Patent ID: 12231265

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The structure and use of disclosed embodiments are discussed in detail below. It should be appreciated, however, that the present disclosure provides many applicable concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific structure and use of embodiments, and do not limit the scope of the disclosure.

FIG.1illustrates an example wireless communication system100. Communication system100includes an access node110with coverage area111. Access node110serves a plurality of user equipments (UEs), including UE120and UE122. UEs in the communication system can be in the form of mobile terminals, PCs, tablets, wearable devices (watches, etc.) and other equipment having a capability of communicating wirelessly with an access node. Transmissions from access node110to a UE is referred to as a downlink (DL) transmission and occurs over a downlink channel (shown inFIG.1as a solid arrowed line112), while transmissions from a UE to access node110is referred to as an uplink (UL) transmission and occurs over an uplink channel (shown inFIG.1as a dashed arrowed line114). Services may be provided to the plurality of UEs by service providers connected to access node110through a backhaul network130, such as the Internet. The wireless communication system100may include multiple distributed access nodes110.

In a typical communications system, there are several operating modes. In a cellular operating mode, communications to and from the plurality of UEs go through access node110, while in device to device communications mode, such as proximity services (ProSe) operating mode, for example, direct communication between UEs is possible. Access nodes may also be commonly referred to as Node Bs, evolved Node Bs (eNBs), next generation (NG) Node Bs (gNBs), master eNBs (MeNBs), secondary eNBs (SeNBs), master gNBs (MgNBs), secondary gNBs (SgNBs), network controllers, control nodes, base stations, access points, transmission points (TPs), transmission-reception points (TRPs), cells, carriers, macro cells, femtocells, pico cells, relays, customer premises equipment (CPE), and so on. UEs may also be commonly referred to as mobile stations, mobiles, terminals, users, subscribers, stations, communication devices, CPEs, relays, Integrated Access and Backhaul (IAB) relays, and the like. It is noted that when relaying is used (based on relays, picos, CPEs, and so on), especially multihop relaying, the boundary between a controller and node controlled by the controller may become blurry, and a dual node (either the controller or the node controlled by the controller) deployment where a first node that provides configuration or control information to a second node is considered to be the controller. Likewise, the concept of UL and DL transmissions can be extended as well. In some circumstances (such as in sidelink, vehicle-to-vehicle (V2V), vehicle-to-anything (V2X), etc., communications), a UE may operate in an access node like manner. In such situations, UEs may also be referred to as nodes.

FIG.2illustrates an example communications system200, providing mathematical expressions of signals transmitted in the communications system. Communications system200includes an access node205communicating with a UE210. As shown inFIG.2, a DL transmission, received at UE210, is expressible as
y=HHx+n
where H: nT×nRis the multiple input multiple output (MIMO) channel matrix, HHis the Hermitian of H, nTis the number of transmit antennas, nRis the number of receive antennas, x: nT×1 is the transmitted signal vector, y: nR×1 is the received signal vector, and n: nR×1 is the received noise vector. Additionally, x is the precoding signal, expressible as
x=Ws,
where: W: nT×r is the precoding matrix or weights, r is the transmission rank, and s: r×1 is the vector of transmitted data symbols. The precoding matrix W is selected, in conjunction with the channel matrix H, to maximize the sum data rate, for example.

For DL channel estimation at UE210, one typical technique involves sending the pilot at each antenna port on one or a set of orthogonal time-frequency resources. Let hi′ be the ithrow of H, then the received pilot signal at the UE is expressible as
yi=hi′Hxi+n,i=1,. . . ,nT.
In this case, the pilots xiare known to UE210. It is then possible for UE210to determine or estimate hi′H, from the equation of yigiven above, with i=1, . . . ,nT, consequently, the whole HH.

AlthoughFIG.2depicts only one access node and one UE, communication system200is not limited to this case. Multiple UEs may be served by the access node, on different time-frequency resources (such as in FDM-TDM communication systems, as in typical cellular systems) or on the same time-frequency resources (such as in multi-user MIMO (MU-MIMO) communication systems, wherein multiple UEs are paired together and transmissions to each UE are individually precoded).

Other mathematical notation used in the discussion is as follows:

{circumflex over (r)}: feedback rank;

Ŵ: nT×{circumflex over (r)} mapped preferred precoding matrix from feedback precoding matrix index (PMI);

{circumflex over (γ)}i: mapped signal plus interference to noise ratio (SINR) of layer i, i=1, . . . , {circumflex over (r)}, from feedback channel quality indicator (CQI);

{circumflex over (D)}: {circumflex over (r)}×{circumflex over (r)} diagonal matrix with diagonal entries being {circumflex over (γ)}i;

ĥ1, Ĥ1: estimated one column or group of columns of DL channel from UL channel sounding. Sometimes replaced with actual values h1, H1, by assuming good channel estimation with high accuracy;

{tilde over (h)}1: normalized ĥ1;

Ĥ: approximated channel matrix from CSI feedback;

Z: matrix after projectingto the orthogonal subspace;

w1, W1: transmit precoding column or part 1, obtained from SRS estimated channel ĥ1, Ĥ1:;

w2, W2: transmit precoding column or part 2, obtained from approximated channel and projection;

RT: nT×nTchannel spatial covariance at transmitter;

RR: nR×nRchannel spatial covariance at receiver;

U: nT×rRTeigenvectors with non-zero eigenvalues; rRTis the rank of RT;

Ud: nT×d, d dominant eigenvectors from U, d≤rRT;

∧: rRT×rRTdiagonal matrix with non-zero eigenvalues λ1, i=1, . . . , rRT;

C: rRT×rRRindependent and identically distributed (i.i.d.) Gaussian complex matrix for fading channel generation;

Ŵ: channel subset defined by feedback PMI;

RŴ: transmit conditional covariance, conditioned on Ŵ by the feedback PMI;

UŴW: nT×rRŴeigenvectors with non-zero eigenvalues, rRŴis the rank of RŴ;

UŴ,d: nT×d, d dominant eigenvectors from UŴ, d≤rRŴ; and

∧Ŵ: rRŴ×rRŴdiagonal matrix with non-zero eigenvalues λ1, i=1, . . . , rRŴ.

