Prediction for channel state information reporting
By enabling user equipment to predict channel characteristics and identify preferred reference signals for single-step CSI reporting, the method addresses inefficiencies in beam management, reducing overhead and improving throughput in wireless communication systems.
Patent Information
- Application Number
- PCT/CN2024/104642
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-07-10
- Publication Date
- 2026-01-15
AI Technical Summary
Existing wireless communication systems face inefficiencies in channel state information reporting due to prediction errors in beam management, leading to increased overhead consumption and throughput interruptions, particularly when using artificial intelligence/machine learning for beam prediction.
Implementing a method where user equipment predicts channel characteristics and identifies preferred reference signals using machine learning, allowing for single-step CSI reporting that includes measurement-based CQIs, reducing the need for network-side close-loop link adaptation and conserving signaling resources.
This approach reduces downlink control information overhead and latency, conserves signaling resources, and increases throughput by focusing on measurement-based CQIs for predicted beams, addressing the inefficiencies in beam management.
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Figure CN2024104642_15012026_PF_FP_ABST
Abstract
Description
PREDICTION FOR CHANNEL STATE INFORMATION REPORTING
[0001] FIELD OF THE DISCLOSURE
[0002] Aspects of the present disclosure generally relate to wireless communication, and specifically relate to techniques, apparatuses, and methods for prediction for channel state information reporting.
[0003] DESCRIPTION OF RELATED ART
[0004] Wireless communication systems are widely deployed to provide various services that may include carrying voice, text, messaging, video, data, and / or other traffic. The services may include unicast, multicast, and / or broadcast services, among other examples. Typical wireless communication systems may employ multiple-access radio access technologies (RATs) capable of supporting communication with multiple users by sharing available system resources (for example, time domain resources, frequency domain resources, spatial domain resources, and / or device transmit power, among other examples) . Examples of such multiple-access RATs 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, and time division synchronous code division multiple access (TD-SCDMA) systems.
[0005] The above multiple-access RATs have been adopted in various telecommunication standards to provide common protocols that enable different wireless communication devices to communicate on a municipal, national, regional, or global level. An example telecommunication standard is New Radio (NR) . NR, which may also be referred to as 5G, is part of a continuous mobile broadband evolution promulgated by the Third Generation Partnership Project (3GPP) . NR (and other mobile broadband evolutions beyond NR) may be designed to better support Internet of things (IoT) and reduced capability device deployments, industrial connectivity, millimeter wave (mmWave) expansion, licensed and unlicensed spectrum access, non-terrestrial network (NTN) deployment, sidelink and other device-to-device direct communication technologies (for example, cellular vehicle-to-everything (CV2X) communication) , massive multiple-input multiple-output (MIMO) , disaggregated network architectures and network topology expansions, multiple-subscriber implementations, high-precision positioning, and / or radio frequency (RF) sensing, among other examples. As the demand for mobile broadband access continues to increase, further improvements in NR may be implemented, and other radio access technologies such as 6G may be introduced, to further advance mobile broadband evolution.SUMMARY
[0006] Some aspects described herein relate to a method of wireless communication performed by a user equipment (UE) . The method may include receiving scheduling information for a channel state information (CSI) report. The method may include predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The method may include identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The method may include transmitting the CSI report with a set of channel quality indicators (CQIs) for the preferred set of reference signals.
[0007] Some aspects described herein relate to a method of wireless communication performed by a network entity. The method may include transmitting a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The method may include transmitting scheduling information for a CSI report. The method may include receiving the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources.
[0008] Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be individually or collectively configured to cause the UE to receive scheduling information for a CSI report. The one or more processors may be individually or collectively configured to cause the UE to predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The one or more processors may be individually or collectively configured to cause the UE to identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The one or more processors may be individually or collectively configured to cause the UE to transmit the CSI report with a set of CQIs for the preferred set of reference signals.
[0009] Some aspects described herein relate to an apparatus for wireless communication at a network entity. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be individually or collectively configured to cause the network entity to transmit a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The one or more processors may be individually or collectively configured to cause the network entity to transmit scheduling information for a CSI report. The one or more processors may be individually or collectively configured to cause the network entity to receive the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources.
[0010] Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a user equipment (UE) . The set of instructions, when executed by one or more processors of the UE, may cause the UE to receive scheduling information for a CSI report. The set of instructions, when executed by one or more processors of the UE, may cause the UE to predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The set of instructions, when executed by one or more processors of the UE, may cause the UE to identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit the CSI report with a set of CQIs for the preferred set of reference signals.
[0011] 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 transmit a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The set of instructions, when executed by one or more processors of the network entity, may cause the network entity to transmit scheduling information for a CSI report. The set of instructions, when executed by one or more processors of the network entity, may cause the network entity to receive the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources.
[0012] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for receiving scheduling information for a CSI report. The apparatus may include means for predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The apparatus may include means for identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The apparatus may include means for transmitting the CSI report with a set of CQIs for the preferred set of reference signals.
[0013] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for transmitting a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The apparatus may include means for transmitting scheduling information for a CSI report. The apparatus may include means for receiving the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources.
[0014] Aspects of the present disclosure may generally be implemented by or as a method, apparatus, system, computer program product, non-transitory computer-readable medium, user equipment, base station, network node, network entity, wireless communication device, and / or processing system as substantially described with reference to, and as illustrated by, the specification and accompanying drawings.
[0015] The foregoing paragraphs of this section have broadly summarized some aspects of the present disclosure. These and additional aspects and associated advantages will be described hereinafter. The disclosed aspects may be used as a basis for modifying or designing other aspects for carrying out the same or similar purposes of the present disclosure. Such equivalent aspects do not depart from the scope of the appended claims. Characteristics of the aspects 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 drawings.BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The appended drawings illustrate some aspects of the present disclosure, but are not limiting of the scope of the present disclosure because the description may enable other aspects. Each of the drawings is provided for purposes of illustration and description, and not as a definition of the limits of the claims. The same or similar reference numbers in different drawings may identify the same or similar elements.
[0017] Fig. 1 is a diagram illustrating an example of a wireless communication network, in accordance with the present disclosure.
[0018] Fig. 2 is a diagram illustrating an example network node in communication with an example user equipment (UE) in a wireless network, in accordance with the present disclosure.
[0019] Fig. 3 is a diagram illustrating an example disaggregated base station architecture, in accordance with the present disclosure.
[0020] Fig. 4 is a diagram illustrating examples of channel state information (CSI) reference signal beam management procedures, in accordance with the present disclosure.
[0021] Fig. 5 is a diagram illustrating an example of a timeline for reporting CSI, in accordance with the present disclosure.
[0022] Fig. 6 is a diagram illustrating an example of prediction for reporting, in accordance with the present disclosure.
[0023] Fig. 7 is a diagram illustrating an example associated with joint prediction and measurement-based channel quality indicator (CQI) reporting, in accordance with the present disclosure.
[0024] Fig. 8 is a diagram illustrating an example of a minimum time duration associated with prediction for CSI reporting, in accordance with the present disclosure.
[0025] Fig. 9 is a diagram illustrating an example of a minimum time duration associated with prediction for CSI reporting, in accordance with the present disclosure.
[0026] Fig. 10 is a diagram illustrating an example process performed, for example, at a UE or an apparatus of a UE, in accordance with the present disclosure.
[0027] Fig. 11 is a diagram illustrating an example process performed, for example, at a network entity or an apparatus of a network entity, in accordance with the present disclosure.
[0028] Fig. 12 is a diagram of an example apparatus for wireless communication, in accordance with the present disclosure.
[0029] Fig. 13 is a diagram of an example apparatus for wireless communication, in accordance with the present disclosure.DETAILED DESCRIPTION
[0030] Various aspects of the present disclosure are described hereinafter with reference to the accompanying drawings. However, aspects of the present disclosure may be embodied in many different forms and is not to be construed as limited to any specific aspect illustrated by or described with reference to an accompanying drawing or otherwise presented in 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 may appreciate that the scope of the disclosure is intended to cover any aspect of the disclosure disclosed herein, whether implemented independently of or in combination with any other aspect of the disclosure. For example, an apparatus may be implemented or a method may be practiced using various combinations or quantities of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover an apparatus having, or a method that is practiced using, other structures and / or functionalities in addition to or other than the structures and / or functionalities with which various aspects of the disclosure set forth herein may be practiced. Any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim.
[0031] Several aspects of telecommunication systems will now be presented with reference to various methods, operations, apparatuses, and techniques. These methods, operations, 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, or algorithms (collectively referred to as “elements” ) . These elements may be implemented using hardware, software, or a combination of hardware and software. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.
[0032] A user equipment (UE) may measure reference signals on a channel and provide a beam report (channel state information (CSI) report) to assist a network entity with scheduling communications. The UE may transmit a UE-initiated CSI report based at least in part on detection of a triggering event. For example, the UE may detect a triggering event, such as a reference signal received power (RSRP) dropping below a threshold, a signal-to-interference-plus-noise ratio (SINR) dropping below a threshold, or a beam failure. The UE may switch beams or provide the beam report without being triggered by the network entity.
[0033] The UE may use artificial intelligence (AI) or machine learning (ML) to identify a Top-1 beam whose actual Layer 1 (L1) -RSRP is low (due to prediction errors) . If a network entity completely trusts a UE-predicted and reported Top-1 beam that has prediction errors, and the network entity uses the beam for downlink scheduling via outer loop link adaptation (OLLA) , the throughput might be interrupted due to the prediction errors. Particularly, legacy OLLA algorithms may decrease the modulation and coding scheme (MCS) quickly when a high block error rate (BLER) is observed, and the MCS may only increase gradually. Therefore, although prediction errors may occur occasionally, throughput interruption may last longer than a duration of the prediction errors.
[0034] Some solutions may attempt to address the effects of the prediction errors. For example, the network entity may additionally transmit the UE predicted beams via reference signals and request the UE to feed back the actual measurement-based channel quality indicators (CQIs) associated with the reference signals. Also, the MCS may be directly determined via close-loop link adaptation instead of OLLA. However, the issue is that there may be multiple UEs in a single cell operating via AI / ML-based beam prediction. The network entity may eventually need to transmit almost all of the narrow-beams at each prediction cycle. Therefore, overhead consumption is similar to that of cell-common reference signals that are transmitted for all candidate beams. That is, more signaling resources are consumed than may be necessary. Another solution may be to develop dedicated OLLA algorithms for UEs operating with prediction-based L1-RSRP reporting. However, the behavior or distributions of prediction errors can be varied across different environments, locations, UE moving / rotation speeds, and different UE vendors / modules. Therefore, simply relying on network-side OLLA algorithm enhancement may not fully resolve the issue. Furthermore, no obvious improvement is observed when sweeping among other MCS increase / decrease parameter combinations together with target BLER values.
[0035] Various aspects relate generally to beam management. Some aspects more specifically relate to UE-side beam prediction that is included with measurement-based CQI reporting in a single CSI reporting step, instead of two reporting steps. The UE may identify the target beams to be measured via AI / ML, focus on the prediction results for measurement, and calculate CQIs. The final CSI report may include only CQIs of predicted beams. The network entity may use close-loop link adaptation (rather than OLLA) to determine the MCS.
[0036] Particular aspects of the subject matter described in this disclosure can be implemented to realize one or more of the following potential advantages. As a result of reporting CQIs based on measurements of predicted beams, the OLLA problems described above may be solved. In contrast with a previous solution, downlink control information (DCI) overhead or latency for scheduling the first step L1-RSRP prediction can be reduced or removed because the network entity may eventually not use such information for downlink scheduling. As a result, signaling resources are conserved and throughput is increased. With a large number of UEs operating via beam prediction, all candidate prediction target beams may be transmitted in a cell-common manner.
[0037] Multiple-access radio access technologies (RATs) have been adopted in various telecommunication standards to provide common protocols that enable wireless communication devices to communicate on a municipal, enterprise, national, regional, or global level. For example, 5G New Radio (NR) is part of a continuous mobile broadband evolution promulgated by the Third Generation Partnership Project (3GPP) . 5G NR supports various technologies and use cases including enhanced mobile broadband (eMBB) , ultra-reliable low-latency communication (URLLC) , massive machine-type communication (mMTC) , millimeter wave (mmWave) technology, beamforming, network slicing, edge computing, Internet of Things (IoT) connectivity and management, and network function virtualization (NFV) .
[0038] As the demand for broadband access increases and as technologies supported by wireless communication networks evolve, further technological improvements may be adopted in or implemented for 5G NR or future RATs, such as 6G, to further advance the evolution of wireless communication for a wide variety of existing and new use cases and applications. Such technological improvements may be associated with new frequency band expansion, licensed and unlicensed spectrum access, overlapping spectrum use, small cell deployments, non-terrestrial network (NTN) deployments, disaggregated network architectures and network topology expansion, device aggregation, advanced duplex communication, sidelink and other device-to-device direct communication, IoT (including passive or ambient IoT) networks, reduced capability (RedCap) UE functionality, industrial connectivity, multiple-subscriber implementations, high-precision positioning, radio frequency (RF) sensing, and / or artificial intelligence or machine learning (AI / ML) , among other examples. These technological improvements may support use cases such as wireless backhauls, wireless data centers, extended reality (XR) and metaverse applications, meta services for supporting vehicle connectivity, holographic and mixed reality communication, autonomous and collaborative robots, vehicle platooning and cooperative maneuvering, sensing networks, gesture monitoring, human-brain interfacing, digital twin applications, asset management, and universal coverage applications using non-terrestrial and / or aerial platforms, among other examples. The methods, operations, apparatuses, and techniques described herein may enable one or more of the foregoing technologies and / or support one or more of the foregoing use cases.
