阅读说明：本技术 描绘每路径角度和延迟信息的信道状态信息（csi）反馈增强 (Channel State Information (CSI) feedback enhancement depicting per-path angle and delay information ) 是由 刘皓 于 2020-02-05 设计创作，主要内容包括：本文中描述的系统、方法、装置和计算机程序产品可以提供描绘每路径角度和延迟信息的CSI反馈增强。例如,一些实施例可以提供新的码本设计,其中准确的角度和延迟信息可以分别利用空域(SD)变换和频域(FD)变换针对每个主导信道路径被获取。具体地,某些实施例可以至少提供用于CSI反馈设计的以下操作：1)UE可以在子载波级别上,根据当前信道测量矩阵,使用傅立叶变换操作来执行FD变换,以确定主导信道路径和对应延迟；2)UE可以利用SD变换针对每个主导信道路径确定角度信息；以及3)在FD变换和SD变换之后,UE可以在其维度上减小信道矩阵,并且UE可以量化线性组合(LC)系数以用于反馈。(Systems, methods, apparatuses, and computer program products described herein may provide CSI feedback enhancement that depicts per-path angle and delay information. For example, some embodiments may provide a new codebook design where accurate angle and delay information may be obtained for each dominant channel path using Spatial (SD) and Frequency Domain (FD) transforms, respectively. In particular, certain embodiments may provide at least the following operations for CSI feedback design: 1) the UE may perform FD transformation using fourier transform operations to determine the dominant channel path and corresponding delay, at the subcarrier level, according to the current channel measurement matrix; 2) the UE may determine angle information for each dominant channel path using an SD transform; and 3) after the FD transform and the SD transform, the UE may reduce the channel matrix in its dimension, and the UE may quantize Linear Combination (LC) coefficients for feedback.)

1. An apparatus, comprising:

means for performing at least one Frequency Domain (FD) transform on the at least one channel measurement matrix at 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 the 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 (SD) transform of at least one second 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 obtaining 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) transform.

3. The apparatus of claim 1 or 2, 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 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.

5. The apparatus of any of claims 1-4, wherein the angle information identifies at least one angle of departure.

6. The apparatus of 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 into at least one matrix having a size of a number of receive antenna ports multiplied by a 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 angular 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 of the one or more dominant channel paths, or for each polarization of a primary channel path of the one or more dominant channel paths.

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

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

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

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

at least one bitmap of said 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, 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 performing at least one reverse Spatial (SD) transform on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD);

means for performing at least one reverse frequency-domain (FD) transform on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD); and

means for using the third recovered channel matrix for 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 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.

13. The apparatus according to any one of claims 10-12, wherein the means for performing the at least one inverse Spatial (SD) transform further comprises:

means for performing the at least one inverse Spatial (SD) transformation 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) transform 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, 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) transform on the at least one channel measurement matrix at a frequency domain granularity using at least one fourier transform operation;

determining one or more dominant channel paths and corresponding delays based on the 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 (SD) transform of at least one second transformed channel matrix; and

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

16. A method, comprising:

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

determining one or more dominant channel paths and corresponding delays based on the 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 (SD) transform of at least one second transformed channel matrix; and

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

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

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

determining one or more dominant channel paths and corresponding delays based on the 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 (SD) transform of at least one second transformed channel matrix; and

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

18. 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:

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;

performing at least one reverse Spatial (SD) transform on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD);

performing at least one reverse frequency-domain (FD) transform on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD); and

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

19. 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;

performing at least one reverse Spatial (SD) transform on the at least one first recovered channel matrix to form at least one second recovered channel matrix in Spatial Domain (SD);

performing at least one reverse frequency-domain (FD) transform on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD); and

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

20. A non-transitory computer readable medium comprising program instructions for causing an apparatus to perform 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;

performing at least one reverse Spatial (SD) transform on the at least one first recovered channel matrix to form at least one second recovered channel measurement matrix in Spatial (SD);

performing at least one reverse frequency-domain (FD) transform on the at least one second recovered channel matrix to form at least one third recovered channel matrix in the Frequency Domain (FD); and

