CN116915291A

CN116915291A - Method and user equipment for reporting channel state information

Info

Publication number: CN116915291A
Application number: CN202310398946.7A
Authority: CN
Inventors: H·沙穆罕默迪安; 裵正铉
Original assignee: Samsung Electronics Co Ltd
Current assignee: Samsung Electronics Co Ltd
Priority date: 2022-04-15
Filing date: 2023-04-14
Publication date: 2023-10-20

Abstract

Systems and methods for reporting channel state information. In some embodiments, the method comprises: receiving, by the UE, a first channel state information reference signal (CSI-RS); receiving, by the UE, a second CSI-RS; calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS; and transmitting a first precoding matrix corresponding to the first predicted channel state information to the network node (gNB).

Description

Method and user equipment for reporting channel state information

Cross Reference to Related Applications

The present application claims the benefit of priority from (i) U.S. provisional application No. 63/331,395, filed on day 4, 2022, and (ii) U.S. provisional application No. 63/410,944, filed on day 9, 2022, 28, the disclosures of which are incorporated by reference in their entireties as if fully set forth herein.

Technical Field

The present disclosure relates generally to wireless communications. More particularly, the subject matter disclosed herein relates to improvements to reporting channel state information.

Background

In a wireless communication system, channel State Information (CSI) measurement and reporting rates may be defined based on channel coherence time in order to fairly track channel time variations. However, in a scenario of high or medium UE mobility, doppler spread implies a fast fading channel and coherence time becomes very small. In this scenario, if CSI measurements are not frequent enough with respect to the channel change rate, performance may be degraded due to CSI aging.

Disclosure of Invention

To address this issue, and to be able to track CSI changes and prevent CSI aging in this case, the network may trigger more frequent CSI measurements. One problem with the above approach is higher resource overhead, UE complexity and power consumption. To overcome these problems, systems and methods for predicting CSI are described herein. The above scheme improves on previous approaches in that it can provide acceptable CSI without causing unacceptable complexity and power consumption.

According to some embodiments, there is provided a method comprising: receiving, by the UE, a first channel state information reference signal (CSI-RS); receiving, by the UE, a second CSI-RS; calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS; and transmitting a first precoding matrix corresponding to the first predicted channel state information to the network node (gNB).

In some embodiments, the method further comprises reporting, by the UE, a capability for predicting channel state information.

In some embodiments, reporting includes reporting a future maximum time at which the UE can predict channel state information.

In some embodiments, the first predicted channel state information is predicted for a first point in time, the first point in time being a set time interval after transmission of the legacy channel state information.

In some embodiments, the first predicted channel state information is predicted for a first point in time, the first point in time being a set time interval after a time when the most recent CSI-RS was received by the UE.

In some embodiments, transmitting the first precoding matrix includes transmitting an array of coefficients, the first precoding matrix being part of an array product of the array of coefficients and the plurality of bases.

In some embodiments: the first predicted channel state information is predicted for a first point in time; and the method further comprises: calculating, by the UE, second predicted channel state information for a second point in time different from the first point in time based on the first CSI-RS and the second CSI-RS, and transmitting a second precoding matrix corresponding to the second predicted channel state information to the network node, the second precoding matrix and the first precoding matrix being transmitted in one CSI report.

In some embodiments: the second precoding matrix is a part of an array product of the coefficient array and the plurality of bases; and the plurality of bases includes a single set of Doppler domain bases that are commonly selected for all spatial and all frequency domain bases of each layer.

In some embodiments: the Doppler domain base set is a set of Q Doppler domain bases; and the method further includes receiving a Radio Resource Control (RRC) transmission, the RRC transmission specifying Q.

In some embodiments, the method further comprises: receiving, by the UE, a plurality of candidate doppler domain bases; and transmitting, by the UE, a set of identifiers identifying the set of Q doppler domain bases, each base of the set of Q doppler domain bases being a respective one of a plurality of candidate doppler domain bases.

According to some embodiments, there is provided a User Equipment (UE) comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause performance of: receiving, by the UE, a first channel state information reference signal (CSI-RS); receiving, by the UE, a second CSI-RS; and calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS.

In some embodiments, the instructions, when executed by the one or more processors, further cause performance of the ability to report by the UE for predicting channel state information.

In some embodiments, the instructions, when executed by the one or more processors, further cause execution of a first precoding matrix corresponding to the first predicted channel state information to a network node (gNB).

In some embodiments, the first predicted channel state information is predicted for a first point in time, the first point in time being a set time interval after a time when the UE received the most recent CSI-RS.

In some embodiments: the first predicted channel state information is predicted for a first point in time; and when executed by the one or more processors, the instructions further cause performance of: calculating, by the UE, second predicted channel state information for a second point in time different from the first point in time based on the first CSI-RS and the second CSI-RS, and transmitting a second precoding matrix corresponding to the second predicted channel state information to the network node, the second precoding matrix and the first precoding matrix being transmitted in one CSI report.

According to some embodiments, there is provided a User Equipment (UE) comprising: means for processing; and a memory storing instructions that, when executed by the means for processing, cause the execution of: receiving, by the UE, a first channel state information reference signal (CSI-RS); receiving, by the UE, a second CSI-RS; and calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS.

Drawings

In the following sections, aspects of the subject matter disclosed herein will be described with reference to exemplary embodiments shown in the drawings, in which:

fig. 1A is a matrix diagram depicting concatenation of precoding vectors in accordance with some embodiments;

fig. 1B is a diagram of a precoding matrix in accordance with some embodiments;

FIG. 2A is a matrix multiplication diagram according to some embodiments;

FIG. 2B is a matrix multiplication diagram according to some embodiments;

FIG. 3 is a table of parameter combinations according to some embodiments;

fig. 4A is a diagram of a compressed precoding matrix in accordance with some embodiments;

fig. 4B is a diagram of a compressed precoding matrix in accordance with some embodiments;

fig. 4C is a diagram of a compressed precoding matrix in accordance with some embodiments;

figure 5A is an illustration of a doppler domain base in accordance with some embodiments;

Fig. 5B is a diagram of a compressed precoding matrix in accordance with some embodiments;

fig. 5C is a diagram of a compressed precoding matrix in accordance with some embodiments;

FIG. 6 is a spectral diagram according to some embodiments;

fig. 7A is a diagram of a portion of a wireless system, according to some embodiments;

FIG. 7B is a flow chart of a method according to some embodiments;

fig. 8 is a block diagram of an electronic device in a network environment according to an embodiment.

Detailed Description

In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be understood by those skilled in the art that the disclosed aspects may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to obscure the subject matter disclosed herein.

Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment disclosed herein. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" or "in accordance with one embodiment" (or other phrases having similar meaning) in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In this regard, as used herein, the word "exemplary" means "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Furthermore, depending on the context discussed herein, singular terms may include corresponding plural forms, whereas plural terms may include corresponding singular forms. Similarly, terms (e.g., "two-dimensional)", "predetermined (pre-determined)", "pixel-specific", etc.) connected with hyphens may sometimes be used interchangeably with corresponding non-capital versions (e.g., "two-dimensional)", "predetermined (pre-determined)", "specific pixels (pixel specific)", etc.), and capital items (e.g., "Counter Clock", "Row Select", "pixel output (pixel out)", etc.) may be used interchangeably with corresponding non-capital versions (e.g., "Counter Clock", "Row Select", "pixel output", etc.). Such occasional interchangeable uses should not be considered inconsistent with each other.

