Generating a channel state information (“CSI”) report

Apparatuses, methods, and systems are disclosed for generating a CSI report. One apparatus includes a transceiver that receives a set of reference signals transmitted from a base station and a processor that transforms the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a DFT-compressed codebook. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero. The apparatus transmits CSI feedback that includes an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, and does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam.

FIELD

The subject matter disclosed herein relates generally to wireless communications and more particularly relates to Type-II codebook compression using phase modification of the beams.

BACKGROUND

The following abbreviations are herewith defined, at least some of which are referred to within the following description: Third Generation Partnership Project (“3GPP”), Fifth Generation Core Network (“5CG”), Fifth Generation System (“5GS”), Authentication, Authorization and Accounting (“AAA”), Access and Mobility Management Function (“AMF”), Access to Restricted Local Operator Services (“ARLOS”), Positive-Acknowledgment (“ACK”), Application Programming Interface (“API”), Authentication Center (“AuC”), Access Stratum (“AS”), Autonomous Uplink (“AUL”), AUL Downlink Feedback Information (“AUL-DFP”), Base Station (“BS”), Binary Phase Shift Keying (“BPSK”), Bandwidth Part (“BWP”), Clear Channel Assessment (“CCA”), Control Element (“CE”), Cyclic Prefix (“CP”), Cyclical Redundancy Check (“CRC”), Channel State Information (“CSI”), Common Search Space (“CSS”), Connection Mode (“CM”, this is a NAS state in 5GS), Core Network (“CN”), Control Plane (“CP”), Data Radio Bearer (“DRB”), Discrete Fourier Transform Spread (“DFTS”), Downlink Control Information (“DCI”), Downlink (“DL”), Downlink Pilot Time Slot (“DwPTS”), Dual Connectivity (“DC”), Dual Registration mode (“DR mode”), Enhanced Clear Channel Assessment (“eCCA”), Enhanced Licensed Assisted Access (“eLAA”), Enhanced Mobile Broadband (“eMBB”), Evolved Node-B (“eNB”), Evolved Packet Core (“EPC”), Evolved Packet System (“EPS”), EPS Mobility Management (“EMM”, this is a NAS state in EPS), Evolved UMTS Terrestrial Radio Access (“E-UTRA”), Evolved UMTS Terrestrial Radio Access Network (“E-UTRAN”), European Telecommunications Standards Institute (“ETSI”), Frame Based Equipment (“FBE”), Frequency Division Duplex (“FDD”), Frequency Division Multiple Access (“FDMA”), Frequency Division Orthogonal Cover Code (“FD-OCC”), General Packet Radio Service (“GPRS”), Generic Public Service Identifier (“GPSI”), Guard Period (“GP”), Global System for Mobile Communications (“GSM”), Globally Unique Temporary UE Identifier (“GUTI”), Hybrid Automatic Repeat Request (“HARQ”), Home Subscriber Server (“HSS”), Home Public Land Mobile Network (“HPLMN”), Information Element (“IE”), Internet-of-Things (“IoT”), International Mobile Subscriber Identity (“IMSI”), Licensed Assisted Access (“LAA”), Load Based Equipment (“LBE”), Listen-Before-Talk (“LBT”), Long Term Evolution (“LTE”), Multiple Access (“MA”), Mobility Management (“MM”), Mobility Management Entity (“MME”), Modulation Coding Scheme (“MCS”), Machine Type Communication (“MTC”), Multiple Input Multiple Output (“MIMO”), Mobile Station International Subscriber Directory Number (“MSISDN”), Multi User Shared Access (“MUSA”), Narrowband (“NB”), Negative-Acknowledgment (“NACK”) or (“NAK”), New Generation (5G) Node-B (“gNB”), New Generation Radio Access Network (“NG-RAN”, a RAN used for 5GS networks), New Radio (“NR”, a 5G radio access technology; also referred to as “5G NR”), Non-Access Stratum (“NAS”), Network Exposure Function (“NEF”), Non-Orthogonal Multiple Access (“NOMA”), Network Slice Selection Assistance Information (“NSSAI”), Operation and Maintenance System (“OAM”), Orthogonal Frequency Division Multiplexing (“OFDM”), Packet Data Unit (“PDU”, used in connection with ‘PDU Session’), Packet Switched (“PS”, e.g., Packet Switched domain or Packet Switched service), Primary Cell (“PCell”), Physical Broadcast Channel (“PBCH”), Physical Downlink Control Channel (“PDCCH”), Physical Downlink Shared Channel (“PDSCH”), Pattern Division Multiple Access (“PDMA”), Physical Hybrid ARQ Indicator Channel (“PHICH”), Physical Random Access Channel (“PRACH”), Physical Resource Block (“PRB”), Physical Uplink Control Channel (“PUCCH”), Physical Uplink Shared Channel (“PUSCH”), Public Land Mobile Network (“PLMN”), Quality of Service (“QoS”), Quadrature Phase Shift Keying (“QPSK”), Radio Access Network (“RAN”), Radio Access Technology (“RAT”), Radio Resource Control (“RRC”), Random-Access Channel (“RACH”), Random Access Response (“RAR”), Radio Network Temporary Identifier (“RNTI”), Reference Signal (“RS”), Registration Area (“RA”, similar to tacking area list used in LTE/EPC), Registration Management (“RM”, refers to NAS layer procedures and states), Remaining Minimum System Information (“RMSI”), Resource Spread Multiple Access (“RSMA”), Round Trip Time (“RTT”), Receive (“RX”), Radio Link Control (“RLC”), Sparse Code Multiple Access (“SCMA”), Scheduling Request (“SR”), Single Carrier Frequency Division Multiple Access (“SC-FDMA”), Secondary Cell (“SCell”), Shared Channel (“SCH”), Session Management (“SM”), Session Management Function (“SMF”), Service Provider (“SP”), Signal-to-Interference-Plus-Noise Ratio (“SINR”), Single Network Slice Selection Assistance Information (“S-NSSAI”), Single Registration mode (“SR mode”), Sounding Reference Signal (“SRS”), System Information Block (“SIB”), Synchronization Signal (“SS”), Supplementary Uplink (“SUL”), Subscriber Identification Module (“SIM”), Tracking Area (“TA”), Transport Block (“TB”), Transport Block Size (“TB S”), Time-Division Duplex (“TDD”), Time Division Multiplex (“TDM”), Time Division Orthogonal Cover Code (“TD-OCC”), Transmission Time Interval (“TTI”), Transmit (“TX”), Unified Access Control (“UAC”), Unified Data Management (“UDM”), User Data Repository (“UDR”), Uplink Control Information (“UCI”), User Entity/Equipment (Mobile Terminal) (“UE”), UE Configuration Update (“UCU”), UE Route Selection Policy (“URSP”), Uplink (“UL”), User Plane (“UP”), Universal Mobile Telecommunications System (“UMTS”), UMTS Subscriber Identification Module (“USIM”), UMTS Terrestrial Radio Access (“UTRA”), UMTS Terrestrial Radio Access Network (“UTRAN”), Uplink Pilot Time Slot (“UpPTS”), Ultra-reliability and Low-latency Communications (“URLLC”), Visited Public Land Mobile Network (“VPLMN”), and Worldwide Interoperability for Microwave Access (“WiMAX”). As used herein, “HARQ-ACK” may represent collectively the Positive Acknowledge (“ACK”) and the Negative Acknowledge (“NACK”). ACK means that a TB is correctly received while NACK (or NAK) means a TB is erroneously received.

