Channel state information reporting using interference measurement resources

Abstract

Aspects of the present disclosure generally relate to wireless communications. In some aspects, a user equipment (UE) may generate a channel state information (CSI) report based at least in part on one or more virtual interference measurement resources (IMRs), each virtual IMR representing a logical resource that is used for beam management and is not transmitted. The UE may transmit the CSI report. Numerous other aspects are described.

Description

Technical Field

[0001] Aspects of the present disclosure relate generally to wireless communications, and to techniques and apparatus for channel state information reporting for interference management resources. Background Art

[0002] Wireless communication systems are widely deployed to provide a variety of telecommunication services, such as telephony, video, data, messaging, and broadcasting. Typical wireless communication systems may employ multiple access technologies that can support communication with multiple users by sharing available system resources (e.g., bandwidth, transmit power, etc.). Examples of such multiple access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single carrier frequency division multiple access (SC-FDMA) systems, time division synchronous code division multiple access (TD-SCDMA) systems, and long term evolution (LTE). LTE / LTE-Advanced is a set of enhancements to the Universal Mobile Telecommunications System (UMTS) mobile standard promulgated by the Third Generation Partnership Project (3GPP).

[0003] A wireless network may include one or more network nodes that support communications for wireless communication devices, such as user equipment (UE) or multiple UEs. A UE may communicate with a network node via downlink communications and uplink communications. A "downlink" (or "DL") refers to a communication link from a network node to a UE, and an "uplink" (or "UL") refers to a communication link from a UE to a network node. Some wireless networks may support device-to-device communications, such as via a local link (e.g., a side link (SL), a wireless local area network (WLAN) link, and / or a wireless personal area network (WPAN) link, etc.).

[0004] The above-mentioned multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different UEs to communicate at a city, country, region and / or global level. New Radio (NR) (which may be referred to as 5G) is a set of enhancements to the LTE mobile standard promulgated by 3GPP. NR is designed to better support mobile broadband Internet access by using orthogonal frequency division multiplexing (OFDM) (CP-OFDM) with a cyclic prefix (CP) on the downlink, using CP-OFDM and / or single carrier frequency division multiplexing (SC-FDM) (also known as discrete Fourier transform spread OFDM (DFT-s-OFDM)) on the uplink, and supporting beamforming, multiple input multiple output (MIMO) antenna technology and carrier aggregation to improve spectrum efficiency, reduce costs, improve services, utilize new spectrum, and better integrate with other open standards. As the demand for mobile broadband access continues to increase, further improvements in LTE, NR and other radio access technologies remain useful. Summary of the invention

[0005] Some aspects described herein relate to a method of wireless communication performed by a user equipment (UE) or a device of a UE. The method may include generating a channel state information (CSI) report based at least in part on one or more virtual interference measurement resources (IMRs), each virtual IMR representing a logical resource that is used for beam management and is not transmitted. The method may include sending the CSI report.

[0006] Some aspects described herein relate to a method of wireless communication performed by a UE or an apparatus of a UE. The method may include: generating a CSI report based at least in part on one or more IMRs transmitted and one or more virtual channel measurement resources (CMRs), each virtual CMR representing a logical resource used for beam management and not transmitted. The method may include: transmitting the CSI report.

[0007] Some aspects described herein relate to a method of wireless communication performed by a network entity or a device of a network entity. The method may include: sending a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource used for beam management and not transmitted: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. The method may include: receiving the CSI report.

[0008] Some aspects described herein relate to a method of wireless communication performed by a network entity or an apparatus of a network entity. The method may include: sending a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent. The method may include: receiving the CSI report.

[0009] Some aspects described herein relate to an apparatus for a UE for wireless communication. The apparatus may include a memory and one or more processors, the one or more processors coupled to the memory. The one or more processors may be configured to generate a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource that is used for beam management and is not transmitted. The one or more processors may be configured to send the CSI report.

[0010] Some aspects described herein relate to an apparatus for a UE for wireless communication. The apparatus may include a memory and one or more processors, the one or more processors coupled to the memory. The one or more processors may be configured to generate a CSI report based at least in part on one or more IMRs and one or more virtual CMRs transmitted, each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The one or more processors may be configured to send the CSI report.

[0011] Some aspects described herein relate to an apparatus of a network entity for wireless communication. The apparatus may include a memory and one or more processors, the one or more processors being coupled to the memory. The one or more processors may be configured to send a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource that is used for beam management and is not transmitted: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The one or more processors may be configured to receive the CSI report.

[0012] Some aspects described herein relate to an apparatus of a network entity for wireless communication. The apparatus may include a memory and one or more processors, the one or more processors coupled to the memory. The one or more processors may be configured to send a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent. The one or more processors may be configured to receive the CSI report.

[0013] Some aspects described herein relate to a non-transitory computer-readable medium storing an instruction set for wireless communication by a UE. The instruction set, when executed by one or more processors of the UE, may cause the UE to generate a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource used for beam management and not transmitted. The instruction set, when executed by one or more processors of the UE, may cause the UE to send the CSI report.

[0014] Some aspects described herein relate to a non-transitory computer-readable medium storing an instruction set for wireless communication by a UE. The instruction set, when executed by one or more processors of the UE, may cause the UE to generate a CSI report based at least in part on one or more IMRs and one or more virtual CMRs transmitted, each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The instruction set, when executed by one or more processors of the UE, may cause the UE to transmit the CSI report.

[0015] Some aspects described herein relate to a non-transitory computer-readable medium storing an instruction set for wireless communication by a network entity. The instruction set, when executed by one or more processors of the network entity, may cause the network entity to send a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource used for beam management and not transmitted: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. The instruction set, when executed by one or more processors of the network entity, may cause the network entity to receive the CSI report.

[0016] Some aspects described herein relate to a non-transitory computer-readable medium storing an instruction set for wireless communication by a network entity. The instruction set, when executed by one or more processors of the network entity, may cause the network entity to send a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent. The instruction set, when executed by one or more processors of the network entity, may cause the network entity to receive the CSI report.

[0017] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for generating a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource used for beam management and not transmitted. The apparatus may include means for transmitting the CSI report.

[0018] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for generating a CSI report based at least in part on one or more IMRs transmitted and one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. The apparatus may include means for transmitting the CSI report.

[0019] Some aspects described herein are directed to an apparatus for wireless communication. The apparatus may include means for sending a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. The apparatus may include means for receiving the CSI report.

[0020] Some aspects described herein are directed to an apparatus for wireless communication. The apparatus may include means for sending a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent. The apparatus may include means for receiving the CSI report.

[0021] The various aspects collectively include methods, apparatus, systems, computer program products, non-transitory computer-readable media, UEs, mobile stations, base stations, network entities, network nodes, wireless communication devices and / or processing systems as fully described herein with reference to the drawings and description and as illustrated in the drawings and description.

[0022] The features and technical advantages of examples according to the present disclosure have been outlined quite extensively above so that the following specific embodiments may be better understood. Additional features and advantages will be described below. The disclosed concepts and specific examples may be easily used as a basis for modifying or designing other structures for achieving the same purpose of the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein, both in terms of their organization and method of operation, and the associated advantages will be better understood by considering the following description in conjunction with the accompanying drawings. Each of the figures in the accompanying drawings is provided for the purpose of illustration and description and not as a definition of limitations to the claims.

