WO2021155514A1

WO2021155514A1 - Channel state information (csi) feedback enhancement depicting per-path angle and delay information

Info

Publication number: WO2021155514A1
Application number: PCT/CN2020/074358
Authority: WO
Inventors: Hao Liu
Original assignee: Nokia Shanghai Bell Co., Ltd.; Nokia Solutions And Networks Oy; Nokia Technologies Oy
Priority date: 2020-02-05
Filing date: 2020-02-05
Publication date: 2021-08-12
Also published as: CN113508538B; CN113508538A

Abstract

Systems, methods, apparatuses, and computer program products described herein may provide CSI feedback enhancement depicting per-path angle and delay information. For instance, some embodiments may provide a new codebook design, in which the exact angle and delay information can be acquired for each dominant channel path exploiting spatial domain (SD) and frequency domain (FD) transformation respectively. Specifically, certain embodiments may provide at least the following operations for CSI feedback design: 1) a UE may perform FD transformation using a Fourier transform operation according to the current channel measurement matrix in a subcarrier level to determine the dominant channel paths and the corresponding delays; 2) the UE may determine the angle information for each dominant channel path exploiting SD transformation; and 3) after FD and SD transformation, the UE may reduce the channel matrix in its dimension, and the UE may quantize linear combination (LC) coefficients for feedback.

Description

CHANNEL STATE INFORMATION (CSI) FEEDBACK ENHANCEMENT DEPICTING PER-PATH ANGLE AND DELAY INFORMATION

FIELD:

Some example embodiments may generally relate 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 communications systems. For example, certain embodiments may relate to systems and/or methods for channel state information (CSI) feedback enhancement depicting per-path angle and delay information.

BACKGROUND:

Examples of mobile or wireless telecommunication systems may include the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN) , Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN) , LTE-Advanced (LTE-A) , MulteFire, LTE-A Pro, and/or fifth generation (5G) radio access technology or new radio (NR) access technology. 5G wireless systems refer to the next generation (NG) of radio systems and network architecture. 5G is mostly built on a new radio (NR) , but a 5G (or NG) network can also build on E-UTRA radio. It is estimated that NR may provide bitrates on the order of 10-20 Gbit/sor higher, and may support at least enhanced mobile broadband (eMBB) and ultra-reliable low-latency-communication (URLLC) as well as massive machine type communication (mMTC) . NR is expected to deliver extreme broadband and ultra-robust, low latency connectivity and massive networking to support the Internet of Things (IoT) . With IoT and machine-to-machine (M2M) communication becoming more widespread, there will be a growing need for networks that meet the needs of lower power, low data rate, and long battery life. It is noted that, in 5G, the nodes that can provide radio access functionality to a user equipment (i.e., similar to Node B in UTRAN or eNB in LTE) may be named gNB when built on NR radio and may be named NG-eNB when built on E-UTRA radio.

SUMMARY:

According to a first embodiment, a method may include carrying out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation. The method may include determining one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix. The method may include determining angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix. The method may include computing at least one linear combination coefficient for at least one third transformed channel matrix.

In a variant, the method may include acquiring the at least one channel measurement matrix across at least one downlink channel state information reference signal (CSI-RS) measurement prior to carrying out the at least one frequency domain (FD) transformation. In a variant, carrying out the at least one frequency domain (FD) transformation may further comprise 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. In a variant, determining the one or more dominant channel paths may further comprise 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.

In a variant, the angle information may identify at least one angle of departure. In a variant, determining the angle information may further comprise reshaping, for at least one dominant channel path of the one or more dominant channel paths, at least one corresponding column vector of the at least one second transformed channel matrix as at least one matrix with a size of a number of receive antenna ports by a number of transmit antenna ports. In a variant, determining the angle information may further comprise determining the angle information based on the at least one matrix in a second dimension of the at least one matrix. The angle information may be common to different receive antenna ports.

In a variant, determining the angle information may comprise searching for 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 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. In a variant, the method may further comprise providing, for uplink channel state information (CSI) feedback, at least one of: feedback of per-path delays using the at least one frequency domain (FD) transformation, feedback of per-path angles using the at least one spatial domain (SD) transformation, 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 computation of at least one non-zero linear combination coefficient.