In 3GPP New Radio (“NR”) systems, Type-1 and Type-II codebook based channel state information (“CSI”) feedback have been adopted to support advanced MIMO transmission. Both types of codebooks are constructed from 2-D DFT based grid of beams and enable the CSI feedback of beam selection as well as PSK based co-phase combining between two polarizations. Type-1 codebooks are used for standard resolution CSI feedback, while Type-II (also referred to as “Type-II”) codebooks are used for high resolution CSI feedback. As a result, it is envisioned that more accurate CSI can be obtained from Type-II codebook based CSI feedback so that better precoded MIMO transmission can be employed by the network.

One Type-II precoding compression scheme was described based on transforming each beam's frequency-domain precoding vectors to the time domain and selecting a subset of the time-domain components which would then be fed back the gNB. The gNB would then perform the inverse transformation to the frequency domain to determine the set of 2L precoding vectors or beams. However, such feedback has a large overhead.

BRIEF SUMMARY

Disclosed are methods for Type-II codebook compression using phase modification of the beams and/or normalization of taps based on a largest tap of the main beam. Apparatuses and systems also perform the functions of the methods.

One method of a UE device for generating a CSI report includes receiving a set of reference signals transmitted from a base station and identifying a set of beams based on the set of reference signals. The method includes transforming the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a Discrete Fourier Transform (DFT)-compressed codebook, each amplitude coefficient vector and phase coefficient vector corresponding to an identified beam. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero. The method includes transmitting CSI feedback to the RAN node. Here, the CSI feedback includes an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam. Additionally, the CSI feedback does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam.

DETAILED DESCRIPTION

Generally, the present disclosure describes systems, methods, and apparatus for improved Type-II codebook compression using phase modification of the beams. In Type-II compression, many of these singular vectors are stacked together before a transformation is applied to it. Having a random phase results in failure of the transformation based compression methods. The singular vectors are typically not unique in the sense that any scaling of the singular vector by a unit magnitude complex number is also a singular vector with the same singular value. Thus, the phase of a singular vector is implementation dependent can be presumed to be random. In addition, when the phase ambiguity of the singular-value decomposition's singular vectors causes wasted overhead when coefficients of the singular vectors are reported such as with Type-II codebook compression.