[0039] Fig. 1 is a diagram illustrating an example of a wireless communication network 100, in accordance with the present disclosure. The wireless communication network 100 may be or may include elements of a 5G (or NR) network or a 6G network, among other examples. The wireless communication network 100 may include multiple network nodes 110, shown as a network node (NN) 110a, a network node 110b, a network node 110c, and a network node 110d. The network nodes 110 may support communications with multiple UEs 120, shown as a UE 120a, a UE 120b, a UE 120c, a UE 120d, and a UE 120e.
[0040] The network nodes 110 and the UEs 120 of the wireless communication network 100 may communicate using the electromagnetic spectrum, which may be subdivided by frequency or wavelength into various classes, bands, carriers, and / or channels. For example, devices of the wireless communication network 100 may communicate using one or more operating bands. In some aspects, multiple wireless networks 100 may be deployed in a given geographic area. Each wireless communication network 100 may support a particular RAT (which may also be referred to as an air interface) and may operate on one or more carrier frequencies in one or more frequency ranges. Examples of RATs include a 4G RAT, a 5G / NR RAT, and / or a 6G RAT, among other examples. In some examples, when multiple RATs are deployed in a given geographic area, each RAT in the geographic area may operate on different frequencies to avoid interference with one another.
[0041] Various operating bands have been defined as frequency range designations FR1 (410 MHz through 7.125 GHz) , FR2 (24.25 GHz through 52.6 GHz) , FR3 (7.125 GHz through 24.25 GHz) , FR4a or FR4-1 (52.6 GHz through 71 GHz) , FR4 (52.6 GHz through 114.25 GHz) , and FR5 (114.25 GHz through 300 GHz) . Although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as a “Sub-6 GHz” band in some documents and articles. Similarly, FR2 is often referred to (interchangeably) as a “millimeter wave” band in some documents and articles, despite being different than the extremely high frequency (EHF) band (30 GHz through 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, which include FR3. Frequency bands falling within FR3 may inherit FR1 characteristics or FR2 characteristics, and thus may effectively extend features of FR1 or FR2 into mid-band frequencies. Thus, “sub-6 GHz, ” if used herein, may broadly refer to frequencies that are less than 6 GHz, that are within FR1, and / or that are included in mid-band frequencies. Similarly, the term “millimeter wave, ” if used herein, may broadly refer to frequencies that are included in mid-band frequencies, that are within FR2, FR4, FR4-aor FR4-1, or FR5, and / or that are within the EHF band. Higher frequency bands may extend 5G NR operation, 6G operation, and / or other RATs beyond 52.6 GHz. For example, each of FR4a, FR4-1, FR4, and FR5 falls within the EHF band. In some examples, the wireless communication network 100 may implement dynamic spectrum sharing (DSS) , in which multiple RATs (for example, 4G / LTE and 5G / NR) are implemented with dynamic bandwidth allocation (for example, based on user demand) in a single frequency band. It is contemplated that the frequencies included in these operating bands (for example, FR1, FR2, FR3, FR4, FR4-a, FR4-1, and / or FR5) may be modified, and techniques described herein may be applicable to those modified frequency ranges.
[0042] A network node 110 may include one or more devices, components, or systems that enable communication between a UE 120 and one or more devices, components, or systems of the wireless communication network 100. A network node 110 may be, may include, or may also be referred to as an NR network node, a 5G network node, a 6G network node, a Node B, an eNB, a gNB, an access point (AP) , a transmission reception point (TRP) , a mobility element, a core, a network entity, a network element, a network equipment, and / or another type of device, component, or system included in a radio access network (RAN) .
[0043] A network node 110 may be implemented as a single physical node (for example, a single physical structure) or may be implemented as two or more physical nodes (for example, two or more distinct physical structures) . For example, a network node 110 may be a device or system that implements part of a radio protocol stack, a device or system that implements a full radio protocol stack (such as a full gNB protocol stack) , or a collection of devices or systems that collectively implement the full radio protocol stack. For example, and as shown, a network node 110 may be an aggregated network node (having an aggregated architecture) , meaning that the network node 110 may implement a full radio protocol stack that is physically and logically integrated within a single node (for example, a single physical structure) in the wireless communication network 100. For example, an aggregated network node 110 may consist of a single standalone base station or a single TRP that uses a full radio protocol stack to enable or facilitate communication between a UE 120 and a core network of the wireless communication network 100.
[0044] Alternatively, and as also shown, a network node 110 may be a disaggregated network node (sometimes referred to as a disaggregated base station) , meaning that the network node 110 may implement a radio protocol stack that is physically distributed and / or logically distributed among two or more nodes in the same geographic location or in different geographic locations. For example, a disaggregated network node may have a disaggregated architecture. In some deployments, disaggregated network nodes 110 may be used in an integrated access and backhaul (IAB) network, in an open radio access network (O-RAN) (such as a network configuration in compliance with the O-RAN Alliance) , or in a virtualized radio access network (vRAN) , also known as a cloud radio access network (C-RAN) , to facilitate scaling by separating base station functionality into multiple units that can be individually deployed.
[0045] The network nodes 110 of the wireless communication network 100 may include one or more central units (CUs) , one or more distributed units (DUs) , and / or one or more radio units (RUs) . A CU may host one or more higher layer control functions, such as radio resource control (RRC) functions, packet data convergence protocol (PDCP) functions, and / or service data adaptation protocol (SDAP) functions, among other examples. A DU may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and / or one or more higher physical (PHY) layers depending, at least in part, on a functional split, such as a functional split defined by the 3GPP. In some examples, a DU also may host one or more lower PHY layer functions, such as a fast Fourier transform (FFT) , an inverse FFT (iFFT) , beamforming, physical random access channel (PRACH) extraction and filtering, and / or scheduling of resources for one or more UEs 120, among other examples. An RU may host RF processing functions or lower PHY layer functions, such as an FFT, an iFFT, beamforming, or PRACH extraction and filtering, among other examples, according to a functional split, such as a lower layer functional split. In such an architecture, each RU can be operated to handle over the air (OTA) communication with one or more UEs 120.
[0046] In some aspects, a single network node 110 may include a combination of one or more CUs, one or more DUs, and / or one or more RUs. Additionally or alternatively, a network node 110 may include one or more Near-Real Time (Near-RT) RAN Intelligent Controllers (RICs) and / or one or more Non-Real Time (Non-RT) RICs. In some examples, a CU, a DU, and / or an RU may be implemented as a virtual unit, such as a virtual central unit (VCU) , a virtual distributed unit (VDU) , or a virtual radio unit (VRU) , among other examples. A virtual unit may be implemented as a virtual network function, such as associated with a cloud deployment.
[0047] Some network nodes 110 (for example, a base station, an RU, or a TRP) may provide communication coverage for a particular geographic area. In the 3GPP, the term “cell” can refer to a coverage area of a network node 110 or to a network node 110 itself, depending on the context in which the term is used. A network node 110 may support one or multiple (for example, three) cells. In some examples, a network node 110 may provide communication coverage for a macro cell, a pico cell, a femto cell, or another type of cell. A macro cell may cover a relatively large geographic area (for example, 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 subscriptions. A femto cell may cover a relatively small geographic area (for example, a home) and may allow restricted access by UEs 120 having association with the femto cell (for example, UEs 120 in a closed subscriber group (CSG) ) . A network node 110 for a macro cell may be referred to as a macro network node. A network node 110 for a pico cell may be referred to as a pico network node. A network node 110 for a femto cell may be referred to as a femto network node or an in-home network node. In some examples, a cell may not necessarily be stationary. For example, the geographic area of the cell may move according to the location of an associated mobile network node 110 (for example, a train, a satellite base station, an unmanned aerial vehicle, or an NTN network node) .
[0048] The wireless communication network 100 may be a heterogeneous network that includes network nodes 110 of different types, such as macro network nodes, pico network nodes, femto network nodes, relay network nodes, aggregated network nodes, and / or disaggregated network nodes, among other examples. In the example shown in Fig. 1, the network node 110a may be a macro network node for a macro cell 130a, the network node 110b may be a pico network node for a pico cell 130b, and the network node 110c may be a femto network node for a femto cell 130c. Various different types of network nodes 110 may generally transmit at different power levels, serve different coverage areas, and / or have different impacts on interference in the wireless communication network 100 than other types of network nodes 110. For example, macro network nodes may have a high transmit power level (for example, 5 to 40 watts) , whereas pico network nodes, femto network nodes, and relay network nodes may have lower transmit power levels (for example, 0.1 to 2 watts) .
[0049] In some examples, a network node 110 may be, may include, or may operate as an RU, a TRP, or a base station that communicates with one or more UEs 120 via a radio access link (which may be referred to as a “Uu” link) . The radio access link may include a downlink and an uplink. “Downlink” (or “DL” ) refers to a communication direction from a network node 110 to a UE 120, and “uplink” (or “UL” ) refers to a communication direction from a UE 120 to a network node 110. Downlink channels may include one or more control channels and one or more data channels. A downlink control channel may be used to transmit DCI (for example, scheduling information, reference signals, and / or configuration information) from a network node 110 to a UE 120. A downlink data channel may be used to transmit downlink data (for example, user data associated with a UE 120) from a network node 110 to a UE 120. Downlink control channels may include one or more physical downlink control channels (PDCCHs) , and downlink data channels may include one or more physical downlink shared channels (PDSCHs) . Uplink channels may similarly include one or more control channels and one or more data channels. An uplink control channel may be used to transmit uplink control information (UCI) (for example, reference signals and / or feedback corresponding to one or more downlink transmissions) from a UE 120 to a network node 110. An uplink data channel may be used to transmit uplink data (for example, user data associated with a UE 120) from a UE 120 to a network node 110. Uplink control channels may include one or more physical uplink control channels (PUCCHs) , and uplink data channels may include one or more physical uplink shared channels (PUSCHs) . The downlink and the uplink may each include a set of resources on which the network node 110 and the UE 120 may communicate.
[0050] Downlink and uplink resources may include time domain resources (frames, subframes, slots, and / or symbols) , frequency domain resources (frequency bands, component carriers, subcarriers, resource blocks, and / or resource elements) , and / or spatial domain resources (particular transmit directions and / or beam parameters) . Frequency domain resources of some bands may be subdivided into bandwidth parts (BWPs) . A BWP may be a continuous block of frequency domain resources (for example, a continuous block of resource blocks) that are allocated for one or more UEs 120. A UE 120 may be configured with both an uplink BWP and a downlink BWP (where the uplink BWP and the downlink BWP may be the same BWP or different BWPs) . A BWP may be dynamically configured (for example, by a network node 110 transmitting a DCI configuration to the one or more UEs 120) and / or reconfigured, which means that a BWP can be adjusted in real-time (or near-real-time) based on changing network conditions in the wireless communication network 100 and / or based on the specific requirements of the one or more UEs 120. This enables more efficient use of the available frequency domain resources in the wireless communication network 100 because fewer frequency domain resources may be allocated to a BWP for a UE 120 (which may reduce the quantity of frequency domain resources that a UE 120 is required to monitor) , leaving more frequency domain resources to be spread across multiple UEs 120. Thus, BWPs may also assist in the implementation of lower-capability UEs 120 by facilitating the configuration of smaller bandwidths for communication by such UEs 120.
[0051] As described above, in some aspects, the wireless communication network 100 may be, may include, or may be included in, an IAB network. In an IAB network, at least one network node 110 is an anchor network node that communicates with a core network. An anchor network node 110 may also be referred to as an IAB donor (or “IAB-donor” ) . The anchor network node 110 may connect to the core network via a wired backhaul link. For example, an Ng interface of the anchor network node 110 may terminate at the core network. Additionally or alternatively, an anchor network node 110 may connect to one or more devices of the core network that provide a core access and mobility management function (AMF) . An IAB network also generally includes multiple non-anchor network nodes 110, which may also be referred to as relay network nodes or simply as IAB nodes (or “IAB-nodes” ) . Each non-anchor network node 110 may communicate directly with the anchor network node 110 via a wireless backhaul link to access the core network, or may communicate indirectly with the anchor network node 110 via one or more other non-anchor network nodes 110 and associated wireless backhaul links that form a backhaul path to the core network. Some anchor network node 110 or other non-anchor network node 110 may also communicate directly with one or more UEs 120 via wireless access links that carry access traffic. In some examples, network resources for wireless communication (such as time resources, frequency resources, and / or spatial resources) may be shared between access links and backhaul links.
[0052] In some examples, any network node 110 that relays communications may be referred to as a relay network node, a relay station, or simply as a relay. A relay may receive a transmission of a communication from an upstream station (for example, another network node 110 or a UE 120) and transmit the communication to a downstream station (for example, a UE 120 or another network node 110) . In this case, the wireless communication network 100 may include or be referred to as a “multi-hop network. ” In the example shown in Fig. 1, the network node 110d (for example, a relay network node) may communicate with the network node 110a (for example, a macro network node) and the UE 120d in order to facilitate communication between the network node 110a and the UE 120d. Additionally or alternatively, a UE 120 may be or may operate as a relay station that can relay transmissions to or from other UEs 120. A UE 120 that relays communications may be referred to as a UE relay or a relay UE, among other examples.
