WO2019218317A1

WO2019218317A1 - Eigenvalue-based channel hardening and explicit feedback

Info

Publication number: WO2019218317A1
Application number: PCT/CN2018/087367
Authority: WO
Inventors: Xiaomao Mao; Frederick Vook; Rana Ahmed; William J. Hillery; Eugene Visotsky
Original assignee: Nokia Shanghai Bell Co., Ltd.; Nokia Solutions And Networks Oy; Nokia Technologies Oy
Priority date: 2018-05-17
Filing date: 2018-05-17
Publication date: 2019-11-21
Also published as: CN112119617A; EP3794785A4; EP3794785A1; CN112119617B

Abstract

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 are configured to, with the at least one processor, cause the apparatus to calculate one or more eigenvectors associated with one or more uplink reference signals. The at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more downlink channel state information reference signals. The at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to receive explicit channel state information from a user equipment.

Description

EIGENVALUE-BASED CHANNEL HARDENING AND EXPLICIT FEEDBACK

BACKGROUND: Field:

Certain embodiments may relate to communication systems. For example, some embodiments may relate to channel state information feedback.

Description of the Related Art:

Channel state information (CSI) may include implicit feedback, explicit feedback, and/or a linear combination codebook, which is a hybrid of implicit and explicit feedback. Explicit feedback returns channel information directly. Discrete Fourier Transform (DFT) vectors may be selected and applied to harden a channel, which may reduce the dimensions of the channel from M·N to B·N, where M is the number of transmit antennas, N is the number of receive antennas, and B is the number of precoders employed. Since DFT precoders are considered narrow beams that are being applied to the channel, a resulting aggregate channel matrix becomes sparser due to the channel hardening effect. However, providing explicit feedback can generally require a large amount of network resources for the reporting functions to maintain the accuracy of CSI reports.

SUMMARY:

In accordance with an embodiment, a method may include calculating, by a network entity, one or more eigenvectors associated with one or more uplink reference signals. The method may further include applying, by the network entity, one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The method may further include receiving, by the network entity, explicit channel state information from a user equipment.

In accordance with an embodiment, an apparatus may include at least one processor and at least one memory including computer program code. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least calculate one or more eigenvectors associated with one or more uplink reference signals. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to receive explicit channel state information from a user equipment.

In accordance with an embodiment, an apparatus may include means for calculating one or more eigenvectors associated with one or more uplink reference signals. The apparatus may further include means for applying one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The apparatus may further include means for receiving explicit channel state information from a user equipment.

In accordance with an embodiment, a non-transitory computer readable medium can, in certain embodiments, be encoded with instructions that may, when executed in hardware, perform a process. The process may include a method that may calculate one or more eigenvectors associated with one or more uplink reference signals. The process may include a method that may apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The process may include a method that may receive explicit channel state information from a user equipment.

In accordance with an embodiment, a computer program product may, according to certain embodiments, have instructions encoded for performing a process. The process may include a method that may calculate one or more eigenvectors associated with one or more uplink reference signals. The process may include a method that may further apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The process may include a method that may further receive explicit channel state information from a user equipment.

In accordance with an embodiment, an apparatus may include circuitry configured to calculate one or more eigenvectors associated with one or more uplink reference signals. The apparatus may further include circuitry configured to apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals. The apparatus may further include circuitry configured to receive explicit channel state information from a user equipment.

In accordance with an embodiment, a method may include aggregating, by a user equipment, one or more downlink channels by collecting one or more channel impulse responses. The method may further include estimating, by the user equipment, one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The method may further include transmitting, by the user equipment, explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

In accordance with an embodiment, an apparatus may include at least one processor and at least one memory including computer program code. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least aggregate one or more downlink channels by collecting one or more channel impulse responses. The at least one memory and the computer program code can be configured to, with the at least one processor, further cause the apparatus to at least estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The at least one memory and the computer program code can be configured to, with the at least one processor, further cause the apparatus to at least transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

In accordance with an embodiment, an apparatus may include means for aggregating one or more downlink channels by collecting one or more channel impulse responses. The apparatus may further include means for estimating one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The apparatus may further include means for transmitting explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

In accordance with an embodiment, a non-transitory computer readable medium can, in certain embodiments, be encoded with instructions that may, when executed in hardware, perform a process. The process may include a method that may aggregate one or more downlink channels by collecting one or more channel impulse responses. The process may include a method that may further estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The process may include a method that may further transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

In accordance with an embodiment, an apparatus may include circuitry configured to aggregate one or more downlink channels by collecting one or more channel impulse responses. The apparatus may include circuitry further configured to estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The apparatus may include circuitry further configured to transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

In accordance with an embodiment, an apparatus may include at least one processor and at least one memory including computer program code. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least aggregate one or more downlink channels by collecting one or more channel impulse responses. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. The at least one memory and the computer program code can be configured to, with the at least one processor, cause the apparatus to at least transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.