According to a second embodiment, a method may include receiving channel state information (CSI) feedback for each of one or more dominant channel paths. The method may include constructing at least one first recovered channel matrix based on the channel state information (CSI) feedback. The method may include carrying out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) . The method may include carrying out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) . The method may include using the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.

In a variant, the channel state information (CSI) feedback may include at least one of the following: 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 variant, constructing the at least one first recovered channel matrix may further comprise 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. In a variant, carrying out the at least one reverse spatial domain (SD) transformation may further comprise carrying out the at least one reverse spatial domain (SD) transformation from angle information to spatial information on the at least one first recovered channel matrix using angle feedback for each of the one or more dominant paths. In a variant, carrying out the at least one reverse frequency domain (FD) transformation may further comprise carrying out the at least one reverse 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.

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

A fourth embodiment may be directed to an apparatus that may include circuitry configured to perform the method according to the first embodiment or the second embodiment, or any of the variants discussed above.

A fifth embodiment may be directed to an apparatus that may include means for performing the method according to the first embodiment or the second embodiment, or any of the variants discussed above.

A 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 variants discussed above.

A seventh embodiment may be directed to a computer program product encoding instructions for performing at least the method according to the first embodiment or the second embodiment, or any of the variants discussed above.

BRIEF DESCRIPTION OF THE DRAWINGS:

For proper understanding of example embodiments, reference should be made to the accompanying drawings, wherein:

Fig. 1 illustrates an example of channel state information (CSI) feedback enhancement depicting per-path angle and delay information, according to some embodiments;

Fig. 2 illustrates an example flow diagram of a method, according to some embodiments;

Fig. 3 illustrates an example flow diagram 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, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of some example embodiments of systems, methods, apparatuses, 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 example embodiments described throughout this specification may be combined in any suitable manner in one or more example embodiments. For example, the usage 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 an embodiment may be included in 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. Additionally, as used herein, the phrase “set of” refers to a set comprising one or more of the referenced items. Accordingly, the phrases “set of, ” “at least one of, ” and “one or more of” can be used interchangeably.

Additionally, if desired, the 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 example embodiments, and not in limitation thereof.

One of the objectives on CSI enhancement is described as evaluating and, if needed, specifying Type II port selection codebook enhancement (based on Rel. 15/16 Type II port selection) , where information related to angle (s) and delay (s) are estimated at the gNB based on sounding reference signals (SRSs) by utilizing downlink/uplink (DL/UL) reciprocity of angle and delay. The remaining DL CSI is reported by the UE, mainly targeting frequency division duplex (FDD) frequency range 1 (FR1) to achieve better trade-off among UE complexity, performance, and reporting overhead.

Type II codebook design was introduced in Rel. 15 NR due to its superior performance gains over Rel-14 LTE. In the Rel. 16 NR phase, a frequency domain (FD) transformation technique was realized and specified in the Type II codebook to significantly reduce feedback overhead without performance loss. As NR is in the process of commercialization, there may be a need for more attention on real deployment scenarios. For example, partial reciprocity on channel statistics (including angle and delay) may be utilized for FR1 FDD CSI enhancement to achieve better trade-off among UE complexity, performance, and reporting overhead.

For Rel. 16 Type II codebook, there exists two kinds of transformation using discrete Fourier transformation (DFT) to reduce the number of CSI feedback elements, including FD transformation and spatial domain (SD) transformation. In general, a channel matrix can be transformed from a FD to a time domain (TD) exploiting FD transformation, which determines the dominant channel paths and the corresponding delays. But Rel. 16 Type II codebook is designed in the subband level, and its FD transformation is performed among multiple subbands. Thus, it cannot achieve the exact delay information for each dominant path.

On the other hand, different channel paths may have different angles of arrival (AoA) or angles of departure (AoD) in the gNB side for uplink or downlink, respectively. SD transformation in Rel. 16 Type II codebook selects L candidate SD beams for a polarization direction in a wideband level, so the candidate SD beams are common to all the dominant channel paths and cannot reflect the exact AoA or AoD information for each dominant path in an angle domain (AD) .

In summary, the existing Rel. 16 Type II codebook cannot determine the exact angle and delay information for each dominant channel path exploiting SD and FD transformation, respectively. Therefore, FDD DL/UL reciprocity of angle and delay cannot be properly used in Type II CSI to reduce the corresponding feedback overhead.