As discussed previously, many UEs, especially low-cost UEs, are incapable of simultaneously transmitting using all available antennas, while they are often able of simultaneously receiving using all available antennas. This restriction is due to the UEs having fewer transmit radio frequency (RF) chains than antennas. The limitation may be a cost reducing measure.

FIG.3illustrates an example UE300. As shown inFIG.3, UE300includes two antennas, antenna305and antenna307. UE300is capable of simultaneously receiving using both antennas, but UE300is capable of simultaneously transmitting only on one antenna due to a limitation on the number of RF transmit chains present in UE300. Some UEs have switching circuitry that will allow the UEs to transmit on a first antenna and then switch to a second antenna to make a subsequent transmission, for example. However, these UEs are still incapable of simultaneously transmitting using all available antennas and require multiple transmission opportunities to transmit on all antennas.

UE300is a specific example of a hardware limited UE, where the UE has Y total antennas that are all capable of simultaneously receiving. However, UE has only X RF transmit chains (where X is less than Y), hence the UE can only simultaneously transmit on X antennas. In order for the UE to transmit over all Y antennas, the UE would require multiple transmission opportunities, enabling the UE to transmit on a first set of X antennas, switch to a second set of X antennas and transmit on the second set of X antennas, and so on.

Additionally, some low-cost UEs do not include switching circuitry that would enable them to switch between different sets of transmit antennas. In such a situation, these UEs would only be able to transmit on a particular set of antennas, and not be able to switch to other antennas. The example embodiments presented herein are focused on these low-cost UEs. However, the example embodiments are also applicable to UEs with switching circuitry, but for are not switching transmit antennas. Perhaps due to time constraints, for example.

A first technique that may be used to obtain information about a DL channel is CSI feedback. CSI feedback is typically used in FDD communication systems. In CSI feedback, an access node transmits reference signals (such as CSI reference signals (CSI-RS)), which are used by a UE that receives the reference signals to make measurements of the DL channels. The UE generates channel information from the measurements and reports the channel information to the access node. The channel information that is reported to the access node includes:

Rank feedback {circumflex over (r)};

PMI feedback Ŵ=[ŵ1, . . . , ŵ{circumflex over (r)}]; and

CQI feedback γ1, . . . , γ{circumflex over (r)}.

However, CSI feedback is quantized to reduce communication overhead, and the quantization of the channel information results in quantization error. Quantization error is the difference between an actual value and its quantized value. The quantization error reduces the accuracy of the channel information reported by the UE; leading to errors in the channel estimation determined from the channel information.

A second technique that may be used to obtain information about a DL is utilizing channel reciprocity on channel measurements based on UL channel sounding. The UL channel sounding based technique is usually used in TDD communication systems. In the UL channel sounding based technique, a UE transmits reference signals (e.g., sounding reference signals (SRSs)), which are used by an access node that receives the reference signals to make measurements of the UL channels. The access node generates channel information for the DL channels from the measurements. Because in TDD communication systems the UL channels and the DL channels share a common frequency band, channel reciprocity enables the measurements made on the UL channels to apply to the DL channels.

However, because some UEs, especially low-cost UEs, are incapable of simultaneously transmitting on all antennas, the access node is not able to make measurements of all of the UL channels in a single transmission opportunity. Hence, the access node is unable to generate channel information for all of the DL channels.

A complete channel matrix is expressible as
H=[h1, . . . ,hNR].

However, in the UL channel sounding based technique involving UEs with the hardware constraint that limits the number of simultaneous transmissions the UEs are able to make, the access node is only able to make measurements of a subset of the total number of UL channels. In other words, the channel information for the DL channels that is not associated with the UL channels over which the UE transmitted the reference signals is missing. Hence, the channel information for the DL channels is expressible as
[hs1,hs2, . . . ]
where s1, s2, . . . ∈{1, . . . , NR}.

When the channel information for the DL channels is determined based on CSI feedback, the following information is available

Rank feedback {circumflex over (r)};

PMI feedback Ŵ=[ŵ1, . . . , ŵ{circumflex over (r)}]; and

CQI feedback γ1, . . . , γ{circumflex over (r)},

where the CQI feedback is the quantized signal to noise ratio (SNR) for each layer. Additionally, in 3GPP LTE or 5G, the CQI feedback corresponds to one codeword that may be mapped to multiple layers. Then, for these layers, the CQI values will be the same. As an example, with rank 4, in 3GPP LTE, γ1=γ2and γ3=γ4, and for 5G, γ1=γ2=γ3=γ4.

According to an example embodiment, methods and apparatus for enhancing channel estimation utilizing both the UL channel sounding based technique for determining information for the DL channels and the CSI feedback are provided. Utilizing both the UL channel sounding based technique and the CSI feedback to perform channel estimation helps to overcome the quantization error present in the channel information reported in the CSI feedback, as well as the missing information for the DL channels not associated with the UL channels over which the UE transmitted reference signals.