[0053] The UEs 120 may be physically dispersed throughout the wireless communication network 100, and each UE 120 may be stationary or mobile. A UE 120 may be, may include, or may be included in an access terminal, another terminal, a mobile station, or a subscriber unit. A UE 120 may be, include, or be coupled with a cellular phone (for example, 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 (for example, a smart watch, smart clothing, smart glasses, a smart wristband, and / or smart jewelry, such as a smart ring or a smart bracelet) , an entertainment device (for example, a music device, a video device, and / or a satellite radio) , an XR device, a vehicular component or sensor, a smart meter or sensor, industrial manufacturing equipment, a Global Navigation Satellite System (GNSS) device (such as a Global Positioning System device or another type of positioning device) , a UE function of a network node, and / or any other suitable device or function that may communicate via a wireless medium.
[0054] A UE 120 and / or a network node 110 may include one or more chips, system-on-chips (SoCs) , chipsets, packages, or devices that individually or collectively constitute or comprise a processing system. The processing system includes processor (or “processing” ) circuitry in the form of one or multiple processors, microprocessors, processing units (such as central processing units (CPUs) , graphics processing units (GPUs) , neural processing units (NPUs) and / or digital signal processors (DSPs) ) , processing blocks, application-specific integrated circuits (ASIC) , programmable logic devices (PLDs) (such as field programmable gate arrays (FPGAs) ) , or other discrete gate or transistor logic or circuitry (all of which may be generally referred to herein individually as “processors” or collectively as “the processor” or “the processor circuitry” ) . One or more of the processors may be individually or collectively configurable or configured to perform various functions or operations described herein. A group of processors collectively configurable or configured to perform a set of functions may include a first processor configurable or configured to perform a first function of the set and a second processor configurable or configured to perform a second function of the set, or may include the group of processors all being configured or configurable to perform the set of functions.
[0055] The processing system may further include memory circuitry in the form of one or more memory devices, memory blocks, memory elements or other discrete gate or transistor logic or circuitry, each of which may include tangible storage media such as random-access memory (RAM) or read-only memory (ROM) , or combinations thereof (all of which may be generally referred to herein individually as “memories” or collectively as “the memory” or “the memory circuitry” ) . One or more of the memories may be coupled (for example, operatively coupled, communicatively coupled, electronically coupled, or electrically coupled) with one or more of the processors and may individually or collectively store processor-executable code (such as software) that, when executed by one or more of the processors, may configure one or more of the processors to perform various functions or operations described herein. Additionally or alternatively, in some examples, one or more of the processors may be preconfigured to perform various functions or operations described herein without requiring configuration by software. The processing system may further include or be coupled with one or more modems (such as a Wi-Fi (for example, IEEE compliant) modem or a cellular (for example, 3GPP 4G LTE, 5G, or 6G compliant) modem) . In some implementations, one or more processors of the processing system include or implement one or more of the modems. The processing system may further include or be coupled with multiple radios (collectively “the radio” ) , multiple RF chains, or multiple transceivers, each of which may in turn be coupled with one or more of multiple antennas. In some implementations, one or more processors of the processing system include or implement one or more of the radios, RF chains or transceivers. The UE 120 may include or may be included in a housing that houses components associated with the UE 120 including the processing system.
[0056] Some UEs 120 may be considered machine-type communication (MTC) UEs, evolved or enhanced machine-type communication (eMTC) , UEs, further enhanced eMTC (feMTC) UEs, or enhanced feMTC (efeMTC) UEs, or further evolutions thereof, all of which may be simply referred to as “MTC UEs” . An MTC UE may be, may include, or may be included in or coupled with a robot, an uncrewed aerial vehicle, a remote device, a sensor, a meter, a monitor, and / or a location tag. Some UEs 120 may be considered IoT devices and / or may be implemented as NB-IoT (narrowband IoT) devices. An IoT UE or NB-IoT device may be, may include, or may be included in or coupled with an industrial machine, an appliance, a refrigerator, a doorbell camera device, a home automation device, and / or a light fixture, among other examples. Some UEs 120 may be considered Customer Premises Equipment, which may include telecommunications devices that are installed at a customer location (such as a home or office) to enable access to a service provider's network (such as included in or in communication with the wireless communication network 100) .
[0057] Some UEs 120 may be classified according to different categories in association with different complexities and / or different capabilities. UEs 120 in a first category may facilitate massive IoT in the wireless communication network 100, and may offer low complexity and / or cost relative to UEs 120 in a second category. UEs 120 in a second category may include mission-critical IoT devices, legacy UEs, baseline UEs, high-tier UEs, advanced UEs, full-capability UEs, and / or premium UEs that are capable of URLLC, enhanced mobile broadband (eMBB) , and / or precise positioning in the wireless communication network 100, among other examples. A third category of UEs 120 may have mid-tier complexity and / or capability (for example, a capability between UEs 120 of the first category and UEs 120 of the second capability) . A UE 120 of the third category may be referred to as a reduced capacity UE ( “RedCap UE” ) , a mid-tier UE, an NR-Light UE, and / or an NR-Lite UE, among other examples. RedCap UEs may bridge a gap between the capability and complexity of NB-IoT devices and / or eMTC UEs, and mission-critical IoT devices and / or premium UEs. RedCap UEs may include, for example, wearable devices, IoT devices, industrial sensors, and / or cameras that are associated with a limited bandwidth, power capacity, and / or transmission range, among other examples. RedCap UEs may support healthcare environments, building automation, electrical distribution, process automation, transport and logistics, and / or smart city deployments, among other examples.
[0058] In some examples, two or more UEs 120 (for example, shown as UE 120a and UE 120e) may communicate directly with one another using sidelink communications (for example, without communicating by way of a network node 110 as an intermediary) . As an example, the UE 120a may directly transmit data, control information, or other signaling as a sidelink communication to the UE 120e. This is in contrast to, for example, the UE 120a first transmitting data in an UL communication to a network node 110, which then transmits the data to the UE 120e in a DL communication. In various examples, the UEs 120 may transmit and receive sidelink communications using peer-to-peer (P2P) communication protocols, device-to-device (D2D) communication protocols, vehicle-to-everything (V2X) communication protocols (which may include vehicle-to-vehicle (V2V) protocols, vehicle-to-infrastructure (V2I) protocols, and / or vehicle-to-pedestrian (V2P) protocols) , and / or mesh network communication protocols. In some deployments and configurations, a network node 110 may schedule and / or allocate resources for sidelink communications between UEs 120 in the wireless communication network 100. In some other deployments and configurations, a UE 120 (instead of a network node 110) may perform, or collaborate or negotiate with one or more other UEs to perform, scheduling operations, resource selection operations, and / or other operations for sidelink communications.
[0059] In various examples, some of the network nodes 110 and the UEs 120 of the wireless communication network 100 may be configured for full-duplex operation in addition to half-duplex operation. A network node 110 or a UE 120 operating in a half-duplex mode may perform only one of transmission or reception during particular time resources, such as during particular slots, symbols, or other time periods. Half-duplex operation may involve time-division duplexing (TDD) , in which DL transmissions of the network node 110 and UL transmissions of the UE 120 do not occur in the same time resources (that is, the transmissions do not overlap in time) . In contrast, a network node 110 or a UE 120 operating in a full-duplex mode can transmit and receive communications concurrently (for example, in the same time resources) . By operating in a full-duplex mode, network nodes 110 and / or UEs 120 may generally increase the capacity of the network and the radio access link. In some examples, full-duplex operation may involve frequency-division duplexing (FDD) , in which DL transmissions of the network node 110 are performed in a first frequency band or on a first component carrier and transmissions of the UE 120 are performed in a second frequency band or on a second component carrier different than the first frequency band or the first component carrier, respectively. In some examples, full-duplex operation may be enabled for a UE 120 but not for a network node 110. For example, a UE 120 may simultaneously transmit an UL transmission to a first network node 110 and receive a DL transmission from a second network node 110 in the same time resources. In some other examples, full-duplex operation may be enabled for a network node 110 but not for a UE 120. For example, a network node 110 may simultaneously transmit a DL transmission to a first UE 120 and receive an UL transmission from a second UE 120 in the same time resources. In some other examples, full-duplex operation may be enabled for both a network node 110 and a UE 120.
[0060] In some examples, the UEs 120 and the network nodes 110 may perform MIMO communication. “MIMO” generally refers to transmitting or receiving multiple signals (such as multiple layers or multiple data streams) simultaneously over the same time and frequency resources. MIMO techniques generally exploit multipath propagation. MIMO may be implemented using various spatial processing or spatial multiplexing operations. In some examples, MIMO may support simultaneous transmission to multiple receivers, referred to as multi-user MIMO (MU-MIMO) . Some RATs may employ advanced MIMO techniques, such as mTRP operation (including redundant transmission or reception on multiple TRPs) , reciprocity in the time domain or the frequency domain, single-frequency-network (SFN) transmission, or non-coherent joint transmission (NCJT) .
[0061] In some aspects, a UE (e.g., a UE 120) may include a communication manager 140. As described in more detail elsewhere herein, the communication manager 140 may receive scheduling information for a CSI report. The communication manager 140 may predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The communication manager 140 may identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The communication manager 140 may transmit the CSI report with a set of CQIs for the preferred set of reference signals. Additionally, or alternatively, the communication manager 140 may perform one or more other operations described herein.
[0062] In some aspects, a network entity (e.g., a network node 110) may include a communication manager 150. As described in more detail elsewhere herein, the communication manager 150 may transmit a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The communication manager 150 may transmit scheduling information for a CSI report. The communication manager 150 may receive the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources. Additionally, or alternatively, the communication manager 150 may perform one or more other operations described herein.
[0063] As indicated above, Fig. 1 is provided as an example. Other examples may differ from what is described with regard to Fig. 1.
[0064] Fig. 2 is a diagram illustrating an example network node 110 in communication with an example UE 120 in a wireless network, in accordance with the present disclosure.
[0065] As shown in Fig. 2, the network node 110 may include a data source 212, a transmit processor 214, a transmit (TX) MIMO processor 216, a set of modems 232 (shown as 232a through 232t, where t ≥ 1) , a set of antennas 234 (shown as 234a through 234v, where v ≥ 1) , a MIMO detector 236, a receive processor 238, a data sink 239, a controller / processor 240, a memory 242, a communication unit 244, a scheduler 246, and / or a communication manager, among other examples. In some configurations, one or a combination of the antenna (s) 234, the modem (s) 232, the MIMO detector 236, the receive processor 238, the transmit processor 214, and / or the TX MIMO processor 216 may be included in a transceiver of the network node 110. The transceiver may be under control of and used by one or more processors, such as the controller / processor 240, and in some aspects in conjunction with processor-readable code stored in the memory 242, to perform aspects of the methods, processes, and / or operations described herein. In some aspects, the network node 110 may include one or more interfaces, communication components, and / or other components that facilitate communication with the UE 120 or another network node.
[0066] The terms “processor, ” “controller, ” or “controller / processor” may refer to one or more controllers and / or one or more processors. For example, reference to “a / the processor, ” “a / the controller / processor, ” or the like (in the singular) should be understood to refer to any one or more of the processors described in connection with Fig. 2, such as a single processor or a combination of multiple different processors. Reference to “one or more processors” should be understood to refer to any one or more of the processors described in connection with Fig. 2. For example, one or more processors of the network node 110 may include transmit processor 214, TX MIMO processor 216, MIMO detector 236, receive processor 238, and / or controller / processor 240. Similarly, one or more processors of the UE 120 may include MIMO detector 256, receive processor 258, transmit processor 264, TX MIMO processor 266, and / or controller / processor 280.
[0067] In some aspects, a single processor may perform all of the operations described as being performed by the one or more processors. In some aspects, a first set of (one or more) processors of the one or more processors may perform a first operation described as being performed by the one or more processors, and a second set of (one or more) processors of the one or more processors may perform a second operation described as being performed by the one or more processors. The first set of processors and the second set of processors may be the same set of processors or may be different sets of processors. Reference to “one or more memories” should be understood to refer to any one or more memories of a corresponding device, such as the memory described in connection with Fig. 2. For example, operation described as being performed by one or more memories can be performed by the same subset of the one or more memories or different subsets of the one or more memories.
[0068] For downlink communication from the network node 110 to the UE 120, the transmit processor 214 may receive data ( “downlink data” ) intended for the UE 120 (or a set of UEs that includes the UE 120) from the data source 212 (such as a data pipeline or a data queue) . In some examples, the transmit processor 214 may select one or more MCSs for the UE 120 in accordance with one or more CQIs received from the UE 120. The network node 110 may process the data (for example, including encoding the data) for transmission to the UE 120 on a downlink in accordance with the MCS (s) selected for the UE 120 to generate data symbols. The transmit processor 214 may process system information (for example, semi-static resource partitioning information (SRPI) ) and / or control information (for example, CQI requests, grants, and / or upper layer signaling) and provide overhead symbols and / or control symbols. The transmit processor 214 may generate reference symbols for reference signals (for example, a cell-specific reference signal (CRS) , a demodulation reference signal (DMRS) , or a CSI reference signal (CSI-RS) ) and / or synchronization signals (for example, a primary synchronization signal (PSS) or a secondary synchronization signals (SSS) ) .
[0069] The TX MIMO processor 216 may perform spatial processing (for example, 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 (for example, T output symbol streams) to the set of modems 232. For example, each output symbol stream may be provided to a respective modulator component (shown as MOD) of a modem 232. Each modem 232 may use the respective modulator component to process (for example, to modulate) a respective output symbol stream (for example, for orthogonal frequency division multiplexing (OFDM) ) to obtain an output sample stream. Each modem 232 may further use the respective modulator component to process (for example, convert to analog, amplify, filter, and / or upconvert) the output sample stream to obtain a time domain downlink signal. The modems 232a through 232t may together transmit a set of downlink signals (for example, T downlink signals) via the corresponding set of antennas 234.