Some embodiments described herein may provide CSI feedback enhancement depicting per-path angle and delay information. For instance, some embodiments may provide a new codebook design, in which the exact angle and delay information can be acquired for each dominant channel path exploiting SD and FD transformation, respectively. Specifically, certain embodiments may provide at least the following operations for CSI feedback design: 1) a UE may perform FD transformation using an inverse fast Fourier transform (iFFT) operation according to the current channel measurement matrix in a subcarrier level to determine the dominant channel paths and the corresponding delays; 2) the UE may determine the angle information (e.g., AoA or AoD) for each dominant channel path exploiting SD transformation; and 3) after FD and SD transformation, the UE may reduce the channel matrix in its dimension, and the UE may quantize linear combination (LC) coefficients for feedback.

As such, certain embodiments related to the proposed CSI scheme may have, for example, system performance gain compared with Rel. 16 Type II CSI, while reducing feedback overhead. Since the payload of SD and FD transformation in the new CSI scheme may be larger than in Rel. 16 Type II CSI, it may be expected that when FDD reciprocity is used for CSI feedback in Rel. 17, the payload of the CSI scheme according to certain embodiments may be further reduced. Certain embodiments that utilize the CSI design described herein may be more convenient to identify angle and delay information in CSI feedback items for future FDD reciprocity application and may have high potential of payload reduction capability.

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

Prior to the operations illustrated in Fig. 1, the UE may acquire a channel measurement matrix. For example, the UE may acquire the channel measurement matrix across a downlink channel state information reference signal (CSI-RS) measurement. As illustrated at 100, the UE may carry out a frequency domain (FD) transformation on a channel measurement matrix in a frequency domain granularity (e.g., a subcarrier level for a channel matrix that comprises multiple subcarriers, a resource block level for a channel matrix that comprises multiple resource blocks, or a subband level for a channel matrix that comprises multiple subbands, etc. ) using a Fourier transform operation (e.g., an inverse fast Fourier transform (iFFT) operation, a discrete Fourier transform (DFT) operation, or an inverse discrete Fourier transform (iDFT) operation, etc. ) . 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 a FD channel measurement matrix) . Assume, for example, a FD channel measurement matrix H _FD is acquired across downlink CSI-RS measurement with the dimension of N _p×N _f, where N _f may be the number of active subcarriers, N _p=N _rx×N _tx may be the number of channel pairs each 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.

The FD channel measurement matrix H _FD may be transformed into the first transformed channel matrix H ₁ exploiting iFFT operation with N _f points in the second dimension of the matrix. H ₁ may have the dimension of N _p×N _f.

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 the one or more dominant channel paths from the first transformed channel matrix (e.g., according to an orthogonal matching pursuit (OMP) searching rule) to form a second transformed channel matrix (e.g., that comprises only the dominant channel paths in TD) . Considering that the selection of the dominant channel paths may be common to the N _p channel pairs, N _path dominant channel paths may be selected from the first transformed channel matrix H ₁ in its second dimension according to OMP searching rule. The location of each channel path within [1, N _f] may represent the delay of the path in some extent. After FD transformation and selection of the one or more dominant channel paths, the second transformed channel matrix H ₂ may 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 at the gNB side) for each of the one or more dominant channel paths using a spatial domain (SD) transformation on 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 as a matrix with a size of a number of receive antenna ports by a number of transmit antenna ports. For channel path i, i-th column vector of the second transformed channel matrix H ₂ may be reshaped as a matrix H ₂ (i) with the size of N _rx×N _tx. The UE may determine the 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 determined according to the matrix H ₂ (i) in its second dimension, and it may be common to different receive antenna ports.

Assume, for example, that the configuration of a 2-dimensional (2-D) antenna port in gNB side may be expressed by (N ₁, N ₂) in each polarization, where N ₁ and N ₂ are the number of antenna ports in the horizontal and vertical dimension, respectively, and that they may be satisfied by N _tx=2×N ₁×N ₂. The azimuth angle of channel path i may be set to

in a horizontal dimension and the zenith angle to θ _i in a vertical dimension. The AoA or AoD information may include the azimuth and zenith angles. Transmit antenna vectors of the two dimensions may have the following items:

for l=1, …, N ₁

for k=1, …, N ₂

where:

and

are the transmit antenna vectors for channel path i in the horizontal and vertical dimensions. Transmit antenna vector w _i may be the Kronecker product between vertical and horizontal vectors for channel path i, that is,

Antenna spacing may be given by d _H and d _V in the horizontal and vertical dimensions, respectively. λ may be the wavelength.