In an embodiment, the channel information for the DL channels derived from the CSI feedback is projected onto an orthogonal subspace of the DL channels associated with the UL channels over which the UE transmitted reference signals. Projecting the channel information for the DL channels derived from the CSI feedback onto the orthogonal subspace of the DL channels associated with the UL channels over which the UE transmitted reference signals provides an estimate of the channel information of the DL channels not associated with the UL channels over which the UE transmitted reference signals. The orthogonal projection helps to reduce the quantization error that is present in the CSI feedback, which would degrade performance.

In an embodiment, one or more dominant eigenvectors of the orthogonal projection is selected as the channel information of the DL channels not associated with the UL channels over which the UE transmitted reference signals.

In an embodiment, the combination of the channel information of the DL channels associated with the UL channels over which the UE transmitted reference signals and the one or more dominant eigenvectors of the orthogonal projection is used as the channel matrix H. The one or more dominant eigenvectors of the orthogonal project may be used as the channel information missing due to UE's inability to transmit reference signals using all of its antennas.

For discussion purposes, consider a rank2link between an access node and a UE, but the UE has only one transmit RF chain and two antennas. Therefore, the UE can only transmit reference signals on one of its two antennas. The limitation may be due to hardware limitations, e.g., a single transmit RF chain or no switching circuitry. Hence, the UE can transmit only on one antenna in a single transmission opportunity. The channel matrix H is expressible as H=[h1, h2]. The channel information determined from the reference signals transmitted by the UE is denoted ĥ1. It is assumed that there is no channel estimation error in determining the channel information based on the reference signals transmitted by the UE. Therefore, h1=ĥ1. Although the discussion focuses on the first of two antennas being used by the UE to transmit reference signals, the example embodiments are operable with the second of two antennas being used by the UE to transmit reference signals.

The CSI feedback reported by the UE is denoted: rank {circumflex over (r)}k=2, PMI Ŵ=[ŵ1, ŵ2], and CQI γ1, γ2.

It is possible to find a better matrix W to improve the sum rate, i.e.,
R=log2det(I+WHHHHW),
where R is the sum rate. In other words, W is the precoding matrix used to precode transmissions transmitted over the rank two link.

Ideally, W is the semi-unitary matrix arising from the singular value decomposition (SVD) of H. W may be expressed as

W=[h1^❘"\[LeftBracketingBar]"h1^❘"\[RightBracketingBar]"w2].
Therefore, because ĥ1is known (the channel information determined from the reference signals transmitted by the UE), only w2needs to be determined to find W.

Assuming that w2is on the orthogonal subspace of h1, Ĥ is the estimated channel matrix determined from the CSI feedback and is expressible as
Ĥ=Ŵ·{circumflex over (D)}1/2and {circumflex over (∧)}=diag{[γ1,γ2]}.

The channel matrix from the CSI feedback, projected onto the orthogonal subspace of h1, is expressible as

Z=(I-h~1⁢h~1H)⁢H⁢and⁢h~1=h1^h1^.

Then the one or more dominant eigenvectors of Z is selected as the solution for w2. With the solution for w2found, the precoding matrix W is known. Transmissions from the access node may be precoded using W and transmitted over the rank 2 link to the UE.

In general, consider a rank M link (where M is greater than or equal to 2) between an access node and a UE, but the UE does not have as many transmit RF chains as antennas. Therefore, the UE can only transmit reference signals on a subset of its antennas. The channel matrix H is expressible as H=[H1H2], where H1is the channel information determined from the reference signals transmitted by the UE, and H2is missing. It is assumed that there is no channel estimation error in determining the channel information based on the reference signals transmitted by the UE. Therefore, H1=Ĥ1.

The channel matrix derived from CSI feedback is expressible as
Ĥ=Ŵ·{circumflex over (D)}1/2,
where

D^=[γ10⋱0γr^].

Ideally, W is the semi-unitary matrix arising from the SVD of H. W may be expressed as
W=[W1W2],

where W1are the dominant eigenvectors of H1. Therefore, because Ĥ1is known (the channel information determined from the reference signals transmitted by the UE), W1is known, and only W2needs to be determined to find W.

The channel matrix from the CSI feedback, projected onto the orthogonal subspace of H1, is expressible as
Z=(I−H1H1†)ĤandH1†=(H1HH1)−1H1H.

Then the one or more dominant eigenvectors of Z is selected as the solution for W2. With the solution for W2found, the precoding matrix W is known. Transmissions from the access node may be precoded using Wand transmitted over the rank M link to the UE.

Alternatively, it is possible to take some dominant eigen directions of H1, and W1, and project Ĥ onto the orthogonal subspace of W1. Then, the eigen decomposition of H1is expressible as
H1=V1D11/2V1H,
and select d1dominant eigenvectors from V1and form W1.

With the projection onto the orthogonal subspace being defined as
Z=(I−W1W1H)Ĥ,
the d2dominate eigenvectors of Z are selected as the solution for W2. The final solution for W is W=[W1W2], as stated above. The sizes d1and d2may be determined based on the eigenvalues of H1and Z, as well as the overall rank of W.

FIG.4illustrates a flow diagram of example operations400occurring in a node communicating with, for example, other nodes or UEs, using a channel matrix generated in accordance with channel information obtained from both CSI feedback and UL reference signals. Operations400may be indicative of operations occurring in a node as the node communicates using a channel matrix generated in accordance with channel information obtained from both CSI feedback and UL reference signals. The node may be an access node making a DL transmission or some other device estimating the DL channel for the access node making the DL transmission.

