阅读说明：本技术 生成信道状态信息(“csi”)报告 (Generating channel state information ('CSI') reports ) 是由 艾哈迈德·欣迪 泰勒·布朗 乌达·米塔尔 于 2020-01-13 设计创作，主要内容包括：公开了用于生成CSI报告的装置、方法和系统。一种装置400包括接收505从基站发送的一组参考信号的收发器425和变换515该组参考信号以获得DFT压缩码本的幅度和相位系数的每层向量的处理器405。这里,对应于一个特定波束的幅度系数向量的第一元素是一,并且对应于特定波束的相位系数向量的第一元素是零。装置400发送520CSI反馈,其包括对应于至少一个识别的波束的幅度系数向量和相位系数向量的向量的一个或多个元素的指示,并且不包括对应于特定波束的幅度系数向量的第一元素和相位系数向量的第一元素。(Apparatuses, methods, and systems for generating CSI reports are disclosed. An apparatus 400 includes a transceiver 425 that receives 505 a set of reference signals transmitted from a base station and a processor 405 that transforms 515 the set of reference signals to obtain per-layer vectors of amplitude and phase coefficients for a DFT compressed codebook. Here, the first element of the magnitude coefficient vector corresponding to a particular beam is one and the first element of the phase coefficient vector corresponding to a particular beam is zero. The apparatus 400 transmits 520CSI feedback comprising an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam and excluding a first element of a magnitude coefficient vector and a first element of a phase coefficient vector corresponding to a particular beam.)

1. A method of generating a channel state information ("CSI") report in a user equipment, the method comprising:

receiving a set of reference signals transmitted from a base station;

identifying a set of beams based on the set of reference signals;

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,

wherein the first element of the magnitude coefficient vector corresponding to a particular beam is one, and

wherein a first element of a phase coefficient vector corresponding to the particular beam is zero; and

transmitting CSI feedback to the base station, wherein the CSI feedback includes an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, wherein the CSI feedback does not include a first element of a magnitude coefficient vector and a first element of a phase coefficient vector corresponding to the particular beam.

2. The method of claim 1, wherein a first element of a magnitude coefficient vector corresponding to the particular beam is greater than or equal to each element of a magnitude coefficient vector corresponding to all identified beams.

3. The method of claim 1, wherein transforming the set of reference signals comprises performing a fourier-based transform comprising at least one of: DFT and inverse DFT.

4. The method of claim 3, wherein transforming the set of reference signals to obtain a vector of amplitude and phase coefficients of a DFT compressed codebook comprises a phase shifting operation prior to the Fourier-based transformation, the phase shifting operation based on a phase of the particular beam.

5. The method of claim 3, further comprising reporting an index corresponding to the particular beam.

6. The method of claim 5, wherein the reported index is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to the Fourier-based transform, and wherein each input vector corresponds to an identified beam.

7. The method of claim 3, wherein the particular beam is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to the Fourier-based transform, and wherein each input vector corresponds to an identified beam.

8. The method of claim 1, wherein transforming the set of reference signals comprises normalizing a magnitude coefficient vector for the identified set of beams based on a first element of the magnitude coefficient vector for the particular beam.

9. The method of claim 1, wherein transforming the set of reference signals comprises subtracting a first element of a phase coefficient vector of the particular beam from a phase of the identified set of beams.

10. The method of claim 1, wherein transforming the set of reference signals comprises quantizing amplitude and phase coefficients of the identified set of beams.

11. A user equipment ("UE") apparatus for generating a channel state information ("CSI") report, the apparatus comprising:

a transceiver that receives a set of reference signals transmitted from a base station; and

a processor:

identifying a set of beams based on the set of reference signals;

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,

wherein the first element of the magnitude coefficient vector corresponding to a particular beam is one, and

wherein a first element of a phase coefficient vector corresponding to the particular beam is zero; and

transmitting CSI feedback to the base station, wherein the CSI feedback includes an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, wherein the CSI feedback does not include a first element of a magnitude coefficient vector and a first element of a phase coefficient vector corresponding to the particular beam.

12. The apparatus of claim 11, wherein a first element of a magnitude coefficient vector corresponding to the particular beam is greater than or equal to each element of magnitude coefficient vectors corresponding to all identified beams.

13. The apparatus of claim 11, wherein transforming the set of reference signals comprises performing a fourier-based transform comprising at least one of: DFT and inverse DFT.

14. The apparatus of claim 13, wherein transforming the set of reference signals to obtain a vector of amplitude and phase coefficients of a DFT compressed codebook comprises a phase shifting operation prior to the fourier based transformation, the phase shifting operation based on a phase of the particular beam.

15. The apparatus of claim 13, wherein the processor reports an index corresponding to the particular beam.

16. The apparatus of claim 15, wherein the reported index is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to the fourier-based transform, and wherein each input vector corresponds to an identified beam.

17. The apparatus of claim 13, wherein the particular beam is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to the fourier-based transform, and wherein each input vector corresponds to an identified beam.

18. The device of claim 11, wherein transforming the set of reference signals comprises normalizing a magnitude coefficient vector for the identified set of beams based on a first element of the magnitude coefficient vector for the particular beam.

19. The device of claim 11, wherein transforming the set of reference signals comprises subtracting a first element of a phase coefficient vector of the particular beam from a phase of the identified set of beams.

20. The device of claim 11, wherein transforming the set of reference signals comprises quantizing amplitude and phase coefficients of the identified set of beams.