Disclosed herein are techniques for providing a suitable phase assignment to the singular vectors, thereby improving transform-based Type-II codebook compression. Codebook compression improves transmission efficiency because fewer bits need to be sent over the air interface from transmitter (e.g., UE) to receiver (e.g., gNB or other RAN node). To improve DFT-based Type-II codebook compression, the transmitting device (e.g., a UE) identifies a set of beams based on the reference signal and identifies a main beam (e.g., strongest beam) using the absolute sum of the singular vector coefficients. In various embodiments, the transmitting device (e.g., UE) modifies beam phases accordingly, thereby enabling proper normalization for quantization of the taps.

One type of spatial compression scheme determines the set of 2L precoding vectors or beams or basis, where 2L<2Nt. The precoding vector at frequency sub-band k (0≤k<Nsb) is a linear combination of a subset of a predefined basis (i.e., DFT matrix) per sub-band which cover different spatial directions. Here, Nsb is the number of sub-bands. This technique uses spatial compression to reduce the number of bits reported to be proportional to 2L<2Nt.

If the beam selection matrix is denoted

W1=[B00B]
Then the resulting 2N1N2×Nsbprecoding matrix for a layer can then be expressed as
W=W1{tilde over (W)}2HVEquation (1)
where H means the Hermitian of a matrix, V is the size Nsb, DFT matrix and {tilde over (W)}2=[W2,1{tilde over (W)}2,2. . . {tilde over (W)}2,2L] is comprised of 2L time-domain coefficient vectors of length Nsb, and W2{tilde over (W)}2HV. W is a set of 2N1N2>1 dimensional precoding vectors (each row is a precoding vector), one each for each of Nsbsub-bands.

The precoder per layer may be expressed as

W⁡(k)=W1⁢W2⁡(k)=[B00B]×[v0,k…v2⁢l-1,k]Equation⁢⁢(2)
where the layer-common W1is 2Nt×2L, the per-layer W2(k) has size 2L×1 and the columns of the Nt×L matrix B=[b1b2. . . bL−1] are columns of a size-Nt standard two-dimensional DFT matrix.

Another Type-II precoding compression scheme transforms a subset of the beam's frequency-domain precoding vectors to the time domain and selects a subset of the time-domain components which would then be fed back the RAN node. The RAN node then performs the inverse transformation back to the frequency domain to determine the set of precoding vectors or beams. The subset of predefined precoding vectors cover different frequency sub-bands. Here, the UE reports: 1) L DFT special basis indices (where L<Nt), 2) M DFT frequency-domain basis indices (where M<Nsb), and 3) 2L×M number of linear combinatorial coefficients (i.e., complex coefficients having both amplitude and phase). This technique uses both spatial compression and frequency compression to reduce the number of bits reported as 2LM<2LNsb<2NtNsb.

The precoder per layer may be expressed as:

In Equation 3, B is the same over all layers. Here {tilde over (W)}2is reported by layer with size 2L×M and the columns of the Nsb×M matrix W3=[f0. . . fM−1] are columns of a size-Nsb standard DFT matrix, also reported per layer.

For {tilde over (W)}2, the element {tilde over (v)}l,mrepresents the quantized amplitude and phase of the coefficient. In certain embodiments, the single vector coefficients may be quantized using multi-stage quantization techniques described in US Provisional Patent Application No. 62/791,721. In other embodiments, traditional quantization techniques may be used.

First, compute W1given the channel matrix (Hsb) for each of the Nsbsub-bands.

Second, compute W2using the estimate of the channel matrix (Hsb) and W1. This step requires finding the singular vectors corresponding to the highest (e.g., largest) singular value of the equivalent channel matrices HsbW1for each sub-band. Each column of W2is the singular vector of one sub-band.

Second, {tilde over (W)}2, can be computed by taking the inverse Fourier transform of the rows of W2i.e.,
{tilde over (W)}2=VW2HEquation (4)

The elements of in {tilde over (W)}2are referred herein as “taps.” Feedback overhead may be reduced when the UE feeds back an indication of non-zero subset of the coefficients in {tilde over (W)}2, e.g., those coefficients with the largest magnitudes. The feedback overhead also depends on how many quantization bits are used to represent these coefficients.

As mentioned above, the singular vectors are not unique and random phases associated with the singular vectors may result in poor performance of the Type-II precoding compression scheme. Providing a proper phase to the singular vectors not only improves the compressibility of the stacked singular vectors but also improves the normalization precision of the quantizer.

