WO2023216126A1

WO2023216126A1 - Channel state information prediction based on multi-segment doppler-domain spectrum distribution

Info

Publication number: WO2023216126A1
Application number: PCT/CN2022/092135
Authority: WO
Inventors: Min Huang; Jing Dai; Chao Wei
Original assignee: Qualcomm Incorporated
Priority date: 2022-05-11
Filing date: 2022-05-11
Publication date: 2023-11-16

Abstract

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE. The UE may determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The UE may transmit a communication indicating the set of parameters of the multi-segment time-domain compression model. Numerous other aspects are described.

Description

CHANNEL STATE INFORMATION PREDICTION BASED ON MULTI-SEGMENT DOPPLER-DOMAIN SPECTRUM DISTRIBUTION

FIELD OF THE DISCLOSURE

Aspects of the present disclosure generally relate to wireless communication and to techniques and apparatuses for channel state information (CSI) prediction based on multi-segment Doppler-domain spectrum distribution.

BACKGROUND

Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasts. Typical wireless communication systems may employ multiple-access technologies capable of supporting communication with multiple users by sharing available system resources (e.g., bandwidth, transmit power, or the like) . Examples of such multiple-access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, time division synchronous code division multiple access (TD-SCDMA) systems, and Long Term Evolution (LTE) . LTE/LTE-Advanced is a set of enhancements to the Universal Mobile Telecommunications System (UMTS) mobile standard promulgated by the Third Generation Partnership Project (3GPP) .

A wireless network may include one or more base stations that support communication for a user equipment (UE) or multiple UEs. A UE may communicate with a base station via downlink communications and uplink communications. “Downlink” (or “DL” ) refers to a communication link from the base station to the UE, and “uplink” (or “UL” ) refers to a communication link from the UE to the base station.

The above multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different UEs to communicate on a municipal, national, regional, and/or global level. New Radio (NR) , which may be referred to as 5G, is a set of enhancements to the LTE mobile standard promulgated by the 3GPP. NR is designed to better support mobile broadband internet access by improving spectral efficiency, lowering costs, improving services, making use of new spectrum, and better integrating with other open standards using orthogonal frequency division multiplexing (OFDM) with a cyclic prefix (CP) (CP-OFDM) on the downlink, using CP-OFDM and/or single-carrier frequency division multiplexing (SC-FDM) (also known as discrete Fourier transform spread OFDM (DFT-s-OFDM) ) on the uplink, as well as supporting beamforming, multiple-input multiple-output (MIMO) antenna technology, and carrier aggregation. As the demand for mobile broadband access continues to increase, further improvements in LTE, NR, and other radio access technologies remain useful.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the above-recited features of the present disclosure can be understood in detail, a more particular description, briefly summarized above, may be had by reference to aspects, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only certain typical aspects of this disclosure and are therefore not to be considered limiting of its scope, for the description may admit to other equally effective aspects. The same reference numbers in different drawings may identify the same or similar elements.

Fig. 1 is a diagram illustrating an example of a wireless network, in accordance with the present disclosure.

Fig. 2 is a diagram illustrating an example of a base station in communication with a user equipment (UE) in a wireless network, in accordance with the present disclosure.

Fig. 3 is a diagram illustrating an example 300 of an open radio access network (O-RAN) architecture, in accordance with the present disclosure.

Fig. 4 is a diagram illustrating an example associated with channel state information (CSI) prediction based on multi-segment Doppler-domain spectrum distribution, in accordance with the present disclosure.

Figs. 5 and 6 are diagrams illustrating example processes associated with CSI prediction based on multi-segment Doppler-domain spectrum distribution, in accordance with the present disclosure.

Figs. 7 and 8 are diagrams of example apparatuses for wireless communication, in accordance with the present disclosure.

SUMMARY

Some aspects described herein relate to a method of wireless communication performed by a UE. The method may include calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE. The method may include determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The method may include transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to a method of wireless communication performed by a network entity. The method may include receiving a communication indicating a set of parameters of a multi-segment time-domain compression model. The method may include predicting channel state information (CSI) associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to a UE for wireless communication. The UE may include a memory and one or more processors coupled to the memory. The one or more processors may be configured to calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE. The one or more processors may be configured to determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The one or more processors may be configured to transmit a communication indicating the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to a network entity for wireless communication. The network entity may include a memory and one or more processors coupled to the memory. The one or more processors may be configured to receive a communication indicating a set of parameters of a multi-segment time-domain compression model. The one or more processors may be configured to predict CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit a communication indicating the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a network entity. The set of instructions, when executed by one or more processors of the network entity, may cause the network entity to receive a communication indicating a set of parameters of a multi-segment time-domain compression model. The set of instructions, when executed by one or more processors of the network entity, may cause the network entity to predict CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the apparatus. The apparatus may include means for determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The apparatus may include means for transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for receiving a communication indicating a set of parameters of a multi-segment time-domain compression model. The apparatus may include means for predicting CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

Aspects generally include a method, apparatus, system, computer program product, non-transitory computer-readable medium, user equipment, network entity, wireless communication device, and/or processing system as substantially described herein with reference to and as illustrated by the drawings and specification.

The foregoing has outlined rather broadly the features and technical advantages of examples according to the disclosure in order that the detailed description that follows may be better understood. Additional features and advantages will be described hereinafter. The conception and specific examples disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. Characteristics of the concepts disclosed herein, both their organization and method of operation, together with associated advantages, will be better understood from the following description when considered in connection with the accompanying figures. Each of the figures is provided for the purposes of illustration and description, and not as a definition of the limits of the claims.

While aspects are described in the present disclosure by illustration to some examples, those skilled in the art will understand that such aspects may be implemented in many different arrangements and scenarios. Techniques described herein may be implemented using different platform types, devices, systems, shapes, sizes, and/or packaging arrangements. For example, some aspects may be implemented via integrated chip embodiments or other non-module-component based devices (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail/purchasing devices, medical devices, and/or artificial intelligence devices) . Aspects may be implemented in chip-level components, modular components, non-modular components, non-chip-level components, device-level components, and/or system-level components. Devices incorporating described aspects and features may include additional components and features for implementation and practice of claimed and described aspects. For example, transmission and reception of wireless signals may include one or more components for analog and digital purposes (e.g., hardware components including antennas, radio frequency (RF) chains, power amplifiers, modulators, buffers, processors, interleavers, adders, and/or summers) . It is intended that aspects described herein may be practiced in a wide variety of devices, components, systems, distributed arrangements, and/or end-user devices of varying size, shape, and constitution.

DETAILED DESCRIPTION

Various aspects of the disclosure are described more fully hereinafter with reference to the accompanying drawings. This disclosure may, however, be embodied in many different forms and should not be construed as limited to any specific structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. One skilled in the art should appreciate that the scope of the disclosure is intended to cover any aspect of the disclosure disclosed herein, whether implemented independently of or combined with any other aspect of the disclosure. For example, an apparatus may be implemented or a method may be practiced using any number of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover such an apparatus or method which is practiced using other structure, functionality, or structure and functionality in addition to or other than the various aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim.

Several aspects of telecommunication systems will now be presented with reference to various apparatuses and techniques. These apparatuses and techniques will be described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, components, circuits, steps, processes, algorithms, or the like (collectively referred to as “elements” ) . These elements may be implemented using hardware, software, or combinations thereof. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.

While aspects may be described herein using terminology commonly associated with a 5G or New Radio (NR) radio access technology (RAT) , aspects of the present disclosure can be applied to other RATs, such as a 3G RAT, a 4G RAT, and/or a RAT subsequent to 5G (e.g., 6G) .

Fig. 1 is a diagram illustrating an example of a wireless network 100, in accordance with the present disclosure. The wireless network 100 may be or may include elements of a 5G (e.g., NR) network and/or a 4G (e.g., Long Term Evolution (LTE) ) network, among other examples. The wireless network 100 may include one or more base stations 110 (shown as a BS 110a, a BS 110b, a BS 110c, and a BS 110d) , a user equipment (UE) 120 or multiple UEs 120 (shown as a UE 120a, a UE 120b, a UE 120c, a UE 120d, and a UE 120e) , and/or other network entities. A base station 110 is an entity that communicates with UEs 120. A base station 110 (sometimes referred to as a BS) may include, for example, an NR base station, an LTE base station, a Node B, an eNB (e.g., in 4G) , a gNB (e.g., in 5G) , an access point, and/or a transmission reception point (TRP) . Each base station 110 may provide communication coverage for a particular geographic area. In the Third Generation Partnership Project (3GPP) , the term “cell” can refer to a coverage area of a base station 110 and/or a base station subsystem serving this coverage area, depending on the context in which the term is used.