[0023] Although various aspects are described in the present disclosure by illustrating some examples, it will be understood by those skilled in the art that such aspects can be implemented in many different arrangements and scenarios. The technology described herein can be implemented using different platform types, devices, systems, shapes, sizes and / or packaging arrangements. For example, some aspects can be implemented via integrated chip implementations or other devices based on non-module components (e.g., end-user devices, vehicles, communication equipment, computing equipment, industrial equipment, retail / shopping equipment, medical equipment, and / or artificial intelligence devices). Various aspects can be implemented in chip-level components, modular components, non-modular components, non-chip-level components, device-level components and / or system-level components. The equipment incorporating the various aspects and features described may include additional components and features for implementing and practicing the various aspects claimed and described. For example, the transmission and reception of wireless signals may include one or more components (e.g., hardware components, including antennas, radio frequency (RF) chains, power amplifiers, modulators, buffers, processors, interleavers, adders and / or summers) for analog and digital purposes. The various aspects described herein are intended to be practiced in various devices, components, systems, distributed arrangements and / or end-user devices of various sizes, shapes and configurations. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to fully understand the above-mentioned features of the present disclosure, a more specific description of the invention briefly summarized above can be obtained by referring to various aspects (some of which are illustrated in the accompanying drawings). However, it should be noted that the accompanying drawings only illustrate certain typical aspects of the present disclosure and are therefore not to be considered as limiting the scope thereof, as the specification may admit of other equally effective aspects. The same reference numerals in different drawings may identify the same or similar elements.

[0025] Figure 1 is a diagram illustrating an example of a wireless network according to the present disclosure.

[0026] Figure 2 is a diagram illustrating an example of communication between a network node and a user equipment (UE) in a wireless network according to the present disclosure.

[0027] Figure 3 is a diagram illustrating an example decomposed base station architecture according to the present disclosure.

[0028] Figure 4 is a diagram illustrating an example of a beam management process according to the present disclosure.

[0029] Figure 5 is a diagram illustrating an example architecture of a functional framework for radio access network intelligence enabled by data collection according to the present disclosure.

[0030] Figure 6is a diagram illustrating an example of artificial intelligence or machine learning based beam management according to the present disclosure.

[0031] Fig. 7A and Figure 7B is a diagram illustrating an example associated with connections between resources for predictive beam management according to the present disclosure.

[0032] Figure 8 is a diagram illustrating an example of connection between a channel measurement resource (CMR) and an interference measurement resource (IMR) according to the present disclosure.

[0033] Fig. 9 is a diagram illustrating an example of a combination of CMR and IMR according to the present disclosure.

[0034] Fig.10 is a diagram illustrating an example associated with generating a CSI report based on a virtual IMR according to the present disclosure.

[0035] Fig.11 is a diagram illustrating an example associated with generating a CSI report based on an actual IMR according to the present disclosure.

[0036] Fig.12 is a diagram illustrating an example process performed, for example, by a UE according to the present disclosure.

[0037] Fig.13 is a diagram illustrating an example process performed, for example, by a UE according to the present disclosure.

[0038] Fig.14 is a diagram illustrating an example process performed, for example, by a network entity according to the present disclosure.

[0039] Fig.15 is a diagram illustrating an example process performed, for example, by a network entity according to the present disclosure.

[0040] Fig.16 is a diagram of an example apparatus for wireless communications according to the present disclosure.

[0041] Fig.17 is a diagram of an example apparatus for wireless communications according to the present disclosure. DETAILED DESCRIPTION

[0042] The various aspects of the present disclosure are described more fully below with reference to the accompanying drawings. However, the present disclosure can be embodied in many different forms, and should not be interpreted as being limited to any specific structure or function presented throughout the present disclosure. On the contrary, these aspects are provided so that the present disclosure will be thorough and complete, and the scope of the present disclosure will be fully conveyed to those skilled in the art. It should be understood by those skilled in the art that the scope of the present disclosure is intended to cover any aspect of the present disclosure disclosed herein, whether it is implemented independently or in combination with any other aspect of the present disclosure. For example, any number of aspects set forth herein may be used to implement a device or practice method. In addition, the scope of the present disclosure is intended to cover such a device or method that is practiced using other structures, functions, or structures and functions in addition to or different from the various aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure disclosed herein may be embodied by one or more elements of the claims.

[0043] Several aspects of telecommunication systems will now be presented with reference to various devices and techniques. These devices and techniques will be described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, components, circuits, steps, processes, algorithms, etc. (collectively referred to as "elements"). These elements can be implemented using hardware, software, or a combination thereof. Whether these elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system.

[0044] Although various aspects may be described herein using terms generally associated with 5G or new radio (NR) radio access technology (RAT), various aspects of the present disclosure may be applicable to other RATs, such as 3G RAT, 4G RAT, and / or post-5G RATs (e.g., 6G).

[0045] Figure 11 is a diagram illustrating an example of a wireless network 100 according to the present disclosure. The wireless network 100 may be a 5G (e.g., NR) network and / or a 4G (e.g., Long Term Evolution (LTE)) network, or may include elements of a 5G (e.g., NR) network and / or elements of a 4G (e.g., Long Term Evolution (LTE)) network, etc. The wireless network 100 may include one or more network nodes 110 (shown as network node 110a, network node 110b, network node 110c, and network node 110d), user equipment (UE) 120 or multiple UEs 120 (shown as UE 120a, UE 120b, UE 120c, UE 120d, and UE 120e), and / or other entities. The network node 110 is a network node that communicates with the UE 120. As shown in the figure, the network node 110 may include one or more network nodes. For example, the network node 110 may be a converged network node, which means that the converged network node is configured to utilize a radio protocol stack that is physically or logically integrated within a single radio access network (RAN) node (e.g., within a single device or unit). As another example, the network node 110 may be a decomposed network node (sometimes referred to as a decomposed base station), which means that the network node 110 is configured to utilize a protocol stack that is physically or logically distributed between two or more nodes (such as one or more central units (CUs), one or more distributed units (DUs), or one or more radio units (RUs)).

[0046] In some examples, the network node 110 is or includes a network node that communicates with the UE 120 via a radio access link, such as an RU. In some examples, the network node 110 is or includes a network node that communicates with other network nodes 110 via a fronthaul link or a midhaul link, such as a DU. In some examples, the network node 110 is or includes a network node that communicates with other network nodes 110 via a midhaul link or communicates with the core network via a backhaul link, such as a CU. In some examples, the network node 110 (such as an aggregated network node 110 or a decomposed network node 110) may include multiple network nodes, such as one or more RUs, one or more CUs, and / or one or more DUs. The network node 110 may include, for example, an NR base station, an LTE base station, a Node B, an eNB (e.g., in 4G), a gNB (e.g., in 5G), an access point, a transmit receive point (TRP), a DU, a RU, a CU, a mobility element of a network, a core network node, a network element, a network equipment, a RAN node, or a combination thereof. In some examples, network nodes 110 may be interconnected to each other or to one or more other network nodes 110 in wireless network 100 via various types of fronthaul, midhaul, and / or backhaul interfaces (such as direct physical connections, air interfaces, or virtual networks) using any suitable transport network.

[0047] In some examples, the network node 110 may provide communication coverage for a particular geographic area. In the Third Generation Partnership Project (3GPP), the term "cell" may refer to the coverage area of ​​the network node 110 and / or the network node subsystem serving the coverage area, depending on the context in which the term is used. The network node 110 may provide communication coverage for a macro cell, a pico cell, a femto cell, and / or another type of cell. A macro cell may cover a relatively large geographic area (e.g., a radius of several kilometers) and may allow unrestricted access by a UE 120 with a service subscription. A pico cell may cover a relatively small geographic area and may allow unrestricted access by a UE 120 with a service subscription. A femto cell may cover a relatively small geographic area (e.g., a home) and may allow restricted access by a UE 120 associated with the femto cell (e.g., a UE 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. The network node 110 for a femto cell may be referred to as a femto network node or a home network node. Figure 1 In the example shown, network node 110a may be a macro network node for macro cell 102a, network node 110b may be a pico network node for pico cell 102b, and network node 110c may be a femto network node for femto cell 102c. The network node may support one or more (e.g., three) cells. In some examples, the cells may not necessarily be stationary, and the geographic area of ​​the cells may move depending on the location of the mobile network node 110 (e.g., a mobile network node).