BRIEF DESCRIPTION OF THE DRAWINGS:

For proper understanding of this disclosure, reference should be made to the accompanying drawings, wherein:

Figure 1 illustrates an example of a signaling diagram according to certain embodiments.

Figure 2 illustrates an example of a method performed by a network entity according to certain embodiments.

Figure 3 illustrates an example of a method performed by a user equipment according to certain embodiments.

Figure 4 illustrates an example of a system according to certain embodiments.

DETAILED DESCRIPTION:

The features, structures, or characteristics of certain embodiments described throughout this specification may be combined in any suitable manner in one or more embodiments. For example, the usage of the phrases “certain embodiments, ” “some embodiments, ” “other embodiments, ” or other similar language, throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. Thus, appearance of the phrases “in certain embodiments, ” “in some embodiments, ” “in other embodiments, ” or other similar language, throughout this specification does not necessarily 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 embodiments.

Certain embodiments may help to improve explicit feedback by a user equipment. The example embodiments described herein may have various benefits and/or advantages. For example, some embodiments may reduce the amount of network resources required for explicit reporting by user equipment while maintaining CSI reporting accuracy. Eigenvectors may be used to harden channels, resulting in a sparse channel that utilizes less network resource overhead. Furthermore, uplink (UL) and/or downlink (DL) channel reciprocity and hardening of the channel at a network entity, such as a gNB, may make channel hardening transparent to the user equipment (UE) , relieving the UE from reporting the eigenvectors or DFT precoders indexes. This reduction in network resource usage may further be achieved while using eigen decomposition techniques to maintain the high accuracy of explicit feedback. Certain embodiments are, therefore, directed to improvements in computer-related technology, specifically, by conserving network resources and reducing power consumption of the UE and/or a network entity located within the network.

Figure 1 illustrates an example of a signaling diagram showing communications between user equipment 130 and network entity 140. User equipment 130 may be similar to user equipment 410, and network entity 140 may be similar to network entity 420, both illustrated in Figure 4. In step 101, UE 130 may transmit one or more UE reference signals to network entity 140. In step 103, network entity 140 may estimate one or more uplink reference signals based on the UE reference signals received from UE 130.

In step 105, network entity 140 may calculate one or more UE channel eigenvectors based on the estimated one or more uplink reference signals. In some embodiments, one or more downlink channel matrices at a physical resource block/sub-band i, estimated from an uplink sounding reference signal, may be denoted by h _i. A spatial channel covariance matrix with current subframe n may then be determined using R _i (n) = h _i ^H·h _i, where H is a conjugate transpose of a matrix, such as the spatial channel covariance matrix. Additionally, an eigen decomposition of R _i (n) may be determined using R _i (n) = U _i·Λ _i·U _i ^H, where U _i is a square matrix whose j ^th column, q _i, j, is the eigenvector of R _i (n) , and Λ _i is a diagonal matrix whose diagonal elements are the corresponding eigenvalues, specifically λ _i, j, where i denotes the PRB index or subband index, and j indicates the element index in the diagonal matrix at the j ^th row and j ^th column. In some embodiments, one or more taps of the channel impulse response may remain after applying each of the selected eigenvectors through channel hardening. By applying one or more channel hardening matrices to one or more CSI-RS ports, one or more aggregated channels at the UE may be sparse, resulting in a reduced number of CIR taps being observed in a time domain. In some embodiments, the number of taps may be limited to one, resulting in the UE reporting explicit feedback with reduced overhead.