A base station 110 may provide communication coverage for a macro cell, a pico cell, a femto cell, and/or another type of cell. A macro cell may cover a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access by UEs 120 with service subscriptions. A pico cell may cover a relatively small geographic area and may allow unrestricted access by UEs 120 with service subscription. A femto cell may cover a relatively small geographic area (e.g., a home) and may allow restricted access by UEs 120 having association with the femto cell (e.g., UEs 120 in a closed subscriber group (CSG) ) . A base station 110 for a macro cell may be referred to as a macro base station. A base station 110 for a pico cell may be referred to as a pico base station. A base station 110 for a femto cell may be referred to as a femto base station or an in-home base station. In the example shown in Fig. 1, the BS 110a may be a macro base station for a macro cell 102a, the BS 110b may be a pico base station for a pico cell 102b, and the BS 110c may be a femto base station for a femto cell 102c. A base station may support one or multiple (e.g., three) cells.

In some aspects, the term “base station” (e.g., the base station 110) or “network node” or “network entity” may refer to an aggregated base station, a disaggregated base station (e.g., described in connection with Fig. 9) , an integrated access and backhaul (IAB) node, a relay node, and/or one or more components thereof. For example, in some aspects, “base station, ” “network node, ” or “network entity” may refer to a central unit (CU) , a distributed unit (DU) , a radio unit (RU) , a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC) , or a Non-Real Time (Non-RT) RIC, or a combination thereof. In some aspects, the term “base station, ” “network node, ” or “network entity” may refer to one device configured to perform one or more functions, such as those described herein in connection with the base station 110. In some aspects, the term “base station, ” “network node, ” or “network entity” may refer to a plurality of devices configured to perform the one or more functions. For example, in some distributed systems, each of a number of different devices (which may be located in the same geographic location or in different geographic locations) may be configured to perform at least a portion of a function, or to duplicate performance of at least a portion of the function, and the term “base station, ” “network node, ” or “network entity” may refer to any one or more of those different devices. In some aspects, the term “base station, ” “network node, ” or “network entity” may refer to one or more virtual base stations and/or one or more virtual base station functions. For example, in some aspects, two or more base station functions may be instantiated on a single device. In some aspects, the term “base station, ” “network node, ” or “network entity” may refer to one of the base station functions and not another. In this way, a single device may include more than one base station.

Deployment of communication systems, such as 5G New Radio (NR) systems, may be arranged in multiple manners with various components or constituent parts. In a 5G NR system, or network, a network node, a network entity, a mobility element of a network, a radio access network (RAN) node, a core network node, a network element, a base station, or a network equipment may be implemented in an aggregated or disaggregated architecture. For example, a base station (such as a Node B (NB) , evolved NB (eNB) , NR base station (BS) , 5G NB, gNodeB (gNB) , access point (AP) , transmit receive point (TRP) , or cell) , or one or more units (or one or more components) performing base station functionality, may be implemented as an aggregated base station (also known as a standalone base station or a monolithic base station) or a disaggregated base station. “Network entity” or “network node” may refer to a disaggregated base station, or to one or more units of a disaggregated base station (such as one or more CUs, one or more DUs, one or more RUs, or a combination thereof) .

An aggregated base station may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node (for example, within a single device or unit) . A disaggregated base station may be configured to utilize a protocol stack that is physically or logically distributed among two or more units (such as one or more CUs, one or more DUs, or one or more RUs) . In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed throughout one or multiple other RAN nodes. The DUs may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU also may be implemented as virtual units (e.g., a virtual central unit (VCU) , a virtual distributed unit (VDU) , or a virtual radio unit (VRU) ) .

Base station-type operation or network design may consider aggregation characteristics of base station functionality. For example, disaggregated base stations may be utilized in an integrated access backhaul (IAB) network, an open radio access network (O-RAN (such as the network configuration sponsored by the O-RAN Alliance) ) , or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN) ) to facilitate scaling of communication systems by separating base station functionality into one or more units that may be individually deployed. A disaggregated base station may include functionality implemented across two or more units at various physical locations, as well as functionality implemented for at least one unit virtually, which may enable flexibility in network design. The various units of the disaggregated base station may be configured for wired or wireless communication with at least one other unit of the disaggregated base station.

In some examples, a cell may not necessarily be stationary, and the geographic area of the cell may move according to the location of a base station 110 that is mobile (e.g., a mobile base station) . In some examples, the base stations 110 may be interconnected to one another and/or to one or more other base stations 110 or network nodes (not shown) in the wireless network 100 through various types of backhaul interfaces, such as a direct physical connection or a virtual network, using any suitable transport network.

The wireless network 100 may include one or more relay stations. A relay station is an entity that can receive a transmission of data from an upstream station (e.g., a base station 110 or a UE 120) and send a transmission of the data to a downstream station (e.g., a UE 120 or a base station 110) . A relay station may be a UE 120 that can relay transmissions for other UEs 120. In the example shown in Fig. 1, the BS 110d (e.g., a relay base station) may communicate with the BS 110a (e.g., a macro base station) and the UE 120d in order to facilitate communication between the BS 110a and the UE 120d. A base station 110 that relays communications may be referred to as a relay station, a relay base station, a relay, or the like.

The wireless network 100 may be a heterogeneous network that includes base stations 110 of different types, such as macro base stations, pico base stations, femto base stations, relay base stations, or the like. These different types of base stations 110 may have different transmit power levels, different coverage areas, and/or different impacts on interference in the wireless network 100. For example, macro base stations may have a high transmit power level (e.g., 5 to 40 watts) whereas pico base stations, femto base stations, and relay base stations may have lower transmit power levels (e.g., 0.1 to 2 watts) .

A network controller 130 may couple to or communicate with a set of base stations 110 and may provide coordination and control for these base stations 110. The network controller 130 may communicate with the base stations 110 via a backhaul communication link. The base stations 110 may communicate with one another directly or indirectly via a wireless or wireline backhaul communication link.

The UEs 120 may be dispersed throughout the wireless network 100, and each UE 120 may be stationary or mobile. A UE 120 may include, for example, an access terminal, a terminal, a mobile station, and/or a subscriber unit. A UE 120 may be a cellular phone (e.g., a smart phone) , a personal digital assistant (PDA) , a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device, a biometric device, a wearable device (e.g., a smart watch, smart clothing, smart glasses, a smart wristband, smart jewelry (e.g., a smart ring or a smart bracelet) ) , an entertainment device (e.g., a music device, a video device, and/or a satellite radio) , a vehicular component or sensor, a smart meter/sensor, industrial manufacturing equipment, a global positioning system device, and/or any other suitable device that is configured to communicate via a wireless medium.

Some UEs 120 may be considered machine-type communication (MTC) or evolved or enhanced machine-type communication (eMTC) UEs. An MTC UE and/or an eMTC UE may include, for example, a robot, a drone, a remote device, a sensor, a meter, a monitor, and/or a location tag, that may communicate with a base station, another device (e.g., a remote device) , or some other entity. Some UEs 120 may be considered Internet-of-Things (IoT) devices, and/or may be implemented as NB-IoT (narrowband IoT) devices. Some UEs 120 may be considered a Customer Premises Equipment. A UE 120 may be included inside a housing that houses components of the UE 120, such as processor components and/or memory components. In some examples, the processor components and the memory components may be coupled together. For example, the processor components (e.g., one or more processors) and the memory components (e.g., a memory) may be operatively coupled, communicatively coupled, electronically coupled, and/or electrically coupled.

In general, any number of wireless networks 100 may be deployed in a given geographic area. Each wireless network 100 may support a particular RAT and may operate on one or more frequencies. A RAT may be referred to as a radio technology, an air interface, or the like. A frequency may be referred to as a carrier, a frequency channel, or the like. Each frequency may support a single RAT in a given geographic area in order to avoid interference between wireless networks of different RATs. In some cases, NR or 5G RAT networks may be deployed.

In some examples, two or more UEs 120 (e.g., shown as UE 120a and UE 120e) may communicate directly using one or more sidelink channels (e.g., without using a base station 110 as an intermediary to communicate with one another) . For example, the UEs 120 may communicate using peer-to-peer (P2P) communications, device-to-device (D2D) communications, a vehicle-to-everything (V2X) protocol (e.g., which may include a vehicle-to-vehicle (V2V) protocol, a vehicle-to-infrastructure (V2I) protocol, or a vehicle-to-pedestrian (V2P) protocol) , and/or a mesh network. In such examples, a UE 120 may perform scheduling operations, resource selection operations, and/or other operations described elsewhere herein as being performed by the base station 110.

Devices of the wireless network 100 may communicate using the electromagnetic spectrum, which may be subdivided by frequency or wavelength into various classes, bands, channels, or the like. For example, devices of the wireless network 100 may communicate using one or more operating bands. In 5G NR, two initial operating bands have been identified as frequency range designations FR1 (410 MHz –7.125 GHz) and FR2 (24.25 GHz –52.6 GHz) . It should be understood that although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as a “Sub-6 GHz” band in various documents and articles. A similar nomenclature issue sometimes occurs with regard to FR2, which is often referred to (interchangeably) as a “millimeter wave” band in documents and articles, despite being different from the extremely high frequency (EHF) band (30 GHz –300 GHz) which is identified by the International Telecommunications Union (ITU) as a “millimeter wave” band.