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

Technical Field

Some example embodiments may relate generally to mobile or wireless telecommunications systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technologies or New Radio (NR) access technologies, or other communication systems. For example, certain embodiments may be directed to systems and/or methods for Channel State Information (CSI) feedback enhancement that depicts 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 a Next Generation (NG) radio system and network architecture. The 5G is built mainly on the New Radio (NR), but the 5G (or NG) network can 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 (eMBB) and ultra-reliable low latency communication (URLLC) as well as large-scale machine type communication (mtc). NR is expected to enable extremely broadband and ultra-robust low-latency connectivity and 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 can provide radio access functionality to user equipment (i.e. similar to a node B in UTRAN or an eNB in LTE) can be named gNB when built on NR radio and NG-eNB when built on E-UTRA radio.

Disclosure of Invention

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

In one variation, the method may include: at least one channel measurement matrix is obtained in at least one downlink channel state information reference signal (CSI-RS) measurement before performing at least one Frequency Domain (FD) transform. In one variation, performing at least one Frequency Domain (FD) transform may further comprise: the 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 angle of departure. In one variation, determining the angle information may further include: for at least one of the one or more dominant channel paths, at least one corresponding column vector of the at least one second transformed channel matrix is reshaped into at least one matrix having a size of the number of receive antenna ports multiplied by the number of transmit antenna ports. In one 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: searching at least one discrete fourier transform vector to match the at least one matrix in the second dimension and represent 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 one variation, the method may further comprise: providing at least one of the following for uplink Channel State Information (CSI) feedback: feedback of per-path delays using at least one Frequency Domain (FD) transform, feedback of per-path angles 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 comprise: channel State Information (CSI) feedback is received for each of one or more dominant channel paths. The method can comprise the following steps: at least one first recovered channel matrix is constructed based on Channel State Information (CSI) feedback. The method can comprise the following steps: at least one reverse Spatial (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 can comprise the following steps: at least one inverse frequency-domain (FD) transform 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 can comprise the following steps: using the third recovered channel matrix for one or more actions, the one or more actions including scheduling or precoding for downlink transmissions.

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

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

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

A seventh embodiment may be directed to a computer program product encoded with instructions for performing at least the method according to the first or 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 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 exemplary embodiments, as generally described and illustrated in the figures herein, could 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 that depict Channel State Information (CSI) feedback enhancement for per-path angle and delay information is not intended to limit the scope of certain embodiments, but is instead 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, throughout this specification, use of the phrase "certain embodiments," "some embodiments," or other similar language 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. Additionally, as used herein, the phrase "a collection of … …" refers to a collection that includes one or more of the referenced items. Thus, the phrases "a set of … …," "at least one of … …," and "one or more of … …" may be used interchangeably.

In addition, the different functions or operations discussed below may be performed in a different order and/or concurrently with each other, if desired. 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) specified type II port selection codebook enhancements (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 downlink/uplink (DL/UL) reciprocity of angle and delay(s). The remaining DL CSI is reported by the UE, mainly for Frequency Division Duplex (FDD) frequency range 1(FR1), to achieve a better tradeoff between UE complexity, performance and reporting overhead.

Due to its superior performance relative to Rel-14 LTE, a type II codebook design is introduced in rel.15 NR. In the rel.1698r stage, Frequency Domain (FD) transform techniques are implemented and specified in the type II codebook to significantly reduce the feedback overhead without performance penalty. As NR is in the process of commercialization, there may be a need for more attention to real deployment scenarios. For example, partial reciprocity in 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 transforms that use a Discrete Fourier Transform (DFT) to reduce the number of CSI feedback elements, including an FD transform and a Spatial (SD) transform. In general, the channel matrix may be transformed from FD to Time Domain (TD) with an FD transform that determines the dominant channel path and corresponding delay. However, the rel.16 type II codebook is designed at a subband level and its FD transform is performed between multiple 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) at the gNB side, respectively. SD transforms in rel.16 type II codebooks select L candidate SD beams for polarization directions on a wideband level, so the candidate SD beams are common to all dominant channel paths and do not reflect the exact AoA or AoD information for each dominant path in the Angular Domain (AD).