[0048] In some aspects, the term "base station" or "network node" may refer to an aggregated base station, a decomposed base station, an integrated access and backhaul (IAB) node, a relay node, or one or more components thereof. For example, in some aspects, a "base station" or "network node" may refer to a CU, a DU, a RU, a near real-time (near RT) RAN intelligent controller (RIC), or a non-real-time (non-RT) RIC, or a combination thereof. In some aspects, the terms "base station", "network node", "network entity" may refer to a device configured to perform one or more functions (such as those described herein in conjunction with the network node 110). In some aspects, the terms "base station", "network node", "network entity" may refer to a plurality of devices configured to perform one or more functions. For example, in some distributed systems, each of a large number of different devices (which may be located in the same geographic location or in different geographic locations) may be configured to perform at least a portion of a function, or to repeat the execution of at least a portion of the function, and the terms "base station", "network node", "network entity" may refer to any one or more of these different devices. In some aspects, the terms "base station", "network node", "network entity" may refer to one or more virtual base stations or one or more virtual base station functions. For example, in some aspects, two or more base station functions may be instantiated on a single device. In some aspects, the terms "base station," "network node," "network entity" may refer to one of the base station functions but not another of the base station functions. In this way, a single device may include more than one base station.

[0049] The wireless network 100 may include one or more relay stations. A relay station is a network node that can receive transmissions of data from an upstream node (e.g., a network node 110 or a UE 120) and transmit transmissions of data to a downstream node (e.g., a UE 120 or a network node 110). A relay station may be a UE 120 that is capable of relaying transmissions for other UEs 120. Figure 1 In the example shown, a network node 110d (e.g., a relay network node) may communicate with a network node 110a (e.g., a macro network node) and a UE 120d to facilitate communications between the network node 110a and the UE 120d. A network node 110 that relays communications may be referred to as a relay station, a relay base station, a relay network node, a relay node, a relay, etc.

[0050] The wireless network 100 may be a heterogeneous network that includes different types of network nodes 110, such as macro network nodes, pico network nodes, femto network nodes, relay network nodes, etc. These different types of network nodes 110 may have different transmit power levels, different coverage areas, and / or different impacts on interference in the wireless network 100. For example, a macro network node may have a high transmit power level (e.g., 5 watts to 40 watts), while a pico network node, a femto network node, and a relay network node may have a lower transmit power level (e.g., 0.1 watt to 2 watts).

[0051] The network controller 130 may be coupled to or in communication with a set of network nodes 110 and may provide coordination and control for the network nodes 110. The network controller 130 may communicate with the network nodes 110 via a backhaul communication link or a midhaul communication link. The network nodes 110 may also communicate directly with each other or indirectly via a wireless backhaul communication link or a wired backhaul communication link. In some aspects, the network controller 130 may be or may include a CU or a core network device.

[0052] UE 120 can be distributed throughout the wireless network 100, and each UE 120 can be stationary or mobile. UE 120 can include, for example, an access terminal, a terminal, a mobile station and / or a subscriber unit. UE 120 can be a cellular phone (e.g., a smart phone), a personal digital assistant (PDA), a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet computer, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device, a biometric device, a wearable device (e.g., a smart watch, smart clothing, smart glasses, a smart wristband, smart jewelry (e.g., a smart ring or a smart bracelet)), an entertainment device (e.g., a music device, a video device and / or a satellite radio), a vehicle component or sensor, a smart meter / sensor, an industrial manufacturing equipment, a global positioning system device, a UE function of a network node and / or any other suitable device configured to communicate via a wireless or wired medium.

[0053] Some UEs 120 may be considered as machine type communication (MTC) or evolved or enhanced machine type communication (eMTC) UEs. MTC UEs and / or eMTC UEs may include, for example, robots, drones, remote devices, sensors, meters, monitors, and / or location tags that may communicate with a network node, another device (e.g., a remote device), or some other entity. Some UEs 120 may be considered as Internet of Things (IoT) devices and / or may be implemented as NB-IoT (narrowband IoT) devices. Some UEs 120 may be considered as customer premises equipment. UE 120 may be included inside a housing that houses components of UE 120, such as a processor component and / or a memory component. In some examples, the processor component and the memory component may be coupled together. For example, a processor component (e.g., one or more processors) and a memory component (e.g., a memory) may be operably coupled, communicatively coupled, electronically coupled, and / or electrically coupled.

[0054] In general, any number of wireless networks 100 may be deployed in a given geographic area. Each wireless network 100 may support a specific RAT and may operate on one or more frequencies. RAT may be referred to as a radio technology, air interface, etc. Frequency may be referred to as a carrier, frequency channel, etc. Each frequency may support a single RAT in a given geographic area to avoid interference between wireless networks of different RATs. In some cases, NR or 5G RAT networks may be deployed.

[0055] In some examples, two or more UEs 120 (e.g., shown as UE 120a and UE 120e) may communicate directly (e.g., without using network node 110 as an intermediary to communicate with each other) using one or more side link channels. For example, UE 120 may communicate using peer-to-peer (P2P) communication, device-to-device (D2D) communication, vehicle-to-everything (V2X) protocols (e.g., which may include vehicle-to-vehicle (V2V) protocols, vehicle-to-infrastructure (V2I) protocols, or vehicle-to-pedestrian (V2P) protocols), and / or mesh networks. In such examples, UE 120 may perform scheduling operations, resource selection operations, and / or other operations described elsewhere herein as being performed by network node 110.

[0056] The devices of the wireless network 100 may communicate using an electromagnetic spectrum that may be subdivided into various categories, bands, channels, etc., based on frequency or wavelength. For example, the devices of the wireless network 100 may communicate using one or more operating bands. In 5G NR, two initial operating bands have been identified as frequency ranges designated FR1 (410 MHz–7.125 GHz) and FR2 (24.25 GHz–52.6 GHz). It should be understood that, although a portion of FR1 is greater than 6 GHz, FR1 is often (interchangeably) referred to as the “below 6 GHz” band in various documents and articles. A similar naming problem sometimes occurs with respect to FR2, which is often (interchangeably) referred to as the “millimeter wave” band in documents and articles, although different from the extremely high frequency (EHF) band (30 GHz–300 GHz) identified as the “millimeter wave” band by the International Telecommunication Union (ITU).

[0057] Frequencies between FR1 and FR2 are generally referred to as mid-band frequencies. Recent 5G NR research has identified the operating bands for these mid-band frequencies as frequency range designation FR3 (7.125GHz–24.25GHz). The bands falling within FR3 can inherit FR1 characteristics and / or FR2 characteristics, and thus the features of FR1 and / or FR2 can be effectively extended to mid-band frequencies. In addition, higher frequency bands are currently being explored to extend 5G NR operations to more than 52.6GHz. For example, three higher operating bands have been identified as frequency range designations FR4a or FR4-1 (52.6GHz–71GHz), FR4 (52.6GHz–114.25GHz), and FR5 (114.25GHz–300GHz). Each of these higher frequency bands falls within the EHF band.