Operations400begin with the node estimating DL channels in accordance with reference signals received on UL channels (block405), such as received from a UE. The node may make measurements of the UL channels conveying the reference signals (e.g., SRS) and estimate the UL channels based on the channel measurements. Utilizing channel reciprocity, the node is able to estimate the DL channels that correspond to the UL channels. However, due to UE limitations (where the UE is incapable of transmitting on all UL channels, for example), the node may not be able to estimate all of the DL channels. Therefore, the DL channel estimates using the UL reference signals are referred to as partial channel measurements. As an example, if the UE is only able to simultaneously transmit on two UL channels, the node is able to estimate only two DL channels that correspond to the two UL channels, independent of the total number of DL channels between the node and the UE.

The node receives CSI feedback (block407). The CSI feedback may be received from the UE. The CSI feedback may include a rank indicator, PMI feedback, and CQI feedback. The CSI feedback may be quantized to reduce communication overhead. The CSI feedback may be optionally filtered or denoised (block409). The filtering or denoising of the CSI feedback may be performed by the node or another device in the communication system. Filtering or denoising the CSI feedback improves the quality of the estimation of the DL channels. The filtering or denoising of the CSI feedback may utilize channel statistics, such as conditional covariance or correlation, or instantaneous fading channel. A detailed discussion of filtering or denoising the CSI feedback is provided below.

The node estimates the DL channels with orthogonal subspace projections (block411). The node uses the CSI feedback and the DL channel estimates based on the UL reference signals to estimate the DL channel. The CSI feedback (which are quantized) and the DL channel estimates based on the UL reference signals (which are partial in nature) are used to approximate all of the DL channels. As an example, the node projects the quantized DL channel estimates (from the CSI feedback) onto an orthogonal subspace of the DL channels estimated based on the UL reference signals to estimate DL channels not estimated in accordance with the UL reference signals.

The node communicates using the DL channel information (block413). The DL channel information comprises DL channel estimates based on the UL reference signals (as obtained in block405, for example) and DL channel estimates of DL channels not associated with the UL channels conveying reference signals. As an example, the node precodes data being transmitted with a precoder derived from the DL channel information and transmits the precoded data.

FIG.5illustrates a flow diagram of example operations500occurring in a node estimating DL channel information with orthogonal subspace projection. Operations500may be indicative of operations occurring in a node as the node estimates DL channel information with an orthogonal subspace projection. Operations500may be an example implementation of block411ofFIG.4.

The node generates a partial precoder using channel information derived based on the UL reference signals (block505). As discussed previously, W is the semi-unitary matrix arising from the SVD of H, and W may be expressed as W=[W1W2], where W1are the dominant eigenvectors of H1, which are determined from the UL reference signals transmitted by the UE and are known.

The node projects the channel information provided by the CSI feedback (Ĥ=Ŵ·{circumflex over (D)}1/2) onto the orthogonal subspace of H1(block507). Projecting the channel information provided by the CSI feedback (which is complete, but may include errors due to the quantization process used to reduce communication overhead) onto the orthogonal subspace helps to mitigate the impact of the quantization error. The projection onto the orthogonal subspace is expressible as Z=(I−H1H1†)Ĥ, where H1†=(H1HH1)−1H1H. The node identifies dominant eigenvector of Z (block509). The dominant eigenvectors of Z are identified and used as the solution for the remainder of the precoder W. In other words, the dominant eigenvectors of Z are used as the solution for W2. In an embodiment, a number of dominant eigenvectors of Z identified is equal to the number of DL channels lacking channel information estimates (i.e., the number of columns of W2). As an example, if there is a total of three DL channels and the UE is only able to transmit using one transmit RF chain, then there are two DL channels lacking channel information estimates (because there is only one DL channel with channel information derived for UL reference signals). In such a situation, the two dominant eigenvectors of Z are identified and used as the solution for W2.

In an embodiment, dominant eigen directions of the precoder and the DL channel information derived from UL reference signals are used rather than the actual precoder and DL channel information in orthogonal subspace projection. Utilizing the dominant eigen directions may help to simplify the orthogonal subspace projection.

FIG.6illustrates a flow diagram of example operations600occurring in a node determining a precoder for DL channels in accordance with estimated channel information. Operations600may be indicative of operations occurring in a node as the node determines a precoder for DL channels in accordance with estimated channel information. Operations600may be an example implementation of block411ofFIG.4.

Operations600begin with the node performing the eigen decomposition of the channel information of the DL channels derived from UL reference signals, H1(block605). The eigen decomposition of H1may be expressed as H1=V1D11/2V1H. The node selects the d1dominant eigenvectors from V1and forms W1, where d1is the number of DL channels derived from the UL reference signals (block607).

The node projects the channel information provided by the CSI feedback (Ĥ=Ŵ·{circumflex over (D)}1/2) onto the orthogonal subspace of W1(block609). Projecting the channel information provided by the CSI feedback (which is complete, but may include errors due to the quantization process used to reduce communication overhead) onto the orthogonal subspace helps to mitigate the impact of the quantization error. The projection onto the orthogonal subspace is expressible as Z=(I−W1W1H)Ĥ. The node selects the dominant eigenvectors of Z as the solution for W2(block611). In an embodiment, the node selects the d2dominant eigenvectors as the solution for W2, where d2is the number of DL channels not associated with the UL reference signals. The precoder for the DL channels is determined as W=[W1W2] (block613).

In an embodiment, the CSI feedback may be processed to improve the quality of the estimation of the DL channels. The processing of the CSI feedback includes filtering or denoising using channel statistics, such as channel covariance or correlation, or instantaneous fading channel. As an example, the impact of the channel covariance or correlation on the sum rate at the transmitter is expressible as an eigen decomposition
RT=U∧UH.