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

Some embodiments described herein may provide CSI feedback enhancement that depicts per-path angle and delay information. For example, some embodiments may provide a new codebook design where accurate angle and delay information may be obtained for each dominant channel path using the SD transform and FD transform, 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 a subcarrier level using an Inverse Fast Fourier Transform (iFFT) operation to determine a dominant channel path and corresponding delay according to a current channel measurement matrix; 2) the UE may determine angle information (e.g., AoA or AoD) for each dominant channel path using the SD transform; and 3) after the FD transform and the SD transform, 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 to rel.16 type II CSI, while reducing feedback overhead. Since the payload of SD transform and FD transform in the new CSI scheme may be larger than in rel.16 type II CSI, it may be expected that the payload of the CSI scheme according to some embodiments may be further reduced when FDD reciprocity is used for CSI feedback in rel.17. Certain embodiments utilizing the CSI design described herein may more conveniently identify angle and delay information in the CSI feedback item for future FDD reciprocity applications and may have a 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, a UE may perform a Frequency Domain (FD) transform on a channel measurement matrix at a frequency domain granularity (e.g., subcarrier level for a channel matrix comprising a plurality of subcarriers, resource block level for a channel matrix comprising a plurality of resource blocks, or subband level for a channel matrix comprising a plurality of 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 the FD channel measurement matrix). Suppose, for example, that the FD channel measurement matrix H_FDIn downlink CSI-RS measurement with dimension N_p×N_fIs obtained, where N_fMay be the number of active subcarriers, N_p＝N_rx×N_txMay be the number of channel pairs, each channel pair linking a transmit antenna port and a receive antenna port, N_txMay be the number of transmit antenna ports, and N_rxMay be the number of receive antenna ports.

FD channel measurement matrix H_FDCan be utilized in the second dimension of the matrix, with N_fThe iFFT operation of the points is transformed into a first transformed channel matrix H₁。H₁May have N_p×N_fOf (c) is calculated.

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 Orthogonal Matching Pursuit (OMP) search rules) to form a second transformed channel matrix (e.g., that includes only the dominant channel paths in the TD). Selection of N pairs taking into account the dominant channel path_pSeveral channel pairs may be common, N_pathThe dominant channel paths may be derived from the first transformed channel matrix H in its second dimension according to OMP search rules₁To select. In [1, N ]_f]The location of each channel path within may indicate to some extent the delay of the path. After FD transformation and selection of one or more dominant channel paths, a second transformed channel matrix H₂Can 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 gbb side) for each of the one or more dominant channel paths using a Spatial (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 the number of receive antenna ports multiplied by the number of transmit antenna ports. For channel path i, the second transformed channel matrix H₂May be reshaped to have N_rx×N_txIs of size H₂(i) In that respect 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, AoA or AoD of a channel path i may be based on the matrix H in its second dimension₂(i) Is determined, and its pair is notMay be common to the receive antenna ports.

Assume, for example, that the configuration of a two-dimensional (2-D) antenna port on the gbb side can be made of (N) in each polarization_1,N₂) Expression of wherein N is₁And N₂The number of antenna ports in the horizontal and vertical dimensions, respectively, and they may be represented by N_tx＝2×N₁×N₂And (4) meeting the requirement. The azimuth angle of the channel path i in the horizontal dimension may be set toAnd the 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 1, …, N₁

For k 1, …, N₂

Wherein:

and

is the transmit antenna vector for channel path i in the horizontal and vertical dimensions. Vector w of transmitting antenna_iMay be the Kronecker product between the vertical vector and the horizontal vector for channel path i, i.e.,the antenna spacing may be defined by d in the horizontal and vertical dimensions, respectively_HAnd d_VIt is given. λ may be a wavelength.