In step 107, network entity 140 may select one or more of the one or more UE channel eigenvectors. For example, the number of selected eigenvectors may be represented as B _i. In some embodiments, one or more eigenvectors may be selected to harden one or more channels by setting a threshold t for eigenvalues. The eigenvalues may be in a random order, an increasing order, or a decreasing order, such as λ _i, 1 ≥ λ _i, 2 ≥ λ _i, 3 ≥ λ _i, .... When the eigenvalues are sorted in decreasing order, if the j ^th eigenvalue is greater than the threshold t, the j ^th eigenvector may be used to form a channel hardening matrix. In one embodiment, the channel hardening matrix may be formed using eigenvectors 1, 2, ..., j _max, where j _max= max {j: λ _i, j ＞ t } . In some embodiments, the threshold t may be dependent on the network entity, UE channel, and/or network entity scheduling capacity.

When eigenvectors in a hardening matrix are considered as the beam basis, one or more values, such as B _i, may be required to be greater than a total number of transmit layers, such as r, in order to form orthogonality between the layers, for example, B _i= max (j _max, r) . For explicit polarization (X-pol) antenna arrays, where orthogonality between layers is provided by exploiting cross polarization isolation, B _i may be determined where B _i = max (j _max, r/2) . In embodiments where X-pol antenna arrays are used, a transmitted polarization layer may experience reduced polarization interference. In addition, where multiple co-located x-pol antenna arrays experience channel variation, one or more channel hardening matrices may be applied with half dimensions associated with each of the polarizations.

In some embodiments, UE may be equipped with more reception (RX) antennae than transmission (TX) antennae. In this example, UE TX antenna switching may be provided to enforce UL/DL reciprocity and/or acquire full DL channel functionality by estimating one or more UL sounding reference signals (SRSs) .

UL/DL reciprocity may be preferably conditioned in various embodiments. For example, in a frequency-division duplexing (FDD) system for a paired spectrum, only long-term spatial information may be extracted from the UL and/or may be mapped to the DL transmission. In embodiments where UE downlink channel matrices h _i for physical resource block (PRB) /subband i are estimated from one or more UL SRSs, the spatial channel covariance matrix at a current subframe n may be determined by averaging all of the PRBs/subbands, for example, R (n) = ∑ _i h _i ^H ·h _i, where H is a conjugate transpose. Thus, eigen decomposition of the spatial channel covariance matrix, such as R (n) , may be determined using R (n) = U ·Λ ·U ^H, where U is a square matrix whose j ^th column is the eigenvector q _j of R (n) , and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues.

In step 109, network entity 140 may form one or more channel hardening matrices based upon the one or more selected eigenvectors. For example, the one or more channel hardening matrices may be denoted by Q _i, and may be subband short-term channel hardening matrices and/or wideband long-term channel hardening matrices. In such embodiments, the resulting channel may be determined by Φ _i= h _i ·Q _i. In one embodiment, Q _i = [q _i, 1, q _i, 2, ..., q _i, Bi] .

In addition, channel state information reporting in the time and/or frequency domain may be applied to Φ _i in order to provide explicit CSI feedback. For example, following the eigen decomposition of the spatial channel covariance matrix, a number of eigenvectors, such as B _i, may be selected and used to form a matrix, such as Q, such that Q _i = Q that hardens the channel for all PRB/subbands. A similar process may be performed in time-division duplex (TDD) systems.

In various embodiments, the formation of the one or more channel hardening matrices may be based, in part, upon one or more of antenna array type, duplexing mode (TDD or FDD) , one or more threshold values, or other factors.

In step 111, network entity 140 may apply the one or more channel hardening matrices to one or more user equipment downlink channel state information reference signals. The one or more channel hardening matrices may be applied as precoders to one or more user equipment downlink channel state information reference signals in several ways. For example, network entity 140 may apply each of the precoders in the one or more channel hardening matrices to one or more antenna ports in a channel state information reference signal (CSI-RS) resource. In another example, the network entity may apply each of the precoders in the one or more channel hardening matrices to a single CSI-RS resource in the set of CSI-RS resources. In this example, each of the CSI-RS resources in the set of CSI-RS resources may have multiple antenna ports, allowing the UE to perform further channel hardening. Additionally, the configuration of precoders in the one or more channel hardening matrices may be updated periodically, for example, by transmitting semi-persistent and/or aperiodic CSI-RS to the UE. In step 113, network entity 140 may transmit one or more CSI-RS signals through the downlink channel to user equipment 130.