FIG. 1depicts an embodiment of a wireless communication system100Type-II codebook compression, according to various embodiments of the disclosure. In one embodiment, the wireless communication system100includes remote units105, base units110, and communication links115. Even though a specific number of remote units105, base units110, and communication links115are depicted inFIG. 1, one of skill in the art will recognize that any number of remote units105, base units110, and communication links115may be included in the wireless communication system100.

In one implementation, the wireless communication system100is compliant with the NR system specified in the 3GPP specifications and/or the LTE system specified in 3GPP. More generally, however, the wireless communication system100may implement some other open or proprietary communication network, for example, WiMAX, among other networks. The present disclosure is not intended to be limited to the implementation of any particular wireless communication system architecture or protocol.

The base units110may be distributed over a geographic region. In certain embodiments, a base unit110may also be referred to as a RAN node, an access terminal, a base, a base station, a Node-B, an eNB, a gNB, a Home Node-B, a relay node, a femtocell, an access point, a device, or by any other terminology used in the art. The base units110are generally part of an access network120, such as a radio access network (“RAN”), that may include one or more controllers communicably coupled to one or more corresponding base units110. These and other elements of the access network120are not illustrated but are well known generally by those having ordinary skill in the art. The base units110connect to the mobile core network130via the access network120. The access network120and mobile core network130may be collectively referred to herein as a “mobile network” or “mobile communication network.”

The base units110may serve a number of remote units105within a serving area, for example, a cell or a cell sector via a wireless communication link. The base units110may communicate directly with one or more of the remote units105via communication signals. Generally, the base units110transmit downlink (“DL”) communication signals to serve the remote units105in the time, frequency, and/or spatial domain. Furthermore, the DL communication signals may be carried over the communication links115. The communication links115may be any suitable carrier in licensed or unlicensed radio spectrum. The communication links115facilitate communication between one or more of the remote units105and/or one or more of the base units110.

In one embodiment, the mobile core network130is a 5G core (“5GC”) or the evolved packet core (“EPC”), which may be coupled to other data network150, like the Internet and private data networks, among other data networks. Each mobile core network130belongs to a single public land mobile network (“PLMN”). The present disclosure is not intended to be limited to the implementation of any particular wireless communication system architecture or protocol. For example, other embodiments of the mobile core network130include an enhanced packet core (“EPC”) or a Multi-Service Core as described by the Broadband Forum (“BBF”).

The mobile core network130includes several network functions (“NFs”). As depicted, the mobile core network130includes an access and mobility management function (“AMF”)133, a session management function (“SMF”)135, and a user plane function (“UPF”)131. Although a specific number of AMFs133, SMFs135, and UPFs131are depicted inFIG. 1, one of skill in the art will recognize that any number and type of network function may be included in the mobile core network130.

The AMF133provides services such as UE registration, UE connection management, and UE mobility management. The SMF135manages the data sessions of the remote units105, such as a PDU session. The UPF131provides user plane (e.g., data) services to the remote units105. A data connection between the remote unit105and a data network150is managed by a UPF131. The UDM137provides user identification handling, access authorization, subscription management, etc.

To support spatial multiplexing and MU-MIMO, the remote unit105provides CSI feedback125to the base unit110using Type-II codebook compression using phase modification of the beams. The remote unit105generates a set of modified channel matrix (HsbW1), where (Hsb) is an estimate of channel matrices for a set of sub-bands and (W1) is the beam space matrix. The remote unit105also generates a set of singular vector coefficients (W2) from the modified channel matrix.

The remote unit105finds the main beam based on the sum of absolute value of singular vector coefficients and sets the phase of all singular vector coefficients based on the phase of the main beam singular vector coefficients, as described in greater detail below.

When computing the matrix W2, scaling each element of the singular vector with a unit magnitude complex scalar coefficient will keep the magnitude of the singular vector the same and it will still remain a singular vector with the same singular value. Because the phase of the singular vector is very much implementation dependent and because the singular vector is determined independently for all the sub-bands, depending upon the implementation, this phase can be presumed to be random from sub-band to sub-band. Observation shows that the Fourier-transform based quantization approach (described above) does not perform well when this phase is random.

To remedy, the phase of each column of W2may be changed as needed to provide a certain structure which helps in quantization later. Because W2is obtained from singular vectors, the elements of W2are referred to as “singular vector coefficients” of the modified channel.

In various embodiments, the remote unit105uses a transformation approach to matrix W2, such that the first tap of the main beam has the largest magnitude among all other taps and hence can be suitably used for normalization. Note that each beam populates a row of the matrix W2. First the remote unit105determines the main beam based on the absolute values of the singular vector coefficients. In various embodiments, the main beam is the particular beam having the strongest tap. One or more matrix transformation techniques may be used in order to force the largest magnitude coefficient of the main beam into the first column (i.e., remap the columns of W2), thus becoming the first tap of the main beam. Note that in other embodiments, the largest magnitude coefficient of the main beam is not forced into the first column, but the index pair (row and column) of the largest magnitude coefficient of the main beam is reported.