While for the instantaneous fading channel, the channel information is expressible as
H=RT1/2CRR1/2.

Under the assumption that there is no receive correlation, C is an i.i.d. random matrix, allowing the channel information to be re-expressed as
H=UA1/2C.

The same correlations may be applicable to any channel vector at any receive antenna at the UE. Furthermore, for most situations, R is not a full rank matrix, ∧ comprises the non-zero eigenvalues, and U is then a semi-unitary matrix. In an embodiment, the dominant eigenvalues may be selected.

FIG.7illustrates an example node700highlighting circuitry to enhance channel estimation utilizing both a UL channel sounding based technique for determining DL channel information and CSI feedback, where node700improves the quality of the DL channel estimates by processing the CSI feedback. Examples of the processing include filtering, denoising, or both filtering and denoising.

Node700includes a CSI feedback processing unit705configured to perform processing of the CSI feedback received by node700. As an example, CSI feedback processing unit705filters, denoises, or filters and denoises the CSI feedback received by node700. The processed CSI feedback, denoted Ĥ, is refined version of the channel information reported in the CSI feedback, which is quantized and may include quantization error. The processed CSI feedback Ĥ generally has less quantization error (when compared to the CSI feedback that has not been processed) due to the processing performed by CSI feedback processing unit705, which may average, filter, or smooth out the channel information reported in the CSI feedback, for example.

Node700also includes a projection unit707configured to project channel information (e.g., the processed CSI feedback Ĥ) on the orthogonal subspace of the channel information derived from UL reference signals H1(such as in block507ofFIG.5or block609ofFIG.6). Node700further includes a selection unit709configured to select one or more dominant eigenvectors of the projection Z provided by projection unit707. The number of dominant eigenvectors selected by selection unit709may be dependent on the number of DL channels not associated with UL channels conveying UL reference signals. In other words, selection unit709selects a number of dominant eigenvectors equal to the number of DL channels that are without channel information derived from UL reference signals.

Example processing performed by CSI feedback processing unit705includes, but is not limited to:

Minimum mean square error (MMSE) filtering;

Denoising via projection of dominant subspaces;

Maximum fairness (MF)/maximum ratio combining (MRC) based filtering;

Quadratic programming.

As related to MMSE or linear MMSE (LMMSE) filtering, with CSI feedback, the signal model for the feedback PMI with quantization noise is expressible as
Ŵ{circumflex over (D)}1/2=U∧1/2C+N.

After MMSE or LMMSE filtering, the fading channel at the receiver (denoted Ĉ) and the processed CSI feedback (denoted Ĥ) are expressible as

Cˆ=Λ12⁢UH(R+σ2⁢I)-1⁢W^·Dˆ1/2,andHˆ=U⁢Λ1/2⁢Cˆ=R⁡(R+σ2⁢I)-1⁢W^·Dˆ1/2.

A projection on the orthogonal subspace of the channel information derived from UL reference signals H1, determined by projection unit707, is expressible, for example, as
Z=(I−{tilde over (h)}1{tilde over (h)}1H)Ĥ.

Selection unit709selects the one or more dominant eigenvectors of Z as the solution for W2.

As related to denoising via projection of dominant subspaces, a projection of the dominant eigenspaces of the covariance (performed by CSI feedback processing unit705, for example) is expressible as
PR=UdUdH.

The CSI feedback may be denoised with the projection (again, by CSI feedback processing unit705, for example), resulting in the processed CSI feedback Ĥ
Ĥ=PR·Ŵ·{circumflex over (D)}1/2.

Projection unit707projects the processed CSI feedback Ĥ on orthogonal subspace of the channel information derived from UL reference signals H1, which may be expressed, for example, as
Z=(I−{tilde over (h)}1{tilde over (h)}1H)Ĥ.

Selection unit709selects the one or more dominant eigenvectors of Z as the solution for W2.

As related to MF/MRC based filtering, a quantization model is expressible as
Ŵ{circumflex over (D)}1/2=U∧1/2C+N.

CSI feedback processing unit705may denoise the CSI feedback using a MRC filter, and the fading channel at the receiver (denoted Ĉ) and the processed CSI feedback (denoted Ĥ) are expressible as

C^=Λ12⁢UH⁢W^·D^1/2,and⁢H^=U⁢Λ1/2⁢C^=R·W^·D^1/2.

Projection unit707projects the processed CSI feedback Ĥ on orthogonal subspace of the channel information derived from UL reference signals H1, which may be expressed, for example, as
Z=(I−{tilde over (h)}1{tilde over (h)}1H)Ĥ.

Selection unit709selects the one or more dominant eigenvectors of Z as the solution for W2.

As related to quadratic programming, high rank channel reconstruction may be performed. The channel reconstruction may be expressed as

maxC′H⁢W^⁢Dˆ1/22=C′⁢H⁢Λ1/2⁢UH⁢W^⁢Dˆ1/22->maxC′T⁢r⁢{C′⁢H⁢Λ1/2⁢UH⁢W^⁢Dˆ⁢W^H⁢U⁢Λ1/2⁢C′}.

Assume that C′ is semi-unitary, i.e., C′ is the dominant eigenvectors of
∧1/2UHŴ{circumflex over (D)}ŴHU∧1/2,

then the channel may be reconstructed as
Ĥ=U∧1/2Ĉ.