In step 115, user equipment 130 may estimate one or more CSI-RSs. In addition, prior to estimating one or more CSI-RSs, the user equipment may aggregate one or more downlink channels by collecting one or more channel impulse responses. In some embodiments, the user equipment may aggregate one or more CSI-RSs in several ways. For example, the user equipment may aggregate one or more CSI-RSs by collecting one or more channel impulse responses from each of the CSI-RS ports in the CSI-RS resource associated with each of the user equipment RX antennae. In another example, the user equipment may aggregate one or more CSI-RSs by collecting channel impulse responses from each of the CSI-RS ports associated with each CSI-RS in the set of CSI-RS resources associated with each of the user equipment RX antennae. In some embodiments, the user equipment may support reporting one or more channel impulse responses of the aggregated channel in a time/frequency domain without having to transmit DFT beam index.

In step 117, user equipment 130 may transmit explicit channel state information feedback to the network entity. In some embodiments, user equipment 130 may report one or more channel hardening precoder indexes with the channel impulse responses of the aggregated channel in time/frequency domain without DFT beam indexes to network entity 140. In addition, user equipment 130 may report reciprocity-based explicit feedback in PUCCH-based periodic CSI reporting.

Figure 2 illustrates an example method performed by a network entity. The network entity may be similar to network entity 420 illustrated in Figure 4. In step 201, the network entity may receive one or more reference signals from a user equipment. As an example, the user equipment may be similar to user equipment 410 illustrated in Figure 4. In step 203, the network entity may estimate one or more uplink reference signals. In step 205, the network entity may obtain user equipment downlink channel information associated with a downlink channel of the user equipment.

In step 207, the network entity may calculate one or more eigenvectors associated with one or more uplink reference signals. In some embodiments, one or more downlink channel matrices at a physical resource block/sub-band i estimated from an uplink sounding reference signal may be denoted by h _i. A spatial channel covariance matrix with current subframe n may then be determined using R _i (n) = h _i ^H·h _i, where H is a conjugate transpose. Additionally, an eigen decomposition of R _i (n) may be determined using R _i (n) = U _i·Λ _i·U _i ^H, where U _i is a square matrix whose j ^th column, q _i, j, is the eigenvector of R _i (n) , and Λ _i is a diagonal matrix whose diagonal elements are the corresponding eigenvalues, specifically λ _i, j, where i denotes the PRB index or subband index, and j indicates the element index in the diagonal matrix at the j ^th row and j ^th column. In some embodiments, one or more taps of the channel impulse response may remain after applying each of the selected eigenvectors through channel hardening. By applying one or more channel hardening matrices to one or more CSI-RS ports, one or more aggregated channels at the UE may be sparse, resulting in a reduced number of CIR taps being observed in a time domain. In some embodiments, the number of taps may be limited to one, where the UE may report explicit feedback with reduced overhead.

In step 209, the network entity may select one or more of the eigenvectors. For example, the number of selected eigenvectors may be represented as B _i. In some embodiments, one or more eigenvectors may be selected to harden one or more channels by setting a threshold t for eigenvalues. The eigenvalues may be in a random order, an increasing order, or a decreasing order, such as λ _i, 1 ≥ λ _i, 2 ≥ λ _i, 3 ≥ λ _i, .... When the eigenvalues are sorted in decreasing order, if the j ^th eigenvalue is greater than the threshold t, the j ^th eigenvalue may be used to form a channel hardening matrix. In one embodiment, the channel hardening matrix may be formed using eigenvectors 1, 2, ..., j _max, where j _max = max {j: λ _i, j ＞ t} . In some embodiments, the threshold t may be dependent on the network entity, UE channel, and/or network entity scheduling capacity.

While eigenvectors in a hardening matrix may be considered as the beam basis, one or more values, such as B _i, may be required to be greater than a total number of transmit layers, such as r, in order to form orthogonality between the layers, for example, B _i = max (j _max, r) . For explicit polarization (X-pol) antenna arrays, where orthogonality between layers may be provided by exploring cross polarization isolation, B _i may be determined where B _i = max (j _max, r/2) . In embodiments where X-pol antenna arrays are used, a layer transmitted in one or more of the polarizations may experience reduced polarization interference. In addition, where multiple co-located x-pol antenna arrays experience channel variation, one or more channel hardening matrices may be applied with half dimensions associated with each of the polarizations.