Technical Field

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

Background

The following abbreviations are hereby defined, at least some of which are referred to in the following description: third generation partnership project ("3 GPP"), fifth generation core network ("5 CG"), fifth generation system ("5 GS"), authentication, authorization and accounting ("AAA"), access and mobility management function ("AMF"), access restricted local operator service ("ARLOS"), positive acknowledgement ("ACK"), application programming interface ("API"), authentication center ("AuC"), access stratum ("AS"), autonomous uplink ("AUL"), AUL downlink feedback information ("AUL-DFI"), base station ("BS"), binary phase shift keying ("BPSK"), bandwidth part ("BWP"), clear channel assessment ("CCA"), control element ("CE"), cyclic prefix ("CP"), cyclic redundancy check ("CRC"), channel state information ("CSI"), common search space ("CSS"), and the like, Connected mode ("CM", which is NAS state in 5 GS), core network ("CN"), control plane ("CP"), data radio bearer ("DRB"), discrete Fourier transform extension ("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", which is NAS state in EPS), evolved UMTS terrestrial radio Access ("E-UTRA"), evolved UMTS terrestrial radio Access network ("E-UTRAN"), (NAS state in 5 GS), European telecommunications standards institute ("ETSI"), frame-based devices ("FBE"), frequency division duplex ("FDD"), frequency division multiple access ("FDMA"), frequency division orthogonal cover code ("FD-OCC"), general packet radio service ("GPRS"), general 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 devices ("LBE"), listen-before-talk ("LBT"), long term evolution ("LTE"), multiple access ("MA"),(s), Mobility management ("MM"), mobility management entity ("MME"), modulation and coding scheme ("MCS"), machine type communication ("MTC"), multiple-input multiple-output ("MIMO"), mobile station international subscriber directory number ("MSISDN"), multiple user shared access ("MUSA"), narrowband ("NB"), negative acknowledgement ("NACK") or ("NAK"), new generation (5G) node-B ("gNB"), new generation radio access network ("NG-RAN", RAN for 5GS networks), new radio ("NR", 5G radio access technology; also known 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"),(s), Packet data units ("PDUs," used in conjunction with a "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"), mode 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"), and, Random access channel ("RACH"), random access response ("RAR"), radio network temporary identifier ("RNTI"), reference signal ("RS"), registration area ("RA", similar to tracking area lists used in LTE/EPC), registration management ("RM", meaning NAS layer procedures and states), remaining minimum system information ("RMSI"), resource extended multiple access ("RSMA"), round trip time ("RTT"), reception ("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"), "LTE-based, Single network slice selection assistance information ("S-NSSAI"), single registration mode ("SR mode"), sounding reference signal ("SRs"), system information block ("SIB"), synchronization signal ("SS"), supplemental uplink ("SUL"), subscriber identity module ("SIM"), tracking area ("TA"), transport block ("TB"), transport block size ("TBs"), time division duplex ("TDD"), time division multiplexing ("TDM"), time division orthogonal cover code ("TD-OCC"), transmission time interval ("TTI"), transmission ("TX"), unified access control ("UAC"), unified data management ("UDM"), user data repository ("UDR"), uplink control information ("UCI"), user entity/device (mobile terminal) ("UE"), UE configuration update ("UCU"), "UE" or "UE" S "or" S "or" S "or" S or "S" or "S or" S or "or, UE routing policies ("URSP"), uplink ("UL"), user plane ("UP"), universal mobile telecommunications system ("UMTS"), UMTS subscriber identity module ("USIM"), UMTS terrestrial radio access ("UTRA"), UMTS terrestrial radio access network ("UTRAN"), uplink pilot time slot ("UpPTS"), ultra-high 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 refer to both positive acknowledgement ("ACK") and negative acknowledgement ("NACK"). ACK means that the TB is correctly received, and NACK (or NAK) means that the TB is incorrectly received.

In 3GPP new radio ("NR") systems, channel state information ("CSI") feedback based on type 1 and type II codebooks has been employed to support advanced MIMO transmissions. Both types of codebooks are constructed from a 2-D DFT based beam grid and support CSI feedback for beam selection and PSK-based in-phase combining between the 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. Thus, it is contemplated that more accurate CSI may be obtained from type II codebook based CSI feedback so that the network may employ better precoded MIMO transmissions.

A type II precoding compression scheme is described based on converting the frequency domain precoding vector for each beam to the time domain and selecting a subset of the time domain components, which are then fed back to the gNB. The gNB will then perform an inverse transform to the frequency domain to determine a set of 2L precoding vectors or beams. However, such feedback has a large overhead.

Disclosure of Invention

Methods for type II codebook compression using phase modification of beams and/or tap normalization based on the largest tap of the main beam are disclosed. The apparatus and system also perform the functions of the method.

One method for a UE device to generate 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 magnitude coefficient vector corresponding to one specific beam is one (unity), and the first element of the phase coefficient vector corresponding to the specific beam is zero. The method includes sending CSI feedback to the RAN node. Here, the CSI feedback comprises an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to the at least one identified beam. In addition, the CSI feedback does not include a first element of the magnitude coefficient vector and a first element of the phase coefficient vector corresponding to the particular beam.

Drawings

A more particular description of the embodiments briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. Understanding that these drawings depict only some embodiments and are not therefore to be considered to be limiting of scope, the embodiments will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

FIG. 1 is a schematic block diagram illustrating one embodiment of a wireless communication system for type II codebook compression using beam phase modification;

FIG. 2 is a diagram illustrating one embodiment of a process for type II codebook compression using phase modification of beams;

FIG. 3 is a diagram illustrating another embodiment of a process for type II codebook compression using tap normalization; and

FIG. 4 is a schematic block diagram illustrating one embodiment of a user equipment device for generating CSI reports; and

fig. 5 is a flow diagram illustrating one embodiment of a method for generating CSI reports.