In accordance with the above, AoA or AoD may be included in transmit antenna vector w_iIt can also be represented as an oversampled DFT vector. The UE may search 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 path). For example, the UE may search for the best DFT vector w_iIn a second dimension with the channel matrix H₂(i) The properties of AoA or AoD for channel path i are matched and depicted in one polarization. This may be an SD transform, by which a third transformed channel matrix H₃May be formed from the second transformed channel matrix and may include the determined angle information in the angle domain. SD transform matrix W for channel path i_iCan be expressed by the following formula:

for channel path i, the third transformed channel matrix may be represented by H₃(i) Expressed and can be calculated as follows:

H₃(i)＝H₂(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 H₃(i) May have only N for each channel path_rxX 2 Linear Combination (LC) coefficients. The UE may provide for uplink Channel State Information (CSI) feedback at 108: feedback per path delay (e.g., delay information) using at least one Frequency Domain (FD) transform, feedback per path angle (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, a sum of a set of non-zero linear combination coefficientsOne less calculation, and/or the like. For per-path delay feedback using FD transformation, assume at N_fAfter point iFFT operation, N_pathThe dominant channel paths are selected according to an OMP search rule. In this case, the indication of per-path delay may be costlyBits are used for feedback.

For per-path-angle feedback using SD transforms, AoA or AoD for each channel path may refer to the azimuth and zenith angles of the polarization in the horizontal and vertical dimensions, respectively. This can be represented as an oversampled DFT vector. Feedback per path angle may be costing altogetherA bit of which N₁And N₂May be the number of antenna ports in the horizontal and vertical dimensions, respectively, and O₁And O₂May be an oversampling ratio in the corresponding dimension.

For a bitmap of a set of LC coefficients, after an FD transform process and an SD transform process, N_pathThe dominant channel paths may have N in total_path×N_rxX 2 LC coefficients. Maximum number of non-zero (NZ) LC coefficients K₀May be a parameter of a Radio Resource Control (RRC) configuration, where K₀≤N_path×N_rxX 2. The bitmap may utilize N_path×N_rxX 2 bits, which may indicate the type for each of the LC coefficients. For example, "1" may represent an NZ coefficient, and "0" may represent a zero coefficient.

For indication of the strongest LC coefficient, an index of the strongest LC coefficient may be usedOne bit to signal. For the quantization of the NZ LC coefficients, there may be K in total₀NZ LC coefficients, which may be signaled in terms of amplitude and phase quantization. The strongest LC coefficients may have the same relationship with othersDifferent quantization bit lengths and quantization sets of LC coefficients.

As illustrated at 108, the network node may receive CSI feedback for each of 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, a 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 the set of linear combination coefficients.

As illustrated at 112, the network node may perform a reverse Spatial (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 (SD) transformation from angular information to spatial information on the first recovered channel matrix using the angular 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) transform from the delay information to frequency-domain (FD) information on the at least one second recovered channel matrix using the 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 certain embodiments, in each feedback instance, the UE may first perform FD transformation at the subcarrier level using iFFT operation according to the current channel measurement matrix to determine the dominant channel path and corresponding delay. The UE may then determine angle information (e.g., AoA or AoD) for each dominant channel path using the SD transform. After the FD transform and the SD transform, the channel matrix may be reduced in its dimensions and its LC coefficients may be quantized for feedback.