UL/DL reciprocity may be preferably conditioned in various embodiments. For example, in a frequency-division duplexing (FDD) system for a paired spectrum, long-term spatial information may be extracted from the UL, and/or may be mapped to the DL transmission. In embodiments where UE downlink channel matrices h _i for PRB/subband i are estimated from a UL SRS, the spatial channel covariance matrix at a current subframe n may be determined by averaging all of the PRBs/subbands, for example, R (n) = ∑ _i h _i ^H·h _i, where H is a conjugate transpose. Thus, eigen decomposition of the spatial channel covariance matrix, such as R (n) , may be determined using R (n) = U ·Λ ·U ^H, where U is a square matrix whose j ^th column is the eigenvector q _j of R (n) , and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues.

In step 211, the network entity may form one or more channel hardening matrices based upon the one or more selected eigenvectors. For example, the one or more channel hardening matrices may be denoted by Q _i, and may be subband short-term channel hardening matrices and/or wideband long-term channel hardening matrices. In such embodiments, the resulting channel, Φ _i, may be determined by Φ _i = h _i ·Q _i. In one embodiment, Q _i = [q _i, 1, q _i, 2, ..., q _i, Bi] .

In response, channel state information reporting in the time and/or frequency domain may be applied to Φ _i in order to provide explicit CSI feedback. For example, following the eigen decomposition of the spatial channel covariance matrix, a number of eigenvectors, such as B _i, may be selected and used to form a matrix, such as Q. In a sample embodiment, where Q _i equals Q, Q may harden the channel for all PRB/subbands. A similar process may be performed in TDD systems.

The formation of the one or more channel hardening matrices may be based upon one or more of antenna array type, duplexing method (TDD or FDD) , one or more threshold values, or other factors.

In step 213, the network entity may apply the one or more channel hardening matrices to one or more user equipment downlink channel state information reference signals. The one or more channel hardening matrices may be applied as precoders to one or more user equipment downlink channel state information reference signals in several ways. For example, the network entity may apply each of the precoders in the one or more channel hardening matrices to one or more antenna ports in the CSI-RS resource. In another example, the network entity may apply each of the precoders in the one or more channel hardening matrices to a single CSI-RS resource in the set of CSI-RS resources. In this example, each of the CSI-RS resources in the set of CSI-RS resources may have multiple antenna ports, allowing the UE to perform further channel hardening. Additionally, the configuration of precoders in the one or more channel hardening matrices may be updated periodically, for example, by transmitting semi-persistent and/or aperiodic CSI-RS to the UE.

In step 215, the network entity may transmit the one or more downlink channel state information reference signals to the user equipment. In step 217, the network entity may receive explicit channel state information feedback from the user equipment.

Figure 3 illustrates an example method performed by a user equipment, similar to user equipment 410 that is illustrated in Figure 4. In step 301, the user equipment may transmit one or more UE reference signals to a network entity, similar to network entity 420 in Figure 4. In step 303, the user equipment may aggregate one or more downlink channels by collecting one or more channel impulse responses from the network entity.

In step 305, the user equipment may estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels. In some embodiments, the user equipment may aggregate one or more CSI-RSs in several ways. For example, the user equipment may aggregate one or more CSI-RSs by collecting one or more channel impulse responses from each of the CSI-RS ports in the CSI-RS resource associated with each of the user equipment RX antennae. In another example, the user equipment may aggregate one or more CSI-RSs by collecting channel impulse responses from each of the CSI-RS ports associated with each CSI-RS in the set of CSI-RS resources associated with each of the user equipment RX antennae. In some embodiments, the user equipment may support reporting one or more channel impulse responses of the aggregated channel in a time/frequency domain without having to transmit DFT beam index.

In step 307, the user equipment may transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity. In some embodiments, the user equipment may report channel hardening precoder indexes with the channel impulse responses of the aggregated channel in time/frequency domain without DFT beam indexes. In some embodiments, the UE may transmit reciprocity-based explicit feedback in PUCCH-based periodic CSI reporting.

Figure 4 illustrates an example of a system according to certain embodiments. In one embodiment, a system may include multiple devices, such as, for example, user equipment 410 and network entity 420.