The frequencies between FR1 and FR2 are often referred to as mid-band frequencies. Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz –24.25 GHz) . Frequency bands falling within FR3 may inherit FR1 characteristics and/or FR2 characteristics, and thus may effectively extend features of FR1 and/or FR2 into mid-band frequencies. In addition, higher frequency bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as frequency range designations FR4a or FR4-1 (52.6 GHz –71 GHz) , FR4 (52.6 GHz –114.25 GHz) , and FR5 (114.25 GHz –300 GHz) . Each of these higher frequency bands falls within the EHF band.

With the above examples in mind, unless specifically stated otherwise, it should be understood that the term “sub-6 GHz” or the like, if used herein, may broadly represent frequencies that may be less than 6 GHz, may be within FR1, or may include mid-band frequencies. Further, unless specifically stated otherwise, it should be understood that the term “millimeter wave” or the like, if used herein, may broadly represent frequencies that may include mid-band frequencies, may be within FR2, FR4, FR4-a or FR4-1, and/or FR5, or may be within the EHF band. It is contemplated that the frequencies included in these operating bands (e.g., FR1, FR2, FR3, FR4, FR4-a, FR4-1, and/or FR5) may be modified, and techniques described herein are applicable to those modified frequency ranges.

In some aspects, a UE, such as a UE 120, may include a communication manager 140. As described in more detail elsewhere herein, the communication manager 140 may calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE; determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices; and transmit a communication indicating the set of parameters of the multi-segment time-domain compression model. Additionally, or alternatively, the communication manager 140 may perform one or more other operations described herein.

In some aspects, a network entity, such as a base station 110, may include a communication manager 150. As described in more detail elsewhere herein, the communication manager 150 may receive a communication indicating a set of parameters of a multi-segment time-domain compression model; and predict CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model. Additionally, or alternatively, the communication manager 150 may perform one or more other operations described herein.

As indicated above, Fig. 1 is provided as an example. Other examples may differ from what is described with regard to Fig. 1.

Fig. 2 is a diagram illustrating an example 200 of a base station 110 in communication with a UE 120 in a wireless network 100, in accordance with the present disclosure. The base station 110 may be equipped with a set of antennas 234a through 234t, such as T antennas (T ≥ 1) . The UE 120 may be equipped with a set of antennas 252a through 252r, such as R antennas (R ≥ 1) .

At the base station 110, a transmit processor 220 may receive data, from a data source 212, intended for the UE 120 (or a set of UEs 120) . The transmit processor 220 may select one or more modulation and coding schemes (MCSs) for the UE 120 based at least in part on one or more channel quality indicators (CQIs) received from that UE 120. The base station 110 may process (e.g., encode and modulate) the data for the UE 120 based at least in part on the MCS (s) selected for the UE 120 and may provide data symbols for the UE 120. The transmit processor 220 may process system information (e.g., for semi-static resource partitioning information (SRPI) ) and control information (e.g., CQI requests, grants, and/or upper layer signaling) and provide overhead symbols and control symbols. The transmit processor 220 may generate reference symbols for reference signals (e.g., a cell-specific reference signal (CRS) or a demodulation reference signal (DMRS) ) and synchronization signals (e.g., a primary synchronization signal (PSS) or a secondary synchronization signal (SSS) ) . A transmit (TX) multiple-input multiple-output (MIMO) processor 230 may perform spatial processing (e.g., precoding) on the data symbols, the control symbols, the overhead symbols, and/or the reference symbols, if applicable, and may provide a set of output symbol streams (e.g., T output symbol streams) to a corresponding set of modems 232 (e.g., T modems) , shown as modems 232a through 232t. For example, each output symbol stream may be provided to a modulator component (shown as MOD) of a modem 232. Each modem 232 may use a respective modulator component to process a respective output symbol stream (e.g., for OFDM) to obtain an output sample stream. Each modem 232 may further use a respective modulator component to process (e.g., convert to analog, amplify, filter, and/or upconvert) the output sample stream to obtain a downlink signal. The modems 232a through 232t may transmit a set of downlink signals (e.g., T downlink signals) via a corresponding set of antennas 234 (e.g., T antennas) , shown as antennas 234a through 234t.

At the UE 120, a set of antennas 252 (shown as antennas 252a through 252r) may receive the downlink signals from the base station 110 and/or other base stations 110 and may provide a set of received signals (e.g., R received signals) to a set of modems 254 (e.g., R modems) , shown as modems 254a through 254r. For example, each received signal may be provided to a demodulator component (shown as DEMOD) of a modem 254. Each modem 254 may use a respective demodulator component to condition (e.g., filter, amplify, downconvert, and/or digitize) a received signal to obtain input samples. Each modem 254 may use a demodulator component to further process the input samples (e.g., for OFDM) to obtain received symbols. A MIMO detector 256 may obtain received symbols from the modems 254, may perform MIMO detection on the received symbols if applicable, and may provide detected symbols. A receive processor 258 may process (e.g., demodulate and decode) the detected symbols, may provide decoded data for the UE 120 to a data sink 260, and may provide decoded control information and system information to a controller/processor 280. The term “controller/processor” may refer to one or more controllers, one or more processors, or a combination thereof. A channel processor may determine a reference signal received power (RSRP) parameter, a received signal strength indicator (RSSI) parameter, a reference signal received quality (RSRQ) parameter, and/or a CQI parameter, among other examples. In some examples, one or more components of the UE 120 may be included in a housing 284.

The network controller 130 may include a communication unit 294, a controller/processor 290, and a memory 292. The network controller 130 may include, for example, one or more devices in a core network. The network controller 130 may communicate with the base station 110 via the communication unit 294.

One or more antennas (e.g., antennas 234a through 234t and/or antennas 252a through 252r) may include, or may be included within, one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, and/or one or more antenna arrays, among other examples. An antenna panel, an antenna group, a set of antenna elements, and/or an antenna array may include one or more antenna elements (within a single housing or multiple housings) , a set of coplanar antenna elements, a set of non-coplanar antenna elements, and/or one or more antenna elements coupled to one or more transmission and/or reception components, such as one or more components of Fig. 2.

On the uplink, at the UE 120, a transmit processor 264 may receive and process data from a data source 262 and control information (e.g., for reports that include RSRP, RSSI, RSRQ, and/or CQI) from the controller/processor 280. The transmit processor 264 may generate reference symbols for one or more reference signals. The symbols from the transmit processor 264 may be precoded by a TX MIMO processor 266 if applicable, further processed by the modems 254 (e.g., for DFT-s-OFDM or CP-OFDM) , and transmitted to the base station 110. In some examples, the modem 254 of the UE 120 may include a modulator and a demodulator. In some examples, the UE 120 includes a transceiver. The transceiver may include any combination of the antenna (s) 252, the modem (s) 254, the MIMO detector 256, the receive processor 258, the transmit processor 264, and/or the TX MIMO processor 266. The transceiver may be used by a processor (e.g., the controller/processor 280) and the memory 282 to perform aspects of any of the methods described herein (e.g., with reference to Figs. 4-8) .

At the base station 110, the uplink signals from UE 120 and/or other UEs may be received by the antennas 234, processed by the modem 232 (e.g., a demodulator component, shown as DEMOD, of the modem 232) , detected by a MIMO detector 236 if applicable, and further processed by a receive processor 238 to obtain decoded data and control information sent by the UE 120. The receive processor 238 may provide the decoded data to a data sink 239 and provide the decoded control information to the controller/processor 240. The base station 110 may include a communication unit 244 and may communicate with the network controller 130 via the communication unit 244. The base station 110 may include a scheduler 246 to schedule one or more UEs 120 for downlink and/or uplink communications. In some examples, the modem 232 of the base station 110 may include a modulator and a demodulator. In some examples, the base station 110 includes a transceiver. The transceiver may include any combination of the antenna (s) 234, the modem (s) 232, the MIMO detector 236, the receive processor 238, the transmit processor 220, and/or the TX MIMO processor 230. The transceiver may be used by a processor (e.g., the controller/processor 240) and the memory 242 to perform aspects of any of the methods described herein (e.g., with reference to Figs. 4-8) .

The controller/processor 240 of the base station 110, the controller/processor 280 of the UE 120, and/or any other component (s) of Fig. 2 may perform one or more techniques associated with CSI prediction based on multi-segment Doppler-domain spectrum distribution, as described in more detail elsewhere herein. For example, the controller/processor 240 of the base station 110, the controller/processor 280 of the UE 120, and/or any other component (s) of Fig. 2 may perform or direct operations of, for example, process 500 of Fig. 5, process 600 of Fig. 6, and/or other processes as described herein. The memory 242 and the memory 282 may store data and program codes for the base station 110 and the UE 120, respectively. In some examples, the memory 242 and/or the memory 282 may include a non-transitory computer-readable medium storing one or more instructions (e.g., code and/or program code) for wireless communication. For example, the one or more instructions, when executed (e.g., directly, or after compiling, converting, and/or interpreting) by one or more processors of the base station 110 and/or the UE 120, may cause the one or more processors, the UE 120, and/or the base station 110 to perform or direct operations of, for example, process 500 of Fig. 5, process 600 of Fig. 6, and/or other processes as described herein. In some examples, executing instructions may include running the instructions, converting the instructions, compiling the instructions, and/or interpreting the instructions, among other examples.