From the above, the AoA or AoD may be included in the transmit antenna vector w _i, which can also be represented as oversampled DFT vectors. The UE may search for a discrete Fourier transform (DFT) vector to match the matrix in the second dimension and to represent the 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 a dominant channel path) . For example, the UE may search for the best DFT vector w _i to match with the channel matrix H ₂ (i) in the second dimension and to depict the property of AoA or AoD for the channel path i in a polarization. This may be the SD transformation, by which a third transformed channel matrix H ₃ may be formed from the second transformed channel matrix and may comprise the determined angle information in an angle domain. The SD transformation matrix W _i for the channel path i may be expressed by:

For the channel path i, the third transformed channel matrix can be expressed by H ₃ (i) and may be calculated as follows:

H ₃ (i) =H ₂ (i) ×W _i

The UE may, at 106, compute a set of linear combination coefficients for the third transformed channel matrix. For example, the UE may quantize the linear combination coefficients. After the FD and SD transformation processes, the channel matrix H ₃ (i) may have only N _rx×2 linear combination (LC) coefficients for each channel path. The UE may, at 108, provide, for uplink channel state information (CSI) feedback, feedback of per-path delays using the at least one frequency domain (FD) transformation (e.g., delay information) , feedback of per-path angles using the at least one spatial domain (SD) transformation (e.g., angle information) , at least one bitmap of the set of linear combination coefficients, at least one indication of at least one particular linear combination coefficient, at least one computation of a set of non-zero linear combination coefficients, and/or the like. For Feedback of per-path delay using FD transformation, suppose that N _path dominant channel paths are selected according to OMP searching rule after N _f-point iFFT operation. In this case, the indication of per-path delay may cost

bits for feedback.

For Feedback of per-path angle using SD transformation, the AoA or AoD of each channel path may refer to the azimuth and zenith angles of a polarization in horizontal and vertical dimensions, respectively. This may be represented as oversampled DFT vectors. The feedback of per-path angle may cost

bits totally, where N ₁ and N ₂ may be the number of antenna ports in the horizontal and vertical dimensions, respectively, and O ₁ and O ₂ may be the oversampling rates in the corresponding dimensions.

For a bitmap of a set of LC coefficients, after the FD and SD transformation processes, N _path dominant channel paths may have N _path×N _rx×2 LC coefficients in total. The maximum number of non-zero (NZ) LC coefficients K ₀ may be a radio resource control (RRC) configured parameter, where K ₀≤N _path×N _rx×2. A bitmap may be defined with N _path×N _rx×2 bits, which may indicate the type for each of the LC coefficients. For example, “1” may denote a NZ coefficient and “0” may denote a zero coefficient.

For indication of the strongest LC coefficient, the index of the strongest LC coefficient may be signaled using

bits. For quantization of NZ LC coefficients, there may be, in total, K ₀ 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 from other LC coefficients.

As illustrated at 108, the network node may receive CSI feedback for each of the one or more dominant channel paths. The 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, or a computation 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 the CSI feedback. For example, the network node may construct the 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 carry out a reverse spatial domain (SD) transformation on the first recovered channel matrix to form a second recovered channel matrix in a spatial domain (SD) . For example, the network node may carry out the reverse spatial domain (SD) transformation 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 carry out a reverse frequency domain (FD) transformation on the second recovered channel matrix to form a third recovered channel matrix in a frequency domain (FD) . For example, the network node may carry out the reverse 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 comprising, for example, scheduling or precoding for downlink transmission.

As described above, according to certain embodiments, in each feedback instance, the UE may first carry out FD transformation using an iFFT operation according to the current channel measurement matrix in a subcarrier level to determine the dominant channel paths and the corresponding delays. The UE may then determine the angle information (e.g., AoA or AoD) for each dominant channel path exploiting SD transformation. After the FD and SD transformations, the channel matrix may be reduced in its dimension, and its LC coefficients may be quantized for feedback.