UE 410 may include one or more of a mobile device, such as a mobile phone, smart phone, personal digital assistant (PDA) , tablet, or portable media player, digital camera, pocket video camera, video game console, navigation unit, such as a global positioning system (GPS) device, desktop or laptop computer, single-location device, such as a sensor or smart meter, or any combination thereof. Network entity 420 may be one or more of a base station, such as an evolved node B (eNB) or 5G or New Radio node B (gNB) , a serving gateway, a server, and/or any other access node or combination thereof. Furthermore, user equipment 410 and/or network entity 420 may be one or more of a citizens broadband radio service device (CBSD) .

One or more of these devices may include at least one processor, respectively indicated as 411 and 421. At least one memory may be provided in one or more of devices indicated at 412 and 422. The memory may be fixed or removable. The memory may include computer program instructions or computer code contained therein.

Processors

411 and 421 and

memories

412 and 422 or a subset thereof, may be configured to provide means corresponding to the various blocks of Figures 1-3. Although not shown, the devices may also include positioning hardware, such as GPS or micro electrical mechanical system (MEMS) hardware, which may be used to determine a location of the device. Other sensors are also permitted and may be included to determine location, elevation, orientation, and so forth, such as barometers, compasses, and the like.

As shown in Figure 4,

transceivers

413 and 423 may be provided, and one or more devices may also include at least one antenna, respectively illustrated as 414 and 424. The device may have many antennas, such as an array of antennas configured for multiple input multiple output (MIMO) communications, or multiple antennas for multiple radio access technologies. Other configurations of these devices, for example, may be provided.

Transceivers

413 and 423 may be a transmitter, a receiver, or both a transmitter and a receiver, or a unit or device that may be configured both for transmission and reception.

Processors

411 and 421 may be embodied by any computational or data processing device, such as a central processing unit (CPU) , application specific integrated circuit (ASIC) , or comparable device. The processors may be implemented as a single controller, or a plurality of controllers or processors.

Memories

412 and 422 may independently be any suitable storage device, such as a non-transitory computer-readable medium. A hard disk drive (HDD) , random access memory (RAM) , flash memory, or other suitable memory may be used. The memories may be combined on a single integrated circuit as the processor, or may be separate from the one or more processors. Furthermore, the computer program instructions stored in the memory and which may be processed by the processors may be any suitable form of computer program code, for example, a compiled or interpreted computer program written in any suitable programming language. Memory may be removable or non-removable.

The memory and the computer program instructions may be configured, with the processor for the particular device, to cause a hardware apparatus such as user eqnipment to perform any of the processes described below (see, for example, Figures 1-3) . Therefore, in certain embodiments, a non-transitory computer-readable medium may be encoded with computer instructions that, when executed in hardware, perform a process such as one of the processes described herein. Alternatively, certain embodiments may be performed entirely in hardware.

In certain embodiments, an apparatus may include circuitry configured to perform any of the processes or functions illustrated in Figures 1-3. For example, circuitry may be hardware-only circuit implementations, such as analog and/or digital circuitry. In another example, circuitry may be a combination of hardware circuits and software, such as a combination of analog and/or digital hardware circuit (s) with software or firmware, and/or any portions of hardware processor (s) with software (including digital signal processor (s) ) , software, and at least one memory that work together to cause an apparatus to perform various processes or functions. In yet another example, circuitry may be hardware circuit (s) and or processor (s) , such as a microprocessor (s) or a portion of a microprocessor (s) , that include software, such as firmware for operation. Software in circuitry may not be present when it is not needed for the operation of the hardware.

One having ordinary skill in the art will readily understand that certain embodiments discussed above may be practiced with steps in a different order, and/or with hardware elements in configurations which are different than those which are disclosed. Therefore, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the invention. In order to determine the metes and bounds of the invention, therefore, reference should be made to the appended claims.