Additionally, the remote unit105transforms the matrix W2to zero-out the phase of the main beam. This enables normalization of all the taps with respect to the first tap of the main beam before quantization. Let m be the index of the main beam.

First, set the phase of all the Nsbterms of the m-th column of W2to zero. Let αijbe the amplitude, and ϕijbe the phase of ijth element of W2, i.e., the ijth element of W2is given by:
W2if=αijexp(√{square root over (−1)}ϕij)  Equation (5)

To zero out the phase of the main beam, the phases of all the beams are offset relative to the first tap (strongest tap) by subtracting the phase of the main beam from the original phases of that beam. This subtraction is performed over all sub-bands, i.e., the new phase values of W2are now given by
ϕ′ij=ϕij−ϕimEquation (6)

Now the ij-th element becomes
W2ij=αijexp(√{square root over (−1)}(ϕij−ϕim))=αijexp(√{square root over (−1)}ϕ′ij))  Equation (7)

For the main beam these elements are non-negative real numbers given by
W2im=αimEquation (8)

Note that in equation 8, the element W2imhas a phase of zero. Because all the Nsb elements corresponding to the main beam of W2has zero phase and {tilde over (W)}2=VW2, the ij-th taps are computed as:

and for the main beam the tap becomes

The zero-th tap of the main beam now becomes
{tilde over (W)}20m=Σk=1NsbαkmEquation (10)

Now if the main beam index m is selected using the magnitude sum of the elements of the stacked singular vectors such that

m=arg⁢⁢maxj⁢(∑i=1Nsb⁢αij)Equation⁢⁢(11)
then the first-tap which is equal to Σi=1Nsbαimbecomes the largest over all possible taps over all the beams. Note that even for the main beam all other taps have smaller magnitude compared with the first tap. This can be easily proven by treating the inverse Fourier transform as a summation of Nsb2-dimensional vectors. The vector summation is maximum if and only if all vectors have the same direction.

Very often the taps may be computed using an oversampling. The tap value at an oversampled location i′ (i′ not an integer) are obtained as

It can also be shown that choosing the main beam using Equation 12 and zeroing out its phase ensures also ensures that first-tap of the main beam is the strongest tap. Next normalization is performed using the first-tap of the main beam, i.e.,

Such transformation forces the magnitude of the first tap of the main beam to unity

(e.g.,w~20⁢⁢mw~20⁢⁢m=1).
Thus, there is no need to explicitly quantize the first tap of the main beam because the value of this tap can be directly inferred to be 1 and its phase can be inferred as zero. Release 16 Type II CSI specifies reporting of the strongest taps of each beam and such reporting generally consist of an amplitude and a phase. Because the first tap, which will always be included due to its maximum amplitude condition, can be inferred to be 1, it need not be reported, thereby saving precious uplink control signaling overhead.

In various embodiments, only the index of the main beam (i.e., the beam containing the strongest coefficient) is reported to the RAN node (e.g., gNB). Thus, the CSI feedback sent to the RAN node does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam, but includes indications of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to the identified beams.

Furthermore, going back to Equation 9a, it can be easily seen the i-th tap of the main beam is complex conjugate of the Nsb−i tap, i.e.,
{tilde over (W)}2im={tilde over (W)}2(Nsb−i)m*  Equation (14)
where * is a complex conjugate operation. Equation 14 enables the transmitter (UE) to quantize and transmit only one half of the main beam taps, because the second half of the taps can be obtained at the receiver/decoder (gNB) using this symmetric property. Similarly, if only a subset of taps are reported on either a common or independent basis (same or different set of taps across beams respectively), the number of possibilities for the combinations of taps is reduced because approximately half the taps are pairs, which means the number of possibilities is approximately cut in half. This also reduces the uplink signaling overhead. However, such a reporting advantage can be taken only in case when tap reporting is independent over all the beams. In the case of common basis reporting, the reporting has to be over an entire range to taps. However, the decoder (gNB) can improve the precoding vector by generating extra taps for the main beam if the reported taps do not follow symmetricity, i.e., i-th tap is reported but Nsb−i is not reported by UE to gNB.

In some embodiments, an upsampling factor is to be reported for all the beams by choosing a fractional part which results in maximum tap value for that beam, then for the main beam the fractional component will always be zero so again there is no need to report the fractional part for the main beam.

Beneficially, normalization with the first tap of the main beam generates good range for quantization of other taps. Additionally, such normalization always results in the first tap of the main beam being ‘1’, so there is no need to report this value. Further, there is no need to specific one of the one of the strongest tap, it will always be the first tap of the main beam and the oversampling factor for the main beam will always be ‘0’. As noted above, using zero phase for the main beam, results in the coefficients before inverse Fourier transform being real and hence the column of {tilde over (W)}2corresponding to the main beam will be symmetric and the quantization method can advantageously use this property to report only half of the main beam taps.