According to some embodiments, the CSI may use some payload for feedback for SD and FD transforms. When FDD reciprocity is used for CSI feedback and SD transforms and FD transforms do not need to be reported, the payload of certain embodiments may be reduced compared to rel.16 type II CSI. In addition, certain embodiments may provide system performance gains when compared to Rel.16 type II CSI, while adjusting the number K of NZ LC coefficients₀It may further reduce feedback overhead. Since the payload of SD transforms and FD transforms in rel.17csi may be larger than in rel.16 type II CSI, certain embodiments may further reduce the payload of CSI when FDD reciprocity is used for CSI feedback. CSI designs according to certain embodiments may more conveniently identify angle and delay information in the CSI feedback item for future FDD reciprocity applications 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 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 comprise: at 200, at least one Frequency Domain (FD) transform is performed or conducted 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 comprise: at 202, 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 method may comprise: at 204, angle information is determined for each of the one or more dominant channel paths using at least one Spatial (SD) transform of the at least one second transformed channel matrix. In one embodiment, the method may comprise: 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 comprise: at least one channel measurement matrix is obtained in at least one downlink channel state information reference signal (CSI-RS) measurement before performing at least one Frequency Domain (FD) transform. In some embodiments, performing at least one Frequency Domain (FD) transform may further comprise: the 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 angle of departure. In some embodiments, determining the angle information may further comprise: for at least one of the one or more dominant channel paths, at least one corresponding column vector of the at least one second transformed channel matrix is reshaped into at least one matrix having a 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 comprise: 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 the at least one matrix in a second dimension and represent 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: for uplink Channel State Information (CSI) feedback, providing at least one of: feedback of per-path delays using at least one Frequency Domain (FD) transform, feedback of per-path angles 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 diagram 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 comprise: at 300, Channel State Information (CSI) feedback is received for each of one or more dominant channel paths. In one embodiment, the method may comprise: at 302, at least one first recovered channel matrix is constructed based on Channel State Information (CSI) feedback. In one embodiment, the method may comprise: at 304, at least one reverse Spatial (SD) transform is performed or conducted 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 comprise: at 306, at least one inverse frequency-domain (FD) transform is performed or conducted 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 comprise: 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 transmission.

In some embodiments, the Channel State Information (CSI) feedback may include 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 (SD) transform may further comprise: at least one inverse Spatial (SD) transform from the angle information to the spatial information is performed on the at least one first recovered channel matrix using the angle feedback for each of the one or more dominant paths. In some embodiments, performing at least one inverse Frequency Domain (FD) transform may further comprise: performing at least one inverse frequency-domain (FD) transform from the delay information to frequency-domain (FD) information on the at least one second recovered channel matrix using the 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 one embodiment, the apparatus 10 may be a node, a host, or a 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) associated with a radio access network (such as an LTE network, 5G, or NR), 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. In an example embodiment, the apparatus 10 may be an eNB in LTE or a gNB in 5G.

It should be understood 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 nodes may be separate apparatuses communicating with each other via a radio path or via a wired connection, or they may be located in the same entity communicating via a wired connection. For example, in some example embodiments where the apparatus 10 represents a gNB, it may be configured with a Central Unit (CU) and Distributed Unit (DU) architecture that divides the gNB functionality. In such an architecture, a CU may be a logical node that includes 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 fronthaul interface. Depending on the function split 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 or special purpose processor. Indeed, as an example, 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. Although a single processor 12 is shown in FIG. 4a, according to other embodiments, multiple processors may be utilized. For example, it should be understood that in some embodiments, the apparatus 10 may include two or more processors, that the two or more processors may form a multi-processor system (e.g., in which case the processor 12 may represent multiple processors), and that the multi-processor system may support multiple processes. In some embodiments, multiprocessor systems may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

The processor 12 may perform functions associated with the operation of the 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 procedures 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 that may be executed by the processor 12. The 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 memory 14 may include program instructions or computer program code that, when executed by processor 12, enable 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 an external computer-readable storage medium, such as an optical disk, a USB drive, a flash drive, or any other storage medium. For example, an external computer readable storage medium may store a computer program or software for execution by processor 12 and/or device 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 and 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 multiple 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: GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, Radio Frequency Identifier (RFID), Ultra Wideband (UWB), MulteFire, and the like. The radio interface may include components such as filters, converters (e.g., digital-to-analog converters, etc.), mappers, Fast Fourier Transform (FFT) modules, and so on, to generate symbols for transmission via one or more downlinks and receive symbols (e.g., via an uplink).

As such, the transceiver 18 may be configured to modulate information onto 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 the 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 include, for example, an operating system that provides operating system functionality for device 10. The memory may also store one or more functional modules, such as applications or programs, that provide additional functionality to the device 10. The components of the 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 may form part of processing circuitry or control circuitry. Additionally, in some embodiments, the transceiver 18 may be included in, or may form part of, transceiver circuitry.