Furthermore, depending on the context discussed herein, singular terms may include corresponding plural forms, whereas plural terms may include corresponding singular forms. It is also noted that the various figures (including component figures) shown and discussed herein are for illustrative purposes only and are not drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Furthermore, where considered appropriate, reference numerals have been repeated among the figures to indicate corresponding and/or analogous elements.

The terminology used herein is for the purpose of describing some example embodiments only and is not intended to limit the claimed subject matter. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It will be understood that when an element or layer is referred to as being "on," "connected to" or "coupled to" another element or layer, it can be directly on, connected or coupled to the other element or layer, or intervening elements or layers may be present. In contrast, when an element is referred to as being "directly on," "directly connected to" or "directly coupled to" another element or layer, there are no intervening elements or layers present. Like numbers refer to like elements throughout. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The terms "first," "second," and the like, as used herein, are used as labels for their preceding nouns and do not imply any type of ordering (e.g., spatial, temporal, logical, etc.) unless explicitly so defined. Furthermore, the same reference numbers may be used throughout two or more drawings to refer to portions, components, blocks, circuits, units, or modules having the same or similar functionality. However, such usage is merely for simplicity of illustration and ease of discussion; it is not intended that the constructional or architectural details of these components or units be the same in all embodiments, or that these commonly referenced parts/modules be the only way to implement some example embodiments disclosed herein.

Unless defined otherwise, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this subject matter belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

As used herein, the term "module" refers to any combination of software, firmware, and/or hardware configured to provide the functionality described herein in connection with the module. For example, software may be embodied as a software package, code, and/or instruction set or instructions, and the term "hardware" as used in any implementation described herein may include, for example, components, hardwired circuitry, programmable circuitry, state machine circuitry, and/or firmware that stores instructions executed by the programmable circuitry, alone or in any combination. These modules may be collectively or individually embodied as circuitry forming part of a larger system, such as, but not limited to, an Integrated Circuit (IC), a system-on-a-chip (SoC), a component, and the like.

As used herein, "a portion" of something means "at least some" of the thing, and as such may mean less than all or all of the thing. Likewise, "a part" of an object includes the whole object as a special case, that is, an example in which the whole object is a part of the object. As used herein, when the second number is "within" the first number X, it means that the second number is at least X-Y, and the second number is at most x+y. As used herein, when the second number is within "Y% of the first number, it means that the second number is at least (1-Y/100) times the first number, and the second number is at most (1+Y/100) times the first number. As used herein, the term "or" should be interpreted as "and/or", e.g., "a or B" means "a" or "B" or any one of "a and B".

Each of the terms "processing circuitry" and "means for processing" is used herein to represent any combination of hardware, firmware, and software for processing data or digital signals. The processing circuit hardware may include, for example, an Application Specific Integrated Circuit (ASIC), a general purpose or special purpose Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Graphics Processing Unit (GPU), and a programmable logic device such as a Field Programmable Gate Array (FPGA). As used herein, each function is performed in processing circuitry by either hardware configured to perform the function (i.e., hardwired) or by more general purpose hardware (such as a CPU) configured to execute instructions stored in a non-transitory storage medium. The processing circuitry may be fabricated on a single Printed Circuit Board (PCB) or distributed over several interconnected PCBs. The processing circuitry may comprise other processing circuitry; for example, the processing circuitry may include two processing circuits interconnected on a PCB, an FPGA and a CPU.

As used herein, when a method (e.g., adjustment) or a first quantity (e.g., a first variable) is referred to as being "based on" a second quantity (e.g., a second variable), this means that the second quantity is an input to the method or affects the first quantity, e.g., the second quantity may be an input (e.g., a unique input, or one of several inputs) that is a function of calculating the first quantity, or the first quantity may be equal to the second quantity, or the first quantity may be the same as the second quantity (e.g., the same location or locations stored in memory as the second quantity).

The type II CSI feedback framework (rel.15) in Release 15 of the fifth generation (5G) standard promulgated by the third generation partnership project (3 GPP) works on a per-subband CSI feedback basis to represent the dominant singular vectors of the Downlink (DL) channel. As shown in fig. 1A, the spatial frequency matrix can be obtained by concatenating precoding vectors of different subbands that are required to be reported for a specified transport layer by a User Equipment (UE).

The precoding matrix W for a particular transmission layer is N _tx ×N _sb Matrix, where N _sb Is the number of Subbands (SB), and N _tx ＝2N ₁ N ₂ Is the number of antenna ports at the network node (gNB). The kth column of W corresponds to the channel precoding vector of SBk as shown in fig. 1B.

The channel precoding matrix can be compressed in the Spatial Domain (SD) or the Frequency Domain (FD) to reduce feedback overhead. Rel.15 type II CSI feedback compresses W only in the spatial domain (i.e., across antenna ports) by performing linear combining using L Discrete Fourier Transform (DFT) beams, and does not compress in the frequency domain (i.e., across rows or SB):

W＝W ₁ W ₂ ，

wherein W is ₁ Comprising a wideband spatial two-dimensional discrete Fourier transform (2D-DFT) beam with dimension N _tx X 2L (as shown in fig. 2A):

and

W ₂ is a vector of combining coefficients (in a linear combination matrix W ₁ Is 2L x 1). Because W is ₁ Is orthogonal to the columns of (a), so W ₂ Is derived as:

for a type II codebook, one way to calculate the Precoding Matrix Indicator (PMI) at the UE side is to find the beam and corresponding coefficients to approximate the precoding vector to be reported for each subband. As a result, the overhead of a type II codebook increases approximately linearly with the number of subbands reported. It is possible to reduce CSI overhead by allowing larger subband sizes, which may thus reduce the number of subbands to report, but if such a mechanism is used, performance may be correspondingly degraded. However, the channels of the different subbands may experience a degree of correlation, which can be exploited to further reduce feedback overhead by performing compression in the frequency domain. For each row of the space-frequency matrix, there may be some basic patterns (basic patterns) along the frequency dimension to facilitate a higher compression codebook using a method similar to that used for spatial compression in rel.15.

In version 16 (rel.16), the precoding matrix W is represented as:

wherein W is ₁ For spatial domain compression, W _freq ＝[f ₀ … f _K-1 ]Is KXN _sb And is used for frequency domain compression, andis a compressed combination coefficient matrix having dimensions 2 lxk. Then, the UE needs to report the DFT beam W ₁ ＝{b _i }，W _freq ＝{f _k Sum of linear combination coefficients ∈ ->

This is illustrated in fig. 2B.