Detailed Description

As will be appreciated by one skilled in the art, aspects of the embodiments may be embodied as a system, apparatus, method or program product. Accordingly, embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects.

For example, the disclosed embodiments may be implemented as hardware circuits comprising custom very large scale integration ("VLSI") circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. The disclosed embodiments may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like. As another example, the disclosed embodiments may include one or more physical or logical blocks of executable code, which may, for instance, be organized as an object, procedure, or function.

Furthermore, embodiments may take the form of a program product contained in one or more computer-readable storage devices storing machine-readable code, computer-readable code, and/or program code, hereinafter referred to as code. The storage device may be tangible, non-transitory, and/or non-transmissive. The memory device may not contain a signal. In a certain embodiment, the storage device uses only signals for accessing the code.

Any combination of one or more computer-readable media may be utilized. The computer readable medium may be a computer readable storage medium. The computer readable storage medium may be a storage device storing the code. A storage device may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing.

More specific examples (a non-exhaustive list) of the storage device would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory ("RAM"), a read-only memory ("ROM"), an erasable programmable read-only memory ("EPROM" or flash memory), a portable compact disc read-only memory ("CD-ROM"), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The code for performing the operations of an embodiment may be in any number of lines and may be written in any combination of one or more programming languages, including an object oriented programming language such as Python, Ruby, Java, Smalltalk, C + + or conventional procedural programming languages, such as the "C" programming language, and/or a machine language such as assembly language. The code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network ("LAN") or a wide area network ("WAN"), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

Reference throughout this specification to "one embodiment," "an embodiment," or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, appearances of the phrases "in one embodiment," "in an embodiment," and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise. The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" also mean "one or more", unless expressly specified otherwise.

As used herein, a list with the conjunction "and/or" includes any single item in the list or combination of items in the list. For example, the list of A, B and/or C includes only a, only B, only C, A in combination with B, B in combination with C, a in combination with C, or A, B and C in combination. As used herein, a list using the term "one or more" includes any single item in the list or combination of items in the list. For example, one or more of A, B and C includes a combination of only a, only B, only C, A and B, B and C, a and C, or A, B and C. As used herein, a list using the term "one of" includes one and only one of any single item in the list. For example, "one of A, B and C" includes only a, only B, or only C and does not include the combination of A, B and C. As used herein, "a member selected from the group consisting of A, B and C" includes one and only one of A, B or C, excluding the combination of A, B and C. As used herein, "a member selected from the group consisting of A, B and C, and combinations thereof" includes a alone, B alone, C, A and B alone, B and C alone, a and C alone, or A, B and C alone.

Furthermore, the described features, structures, or characteristics of the embodiments may be combined in any suitable manner. In the following description, numerous specific details are provided, such as examples of programming, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a thorough understanding of embodiments. One skilled in the relevant art will recognize, however, that an embodiment may be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the embodiments.

Aspects of the embodiments are described below with reference to schematic flow charts and/or schematic block diagrams of methods, apparatuses, systems, and program products according to the embodiments. It will be understood that each block of the flowchart illustrations and/or schematic block diagrams, and combinations of blocks in the flowchart illustrations and/or schematic block diagrams, can be implemented by code. The code may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The code may also be stored in a storage device that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the storage device produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The code may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the code which executes on the computer or other programmable apparatus provides processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and/or block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, systems, methods and program products according to various embodiments. In this regard, each block in the flowchart and/or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s).

It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more blocks, or portions thereof, of the illustrated figures.

Although various arrow types and line types may be employed in the flow chart diagrams and/or block diagram block diagrams, they are understood not to limit the scope of the corresponding embodiments. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the depicted embodiment. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted embodiment. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and code.

The description of the elements in each figure may refer to elements of previous figures. Like numbers refer to like elements throughout, including alternative embodiments of the same elements.

In general, this disclosure describes systems, methods, and apparatuses for improving type II codebook compression using phase modification of beams. In type II compression, many singular vectors are stacked together before applying the transform to them. Having random phases can cause transform-based compression methods to fail. The singular vectors are generally not unique in the sense that any scaling of the singular vectors by unit magnitude complex numbers is also a singular vector having the same singular values. Thus, the phase dependence of the singular vectors can be assumed to be random depending on the implementation. Furthermore, when the phase ambiguity of the singular vectors of the singular value decomposition results in a cost waste, when for example the coefficients of the riding vector are reported compressed using a type II codebook.

Disclosed herein are techniques for providing appropriate phase assignments to 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 the transmitter (e.g., UE) to the receiver (e.g., gNB or other RAN node). To improve DFT-based type II codebook compression, a transmitting device (e.g., a UE) identifies a set of beams based on a reference signal and identifies the primary beam (e.g., the strongest beam) using the absolute sum of singular vector coefficients. In various embodiments, the transmitting device (e.g., UE) modifies the beam phases accordingly, thereby enabling proper normalization of the tap quantization.

One type of spatial compression scheme determines a set of 2L precoding vectors or beams or basis, where 2L < 2 Nt. The precoding vector at frequency subband k (0 ≦ k < Nsb) is a linear combination of a predefined base (i.e., DFT matrix) subset of each subband covering different spatial directions. Here, Nsb is the number of subbands. The technique uses spatial compression to reduce the number of bits in proportion to 2L < 2 Nt.