[0058] In view of the above examples, unless otherwise specifically stated, it should be understood that if the term "below 6 GHz" or the like is used herein, the term may broadly refer to frequencies that may be lower than 6 GHz, may be within FR1, or may include mid-band frequencies. In addition, unless otherwise specifically stated, it should be understood that if the term "millimeter wave" or the like is used herein, the term may broadly refer to frequencies that may include mid-band frequencies, may be within FR2, FR4, FR4-a or FR4-1 and / or FR5, or may be within the EHF band. It is contemplated that the frequencies included in these operating bands (e.g., FR1, FR2, FR3, FR4, FR4-a, FR4-1, and / or FR5) may be modified, and the techniques described herein are applicable to those modified frequency ranges.

[0059] In some aspects, UE 120 may include a communication manager 140. As described in greater detail elsewhere herein, the communication manager 140 may generate a channel state information (CSI) report based at least in part on one or more virtual interference measurement resources (IMRs), each virtual IMR representing a logical resource that is used for beam management and is not transmitted. The communication manager 140 may transmit the CSI report.

[0060] In some aspects, the communication manager 140 may generate a CSI report based at least in part on the transmitted one or more IMRs and one or more virtual channel measurement resources (CMRs), each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The communication manager 140 may send the CSI report. Additionally or alternatively, the communication manager 140 may perform one or more other operations described herein.

[0061] In some aspects, a network entity (e.g., network node 110) may include a communication manager 150. As described in greater detail elsewhere herein, the communication manager 150 may send a configuration for generating a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource that is used for beam management and is not transmitted, and one or more of: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The communication manager 150 may receive the CSI report.

[0062] In some aspects, the communication manager 150 may send a configuration for generating a CSI report based at least in part on the transmitted one or more IMRs and one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted. The communication manager 150 may receive the CSI report. Additionally or alternatively, the communication manager 150 may perform one or more other operations described herein.

[0063] As indicated above, Figure 1 are provided as examples. Other examples can be found in the Figure 1 The examples described are different.

[0064] Figure 22 is a diagram illustrating an example 200 of a network node 110 communicating with a UE 120 in a wireless network 100 according to the present disclosure. The network node 110 may be equipped with a set of antennas 234a to 234t, such as T antennas (T≥1). The UE 120 may be equipped with a set of antennas 252a to 252r, such as R antennas (R≥1). The network node 110 of example 200 includes one or more radio frequency components, such as an antenna 234 and a modem 254. In some examples, the network node 110 may include an interface, a communication component, or another component that facilitates communication with the UE 120 or another network node. Some network nodes 110 may not include a radio frequency component that facilitates direct communication with the UE 120, such as one or more CUs or one or more DUs.

[0065] At the network node 110, the transmit processor 220 may receive data intended for the UE 120 (or a set of UEs 120) from the data source 212. The transmit processor 220 may select one or more modulation and coding schemes (MCS) for the UE 120 based at least in part on one or more channel quality indicators (CQI) received from the UE 120. The network node 110 may process (e.g., encode and modulate) the data for the UE 120 based at least in part on the MCS selected for the UE 120, and may provide data symbols for the UE 120. The transmit processor 220 may process system information (e.g., for semi-static resource allocation information (SRPI)) and control information (e.g., CQI requests, grants, and / or upper layer signaling), and provide overhead symbols and control symbols. The transmit processor 220 may generate reference symbols for reference signals (e.g., cell-specific reference signals (CRS) or demodulation reference signals (DMRS)) and synchronization signals (e.g., primary synchronization signals (PSS) or secondary synchronization signals (SSS)). The transmit (TX) multiple-input multiple-output (MIMO) processor 230 may perform spatial processing (e.g., pre-coding) on ​​data symbols, control symbols, overhead symbols, and / or reference symbols, where applicable, and may provide a set of output symbol streams (e.g., T output symbol streams) to a corresponding set of modems 232 (e.g., T modems) (shown as modems 232a to 232t). For example, each output symbol stream may be provided to a modulator component (shown as MOD) of the modem 232. Each modem 232 may process a corresponding output symbol stream (e.g., for OFDM) using a corresponding modulator component to obtain an output sample stream. Each modem 232 may also process (e.g., convert to analog, amplify, filter, and / or up-convert) the output sample stream using a corresponding modulator component to obtain a downlink signal. The modems 232a to 232t may transmit a set of downlink signals (e.g., T downlink signals) via a set of corresponding antennas 234 (e.g., T antennas) (shown as antennas 234a to 234t).

[0066] At the UE 120, a set of antennas 252 (shown as antennas 252a to 252r) may receive downlink signals from the network node 110 and / or other network nodes 110 and may provide a set of received signals (e.g., R received signals) to a set of modems 254 (e.g., R modems) (shown as modems 254a to 254r). For example, each received signal may be provided to a demodulator component (shown as DEMOD) of the modem 254. Each modem 254 may use a corresponding demodulator component to condition (e.g., filter, amplify, downconvert, and / or digitize) the received signal to obtain input samples. Each modem 254 may use a demodulator component to further process the input samples (e.g., for OFDM) to obtain received symbols. A MIMO detector 256 may obtain received symbols from the modem 254, may perform MIMO detection on the received symbols where applicable, and may provide detected symbols. The receive processor 258 may process (e.g., demodulate and decode) the detected symbols, may provide decoded data for the UE 120 to the data sink 260, and may provide decoded control information and system information to the controller / processor 280. The term "controller / processor" may refer to one or more controllers, one or more processors, or a combination thereof. The channel processor may determine a reference signal received power (RSRP) parameter, a received signal strength indicator (RSSI) parameter, a reference signal received quality (RSRQ) parameter, and / or a CQI parameter, among other things. In some examples, one or more components of the UE 120 may be included in the housing 284.

[0067] The network controller 130 may include a communication unit 294, a controller / processor 290, and a memory 292. The network controller 130 may include, for example, one or more devices in a core network. The network controller 130 may communicate with the network node 110 via the communication unit 294.

[0068] One or more antennas (e.g., antennas 234a to 234t and / or antennas 252a to 252r) may include, or may be included within, one or more antenna panels, one or more antenna groups, one or more groups of antenna elements, and / or one or more antenna arrays, etc. An antenna panel, an antenna group, a group of antenna elements, and / or an antenna array may include one or more antenna elements (in a single housing or multiple housings), a group of coplanar antenna elements, a group of non-coplanar antenna elements, and / or may be coupled to one or more transmit and / or receive components (such as, Figure 2 One or more antenna elements of one or more components).

[0069] On the uplink, at the UE 120, the transmit processor 264 may receive and process data from the data source 262 and control information from the controller / processor 280 (e.g., for reports including RSRP, RSSI, RSRQ, and / or CQI). The transmit processor 264 may generate reference symbols for one or more reference signals. The symbols from the transmit processor 264 may be pre-decoded by the TX MIMO processor 266, where applicable, further processed by the modem 254 (e.g., for DFT-s-OFDM or CP-OFDM), and sent to the network node 110. In some examples, the modem 254 of the UE 120 may include a modulator and a demodulator. In some examples, the UE 120 includes a transceiver. The transceiver may include any combination of an antenna 252, a modem 254, a MIMO detector 256, a receive processor 258, a transmit processor 264, and / or a TX MIMO processor 266. The transceiver may be used by a processor (eg, controller / processor 280) and memory 282 to perform the functions described herein (eg, with reference to Figures 4 to 17 ) or any aspects of any of the methods described herein.

