storage capacity for arithmetic operation(s), and/or an arithmetic processor to perform arithmetic operation(s).

The example embodiments described herein are equally applicable to both singular and plural implementations, whether singular or plural language is used in connection with describing certain embodiments. For example, embodiments describing the operation of a single network node are equally applicable to embodiments comprising multiple instances of a network node, and vice versa.

Those of ordinary skill in the art will readily appreciate that the example embodiments discussed above may be practiced with different order of operations and/or with hardware elements in different configurations than those disclosed. Thus, while some embodiments have been described based upon these exemplary preferred embodiments, it would be apparent to those of ordinary skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the example embodiments.

Claims

1. An apparatus for communication, comprising:

means for performing at least one Frequency Domain (FD) transformation on at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation to form at least one first transformed channel matrix;

means for determining one or more dominant channel paths based on the at least one first transformed channel matrix to form at least one second transformed channel matrix;

means for determining, for each of the one or more dominant channel paths, angle information using at least one Spatial Domain (SD) transform of the at least one second transformed channel matrix to form at least one third transformed channel matrix; and

means for calculating at least one linear combination coefficient for the at least one third transformed channel matrix.

2. The apparatus of claim 1, further comprising:

means for acquiring the at least one channel measurement matrix in at least one downlink channel state information reference signal (CSI-RS) measurement prior to performing the at least one Frequency Domain (FD) transformation.

3. The apparatus of claim 1, wherein the means for performing the at least one Frequency Domain (FD) transform further comprises:

means for transforming the at least one channel measurement matrix into at least one Time Domain (TD) channel matrix to form the at least one first transformed channel matrix.

4. The apparatus of claim 1, wherein the means for determining the one or more dominant channel paths further comprises:

means for selecting the one or more dominant channel paths from the at least one first transformed channel matrix to form the at least one second transformed channel matrix.

5. The apparatus of claim 1, wherein the angle information identifies at least one departure angle.

6. The apparatus of claim 5, wherein the means for determining the angle information further comprises:

means for reshaping at least one corresponding column vector of the at least one second transformed channel matrix for at least one of the one or more dominant channel paths into at least one matrix having the size of the number of receive antenna ports multiplied by the number of transmit antenna ports.

7. The apparatus of claim 6, wherein the means for determining the angle information further comprises:

means for determining the angle information based on the at least one matrix in a second dimension of the at least one matrix,

wherein the angle information is common to different receive antenna ports.

8. The apparatus of claim 7, wherein the means for determining the angle information comprises:

means for searching at least one discrete fourier transform vector to match the at least one matrix in the second dimension and to represent the angle information, wherein the angle information is different for each dominant channel path of the one or more dominant channel paths or for each polarization of a dominant channel path of the one or more dominant channel paths.

9. The apparatus of any one of claims 1-8, further comprising:

means for providing at least one of the following for uplink Channel State Information (CSI) feedback:

feedback per path delay using the at least one Frequency Domain (FD) transform,

feedback of the angle per path using the at least one Spatial Domain (SD) transform,

At least one bitmap of the at least one linear combination coefficient,

at least one indication of at least one particular linear combination coefficient, or

At least one calculation of at least one non-zero linear combination coefficient.

10. An apparatus for communication, comprising:

means for receiving Channel State Information (CSI) feedback for each of the one or more dominant channel paths;

means for constructing at least one first recovered channel matrix based on a set of linear combination coefficients comprised by the Channel State Information (CSI) feedback;

means for performing at least one inverse Spatial Domain (SD) transform on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant channel paths to form at least one second recovered channel matrix in Spatial Domain (SD);

means for performing at least one inverse Frequency Domain (FD) transformation on the at least one second recovered channel matrix using the delay feedback for each of the one or more dominant channel paths to form at least one third recovered channel matrix in the Frequency Domain (FD); and

Means for using the at least one third recovered channel matrix for one or more actions, the one or more actions including scheduling or precoding for downlink transmissions.

11. The apparatus of claim 10, wherein the Channel State Information (CSI) feedback comprises at least one of:

delay information for each of the one or more dominant paths,

angle information for each of the one or more dominant paths, or

At least one linear combination coefficient.

12. The apparatus of claim 10, wherein the means for constructing the at least one first recovered channel matrix further comprises:

means for constructing the at least one first recovered channel matrix for each of the one or more dominant paths based on one or more linear combination coefficients.

13. The apparatus of claim 10, wherein the means for performing the at least one inverse Spatial Domain (SD) transform further comprises:

means for performing the at least one inverse Spatial Domain (SD) transform from angular information to spatial information on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant paths.

14. The apparatus of any of claims 10-13, wherein the means for performing the at least one inverse Frequency Domain (FD) transform further comprises:

means for performing the at least one inverse Frequency Domain (FD) transformation from delay information to Frequency Domain (FD) information on the at least one second recovered channel matrix using delay feedback for each of the one or more dominant paths.

15. An apparatus for communication, comprising:

at least one processor; and

at least one memory including computer program code,

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:

performing at least one Frequency Domain (FD) transformation on the at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation to form at least one first transformed channel matrix;

determining one or more dominant channel paths based on the at least one first transformed channel matrix to form at least one second transformed channel matrix;

determining angle information for each of the one or more dominant channel paths using at least one Spatial Domain (SD) transform of the at least one second transformed channel matrix to form at least one third transformed channel matrix; and

At least one linear combination coefficient is calculated for the at least one third transformed channel matrix.

16. A method for communication, comprising:

determining one or more dominant channel paths based on the at least one first transformed channel measurement matrix to form at least one second transformed channel matrix;

17. A non-transitory computer readable medium comprising program instructions for causing an apparatus to at least:

18. An apparatus for communication, comprising:

at least one processor; and

at least one memory including computer program code,

receiving Channel State Information (CSI) feedback for each of the one or more dominant channel paths;

constructing at least one first recovered channel matrix based on a set of linear combination coefficients included in the Channel State Information (CSI) feedback;

performing at least one inverse Spatial Domain (SD) transform on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant channel paths to form at least one second recovered channel matrix in Spatial Domain (SD);

Performing at least one inverse Frequency Domain (FD) transformation on the at least one second recovered channel matrix using delay feedback for each of the one or more dominant channel paths to form at least one third recovered channel matrix in the Frequency Domain (FD); and

the at least one third recovered channel matrix is used for one or more actions including scheduling or precoding for downlink transmissions.

19. A method for communication, comprising:

20. A non-transitory computer readable medium comprising program instructions for causing an apparatus to at least:

performing at least one inverse Spatial Domain (SD) transform on the at least one first recovered channel matrix using angular feedback for each of the one or more dominant channel paths to form at least one second recovered channel measurement matrix in Spatial Domain (SD);