In some aspects, a UE includes means for calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE; means for determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices; and/or means for transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model. The means for the UE to perform operations described herein may include, for example, one or more of communication manager 140, antenna 252, modem 254, MIMO detector 256, receive processor 258, transmit processor 264, TX MIMO processor 266, controller/processor 280, or memory 282.

In some aspects, a network entity, such as a base station, includes means for receiving a communication indicating a set of parameters of a multi-segment time-domain compression model; and/or means for predicting CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model. The means for the base station to perform operations described herein may include, for example, one or more of communication manager 150, transmit processor 220, TX MIMO processor 230, modem 232, antenna 234, MIMO detector 236, receive processor 238, controller/processor 240, memory 242, or scheduler 246.

While blocks in Fig. 2 are illustrated as distinct components, the functions described above with respect to the blocks may be implemented in a single hardware, software, or combination component or in various combinations of components. For example, the functions described with respect to the transmit processor 264, the receive processor 258, and/or the TX MIMO processor 266 may be performed by or under the control of the controller/processor 280.

As indicated above, Fig. 2 is provided as an example. Other examples may differ from what is described with regard to Fig. 2.

Fig. 3 is a diagram illustrating an example 300 of an O-RAN architecture, in accordance with the present disclosure. As shown in Fig. 3, the O-RAN architecture may include a control unit (CU) 310 that communicates with a core network 320 via a backhaul link. Furthermore, the CU 310 may communicate with one or more DUs 330 via respective midhaul links. The DUs 330 may each communicate with one or more RUs 340 via respective fronthaul links, and the RUs 340 may each communicate with respective UEs 120 via radio frequency (RF) access links. The DUs 330 and the RUs 340 may also be referred to as O-RAN DUs (O-DUs) 330 and O-RAN RUs (O-RUs) 340, respectively.

In some aspects, the DUs 330 and the RUs 340 may be implemented according to a functional split architecture in which functionality of a base station 110 (e.g., an eNB or a gNB) is provided by a DU 330 and one or more RUs 340 that communicate over a fronthaul link. Accordingly, as described herein, a base station 110 may include a DU 330 and one or more RUs 340 that may be co-located or geographically distributed. In some aspects, the DU 330 and the associated RU (s) 340 may communicate via a fronthaul link to exchange real-time control plane information via a lower layer split (LLS) control plane (LLS-C) interface, to exchange non-real-time management information via an LLS management plane (LLS-M) interface, and/or to exchange user plane information via an LLS user plane (LLS-U) interface.

Accordingly, the DU 330 may correspond to a logical unit that includes one or more base station functions to control the operation of one or more RUs 340. For example, in some aspects, the DU 330 may host a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more high physical (PHY) layers (e.g., forward error correction (FEC) encoding and decoding, scrambling, and/or modulation and demodulation) based at least in part on a lower layer functional split. Higher layer control functions, such as a packet data convergence protocol (PDCP) , radio resource control (RRC) , and/or service data adaptation protocol (SDAP) , may be hosted by the CU 310. The RU (s) 340 controlled by a DU 330 may correspond to logical nodes that host RF processing functions and low-PHY layer functions (e.g., fast Fourier transform (FFT) , inverse FFT (iFFT) , digital beamforming, and/or physical random access channel (PRACH) extraction and filtering) based at least in part on the lower layer functional split. Accordingly, in an O-RAN architecture, the RU (s) 340 handle all over the air (OTA) communication with a UE 120, and real-time and non-real-time aspects of control and user plane communication with the RU (s) 340 are controlled by the corresponding DU 330, which enables the DU (s) 330 and the CU 310 to be implemented in a cloud-based RAN architecture.

In some aspects, the techniques and apparatuses for CSI prediction based on multi-segment Doppler-domain spectrum distribution as described herein can be implemented in an O-RAN architecture such as that illustrated in Fig. 3.

As indicated above, Fig. 3 is provided as an example. Other examples may differ from what is described with regard to Fig. 3.

A network entity, such as a base station, may transmit many beams to a UE. For example, the network entity may generate the beams using an antenna panel that generates beams at a spatial and/or phase displacement from each other. The network entity and the UE may select a set of beams that are to be used for communication between the network entity and the UE. For example, the set of beams transmitted from the network entity to the UE may be referred to herein as a communication link, a downlink, and/or the like. The communication link between the network entity and the UE may propagate in a medium and/or through various geometric paths, which are collectively referred to herein as a channel between the network entity and the UE.

In some aspects, the UE may select a set of beams for communication with the network entity. For example, the UE may select the set of beams based at least in part on the set of beams being associated with favorable characteristics (e.g., a satisfactory receive power, a satisfactory signal-to-interference-plus-noise ratio (SINR) value, etc. ) . The UE may generate a codeword that indicates the set of beams and parameters to be used for using a codebook based at least in part on performing channel estimation of the channel between the network entity and the UE.

One such codebook is the type-II codebook, prescribed in 5G/NR. The type-II codebook may use a two-stage procedure to generate the codeword: a first stage wherein the set of beams is selected for a wideband of the communication link (e.g., sometimes referred to herein as W1) , and a second stage wherein linear combination is performed, for a set of subbands, using the set of beams for each set of subbands. The codeword may be based at least in part on the linear combination, and may indicate the set of beams and/or respective amplitudes, phase coefficients, or the like. Thus, the UE may provide an indication of channel state at the UE and may request the set of beams to be used for the UE. The type-II codebook may provide more precise specification of the channel state than a type-I codebook, which may provide a predefined codeword-based approach to specifying selected beams. Thus, the type-II codebook may be referred to as a high-resolution codebook in comparison to the type-I codebook. The type-II codebook can, for example, improve multi-user multiple input multiple output (MU-MIMO) performance on the communication link.

For one type of type-II codebook (e.g., the codebook specified in Release 15 of the 3GPP standard for 5G/NR) , a precoder is based at least in part on a linear combination of discrete Fourier transform (DFT) beams. The linear combination may define the precoder W as W=W ₁W ₂ , wherein the spatial domain compression matrix

wherein

are L spatial domain basis vectors of dimension N ₁N ₂×1 (mapped to the two polarizations, so 2L in total) , P=2N ₁N ₂ indicates a number of dimensions (sometimes represented as D) , and the combination coefficient matrix W ₂ is composed of K=2Lυ linear combination coefficients, where υ indicates a total number of layers. Each column in W ₂ indicates the linear combination of complex coefficients (i.e., amplitude and phase) for one layer, wherein the amplitude coefficient is given by

for l=0, …, v-1, and

and

are the wideband and subband coefficients, respectively. The phase coefficient is given by

for l=0, …, v-1, and c _i is one of the 8 phase-shift keying (8PSK) or the quadrature phase-shift keying (QPSK) constellation points.

The UE may report the above values and/or other values associated with channel estimation using channel state information (CSI) feedback. CSI feedback for the type-II codebook may include two parts: a first part, sometimes referred to as CSI part I, and a second part, sometimes referred to as CSI part II. In some cases, the first part may have a smaller payload than the second part, or may have a fixed payload. For example, the first part may have a payload size of less than approximately 50 bits, whereas the second part may have a variable payload size that may be dependent on the first part. In some cases, the second part may have a payload size of approximately 100 bits to 600 bits, although other values may be used.

In some cases, the first part may identify one or more of: a rank indicator (RI) (e.g., 1 bit to indicate one layer υ=1 or two layers υ=2 when the configured maximum rank is 2) ; wideband and subband differential channel quality indicators (CQIs) , for which a total payload size may be dependent on the number of subbands (e.g., approximately 4 + 18 × 2 = 40 bits for 19 subbands) ; an indication of the number of non-zero wideband amplitude coefficients Q _l for each layer; and/or the like. In some cases, the second part may identify one or more of: wideband and/or subband precoding matrix indicators (PMIs) including a spatial basis vector selection indication; wideband and subband amplitude coefficients; subband phase coefficients; and/or the like.

In some cases, the type-II CSI feedback may use a compressed type-II precoder. This may reduce overhead of type-II CSI feedback. The compressed precoder may exploit the sparsity of the spatial domain and/or the frequency domain. For example, an example of a compressed type-II precoder W is given by

wherein the precoder matrix W has P=2N ₁N ₂ rows (representing the spatial domain and the number of ports) and N ₃ columns (wherein N ₃ is a frequency-domain compression unit of resource blocks or reporting subbands) . The W ₁ matrix, described above, is the spatial basis consisting of L beams per polarization group (hence a total of 2L beams) . The

matrix indicates all of the required linear combination complex coefficients (amplitude and co-phasing) , similarly to what is described above. The W _f matrix is composed of the basis vectors used to perform compression in frequency domain, W _f= [f ₀ f ₁…f _M-1] , where

are M size-N ₃×1 orthogonal DFT vectors for each spatial basis i=0, …, 2L-1. The above type-II CSI feedback may be referred to in some cases as enhanced type-II CSI feedback or modified type-II CSI feedback (e.g., enhanced relative to an approach that does not use basis vectors in the spatial and frequency domains to compress feedback size) .