[0070] At the network node 110, uplink signals from the UE 120 and / or other UEs may be received by the antenna 234, processed by the modem 232 (e.g., a demodulator component (shown as DEMOD) of the modem 232), detected by the MIMO detector 236 (where applicable), and further processed by the receive processor 238 to obtain decoded data and control information transmitted by the UE 120. The receive processor 238 may provide the decoded data to the data sink 239 and the decoded control information to the controller / processor 240. The network node 110 may include a communication unit 244 and may communicate with the network controller 130 via the communication unit 244. The network node 110 may include a scheduler 246 to schedule one or more UEs 120 for downlink communication and / or uplink communication. In some examples, the modem 232 of the network node 110 may include a modulator and a demodulator. In some examples, the network node 110 includes a transceiver. The transceiver may include any combination of antenna 234, modem 232, MIMO detector 236, receive processor 238, transmit processor 220, and / or TX MIMO processor 230. The transceiver may be used by a processor (e.g., controller / processor 240) and memory 242 to perform operations described herein (e.g., with reference to Figures 4 to 17 ) or any aspects of any of the methods described herein.

[0071] As described in more detail elsewhere herein, a controller / processor of a network entity (e.g., controller / processor 240 of network node 110), controller / processor 280 of UE 120, and / or Figure 2 Any other component of the network node 110 may perform one or more techniques associated with CSI reporting for virtual IMRs and virtual CMRs. For example, the controller / processor 240 of the network node 110, the controller / processor 280 of the UE 120, and / or Figure 2 Any other component of the Fig.12 The process 1200 Fig.13 Process 1300, Fig.14 The process of 1400 Fig.15 1500 and / or operations of other processes as described herein. Memory 242 and memory 282 may store data and program codes for network node 110 and UE 120, respectively. In some examples, memory 242 and / or memory 282 may include a non-transitory computer-readable medium storing one or more instructions (e.g., code and / or program code) for wireless communication. For example, the one or more instructions, when executed (e.g., directly, or after compilation, conversion, and / or interpretation) by one or more processors of network node 110 and / or UE 120, may cause the one or more processors, UE 120, and / or network node 110 to perform or direct, for example, Fig.12 The process 1200 Fig.13 Process 1300, Fig.14 The process of 1400 Fig.15 The process 1500 and / or operations of other processes as described herein. In some examples, executing instructions may include running instructions, converting instructions, compiling instructions, and / or interpreting instructions, etc.

[0072] In some aspects, the UE 120 includes means for generating a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource that is used for beam management and is not transmitted; and / or means for transmitting the CSI report. Means for the UE 120 to perform operations described herein may include, for example, one or more of the communication manager 140, the antenna 252, the modem 254, the MIMO detector 256, the receive processor 258, the transmit processor 264, the TX MIMO processor 266, the controller / processor 280, or the memory 282.

[0073] In some aspects, the UE 120 includes means for generating a CSI report based at least in part on the transmitted one or more IMRs and one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted, and / or means for transmitting the CSI report.

[0074] In some aspects, a network entity (e.g., network node 110) includes means for sending a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted; and / or means for receiving the CSI report. In some aspects, means for the network entity to perform operations described herein may include, for example, one or more of the following: communication manager 150, transmit processor 220, TX MIMO processor 230, modem 232, antenna 234, MIMO detector 236, receive processor 238, controller / processor 240, memory 242, or scheduler 246.

[0075] In some aspects, the network entity includes means for sending a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent; and / or means for receiving the CSI report.

[0076] Although Figure 2 The blocks in the 200 and 210 are illustrated as distinct components, but the functionality described above for these blocks may be implemented in a single hardware, software, or combined component or in various combinations of components. For example, the functionality described for 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.

[0077] As indicated above, Figure 2 are provided as examples. Other examples can be found in the Figure 2 The examples described are different.

[0078] The deployment of a communication system (such as a 5G NR system) can be arranged with various components or components in a variety of ways. In a 5G NR system or network, a network node, a network entity, a mobility element of a network, a RAN node, a core network node, a network element, a base station or network equipment can be implemented in an aggregated or decomposed architecture. For example, a base station (such as a node B (NB), an evolved NB (eNB), an NR BS, a 5G NB, an access point (AP), a TRP or a cell, etc.) or one or more units (or one or more components) that perform base station functionality can be implemented as an aggregated base station (also called an independent base station or a monolithic base station) or a decomposed base station. "Network entity" or "network node" may refer to a decomposed base station or one or more units of a decomposed base station (such as one or more CUs, one or more DUs, one or more RUs, or a combination thereof).

[0079] An aggregated base station (e.g., an aggregated network node) may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node (e.g., within a single device or unit). A decomposed base station (e.g., a decomposed network node) may be configured to utilize a protocol stack that is physically or logically distributed between two or more units (such as one or more CUs, one or more DUs, or one or more RUs). In some examples, a CU may be implemented within a network node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed across one or more other network nodes. A DU may be implemented to communicate with one or more RUs. Each of a CU, a DU, and a RU may also be implemented as a virtual unit, such as a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU), and the like.

[0080] Base station type operations or network designs may take into account the aggregated nature of base station functionality. For example, a decomposed base station may be utilized in an IAB network, an open radio access network (O-RAN (such as a network configuration initiated by the O-RAN Alliance)), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN)) to facilitate the scaling of a communication system by separating base station functionality into one or more units that can be deployed separately. A decomposed base station may include functionality implemented across two or more units at various physical locations, as well as functionality implemented virtually for at least one unit, which may enable flexibility in network design. Individual units of a decomposed base station may be configured for wired or wireless communication with at least one other unit of the decomposed base station.

[0081] Figure 33 is a diagram illustrating an example disaggregated base station architecture 300 according to the present disclosure. The disaggregated base station architecture 300 may include a CU 310 that may communicate directly with a core network 320 via a backhaul link, or indirectly with the core network 320 through one or more disaggregated control units, such as a near-RT RIC 325 via an E2 link, or a non-RT RIC 315 associated with a service management and orchestration (SMO) framework 305, or both. The CU 310 may communicate with one or more DUs 330 via respective midhaul links, such as via an F1 interface. 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 radio frequency (RF) access links. In some implementations, a UE 120 may be served simultaneously by multiple RUs 340.

[0082] Each of the units (including CU 310, DU 330, RU 340) and the near-RT RIC 325, non-RT RIC 315, and SMO framework 305 may include or be coupled to one or more interfaces, the one or more interfaces being configured to receive or send signals, data, or information (collectively referred to as signals) via a wired or wireless transmission medium. Each of the units or an associated processor or controller that provides instructions to one or more communication interfaces of the corresponding unit may be configured to communicate with one or more of the other units via a transmission medium. In some examples, each of the units may include a wired interface and a wireless interface, the wired interface being configured to receive signals or send signals to one or more of the other units via a wired transmission medium, the wireless interface being configured to receive signals or send signals to one or more of the other units via a wired transmission medium, or both.

[0083] In some aspects, CU 310 may host one or more higher layer control functions. Such control functions may include radio resource control (RRC) functions, packet data convergence protocol (PDCP) functions, or service data adaptation protocol (SDAP) functions, etc. Each control function may be implemented using an interface that is configured to communicate signals with other control functions hosted by CU 310. CU 310 may be configured to handle user plane functionality (e.g., central unit-user plane (CU-UP) functionality), control plane functionality (e.g., central unit-control plane (CU-CP) functionality), or a combination thereof. In some specific implementations, CU 310 may be logically divided into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP unit may communicate bidirectionally with the CU-CP unit via an interface (such as an E1 interface). As needed, CU 310 may be implemented to communicate with DU 330 for network control and signaling.

[0084] Each DU 330 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RUs 340. In some aspects, the DU 330 may host one or more of a radio link control (RLC) layer, a MAC layer, and one or more high physical (PHY) layers, at least in part, according to a functional partitioning (such as that defined by 3GPP). In some aspects, one or more high PHY layers may be implemented by one or more modules for forward error correction (FEC) encoding and decoding, scrambling, modulation and demodulation, etc. In some aspects, the DU 330 may also host one or more low PHY layers, such as one or more modules for fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming or physical random access channel (PRACH) extraction and filtering, etc. Each layer (which may also be referred to as a module) may be implemented using an interface that is configured to communicate signals with other layers (and modules) hosted by the DU 330 or with control functions hosted by the CU 310.