[0070] A downlink signal may include a DCI communication, a MAC control element (MAC CE) communication, an RRC communication, a downlink reference signal, or another type of downlink communication. Downlink signals may be transmitted on a PDCCH, a PDSCH, and / or on another downlink channel. A downlink signal may carry one or more transport blocks (TBs) of data. A TB may be a unit of data that is transmitted over an air interface in the wireless communication network 100. A data stream (for example, from the data source 212) may be encoded into multiple TBs for transmission over the air interface. The quantity of TBs used to carry the data associated with a particular data stream may be associated with a TB size common to the multiple TBs. The TB size may be based on or otherwise associated with radio channel conditions of the air interface, the MCS used for encoding the data, the downlink resources allocated for transmitting the data, and / or another parameter. In general, the larger the TB size, the greater the amount of data that can be transmitted in a single transmission, which reduces signaling overhead. However, larger TB sizes may be more prone to transmission and / or reception errors than smaller TB sizes, but such errors may be mitigated by more robust error correction techniques.
[0071] For uplink communication from the UE 120 to the network node 110, uplink signals from the UE 120 may be received by an antenna 234, may be processed by a modem 232 (for example, a demodulator component, shown as DEMOD, of a modem 232) , may be detected by the MIMO detector 236 (for example, a receive (Rx) MIMO processor) if applicable, and / or may be further processed by the receive processor 238 to obtain decoded data and / or control information. The receive processor 238 may provide the decoded data to a data sink 239 (which may be a data pipeline, a data queue, and / or another type of data sink) and provide the decoded control information to a processor, such as the controller / processor 240.
[0072] The network node 110 may use the scheduler 246 to schedule one or more UEs 120 for downlink or uplink communications. In some aspects, the scheduler 246 may use DCI to dynamically schedule DL transmissions to the UE 120 and / or UL transmissions from the UE 120. In some examples, the scheduler 246 may allocate recurring time domain resources and / or frequency domain resources that the UE 120 may use to transmit and / or receive communications using an RRC configuration (for example, a semi-static configuration) , for example, to perform semi-persistent scheduling (SPS) or to configure a configured grant (CG) for the UE 120.
[0073] One or more of the transmit processor 214, the TX MIMO processor 216, the modem 232, the antenna 234, the MIMO detector 236, the receive processor 238, and / or the controller / processor 240 may be included in an RF chain of the network node 110. An RF chain may include one or more filters, mixers, oscillators, amplifiers, analog-to-digital converters (ADCs) , and / or other devices that convert between an analog signal (such as for transmission or reception via an air interface) and a digital signal (such as for processing by one or more processors of the network node 110) . In some aspects, the RF chain may be or may be included in a transceiver of the network node 110.
[0074] In some examples, the network node 110 may use the communication unit 244 to communicate with a core network and / or with other network nodes. The communication unit 244 may support wired and / or wireless communication protocols and / or connections, such as Ethernet, optical fiber, common public radio interface (CPRI) , and / or a wired or wireless backhaul, among other examples. The network node 110 may use the communication unit 244 to transmit and / or receive data associated with the UE 120 or to perform network control signaling, among other examples. The communication unit 244 may include a transceiver and / or an interface, such as a network interface.
[0075] The UE 120 may include a set of antennas 252 (shown as antennas 252a through 252r, where r ≥ 1) , a set of modems 254 (shown as modems 254a through 254u, where u ≥ 1) , a MIMO detector 256, a receive processor 258, a data sink 260, a data source 262, a transmit processor 264, a TX MIMO processor 266, a controller / processor 280, a memory 282, and / or a communication manager 140, among other examples. One or more of the components of the UE 120 may be included in a housing 284. In some aspects, one or a combination of the antenna (s) 252, the modem (s) 254, the MIMO detector 256, the receive processor 258, the transmit processor 264, or the TX MIMO processor 266 may be included in a transceiver that is included in the UE 120. The transceiver may be under control of and used by one or more processors, such as the controller / processor 280, and in some aspects in conjunction with processor-readable code stored in the memory 282, to perform aspects of the methods, processes, or operations described herein. In some aspects, the UE 120 may include another interface, another communication component, and / or another component that facilitates communication with the network node 110 and / or another UE 120.
[0076] For downlink communication from the network node 110 to the UE 120, the set of antennas 252 may receive the downlink communications or signals from the network node 110 and may provide a set of received downlink signals (for example, R received signals) to the set of modems 254. For example, each received signal may be provided to a respective demodulator component (shown as DEMOD) of a modem 254. Each modem 254 may use the respective demodulator component to condition (for example, filter, amplify, downconvert, and / or digitize) a received signal to obtain input samples. Each modem 254 may use the respective demodulator component to further demodulate or process the input samples (for example, for OFDM) to obtain received symbols. The MIMO detector 256 may obtain received symbols from the set of modems 254, may perform MIMO detection on the received symbols if applicable, and may provide detected symbols. The receive processor 258 may process (for example, decode) the detected symbols, may provide decoded data for the UE 120 to the data sink 260 (which may include a data pipeline, a data queue, and / or an application executed on the UE 120) , and may provide decoded control information and system information to the controller / processor 280.
[0077] For uplink communication from the UE 120 to the network node 110, the transmit processor 264 may receive and process data ( “uplink data” ) from a data source 262 (such as a data pipeline, a data queue, and / or an application executed on the UE 120) and control information from the controller / processor 280. The control information may include one or more parameters, feedback, one or more signal measurements, and / or other types of control information. In some aspects, the receive processor 258 and / or the controller / processor 280 may determine, for a received signal (such as received from the network node 110 or another UE) , one or more parameters relating to transmission of the uplink communication. The one or more parameters may include an RSRP parameter, a received signal strength indicator (RSSI) parameter, a reference signal received quality (RSRQ) parameter, a CQI parameter, or a transmit power control (TPC) parameter, among other examples. The control information may include an indication of the RSRP parameter, the RSSI parameter, the RSRQ parameter, the CQI parameter, the TPC parameter, and / or another parameter. The control information may facilitate parameter selection and / or scheduling for the UE 120 by the network node 110.
[0078] The transmit processor 264 may generate reference symbols for one or more reference signals, such as an uplink DMRS, an uplink sounding reference signal (SRS) , and / or another type of reference signal. The symbols from the transmit processor 264 may be precoded by the TX MIMO processor 266, if applicable, and further processed by the set of modems 254 (for example, for DFT-s-OFDM or CP-OFDM) . The TX MIMO processor 266 may perform spatial processing (for example, 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 (for example, U output symbol streams) to the set of modems 254. For example, each output symbol stream may be provided to a respective modulator component (shown as MOD) of a modem 254. Each modem 254 may use the respective modulator component to process (for example, to modulate) a respective output symbol stream (for example, for OFDM) to obtain an output sample stream. Each modem 254 may further use the respective modulator component to process (for example, convert to analog, amplify, filter, and / or upconvert) the output sample stream to obtain an uplink signal.
[0079] The modems 254a through 254u may transmit a set of uplink signals (for example, R uplink signals or U uplink symbols) via the corresponding set of antennas 252. An uplink signal may include a UCI communication, a MAC CE communication, an RRC communication, or another type of uplink communication. Uplink signals may be transmitted on a PUSCH, a PUCCH, and / or another type of uplink channel. An uplink signal may carry one or more TBs of data. Sidelink data and control transmissions (that is, transmissions directly between two or more UEs 120) may generally use similar techniques as were described for uplink data and control transmission, and may use sidelink-specific channels such as a physical sidelink shared channel (PSSCH) , a physical sidelink control channel (PSCCH) , and / or a physical sidelink feedback channel (PSFCH) .
[0080] One or more antennas of the set of antennas 252 or the set of antennas 234 may include, or may be included within, one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays, among other examples. An antenna panel, an antenna group, a set of antenna elements, 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, or one or more antenna elements coupled with one or more transmission or reception components, such as one or more components of Fig. 2. As used herein, “antenna” can refer to one or more antennas, one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays. “Antenna panel” can refer to a group of antennas (such as antenna elements) arranged in an array or panel, which may facilitate beamforming by manipulating parameters of the group of antennas. “Antenna module” may refer to circuitry including one or more antennas, which may also include one or more other components (such as filters, amplifiers, or processors) associated with integrating the antenna module into a wireless communication device.
[0081] In some examples, each of the antenna elements of an antenna 234 or an antenna 252 may include one or more sub-elements for radiating or receiving radio frequency signals. For example, a single antenna element may include a first sub-element cross-polarized with a second sub-element that can be used to independently transmit cross-polarized signals. The antenna elements may include patch antennas, dipole antennas, and / or other types of antennas arranged in a linear pattern, a two-dimensional pattern, or another pattern. A spacing between antenna elements may be such that signals with a desired wavelength transmitted separately by the antenna elements may interact or interfere constructively and destructively along various directions (such as to form a desired beam) . For example, given an expected range of wavelengths or frequencies, the spacing may provide a quarter wavelength, a half wavelength, or another fraction of a wavelength of spacing between neighboring antenna elements to allow for the desired constructive and destructive interference patterns of signals transmitted by the separate antenna elements within that expected range.
[0082] The amplitudes and / or phases of signals transmitted via antenna elements and / or sub-elements may be modulated and shifted relative to each other (such as by manipulating phase shift, phase offset, and / or amplitude) to generate one or more beams, which is referred to as beamforming. The term “beam” may refer to a directional transmission of a wireless signal toward a receiving device or otherwise in a desired direction. “Beam” may also generally refer to a direction associated with such a directional signal transmission, a set of directional resources associated with the signal transmission (for example, an angle of arrival, a horizontal direction, and / or a vertical direction) , and / or a set of parameters that indicate one or more aspects of a directional signal, a direction associated with the signal, and / or a set of directional resources associated with the signal. In some implementations, antenna elements may be individually selected or deselected for directional transmission of a signal (or signals) by controlling amplitudes of one or more corresponding amplifiers and / or phases of the signal (s) to form one or more beams. The shape of a beam (such as the amplitude, width, and / or presence of side lobes) and / or the direction of a beam (such as an angle of the beam relative to a surface of an antenna array) can be dynamically controlled by modifying the phase shifts, phase offsets, and / or amplitudes of the multiple signals relative to each other.
[0083] Different UEs 120 or network nodes 110 may include different numbers of antenna elements. For example, a UE 120 may include a single antenna element, two antenna elements, four antenna elements, eight antenna elements, or a different number of antenna elements. As another example, a network node 110 may include eight antenna elements, 24 antenna elements, 64 antenna elements, 128 antenna elements, or a different number of antenna elements. Generally, a larger number of antenna elements may provide increased control over parameters for beam generation relative to a smaller number of antenna elements, whereas a smaller number of antenna elements may be less complex to implement and may use less power than a larger number of antenna elements. Multiple antenna elements may support multiple-layer transmission, in which a first layer of a communication (which may include a first data stream) and a second layer of a communication (which may include a second data stream) are transmitted using the same time and frequency resources with spatial multiplexing.
[0084] 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.
[0085] Fig. 3 is a diagram illustrating an example disaggregated base station architecture 300, in accordance with the present disclosure. One or more components of the example disaggregated base station architecture 300 may be, may include, or may be included in one or more network nodes (such one or more network nodes 110) . The disaggregated base station architecture 300 may include a CU 310 that can communicate directly with a core network 320 via a backhaul link, or that can communicate indirectly with the core network 320 via one or more disaggregated control units, such as a Non-RT RIC 350 associated with a Service Management and Orchestration (SMO) Framework 360 and / or a Near-RT RIC 370 (for example, via an E2 link) . The CU 310 may communicate with one or more DUs 330 via respective midhaul links, such as via F1 interfaces. Each of the DUs 330 may communicate with one or more RUs 340 via respective fronthaul links. Each of the RUs 340 may communicate with one or more UEs 120 via respective RF access links. In some deployments, a UE 120 may be simultaneously served by multiple RUs 340.
[0086] Each of the components of the disaggregated base station architecture 300, including the CUs 310, the DUs 330, the RUs 340, the Near-RT RICs 370, the Non-RT RICs 350, and the SMO Framework 360, may include one or more interfaces or may be coupled with one or more interfaces for receiving or transmitting signals, such as data or information, via a wired or wireless transmission medium.
[0087] In some aspects, the CU 310 may be logically split into one or more CU user plane (CU-UP) units and one or more CU control plane (CU-CP) units. A CU-UP unit may communicate bidirectionally with a CU-CP unit via an interface, such as the E1 interface when implemented in an O-RAN configuration. The CU 310 may be deployed to communicate with one or more DUs 330, as necessary, for network control and signaling. Each 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, a DU 330 may host various layers, such as an RLC layer, a MAC layer, or one or more PHY layers, such as one or more high PHY layers or one or more low PHY layers. Each layer (which also may be referred to as a module) may be implemented with an interface for communicating signals with other layers (and modules) hosted by the DU 330, or for communicating signals with the control functions hosted by the CU 310. Each RU 340 may implement lower layer functionality. In some aspects, real-time and non-real-time aspects of control and user plane communication with the RU (s) 340 may be controlled by the corresponding DU 330.