As used herein, the term "circuitry" may refer to hardware circuitry implementations only (e.g., analog and/or digital circuitry), combinations of hardware circuitry and software, combinations of analog and/or digital hardware circuitry and software/firmware, any portion of 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 hardware circuitry(s) and/or processor(s), or portions thereof, that use software for operation, but may not be present when software 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 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 certain embodiments, the 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, 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 of the operations of the flow diagrams 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 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 reverse Spatial (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 reverse frequency-domain (FD) transform is performed or conducted 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: using the third recovered channel matrix for one or more actions, the 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 a communication network or associated with such a 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, smartphone, IoT device, sensor, or NB-IoT device, among others. 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, the apparatus 20 may be configured to operate using one or more radio access technologies, such as GSM, 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 executing instructions or operations. The processor 22 may be any type of general or special purpose processor. Indeed, as an example, 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. Although a single processor 22 is shown in FIG. 4b, according to other embodiments, multiple processors may be utilized. For example, it should be understood that in some embodiments, apparatus 20 may include two or more processors, that the two or more processors may form a multi-processor system (e.g., in which case processor 22 may represent multiple processors), and that the multi-processor system may support multiple processes. In some embodiments, multiprocessor systems may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

Processor 22 may perform functions associated with 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 apparatus 20, including procedures relating to management of communication resources.

The apparatus 20 may also include or be coupled to a memory 24 (internal or external), and the memory 24 may be coupled to the processor 22 for storing information and instructions that may be executed by the processor 22. The 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 memory 24 may include program instructions or computer program code that, when executed by processor 22, enable 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, a USB drive, a flash drive, or any other storage media. For example, an external computer-readable storage medium may store a computer program or software for execution by processor 22 and/or apparatus 20.

In some embodiments, the apparatus 20 may also include or be coupled to one or more antennas 25 for receiving downlink signals and for transmission from the apparatus 20 via the uplink. The apparatus 20 may also 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-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 (e.g., digital-to-analog converters, etc.), symbol demappers, signal shaping components, Inverse Fast Fourier Transform (IFFT) modules, etc., to process symbols, such as OFDMA symbols, carried by the downlink or uplink.

For example, transceiver 28 may be configured to modulate information onto a carrier waveform for transmission by antenna(s) 25, and to 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, the 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 to the apparatus 20. The components of the apparatus 20 may be implemented in hardware, or as any suitable combination of hardware and software. According to an example embodiment, the apparatus 20 may optionally be configured to communicate with the 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 may form part of, processing circuitry or control circuitry. Additionally, in some embodiments, the 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 certain 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, the 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, the apparatus 20 may be controlled by the memory 24 and the processor 22 to: at least one Frequency Domain (FD) transform is performed or performed on the 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 (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: for at least one third transformed channel matrix, at least one linear combination coefficient is calculated.

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 leads to improved functionality of communication networks and their nodes, and therefore constitutes at least an improvement in the technical field of feedback signaling for UE-network nodes, among other things.

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

In some example embodiments, the apparatus may be included in or associated with at least one software application, module, unit or entity configured as arithmetic operation(s) performed by at least one operations processor, or a program or portion thereof (including added or updated software routines). Programs (also known as program products or computer programs, including software routines, applets, and macros) may be stored in any device-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 that, when the program is run, are configured to perform some example embodiments. The one or more computer-executable components may be at least one software code or code portion. The modifications and configurations required for implementing 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, software routine(s) may be downloaded into the device.

By way of example, the software or computer program code or code portions may be in source code form, object code form, or in some intermediate form, and may be stored on some type of carrier, distribution medium, or computer-readable medium, which may be any entity or device capable of carrying the program. Such a carrier may comprise, for example, a record medium, computer memory, read-only memory, an optical and/or electrical carrier signal, a telecommunication signal, and/or a software distribution package. 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), for example, by using 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 a memory to provide storage capacity for arithmetic operation(s) and/or an arithmetic processor to perform 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, embodiments describing the operation of a single network node are equally applicable to embodiments comprising multiple instances of the network node, and vice versa.

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