The CSI feedback for this enhanced type-II CSI feedback may include a spatial domain basis vector selection that is similar to the approach described in connection with the type-II CSI feedback configuration. The CSI feedback may further include a frequency-domain (FD) basis subset selection (wherein M out of a total of N ₃ basis vectors are selected) . In some cases, common FD basis vectors for all of the 2L spatial beams may be used, which is referred to herein as Alternative 1. In these cases, M basis vectors are dynamically selected and reported. The value of M may be configured by the network or reported by the UE. In other cases, referred to herein as Alternative 2, independent FD basis vectors may be used for each spatial domain basis vector, with potentially different numbers and/or selections of FD basis vectors for each spatial domain basis vector. The total number of FD basis vectors across all of the 2L spatial beams may be configured.

The enhanced type-II CSI feedback may further include the FD coefficients (e.g., amplitude and phase) in

For Alternative 1 (the common FD basis vector subset selection) , the enhanced type-II CSI feedback may report only a subset K ₀＜K=2LM of the coefficients. For Alternative 2 (the independent basis subset selection) , the enhanced type-II CSI feedback may report

amplitude and phase coefficients, wherein M _i is the number of FD basis vectors associated with one spatial beam. A variety of quantization and reporting options may be used, two examples of which are provided below. As a first example, for each of the K or K ₀ FD coefficients, the enhanced type-II CSI feedback may use 3-bit amplitude and QPSK or 8PSK phase. As a second example, the enhanced type-II CSI feedback may report a 3-bit wideband amplitude for each beam or spatial domain basis vector, a 2-bit or 3-bit differential amplitude for each FD coefficient, and a QPSK or 8PSK phase bit.

In some scenarios, a UE may be moving at relatively high velocity relative to a network entity with which the UE is to communicate. In such a scenario, the channel between the network entity and the UE can also vary at a relatively high rate due to the velocity of the UE. In such a case, a time-domain codebook can represent the varying (over time instance n) precoder W as given by

Here, the coefficient matrix

is compressed into the Doppler-domain.

In some scenarios, such as when a UE is moving at a relatively high velocity such that the channel varies at a relatively high rate, the network entity may be configured to predict CSI (e.g., so that an upcoming channel condition can be anticipated) . In general, a CSI prediction technique may require a UE to report Doppler-domain basis vectors and coefficients so that the network entity can perform a CSI prediction in one or more upcoming time slots.

Conventional techniques for CSI prediction are based on an assumption that a Doppler-domain spectrum distribution is composed of either a single frequency band or multiple discrete frequency values. A single frequency band scenario is a scenario in which there is only one relatively large scattering cluster in the channel. A multiple discrete frequency value scenario is a scenario in which there are multiple relatively small scattering clusters in the channel. However, in practice, a Doppler-domain spectrum distribution can include multiple frequency bands (spectrum segments) , meaning that, in practice, there can be a scenario in which there are multiple relatively large scattering clusters in the channel. In such a scenario, the conventional techniques for CSI prediction are inadequate and, therefore, CSI predictions performed using the conventional techniques may not be sufficiently accurate, meaning that network performance (e.g., transmission throughput) may be negatively impacted.

Some aspects described herein provide techniques and apparatuses for CSI prediction based on multi-segment Doppler-domain spectrum distribution. In some aspects, a UE may calculate a plurality of coefficient matrices, each being calculated based at least in part on a respective reference signal received by the UE. The UE may then determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices, and may transmit a communication indicating the set of parameters of the multi-segment time-domain compression model. In some aspects, a network entity may receive the communication indicating the set of parameters of the multi-segment time-domain compression model, and may predict CSI associated with the UE based at least in part on the set of parameters of the multi-segment time-domain compression model. Additional details are provided below.

In some aspects, the techniques and apparatuses described herein can be utilized for CSI prediction in the presence of any type of Doppler-domain spectrum distributions (e.g., a single frequency band, multiple discrete frequency values, multiple frequency bands, or the like) . Thus, the techniques and apparatuses described herein can improve prediction accuracy and robustness, thereby increasing transmission throughput in, for example, a high-speed UE scenario.

Fig. 4 is a diagram illustrating an example 400 associated with CSI prediction based on multi-segment Doppler-domain spectrum distribution, in accordance with aspects of the present disclosure. As shown in Fig. 4, example 400 includes communication between a network entity 402 and a UE 404. In some aspects, the network entity 402 corresponds to a base station 110 or an apparatus 800, as described herein. In some aspects, the UE 404 corresponds to a UE 404 or an apparatus 700, as described herein. In some aspects, the network entity 402 and the UE 404 may be included in a wireless network, such as wireless network 100. In some aspects, the network entity 402 and the UE 404 may communicate via a wireless access link, which may include an uplink and a downlink.

As shown by reference 406, the network entity 402 may transmit, and the UE 404 may receive, a configuration associated with a multi-segment time-domain compression model. In some aspects, the multi-segment time-domain compression model is a model based at least in part on which the network entity 402 can perform a CSI prediction associated with the UE 404, where the CSI prediction is for a spatial-frequency coefficient matrix in multiple time occasions

In some aspects, the form of the multi-segment time-domain compression model for precoding matrix indicator (PMI) enhanced type-II codebook space-frequency coefficients

is

(sometimes referred to herein as Equation 1) , where ⊙ represents a per-element multiplication,

are elements in the same position (e.g., the ith row, the jth column) of

are time-domain basis vectors for the mth Doppler-domain spectrum segment with center frequency

and bandwidth

M≥1 is a quantity of Doppler-domain spectrum segments,

represents an impact of a deviation of spectrum segment center

T _slot is a time interval between two reference signal transmission occasions, and

is per-segment time-domain basis combination coefficients for the mth Doppler-domain spectrum segment. In some aspects, a type of d _m, k can be a Slepian basis or an FFT basis (e.g., as dictated by a relevant standard document, as configured by the network entity 402, or the like) . In some aspects, when Slepian basis with bandwidth

is adopted,

are the K dominant eigenvectors of matrix D _m= (d _ij) _i, j=1～N, where

K≤N. In some aspects, when FFT basis is adopted,

where l _k is the index of the kth selected FFT basis vector, k=1～K. In some examples,

are determined based on a least-square criterion.

In some aspects, the configuration associated with the multi-segment time-domain compression model indicates a quantity of reference signal transmission occasions N, a quantity of CSI prediction occasions

amaximum quantity of Doppler-domain spectrum segments M _max, a type of time-domain basis for a Doppler-domain spectrum segment (e.g., FFT, Slepian, or the like) , or a quantity of time-domain basis vectors K. In some aspects, the network entity 402 may transmit, and the UE 404 may receive, the configuration associated with the multi-segment time-domain compression model together with a configuration associated with an enhanced type-II codebook.

As shown by

references

408 and 410, the UE 404 may receive a reference signal at a given transmission occasion and may perform channel estimation based at least in part on the reference signal received at the given transmission occasion. For example, as indicated by reference 408-1, the network entity 402 may transmit, and the UE 404 may receive, a reference signal (e.g., a CSI reference signal (CSI-RS) , a tracking reference signal (TRS) , or the like) at a first transmission occasion. As shown by reference 410-1, the UE 404 may perform channel estimation based at least in part on the reference signal received at the first transmission occasion. As shown by references 408-N and 410-N, the UE 404 may repeat these operations for N -1 additional reference signals. Here, N corresponds to the quantity of reference signal transmission occasions indicated in the configuration for the multi-segment time-domain compression model.

As shown by reference 412, the UE 404 may determine a set of parameters of the multi-segment time-domain compression model. In some aspects, the UE 404 may determine the set of parameters based at least in part on a plurality of coefficient matrices calculated by the UE 404. For example, in some aspects, the UE 404 may calculate a plurality of coefficient matrices, where each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal. As a particular example, the UE 404 may calculate a first coefficient matrix based at least in part on the reference signal received at the first transmission occasion (e.g., based at least in part on channel estimation performed using the first reference signal) , may calculate an N ^th coefficient matrix based at least in part on the reference signal received at the N ^th transmission occasion (e.g., based at least in part on channel estimation performed using the N ^th reference signal) , and so on. The UE 404 may then determine the set of parameters for the multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices.