Since most of the type II feedback overhead is due to quantization of subband coefficients, this scheme will significantly reduce the amount of reported coefficients. The granularity of the frequency domain compressed CSI depends on the number of new bases. For example, if a multiple-input multiple-output (MIMO) channel is flat, the value of K can be set to 1, and W _freq Is an all 1 vector. Alternatively, when there is no channel correlation between different subbands, the value of K is set to N _sb And W is _freq Is the identity matrix (i.e., the scheme then reverts back to the Rel-15 type II codebook).

Number of Frequency Domain (FD) units before compression N _sb The relation between (PMI subband size) and the number of FD units after compression K is given by

Wherein, the liquid crystal display device comprises a liquid crystal display device,and N is _sb，CQI Is the Channel Quality Indicator (CQI) subband size N _sb，CQI ＝N _sb /R

Where R e {1,2} is the ratio of PMI and CQI subband sizes (r=1 is a default value, r=2 is optional). The values of R and p are configured by higher layers to indicate the value of K. For selection of "FD group" (i.e., N _sb Index of K DFT vectors) in the table, two cases are discussed in rel.16:

(i) If N _sb Less than or equal to 19: free selection of any K indices (byBit indicator indication).

(ii) If N _sb > 19: the two steps are adopted:

Ue selects and reports parameter K _initial ∈{-(N′ _sb -1)，-(N′ _sb -2), …, -1,0}, where N' _sb ＝2K。

Ue from the intermediate set ints= { mod (K _initial +n，N _sb )}，n＝0，1，...，N′ _sb In-1, from N' _sb K indices are selected.

Matrix arrayIncluding amplitude and phase coefficients, which produce a linear combination of the L selected beams. Of the 2LK coefficients, only the reduced number K is reported for each layer i _NZ，i ≤K ₀ Wherein

Parameters (parameters)Is of a high-level configuration. Some parameters of FD/SD compression are limited to some predefined combinations, given by the table of fig. 3.

As described above, in rel.16, CSI measurement and reporting rates are defined based on channel coherence time in order to fairly track channel time variations. However, in a scenario of high or medium UE mobility, doppler spread implies a fast fading channel and coherence time becomes very small. In this scenario, if CSI measurements are not frequent enough with respect to the channel change rate, performance may be significantly degraded due to CSI aging. To handle such fast fading channels and thus track CSI changes, one solution is for the network to trigger more frequent CSI measurements with higher CSI reference signal (CSI-RS) transmission rates by configuring smaller periodicity (for persistent/semi-persistent (P/SP) CSI-RS resources) or by transmission of aperiodic CSI-RS resources. However, a higher CSI update rate is an expensive solution because it greatly increases the resource overhead as well as the UE complexity and power consumption.

Another alternative solution is to use the doppler domain information to predict channel variations at the gNB and reduce reporting events. This may significantly reduce resource overhead and UE complexity. In the current New Radio (NR) CSI framework, time domain correlation information between different instances is difficult to obtain at the gNB. This is because the legacy PMI feedback is observed based on a single channel implementation, and the time domain correlation information between different channel implementations may not be fully preserved in their corresponding reported PMIs. Furthermore, the gNB may not be able to fully perceive the time domain correlation information due to quantization of PMI reports. That is, a joint CSI framework may be required in which reports corresponding to multiple instances implicitly or explicitly include time domain channel correlation information.

The following section discusses CSI report enhancements for high or medium UE speeds. The report may include an implicit report or an explicit report.

Implicit reporting may be performed as follows. In NR systems, the CSI framework is based on a linear codebook design that maps symbols in the frequency domain to transmit antennas. Time domain channel variations are tracked discretely by cycling CSI reports. At each CSI reporting instance, it is assumed that the gNB selects a precoding matrix according to CSI feedback including information about a precoding matrix index, a rank indicator, and a channel quality indicator. Due to the significant overhead, such discrete CSI reporting designs may not be a practical framework for high or medium UE mobility scenarios. To address this problem, the CSI framework may be enhanced to additionally provide the gNB with time domain channel correlation information. As previously mentioned, the gNB may not be able to fully derive the time domain correlation information between different channel realizations from the discrete report of PMIs. The joint CSI reporting framework may alleviate this problem and provide the gNB with time domain channel correlation information. This time domain channel correlation information may enable the gNB to predict channel variations and thus reduce the required CSI reporting re-transmissions. Thus, the joint CSI feedback may include mapping information to a time-frequency domain of the transmit antennas.

Precoding matrix and last N can be assumed for nth CSI reporting time instance _csi Precoding matrix correlations for the CSI reporting instances. This information can be used to predict and infer precoder changes with a certain accuracy, so that the occurrence of CSI reporting can be reduced. In some embodiments, an autoregressive model is used. For example, p-order autoregressive model of precoding matrix:

W ⁽ⁿ⁺¹ )＝a ⁽¹⁾ W ⁽ⁿ⁾ +a ⁽²⁾ W ^(n-1) +…+a ^(p) W ^(n-p+1) +N

wherein W is ⁽ⁿ⁺¹⁾ Is time (n+1) T _s (T _s Is the symbol rate), a ⁽¹⁾ ，...，a ^(p) Is an Autoregressive (AR) coefficient, and N is noise (e.g., additive White Gaussian Noise (AWGN)). Note that each AR coefficient a ⁽ⁱ⁾ I=1 …, p can generally be a dimension N with element-wise multiplication operations _tx ×N _sb Or simply scalar values.

Multiplying both sides of the above equation byAnd taking an expected value to obtain:

R _W ^(n+1，n) ＝a ⁽¹⁾ R _W ^(n，n) R _W (0)+a ⁽²⁾ R _W ^(n，n-1) +…+a ^(p) R _W ^(n，n-p+1)

by means of… and->The same procedure was repeated, and assuming a generalized stationary (WSS) procedure, a Yule-Walker equation was derived as follows:

coefficient a ⁽¹⁾ ，…，a ^(p) Can be estimated as:

that is, the precoder is utilized to auto-correlate matrix R _w Can derive coefficientsAnd W is ⁽ⁿ⁺¹⁾ May be based on the last p observations of W (i.e., W ⁽ⁿ⁾ ，W ^(n-2) +…，W ^(n-p+1) ) To extrapolate. In the traditional CSI framework, the gNB needs to calculate the time domain correlation R based on observations of quantized versions of the precoding matrix on discrete CSI reports _w . Due to quantization, the gNB may not be able to fully recover the correlation information. To address this problem, the time domain channel correlation information can be reported in CSI reporting as a separate matrix, where the time domain correlation of the precoding matrix is calculated at the UE and then quantized and reported to the gNB. This may generally provide less transmission loss of correlation information, and thus provide W at the gNB ⁽ⁿ⁺¹⁾ Is provided. For example, the CSI report at the nth CSI report time instance includes the precoding matrix W ⁽ⁿ⁾ Precoder correlation matrix W for each layer _R ⁽ⁿ⁾ Wherein the precoding matrix is as followsDefined in the legacy CSI reporting framework:

W ⁽ⁿ⁾ ＝W ₁ ⁽ⁿ⁾ W ₂ ⁽ⁿ⁾ ，

wherein W is ₁ ⁽ⁿ⁾ Is an N comprising a wideband spatial 2D-DFT beam _tx X 2L matrix, given by:

w is provided ₂ ⁽ⁿ⁾ Is 2L N _sb Is given by:

wherein, the liquid crystal display device comprises a liquid crystal display device,is a matrix of frequency domain compression coefficients having dimensions 2L K, and W _freq ＝[f ₀ … f _K-1 ]Having dimensions KXN _sb Representing a set of bases for frequency domain compression.