Projection unit707projects the processed CSI feedback Ĥ on orthogonal subspace of the channel information derived from UL reference signals H1, which may be expressed, for example, as
Z=(I−{tilde over (h)}1{tilde over (h)}1H)Ĥ.

Selection unit709selects the one or more dominant eigenvectors of Z as the solution for W2.

Some or all of CSI feedback processing unit705, projection unit707, and selection unit709may be implemented in software executing in one or more processors, one or more integrated circuits (such as field programmable logic arrays (FPGAs) or application-specific integrated circuits (ASICs)), etc. In performance critical implementations, computationally heavy portions may be implemented as integrated circuits that operate in cooperation with software executing on one or more processors.

In an embodiment, the CSI feedback may be processed with a conditional covariance to improve the quality of the estimation of the DL channels. In situations when there is CSI feedback, the channel is not independent from the feedback PMI. Then, it is possible to consider the following conditional covariance (which is conditional on the feedback PMI) for a channel set with given feedback Ŵ
Ŵ{H∈CnT×nR:R(H,Ŵ)≥R(H,W),W∈C,hi( )C(O,R)}
RŴE{HHH|H∈Ŵ}.
The eigen decomposition of RŴis expressible as
RŴ=UŴ∧ŴUŴH.

FIG.8illustrates an example node800highlighting circuitry to enhance channel estimation utilizing both a UL channel sounding based technique for determining DL channel information and CSI feedback, where node800improves the quality of the DL channel estimates by processing the CSI feedback with a conditional covariance. Examples of the processing include filtering, denoising, or both filtering and denoising.

Node800includes a covariance unit805configured to determine a conditional covariance for the feedback PMI (denoted RŴ). As an example, the CSI feedback defines a subset of channels that is measured to derive the feedback reported by the CSI feedback. Therefore, the channel statistics may be a covariance that is conditional on the CSI feedback (in particular, the PMI feedback portion of the CSI feedback).

Node800also includes a CSI feedback processing unit807configured to perform processing of the CSI feedback received by node800. As an example, CSI feedback processing unit807filters, denoises, or filters and denoises the CSI feedback received by node800in combination with the conditional covariance provided by covariance unit805. The processed CSI feedback, denoted Ĥ, is refined version of the channel information reported in the CSI feedback, which is quantized and may include quantization error. The processed CSI feedback Ĥ generally has less quantization error due to the processing performed by CSI feedback processing unit807, which may average or smooth out the channel information reported in the CSI feedback, for example.

Node800also includes a projection unit809configured to project channel information (e.g., the processed CSI feedback Ĥ) on the orthogonal subspace of the channel information derived from UL reference signals H1(such as in block507ofFIG.5or block609ofFIG.6). Node800further includes a selection unit811configured to select one or more dominant eigenvectors of the projection Z provided by projection unit809. The number of dominant eigenvectors selected by selection unit811may be dependent on the number of DL channels not associated with UL channels conveying UL reference signals. In other words, selection unit811selects a number of dominant eigenvectors equal to the number of DL channels that are without channel information derived from UL reference signals.

Example processing performed by CSI feedback processing unit807includes, but is not limited to:

Minimum mean square error (MMSE) filtering with the conditional covariance;

Denoising via projection of dominant subspaces with the conditional covariance;

Maximum fairness (MF)/maximum ratio combining (MRC) based filtering with the conditional covariance;

Quadratic programming with the conditional covariance.

The discussion of the example processing performed by CSI feedback processing unit807ofFIG.8presented above also apply when the conditional covariance is used to further enhance the feedback. However, the general covariance matrix presented previously is replaced with a conditional matrix.

Some or all of covariance unit805, CSI feedback processing unit807, projection unit809, and selection unit811may be implemented in software executing in one or more processors, one or more integrated circuits (such as FPGAs or ASICs), etc. In performance critical implementations, computationally heavy portions may be implemented as integrated circuits that operate in cooperation with software executing on one or more processors.

As related to MMSE or linear MMSE (LMMSE) filtering, the processed CSI feedback is expressible as
Ĥ=RŴ(RŴσ2I)−1Ŵ·{circumflex over (D)}1/2.

As related to denoising via projection of dominant subspaces, a projection on the orthogonal subspace is expressible as
PRŴ=UŴ,dUŴ,dH
Ĥ=PRŴ·Ŵ·{circumflex over (D)}1/2.

As related to MF/MRC based filtering, the processed CSI feedback is expressible as
Ĥ=PŴ·Ŵ·{circumflex over (D)}1/2

As related to quadratic programming, the dominant eigenvectors are expressible as
ĈŴ∝ eigenvectors of (∧Ŵ1/2UŴHŴ{circumflex over (D)}ŴHUŴ∧Ŵ1/2,
and
Ĥ=UŴ·∧Ŵ1/2·ĈŴ.

Performance evaluation of the example embodiments were performed utilizing the following model:

Access node: 8 transmit antenna;

UE: 2 receive antenna;

Channel model:Scattering channel model,Angle spread 15 degrees, random central, uniform power distribution along ring,Access node—cross polarized antennas, cross polarization correlation γ=0.3,UE—antenna correlation 0;

Conditional covariance generation: Monte Carlo;

Measurement:
RateR=log2det(I+WHHHHW);

Given channel covariance R and codebook C, obtain the conditional covariance as:Eigen decomposition of R and nonzero eigen mode
R=U∧UH,Generate N samples of {H} according to
H=U∧1/2C,where cijin C is i.i.d. complex Gaussian with unit variance,For each H, search the PMI in codebook C based on a certain criterion, e.g., MIMO capacity. With the resulting matrix W, put the channel H to the setW.For each setWW∈C, a conditional covariance RŴis obtained by averaging of HHHH∈W.