If the beam selection matrix is represented as

2N of the resulting layer₁N₂×N_sbThe precoding matrix can be expressed as

Where H denotes the Hermitian of the matrix and V is the size N of the DFT matrix_sb，

From length N_sbAnd 2L time-domain coefficient vectors, andw is a group of 2N₁N₂X 1-dimensional precoding vectors (each row is a precoding vector), one for each of N_sbEach of the sub-bands.

The precoder of each layer may be represented as

Wherein the middle layer is common to W₁Is 2Nt × 2L, each layer W₂(k) Is 2 lx 1, Nt × L matrix column B ═ B₁ b₂ … b_L-1]Is a column of a standard two-dimensional DFT matrix of size Nt.

Another type II precoding compression scheme converts a subset of the frequency domain precoding vectors of the beams to the time domain and selects a subset of the time domain components, which are then fed back to the RAN node. The RAN node then performs an inverse transform back to the frequency domain to determine a set of precoding vectors or beams. The subset of predefined precoding vectors covers different frequency subbands. Here, the UE reports: 1) l DFT special base indices (where L < Nt), 2) M DFT frequency domain base indices (where M < Nsb), and 3)2L × M linear combination coefficients (i.e., complex coefficients with amplitude and phase). The technique uses spatial compression and frequency compression to reduce the number of bits reported as 2LM < 2LNsb < 2 NtNsb.

The precoder for each layer may be represented as:

in equation 3, B is the same in all layers. Here, thePer layer reporting, size 2 LxM, Nsb xM matrix W₃＝[f₀ … f_M-1]Is a column of a standard DFT matrix of size Nsb, also reported per layer.

For theThe element isRepresenting the quantized amplitude and phase of the coefficients. In some embodiments, the single vector coefficients may be quantized using the multi-level quantization technique described in U.S. provisional patent application No. 62/791,721. In other embodiments, conventional quantization techniques may be used.

First, for each N_sbThe subband computation gives the channel matrix (H)_sb) W of (2)₁。

Second, a channel matrix (H) is used_sb) And W₁Is calculated by estimating₂. This step requires finding the equivalent channel matrix H corresponding to each subband_sbW₁The singular vector of the highest (e.g., largest) singular value of (a). W₂Each column of (a) is a singular vector for one subband.

Secondly, can pass through the pair W₂Performing inverse Fourier transform calculationNamely, it is

The element in (a) is referred to herein as a "tap". When UE feeds backBy a non-zero subset of coefficients (e.g., those coefficients having the largest magnitude), feedback overhead may be reduced. The feedback overhead also depends on how many quantization bits are used to represent the coefficients.

As described above, the singular vectors are not unique and the random phase associated with the singular vectors may result in poor performance for the type II precoding compression scheme. Providing the appropriate phase for the singular vectors not only improves the compressibility of the stacked singular vectors, but also improves the normalization accuracy of the quantizer.

Fig. 1 depicts an embodiment of a wireless communication system 100 type II codebook compression in accordance with various embodiments of the present disclosure. In one embodiment, wireless communication system 100 includes remote unit 105, base unit 110, and communication link 115. Although a particular number of remote units 105, base units 110, and communication links 115 are depicted in fig. 1, those skilled in the art will recognize that any number of remote units 105, base units 110, and communication links 115 may be included in wireless communication system 100.

In one implementation, the wireless communication system 100 conforms to an NR system specified in 3GPP specifications and/or an LTE system specified in 3 GPP. More generally, however, the wireless communication system 100 may implement some other open or proprietary communication network, such as other networks like WiMAX. The present disclosure is not intended to be limited to implementation of any particular wireless communication system architecture or protocol.

In one embodiment, remote unit 105 may include a computing device, such as a desktop computer, a laptop computer, a personal digital assistant ("PDA"), a tablet computer, a smart phone, a smart television (e.g., a television connected to the internet), a smart appliance (e.g., an appliance connected to the internet), a set-top box, a gaming console, a security system (including a security camera), an in-vehicle computer, a network device (e.g., a router, switch, modem), and so forth. In some embodiments, remote unit 105 includes a wearable device, such as a smart watch, a fitness band, an optical head-mounted display, and so forth. Moreover, remote unit 105 may be referred to as a subscriber unit, mobile device, mobile station, user, terminal, mobile terminal, fixed terminal, subscriber station, UE, user terminal, device, or other terminology used in the art. Remote units 105 may communicate directly with one or more base units 110 via uplink ("UL") and downlink ("DL") communication signals. Further, UL and DL communication signals may be carried over communication link 115.

Base units 110 may be distributed over a geographic area. In some embodiments, base station unit 110 may also be referred to as a RAN Node, access terminal, base station, Node-B, eNB, gNB, home Node-B, relay Node, femtocell, access point, device, or any other terminology used in the art. Base unit 110 is typically part of an access network 120, such as a radio access network ("RAN"), which may include one or more controllers communicatively coupled to one or more corresponding base units 110. These and other elements of access network 120 are not shown, but are well known to those of ordinary skill in the art. The base station unit 110 is connected to a mobile core network 130 via an access network 120. The access network 120 and the mobile core network 130 may be collectively referred to herein as a "mobile network" or a "mobile communication network".

Base unit 110 may serve multiple remote units 105 within a service area (e.g., a cell or cell sector) via wireless communication links. The base unit 110 may communicate directly with one or more remote units 105 via communication signals. Typically, base unit 110 transmits downlink ("DL") communication signals in the time, frequency, and/or spatial domains to serve remote unit 105. Further, DL communication signals may be carried over communication link 115. The communication link 115 may be any suitable carrier in the licensed or unlicensed radio spectrum. Communication links 115 facilitate communication between one or more remote units 105 and/or one or more base units 110.