For precoder correlation matrix W in CSI reports _R ⁽ⁿ⁾ The UE remains from last N _csi Channel state information for 1 CSI reporting instance and computes the information to be included in matrix W on an element-by-element basis _R ⁽ⁿ⁾ Time domain correlation matrix R of precoder in (b) _W ^(n，n-m) ，m＝0，…，N _csi -1：

And is also provided with

This is illustrated in fig. 4A.

W is compressed in space domain using wideband 2D-DFT beams following the same logic as in Rel.16 _R ⁽ⁿ⁾ Matrix, obtain:

wherein the method comprises the steps of

And, further compressed in the frequency domain with the same logic as in rel.16Matrix, obtain:

wherein the time domain correlation information can be represented at W as follows _freq ＝[f ₀ … f _K-1 ]The base is reported:

wherein, the liquid crystal display device comprises a liquid crystal display device,as->Element-wise time domain correlation matrix (i.e. frequency domain compressed precoding matrix as defined in rel. 16):

thus W is _R ⁽ⁿ⁾ The matrix is represented as:

wherein, the liquid crystal display device comprises a liquid crystal display device,is a precoder correlation matrix +.>Is an element of (a). This is illustrated in fig. 4B.

The above scheme is based on compressed precoding matrix as followsAssumption of a p-th order autoregressive model (rather than W):

wherein, the liquid crystal display device comprises a liquid crystal display device,is a compressed AR coefficient, and each coefficient +.>Typically can be a 2 lxk matrix (used with element-wise multiplication) or simply scalar values.

Alternatively, the UE may estimate the coefficients itselfThese estimates are then included in the CSI report instead of the time domain correlation information. For example, the CSI report at the nth CSI report time instance may include the precoding matrix W ⁽ⁿ⁾ Correlation coefficient matrix A of each layer ⁽ⁿ⁾ Wherein the precoding matrix is as defined in the legacy CSI reporting framework:

And a correlation coefficient matrixUsually N _tx ×N _sb X p matrix (i.e. corresponding to W) or in compressed form +.>Is 2L x K x p (i.e. with +.>Corresponding). p is the order of the autoregressive model. Thus, the correlation coefficient matrix is expressed as:

this is shown in fig. 4C.

In this case, the observations of the precoding matrix of the previous CSI instance are exploited and (additionally reported by the UE)Then the gNB can assume the following autoregressive model to generate an initial estimate W of the precoding matrix ⁽ⁿ⁺¹⁾ ：

Wherein, due to the presence of AWGN noise N, gNB may apply an estimation technique such as maximum likelihood, least squares, minimum Mean Square Error (MMSE), kalman filter or wiener filtering to predict the time (n+1) T _s Precoding matrix W at ⁽ⁿ⁺¹⁾ 。

Other alternative solutions may rely on other linear prediction techniques at the UE so that the UE may use a kalman filter method, wiener filterA method or other nonlinear technique to calculate a coefficient matrix or state transition matrix. In this scheme, the UE may periodically report a containing a coefficient matrix or state transition matrix for the channel precoder W ⁽ⁿ⁾ The matrix, and the gNB may use this information and observations of previous CSI reporting instances to predict the precoding matrix.

CSI reporting overhead may be reduced by further compressing the precoding matrix in the time domain. This can compress W by using the set of time domain bases _R (n) matrix implementation, assuming that the base pattern may exist along the time dimension, using a method similar to that applied to spatial and frequency domain compression in the conventional CSI reporting framework:

wherein, the liquid crystal display device comprises a liquid crystal display device,is a precoder correlation matrix of time-domain compression with dimensions 2L K M, and W _time ＝[τ ₀ … τ _M-1 ]MXN, which is time-domain compressed _csi Is a base of (2). Then W is _R ⁽ⁿ⁾ The matrix is derived as:

similarly:

wherein [ alpha ] _i，k，m ] _2L×K×M Is a correlation coefficient matrixIs an element of (a).

Further, in all of the above schemes, it is assumed that for all transmitter ports (or alternativelyThe 2D-DFT beam) and all subcarriers (or frequency-domain compressed basis) report time-domain channel correlation information. That is, each a ⁽ⁱ⁾ I=1 …, p is generally assumed to be N _tx ×N _sb Or alternatively 2 lxk). However, this may not be necessary, as the channel correlation information may not always change with frequency or broadband beams. In this case, it is possible to make the assumption that each a ⁽ⁱ⁾ I=1 …, p is a vector (e.g., N _tx X 1 (or alternatively 2L x 1) or 1 XN _sb (or alternatively 1 x K)) or simply scalar values to simplify the scheme. For example, precoder correlation matrix Or a correlation coefficient matrix->May be defined on only one frequency subband (or alternatively on the frequency domain basis) but still be applicable to all subbands (or alternatively on the frequency domain basis). In frequency range 1 (FR 1) applications, the wideband spatial 2D-DFT beam (i.e., W ₁ ⁽ⁿ⁾ ) The same may also be maintained for multiple CSI reporting time instances. That is, the fast fading effect as a result of doppler spread may be only a linear combination coefficient matrix (i.e., W ₂ ⁽ⁿ⁾ ) Is obvious. This simplifies the scheme described above, so that the precoder correlation matrix +.>Or a correlation coefficient matrix->May be defined on only one transmit port (or 2D-DFT beam) but still be applicable to all ports (or beams). />

The signaling of such CSI reporting framework may be performed as follows. N in the above scheme _csi And the value of p may be Radio Resource Control (RRC) configured to the UE. Selected to beThe temporal base subset is per layer (i.e.,or p _l L=0, 1, …, RI-1), wherein +.>Or->A bit indicates the time domain base set selected for the first layer.

In all of the above schemes, channel correlation information over time is derived and included in CSI reports in the time domain. This may greatly increase CSI reporting overhead. To address this problem, one solution is to report channel correlation information to the gNB in the Doppler domain instead of the time domain. The Doppler domain is shown in FIG. 5A.

The time domain channel correlation information can be transmitted in the doppler domain with a more sparse matrix. This may significantly reduce CSI reporting overhead. This can be seen as having several doppler components inside each element of the channel matrix, which can be represented using a linear combination of the doppler domain basis sets:

and similarly:

wherein, the liquid crystal display device comprises a liquid crystal display device,is the Doppler domain base of Mx1. The value of M is RRC configured for the UE. The selected Doppler domain base subset is per layer (i.e., M _l L=0, 1, …, RI-1), where may be requiredA bit indicates the doppler domain base subset selected for the first layer.