FIG.9Aillustrates a data plot900of downlink SNR vs sum rate R, comparing the embodiment techniques with CSI feedback only channel information. As shown inFIG.9A, the sum rate R for CSI feedback only (line905) and a rank 1 channel (line910) is below the embodiment techniques for most values of downlink SNR. Most of the embodiment techniques perform similarly and for any given downlink SNR lie within a region, such as region950.

FIG.9Billustrates a detailed view of region950of data plot900. Region950is shown in greater detail inFIG.9B. As shown inFIG.9B, the embodiment techniques that feature conditional covariance processing offer higher sum rate R (e.g., highlight955) than the embodiment techniques that to do not utilize conditional covariance.

FIG.10illustrates an example communication system1000. In general, the system woo enables multiple wireless or wired users to transmit and receive data and other content. The system1000may implement one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), or non-orthogonal multiple access (NOMA).

In this example, the communication system woo includes electronic devices (ED)1010a-1010c,radio access networks (RANs)1020a-1020b,a core network1030, a public switched telephone network (PSTN)1040, the Internet1050, and other networks1060. While certain numbers of these components or elements are shown inFIG.10, any number of these components or elements may be included in the system1000.

The EDs1010a-1010care configured to operate or communicate in the system1000. For example, the EDs1010a-1010care configured to transmit or receive via wireless or wired communication channels. Each ED1010a-1010crepresents any suitable end user device and may include such devices (or may be referred to) as a user equipment or device (UE), wireless transmit or receive unit (WTRU), mobile station, fixed or mobile subscriber unit, cellular telephone, personal digital assistant (PDA), smartphone, laptop, computer, touchpad, wireless sensor, or consumer electronics device.

The RANs1020a-1020bhere include base stations1070a-1070b,respectively. Each base station1070a-1070bis configured to wirelessly interface with one or more of the EDs1010a-1010cto enable access to the core network1030, the PSTN1040, the Internet1050, or the other networks1060. For example, the base stations1070a-1070bmay include (or be) one or more of several well-known devices, such as a base transceiver station (BTS), a Node-B (NodeB), an evolved NodeB (eNodeB), a Next Generation (NG) NodeB (gNB), a Home NodeB, a Home eNodeB, a site controller, an access point (AP), or a wireless router. The EDs1010a-1010care configured to interface and communicate with the Internet1050and may access the core network1030, the PSTN1040, or the other networks1060.

In the embodiment shown inFIG.10, the base station1070aforms part of the RAN1020a,which may include other base stations, elements, or devices. Also, the base station1070bforms part of the RAN1020b,which may include other base stations, elements, or devices. Each base station1070a-1070boperates to transmit or receive wireless signals within a particular geographic region or area, sometimes referred to as a “cell.” In some embodiments, multiple-input multiple-output (MIMO) technology may be employed having multiple transceivers for each cell.

The base stations1070a-1070bcommunicate with one or more of the EDs1010a-1010cover one or more air interfaces1090using wireless communication links. The air interfaces1090may utilize any suitable radio access technology.

It is contemplated that the system1000may use multiple channel access functionality, including such schemes as described above. In particular embodiments, the base stations and EDs implement 5G New Radio (NR), LTE, LTE-A, or LTE-B. Of course, other multiple access schemes and wireless protocols may be utilized.

The RANs1020a-1020bare in communication with the core network1030to provide the EDs1010a-1010cwith voice, data, application, Voice over Internet Protocol (VoIP), or other services. Understandably, the RANs1020a-1020bor the core network1030may be in direct or indirect communication with one or more other RANs (not shown). The core network1030may also serve as a gateway access for other networks (such as the PSTN1040, the Internet1050, and the other networks1060). In addition, some or all of the EDs1010a-1010cmay include functionality for communicating with different wireless networks over different wireless links using different wireless technologies or protocols. Instead of wireless communication (or in addition thereto), the EDs may communicate via wired communication channels to a service provider or switch (not shown), and to the Internet1050.

AlthoughFIG.10illustrates one example of a communication system, various changes may be made toFIG.10. For example, the communication system1000could include any number of EDs, base stations, networks, or other components in any suitable configuration.

FIGS.11A and11Billustrate example devices that may implement the methods and teachings according to this disclosure. In particular,FIG.11Aillustrates an example ED1110, andFIG.11Billustrates an example base station1170. These components could be used in the system1000or in any other suitable system.

As shown inFIG.11A, the ED1110includes at least one processing unit1100. The processing unit1100implements various processing operations of the ED1110. For example, the processing unit1100could perform signal coding, data processing, power control, input/output processing, or any other functionality enabling the ED1110to operate in the system1000. The processing unit1100also supports the methods and teachings described in more detail above. Each processing unit1100includes any suitable processing or computing device configured to perform one or more operations. Each processing unit1100could, for example, include a microprocessor, microcontroller, digital signal processor, field programmable gate array, or application specific integrated circuit.

The ED1110also includes at least one transceiver1102. The transceiver1102is configured to modulate data or other content for transmission by at least one antenna or NIC (Network Interface Controller)1104. The transceiver1102is also configured to demodulate data or other content received by the at least one antenna1104. Each transceiver1102includes any suitable structure for generating signals for wireless or wired transmission or processing signals received wirelessly or by wire. Each antenna1104includes any suitable structure for transmitting or receiving wireless or wired signals. One or multiple transceivers1102could be used in the ED1110, and one or multiple antennas1104could be used in the ED1110. Although shown as a single functional unit, a transceiver1102could also be implemented using at least one transmitter and at least one separate receiver.