FIG. 2depicts a first procedure200for Type-II codebook compression using phase modification of the beams, according to embodiments of the disclosure. The procedure200may be performed by a UE, such as the remote unit105. The procedure200begins as the UE computes205the beam selection matrix (W1) and generates210the modified channel matrix (HsbW1), as described above. Additionally, the UE generates215a set of singular vector coefficients (i.e., matrix W2) from the modified channel matrix and defines220a particular beam (i.e., main beam) based on the singular vector coefficients. In various embodiments, the particular beam is selected based on based on the sum of absolute value of singular vector coefficients.

The UE modifies225the phase of all singular vector coefficients based on the phase of the main beam singular vector coefficients. As discussed above, phase modification solves the issue of random phases causing poor performance of the Discrete Fourier Transformation-based Type-II codebook compression. The UE computes230the pre-coding matrix using the modified singular vector coefficients and transmits235CSI feedback to the decoder (e.g., gNB).

FIG. 3depicts a second procedure300for Type-II codebook compression using phase modification of the beams, according to embodiments of the disclosure. The procedure300may be performed by a UE, such as the remote unit105. The procedure300begins as UE generates305a set of singular vector coefficients (W2) from the modified channel matrix (HsbW1), as described above. The UE generates310the matrix ({tilde over (W)}2) by performing an inverse Fourier transform of W2, e.g., to generate the taps. Further, the UE normalizes315the taps by dividing by the first tap of the main beam and quantizes320the taps using appropriate bits. In certain embodiments, quantizing the taps includes quantizing only half of the taps, wherein the decoder uses the symmetric property to generate the other taps. The UE further transmits325CSI feedback (e.g., pre-coding matrix) to the decoder (e.g., gNB).

FIG. 4depicts a user equipment apparatus400that may be used for Type-II codebook compression using phase modification of the beams, according to embodiments of the disclosure. The UE. In various embodiments, the user equipment apparatus400is used to implement one or more of the solutions described above. The user equipment apparatus400may be one embodiment of the remote unit105, described above. Furthermore, the user equipment apparatus400may include a processor405, a memory410, an input device415, an output device420, and a transceiver425. In some embodiments, the input device415and the output device420are combined into a single device, such as a touchscreen. In certain embodiments, the user equipment apparatus400may not include any input device415and/or output device420. In various embodiments, the user equipment apparatus400may include one or more of: the processor405, the memory410, and the transceiver425, and may not include the input device415and/or the output device420.

The processor405, in one embodiment, may include any known controller capable of executing computer-readable instructions and/or capable of performing logical operations. For example, the processor405may be a microcontroller, a microprocessor, a central processing unit (“CPU”), a graphics processing unit (“GPU”), an auxiliary processing unit, a field programmable gate array (“FPGA”), or similar programmable controller. In some embodiments, the processor405executes instructions stored in the memory410to perform the methods and routines described herein. The processor405is communicatively coupled to the memory410, the input device415, the output device420, and the transceiver425.

In various embodiments, the transceiver425receives a set of reference signals and the processor405identifies a set of beams based on the set of reference signals. The processor405transforms the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a Discrete Fourier Transform (DFT)-compressed codebook, each amplitude coefficient vector and phase coefficient vector corresponding to an identified beam. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero.

In some embodiments, the first element of the amplitude coefficient vector corresponding to the particular beam is the greater than or equal to each of the elements of the amplitude coefficient vectors corresponding to all identified beams.

In some embodiments, transforming the set of reference signals includes the processor405performing a Fourier-based transformation comprising at least one of: a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain vectors of amplitude and phase coefficients of a DFT-compressed codebook may include the processor405performing a phase offset operation prior to the Fourier-based transformation, the phase offset operation based on the phase of the particular beam. In certain embodiments, the processor405identifies the particular beam based on a summation of the magnitude values of elements of input vectors. Note here that the input vectors are input to the Fourier-based transformation, wherein each input vector corresponds to an identified beam.

In some embodiments, transforming the set of reference signals includes the processor405normalizing amplitude coefficient vectors of the identified set of beams based on the first element of the amplitude coefficient vector of the particular beam. In some embodiments, transforming the set of reference signals includes the processor405subtracting the first element of the phase coefficient vector of the particular beam from the phases of the identified set of beams. In some embodiments, transforming the set of reference signals includes the processor405quantizing the amplitude and phase coefficients of the identified set of beams.

Via the transceiver425, the processor405transmits CSI feedback to the base station, wherein the CSI feedback comprises an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, wherein the CSI feedback does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam.