In some aspects, to calculate the plurality of coefficient matrices, the UE 404 may calculate

for each reference signal transmission occasion. In some aspects, after calculating

the UE 404 may construct a vector x= [x ₁, x ₂, …, x _N] ^T for a given element in

In some aspects, the UE 404 may then determine the parameters of each Doppler-domain spectrum segment in the multi-segment time-domain compression model

m=1, …, M≤M _max based at least in part on the vector x. That is, in some aspects, the UE 404 may construct a plurality of vectors x, each corresponding to a particular element in

and may determine parameters of a plurality of Doppler-domain spectrum segments

m=1, …, M≤M _max based at least in part on the plurality of vectors x. For example, the UE 404 may apply an FFT transform to the vector x, which generates a Doppler-domain spectrum y= [y ₁, y ₂, …, y _N] ^T. From a power distribution of y, the UE 404 can obtain a quantity of Doppler-domain spectrum segments (denoted as M) and values of

and can then construct an FFT basis or Slepian basis matrix

where

Here, by denoting

γ _m= [γ _m, 1, γ _m, 1, …, γ _m, K] ^T, and

Equation 1 noted above can be represented as

Thus, the UE 404 can derive basis vector coefficients

based on

Notably, to ensure validity, the condition N≥MK should be satisfied (e.g., if N=10, K=2, and M=2, then

has size N× (MK) =10×4, and γ _all has size (MK) ×1=4×1) .

Additionally, or alternatively, in some aspects, the UE 404 may predict the precoding matrixes at time occasions

denoted as

based on the received reference signal at time occasions 1～ N. Then, the UE 404 may concatenate the calculated

and the predicted

as

and construct a vector

for a given element in

Then, similar to the operation on x, the UE 404 can derive basis vector coefficients

for

Additionally, or alternatively, in some aspects, the UE 404 may construct a vector

for a given element in

for

In some aspects, which of x,

is used to calculate

may be dictated by a relevant wireless communication standard or may be configured by the network entity 402.

In this way, the UE 404 may determine the set of parameters for the multi-segment time-domain compression model. In some aspects, the set of parameters may include the quantity of Doppler-domain spectrum segments M, a center frequency of each Doppler-domain spectrum segment

abandwidth of each Doppler-domain spectrum segment

, an index of a selected FFT basis associated with a time-domain basis vector

(e.g., when FFT basis is used) , or an indication of a per-segment time-domain basis combination coefficient for each Doppler-domain spectrum segment

m=1～M (1 to M) . Notably, in some aspects, one or more parameters of the set of parameters can be common to multiple elements of

which may reduce overhead associated with reporting the set of parameters. Additionally, or alternatively, one or more parameters of the set of parameters can be specific to a particular element of

which may provide improved performance.

As shown by reference 414, the UE 404 may transmit, and the network entity 402 may receive, a communication indicating the set of parameters of the multi-segment time-domain compression model.

As shown by reference 416, the network entity 402 may predict CSI associated with the UE 404 based at least in part on the set of parameters of the multi-segment time-domain compression model. For example, in some aspects, the network entity 402 may construct a plurality of predicted vectors based at least in part on the set of parameters. Here, each predicted vector of the plurality of predicted vectors corresponds to a particular element in a plurality of predicted coefficient matrices. The network entity 402 may then predict the CSI based at least in part on the plurality of predicted vectors.

In some aspects, based at least in part on the set of parameters, the network entity 402 may restore the time-domain compression model, and predict the CSI in the slots

More particularly, the network entity 402 may predict the CSI values

for each element in

based on the set of parameters for the multi-segment time-domain compression model as indicated by the UE 404. For example, if

is derived based on x or

the network entity 402 may calculate

with

being the last

elements of

In another example, if

is derived based on

the network entity 402 may calculate

The network entity 402 may repeat these operations for each element in

In some aspects, a spatial basis matrix W ₁ and frequency basis matrix

(i.e., the other matrices utilized in determining the precoder) can be determined based at least in part on a reported value for slot N.

In this way, a CSI prediction based on multi-segment Doppler-domain spectrum distribution can be performed. As noted above, the techniques and apparatuses described herein can be utilized for CSI prediction in the presence of any type of Doppler-domain spectrum distributions (e.g., a single frequency band, multiple discrete frequency values, multiple frequency bands, or the like) . For example, when M=1, the multi-segment time-domain compression model simplifies to Doppler-domain spectrum with a single frequency band. As another example, when K=1, the multi-segment time-domain compression model simplifies to Doppler-domain spectrum with multiple discrete frequency values. Thus, the techniques and apparatuses described herein can improve prediction accuracy and robustness in the presence of any type of Doppler-domain spectrum distribution, thereby enabling transmission throughput in, for example, a high-speed UE scenario.

As indicated above, Fig. 4 is provided as an example. Other examples may differ from what is described with respect to Fig. 4.

Fig. 5 is a diagram illustrating an example process 500 performed, for example, by a UE, in accordance with the present disclosure. Example process 500 is an example where the UE (e.g., UE 120) performs operations associated with CSI prediction based on multi-segment doppler-domain spectrum distribution.

As shown in Fig. 5, in some aspects, process 500 may include calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE (block 510) . For example, the UE (e.g., using communication manager 140 and/or matrix calculation component 708, depicted in Fig. 7) may calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE, as described above.

As further shown in Fig. 5, in some aspects, process 500 may include determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices (block 520) . For example, the UE (e.g., using communication manager 140 and/or parameter determination component 710, depicted in Fig. 7) may determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices, as described above.

As further shown in Fig. 5, in some aspects, process 500 may include transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model (block 530) . For example, the UE (e.g., using communication manager 140 and/or transmission component 704, depicted in Fig. 7) may transmit a communication indicating the set of parameters of the multi-segment time-domain compression model, as described above.

Process 500 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, process 500 includes receiving a configuration associated with the multi-segment time-domain compression model, wherein the set of parameters is determined based at least in part on the configuration.

In a second aspect, alone or in combination with the first aspect, the configuration indicates at least one of a quantity of reference signal transmission occasions, a quantity of CSI prediction occasions, a maximum quantity of Doppler-domain spectrum segments, a type of time-domain basis for a Doppler-domain spectrum segment, or a quantity of time-domain basis vectors.

In a third aspect, alone or in combination with one or more of the first and second aspects, determining the set of parameters comprises constructing a plurality of vectors, each vector of the plurality of vectors corresponding to a particular element in the plurality of coefficient matrices, and determining parameters of a plurality of Doppler-domain spectrum segments based at least in part on the plurality of vectors.

In a fourth aspect, alone or in combination with one or more of the first through third aspects, the set of parameters includes at least one of a quantity of Doppler-domain spectrum segments, a center frequency of a Doppler-domain spectrum segment, a bandwidth of the Doppler-domain spectrum segment, an index of a selected FFT basis associated with a time-domain basis vector, or an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.

In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, one or more parameters of the set of parameters are common to multiple elements of the plurality of coefficient matrices.

In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, one or more parameters of the set of parameters are specific to a particular element of the plurality of coefficient matrices.

Although Fig. 5 shows example blocks of process 500, in some aspects, process 500 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 5. Additionally, or alternatively, two or more of the blocks of process 500 may be performed in parallel.

Fig. 6 is a diagram illustrating an example process 600 performed, for example, by a network entity, in accordance with the present disclosure. Example process 600 is an example where the network entity (e.g., base station 110) performs operations associated with CSI prediction based on multi-segment doppler-domain spectrum distribution.

As shown in Fig. 6, in some aspects, process 600 may include receiving a communication indicating a set of parameters of a multi-segment time-domain compression model (block 610) . For example, the network entity (e.g., using communication manager 150 and/or reception component 802, depicted in Fig. 8) may receive a communication indicating a set of parameters of a multi-segment time-domain compression model, as described above.

As further shown in Fig. 6, in some aspects, process 600 may include predicting CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model (block 620) . For example, the network entity (e.g., using communication manager 150 and/or CSI prediction component 808, depicted in Fig. 8) may predict CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model, as described above.

Process 600 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, process 600 includes transmitting a configuration associated with the multi-segment time-domain compression model.

In a third aspect, alone or in combination with one or more of the first and second aspects, predicting the CSI comprises constructing a plurality of predicted vectors based at least in part on the set of parameters, each predicted vector of the plurality of predicted vectors corresponding to a particular element in a plurality of predicted coefficient matrices, and predicting the CSI based at least in part on the plurality of predicted vectors.

In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, one or more parameters of the set of parameters are common to multiple elements of a plurality of coefficient matrices.

In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, one or more parameters of the set of parameters are specific to a particular element of a plurality of coefficient matrices.

Although Fig. 6 shows example blocks of process 600, in some aspects, process 600 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 6. Additionally, or alternatively, two or more of the blocks of process 600 may be performed in parallel.

Fig. 7 is a diagram of an example apparatus 700 for wireless communication. The apparatus 700 may be a UE, or a UE may include the apparatus 700. In some aspects, the apparatus 700 includes a reception component 702 and a transmission component 704, which may be in communication with one another (for example, via one or more buses and/or one or more other components) . As shown, the apparatus 700 may communicate with another apparatus 706 (such as a UE, a base station, or another wireless communication device) using the reception component 702 and the transmission component 704. As further shown, the apparatus 700 may include the communication manager 140. The communication manager 140 may include one or more of a matrix calculation component 708 or a parameter determination component 710, among other examples.