[0085] Each RU 340 may implement lower layer functionality. In some deployments, the RU 340 controlled by the DU 330 may correspond to a logical node that hosts RF processing functions or low PHY layer functions based on functional split (e.g., functional split defined by 3GPP) (such as lower layer functional split), such as performing FFT, performing iFFT, digital beamforming, or PRACH extraction and filtering, etc. In this architecture, each RU 340 may be operated to handle over-the-air (OTA) communications with one or more UEs 120. In some specific implementations, real-time and non-real-time aspects of control plane communications and user plane communications with the RU 340 may be controlled by the corresponding DU 330. In some scenarios, this configuration may enable each DU 330 and CU 310 to be implemented in a cloud-based RAN architecture (such as a vRAN architecture).

[0086] The SMO framework 305 may be configured to support RAN deployment and provisioning of non-virtualized network elements and virtualized network elements. For non-virtualized network elements, the SMO framework 305 may be configured to support the deployment of dedicated physical resources for RAN coverage requirements, which may be managed via an operation and maintenance interface (such as an O1 interface). For virtualized network elements, the SMO framework 305 may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud) platform 390) to perform network element lifecycle management (such as instantiating virtualized network elements) via a cloud computing platform interface (such as an O2 interface). Such virtualized network elements may include, but are not limited to, CU 310, DU 330, RU 340, non-RT RIC 315, and near-RTRIC 325. In some specific implementations, the SMO framework 305 may communicate with hardware aspects of the 4G RAN (such as an open eNB (O-eNB) 311) via the O1 interface. Additionally, in some implementations, the SMO framework 305 can communicate directly with each of the one or more RUs 340 via a corresponding O1 interface. The SMO framework 305 can also include a non-RT RIC 315 configured to support the functionality of the SMO framework 305.

[0087] The non-RT RIC 315 may be configured to include logic functions that enable non-real-time control and optimization of RAN elements and resources, artificial intelligence / machine learning (AI / ML) workflows including model training and updating, or policy-based guidance of applications / features in the near-RT RIC 325. The non-RT RIC 315 may be coupled to or in communication with the near-RT RIC 325 (such as via an A1 interface). The near-RT RIC 325 may be configured to include logic functions that enable near-real-time control and optimization of RAN elements and resources via data collection and actions through an interface (such as via an E2 interface) that connects one or more CUs 310, one or more DUs 330, or both, and the O-eNB with the near-RT RIC 325. In some examples, the near-RT RIC 325 may be a logic function that enables near-real-time control and optimization of O-RAN elements and resources via fine-grained data collection and actions on the E2 interface. The near-RT RIC 325 may be co-located with the RAN or network entity to provide real-time processing, such as online ML training or near real-time ML inference. The non-RT RIC 315 may be a logic function that implements non-real-time control and optimization of RAN elements and resources, AI / ML workflows including model training and updating, and policy-based guidance of applications / features in the near-RT RIC 325, and ML inference with less latency specifications. The non-RT RIC 315 may be located farther from the RAN or network node, such as on a cloud-based server or on an edge server.

[0088] In some implementations, in order to generate an AI / ML model to be deployed in the near-RT RIC 325, the non-RT RIC 315 may receive parameters or external enrichment information from an external server. Such information may be utilized by the near-RT RIC 325 and may be received from a non-network data source or from a network function at the SMO framework 305 or the non-RT RIC 315. In some examples, the non-RT RIC 315 or the near-RT RIC 325 may be configured to tune RAN behavior or performance. For example, the non-RT RIC 315 may monitor long-term trends and patterns of performance and employ AI / ML models to perform corrective actions through the SMO framework 305 (such as via reconfiguration of the O1 interface) or via the creation of RAN management policies (such as A1 interface policies).

[0089] As indicated above, Figure 3 are provided as examples. Other examples can be found in the Figure 3 The examples described are different.

[0090] Figure 44 is a diagram illustrating examples 400, 410, and 420 of a beam management process according to the present disclosure. Figure 4 As shown, examples 400, 410, and 420 include UE 120 communicating with a network entity (e.g., network node 110) in a wireless network (e.g., wireless network 100). Figure 4 The devices shown are provided as examples, and the wireless network may support communication and beam management between other devices (e.g., between UE 120 and network node 110 or TRP, between mobile terminal nodes and control nodes, between IAB child nodes and IAB parent nodes, and / or between scheduled nodes and scheduling nodes). In some aspects, UE 120 and network node 110 may be in a connected state (e.g., RRC connected state).

[0091] like Figure 4 As shown, example 400 may include a network node 110 (e.g., one or more network node devices such as RU, DU, and / or CU) and a UE 120, the network node communicating with the UE to perform beam management using a CSI reference signal (CSI-RS). Example 400 depicts a first beam management process (e.g., P1 CSI-RS beam management). The first beam management process may be referred to as a beam selection process, an initial beam acquisition process, a beam scanning process, a cell search process, and / or a beam search process. Figure 4 As shown in example 400, the CSI-RS may be configured to be sent from the network node 110 to the UE 120. The CSI-RS may be configured to be periodic (e.g., using RRC signaling), semi-persistent (e.g., using medium access control (MAC) control element (MAC CE) signaling), and / or aperiodic (e.g., using downlink control information (DCI)).

[0092] The first beam management process may include the network node 110 performing beam scanning on multiple transmit (Tx) beams. The network node 110 may use each transmit beam used for beam management to transmit a CSI-RS. In order to enable the UE 120 to perform receive (Rx) beam scanning, the network node may use a transmit beam to transmit each CSI-RS multiple times (e.g., with repetitions) within the same RS resource set, so that the UE 120 may sweep the receive beam in multiple transmit 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 M times on each of the N transmit beams, 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 scanning on the receive beam of the UE 120. Thus, the first beam management process may enable UE 120 to measure CSI-RS on different transmit beams using different receive beams to support selection of a network node 110 transmit beam / UE 120 receive beam pair. UE 120 may report the measurements to network node 110 to enable network node 110 to select one or more beam pairs for communication between network node 110 and UE 120. Although example 400 has been described in conjunction with CSI-RS, the first beam management process may also use synchronization signal blocks (SSBs) to perform beam management in a similar manner as described above.

[0093] like Figure 4 As shown, example 410 may include network node 110 and UE 120 communicating to perform beam management using CSI-RS. 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. Figure 4As shown in example 410, a CSI-RS may be configured to be transmitted from a network node 110 to a UE 120. The CSI-RS may be configured to be non-periodic (e.g., using a DCI). The second beam management process may include the network node 110 performing beam scanning on 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 at least in part based on measurements reported by the UE 120 in conjunction with the first beam management process). The network node 110 may transmit the CSI-RS using each of the one or more transmit beams used for beam management. The UE 120 may measure each CSI-RS using a single (e.g., identical) receive beam (e.g., determined at least in part based on measurements performed in conjunction with the first beam management process). The second beam management process may enable the network node 110 to select the best transmit beam based at least in part on measurements of the CSI-RS reported by the UE 120 (e.g., measured by the UE 120 using a single receive beam).