In some embodiments, the processor405reports an index corresponding to the particular beam. For example, the CSI feedback may include an indication of the beam index of the particular beam. In such embodiments, the reported index may be identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

The memory410, in one embodiment, is a computer readable storage medium. In some embodiments, the memory410includes volatile computer storage media. For example, the memory410may include a RAM, including dynamic RAM (“DRAM”), synchronous dynamic RAM (“SDRAM”), and/or static RAM (“SRAM”). In some embodiments, the memory410includes non-volatile computer storage media. For example, the memory410may include a hard disk drive, a flash memory, or any other suitable non-volatile computer storage device. In some embodiments, the memory410includes both volatile and non-volatile computer storage media.

In some embodiments, the memory410stores data related to Type-II codebook compression using phase modification of the beams. In certain embodiments, the memory410also stores program code and related data, such as an operating system or other controller algorithms operating on the remote unit105.

The input device415, in one embodiment, may include any known computer input device including a touch panel, a button, a keyboard, a stylus, a microphone, or the like. In some embodiments, the input device415may be integrated with the output device420, for example, as a touchscreen or similar touch-sensitive display. In some embodiments, the input device415includes a touchscreen such that text may be input using a virtual keyboard displayed on the touchscreen and/or by handwriting on the touchscreen. In some embodiments, the input device415includes two or more different devices, such as a keyboard and a touch panel.

In certain embodiments, the output device420includes one or more speakers for producing sound. For example, the output device420may produce an audible alert or notification (e.g., a beep or chime). In some embodiments, the output device420includes one or more haptic devices for producing vibrations, motion, or other haptic feedback. In some embodiments, all or portions of the output device420may be integrated with the input device415. For example, the input device415and output device420may form a touchscreen or similar touch-sensitive display. In other embodiments, the output device420may be located near the input device415.

In various embodiments, the transceiver425communicates with one or more network functions of a mobile communication network via one or more access networks. The transceiver425operates under the control of the processor405to transmit messages, data, and other signals and also to receive messages, data, and other signals. For example, the processor405may selectively activate the transceiver (or portions thereof) at particular times in order to send and receive messages.

The transceiver425may include one or more transmitters430and one or more receivers435. Although only one transmitter430and one receiver435are illustrated, the user equipment apparatus400may have any suitable number of transmitters430and receivers435. Further, the transmitter(s)430and the receiver(s)435may be any suitable type of transmitters and receivers. In one embodiment, the transceiver425includes a first transmitter/receiver pair used to communicate with a mobile communication network over licensed radio spectrum and a second transmitter/receiver pair used to communicate with a mobile communication network over unlicensed radio spectrum.

In certain embodiments, the first transmitter/receiver pair used to communicate with a mobile communication network over licensed radio spectrum and the second transmitter/receiver pair used to communicate with a mobile communication network over unlicensed radio spectrum may be combined into a single transceiver unit, for example a single chip performing functions for use with both licensed and unlicensed radio spectrum. In some embodiments, the first transmitter/receiver pair and the second transmitter/receiver pair may share one or more hardware components. For example, certain transceivers425, transmitters430, and receivers435may be implemented as physically separate components that access a shared hardware resource and/or software resource, such as for example, the network interface440.

In various embodiments, one or more transmitters430and/or one or more receivers435may be implemented and/or integrated into a single hardware component, such as a multi-transceiver chip, a system-on-a-chip, an ASIC, or other type of hardware component. In certain embodiments, one or more transmitters430and/or one or more receivers435may be implemented and/or integrated into a multi-chip module. In some embodiments, other components such as the network interface440or other hardware components/circuits may be integrated with any number of transmitters430and/or receivers435into a single chip. In such embodiment, the transmitters430and receivers435may be logically configured as a transceiver425that uses one more common control signals or as modular transmitters430and receivers435implemented in the same hardware chip or in a multi-chip module.

FIG. 5depicts one embodiment of a method500for generating a CSI report, according to embodiments of the disclosure. In various embodiments, the method500is performed by the remote unit105and/or the user equipment apparatus400, described above. In some embodiments, the method500is performed by a processor, such as a microcontroller, a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processing unit, a FPGA, or the like.

The method500begins and receives505a set of reference signals transmitted from a RAN node. The method500includes identifying510a set of beams based on the set of reference signals.

The method500includes transforming515the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a Discrete Fourier Transform (DFT)-compressed codebook, each amplitude coefficient vector and phase coefficient vector corresponding to an identified beam. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero.