According to certain embodiments, CSI may use some payload for the feedback of the SD and FD transformations. When FDD reciprocity is used for CSI feedback and there is no need for reporting of SD and FD transformations, the payload of certain embodiments may be reduced compared to Rel. 16 Type II CSI. In addition, certain embodiments may provide system performance gain compared with Rel. 16 Type II CSI, while it can further reduce feedback overhead when adjusting the number of NZ LC coefficients K ₀. Since the payload of SD and FD transformations in Rel. 17 CSI may be larger than in Rel. 16 Type II CSI, certain embodiments, when FDD reciprocity is used for CSI feedback, may further reduce the payload of CSI. The CSI design according to certain embodiments may be more convenient to identify angle and delay information in CSI feedback items for future FDD reciprocity application and may have a 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 diagram of a method, according to some embodiments. For example, Fig. 2 shows example operations of a UE (e.g., apparatus 20) . Some of the operations illustrated in Fig. 2 may be similar to some operations shown in, and described with respect to, Fig. 1.

In an embodiment, the method may include, at 200, performing or carrying out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation. In an embodiment, the method may include, at 202, determining one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix. In an embodiment, the method may include, at 204, determining angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix. In an embodiment, the method may include, at 206, computing at least one linear combination coefficient for at least one third transformed channel matrix.

In some embodiments, the method may include acquiring the at least one channel measurement matrix across at least one downlink channel state information reference signal (CSI-RS) measurement prior to carrying out the at least one frequency domain (FD) transformation. In some embodiments, carrying out the at least one frequency domain (FD) transformation may further comprise 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. In some embodiments, determining the one or more dominant channel paths may further comprise 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.

In some embodiments, the angle information may identify at least one angle of departure. In some embodiments, determining the angle information may further comprise reshaping, for at least one dominant channel path of the one or more dominant channel paths, at least one corresponding column vector of the at least one second transformed channel matrix as at least one matrix with a size of a number of receive antenna ports by a number of transmit antenna ports. In some embodiments, determining the angle information may further comprise determining the angle information based on the at least one matrix in a second dimension of the at least one matrix. The angle information may be common to different receive antenna ports.

In some embodiments, determining the angle information may comprise searching for at least one discrete Fourier transform vector to match the at least one matrix in the second dimension and to represent the angle information. The angle information may be different for each 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. In some embodiments, the method may further comprise providing, for uplink channel state information (CSI) feedback, at least one of: feedback of per-path delays using the at least one frequency domain (FD) transformation, feedback of per-path angles using the at least one spatial domain (SD) transformation, 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 computation 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 diagram of a method, according to some embodiments. For example, Fig. 3 shows example operations of a network node (e.g., apparatus 10) . Some of the operations illustrated in Fig. 3 may be similar to some operations shown in, and described with respect to, Fig. 1.

In an embodiment, the method may include, at 300, receiving channel state information (CSI) feedback for each of one or more dominant channel paths. In an embodiment, the method may include, at 302, constructing at least one first recovered channel matrix based on the channel state information (CSI) feedback. In an embodiment, the method may include, at 304, performing or carrying out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) . In an embodiment, the method may include, at 306, performing or carrying out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) . In an embodiment, the method may include, at 308, using the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.

In some embodiments, the channel state information (CSI) feedback may include at least one of the following: 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 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. In some embodiments, carrying out the at least one reverse spatial domain (SD) transformation may further comprise carrying out the at least one reverse spatial domain (SD) transformation from angle information to spatial information on the at least one first recovered channel matrix using angle feedback for each of the one or more dominant paths. In some embodiments, carrying out the at least one reverse frequency domain (FD) transformation may further comprise carrying out the at least one reverse 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 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 an embodiment. In an embodiment, apparatus 10 may be a node, host, or server in a communications network or serving such a network. For example, apparatus 10 may be a network node (e.g., that comprises a RAN node, an AMF node, an AUSF node, a UDM node, a UDR node, a captive portal, a HSS, and/or the like) , satellite, base station, a Node B, an evolved Node B (eNB) , 5G Node B or access point, next generation Node B (NG-NB or gNB) , and/or a WLAN access point, associated with a radio access network, such as a LTE network, 5G or NR. In example embodiments, apparatus 10 may be an eNB in LTE or gNB in 5G.