[0088] The SMO Framework 360 may support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO Framework 360 may support the deployment of dedicated physical resources for RAN coverage requirements, which may be managed via an operations and maintenance interface, such as an O1 interface. For virtualized network elements, the SMO Framework 360 may interact with a cloud computing platform (such as an open cloud (O-Cloud) platform 390) to perform network element life cycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface, such as an O2 interface. A virtualized network element may include, but is not limited to, a CU 310, a DU 330, an RU 340, a non-RT RIC 350, and / or a Near-RT RIC 370. In some aspects, the SMO Framework 360 may communicate with a hardware aspect of a 4G RAN, a 5G NR RAN, and / or a 6G RAN, such as an open eNB (O-eNB) 380, via an O1 interface. Additionally or alternatively, the SMO Framework 360 may communicate directly with each of one or more RUs 340 via a respective O1 interface. In some deployments, this configuration can enable each DU 330 and the CU 310 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.
[0089] The Non-RT RIC 350 may include or may implement a logical function that enables non-real-time control and optimization of RAN elements and resources, AI / ML workflows including model training and updates, and / or policy-based guidance of applications and / or features in the Near-RT RIC 370. The Non-RT RIC 350 may be coupled to or may communicate with (such as via an A1 interface) the Near-RT RIC 370. The Near-RT RIC 370 may include or may implement a logical function that enables near-real-time control and optimization of RAN elements and resources via data collection and actions via an interface (such as via an E2 interface) connecting one or more CUs 310, one or more DUs 330, and / or an O-eNB with the Near-RT RIC 370.
[0090] In some aspects, to generate AI / ML models to be deployed in the Near-RT RIC 370, the Non-RT RIC 350 may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC 370 and may be received at the SMO Framework 360 or the Non-RT RIC 350 from non-network data sources or from network functions. In some examples, the Non-RT RIC 350 or the Near-RT RIC 370 may tune RAN behavior or performance. For example, the Non-RT RIC 350 may monitor long-term trends and patterns for performance and may employ AI / ML models to perform corrective actions via the SMO Framework 360 (such as reconfiguration via an O1 interface) or via creation of RAN management policies (such as A1 interface policies) .
[0091] As indicated above, Fig. 3 is provided as an example. Other examples may differ from what is described with regard to Fig. 3.
[0092] The network node 110, the controller / processor 240 of the network node 110, the UE 120, the controller / processor 280 of the UE 120, the CU 310, the DU 330, the RU 340, or any other component (s) of Figs. 1, 2, or 3 may implement one or more techniques or perform one or more operations associated with prediction for CSI reporting, as described in more detail elsewhere herein. For example, the controller / processor 240 of the network node 110, the controller / processor 280 of the UE 120, any other component (s) of Fig. 2, the CU 310, the DU 330, or the RU 340 may perform or direct operations of, for example, process 1000 of Fig. 10, process 1100 of Fig. 11, or other processes as described herein (alone or in conjunction with one or more other processors) . The memory 242 may store data and program codes for the network node 110, the network node 110, the CU 310, the DU 330, or the RU 340. The memory 282 may store data and program codes for the UE 120. In some examples, the memory 242 or the memory 282 may include a non-transitory computer-readable medium storing a set of instructions (for example, code or program code) for wireless communication. The memory 242 may include one or more memories, such as a single memory or multiple different memories (of the same type or of different types) . The memory 282 may include one or more memories, such as a single memory or multiple different memories (of the same type or of different types) . For example, the set of instructions, when executed (for example, directly, or after compiling, converting, or interpreting) by one or more processors of the network node 110, the UE 120, the CU 310, the DU 330, or the RU 340, may cause the one or more processors to perform process 1000 of Fig. 10, process 1100 of Fig. 11, 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.
[0093] In some aspects, a UE (e.g., a UE 120) includes means for receiving scheduling information for a CSI report; means for predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources; means for identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics; and / or means for transmitting the CSI report with a set of CQIs for the preferred set of reference signals. 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.
[0094] In some aspects, a network entity (e.g., a network node 110) includes means for transmitting a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources; means for transmitting scheduling information for a CSI report; and / or means for receiving the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources. In some aspects, the means for the network entity to perform operations described herein may include, for example, one or more of communication manager 150, transmit processor 214, TX MIMO processor 216, modem 232, antenna 234, MIMO detector 236, receive processor 238, controller / processor 240, memory 242, or scheduler 246.
[0095] Fig. 4 is a diagram illustrating examples 400, 410, and 420 of CSI-RS beam management procedures, in accordance with the present disclosure. As shown in Fig. 4, examples 400, 410, and 420 include a UE 120 in communication with a network node 110 in a wireless network (e.g., wireless network 100) . However, the devices shown in Fig. 4 are provided as examples, and the wireless network may support communication and beam management between other devices (e.g., between a UE 120 and a network node 110 or TRP, between a mobile termination node and a control node, between an IAB child node and an IAB parent node, and / or between a scheduled node and a scheduling node) . In some aspects, the UE 120 and the network node 110 may be in a connected state (e.g., an RRC connected state) .
[0096] As shown in Fig. 4, example 400 may include a network node 110 (e.g., one or more network node devices such as an RU, a DU, and / or a CU, among other examples) and a UE 120 communicating to perform beam management using CSI-RSs. Example 400 depicts a first beam management procedure (e.g., P1 CSI-RS beam management) . The first beam management procedure may be referred to as a beam selection procedure, an initial beam acquisition procedure, a beam sweeping procedure, a cell search procedure, and / or a beam search procedure. As shown in Fig. 4 and example 400, CSI-RSs may be configured to be transmitted from the network node 110 to the UE 120. The CSI-RSs may be configured to be periodic (e.g., using RRC signaling) , semi-persistent (e.g., using MAC CE signaling) , and / or aperiodic (e.g., using DCI) .
[0097] The first beam management procedure may include the network node 110 performing beam sweeping over multiple transmit (Tx) beams. The network node 110 may transmit a CSI-RS using each transmit beam for beam management. To enable the UE 120 to perform receive (Rx) beam sweeping, the network node may use a transmit beam to transmit (e.g., with repetitions) each CSI-RS at multiple times within the same reference signal (RS) resource set so that the UE 120 can sweep through receive beams in multiple transmission instances. For example, if the network node 110 has a set of N transmit beams and the UE 120 has a set of M receive beams, the CSI-RS may be transmitted on each of the N transmit beams M times so that the UE 120 may receive M instances of the CSI-RS per transmit beam. In other words, for each transmit beam of the network node 110, the UE 120 may perform beam sweeping through the receive beams of the UE 120. As a result, the first beam management procedure may enable the UE 120 to measure a CSI-RS on different transmit beams using different receive beams to support selection of network node 110 transmit beams / UE 120 receive beam (s) beam pair (s) . The UE 120 may report the measurements to the network node 110 in a CSI report to enable the network node 110 to select one or more beam pair (s) for communication between the network node 110 and the UE 120. While example 400 has been described in connection with CSI-RSs, the first beam management process may also use synchronization signal blocks (SSBs) for beam management in a similar manner as described above.
[0098] As shown in Fig. 4, example 410 may include a network node 110 and a UE 120 communicating to perform beam management using CSI-RSs. Example 410 depicts a second beam management procedure (e.g., P2 CSI-RS beam management) . The second beam management procedure may be referred to as a beam refinement procedure, a network node beam refinement procedure, a TRP beam refinement procedure, and / or a transmit beam refinement procedure. As shown in Fig. 4 and example 410, CSI-RSs may be configured to be transmitted from the network node 110 to the UE 120. The CSI-RSs may be configured to be aperiodic (e.g., using DCI) . The second beam management procedure may include the network node 110 performing beam sweeping over one or more transmit beams. The one or more transmit beams may be a subset of all transmit beams associated with the network node 110 (e.g., determined based at least in part on measurements reported by the UE 120 in connection with the first beam management procedure) . The network node 110 may transmit a CSI-RS using each transmit beam of the one or more transmit beams for beam management. The UE 120 may measure each CSI-RS using a single (e.g., a same) receive beam (e.g., determined based at least in part on measurements performed in connection with the first beam management procedure) . The second beam management procedure may enable the network node 110 to select a best transmit beam based at least in part on measurements of the CSI-RSs (e.g., measured by the UE 120 using the single receive beam) reported by the UE 120.
[0099] As shown in Fig. 4, example 420 depicts a third beam management procedure (e.g., P3 CSI-RS beam management) . The third beam management procedure may be referred to as a beam refinement procedure, a UE beam refinement procedure, and / or a receive beam refinement procedure. As shown in Fig. 4 and example 420, one or more CSI-RSs may be configured to be transmitted from the network node 110 to the UE 120. The CSI-RSs may be configured to be aperiodic (e.g., using DCI) . The third beam management process may include the network node 110 transmitting the one or more CSI-RSs using a single transmit beam (e.g., determined based at least in part on measurements reported by the UE 120 in connection with the first beam management procedure and / or the second beam management procedure) . To enable the UE 120 to perform receive beam sweeping, the network node may use a transmit beam to transmit (e.g., with repetitions) CSI-RS at multiple times within the same RS resource set so that UE 120 can sweep through one or more receive beams in multiple transmission instances. The one or more receive beams may be a subset of all receive beams associated with the UE 120 (e.g., determined based at least in part on measurements performed in connection with the first beam management procedure and / or the second beam management procedure) . The third beam management procedure may enable the network node 110 and / or the UE 120 to select a best receive beam based at least in part on reported measurements received from the UE 120 (e.g., of the CSI-RS of the transmit beam using the one or more receive beams) .
[0100] Beam management involves decision making and signaling by the network entity that adds latency. In some aspects, a UE may initiate beam reports (CSI reports) . For example, the UE may detect a triggering event, such as the quality of a current beam falling below a threshold (Event 1) , the quality of a new beam being a threshold better than the quality of a current beam (Event 2) , the quality of a new beam being better than a threshold (Event 3) , or the quality of a current beam being worse than a new beam by a threshold (Event 4) . The UE may transmit a CSI report based at least in part on detection of the triggering event. The UE may switch beams or provide the CSI report without being triggered by the network entity. UE-initiated beam management reduces the latency and overhead involved with the network signaling for beam reporting.
[0101] With UE-initiated or event-driven beam reporting, a UE may transmit a first PUCCH message to inform a network entity (e.g., a gNB) to schedule or prepare for reception of a second UL channel or resource with the beam report. The PUCCH message may include a scheduling request (SR) . For UE-initiated / event-driven beam reporting, two modes are supported, Mode A or Mode B. Mode A may involve a gNB dynamically scheduling UCI. At step 1, a UE transmits a first PUCCH (one-bit / multi-bit) to request a resource of a second UL channel to carry the beam report. The UE may request a format (e.g., SR, UCI type) . At step 2, the UE detects the DCI format to indicate the resource to the carry beam report. At step 3, the UE transmits the beam report in the resource. The resource for the second UL channel may be a PUCCH, a PUSCH, or both.
[0102] Mode B may involve UCI in a preconfigured resource for the second UL channel. At step 1, the UE transmits a first PUCCH (one-bit / multi-bit) notifying the resource to carry a beam report. A notification format may include an SR or a new UCI type. At step 2, the UE transmits the beam report in the resource. The resource for the second UL channel may be a PUCCH, a PUSCH, or both. The notification with the first PUCCH message in step 1 is in a separate reporting instance from the beam report in step 2. Cross-component carrier (CC) beam reporting may be supported for both modes.
[0103] A CSI report configuration may be a layer 1 (L1) CSI report configuration and may indicate periodic PUSCH or PUCCH resources, a semi-persistent PUCCH, a semi-persistent PUSCH, or an aperiodic PUSCH or PUCCH. A network entity may request CSI (e.g., via a CSI-AperiodicTriggerStateList message) . The CSI report configuration may be defined for a gNB-triggered CSI report. In some aspects, the CSI report configuration may be defined for UE-initiated beam reporting.
[0104] In some aspects, the UE may be configured for UE-initiated beam reporting, with an enhanced L1 CSI report configuration that indicates a resource for a first PUCCH message. The first PUCCH message may indicate whether an event is detected by the UE. The resource for the first PUCCH may be associated with a set of PUCCH occasions used for transmission of the beam report.
[0105] In some aspects, the first PUCCH resource may be configured under the L1 CSI report configuration (e.g., CSI-ReportConfig) . The L1 CSI report configuration may be associated with an event. The L1 CSI report configuration may include an identifier (ID) that is associated with an event configuration. In some aspects, the first PUCCH resource may be configured under a report configuration type (e.g., reportConfigType) in the CSI-ReportConfig. However, it is not clear which reference signal resource is to be used for measurement of a current beam.
[0106] Set B beams include beams for measurement, or measured beams. Set A beams include beams targeted for prediction. Set A may have more beams than Set B, and Set B may be a subset of Set A. However, the UE will not measure all of the Set A beams. The UE may first try to predict which Set A beams are more optimal and then focus on the predicted Set A beams that are expected to better than the Set A beams. Data collected from Set B may be used in relation to Set A for AI training purposes. In an example, a network entity (e.g., gNB) instructs a UE to measure and report the RSRP from the 16 beams in Set B. Separately, the network entity may have a configuration for Set A, which includes a wider set of 64 beams. This larger set is used for more detailed measurement and AI model training. The UE performs the measurements and sends the data back to the network entity, which uses this information to associate the results from Set B to Set A. This association is used to train the AI model, where RSRP measurements are the input and the best beam ID from Set A is the desired output.
[0107] As indicated above, Fig. 4 is provided as an example of beam management procedures. Other examples of beam management procedures may differ from what is described with respect to Fig. 4. For example, the UE 120 and the network node 110 may perform the third beam management procedure before performing the second beam management procedure, and / or the UE 120 and the network node 110 may perform a similar beam management procedure to select a UE transmit beam.