In one embodiment, the mobile core network 130 is a 5G core ("5 GC") or evolved packet core ("EPC"), which may be coupled to other data networks 150, such as the internet and other data networks, such as private data networks. Each mobile core network 130 belongs to a single public land mobile network ("PLMN"). The present disclosure is not intended to be limited to implementation of any particular wireless communication system architecture or protocol. Other embodiments of mobile core network 130 include, for example, an enhanced packet core ("EPC") or a multi-service core as described by the broadband forum ("BBF").

The mobile core network 130 includes several network functions ("NFs"). As shown, the mobile core network 130 includes an access and mobility management function ("AMF") 133, a session management function ("SMF") 135, and a user plane function ("UPF") 131. Although a particular number of AMFs 133, SMFs 135, and UPFs 131 are depicted in fig. 1, those skilled in the art will recognize that any number and type of network functions may be included in mobile core network 130.

The AMF 133 provides services such as UE registration, UE connection management, and UE mobility management. The SMF 135 manages data sessions, e.g., PDU sessions, for the remote unit 105. The UPF 131 provides user plane (e.g., data) services to the remote unit 105. The data connection between the remote unit 105 and the data network 150 is managed by the UPF 131. UDM 137 provides user identification processing, access authorization, subscription management, etc.

To support spatial multiplexing and MU-MIMO, remote unit 105 provides CSI feedback 125 to base unit 110 using type II codebook compression using phase modification of beams. Remote unit 105 generates a set of modified channel matrices (H)_sbW₁) Wherein (H)_sb) Estimation of a channel matrix being a set of subbandsAnd (W)₁) Is a beam space matrix. The remote unit 105 also generates a set of singular vector coefficients (W) from the modified channel matrix₂)。

The remote unit 105 finds the main beam based on the sum of the absolute values of the singular vector coefficients and sets the phase of all the singular vector coefficients based on the phase of the main beam singular vector coefficients, as described in more detail below.

When calculating the matrix W₂Scaling each element of the singular vector with a unity magnitude complex scalar coefficient will keep the magnitude of the singular vector the same, and it will still keep the singular vector with the same singular value. Since the phase of the singular vector is very implementation dependent and since the singular vector is determined independently for all subbands, it can be assumed that the phase is random from subband to subband depending on the implementation. Observations have shown that fourier transform based quantization methods (as described above) do not perform well when the phase is random.

For remediation, W₂The phase of each column of (a) may be varied as needed to provide a particular structure that facilitates later quantization. Because of W₂Is obtained from singular vectors, so W₂Is referred to as the "singular vector coefficients" of the modified channel.

In various embodiments, remote unit 105 pairs matrix W₂The transform method is used such that the first tap of the main beam has the largest amplitude among all other taps and can therefore be used appropriately for normalization. Note that each beam fills the matrix W₂One row of (a). First, the remote unit 105 determines the main beam based on the absolute values of the singular vector coefficients. In various embodiments, the main beam is the particular beam with the strongest tap. One or more matrixing techniques may be used to force the maximum amplitude coefficient of the main beam into the first column (i.e., remap W₂Column) to become the first tap of the main beam. It is noted that in other embodiments, the maximum amplitude coefficient of the main beam is not forced into the first column, but rather an index pair (rows and columns) of the maximum amplitude coefficient of the main beam is reported.

In addition, remote unit 105 transforms the momentArray W₂To null the phase of the main beam. This enables all taps to be normalized with respect to the first tap of the main beam before quantization. Let m be the index of the main beam.

Firstly, W is mixed₂All N of the m-th column of (1)_sbThe phase of the term is set to zero. Let alpha_ijIs amplitude, phi_ijIs W₂Of the ijth element, i.e. W₂Is given by:

to zero the phase of the main beam, the phases of all beams are offset with respect to the first tap (the strongest tap) by subtracting the phase of the main beam from the original phase of that beam. This subtraction is performed on all sub-bands, i.e. W₂Is now given by

φ′_ij＝φ_ij-φ_imEquation (6)

Now the ijth element becomes

For the main beam, these elements are non-negative real numbers given by

W_2im＝α_imEquation (8)

Note that in equation 8, the element w_2imIs zero. Because it corresponds to W₂All N of the main beam of_sbEach element has a zero phase andthe ijth tap is calculated as:

and for the main beam the tap becomes

The zeroth tap of the main beam now becomes

Now, if the sum of the magnitudes of the elements of the stacked singular vectors is used to select the main beam index m, such that

Is equal toBecomes the largest of all possible taps on all beams. Note that even for the main beam, all other taps have smaller amplitudes than the first tap. This can be done by considering the inverse fourier transform as N_sbThe sum of the two-dimensional vectors is easily demonstrated. The vector sum is maximum if and only if all vectors have the same direction.

Over-sampling can be used to compute the taps in general. The tap value at the oversampling position i '(i' is not an integer) is obtained as

It can also be shown that using equation 12 to select the main beam and zero its phase also ensures that the first tap of the main beam is the strongest tap. The next normalization is performed using the first tap of the main beam, i.e.

This transformation forces the amplitude of the first tap of the main beam to be uniform (e.g.,). Thus, there is no need to explicitly quantize the first tap of the main beam, since the value of this tap can be directly inferred as 1 and its phase can be inferred as 0. Release 16 type II CSI specifies the reporting of the strongest tap of each beam and such reporting is typically composed of amplitude and phase. Since the first tap is always included because it has the largest magnitude, it can be inferred to be 1, and therefore no reporting is required, thus saving valuable uplink control signaling overhead.