The ED1110further includes one or more input/output devices1106or interfaces (such as a wired interface to the Internet1050). The input/output devices1106facilitate interaction with a user or other devices (network communications) in the network. Each input/output device1106includes any suitable structure for providing information to or receiving information from a user, such as a speaker, microphone, keypad, keyboard, display, or touch screen, including network interface communications.

In addition, the ED1110includes at least one memory1108. The memory1108stores instructions and data used, generated, or collected by the ED1110. For example, the memory1108could store software or firmware instructions executed by the processing unit(s)1100and data used to reduce or eliminate interference in incoming signals. Each memory1108includes any suitable volatile or non-volatile storage and retrieval device(s). Any suitable type of memory may be used, such as random access memory (RAM), read only memory (ROM), hard disk, optical disc, subscriber identity module (SIM) card, memory stick, secure digital (SD) memory card, and the like.

As shown inFIG.11B, the base station1170includes at least one processing unit1150, at least one transceiver1152, which includes functionality for a transmitter and a receiver, one or more antennas1156, at least one memory1158, and one or more input/output devices or interfaces1166. A scheduler, which would be understood by one skilled in the art, is coupled to the processing unit1150. The scheduler could be included within or operated separately from the base station1170. The processing unit1150implements various processing operations of the base station1170, such as signal coding, data processing, power control, input/output processing, or any other functionality. The processing unit1150can also support the methods and teachings described in more detail above. Each processing unit1150includes any suitable processing or computing device configured to perform one or more operations. Each processing unit1150could, for example, include a microprocessor, microcontroller, digital signal processor, field programmable gate array, or application specific integrated circuit.

Each transceiver1152includes any suitable structure for generating signals for wireless or wired transmission to one or more EDs or other devices. Each transceiver1152further includes any suitable structure for processing signals received wirelessly or by wire from one or more EDs or other devices. Although shown combined as a transceiver1152, a transmitter and a receiver could be separate components. Each antenna1156includes any suitable structure for transmitting or receiving wireless or wired signals. While a common antenna1156is shown here as being coupled to the transceiver1152, one or more antennas1156could be coupled to the transceiver(s)1152, allowing separate antennas1156to be coupled to the transmitter and the receiver if equipped as separate components. Each memory1158includes any suitable volatile or non-volatile storage and retrieval device(s). Each input/output device1166facilitates interaction with a user or other devices (network communications) in the network. Each input/output device1166includes any suitable structure for providing information to or receiving/providing information from a user, including network interface communications.

FIG.12is a block diagram of a computing system1200that may be used for implementing the devices and methods disclosed herein. For example, the computing system can be any entity of UE, access network (AN), mobility management (MM), session management (SM), user plane gateway (UPGW), or access stratum (AS). Specific devices may utilize all of the components shown or only a subset of the components, and levels of integration may vary from device to device. Furthermore, a device may contain multiple instances of a component, such as multiple processing units, processors, memories, transmitters, receivers, etc. The computing system1200includes a processing unit1202. The processing unit includes a central processing unit (CPU)1214, memory1208, and may further include a mass storage device1204, a video adapter1210, and an I/O interface1212connected to a bus1220.

The bus1220may be one or more of any type of several bus architectures including a memory bus or memory controller, a peripheral bus, or a video bus. The CPU1214may comprise any type of electronic data processor. The memory1208may comprise any type of non-transitory system memory such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), read-only memory (ROM), or a combination thereof. In an embodiment, the memory1208may include ROM for use at boot-up, and DRAM for program and data storage for use while executing programs.

The mass storage1204may comprise any type of non-transitory storage device configured to store data, programs, and other information and to make the data, programs, and other information accessible via the bus1220. The mass storage1204may comprise, for example, one or more of a solid state drive, hard disk drive, a magnetic disk drive, or an optical disk drive.

The video adapter1210and the I/O interface1212provide interfaces to couple external input and output devices to the processing unit1202. As illustrated, examples of input and output devices include a display1218coupled to the video adapter1210and a mouse, keyboard, or printer1216coupled to the I/O interface1212. Other devices may be coupled to the processing unit1202, and additional or fewer interface cards may be utilized. For example, a serial interface such as Universal Serial Bus (USB) (not shown) may be used to provide an interface for an external device.

The processing unit1202also includes one or more network interfaces1206, which may comprise wired links, such as an Ethernet cable, or wireless links to access nodes or different networks. The network interfaces1206allow the processing unit1202to communicate with remote units via the networks. For example, the network interfaces1206may provide wireless communication via one or more transmitters/transmit antennas and one or more receivers/receive antennas. In an embodiment, the processing unit1202is coupled to a local-area network1222or a wide-area network for data processing and communications with remote devices, such as other processing units, the Internet, or remote storage facilities.

It should be appreciated that one or more steps of the embodiment methods provided herein may be performed by corresponding units or modules. For example, a signal may be transmitted by a transmitting unit or a transmitting module. A signal may be received by a receiving unit or a receiving module. A signal may be processed by a processing unit or a processing module. Other steps may be performed by an estimating unit or module, an estimating unit or module, a projecting unit or module, a selecting unit or module, a combining unit or module, a precoding unit or module, a processing unit or module, a filtering unit or module, a denoising unit or module, a determining, a decomposing unit or module, or a communicating unit or module. The respective units or modules may be hardware, software, or a combination thereof. For instance, one or more of the units or modules may be an integrated circuit, such as field programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs).

Although the present disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the scope of the disclosure as defined by the appended claims.