[0108] Fig. 5 is a diagram illustrating an example 500 of a timeline for reporting CSI, in accordance with the present disclosure.
[0109] A PDCCH 502 may trigger one or more aperiodic CSI (AP-CSI) reports associated with an aperiodic channel measurement resource (AP-CMR) 504 and / or an aperiodic interference measurement resource (AP-IMR) 506. An AP-CSI report may be included in a PDSCH 508. For the nth AP-CSI report associated with an AP-CMR or an AP-IMR triggered by DCI, the UE may only provide a valid AP-CSI report if the first uplink symbol to carry the AP-CSI report starts no earlier than at symbol Zref, and the first uplink symbol to carry the nth AP-CSI report starts no earlier than at symbol Z′ref (n) . The effect of a timing advance (TA) may be considered in each case. Zref may be the next uplink symbol with its cyclic prefix (CP) starting a CSI processing time Tproc, CSI after the end of the last symbol of the PDCCH carrying the DCI. Z′ref (n) may be the next uplink symbol with its CP starting T′proc, CSI after the end of the last symbol of the latest of AP-CMR / AP-IMR. If the first uplink symbol to carry the AP-CSI report triggered by the DCI starts later than Zref for feedback via PUSCH, the UE may ignore the DCI if no hybrid automatic repeat request (HARQ) acknowledgement (ACK) or TB is multiplexed on the PUSCH. If the first uplink symbol to carry the AP-CSI report triggered by the DCI starts later than Z′ref (n) for feedback via PUSCH, the UE may ignore the DCI if the number of triggered reports is only one and no HARQ-ACK / TB is multiplexed on the PUSCH. Otherwise, the UE may not be required to update the AP-CSI report.
[0110] and where M is the number of updated CSI reports according to CSI priority rules. Z (m) and Z′ (m) may correspond to the mth updated CSI report. The values of Z and Z’ may be based on a subcarrier spacing (SCS) and may be associated with communications on the PDCCH, CMRs / IMRs, and communications on the PUSCH. The values of Z and Z’ may be based on a field (e.g., reportQuantity) of the CSI report, which may include, for example, a Type-I / Type-II precoding matrix indicator (PMI) , a CQI, and / or an RSRP / SINR. The values of Z and Z’ may be based on the number of CSI-RS reports for PMI feedback (whether the report is a wideband PMI or subband-specific PMIs) and / or UE reported capabilities for RSRP / SINR feedback.
[0111] AI / ML may occasionally identify a Top-1 beam whose actual L1-RSRP is low (due to prediction errors) . If a network entity completely trusts a UE-predicted and reported Top-1 beam that has prediction errors, and the network entity uses the beam for PDSCH scheduling via OLLA, the throughput might be interrupted due to the prediction errors. Particularly, legacy OLLA algorithms may decrease the MCS quickly when a high BLER is observed, and the MCS may only increase gradually. Therefore, although prediction errors may occur occasionally, throughput interruption may last longer than a duration of the prediction errors.
[0112] Some solutions may attempt to address the effects of the prediction errors. For example, the network entity may additionally transmit the UE predicted beams via AP-CSI-RSs and request the UE to feed back the actual measurement based CQIs associated with such CSI-RSs. Also, the MCS may be directly determined via close-loop link adaptation instead of OLLA. However, the issue is that there may be multiple UEs in a single cell operating via AI / ML based beam prediction. The network entity may eventually need to transmit almost all of the narrow-beams at each prediction cycle. Therefore, overhead consumption is similar to that of cell-common CSI-RSs that are transmitted for all candidate beams.
[0113] Another solution may be to develop dedicated OLLA algorithms for UEs operating with prediction-based L1-RSRP reporting. However, the behavior or distributions of prediction errors can be varied across different environments, locations, UE moving / rotation speeds, and different UE vendors / modules. Therefore, simply relying on network-side OLLA algorithm enhancement may not fully resolve the issue. Furthermore, no obvious improvement is observed when sweeping among other MCS increase / decrease parameter combinations together with target BLER values.
[0114] As indicated above, Fig. 5 is provided as an example. Other examples may differ from what is described with regard to Fig. 5.
[0115] Fig. 6 is a diagram illustrating an example 600 of prediction for reporting, in accordance with the present disclosure.
[0116] According to various aspects described herein, UE-side beam prediction may be included with measurement-based CQI reporting in a single CSI reporting step, instead of two reporting steps. The UE may identify the target beams to be measured via AI / ML, focus on the prediction results for measurement, and calculate CQIs. The final CSI report (e.g., reportQuantity) may include only CQIs of predicted beams. The network entity may use close-loop link adaptation (rather than OLLA) to determine the MCS. As a result, the OLLA problems described above may be solved. In contrast with a previous solution, DCI overhead or latency for scheduling the first step L1-RSRP prediction can be reduced or removed because the network entity may eventually not use such information for downlink scheduling. As a result, signaling resources are conserved and throughput is increased. With a large number of UEs operating via beam prediction, all candidate prediction target beams may be transmitted in a cell-common manner (via CSI-RSs or narrow-beams that are a subset of the SSBs) .
[0117] In some aspects, AI / ML functionality / model information and / or Set A and Set B beams may be signaled for measurement-based CSI reports (apart from prediction-based CSI reports) . Timeline rules and / or capabilities may be indicated considering the gap between Set B beams or a gap between an AP-CSI report triggering command (e.g., DCI) and cell-common CSI-RSs, allowing the UE to properly process AI / ML algorithms and identify the target beams to be measured.
[0118] Example 600 shows joint prediction and measurement-based CQI reporting. A UE may be scheduled for a CSI report 612 whose CMRs include two groups of downlink reference signal (DL-RS) resources configured via SSB / CSI-RS resources. At a given reporting occasion, a first group of DL-RSs may be transmitted before a second group of DL-RSs, in the temporal domain. The second group of DL-RSs may be with Set A beams 604 while the first group of DL-RSs may be with Set B beams 602. A network entity may transmit all of the DL-RSs on the Set A beams 604, but the UE does not measure all of the DL-RSs on the Set A beams 604. At a given reporting occasion, the UE may predict resources that are a subset 614 of the Set A beams 604 associated with second group of DL-RSs, based at least in part on measurements 606 of the first group of DL-RSs (e.g., L1-RSRP measurements, L1-SINRs, channel impulse responses (CIRs) , angles of arrival (AoAs) , and / or angles of departure (AoDs) ) . The predicted resources may be further based at least in part on measurements 608 predicted by AI / ML. The predicted resources may be associated with predicted resource IDs.
[0119] The CSI report 612 may include CQIs of the predicted resources of the second group of DL-RSs (and indicate the predicted resource IDs of the predicted resources) . The CQIs determined for the predicted resources may be calculated via actual measurements 610 of the predicted resources (measurements of the DL-RSs associated with the subset 614) . Optionally, the UE may predict the resources based at least in part on historical measurements of predicted resources in the second group of DL-RSs from previous reporting occasions. A prediction may be based at least in part on whether the second group of DL-RSs are periodic (P) or semi-periodic (SP) CSI-RSs or SSBs.
[0120] In some aspects, only a single DL-RS in the second group of DL-RSs and its measured CQI may be addressed in a CSI payload of the CSI report 612. Alternatively, a CSI report setting associated with the CSI report 612 may indicate a specific quantity of DL-RSs in the second group of DL-RSs to be addressed in the CSI report payload, and / or to be considered for actual measurements. A network entity may indicate a new report quantity for CSI reports that specifies the UE behavior (e.g., CRI-RI-CQI-Predict or SSBRI-CQI-Predict) .
[0121] In some aspects, the network entity may indicate AI / ML functionality and / or model IDs to be used for the prediction associated with the CSI report 612. An associated AI / ML functionality or model ID may be an ID that identifies network-side additional conditions across training and inference for a UE-sided model and with UE assumptions associated with AI / ML life cycle management (e.g., data collection, training, deployment, inference, performance monitoring, activation, deactivation, switching) . Examples of network-side additional conditions for beam prediction may include a number, ordering, or indexing of Set A and Set B beams, absolute or relative pointing directions (e.g., with respect to boresight direction relative to the center of transmit antenna panel) , beam shapes (i.e., angular specific beam forming gains) , quasi-co-location (QCL) relationships across / within Set A / Set B beams, and / or temporal parameters (e.g., periodicity of Set A / Set B beams, target future occasions for temporal prediction) .
[0122] The network entity may indicate the AI / ML functionality and / or model IDs in a CSI report setting, a CSI resource setting, or a CSI-RS / SSB resource set via RRC signaling, a MAC-CE activating the CSI report 612, or a MAC-CE activating SP CSI-RS resources involved in the CSI report 612. The network entity may indicate the AI / ML functionality and / or model IDs via RRC signaling (e.g., CSI-AssociatedReportConfigInfo) for AP CSI reports. When signaling the AI / ML functionality and / or model IDs via the above signaling schemes, the network entity may also signal the measurement types (e.g., out of an L1-RSRP, an L1-SINR, a CIR, an AoA, and / or an AoD) to be used to derive the predicted resources.
[0123] The network entity may also indicate an association between the first group of DL-RSs and the second group of DL-RSs. The association may include absolute or relative beam pointing directions, absolute or relative beam-widths, and / or QCL relationships.
[0124] Note that rather than the CSI report 612 being purely prediction-based (e.g., predicted L1-RSRP or Top-K beams) , the CSI report 612 may be a mixture of prediction and measurement (e.g., the resource IDs are predicted but their CQIs are measured) . This mixture may also be referred to as “joint prediction and measurement-based CQI reporting” .
[0125] As indicated above, Fig. 6 is provided as an example. Other examples may differ from what is described with regard to Fig. 6.
[0126] Fig. 7 is a diagram illustrating an example 700 associated with joint prediction and measurement-based CQI reporting, in accordance with the present disclosure. As shown in Fig. 7, a network entity 710 (e.g., network node 110) and a UE 720 (e.g., UE 120) may communicate with one another via a wireless network (e.g., wireless communication network 100) .
[0127] As shown by reference number 725, the network entity 710 may transmit (and the UE 720 may receive) a configuration or resource setting. The network entity 710 may transmit (and the UE 720 may receive) the configuration or resource setting via DCI, RRC signaling, or a MAC-CE. The network entity 710 may provide an indication (e.g., in the configuration or resource setting) of a measurement type for the prediction of the channel characteristics. The configuration or resource setting may be associated with reporting CSI using predicted channel characteristics. The predicted channel characteristics may include a predicted signal strength (e.g., predicted L1-RSRPs or SINRs) , a predicted top resource (e.g., predicted Top-K resource IDs) , a predicted probability of being a top resource (e.g., predicted probabilities of being a Top-1 resource or Top-K resources with respect to an L1-RSRP or SINR) , or a combination thereof. In some aspects, the configuration or resource setting may indicate one or more AI / ML functionalities or models for predicting channel characteristics. In some aspects, the configuration or resource setting may indicate an association between a first group of resources (of Set B beams) and a second group of resources (of Set A beams) . As shown by reference number 730, the network entity 710 may transmit (and the UE 720 may receive) scheduling information (e.g., in DCI) for a CSI report. As shown by reference number 735, the network entity 710 may transmit a MAC-CE (e.g., that activates a group of resources indicated by the scheduling information) .
[0128] The network entity 710 may transmit DL-RSs of the first group of resources. As shown by reference number 740, the UE 720 may measure at least one of the DL-RSs. In some aspects, the UE 720 may obtain an indication (e.g., via signaling or stored configuration information) of a minimum time duration between a last symbol of DCI triggering the CSI report and a first symbol of a measurable reference signal of the second group of resources. The UE 720 may measure a reference signal of the second group of resources (e.g., DL-RSs) based at least in part on a time duration between the last symbol of the DCI triggering the CSI report and the first symbol of the measurable reference signal of the second group of resources satisfying the minimum time duration.
[0129] As shown by reference number 745, the UE 720 may predict channel characteristics of the second group of resources based at least in part on measurements of the first group of resources. In some aspects, the UE 720 may predict the channel characteristics further based at least in part on historical measurements of the second group of resources (e.g., of previous reporting occasions) . In some aspects, the UE may obtain an indication of a minimum time duration between a last symbol in a most recent measurement occasion of the first group of resources and a first symbol of a most recent measurement occasion of the second group of resources. The UE 720 may predict the channel characteristics based at least in part on the measurements of the first group of resources, and based at least in part on a time duration between a last symbol of the first group of resources and a first symbol of the second group of resources satisfying the minimum time duration (e.g., being equal to or greater than the minimum time duration) .
[0130] As shown by reference number 750, the UE 720 may identify a preferred set of reference signals from among the second group of resources based at least in part on the predicted channel characteristics. The UE 720 may measure the preferred set of reference signals. As shown by reference number 755, the UE 720 may transmit (and the network entity 710 may receive) a set of CQIs (one or more CQIs) for the preferred set of reference signals. Each CQI may correspond to a respective preferred reference signal. Note that all of the second group of resources may be transmitted.
[0131] As indicated above, Fig. 7 is provided as an example. Other examples may differ from what is described with regard to Fig. 7.
[0132] Fig. 8 is a diagram illustrating an example 810 of a minimum time duration associated with prediction for CSI reporting, in accordance with the present disclosure.