In all CSI reporting frameworks discussed above, each CSI-RS transmission instance is accompanied by a corresponding reporting instance as in the current specification (e.g., at rel. 16). This may not be necessary because time domain correlation information of the channel may be included in the CSI report, and this information may reduce reporting occurrences and overhead. Applicable to all schemes discussed above, CSI reporting may thus be designed to be done with a period that is L times larger than the CSI-RS transmission period. With this scheme, the UE may observe the reception of each CSI-RS transmission instance, and may derive legacy CSI for each of these instances. CSI reporting may occur every L CSI-RS receptions, where the UE may report compressed CSI (including all calculated CSI) to the gNB. This information is used as training data at the gNB to predict and track the precoding matrix changes over time.

CSI reporting of the precoding matrix may have an additional dimension representing time. That is, the UE may need to inform the gNB about the frequency subcarriers and the precoding coefficients over L time instances. Thus, for each layer of transmission,can be derived as a precoding matrix W over CSI time instances ⁽ⁿ⁾ Where n=1, …, L: />

Wherein each W is ⁽ⁿ⁾ As defined in the legacy CSI reporting framework:

this is illustrated in fig. 5B.

Then, canTo further compress in the time domain by using the set of time domain basesTo reduce CSI reporting overhead:

wherein W is _time ＝[τ ₀ … τ _M-1 ]Is an mxl basis for time domain compression, and [ omega ] _i，k，m ] _2L×K×M Is an element of a matrix of compression coefficients. For these groups [ tau ] ₀ … τ _M-1 ]In another explanation of (a) the number of (c) is,is a compressed precoding matrix transmitted in a more sparse matrix in the doppler domain (and a compressed precoding matrix transmitted in the time domainOn the contrary). This can be seen as several doppler components inside each element of the channel matrix, which can be represented by a linear combination of the doppler domain basis sets:

wherein, the liquid crystal display device comprises a liquid crystal display device,is the Doppler domain base of Mx1. The M value in both schemes is RRC configured for the UE. The selected Doppler domain base subset is per layer (i.e., M _i L=0, 1, …, RI-1), wherein +.>A bit indicates the doppler domain base subset selected for the first layer.

As described above, the gNB may also need time domain correlation information of the channel or precoding matrix due to CSI report quantization. An alternative approach, which is more compatible with the current specification, is to make a conventional form of CSI reporting after each CSI transmission instance, but new time domain correlation information W _R Is included only in CSI reports for every L CSI reporting instances. The UE may observe the reception of each CSI-RS transmission instance and derive a corresponding time domain correlation for each of these instances, but report CSI (including time domain correlation information) to the gNB only after every L CSI-RS receptions. This is illustrated in fig. 5C.

Explicit reporting may be performed as follows. An alternative solution is for the UE to explicitly report the doppler shift value to the gNB instead of reporting the time correlation information. This information may be used at gNB with Tap Delay Line (TDL) or Clustered Delay Line (CDL) channel modeling to predict the channel's change over time. However, this may require an accurate estimate of the doppler shift at the UE and a channel reciprocity assumption. To this end, one approach is that at each CSI acquisition time instance, multiple CSI-RS resources are then transmitted in a bundled form (or with reasonably small time slots), and all of these resources are jointly used by the UE for more accurate doppler shift estimation. However, this approach may imply a significant resource overhead. Another alternative solution is that each CSI acquisition is paired with a Timing Reference Signal (TRS) signal transmission with a reasonable time gap (e.g., less than CSI aging) so that the UE's doppler shift estimate can be included in the CSI report. The TRS signal is specifically designed to help the UE track the frequency offset and, due to the higher time and frequency domain densities of the TRS signal, the UE is able to provide an accurate estimate of the doppler shift and feed it back to the gNB within the corresponding CSI report.

The channel impulse response is shown as:

wherein a is _k，t And τ _k Representing tapped delay line modesThe magnitude and delay of the kth tap in the pattern, and L is the total number of taps. Each channel tap a _k，t Representing the sum of infinite random propagation paths due to diffusers uniformly distributed around the circumference. That is, according to the central limit theorem, a _k，t Is a complex random variable in which its real and imaginary parts are gaussian random variables independently and equidistributed at each time t

The second order statistic of the TDL channel is shown as being equal to J ₀ (2πf _D (t ₂ -t ₁ ) Of J), wherein ₀ Is a zero-order Bessel function of the first class, and f _D Is the maximum doppler shift. The channel autocorrelation function can be used to derive the doppler power spectral density. The fourier transform is performed and the doppler spectrum is derived as follows, which is a classical U-shaped Jakes spectrum with two peaks at the positive and negative of the maximum doppler frequency:

since the Power Spectral Density (PSD) of an autoregressive process has a rational form, an autoregressive model is typically used to model the Jake process. The autoregressive model uses all-pole infinite impulse response filtering to shape the spectrum of the uncorrelated gaussian process to match the doppler spectrum of the Jake process. For illustration, assume an autoregressive model of a channel of order p, at time (n+1) T _s (T _s Is the symbol rate) is defined as:

H ⁽ⁿ⁺¹⁾ ＝a ⁽¹⁾ H ⁽ⁿ⁾ +a ⁽²⁾ H ^(n-1) +…+a ^(p） H ^(n-p+1) +N，

wherein a is ⁽¹⁾ ，…，a ^(p) Is the AR coefficient and N is AWGN noise. The corresponding PSD of the AR (p) model is derived as follows:

wherein sigma _N ² Is AWGN noise NIs a variance of (c). The second-order autoregressive model has two peaks in the frequency spectrum, which are between [ -pi, pi]And can be considered as positive and negative maximum doppler frequencies in the U-shaped Jakes spectrum. The position and sharpness of these peaks can be adjusted by the order p of several AR models and advanced cascading techniques. This is illustrated in fig. 6.

Thus, by choosing p correctly, an autoregressive model can be used to approximate the U-shaped Doppler spectrum. Note that many methods such as markov chains, subspace-based methods using ESPRIT, root-MUSIC algorithms, neural networks and kalman filtering can be used to predict the channel profile, as all these methods are suitable for generating the relevant rayleigh process. Among these methods, autoregressive modeling can be an efficient method of predicting channel profiles because it is simple and closely related to linear prediction.

The gNB can predict the channel change over time using the knowledge of doppler shift provided by the UE explicit report. One implementation at the gNB is for the gNB to use the doppler shift values reported by the UE to derive the autocorrelation of the channel coefficients in the time domain, as follows:

R _H (m)＝E{H ⁽ⁿ⁾ H ^(n-m)H }＝J ₀ (2πf _D mT _s )

Then, using the Yule-Walker equation, gNB can estimate the coefficients of the AR (p) model of the channel as follows:

therefore, gNB can estimate the AR coefficient by using these estimates and the observation H as input to the estimation technique ⁽ⁿ⁾ ，…，H ^(n-p+1) To predict the time (n+1) T _s Channel matrix at (a), estimation techniques such as maximum likelihood estimation, least squares estimation, minimum Mean Square Error (MMSE) estimation, kalman filtering, or wiener filtering.