In various embodiments, only the index of the primary beam (i.e., the beam containing the strongest coefficients) is reported to the RAN node (e.g., the gNB). Thus, the CSI feedback sent to the RAN node does not include the first element of the magnitude coefficient vector and the first element of the phase coefficient vector corresponding to a particular beam, but rather includes an indication of one or more elements of the vector of magnitude coefficient vector and phase coefficient vector corresponding to the identified beam.

Furthermore, returning to equation 9a, it can be readily seen that the i-th tap of the main beam is N_sb-iThe complex conjugate of the tap, i.e.,

where is the complex conjugate operation. Equation 14 enables the transmitter (UE) to quantize and transmit only half of the main beam tap, since the second half of the tap can be obtained at the receiver/decoder (gNB) using this symmetry property. Similarly, if only a subset of taps (the same or different groups of taps across a beam, respectively) are reported on a common or independent basis, the number of possibilities for tap combining is reduced, since about half of the taps are paired, which means that the number of possibilities is reduced by about half. This also reduces uplink signaling overhead. However, only in the case where the tap reports are independent of all beams,can such reporting advantages be utilized. In the case of common base reporting, the reporting must be done over the entire range of taps. However, if the reported taps do not follow symmetry, i.e., the ith tap is reported, but the UE does not report N to the gNB_sb-iThe decoder (gNB) can refine the precoding vector by generating additional taps for the main beam.

In some embodiments, the upsampling factors for all beams are reported by selecting the fractional portion that results in the largest tap value for that beam, and then for the main beam, the fractional component will always be zero, so again there is no need to report the fractional portion of the main beam.

Advantageously, the normalization of the first tap of the main beam yields a good range for the quantization of the other taps. Furthermore, this normalization always results in the first tap of the main beam being "1", so there is no need to report this value. Furthermore, one of the strongest taps need not be specified, it is always the first tap of the main beam, and the oversampling factor for the main beam will always be "0". As described above, using zero phase for the main beam results in the coefficients before the inverse Fourier transform being real and therefore corresponding to that of the main beamThe columns of (a) will be symmetrical and the quantization method may advantageously use this property to report only half of the main beam taps.

Fig. 2 depicts a first process 200 of type II codebook compression using phase modification of beams according to an embodiment of the present disclosure. Process 200 may be performed by a UE, such as remote unit 105. The process 200 begins with the UE computing 205 a beam selection matrix (W)₁) And generates 210 a modified channel matrix (H)_sb W₁) As described above. In addition, the UE generates 215 a set of singular vector coefficients (i.e., the matrix W) from the modified channel matrix₂) And defines 220 a particular beam (i.e., the main beam) based on the singular vector coefficients. In various embodiments, the particular beam is selected based on the sum of the absolute values of the singular vector coefficients.

The UE modifies 225 the phases of all singular vector coefficients based on the phase of the main beam singular vector coefficient. As described above, the phase modification solves the problem that random phase causes poor performance of type II codebook compression based on discrete fourier transform. The UE computes 230 a precoding matrix using the modified singular vector coefficients and sends 235CSI feedback to a decoder (e.g., the gNB).

Fig. 3 depicts a second procedure 300 for type II codebook compression using phase modification of beams in accordance with an embodiment of the present disclosure. Process 300 may be performed by a UE, such as remote unit 105. Process 300 begins with the UE starting from the modified channel matrix (H)_sb W₁) Generating 305 a set of singular vector coefficients (W)₂) As described above. UE by executing W₂Inverse fourier transform of (d) to generate 310 a matrixFor example to generate taps. Further, the UE normalizes 315 taps by dividing by the first tap of the main beam and quantizes 320 taps using the appropriate bits. In some embodiments, the quantized taps include taps that are quantized only half, where the decoder uses symmetry properties to generate other taps. The UE further sends 325CSI feedback (e.g., precoding matrix) to a decoder (e.g., gNB).

Fig. 4 depicts a user equipment device 400 that may be used for type II codebook compression using phase modification of beams in accordance with an embodiment of the present disclosure. And the UE. In various embodiments, the user equipment device 400 is used to implement one or more of the above solutions. The user equipment device 400 may be one embodiment of the remote unit 105 described above. Further, the user equipment device 400 may include a processor 405, a memory 410, an input device 415, an output device 420, and a transceiver 425. In some embodiments, the input device 415 and the output device 420 are combined into a single device, such as a touch screen. In some embodiments, the user equipment device 400 may not include any input devices 415 and/or output devices 420. In various embodiments, the user equipment device 400 may include one or more of the following: processor 405, memory 410, and transceiver 425, and may not include input device 415 and/or output device 420.

In one embodiment, the processor 405 may include any known controller capable of executing computer readable instructions and/or capable of performing logical operations. For example, the processor 405 may be a microcontroller, microprocessor, central processing unit ("CPU"), graphics processing unit ("GPU"), auxiliary processing unit, field programmable gate array ("FPGA"), or similar programmable controller. In some embodiments, the processor 405 executes instructions stored in the memory 410 to perform the methods and routines described herein. The processor 405 is communicatively coupled to the memory 410, the input device 415, the output device 420, and the transceiver 425.

In various embodiments, the transceiver 425 receives a set of reference signals and the processor 405 identifies a set of beams based on the set of reference signals. Processor 405 transforms a set of reference signals to obtain per-layer vectors of amplitude and phase coefficients for 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 magnitude coefficient vector corresponding to a particular beam is one and the first element of the phase coefficient vector corresponding to a particular beam is zero.