[0133] Example 800 shows an AI / ML inference period 802 between the first group of DL-RSs (Set B beams 602) and the second group of DL-RSs (Set A beams 604) . There may be some latency (AI / ML inference period 802) that is expected in order to predict the Top-K Set A beams that are to actually be measured for CQI calculation. In some aspects, there may be a restriction on a time duration from Set B beams 602 to Set A beams 604. At a given CSI reporting occasion, there may be a minimum time duration 812 (shown in example 810) between the last symbol of a DL-RS in the first group of DL-RSs in its most recent measurement occasion before the CSI reference resource with respect to the CSI reporting occasion, and the first symbol of the second group of DL-RSs in its most recent measurement occasion before the CSI reference resource with respect to the CSI reporting occasion. The minimum time duration 812 may be based at least in part on defined standard or stored configuration information, which may be defined separately for different SCSs, different AI / ML functionality / model IDs, and / or different types / combinations / numbers of the first group of DL-RSs and the second group of DL-RSs. The minimum time duration 812 may be based at least in part on UE capability reporting, which may be optionally reported separately for different SCSs, different AI / ML functionality / model IDs, and / or different types / combinations / numbers of the first group of DL-RSs and the second group of DL-RSs.
[0134] In some aspects, at the considered CSI reporting occasion, the UE may not use measurement results on a DL-RS in the first group of DL-RSs to derive the predicted resources in the second group of DL-RSs, if a time duration between the last symbol of the DL-RS in the first group of DL-RSs and the first symbol of the second group of DL-RSs both before the CSI reference resource with respect to the CSI reporting occasion exceeds the minimum time duration 812. Example 810 shows two Set B beams 814 for which measurements of the DL-RSs may not be used as prediction inputs for the current reporting occasion (but can be used for subsequent reporting occasions) . Nevertheless, the UE may still measure the considered DL-RS in the first group of DL-RSs, to be used for prediction associated with later prediction or reporting occasions.
[0135] As indicated above, Fig. 8 is provided as an example. Other examples may differ from what is described with regard to Fig. 8.
[0136] Fig. 9 is a diagram illustrating an example 910 of a minimum time duration associated with prediction for CSI reporting, in accordance with the present disclosure.
[0137] Example 900 shows an AI / ML inference period 904 between the DCI 902 triggering an AP CSI report and the first symbol of a measurable DL-RS in the second group of DL-RSs in its most recent measurement occasion before the CSI reference resource with respect to the CSI reporting occasion for the CSI report 612. The UE may only trigger AI / ML inference after receiving the DCI 902 (although measurements on the Set B beams 602 can be carried out before the AI / ML inference) . In some aspects, there may be a restriction on a time duration from the DCI 902 to the Set A beams 604. At a given CSI reporting occasion, there may be a minimum time duration between the last symbol of the DCI 902 and the first symbol of the second group of DL-RSs in its most recent measurement occasion before the CSI reference resource with respect to the CSI reporting occasion. The minimum time duration 912 (shown in example 910) may be based at least in part on defined standard or stored configuration information, which may be defined separately for different SCSs, different AI / ML functionality / model IDs, and / or different types / combinations / numbers of the first group of DL-RSs and the second group of DL-RSs. The minimum time duration 912 may be based at least in part on UE capability reporting, which may be reported separately for different SCSs, different AI / ML functionality / model IDs, and / or different types / combinations / numbers of the first group of DL-RSs and the second group of DL-RSs.
[0138] In some aspects, at the considered CSI reporting occasion, the UE may not measure a DL-RS in the second group of DL-RSs and determine its CQI, if a time duration between the last symbol of the DCI 902 and the first symbol of the second group of DL-RSs before the CSI reference resource with respect to the CSI reporting occasion exceeds the minimum time duration 912. Beams 914 are within the minimum time duration 912. Even if the beams 914 are among the Top-K predicted Set A beams, the UE may not measure DL-RSs of the beams 914 due to timeline restrictions.
[0139] In some aspects, the UE may be allowed to report an inaccurate CQI, if the DL-RS in the second group of DL-RSs is expected to be addressed in the CSI report, because the UE prediction results identified that the DL-RS is to be addressed. Since the minimum time duration 912 is aligned between the network entity and the UE, the network entity may have information that the reported CQI of the DL-RS in the second group of DL-RSs is not to be trusted. It is then up to the network entity to decide how to proceed. By using the minimum time duration, the UE may report more accurate CQIs, which improves communications. As a result, signaling resources are conserved and throughput is increased.
[0140] As indicated above, Fig. 9 is provided as an example. Other examples may differ from what is described with regard to Fig. 9.
[0141] Fig. 10 is a diagram illustrating an example process 1000 performed, for example, at a UE or an apparatus of a UE, in accordance with the present disclosure. Example process 1000 is an example where the apparatus or the UE (e.g., UE 120, UE 720) performs operations associated with prediction for CSI reporting.
[0142] As shown in Fig. 10, in some aspects, process 1000 may include receiving scheduling information for a CSI report (block 1010) . For example, the UE (e.g., using reception component 1202 and / or communication manager 1206, depicted in Fig. 12) may receive scheduling information for a CSI report, as described above.
[0143] As further shown in Fig. 10, in some aspects, process 1000 may include predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources (block 1020) . For example, the UE (e.g., using communication manager 1206, depicted in Fig. 12) may predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources, as described above.
[0144] As further shown in Fig. 10, in some aspects, process 1000 may include identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics (block 1030) . For example, the UE (e.g., using communication manager 1206, depicted in Fig. 12) may identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics, as described above.
[0145] As further shown in Fig. 10, in some aspects, process 1000 may include transmitting the CSI report with a set of CQIs for the preferred set of reference signals (block 1040) . For example, the UE (e.g., using transmission component 1204 and / or communication manager 1206, depicted in Fig. 12) may transmit the CSI report with a set of CQIs for the preferred set of reference signals, as described above.
[0146] Process 1000 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.
[0147] In a first aspect, the channel characteristics include a predicted signal strength, a predicted top resource, a predicted probability of being a top resource, or a combination thereof.
[0148] In a second aspect, alone or in combination with the first aspect, the set of CQIs are based at least in part on measurements of the preferred set of reference signals.
[0149] In a third aspect, alone or in combination with one or more of the first and second aspects, the CSI report indicates the preferred set of reference signals.
[0150] In a fourth aspect, alone or in combination with one or more of the first through third aspects, the first group of resources are associated with Set B beams, and the second group of resources are associated with Set A beams.
[0151] In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, predicting the channel characteristics includes predicting the channel characteristics further based at least in part on historical measurements of the second group of resources.
[0152] In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, process 1000 includes receiving a configuration for reporting CSI using predicted channel characteristics.
[0153] In a seventh aspect, alone or in combination with one or more of the first through sixth aspects, process 1000 includes receiving, via radio resource control signaling, a configuration or a resource setting that indicates an AI / ML functionality or model to be used for prediction of the channel characteristics.
[0154] In an eighth aspect, alone or in combination with one or more of the first through seventh aspects, process 1000 includes receiving a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an AI / ML functionality or model to be used for prediction of the channel characteristics.
[0155] In a ninth aspect, alone or in combination with one or more of the first through eighth aspects, process 1000 includes receiving an indication of a measurement type for prediction of the channel characteristics.
[0156] In a tenth aspect, alone or in combination with one or more of the first through ninth aspects, process 1000 includes receiving, via RRC signaling, a configuration or a resource setting that indicates an association between the first group of resources and the second group of resources.
[0157] In an eleventh aspect, alone or in combination with one or more of the first through tenth aspects, process 1000 includes receiving a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0158] In a twelfth aspect, alone or in combination with one or more of the first through eleventh aspects, process 1000 includes obtaining an indication of a minimum time duration between a last symbol in a most recent measurement occasion of the first group of resources and a first symbol of a most recent measurement occasion of the second group of resources.
[0159] In a thirteenth aspect, alone or in combination with one or more of the first through twelfth aspects, predicting the channel characteristics includes predicting the channel characteristics for the second group of resources based at least in part on the measurements of the first group of resources, and based at least in part on a time duration between a last symbol of the first group of resources and a first symbol of the second group of resources satisfying the minimum time duration.
[0160] In a fourteenth aspect, alone or in combination with one or more of the first through thirteenth aspects, process 1000 includes obtaining an indication of a minimum time duration between a last symbol of DCI triggering the CSI report and a first symbol of a measurable reference signal of the second group of resources.
[0161] In a fifteenth aspect, alone or in combination with one or more of the first through fourteenth aspects, process 1000 includes measuring a reference signal of the second group of resources based at least in part on a time duration between the last symbol of the DCI triggering the CSI report and the first symbol of the measurable reference signal of the second group of resources satisfying the minimum time duration.
[0162] Although Fig. 10 shows example blocks of process 1000, in some aspects, process 1000 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 10. Additionally, or alternatively, two or more of the blocks of process 1000 may be performed in parallel.
[0163] Fig. 11 is a diagram illustrating an example process 1100 performed, for example, at a network entity or an apparatus of a network entity, in accordance with the present disclosure. Example process 1100 is an example where the apparatus or the network entity (e.g., network node 110, network entity 710) performs operations associated with prediction for CSI reporting.
[0164] As shown in Fig. 11, in some aspects, process 1100 may include transmitting a configuration or a resource setting that indicates an ML functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources (block 1110) . For example, the network entity (e.g., using transmission component 1304 and / or communication manager 1306, depicted in Fig. 13) may transmit a configuration or a resource setting that indicates a ML functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources, as described above.
[0165] As further shown in Fig. 11, in some aspects, process 1100 may include transmitting scheduling information for a CSI report (block 1120) . For example, the network entity (e.g., using transmission component 1304 and / or communication manager 1306, depicted in Fig. 13) may transmit scheduling information for a CSI report, as described above.
[0166] As further shown in Fig. 11, in some aspects, process 1100 may include receiving the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources (block 1130) . For example, the network entity (e.g., using reception component 1302 and / or communication manager 1306, depicted in Fig. 13) may receive the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources, as described above.
[0167] Process 1100 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.
[0168] In a first aspect, transmitting the configuration or setting includes transmitting the configuration or setting in a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources.
[0169] In a second aspect, alone or in combination with the first aspect, the configuration or the resource setting indicates an association between the first group of resources and the second group of resources.
[0170] In a third aspect, alone or in combination with one or more of the first and second aspects, process 1100 includes transmitting a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0171] Although Fig. 11 shows example blocks of process 1100, in some aspects, process 1100 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 11. Additionally, or alternatively, two or more of the blocks of process 1100 may be performed in parallel.
[0172] Fig. 12 is a diagram of an example apparatus 1200 for wireless communication, in accordance with the present disclosure. The apparatus 1200 may be a UE, or a UE may include the apparatus 1200. In some aspects, the apparatus 1200 includes a reception component 1202, a transmission component 1204, and / or a communication manager 1206, which may be in communication with one another (for example, via one or more buses and / or one or more other components) . In some aspects, the communication manager 1206 is the communication manager 140 described in connection with Fig. 1. As shown, the apparatus 1200 may communicate with another apparatus 1208, such as a UE or a network node (such as a CU, a DU, an RU, or a base station) , using the reception component 1202 and the transmission component 1204.
[0173] In some aspects, the apparatus 1200 may be configured to perform one or more operations described herein in connection with Figs. 1-9. Additionally, or alternatively, the apparatus 1200 may be configured to perform one or more processes described herein, such as process 1000 of Fig. 10. In some aspects, the apparatus 1200 and / or one or more components shown in Fig. 12 may include one or more components of the UE described in connection with Fig. 1 and Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 12 may be implemented within one or more components described in connection with Fig. 1 and 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 one or more memories. 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 one or more controllers or one or more processors to perform the functions or operations of the component.
[0174] The reception component 1202 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 1208. The reception component 1202 may provide received communications to one or more other components of the apparatus 1200. In some aspects, the reception component 1202 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 1200. In some aspects, the reception component 1202 may include one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receive processors, one or more controllers / processors, one or more memories, or a combination thereof, of the UE described in connection with Fig. 1 and Fig. 2.
[0175] The transmission component 1204 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 1208. In some aspects, one or more other components of the apparatus 1200 may generate communications and may provide the generated communications to the transmission component 1204 for transmission to the apparatus 1208. In some aspects, the transmission component 1204 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 1208. In some aspects, the transmission component 1204 may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or a combination thereof, of the UE described in connection with Fig. 1 and Fig. 2. In some aspects, the transmission component 1204 may be co-located with the reception component 1202 in one or more transceivers.
[0176] The communication manager 1206 may support operations of the reception component 1202 and / or the transmission component 1204. For example, the communication manager 1206 may receive information associated with configuring reception of communications by the reception component 1202 and / or transmission of communications by the transmission component 1204. Additionally, or alternatively, the communication manager 1206 may generate and / or provide control information to the reception component 1202 and / or the transmission component 1204 to control reception and / or transmission of communications.
[0177] The reception component 1202 may receive scheduling information for a CSI report. The communication manager 1206 may predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources. The communication manager 1206 may identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics. The transmission component 1204 may transmit the CSI report with a set of CQIs for the preferred set of reference signals.
[0178] The reception component 1202 may receive a configuration for reporting CSI using predicted channel characteristics. The reception component 1202 may receive, via RRC signaling, a configuration or a resource setting that indicates an AI / ML functionality or model to be used for prediction of the channel characteristics.
[0179] The reception component 1202 may receive a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an AI / ML functionality or model to be used for prediction of the channel characteristics.