However, in CDL channel modeling, explicit reporting of doppler shift values may be tap-by-tap. For illustration, the CDL channel impulse response is shown primarily as:

wherein, the liquid crystal display device comprises a liquid crystal display device,the channel coefficients for ray m, which is cluster n, are as follows:

wherein F is _tx，s，θ Andis the field pattern of the transmitting antenna element s, and F _rx，u，θ And->Is the field pattern of the receiving antenna element u. />And->Is the random initial phase, κ, of each ray m of each cluster n and for four different polarization combinations (i.e., θ, θφ, φθ, and φφ) _n，m Is the cross-polarization power ratio on a linear scale.And->Are respectively provided with a separation angle theta _n，m，ZOD 、/>And angle of arrival theta _n，m，ZOA 、/>Is given by +.>

And->Position vectors of transmit antenna element s and receive antenna element u, respectively, < >>Is provided with velocity v and traveling angle theta _v And->Is given by

Note that the time-varying nature of the channel impulse response comes mainly from the doppler frequency component, which depends on the angle of arrival (azimuth of arrival (AOA) and zenith angle of arrival (ZOA)), UE velocity and angle of travel (i.e.)). Thus (S)>The following can be written:

wherein the method comprises the steps of

And, in addition, the processing unit,is the doppler shift corresponding to ray m in cluster n. Thus, channel tap c is reported explicitly _{u，s，n，m} Tap position τ _n And Doppler shift f _D，n，m gNB can predict the change of the channel over time. However, this type of explicit reporting has a significant overhead. To address this problem, another alternative is that the explicit reporting of the UE is tap-by-tap. That is, use is made of

Wherein, the liquid crystal display device comprises a liquid crystal display device,the UE can report tap c to the gNB _u，s，n Tap-by-tap value τ _n And Doppler shift f _D，n 。

Further, the second order statistics of the CDL channel are derived as:

thus, with knowledge of the doppler shift and channel tap power provided by the UE explicit reports, the gNB can derive the autocorrelation of the channel coefficients in the time domain and thus predict the channel matrix, as described above. New UE capabilities are introduced.

As described above, the gNB may not be able to fully derive time domain correlation information from multiple CSI reports corresponding to different channel realizations, as this information may not be fully preserved in the PMIs they report.

Under the assumption of UE-side prediction, for CSI reporting and measurement for Rel-18 type II codebook improvement for high/medium speed, one of the following alternatives may be employed in the definition of UE-side prediction:

alt1 after a slot with reference resources, the UE "predicts" the channel/CSI

Alt2 after time slot n (where CSI is reported), the UE "predicts" the channel/CSI

With this scheme, the UE may observe reception of multiple CSI-RS resources (e.g., in burst format) and then derive a future PMI based on observation and computation of legacy CSI for multiple CSI-RS transmission instances. Future definitions may consider a reference resource slot (i.e., alt1 described above) or a reporting slot (i.e., alt2 described above) as the reference slot. The predicted PMI may be included in a CSI report containing a plurality of calculated PMIs in a non-compressed structure or a compressed structure using time/doppler domain basis.

The schemes discussed above may include introducing new UE capabilities that indicate how far the UE can predict future CSI in the time domain. To illustrate, the UE capability can be defined in terms of a temporal distance between the predicted point and the reference point (as described above). The UE capability can be based simply on a specific number of slots or number of Orthogonal Frequency Division Multiplexing (OFDM) symbols, or number of CSI-RS periods.

Note that for such UE capabilities, the timing of CSI-RS resources and the time distance between the predicted points play an important role. Another alternative (in addition to Alt1 and Alt2 above) is that the UE capability is defined on the time distance between the timing of the CSI-RS resources and the reference point. More than one alternative can be combined to implement UE capabilities. For example, the ability to predict the time distance between the point and the reference point and the ability to predict the time distance between the timing of the CSI-RS resource and the reference point can be utilized together to effectively achieve the ability to predict the time distance between the point and the timing of the CSI-RS transmission.

In some embodiments, CSI reporting of the precoding matrix may have an additional dimension representing time, where the UE informs the gNB of the precoding coefficients over several time instances. For each layer transmission, the precoder can be derived as a concatenation of precoding matrices over several CSI time instances. Furthermore, the UE may reduce CSI reporting overhead by using a time/doppler domain base set common to all SD/FD bases to compress the precoder in the time domain:

in some embodiments, the total number of Doppler Domain (DD) bases (i.e., M or N4, which are used interchangeably herein) is RRC configured to the UE, and the selected base set (i.e., M _l Or Q, which is used interchangeably herein) is indicated by layer.

For Rel-18 type II codebook refinement for high/medium speed, some embodiments support the following codebook structure, where N4 is configured via higher layer signaling gNB:

for n4=1, the doppler domain base is to reuse the legacy W ₁ 、And W is _f Identity matrix (without Doppler domain compression), e.g +.>

For N4 > 1, reuse of legacy W for Doppler-domain orthogonal DFT base co-selected for all SD/FD bases ₁ And W is _f For example

The expression generates a set of precoding matrices corresponding to one or more points in time (e.g., one or more points in time in the future). Each precoding matrix is part of a result, which is an array of coefficientsWith a plurality of radicals (e.g. W _f And W is _d ) Is a product of the array of (a) and (b). As used herein, an "array product" is any of the arraysWhat product, including matrix product or matrix outer product. As used herein, the term "array" refers to a collection of n-dimensionally (e.g., 1-dimensionally, 2-dimensionally, or 3-dimensionally) ordered numbers, regardless of how stored (e.g., in contiguous storage locations, or in linked lists).

In the latter case, (i) Q (representing the number of DD basis vectors selected) > 1 is only allowed, and (ii) Q may be RRC configured (in some embodiments) or reported by the UE (in some embodiments).

The detailed design of the SD/FD base including the associated Uplink Control Information (UCI) parameters may follow conventional specifications.

For type II codebook refinement for high or medium speed, the selection of DD base vectors may be layer-specific. The number of DD basis vectors (denoted as Q) selected may be layer-common.

Fig. 7A illustrates a portion of a wireless system. User Equipment (UE) 705 delivers transmissions to network node (gNB) 710 and receives transmissions from gNB 710. The UE includes a radio 715 and processing circuitry (or "processor") 720. In operation, the processing circuitry may perform various methods described herein, e.g., it may receive (via radio as part of a transmission received from the gNB 710) information from the gNB 710, and it may send (via radio as part of a transmission sent to the gNB 710) information to the gNB 710.

In operation, UE 705 may report its ability to predict CSI to gNB 710, and may also report to gNB 710 the future maximum time at which the UE can predict CSI. To allow the gNB 710 to utilize the predicted CSI, the UE 705 may send one or more precoding matrices to the gNB 710. The predicted CSI may be predicted for a future time, which is a set time interval after the transmission of the legacy CSI. As used herein, a "legacy CSI" is CSI that is an estimate of the current CSI (i.e., not predicted CSI). In some embodiments, the predicted CSI is predicted for a future time that is a set time interval after the time that UE 705 received the most recent CSI-RS.