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

In some embodiments, transforming the set of reference signals includes the processor 405 performing a fourier-based transform that includes at least one of a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain a vector of amplitude and phase coefficients of the DFT compressed codebook may comprise the processor 405 performing a phase shifting operation based on the phase of a particular beam prior to the fourier based transformation. In some embodiments, processor 405 identifies a particular beam based on a sum of the magnitudes of the elements of the input vector. Note that the input vectors are the inputs of a fourier-based transform, where each input vector corresponds to an identified beam.

In some embodiments, transforming the set of reference signals includes the processor 405 normalizing the magnitude coefficient vector for the identified set of beams based on a first element of the magnitude coefficient vector for the particular beam. In some embodiments, transforming the set of reference signals includes the processor 405 subtracting a first element of the phase coefficient vector for the particular beam from the phases of the identified set of beams. In some embodiments, converting the set of reference signals includes processor 405 quantizing amplitude and phase coefficients of the identified set of beams.

Through transceiver 425, processor 405 transmits CSI feedback to the base station, wherein the CSI feedback comprises an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to at least one identified beam, wherein the CSI feedback does not comprise a first element of a magnitude coefficient vector and a first element of a phase coefficient vector corresponding to a particular beam.

In some embodiments, the processor 405 reports an index corresponding to a particular beam. For example, the CSI feedback may include an indication of a beam index of a particular beam. In such embodiments, the index of the report may be identified based on a sum of magnitudes of elements of input vectors, where the input vectors are input to the fourier-based transform, and where each input vector corresponds to an identified beam.

In one embodiment, memory 410 is a computer-readable storage medium. In some embodiments, memory 410 includes volatile computer storage media. For example, the memory 410 may include RAM, including dynamic RAM ("DRAM"), synchronous dynamic RAM ("SDRAM"), and/or static RAM ("SRAM"). In some embodiments, memory 410 includes non-volatile computer storage media. For example, memory 410 may include a hard drive, flash memory, or any other suitable non-volatile computer storage device. In some embodiments, memory 410 includes both volatile and nonvolatile computer storage media.

In some embodiments, memory 410 stores data related to type II codebook compression using phase modification of beams. In certain embodiments, memory 410 also stores program code and related data, such as an operating system or other controller algorithms operating on remote unit 105.

In one embodiment, input device 415 may comprise any known computer input device, including a touch panel, buttons, a keyboard, a stylus, a microphone, and the like. In some embodiments, the input device 415 may be integrated with the output device 420, for example as a touch screen or similar touch sensitive display. In some embodiments, the input device 415 includes a touch screen such that text can be entered using a virtual keyboard displayed on the touch screen and/or by handwriting on the touch screen. In some embodiments, input device 415 includes two or more different devices, such as a keyboard and a touch panel.

In one embodiment, output device 420 is designed to output visual, audible, and/or tactile signals. In some embodiments, output device 420 comprises an electronically controllable display or display device capable of outputting visual data to a user. For example, output device 420 may include, but is not limited to, an LCD display, an LED display, an OLED display, a projector, or similar display device capable of outputting images, text, and the like to a user. As another non-limiting example, the output device 420 may include a wearable display, such as a smart watch, smart glasses, heads-up display, and the like, separate from but communicatively coupled with the rest of the user equipment apparatus 400. Further, output device 420 may be a component of a smart phone, personal digital assistant, television, desktop computer, notebook (laptop) computer, personal computer, vehicle dashboard, or the like.

In some embodiments, the output device 420 includes one or more speakers for producing sound. For example, the output device 420 may generate an audible alarm or notification (e.g., a beep or alert tone). In some embodiments, output device 420 includes one or more haptic devices for generating vibrations, motions, or other haptic feedback. In some embodiments, all or part of the output device 420 may be integrated with the input device 415. For example, the input device 415 and the output device 420 may form a touch screen or similar touch sensitive display. In other embodiments, the output device 420 may be located near the input device 415.

In various embodiments, the transceiver 425 communicates with one or more network functions of the mobile communication network via one or more access networks. The transceiver 425 operates under the control of the processor 405 to transmit and also receive messages, data, and other signals. For example, the processor 405 may selectively activate the transceiver (or portions thereof) at particular times in order to send and receive messages.

The transceiver 425 may include one or more transmitters 430 and one or more receivers 435. Although only one transmitter 430 and one receiver 435 are shown, the user equipment device 400 may have any suitable number of transmitters 430 and receivers 435. In addition. For example, the transmitter 430 and receiver 435 may be any suitable type of transmitter and receiver. In one embodiment, the transceiver 425 includes a first transmitter/receiver pair for communicating with a mobile communications network over a licensed radio spectrum and a second transmitter/receiver pair for communicating with the mobile communications network over an unlicensed radio spectrum.

In some embodiments, a first transmitter/receiver pair for communicating with a mobile communications network over a licensed radio spectrum and a second transmitter/receiver pair for communicating with a mobile communications network over an unlicensed radio spectrum may be combined into a single transceiver unit, e.g., a single chip that performs the functions for the licensed and unlicensed radio spectrums. In some embodiments, the first transmitter/receiver pair and the second transmitter/receiver pair may share one or more hardware components. For example, certain transceivers 425, transmitters 430, and receivers 435 may be implemented as physically separate components accessing shared hardware resources and/or software resources (e.g., network interface 440).

In various embodiments, the one or more transmitters 430 and/or the one or more receivers 435 may 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 some embodiments, one or more transmitters 430 and/or one or more receivers 435 may be implemented and/or integrated into a multi-chip module. In some embodiments, other components, such as the network interface 440 or other hardware components/circuits, may be integrated with any number of transmitters 430 and/or receivers 435 into a single chip. In such embodiments, the transmitter 430 and receiver 435 may be logically configured as a transceiver 425 using one or more common control signals or as a modular transmitter 430 and receiver 435 implemented in the same hardware chip or multi-chip module.