[0094] like Figure 4 As shown, example 420 depicts a third beam management process (e.g., P3 CSI-RS beam management). The third beam management process may be referred to as a beam refinement process, a UE beam refinement process, and / or a receive beam refinement process. Figure 4 As shown in example 420, one or more CSI-RS may be configured to be sent from the network node 110 to the UE 120. The CSI-RS may be configured to be non-periodic (e.g., using DCI). The third beam management process may include the network node 110 sending one or more CSI-RS using a single transmit beam (e.g., determined at least in part based on measurements reported by the UE 120 in conjunction with the first beam management process and / or the second beam management process). In order to enable the UE 120 to perform receive beam scanning, the network node may use the transmit beam to send multiple times (e.g., with repetitions) CSI-RS within the same RS resource set, so that the UE 120 can sweep 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 at least in part based on measurements performed in conjunction with the first beam management process and / or the second beam management process). The third beam management process may enable the network node 110 and / or the UE 120 to select the best receive beam based at least in part on reported measurements received from the UE 120 (eg, reported measurements of the CSI-RS of the transmit beam using the one or more receive beams).

[0095] Wireless networks may operate at higher frequency bands, such as within millimeter wave (mmW) bands (e.g., FR2 above 28 GHz, FR4 above 60 GHz, or THz bands above 100 GHz, etc.), to provide high data rates. For example, wireless devices (such as network nodes and UEs) may communicate with each other through beamforming techniques to improve communication speed and reliability. Beamforming techniques may enable wireless devices to send signals in a specific direction, rather than sending omnidirectional signals in all directions. In some examples, a wireless device may send signals from multiple antenna elements using a wavelength and phase that are common to the transmissions from the multiple antenna elements, and the signals from the multiple antenna elements may be combined to create a combined signal with a longer range and a more directional beam. The beam width of the signal may vary based on the transmission frequency. For example, the width of the beam may be negatively correlated with the frequency, wherein the beam width may decrease as the transmission frequency increases, because more radiating elements may be placed in each given area at the transmitter due to a smaller wavelength. Thus, a higher frequency band (e.g., a THz or sub-THz band) may enable a wireless device to form a much narrower beam structure (e.g., a pencil beam, a laser beam, or a narrow beam, etc.) than a beam structure at or below FR2 because more radiating elements may be placed per given area at the antenna element due to the smaller wavelength. A higher frequency band may have a short delay spread (e.g., a few nanoseconds) and may translate into a coherent frequency bandwidth of tens (10) MHz. In addition, a higher frequency band may provide a huge available bandwidth that may be occupied by a larger bandwidth carrier, such as 1000 MHz or more per carrier. In some examples, the transmission path of a narrower beam may be more likely to be customized for a receiver, such that the transmission may be more likely to meet a line of sight (LOS) condition because a narrower beam may be more likely to reach a receiver without being blocked by obstacles. Moreover, since the transmission path may be narrow, transmission and / or refraction may be less likely to occur for a narrower beam.

[0096] Although higher frequency bands may provide a more efficient beam structure and a higher transmission rate, higher frequency bands may also encounter higher attenuation and diffraction losses, wherein the obstruction of the LOS path may degrade the quality of the wireless link. For example, when two wireless devices communicate with each other based on a LOS path in a higher frequency band and the LOS path is blocked by obstacles such as pedestrians, buildings and / or vehicles, the received power may drop significantly. Therefore, compared with lower frequency bands, wireless communications based on higher frequency bands may be more susceptible to environmental changes. In order to ensure that the UE 120 and the network node 110 communicate using the best beam or beam pair, a beam management process (e.g., such as combining Figure 4The beam management process described herein may be performed by UE 120 and / or network node 110. However, because higher frequency bands may be more susceptible to environmental changes than lower frequency bands, it may be necessary to perform the beam management process more frequently and / or using additional beams. This may introduce significant overhead and consume network resources, processing resources, and / or power resources of the UE (and / or network node) associated with performing the beam management process.

[0097] As indicated above, Figure 4 is provided as an example of a beam management process. Other examples of beam management processes can be found in Figure 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.

[0098] Figure 5 is a diagram of an example architecture 500 illustrating a functional framework for RAN intelligence enabled by data collection according to the present disclosure. In some scenarios, the functional framework for RAN intelligence may be implemented by further enhancing data collection through use cases and / or examples. For example, principles or algorithms of RAN intelligence enabled by AI / ML and associated functional frameworks (e.g., AI functionality and / or input / output of components for enabling AI optimization) have been utilized or studied to identify the benefits of an AI-enabled RAN through possible use cases (e.g., beam management, energy saving, load balancing, mobility management and / or coverage optimization, etc.). In one example, as shown in architecture 500, the functional framework for RAN intelligence may include multiple logical entities, such as a model training host 502, a model inference host 504, a data source 506, and participants 508.

[0099] The model inference host 504 may be configured to run an AI / ML model based on the inference data provided by the data source 506, and the model inference host 504 may generate output (e.g., prediction) using the inference data input to the participant 508. The participant 508 may be an element or entity of the core network or RAN. For example, the participant 508 may be a UE, a network node, a network entity, a base station (e.g., a gNB), a CU, a DU, and / or a RU, etc. In addition, the participant 508 may also depend on the type of task performed by the model inference host 504, the type of inference data provided to the model inference host 504, and / or the type of output generated by the model inference host 504. For example, if the output from the model inference host 504 is associated with beam management, the participant 508 may be a UE, a DU, or a RU; and if the output from the model inference host 504 is associated with Tx / Rx scheduling, the participant 508 may be a CU or a DU.

[0100] After the participant 508 receives the output from the model inference host 504, the participant 508 may determine whether to take an action based on the output. For example, if the participant 508 is a DU or RU, and the output from the model inference host 504 is associated with beam management, the participant 508 may determine whether to change / modify the Tx / Rx beam based on the output. If the participant 508 determines an action based on the output, the participant 508 may indicate the action to at least one action subject 510. For example, if the participant 508 determines to change / modify the Tx / Rx beam used for communication between the participant 508 and the action subject 510 (e.g., UE 120), the participant 508 may send a beam (re) configuration or beam switching indication to the action subject 510. The participant 508 may modify its Tx / Rx beam based on the beam (re) configuration, such as switching to a new Tx / Rx beam or applying different parameters to the Tx / Rx beam, etc. As another example, participant 508 may be a UE, and the output from model inference host 504 may be associated with beam management. For example, the output may be one or more predicted measurements for one or more beams. Participant 508 (e.g., UE) may determine to send a measurement report (e.g., a layer 1 (L1) RSRP report) to network node 110.

[0101] The data source 506 may also be configured to collect data that is used as training data for training the ML model or as inference data for feeding the ML model inference operation. For example, the data source 506 may collect data from one or more core network and / or RAN entities (which may include an action subject 510) and provide the collected data to the model training host 502 for ML model training. For example, after the action subject 510 (e.g., UE 120) receives the beam configuration from the participant 508, the action subject 510 may provide performance feedback associated with the beam configuration to the data source 506, wherein the performance feedback may be used by the model training host 502 to monitor or evaluate ML model performance, such as whether the output (e.g., prediction) provided to the participant 508 is accurate. In some examples, if the output provided by the participant 508 is inaccurate (or the accuracy is below an accuracy threshold), the model training host 502 may determine to modify or retrain the ML model used by the model inference host, such as via ML model deployment / update.

[0102] As indicated above, Figure 5 are provided as examples. Other examples can be found in the Figure 5 The examples described are different.

[0103] Figure 6 6 is a diagram illustrating an example 600 of AI / ML-based beam management according to the present disclosure. Figure 6 As shown, the AI / ML model 610 may be deployed at or on the UE 120. For example, a model inference host (such as the model inference host 504) may be deployed at or on the UE 120. The AI / ML model 610 may enable the UE 120 to determine one or more inferences or predictions based on data input to the AI / ML model 610.