It should be understood that, in some example embodiments, apparatus 10 may be comprised of an edge cloud server as a distributed computing system where the server and the radio node may be stand-alone apparatuses communicating with each other via a radio path or via a wired connection, or they may be located in a same entity communicating via a wired connection. For instance, in certain example embodiments where apparatus 10 represents a gNB, it may be configured in a central unit (CU) and distributed unit (DU) architecture that divides the gNB functionality. In such an architecture, the CU may be a logical node that includes gNB functions such as transfer of user data, mobility control, radio access network sharing, positioning, and/or session management, etc. The CU may control the operation of DU (s) over a front-haul interface. The DU may be a logical node that includes a subset of the gNB functions, depending on the functional split option. It should be noted that one of ordinary skill in the art would understand that apparatus 10 may include components or features not shown in Fig. 4a.

As illustrated in the example of Fig. 4a, apparatus 10 may include a processor 12 for processing information and executing instructions or operations. Processor 12 may be any type of general or specific purpose processor. In fact, processor 12 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) , field-programmable gate arrays (FPGAs) , application-specific integrated circuits (ASICs) , and processors based on a multi-core processor architecture, as examples. While 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 certain embodiments, apparatus 10 may include two or more processors that may form a multiprocessor system (e.g., in this case processor 12 may represent a multiprocessor) that may support multiprocessing. In certain 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 individual bits forming a communication message, formatting of information, and overall control of the apparatus 10, including processes related to management of communication resources.

Apparatus 10 may further include or be coupled to a memory 14 (internal or external) , which may be coupled to processor 12, for storing information and instructions that may be executed by 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 nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory. For example, memory 14 can be comprised of any combination of random access memory (RAM) , read only memory (ROM) , static storage such as a magnetic or optical disk, hard disk drive (HDD) , or any other type of non-transitory machine or computer readable media. The instructions stored in memory 14 may include program instructions or computer program code that, when executed by processor 12, enable the apparatus 10 to perform tasks as described herein.

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

In some embodiments, apparatus 10 may also include or be coupled to one or more antennas 15 for transmitting and receiving signals and/or data to and from apparatus 10. Apparatus 10 may further include or be coupled to a transceiver 18 configured to transmit and receive information. The transceiver 18 may include, for example, a plurality of radio interfaces that may be coupled to the antenna (s) 15. The radio interfaces may correspond to a plurality of radio access technologies including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, radio frequency identifier (RFID) , ultrawideband (UWB) , MulteFire, and the like. The radio interface may include components, such as filters, converters (for example, digital-to-analog converters and the like) , mappers, a Fast Fourier Transform (FFT) module, and the like, to generate symbols for a transmission via one or more downlinks and to receive symbols (for example, via an uplink) .

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

In an embodiment, memory 14 may store software modules that provide functionality when executed by processor 12. The modules may include, for example, an operating system that provides operating system functionality for apparatus 10. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for 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, processor 12 and memory 14 may be included in or may form a part of processing circuitry or control circuitry. In addition, in some embodiments, transceiver 18 may be included in or may form a part of transceiver circuitry.

As used herein, the term “circuitry” may refer to hardware-only circuitry implementations (e.g., analog and/or digital circuitry) , combinations of hardware circuits and software, combinations of analog and/or digital hardware circuits with software/firmware, any portions of hardware processor (s) with software (including digital signal processors) that work together to case an apparatus (e.g., apparatus 10) to perform various functions, and/or hardware circuit (s) and/or processor (s) , or portions thereof, that use software for operation but where the software may not be present when it is not needed for operation. As a further example, as used herein, the term “circuitry” may also cover an implementation of merely a hardware circuit or processor (or multiple processors) , or 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, cellular network node or device, or other computing or network device.

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

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

For instance, in one embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to receive channel state information (CSI) feedback for each of one or more dominant channel paths. In one embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to construct at least one first recovered channel matrix based on the channel state information (CSI) feedback. In one embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to perform or carry out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) . In one embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to perform or carry out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) . In one embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to use the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.

Fig. 4b illustrates an example of an apparatus 20 according to another embodiment. In an embodiment, apparatus 20 may be a node or element in a communications network or associated with such a network, such as a UE, mobile equipment (ME) , mobile station, mobile device, stationary 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 device, subscriber station, wireless terminal, tablet, smart phone, IoT device, sensor or NB-IoT device, or the like. As one example, apparatus 20 may be implemented in, for instance, a wireless handheld device, a wireless plug-in accessory, or the like.