In some embodiments, transforming515the set of reference signals includes performing a Fourier-based transformation comprising at least one of: a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain vectors of amplitude and phase coefficients of a DFT-compressed codebook may include a phase offset operation prior to the Fourier-based transformation, the phase offset operation based on the phase of the particular beam. In various embodiments, the particular beam is identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

In some embodiments, transforming515the set of reference signals includes normalizing amplitude coefficient vectors of the identified set of beams based on the first element of the amplitude coefficient vector of the particular beam. In some embodiments, transforming515the set of reference signals includes subtracting the first element of the phase coefficient vector of the particular beam from the phases of the identified set of beams. In some embodiments, transforming515the set of reference signals includes quantizing the amplitude and phase coefficients of the identified set of beams. In various embodiments, the first element of the amplitude coefficient vector corresponding to the particular beam is greater than or equal to each of the elements of the amplitude coefficient vectors corresponding to all identified beams.

The method500includes transmitting520CSI feedback to the RAN node. Here, the CSI feedback includes an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam. Additionally, the CSI feedback does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam. The method500ends.

In some embodiments, transmitting520CSI feedback to the RAN node includes reporting an index corresponding to the particular beam. In one embodiment, the reported index is identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

Disclosed herein is a first apparatus for generating a CSI report, according to embodiments of the disclosure. The first apparatus may be implemented by a UE device using Discrete Fourier Transformation-based Type-II codebook compression, such as the remote unit105and/or the user equipment apparatus400. The first apparatus includes a transceiver that receives a set of reference signals transmitted from a base station and a processor that identifies a set of beams based on the set of reference signals. The processor transforms the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a Discrete Fourier Transform (DFT)-compressed codebook, each amplitude coefficient vector and phase coefficient vector corresponding to an identified beam. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero. Via the transceiver, the processor transmits CSI feedback to the base station, wherein the CSI feedback comprises an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, wherein the CSI feedback does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam.

In some embodiments, the first element of the amplitude coefficient vector corresponding to the particular beam is the greater than or equal to each of the elements of the amplitude coefficient vectors corresponding to all identified beams.

In some embodiments, transforming the set of reference signals includes performing a Fourier-based transformation comprising at least one of: a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain vectors of amplitude and phase coefficients of a DFT-compressed codebook may include a phase offset operation prior to the Fourier-based transformation, the phase offset operation based on the phase of the particular beam. In certain embodiments, the particular beam is identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

In some embodiments, the processor reports an index corresponding to the particular beam. For example, the CSI feedback may include an indication of the beam index of the particular beam. In such embodiments, the reported index may be identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

In some embodiments, transforming the set of reference signals includes normalizing amplitude coefficient vectors of the identified set of beams based on the first element of the amplitude coefficient vector of the particular beam. In some embodiments, transforming the set of reference signals includes subtracting the first element of the phase coefficient vector of the particular beam from the phases of the identified set of beams. In some embodiments, transforming the set of reference signals includes quantizing the amplitude and phase coefficients of the identified set of beams.

Disclosed herein is a first method for generating a CSI report, according to embodiments of the disclosure. The first method may be performed by a UE device for Type-II codebook compression using a Discrete Fourier Transformation-based Type-II codebook compression, such as the remote unit105and/or the user equipment apparatus800. The first method includes receiving a set of reference signals transmitted from a base station and identifying a set of beams based on the set of reference signals. The first method includes transforming the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients of a Discrete Fourier Transform (DFT)-compressed codebook, each amplitude coefficient vector and phase coefficient vector corresponding to an identified beam. Here, the first element of the amplitude coefficient vector corresponding to one particular beam is unity and the first element of the phase coefficient vector corresponding to the particular beam is zero. The method includes transmitting CSI feedback to the RAN node. Here, the CSI feedback includes an indication of one or more elements of the vectors of amplitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam. Additionally, the CSI feedback does not include the first element of the amplitude coefficient vector and the first element of the phase coefficient vector corresponding to the particular beam.

In some embodiments, the first element of the amplitude coefficient vector corresponding to the particular beam is greater than or equal to each of the elements of the amplitude coefficient vectors corresponding to all identified beams.

In some embodiments, transforming the set of reference signals includes performing a Fourier-based transformation comprising at least one of: a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain vectors of amplitude and phase coefficients of a DFT-compressed codebook may include performing a phase offset operation prior to the Fourier-based transformation, the phase offset operation based on the phase of the particular beam. In certain embodiments, the particular beam is identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

In some embodiments, the first method includes reporting an index corresponding to the particular beam. In certain embodiments, the reported index is identified based on a summation of the magnitude values of elements of input vectors, wherein the input vectors are input to the Fourier-based transformation, and wherein each input vector corresponds to an identified beam.

In some embodiments, transforming the set of reference signals includes normalizing amplitude coefficient vectors of the identified set of beams based on the first element of the amplitude coefficient vector of the particular beam. In some embodiments, transforming the set of reference signals includes subtracting the first element of the phase coefficient vector of the particular beam from the phases of the identified set of beams. In some embodiments, transforming the set of reference signals includes quantizing the amplitude and phase coefficients of the identified set of beams.