Fig. 7B is a flow chart of a method in some embodiments. The method comprises the following steps: at 730, receiving, by the UE, a first channel state information reference signal (CSI-RS); at 732, receiving, by the UE, a second CSI-RS; and at 734, calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS. The method further comprises the steps of: reporting, by the UE, the capability for predicting channel state information at 736; at 738, a first precoding matrix corresponding to the first predicted channel state information is sent to a network node (gNB); at 740, calculating, by the UE, second predicted channel state information for a second point in time different from the first point in time based on the first CSI-RS and the second CSI-RS; and transmitting a second precoding matrix corresponding to the second predicted channel state information to the network node at 742. The method further comprises the steps of: at 744, receiving, by the UE, a set of candidate doppler domain basis vectors; and at 746, transmitting, by the UE, a set of identifiers identifying a set of Q doppler domain basis vectors, each basis vector of the set of Q doppler domain basis vectors being a respective one of the set of candidate doppler domain basis vectors.

Fig. 8 is a block diagram of an electronic device (e.g., UE 705) in a network environment 800 according to an embodiment. Referring to fig. 8, an electronic device 801 in a network environment 800 may communicate with the electronic device 802 via a first network 898 (e.g., a short range wireless communication network) or with the electronic device 804 or server 808 via a second network 899 (e.g., a remote wireless communication network). The electronic device 801 may communicate with the electronic device 804 via a server 808. The electronic device 801 may include a processor 820, a memory 830, an input device 840, a sound output device 855, a display device 860, an audio module 870, a sensor module 876, an interface 877, a haptic module 879, a camera module 880, a power management module 888, a battery 889, a communication module 890, a Subscriber Identity Module (SIM) card 896, or an antenna module 897. In one embodiment, at least one component (e.g., display device 860 or camera module 880) may be omitted from electronic device 801, or one or more other components may be added to electronic device 801. Some of the components may be implemented as a single Integrated Circuit (IC). For example, a sensor module 876 (e.g., a fingerprint sensor, iris sensor, or illuminance sensor) may be embedded in a display device 860 (e.g., a display).

Processor 820 may execute software (e.g., program 840) to control at least one other component (e.g., hardware or software component) of electronic device 801 coupled to processor 820 and may perform various data processing or calculations.

As at least part of the data processing or calculation, processor 820 may load commands or data received from another component (e.g., sensor module 846 or communication module 890) into volatile memory 832, process commands or data stored in volatile memory 832, and store the resulting data in non-volatile memory 834. The processor 820 may include a main processor 821 (e.g., a Central Processing Unit (CPU) or an Application Processor (AP)) and a sub-processor 823 (e.g., a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a sensor hub processor, or a Communication Processor (CP)), and the sub-processor 823 may operate independently of the main processor 821 or in combination with the main processor 821. Additionally or alternatively, the secondary processor 823 may be adapted to consume less power than the primary processor 821 or perform certain functions. The secondary processor 823 may be implemented separately from the primary processor 821 or as part of the primary processor 821.

The secondary processor 823 may replace the primary processor 821 when the primary processor 821 is in an inactive (e.g., sleep) state, or the secondary processor 823 may control at least some functions or states associated with at least one of the components of the electronic device 801 (e.g., the display device 860, the sensor module 876, or the communication module 890) with the primary processor 821 when the primary processor 821 is in an active state (e.g., executing an application). The secondary processor 823 (e.g., an image signal processor or a communication processor) may be implemented as part of another component (e.g., a camera module 880 or a communication module 890) functionally associated with the secondary processor 823.

The memory 830 may store various data used by at least one component of the electronic device 801 (e.g., the processor 820 or the sensor module 876). The various data may include, for example, input data or output data for the software (e.g., program 840) and commands associated therewith. Memory 830 may include volatile memory 832 or nonvolatile memory 834.

Programs 840 may be stored as software in memory 830 and may include, for example, an Operating System (OS) 842, middleware 844, or applications 846.

The input device 850 may receive commands or data from outside the electronic device 801 (e.g., a user) to be used by another component of the electronic device 801 (e.g., the processor 820). Input device 850 may include, for example, a microphone, a mouse, or a keyboard.

The sound output device 855 may output a sound signal to the outside of the electronic device 801. The sound output device 855 may comprise, for example, a speaker or a receiver. The speaker may be used for general purposes such as playing multimedia or audio recordings, and the receiver may be used to receive incoming calls. The receiver may be implemented separately from the speaker or as part of the speaker.

The display device 860 may visually provide information to an exterior (e.g., a user) of the electronic device 801. The display device 860 may include, for example, a display, a holographic device, or a projector, and control circuitry that controls a corresponding one of the display, holographic device, and projector. The display device 860 may include touch circuitry adapted to detect touches, or sensor circuitry (e.g., pressure sensors) adapted to measure the strength of touch-induced forces.

The audio module 870 may convert sound into electrical signals and vice versa. The audio module 870 may obtain sound via the input device 850 or output sound via a sound output device 855 or headphones of the external electronic device 802 that is directly (e.g., wired) or wirelessly coupled with the electronic device 801.

The sensor module 876 may detect an operational state (e.g., power or temperature) of the electronic device 801 or an environmental state (e.g., a state of a user) external to the electronic device 801 and then generate an electrical signal or data value corresponding to the detected state. The sensor module 876 may include, for example, a gesture sensor, a gyroscope sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an Infrared (IR) sensor, a biological sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

The interface 877 may support one or more specified protocols for the electronic device 801 to couple directly (e.g., wired) or wirelessly with an external electronic device 802. The interface 877 may include, for example, a High Definition Multimedia Interface (HDMI), a Universal Serial Bus (USB) interface, a Secure Digital (SD) card interface, or an audio interface.

The connection terminal 878 may include a connector via which the electronic device 801 can be physically connected to the external electronic device 802. The connection terminal 878 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

The haptic module 879 may convert the electrical signal into a mechanical stimulus (e.g., vibration or motion) or an electrical stimulus, which may be recognized by the user via touch or kinesthetic sense. The haptic module 879 may include, for example, a motor, a piezoelectric element, or an electro-stimulator.

The camera module 880 may capture still images or moving images. The camera module 880 may include one or more lenses, an image sensor, an image signal processor, or a flash. The power management module 888 can manage power supplied to the electronic device 801. The power management module 888 may be implemented, for example, as at least a portion of a Power Management Integrated Circuit (PMIC).

A battery 889 may provide power to at least one component of the electronic device 801. The battery 889 may include, for example, a primary non-rechargeable battery, a secondary rechargeable battery, or a fuel cell.