In some example embodiments, apparatus 20 may include one or more processors, one or more computer-readable storage medium (for example, memory, storage, or the like) , one or more radio access components (for example, a modem, a transceiver, or the like) , 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 technologies. It should be noted that one of ordinary skill in the art would understand that apparatus 20 may include components or features not shown in Fig. 4b.

As illustrated in the example of Fig. 4b, apparatus 20 may include or be coupled to a processor 22 for processing information and executing instructions or operations. Processor 22 may be any type of general or specific purpose processor. In fact, processor 22 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) , field-programmable gate arrays (FPGAs) , application-specific integrated circuits (ASICs) , and processors based on a multi-core processor architecture, as examples. While 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 certain embodiments, apparatus 20 may include two or more processors that may form a multiprocessor system (e.g., in this case processor 22 may represent a multiprocessor) that may support multiprocessing. In certain 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 individual bits forming a communication message, formatting of information, and overall control of the apparatus 20, including processes related to management of communication resources.

Apparatus 20 may further include or be coupled to a memory 24 (internal or external) , which may be coupled to processor 22, for storing information and instructions that may be executed by 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 nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory. For example, memory 24 can be comprised of any combination of random access memory (RAM) , read only memory (ROM) , static storage such as a magnetic or optical disk, hard disk drive (HDD) , or any other type of non-transitory machine or computer readable media. The instructions stored in memory 24 may include program instructions or computer program code that, when executed by processor 22, enable the apparatus 20 to perform tasks as described herein.

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

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

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

In an embodiment, memory 24 stores software modules that provide functionality when executed by processor 22. The modules may include, for example, an operating system that provides operating system functionality for apparatus 20. The memory may also store one or more functional modules, such as an application or program, to 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 communications link 70 according to any radio access technology, such as NR.

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

As discussed above, according to some embodiments, apparatus 20 may be a UE, mobile device, mobile station, ME, IoT device and/or NB-IoT device, for example. According to certain embodiments, apparatus 20 may be controlled by memory 24 and processor 22 to perform the functions associated with 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 flow charts or signaling diagrams described herein, such as those illustrated in Figs. 1-3.

For instance, in one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to perform or carry out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to determine one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to determine angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on the at least one second transformed channel matrix. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to compute at least one linear combination coefficient for at least one third transformed channel matrix.

Therefore, certain example embodiments provide several technological improvements, enhancements, and/or advantages over existing technological processes. For example, one benefit of some example embodiments is system performance gain and reduced feedback overhead. Accordingly, the use of some example embodiments results in improved functioning of communications networks and their nodes and, therefore constitute an improvement at least to the technological field of UE-network node feedback signaling, among others.

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

In some example embodiments, an apparatus may be included or be associated with at least one software application, module, unit or entity configured as arithmetic operation (s) , or as a program or portions of it (including an added or updated software routine) , executed by at least one operation processor. Programs, also called 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.

A computer program product may include one or more computer-executable components which, when the program is run, are configured to carry out some example embodiments. The one or more computer-executable components may be at least one software code or portions of code. Modifications and configurations required for implementing functionality of an example embodiment may be performed as routine (s) , which may be implemented as added or updated software routine (s) . In one example, software routine (s) may be downloaded into the apparatus.

As an example, software or a computer program code or portions of code may be in a source code form, object code form, or in some intermediate form, and it may be stored in some sort of carrier, distribution medium, or computer readable medium, which may be any entity or device capable of carrying the program. Such carriers may include a record medium, computer memory, read-only memory, photoelectrical and/or electrical carrier signal, telecommunications signal, and/or software distribution package, for example. Depending on the processing power needed, the computer program may be executed in a single electronic digital computer or it may be distributed amongst a number of computers. The computer readable medium or computer readable storage medium may be a non-transitory medium.

In other example embodiments, the functionality may be performed by hardware or circuitry included in an apparatus (e.g., apparatus 10 or apparatus 20) , for example 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 a non-tangible means that can be carried by an electromagnetic signal downloaded from the Internet or other network.

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

Example embodiments described herein apply equally to both singular and plural implementations, regardless of whether singular or plural language is used in connection with describing certain embodiments. For example, an embodiment that describes operations of a single network node equally applies to embodiments that include multiple instances of the network node, and vice versa.