In some aspects, the apparatus 700 may be configured to perform one or more operations described herein in connection with Fig. 4. Additionally, or alternatively, the apparatus 700 may be configured to perform one or more processes described herein, such as process 500 of Fig. 5. In some aspects, the apparatus 700 and/or one or more components shown in Fig. 7 may include one or more components of the UE described in connection with Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 7 may be implemented within one or more components described in connection with Fig. 2. Additionally, or alternatively, one or more components of the set of components may be implemented at least in part as software stored in a memory. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by a controller or a processor to perform the functions or operations of the component.

The reception component 702 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 706. The reception component 702 may provide received communications to one or more other components of the apparatus 700. In some aspects, the reception component 702 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, de-mapping, equalization, interference cancellation, or decoding, among other examples) , and may provide the processed signals to the one or more other components of the apparatus 700. In some aspects, the reception component 702 may include one or more antennas, a modem, a demodulator, a MIMO detector, a receive processor, a controller/processor, a memory, or a combination thereof, of the UE described in connection with Fig. 2.

The transmission component 704 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 706. In some aspects, one or more other components of the apparatus 700 may generate communications and may provide the generated communications to the transmission component 704 for transmission to the apparatus 706. In some aspects, the transmission component 704 may perform signal processing on the generated communications (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, among other examples) , and may transmit the processed signals to the apparatus 706. In some aspects, the transmission component 704 may include one or more antennas, a modem, a modulator, a transmit MIMO processor, a transmit processor, a controller/processor, a memory, or a combination thereof, of the UE described in connection with Fig. 2. In some aspects, the transmission component 704 may be co-located with the reception component 702 in a transceiver.

The matrix calculation component 708 may calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE. The parameter determination component 710 may determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices. The transmission component 704 may transmit a communication indicating the set of parameters of the multi-segment time-domain compression model.

The reception component 702 may receive a configuration associated with the multi-segment time-domain compression model, wherein the set of parameters is determined based at least in part on the configuration.

The number and arrangement of components shown in Fig. 7 are provided as an example. In practice, there may be additional components, fewer components, different components, or differently arranged components than those shown in Fig. 7. Furthermore, two or more components shown in Fig. 7 may be implemented within a single component, or a single component shown in Fig. 7 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 7 may perform one or more functions described as being performed by another set of components shown in Fig. 7.

Fig. 8 is a diagram of an example apparatus 800 for wireless communication. The apparatus 800 may be a network entity, or a network entity may include the apparatus 800. In some aspects, the apparatus 800 includes a reception component 802 and a transmission component 804, which may be in communication with one another (for example, via one or more buses and/or one or more other components) . As shown, the apparatus 800 may communicate with another apparatus 806 (such as a UE, a base station, or another wireless communication device) using the reception component 802 and the transmission component 804. As further shown, the apparatus 800 may include the communication manager 150. The communication manager 150 may include a CSI prediction component 808, among other examples.

In some aspects, the apparatus 800 may be configured to perform one or more operations described herein in connection with Fig. 4. Additionally, or alternatively, the apparatus 800 may be configured to perform one or more processes described herein, such as process 600 of Fig. 6. In some aspects, the apparatus 800 and/or one or more components shown in Fig. 8 may include one or more components of the network entity described in connection with Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 8 may be implemented within one or more components described in connection with Fig. 2. Additionally, or alternatively, one or more components of the set of components may be implemented at least in part as software stored in a memory. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by a controller or a processor to perform the functions or operations of the component.

The reception component 802 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 806. The reception component 802 may provide received communications to one or more other components of the apparatus 800. In some aspects, the reception component 802 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, de-mapping, equalization, interference cancellation, or decoding, among other examples) , and may provide the processed signals to the one or more other components of the apparatus 800. In some aspects, the reception component 802 may include one or more antennas, a modem, a demodulator, a MIMO detector, a receive processor, a controller/processor, a memory, or a combination thereof, of the network entity described in connection with Fig. 2.

The transmission component 804 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 806. In some aspects, one or more other components of the apparatus 800 may generate communications and may provide the generated communications to the transmission component 804 for transmission to the apparatus 806. In some aspects, the transmission component 804 may perform signal processing on the generated communications (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, among other examples) , and may transmit the processed signals to the apparatus 806. In some aspects, the transmission component 804 may include one or more antennas, a modem, a modulator, a transmit MIMO processor, a transmit processor, a controller/processor, a memory, or a combination thereof, of the network entity described in connection with Fig. 2. In some aspects, the transmission component 804 may be co-located with the reception component 802 in a transceiver.

The reception component 802 may receive a communication indicating a set of parameters of a multi-segment time-domain compression model. The CSI prediction component 808 may predict CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

The transmission component 804 may transmit a configuration associated with the multi-segment time-domain compression model.

The number and arrangement of components shown in Fig. 8 are provided as an example. In practice, there may be additional components, fewer components, different components, or differently arranged components than those shown in Fig. 8. Furthermore, two or more components shown in Fig. 8 may be implemented within a single component, or a single component shown in Fig. 8 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 8 may perform one or more functions described as being performed by another set of components shown in Fig. 8.

The following provides an overview of some Aspects of the present disclosure:

Aspect 1: A method of wireless communication performed by a UE, comprising: calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE; determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices; and transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model.

Aspect 2: The method of Aspect 1, further comprising receiving a configuration associated with the multi-segment time-domain compression model, wherein the set of parameters is determined based at least in part on the configuration.

Aspect 3: The method of Aspect 2, wherein the configuration indicates at least one of: a quantity of reference signal transmission occasions, a quantity of CSI prediction occasions, a maximum quantity of Doppler-domain spectrum segments, a type of time-domain basis for a Doppler-domain spectrum segment, or a quantity of time-domain basis vectors.

Aspect 4: The method of any of Aspects 1-3, wherein determining the set of parameters comprises: constructing a plurality of vectors, each vector of the plurality of vectors corresponding to a particular element in the plurality of coefficient matrices, and determining parameters of a plurality of Doppler-domain spectrum segments based at least in part on the plurality of vectors.

Aspect 5: The method of any of Aspects 1-4, wherein the set of parameters includes at least one of: a quantity of Doppler-domain spectrum segments, a center frequency of a Doppler-domain spectrum segment, a bandwidth of the Doppler-domain spectrum segment, an index of a selected FFT basis associated with a time-domain basis vector, or an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.

Aspect 6: The method of any of Aspects 1-5, wherein one or more parameters of the set of parameters are common to multiple elements of the plurality of coefficient matrices.

Aspect 7: The method of any of Aspects 1-6, wherein one or more parameters of the set of parameters are specific to a particular element of the plurality of coefficient matrices.

Aspect 8: A method of wireless communication performed by a base station, comprising: receiving a communication indicating a set of parameters of a multi-segment time-domain compression model; and predicting CSI associated with a UE based at least in part on the set of parameters of the multi-segment time-domain compression model.

Aspect 9: The method of Aspect 8, further comprising transmitting a configuration associated with the multi-segment time-domain compression model.

Aspect 10: The method of Aspect 9, wherein the configuration indicates at least one of: a quantity of reference signal transmission occasions, a quantity of CSI prediction occasions, a maximum quantity of Doppler-domain spectrum segments, a type of time-domain basis for a Doppler-domain spectrum segment, or a quantity of time-domain basis vectors.

Aspect 11: The method of any of Aspects 8-10, wherein predicting the CSI comprises: constructing a plurality of predicted vectors based at least in part on the set of parameters, each predicted vector of the plurality of predicted vectors corresponding to a particular element in a plurality of predicted coefficient matrices, and predicting the CSI based at least in part on the plurality of predicted vectors.

Aspect 12: The method of any of Aspects 8-11, wherein the set of parameters includes at least one of: a quantity of Doppler-domain spectrum segments, a center frequency of a Doppler-domain spectrum segment, a bandwidth of the Doppler-domain spectrum segment, an index of a selected FFT basis associated with a time-domain basis vector, or an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.

Aspect 13: The method of any of Aspects 8-12, wherein one or more parameters of the set of parameters are common to multiple elements of a plurality of coefficient matrices.

Aspect 14: The method of any of Aspects 8-13, wherein one or more parameters of the set of parameters are specific to a particular element of a plurality of coefficient matrices.

Aspect 15: An apparatus for wireless communication at a device, comprising a processor; memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform the method of one or more of Aspects 1-7.

Aspect 16: A device for wireless communication, comprising a memory and one or more processors coupled to the memory, the one or more processors configured to perform the method of one or more of Aspects 1-7.

Aspect 17: An apparatus for wireless communication, comprising at least one means for performing the method of one or more of Aspects 1-7.

Aspect 18: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform the method of one or more of Aspects 1-7.

Aspect 19: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method of one or more of Aspects 1-7.

Aspect 20: An apparatus for wireless communication at a device, comprising a processor; memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform the method of one or more of Aspects 8-14.