[0180] The reception component 1202 may receive an indication of a measurement type for prediction of the channel characteristics. The reception component 1202 may receive, via RRC signaling, a configuration or a resource setting that indicates an association between the first group of resources and the second group of resources. The reception component 1202 may receive a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0181] The reception component 1202 may obtain an indication of a minimum time duration between a last symbol in a most recent measurement occasion of the first group of resources and a first symbol of a most recent measurement occasion of the second group of resources. The reception component 1202 may obtain an indication of a minimum time duration between a last symbol of DCI triggering the CSI report and a first symbol of a measurable reference signal of the second group of resources.
[0182] The communication manager 1206 may measure a reference signal of the second group of resources based at least in part on a time duration between the last symbol of the DCI triggering the CSI report and the first symbol of the measurable reference signal of the second group of resources satisfying the minimum time duration.
[0183] The number and arrangement of components shown in Fig. 12 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. 12. Furthermore, two or more components shown in Fig. 12 may be implemented within a single component, or a single component shown in Fig. 12 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 12 may perform one or more functions described as being performed by another set of components shown in Fig. 12.
[0184] Fig. 13 is a diagram of an example apparatus 1300 for wireless communication, in accordance with the present disclosure. The apparatus 1300 may be a network entity, or a network entity may include the apparatus 1300. In some aspects, the apparatus 1300 includes a reception component 1302, a transmission component 1304, and / or a communication manager 1306, which may be in communication with one another (for example, via one or more buses and / or one or more other components) . In some aspects, the communication manager 1306 is the communication manager 150 described in connection with Fig. 1. As shown, the apparatus 1300 may communicate with another apparatus 1308, such as a UE or a network node (such as a CU, a DU, an RU, or a base station) , using the reception component 1302 and the transmission component 1304.
[0185] In some aspects, the apparatus 1300 may be configured to perform one or more operations described herein in connection with Figs. 1-9. Additionally, or alternatively, the apparatus 1300 may be configured to perform one or more processes described herein, such as process 1100 of Fig. 11. In some aspects, the apparatus 1300 and / or one or more components shown in Fig. 13 may include one or more components of the network entity described in connection with Fig. 1 and Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 13 may be implemented within one or more components described in connection with Fig. 1 and 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 one or more memories. 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 one or more controllers or one or more processors to perform the functions or operations of the component.
[0186] The reception component 1302 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 1308. The reception component 1302 may provide received communications to one or more other components of the apparatus 1300. In some aspects, the reception component 1302 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 1300. In some aspects, the reception component 1302 may include one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receive processors, one or more controllers / processors, one or more memories, or a combination thereof, of the network entity described in connection with Fig. 1 and Fig. 2.
[0187] The transmission component 1304 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 1308. In some aspects, one or more other components of the apparatus 1300 may generate communications and may provide the generated communications to the transmission component 1304 for transmission to the apparatus 1308. In some aspects, the transmission component 1304 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 1308. In some aspects, the transmission component 1304 may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or a combination thereof, of the network entity described in connection with Fig. 1 and Fig. 2. In some aspects, the transmission component 1304 may be co-located with the reception component 1302 in one or more transceivers.
[0188] The communication manager 1306 may support operations of the reception component 1302 and / or the transmission component 1304. For example, the communication manager 1306 may receive information associated with configuring reception of communications by the reception component 1302 and / or transmission of communications by the transmission component 1304. Additionally, or alternatively, the communication manager 1306 may generate and / or provide control information to the reception component 1302 and / or the transmission component 1304 to control reception and / or transmission of communications.
[0189] The transmission component 1304 may transmit a configuration or a resource setting that indicates an AI / ML functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources. The transmission component 1304 may transmit scheduling information for a CSI report. The reception component 1302 may receive the CSI report with a set of CQIs for a preferred set of reference signals among the second group of resources.
[0190] The transmission component 1304 may transmit a MAC-CE that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0191] The number and arrangement of components shown in Fig. 13 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. 13. Furthermore, two or more components shown in Fig. 13 may be implemented within a single component, or a single component shown in Fig. 13 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 13 may perform one or more functions described as being performed by another set of components shown in Fig. 13.
[0192] The following provides an overview of some Aspects of the present disclosure:
[0193] Aspect 1: A method of wireless communication performed by a user equipment (UE) , comprising: receiving scheduling information for a channel state information (CSI) report; predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources; identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics; and transmitting the CSI report with a set of channel quality indicators (CQIs) for the preferred set of reference signals.
[0194] Aspect 2: The method of Aspect 1, wherein the channel characteristics include a predicted signal strength, a predicted top resource, a predicted probability of being a top resource, or a combination thereof.
[0195] Aspect 3: The method of any of Aspects 1-2, wherein the set of CQIs are based at least in part on measurements of the preferred set of reference signals.
[0196] Aspect 4: The method of any of Aspects 1-3, wherein the CSI report indicates the preferred set of reference signals.
[0197] Aspect 5: The method of any of Aspects 1-4, wherein the first group of resources are associated with Set B beams, and the second group of resources are associated with Set A beams.
[0198] Aspect 6: The method of any of Aspects 1-5, wherein predicting the channel characteristics includes predicting the channel characteristics further based at least in part on historical measurements of the second group of resources.
[0199] Aspect 7: The method of any of Aspects 1-6, further comprising receiving a configuration for reporting CSI using predicted channel characteristics.
[0200] Aspect 8: The method of any of Aspects 1-7, further comprising receiving, via radio resource control signaling, a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of the channel characteristics.
[0201] Aspect 9: The method of any of Aspects 1-8, further comprising receiving a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources and that indicates a machine learning functionality or model to be used for prediction of the channel characteristics.
[0202] Aspect 10: The method of any of Aspects 1-9, further comprising receiving an indication of a measurement type for prediction of the channel characteristics.
[0203] Aspect 11: The method of any of Aspects 1-10, further comprising receiving, via radio resource control signaling, a configuration or a resource setting that indicates an association between the first group of resources and the second group of resources.
[0204] Aspect 12: The method of any of Aspects 1-11, further comprising receiving a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0205] Aspect 13: The method of any of Aspects 1-12, further comprising obtaining an indication of a minimum time duration between a last symbol in a most recent measurement occasion of the first group of resources and a first symbol of a most recent measurement occasion of the second group of resources.
[0206] Aspect 14: The method of Aspect 13, wherein predicting the channel characteristics includes predicting the channel characteristics for the second group of resources based at least in part on the measurements of the first group of resources, and based at least in part on a time duration between a last symbol of the first group of resources and a first symbol of the second group of resources satisfying the minimum time duration.
[0207] Aspect 15: The method of any of Aspects 1-14, further comprising obtaining an indication of a minimum time duration between a last symbol of downlink control information (DCI) triggering the CSI report and a first symbol of a measurable reference signal of the second group of resources.
[0208] Aspect 16: The method of Aspect 15, further comprising measuring a reference signal of the second group of resources based at least in part on a time duration between the last symbol of the DCI triggering the CSI report and the first symbol of the measurable reference signal of the second group of resources satisfying the minimum time duration.
[0209] Aspect 17: A method of wireless communication performed by a network entity, comprising: transmitting a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources; transmitting scheduling information for a channel state information (CSI) report; and receiving the CSI report with a set of channel quality indicators (CQIs) for a preferred set of reference signals among the second group of resources.
[0210] Aspect 18: The method of Aspect 17, wherein transmitting the configuration or setting includes transmitting the configuration or setting in a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources.
[0211] Aspect 19: The method of any of Aspects 17-18, wherein the configuration or the resource setting indicates an association between the first group of resources and the second group of resources.
[0212] Aspect 20: The method of any of Aspects 17-19, further comprising transmitting a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.
[0213] Aspect 21: An apparatus for wireless communication at a device, the apparatus comprising one or more processors; one or more memories coupled with the one or more processors; and instructions stored in the one or more memories and executable by the one or more processors to cause the apparatus to perform the method of one or more of Aspects 1-20.
[0214] Aspect 22: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors configured to cause the device to perform the method of one or more of Aspects 1-20.
[0215] Aspect 23: An apparatus for wireless communication, the apparatus comprising at least one means for performing the method of one or more of Aspects 1-20.
[0216] Aspect 24: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by one or more processors to perform the method of one or more of Aspects 1-20.
[0217] Aspect 25: 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 1-20.
[0218] Aspect 26: A device for wireless communication, the device comprising a processing system that includes one or more processors and one or more memories coupled with the one or more processors, the processing system configured to cause the device to perform the method of one or more of Aspects 1-20.
[0219] Aspect 27: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors individually or collectively configured to cause the device to perform the method of one or more of Aspects 1-20.
[0220] 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.
[0221] As used herein, the term “component” is intended to be broadly construed as hardware or a combination of hardware and at least one of software or firmware. “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, 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 or a combination of hardware and software. It will be apparent that systems or methods described herein may be implemented in different forms of hardware or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems or methods is not limiting of the aspects. Thus, the operation and behavior of the systems or methods are described herein without reference to specific software code, because those skilled in the art will understand that software and hardware can be designed to implement the systems or methods based, at least in part, on the description herein. A component being configured to perform a function means that the component has a capability to perform the function, and does not require the function to be actually performed by the component, unless noted otherwise.
[0222] 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, or not equal to the threshold, among other examples.
[0223] 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 (for example, 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) .
[0224] 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, ” and similar terms are intended to be open-ended terms that do not limit an element that they modify (for example, an element “having” A may also have B) . Further, the phrase “based on” is intended to mean “based on or otherwise in association with” 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 (for example, if used in combination with “either” or “only one of” ) . It should be understood that “one or more” is equivalent to “at least one. ”
[0225] Even though particular combinations of features are recited in the claims 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 or disclosed in the specification. The disclosure of various aspects includes each dependent claim in combination with every other claim in the claim set.
Claims
1.An apparatus for wireless communication at a user equipment (UE) , comprising:one or more memories; andone or more processors, coupled to the one or more memories, individually or collectively configured to cause the UE to:receive scheduling information for a channel state information (CSI) report;predict channel characteristics for a second group of resources based at least in part on measurements of a first group of resources;identify a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics; andtransmit the CSI report with a set of channel quality indicators (CQIs) for the preferred set of reference signals.2.The apparatus of claim 1, wherein the channel characteristics include a predicted signal strength, a predicted top resource, a predicted probability of being a top resource, or a combination thereof.3.The apparatus of claim 1, wherein the set of CQIs are based at least in part on measurements of the preferred set of reference signals.4.The apparatus of claim 1, wherein the CSI report indicates the preferred set of reference signals.5.The apparatus of claim 1, wherein the first group of resources are associated with Set B beams, and the second group of resources are associated with Set A beams.6.The apparatus of claim 1, wherein to cause the UE to predict the channel characteristics, the one or more processors are individually or collectively configured to cause the UE to predict the channel characteristics further based at least in part on historical measurements of the second group of resources.7.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive a configuration for reporting CSI using predicted channel characteristics.8.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive, via radio resource control signaling, a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of the channel characteristics.9.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources and that indicates a machine learning functionality or model to be used for prediction of the channel characteristics.10.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive an indication of a measurement type for prediction of the channel characteristics.11.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive, via radio resource control signaling, a configuration or a resource setting that indicates an association between the first group of resources and the second group of resources.12.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to receive a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources and that indicates an association between the first group of resources and the second group of resources.13.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to obtain an indication of a minimum time duration between a last symbol in a most recent measurement occasion of the first group of resources and a first symbol of a most recent measurement occasion of the second group of resources.14.The apparatus of claim 13, wherein to cause the UE to predict the channel characteristics, the one or mor processors are individually or collectively configured to cause the UE to predict the channel characteristics for the second group of resources based at least in part on the measurements of the first group of resources, and based at least in part on a time duration between a last symbol of the first group of resources and a first symbol of the second group of resources satisfying the minimum time duration.15.The apparatus of claim 1, wherein the one or more processors are individually or collectively configured to cause the UE to obtain an indication of a minimum time duration between a last symbol of downlink control information (DCI) triggering the CSI report and a first symbol of a measurable reference signal of the second group of resources.16.The apparatus of claim 15, wherein the one or more processors are individually or collectively configured to cause the UE to measure a reference signal of the second group of resources based at least in part on a time duration between the last symbol of the DCI triggering the CSI report and the first symbol of the measurable reference signal of the second group of resources satisfying the minimum time duration.17.An apparatus for wireless communication at a network entity, comprising:one or more memories; andone or more processors, coupled to the one or more memories, individually or collectively configured to cause the network entity to:transmit a configuration or a resource setting that indicates a machine learning functionality or model to be used for prediction of channel characteristics of a second group of resources based at least in part on measurements of a first group of resources;transmit scheduling information for a channel state information (CSI) report; andreceive the CSI report with a set of channel quality indicators (CQIs) for a preferred set of reference signals among the second group of resources.18.The apparatus of claim 17, wherein to cause the network entity to transmit the configuration or setting, the one or more processors are individually or collectively configured to cause the network entity to transmit the configuration or setting in a medium access control control element that activates the CSI report, the first group of resources, or the second group of resources.19.The apparatus of claim 17, wherein the configuration or the resource setting indicates an association between the first group of resources and the second group of resources.20.A method of wireless communication performed by a user equipment (UE) , comprising:receiving scheduling information for a channel state information (CSI) report;predicting channel characteristics for a second group of resources based at least in part on measurements of a first group of resources;identifying a preferred set of reference signals among the second group of resources based at least in part on the predicted channel characteristics; andtransmitting the CSI report with a set of channel quality indicators (CQIs) for the preferred set of reference signals.
Citation Information
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