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

Claims

An apparatus, comprising:

means for carrying out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation;

means for determining one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix;

means for determining angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix; and

means for computing at least one linear combination coefficient for at least one third transformed channel matrix.
The apparatus according to claim 1, further comprising:

means for acquiring the at least one channel measurement matrix across at least one downlink channel state information reference signal (CSI-RS) measurement prior to carrying out the at least one frequency domain (FD) transformation.
The apparatus according to claims 1 or 2, wherein the means for carrying out the at least one frequency domain (FD) transformation 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.
The apparatus according to any of claims 1-3, 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.
The apparatus according to any of claims 1-4, wherein the angle information identifies at least one angle of departure.
The apparatus according to claim 5, wherein the means for determining the angle information further comprises:

means for reshaping, for at least one dominant channel path of the one or more dominant channel paths, at least one corresponding column vector of the at least one second transformed channel matrix as at least one matrix with a size of a number of receive antenna ports by a number of transmit antenna ports.
The apparatus according to 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.
The apparatus according to claim 7, wherein the means for determining the angle information comprises:

means for searching for 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 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.
The apparatus according to any of claims 1-8, further comprising:

means for providing, for uplink channel state information (CSI) feedback, at least one of:

feedback of per-path delays using the at least one frequency domain (FD) transformation,

feedback of per-path angles using the at least one spatial domain (SD) transformation,

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 computation of at least one non-zero linear combination coefficient.
An apparatus, comprising:

means for receiving channel state information (CSI) feedback for each of one or more dominant channel paths;

means for constructing at least one first recovered channel matrix based on the channel state information (CSI) feedback;

means for carrying out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) ;

means for carrying out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) ; and

means for using the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.
The apparatus according to claim 10, wherein the channel state information (CSI) feedback includes at least one of the following:

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.
The apparatus according to claims 10 or 11, 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.
The apparatus according to any of claims 10-12, wherein the means for carrying out the at least one reverse spatial domain (SD) transformation further comprises:

means for carrying out the at least one reverse spatial domain (SD) transformation from angle information to spatial information on the at least one first recovered channel matrix using angle feedback for each of the one or more dominant paths.
The apparatus according to any of claims 10-13, wherein the means for carrying out the at least one reverse frequency domain (FD) transformation further comprises:

means for carrying out the at least one reverse 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.
An apparatus, 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:

carry out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation;

determine one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix;

determine angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix; and

compute at least one linear combination coefficient for at least one third transformed channel matrix.
A method, comprising:

carrying out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation;

determining one or more dominant channel paths and corresponding delays based on at least one first transformed channel measurement matrix;

determining angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix; and

computing at least one linear combination coefficient for at least one third transformed channel matrix.
Anon-transitory computer readable medium comprising program instructions for causing an apparatus to carry out at least the following:

carrying out at least one frequency domain (FD) transformation on at least one channel measurement matrix in a frequency domain granularity using at least one Fourier transform operation;

determining one or more dominant channel paths and corresponding delays based on at least one first transformed channel matrix;

determining angle information for each of the one or more dominant channel paths using at least one spatial domain (SD) transformation on at least one second transformed channel matrix; and

computing at least one linear combination coefficient for at least one third transformed channel matrix.
An apparatus, 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:

receive channel state information (CSI) feedback for each of one or more dominant channel paths;

construct at least one first recovered channel matrix based on the channel state information (CSI) feedback;

carry out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) ;

carry out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) ; and

use the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.
A method, comprising:

receiving channel state information (CSI) feedback for each of one or more dominant channel paths;

constructing at least one first recovered channel matrix based on the channel state information (CSI) feedback;

carrying out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel matrix in a spatial domain (SD) ;

carrying out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) ; and

using the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.
Anon-transitory computer readable medium comprising program instructions for causing an apparatus to carry out at least the following:

receiving channel state information (CSI) feedback for each of one or more dominant channel paths;

constructing at least one first recovered channel matrix based on the channel state information (CSI) feedback;

carrying out at least one reverse spatial domain (SD) transformation on the at least one first recovered channel matrix to form at least one second recovered channel measurement matrix in a spatial domain (SD) ;

carrying out at least one reverse frequency domain (FD) transformation on the at least one second recovered channel matrix to form at least one third recovered channel matrix in a frequency domain (FD) ; and

using the third recovered channel matrix for one or more actions comprising scheduling or precoding for downlink transmission.