Aspect 21: A device for wireless communication, comprising a memory and one or more processors coupled to the memory, the one or more processors configured to perform the method of one or more of Aspects 8-14.

Aspect 22: An apparatus for wireless communication, comprising at least one means for performing the method of one or more of Aspects 8-14.

Aspect 23: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform the method of one or more of Aspects 8-14.

Aspect 24: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method of one or more of Aspects 8-14.

The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the aspects to the precise forms disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the aspects.

As used herein, the term “component” is intended to be broadly construed as hardware and/or a combination of hardware and software. “Software” shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, and/or functions, among other examples, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. As used herein, a “processor” is implemented in hardware and/or a combination of hardware and software. It will be apparent that systems and/or methods described herein may be implemented in different forms of hardware and/or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and/or methods is not limiting of the aspects. Thus, the operation and behavior of the systems and/or methods are described herein without reference to specific software code, since those skilled in the art will understand that software and hardware can be designed to implement the systems and/or methods based, at least in part, on the description herein.

As used herein, “satisfying a threshold” may, depending on the context, refer to a value being greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, not equal to the threshold, or the like.

Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. Many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. The disclosure of various aspects includes each dependent claim in combination with every other claim in the claim set. As used herein, a phrase referring to “at least one of” a list of items refers to any combination of those items, including single members. As an example, “at least one of: a, b, or c” is intended to cover a, b, c, a + b, a + c, b + c, and a + b + c, as well as any combination with multiples of the same element (e.g., a + a, a + a + a, a + a + b, a + a + c, a + b + b, a + c + c, b + b, b + b + b, b + b + c, c + c, and c + c + c, or any other ordering of a, b, and c) .

No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more. ” Further, as used herein, the article “the” is intended to include one or more items referenced in connection with the article “the” and may be used interchangeably with “the one or more. ” Furthermore, as used herein, the terms “set” and “group” are intended to include one or more items and may be used interchangeably with “one or more. ” Where only one item is intended, the phrase “only one” or similar language is used. Also, as used herein, the terms “has, ” “have, ” “having, ” or the like are intended to be open-ended terms that do not limit an element that they modify (e.g., an element “having” A may also have B) . Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and/or, ” unless explicitly stated otherwise (e.g., if used in combination with “either” or “only one of” ) .

Claims

A user equipment (UE) for wireless communication, comprising:

a memory; and

one or more processors, coupled to the memory, configured to:

calculate a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE;

determine a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices; and

transmit a communication indicating the set of parameters of the multi-segment time-domain compression model.
The UE of claim 1, wherein the one or more processors are further configured to receive a configuration associated with the multi-segment time-domain compression model, wherein the set of parameters is determined based at least in part on the configuration.
The UE of claim 2, wherein the configuration indicates at least one of:

a quantity of reference signal transmission occasions,

a quantity of channel state information (CSI) prediction occasions,

a maximum quantity of Doppler-domain spectrum segments,

a type of time-domain basis for a Doppler-domain spectrum segment, or

a quantity of time-domain basis vectors.
The UE of any of claims 1-3, wherein the one or more processors, to determine the set of parameters, are configured to:

construct a plurality of vectors, each vector of the plurality of vectors corresponding to a particular element in the plurality of coefficient matrices, and

determine parameters of a plurality of Doppler-domain spectrum segments based at least in part on the plurality of vectors.
The UE of any of claims 1-4, wherein the set of parameters includes at least one of:

a quantity of Doppler-domain spectrum segments,

a center frequency of a Doppler-domain spectrum segment,

a bandwidth of the Doppler-domain spectrum segment,

an index of a selected fast Fourier transform (FFT) basis associated with a time-domain basis vector, or

an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.
The UE of any of claims 1-5, wherein one or more parameters of the set of parameters are common to multiple elements of the plurality of coefficient matrices.
The UE of any of claims 1-6, wherein one or more parameters of the set of parameters are specific to a particular element of the plurality of coefficient matrices.
A network entity for wireless communication, comprising:

a memory; and

one or more processors, coupled to the memory, configured to:

receive a communication indicating a set of parameters of a multi-segment time-domain compression model; and

predict channel state information (CSI) associated with a user equipment (UE) based at least in part on the set of parameters of the multi-segment time-domain compression model.
The network entity of claim 8, wherein the one or more processors are further configured to transmit a configuration associated with the multi-segment time-domain compression model.
The network entity of claim 9, wherein the configuration indicates at least one of:

a quantity of reference signal transmission occasions,

a quantity of channel state information (CSI) prediction occasions,

a maximum quantity of Doppler-domain spectrum segments,

a type of time-domain basis for a Doppler-domain spectrum segment, or

a quantity of time-domain basis vectors.
The network entity of any of claims 8-10, wherein the one or more processors, to predict the CSI, are configured to:

construct a plurality of predicted vectors based at least in part on the set of parameters, each predicted vector of the plurality of predicted vectors corresponding to a particular element in a plurality of predicted coefficient matrices, and

predict the CSI based at least in part on the plurality of predicted vectors.
The network entity of any of claims 8-11, wherein the set of parameters includes at least one of:

a quantity of Doppler-domain spectrum segments,

a center frequency of a Doppler-domain spectrum segment,

a bandwidth of the Doppler-domain spectrum segment,

an index of a selected fast Fourier transform (FFT) basis associated with a time-domain basis vector, or

an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.
The network entity of any of claims 8-12, wherein one or more parameters of the set of parameters are common to multiple elements of a plurality of coefficient matrices.
The network entity of any of claims 8-13, wherein one or more parameters of the set of parameters are specific to a particular element of a plurality of coefficient matrices.
A method of wireless communication performed by a user equipment (UE) , comprising:

calculating a plurality of coefficient matrices, wherein each coefficient matrix of the plurality of coefficient matrices is calculated based at least in part on a respective reference signal from a plurality of reference signals received by the UE;

determining a set of parameters of a multi-segment time-domain compression model based at least in part on the plurality of coefficient matrices; and

transmitting a communication indicating the set of parameters of the multi-segment time-domain compression model.
The method of claim 15, further comprising receiving a configuration associated with the multi-segment time-domain compression model, wherein the set of parameters is determined based at least in part on the configuration.
The method of claim 16, wherein the configuration indicates at least one of:

a quantity of reference signal transmission occasions,

a quantity of channel state information (CSI) prediction occasions,

a maximum quantity of Doppler-domain spectrum segments,

a type of time-domain basis for a Doppler-domain spectrum segment,

or

a quantity of time-domain basis vectors.
The method of any of claims 15-17, wherein determining the set of parameters comprises:

constructing a plurality of vectors, each vector of the plurality of vectors corresponding to a particular element in the plurality of coefficient matrices, and

determining parameters of a plurality of Doppler-domain spectrum segments based at least in part on the plurality of vectors.
The method of any of claims 15-18, wherein the set of parameters includes at least one of:

a quantity of Doppler-domain spectrum segments,

a center frequency of a Doppler-domain spectrum segment,

a bandwidth of the Doppler-domain spectrum segment,

an index of a selected fast Fourier transform (FFT) basis associated with a time-domain basis vector, or

an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.
The method of any of claims 15-19, wherein one or more parameters of the set of parameters are common to multiple elements of the plurality of coefficient matrices.
The method of any of claims 15-20, wherein one or more parameters of the set of parameters are specific to a particular element of the plurality of coefficient matrices.
A method of wireless communication performed by a network entity, comprising:

receiving a communication indicating a set of parameters of a multi-segment time-domain compression model; and

predicting channel state information (CSI) associated with a user equipment (UE) based at least in part on the set of parameters of the multi-segment time-domain compression model.
The method of claim 22, further comprising transmitting a configuration associated with the multi-segment time-domain compression model.
The method of claim 23, wherein the configuration indicates at least one of:

a quantity of reference signal transmission occasions,

a quantity of channel state information (CSI) prediction occasions,

a maximum quantity of Doppler-domain spectrum segments,

a type of time-domain basis for a Doppler-domain spectrum segment,

or

a quantity of time-domain basis vectors.
The method of any of claims 22-24, wherein predicting the CSI comprises:

constructing a plurality of predicted vectors based at least in part on the set of parameters, each predicted vector of the plurality of predicted vectors corresponding to a particular element in a plurality of predicted coefficient matrices, and

predicting the CSI based at least in part on the plurality of predicted vectors.
The method of any of claims 22-25, wherein the set of parameters includes at least one of:

a quantity of Doppler-domain spectrum segments,

a center frequency of a Doppler-domain spectrum segment,

a bandwidth of the Doppler-domain spectrum segment,

an index of a selected fast Fourier transform (FFT) basis associated with a time-domain basis vector, or

an indication of a per-segment time-domain basis combination coefficient for a Doppler-domain spectrum segment.
The method of any of claims 22-26, wherein one or more parameters of the set of parameters are common to multiple elements of a plurality of coefficient matrices.
The method of any of claims 22-27, wherein one or more parameters of the set of parameters are specific to a particular element of a plurality of coefficient matrices.