The communication module 890 may support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device 801 and an external electronic device (e.g., the electronic device 802, the electronic device 804, or the server 808), and performing communication via the established communication channel. The communication module 890 may include one or more communication processors that may operate independently of the processor 820 (e.g., an AP) and support direct (e.g., wired) or wireless communication. The communication module 890 may include a wireless communication module 892 (e.g., a cellular communication module, a short-range wireless communication module, or a Global Navigation Satellite System (GNSS) communication module) or a wired communication module 894 (e.g., a Local Area Network (LAN) communication module or a Power Line Communication (PLC) module). A corresponding one of these communication modules may communicate with external electronic devices via a first network 898 (e.g., a standard short-range communication network such as bluetooth (TM), wireless fidelity (Wi-Fi) direct, or infrared data association (IrDA)) or a second network 899 (e.g., a remote communication network such as a cellular network, the internet, or a computer network (e.g., a LAN or Wide Area Network (WAN)). These different types of communication modules may be implemented as a single component (e.g., a single IC), or may be implemented as multiple components (e.g., multiple ICs) that are separate from each other. The wireless communication module 892 may use subscriber information (e.g., an International Mobile Subscriber Identity (IMSI)) stored in the subscriber identification module 896 to identify and authenticate the electronic device 801 in a communication network, such as the first network 898 or the second network 899.

The antenna module 897 may transmit signals or power to the outside of the electronic device 801 (e.g., an external electronic device) or receive signals or power from the outside of the electronic device 801. The antenna module 897 may include one or more antennas and thus, for example, at least one antenna suitable for a communication scheme used in a communication network such as the first network 898 or the second network 899 may be selected by the communication module 890 (e.g., the wireless communication module 892). The signal or power may then be transmitted or received between the communication module 890 and the external electronic device via the selected at least one antenna.

Commands or data may be sent or received between the electronic device 801 and the external electronic device 804 via a server 808 coupled to the second network 899. Each of the electronic devices 802 and 804 may be the same type or a different type of device than the electronic device 801. All or some of the operations to be performed on the electronic device 801 may be performed on one or more external electronic devices 802, 804, or 808. For example, if the electronic device 801 should perform a function or service automatically or in response to a request from a user or another device, the electronic device 801 may request one or more external electronic devices to perform at least a portion of the function or service instead of or in addition to performing the function or service. The external electronic device or devices receiving the request may perform at least a portion of the requested function or service, or additional functions or additional services related to the request, and communicate the result of the execution to the electronic device 801. The electronic device 801 may provide results as at least a portion of a reply to a request with or without further processing of the results. To this end, for example, cloud computing, distributed computing, or client-server computing techniques may be used.

Embodiments of the subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on a computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or additionally, the program instructions can be encoded on a manually generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode information for transmission to suitable receiver apparatus for execution by data processing apparatus. The computer storage medium can be or be included in a computer readable storage device, a computer readable storage substrate, a random or serial access memory array, or a device, or a combination thereof. Furthermore, while the computer storage medium is not a propagated signal, the computer storage medium may be a source or destination of computer program instructions encoded in an artificially generated propagated signal. Computer storage media can also be or be included in one or more separate physical components or media (e.g., multiple CDs, hard disks, or other storage devices). Furthermore, the operations described in this specification may be implemented as operations performed by a data processing apparatus on data stored on one or more computer readable storage devices or received from other sources.

While this specification may contain many specific implementation details, these should not be construed as limitations on the scope of any claimed subject matter, but rather as descriptions of features specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Furthermore, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Thus, particular embodiments of the subject matter have been described herein. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some implementations, multitasking and parallel processing may be advantageous.

As will be recognized by those skilled in the art, the innovative concepts described herein can be modified and varied over a wide range of applications. Accordingly, the scope of the claimed subject matter should not be limited to any of the specific exemplary teachings discussed above, but is defined by the following claims.

Claims

1. A method, comprising:

receiving, by the UE, a first channel state information reference signal (CSI-RS);

receiving, by the UE, a second CSI-RS;

calculating, by the UE, first predicted channel state information based on the first CSI-RS and the second CSI-RS; and

a first precoding matrix corresponding to the first predicted channel state information is transmitted to a network node (gNB).

2. The method of claim 1, further comprising reporting, by the UE, a capability to predict channel state information.

3. The method of claim 2, wherein reporting comprises reporting a future maximum time at which the UE can predict channel state information.

4. The method of claim 1, wherein the first predicted channel state information is predicted for a first point in time, the first point in time being a set time interval after transmitting the legacy channel state information.

5. The method of claim 1, wherein the first predicted channel state information is predicted for a first point in time, the first point in time being a set time interval after a time when a most recent CSI-RS is received by the UE.

6. The method of claim 1, wherein transmitting a first precoding matrix comprises transmitting an array of coefficients, the first precoding matrix being part of an array product of the array of coefficients and a plurality of bases.

7. The method according to claim 6, wherein:

the first predicted channel state information is predicted for a first point in time; and is also provided with

The method further comprises:

calculating, by the UE, second predicted channel state information for a second point in time different from the first point in time based on the first CSI-RS and the second CSI-RS, and

transmitting a second precoding matrix corresponding to the second predicted channel state information to the network node,

The second precoding matrix and the first precoding matrix are transmitted in one CSI report.

8. The method of claim 7, wherein:

the second precoding matrix is a part of an array product of the coefficient array and the plurality of bases; and is also provided with

The plurality of bases includes a single set of Doppler domain bases that are commonly selected for all spatial and all frequency domain bases of each layer.

9. The method according to claim 8, wherein:

the Doppler domain base set is a set of Q Doppler domain bases; and is also provided with

The method further includes receiving a Radio Resource Control (RRC) transmission, the RRC transmission specifying Q.

10. The method of claim 9, further comprising:

receiving, by the UE, a plurality of candidate doppler domain bases; and

a set of identifiers identifying the set of Q doppler domain bases is transmitted by the UE, each base of the set of Q doppler domain bases being a respective one of a plurality of candidate doppler domain bases.

11. A User Equipment (UE), comprising:

one or more processors; and

a memory storing instructions that, when executed by one or more processors, cause performance of:

receiving, by the UE, a second CSI-RS; and

The first predicted channel state information is calculated by the UE based on the first CSI-RS and the second CSI-RS.

12. The UE of claim 11, wherein the instructions, when executed by the one or more processors, further cause performance of the ability to report, by the UE, the predicted channel state information.

13. The UE of claim 12, wherein reporting comprises reporting a future maximum time at which the UE can predict channel state information.

14. The UE of claim 13, wherein the instructions, when executed by the one or more processors, further cause the execution of transmitting a first precoding matrix corresponding to the first predicted channel state information to a network node (gNB).

15. The UE of claim 14, wherein the first predicted channel state information is predicted for a first point in time that is a set time interval after transmitting legacy channel state information.

16. The UE of claim 14, wherein the first predicted channel state information is predicted for a first point in time that is a set time interval after a time when a most recent CSI-RS was received by the UE.

17. The UE of claim 14, wherein transmitting a first precoding matrix comprises transmitting an array of coefficients, the first precoding matrix being part of an array product of the array of coefficients and a plurality of bases.

18. The UE of claim 17, wherein:

The instructions, when executed by the one or more processors, further cause performance of:

19. The UE of claim 18, wherein:

20. A User Equipment (UE), comprising:

means for processing; and

a memory storing instructions that, when executed by means for processing, cause execution of:

receiving, by the UE, a second CSI-RS; and