Partial Glossary

3GPP 3rd Generation Partnership Project

5G 5th Generation Wireless System

ASIC Application-specific Integrated Circuit

CBRS Citizens Broadband Radio Service

CIR Channel Impulse Response

CPU Central Processing Unit

CSI Channel State Information

CSI-RS Channel State Information Reference Signal

DFT Discrete Fourier Transform

DL Downlink

eNB Evolved node B

FDD Frequency-Division Duplex

FTT Fast Fourier Transform

gNB Next Generation node B

GPS Global Positioning System

HDD Hard Disk Drive

IFFT Inverse Fast Fourier Transform

LTE Long-Term Evolution

MEMS Micro Electrical Mechanical System

MIMO Multiple-Input Multiple-Output

MU Multiple-User

NR RAN Next Generation Radio Access Network

NR New Radio

PDA Personal Digital Assistant

PRB Physical Resource Block

PUCCH Physical Uplink Control Channel

QCL Quasi-Co-Location

RAM Random Access Memory

RX Reception

SRS Sounding Reference Signal

TDD Time-Division Duplex

TX Transmission

UE User Equipment

UL Uplink

Claims

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 to:

calculate one or more eigenvectors associated with one or more uplink reference signals;

apply one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals; and

receive explicit channel state information from a user equipment.
The apparatus according to claim 1, wherein the one or more channel hardening matrices are at least one of subband short-term channel hardening matrices and/or wideband long-term channel hardening matrices.
The apparatus according to claims 1 or 2, wherein the formation of the one or more channel hardening matrices is based upon one or more of system configurations and scheduling decisions.
The apparatus according to any of claims 1-3, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to:

determine a spatial channel covariance matrix with a current subframe based upon one or more channel vectors at a physical resource block/subband estimated from one or more uplink sounding reference signals.
The apparatus according to any of claims 1-4, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to:

form the one or more channel hardening matrices based upon one or more selected eigenvectors.
The apparatus according to any of claims 1-5, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to:

transmit one or more downlink reference signals to the user equipment.
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 to:

aggregate one or more downlink channels by collecting one or more channel impulse responses;

estimate one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels; and

transmit explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.
The apparatus according to claim 7, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to:

receive one or more downlink reference signals from the network entity.
The apparatus according to claims 7 or 8, wherein the one or more channel impulse responses are collected from each CSI-RS port in a CSI-RS resource associated with each reception antenna.
The apparatus according to any of claims 7-9, wherein the one or more channel impulse responses are collected from each CSI-RS port associated with one or more CSI-RSs in a set of CSI-RS resources associated with each reception antenna.
A method, comprising:

calculating, by a network entity, one or more eigenvectors associated with one or more uplink reference signals;

applying, by the network entity, one or more channel hardening matrices based upon the one or more eigenvectors to one or more user equipment downlink channel state information reference signals; and

receiving, by the network entity, explicit channel state information from a user equipment.
The method according to claim 11, wherein the one or more channel hardening matrices are at least one of subband short-term channel hardening matrices and/or wideband long-term channel hardening matrices.
The method according to any of claims 11 or 12, wherein the formation of the one or more channel hardening matrices is based upon one or more of system configurations and scheduling decisions.
The method according to any of claims 11-13, further comprising:

determining, by the network entity, a spatial channel covariance matrix with a current subframe based upon one or more channel vectors at a physical resource block/sub-band estimated from an uplink sounding reference signal.
The method according to any of claims 11-14, further comprising:

forming, by the network entity, the one or more channel hardening matrices based upon one or more selected eigenvectors.
The method according to any of claims 11-15, further comprising:

transmitting, by the network entity, one or more downlink reference signals to the user equipment.
A method, comprising:

aggregating, by a user equipment, one or more downlink channels by collecting one or more channel impulse responses;

estimating, by the user equipment, one or more channel state information reference signals (CSI-RSs) based upon the aggregated one or more downlink channels; and

transmitting, by the user equipment, explicit channel state information feedback based upon the one or more estimated CSI-RSs to a network entity.
The method according to claim 17, further comprising:

receiving, by the user equipment, one or more downlink reference signals from the network entity.
The method according to claims 17 or 18, wherein the one or more channel impulse responses are collected from each CSI-RS port in a CSI-RS resource associated with each reception antenna.
The method according to any of claims 17-19, wherein the one or more channel impulse responses are collected from each CSI-RS port associated with one or more CSI-RSs in a set of CSI-RS resources associated with each reception antenna.
A non-transitory computer-readable medium encoding instructions that, when executed in hardware, perform a process according to any of claims 1-20.
An apparatus comprising means for performing a process according to any of claims 1-20.
An apparatus comprising circuitry configured to cause the apparatus to perform a process according to any of claims 1-20.
A computer program product encoded with instructions for performing a process according to any of claims 1-20.