Fig. 5 depicts one embodiment of a method 500 for generating CSI reports in accordance with an embodiment of the present disclosure. In various embodiments, the method 500 is performed by the remote unit 105 and/or the user equipment device 400, as described above. In some embodiments, method 500 is performed by a processor, such as a microcontroller, microprocessor, Central Processing Unit (CPU), Graphics Processing Unit (GPU), auxiliary processing unit, FPGA, or the like.

The method 500 begins and receives 505 a set of reference signals transmitted from a RAN node. The method 500 includes identifying 510 a set of beams based on a set of reference signals.

The method 500 includes transforming 515 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 magnitude coefficient vector corresponding to a particular beam is one and the first element of the phase coefficient vector corresponding to a particular beam is zero.

In some embodiments, transforming 515 the set of reference signals includes performing a fourier-based transform that includes at least one of a DFT and an inverse DFT. In such embodiments, transforming a set of reference signals to obtain vectors of amplitude and phase coefficients of a DFT compressed codebook may include a phase shifting operation prior to a fourier-based transformation, the phase shifting operation based on the phase of a particular beam. In various embodiments, a particular beam is identified based on a sum of magnitudes of elements of an input vector, wherein the input vectors are input to a fourier-based transform, and wherein each input vector corresponds to an identified beam.

In some embodiments, transforming 515 the set of reference signals includes normalizing the magnitude coefficient vector for the identified set of beams based on a first element of the magnitude coefficient vector for the particular beam. In some embodiments, transforming 515 the set of reference signals includes subtracting a first element of a phase coefficient vector for the particular beam from the phase of the identified set of beams. In some embodiments, transforming 515 the set of reference signals includes quantizing amplitude and phase coefficients of the identified set of beams. In various embodiments, the first element of the magnitude coefficient vector corresponding to a particular beam is greater than or equal to each element of the magnitude coefficient vectors corresponding to all identified beams.

The method 500 includes sending 520CSI feedback to the RAN node. Here, the CSI feedback comprises an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to the at least one identified beam. In addition, the CSI feedback does not include a first element of the magnitude coefficient vector and a first element of the phase coefficient vector corresponding to the particular beam. The method 500 ends.

In some embodiments, sending 520CSI feedback to the RAN node includes reporting an index corresponding to a particular beam. In one embodiment, the index of the report is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to a fourier-based transform, and wherein each input vector corresponds to an identified beam.

Disclosed herein is a first apparatus for generating a CSI report according to an embodiment of the present disclosure. The first apparatus may be implemented by a UE device, such as remote unit 105 and/or user equipment apparatus 400, that uses discrete fourier transform-based type II codebook compression. 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 a 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 magnitude coefficient vector corresponding to a particular beam is one and the first element of the phase coefficient vector corresponding to a particular beam is zero. The processor, through the transceiver, transmits CSI feedback to the base station, wherein the CSI feedback includes an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to the at least one identified beam, wherein the CSI feedback does not include a first element of the magnitude coefficient vector and a first element of the phase coefficient vector corresponding to a particular beam.

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

In some embodiments, transforming the set of reference signals includes performing a fourier-based transform, the transform including at least one of a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain a vector of amplitude and phase coefficients of the DFT compressed codebook may include a phase shifting operation prior to the fourier based transformation, the phase shifting operation based on the phase of the particular beam. In some embodiments, the particular beam is identified based on a sum of magnitudes of elements of an input vector, wherein the input vectors are input to a fourier-based transform, and wherein each input vector corresponds to an identified beam.

In some embodiments, the processor reports an index corresponding to a particular beam. For example, the CSI feedback may include an indication of a beam index of a particular beam. In such embodiments, the index of the report may be identified based on a sum of magnitudes of elements of input vectors, where the input vectors are input to the fourier-based transform, and where each input vector corresponds to an identified beam.

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

In accordance with an embodiment of the present disclosure, a first method for generating a CSI report is disclosed herein. The first method may be performed by a UE device for type II codebook compression using discrete fourier transform based type II codebook compression, such as the remote unit 105 and/or the user equipment device 800. A 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. A 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 magnitude coefficient vector corresponding to a particular beam is one and the first element of the phase coefficient vector corresponding to a particular beam is zero. The method includes sending CSI feedback to the RAN node. Here, the CSI feedback comprises an indication of one or more elements of a vector of magnitude coefficient vectors and phase coefficient vectors corresponding to the at least one identified beam. In addition, the CSI feedback does not include a first element of the magnitude coefficient vector and a first element of the phase coefficient vector corresponding to the particular beam.

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

In some embodiments, transforming the set of reference signals includes performing a fourier-based transform, the transform including at least one of a DFT and an inverse DFT. In such embodiments, transforming the set of reference signals to obtain a vector of amplitude and phase coefficients of the DFT compressed codebook may include performing a phase shifting operation based on the phase of a particular beam prior to the fourier based transformation. In some embodiments, the particular beam is identified based on a sum of magnitudes of elements of an input vector, wherein the input vectors are input to a fourier-based transform, and wherein each input vector corresponds to an identified beam.

In some embodiments, the first method includes reporting an index corresponding to a particular beam. In certain embodiments, the index of the report is identified based on a sum of magnitudes of elements of input vectors, wherein the input vectors are input to a fourier-based transform, and wherein each input vector corresponds to an identified beam.

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

Embodiments may be practiced in other specific forms. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.