[0104] For example, as indicated by reference numeral 615, the input of the AI / ML model 610 may include measurements associated with the first beam set. For example, the network node 110 may send one or more signal values ​​of corresponding beams from the first beam set. The UE 120 may perform measurements (e.g., L1 RSRP measurements or other measurements) on the first beam set to obtain a first measurement set. For example, each beam from the first beam set may be associated with one or more measurements performed by the UE 120. The UE 120 may input the first measurement set (e.g., L1 RSRP measurement values) into the AI / ML model 610 together with information associated with the first beam set and / or the second beam set, such as beam direction (e.g., spatial direction), beam width, beam shape, and / or other characteristics of corresponding beams from the first beam set and / or the second beam set.

[0105] As indicated by reference numeral 620, the AI / ML model 610 may output one or more predictions. The one or more predictions may include a predicted measurement value associated with the second set of beams (e.g., a predicted L1 RSRP measurement value). This may reduce the number of beam measurements performed by the UE 120, thereby converting the power of the UE 120 and / or network resources that would otherwise be used to measure all beams included in the first set of beams and the second set of beams. This type of prediction may be referred to as codebook-based spatial domain selection or prediction.

[0106] As another example, the output of the AI / ML model 610 may include the point direction, angle of departure (AoD), and / or angle of arrival (AoA) of the beams included in the second beam set. This type of prediction may be referred to as non-codebook based spatial domain selection or prediction. As another example, multiple measurement reports or values ​​collected at different time points may be input to the AI / ML model 610. This may enable the AI / ML model 610 to output codebook-based and / or non-codebook based predictions of measurement values, AoD and / or AoA, etc. for beams at future times. As described herein, the output of the AI / ML model 610 may facilitate an initial access process, a secondary cell group (SCG) setup process, a beam refinement process (e.g., as described above in conjunction with Figure 4 The P2 beam management process or the P3 beam management process described herein), link quality or interference adaptation process, beam failure and / or beam blocking prediction, and / or radio link failure prediction, etc. This can lead to improved management accuracy without excessive beam scanning.

[0107] In some examples, the first beam set may be referred to as a set B beam, and the second beam set may be referred to as a set A beam. In some examples, the first beam set (e.g., set B beams) may be a subset of the second beam set (e.g., set A beams). In some other examples, the first beam set and the second beam set may be different beams and / or may be mutually exclusive sets. For example, the first beam set (e.g., set B beams) may include wide beams (e.g., unrefined beams or beams with a beam width that satisfies a first threshold), and the second beam set (e.g., set A beams) may include narrow beams (e.g., refined beams or beams with a beam width that satisfies a second threshold). In one example, the AI / ML model 610 may perform spatial domain downlink beam prediction of the beams included in the set A beam based on the measurement results of the beams included in the set B beams. As another example, the AI / ML model 610 may perform temporal downlink beam prediction for beams included in the set A beams based on historical measurements of beams included in the set B beams.

[0108] As described above, in order to perform the prediction described herein, the UE 120 and / or the AI / ML model 610 may expect information associated with the first beam set and / or the second beam set in order to accurately perform the prediction. For example, the UE 120 and / or the AI / ML model 610 may use information such as the beam direction (e.g., spatial direction), beam width, beam shape, and / or other characteristics of the corresponding beams from the first beam set and / or the second beam set to accurately perform the above prediction. However, the information may be associated with the beamforming technology performed at the network entity (e.g., the network node 110). Therefore, the network node 110 may send the information, and the UE 120 may receive the information (e.g., the beam direction (e.g., spatial direction), beam width, beam shape, and / or other characteristics of the corresponding beams from the first beam set and / or the second beam set). However, this may consume significant signaling overhead, especially in the case where the network node 110 may dynamically change the beamforming technology or shape (e.g., thereby requiring another transmission of the above information). Furthermore, explicit indication of the beamforming techniques performed at the network node 110 may contemplate detailed disclosure of proprietary or confidential information. Thus, in some cases, the network node 110 may not provide explicit indication of some or all of the information that the UE 120 accurately performs the above-described predictions. As a result, the AI / ML predictions performed by the UE 120 may be degraded because the UE 120 may not have access to information of beam characteristics or beam shapes associated with the AI / ML predictions.

[0109] In some aspects, there may be a connection between resources used for predictive beam management. For example, UE 120 may receive an indication of a first resource set and a second resource set and an indication of one or more connections between the first resource set and the second resource set. The one or more connections may include a connection associated with a resource included in the first resource set or the second resource set, the connection being defined relative to one or more resources included in a resource set different from the first resource set or the second resource set. In other words, the connection may be an implicit connection that defines beam characteristics associated with a given resource relative to beams associated with other resources included in different sets. In some examples, the connections described herein may be referred to as implicit connections, associations, correlations, relationships, correspondences, mappings, and / or links, etc. The connection may indicate a relationship between a first spatial direction or a first beam associated with the resource and a second spatial direction or a second beam of one or more resources included in the different resource set. The first resource set may be a channel measurement resource for CSI reporting, and the second resource set may be a resource (e.g., a nominal resource) that is not actually measured by UE 120. For example, a first set of resources may be associated with a set B beam and a second set of resources may be associated with a set A beam. In some aspects, the connection may be a graph-based connection or may be a linear combination.

[0110] UE 120 may send a CSI report indicating measurement values ​​associated with the first resource set and the second resource set. A first one or more measurement values ​​from the measurement values ​​associated with the first resource set may be measured by UE 120. A second one or more measurement values ​​from the measurement values ​​associated with the second resource set may be predicted by UE 120 based at least in part on the first one or more measurement values ​​and the one or more connections. In other words, UE 120 may use the connection between the first resource set and the second resource set to obtain beam characteristics or beam shapes associated with the first resource set and the second resource set. UE 120 may use the beam characteristics or beam shapes associated with the first resource set and the second resource set to perform one or more AI / ML predictions associated with the first resource set and the second resource set.

[0111] In some aspects, one or more resources included in the second set of resources may be used to send a configuration indicator (TCI) status indication. Additionally or alternatively, one or more resources included in the second set of resources may be used by UE 120 as a source reference for a quasi-co-located (QCL) source (e.g., even if UE 120 has not actually received and / or measured a signal via the second set of resources).

[0112] Thus, the UE 120 may be enabled to perform improved predictive beam management by obtaining beam characteristics (e.g., beam shape and / or beam width) associated with the first set of resources and the second set of resources. In addition, by using an implicit connection between the two resource sets, the UE 120 and / or the network node 110 may save signaling overhead, network resources, processing resources, and / or power associated with indicating beam characteristics (e.g., beam shape and / or beam width) associated with the first set of resources and the second set of resources. For example, by using an implicit connection between the two resource sets, detailed beamforming information or a specific implementation performed at the network node 110 does not need to be disclosed or indicated to the UE 120.

[0113] As indicated above, Figure 6 are provided as examples. Other examples can be found in the Figure 6 The examples described are different.

[0114] Fig. 7A and Figure 7B is a diagram illustrating an example 700 associated with connections between resources for predictive beam management according to the present disclosure. Fig. 7A As shown, a network entity (e.g., a network node 110, a base station, a CU, a DU, and / or a RU) may communicate with a UE 120. In some aspects, the network node 110 and the UE 120 may be part of a wireless network (e.g., the wireless network 100). The UE 120 and the network node 110 may be in communication with each other. Fig. 7A The operations shown are performed after a wireless connection has been established.

[0115] In some aspects, the actions described herein as being performed by the network node 110 may be performed by a plurality of different network nodes. For example, a configuration action may be performed by a first network node (e.g., a CU or a DU), and a radio communication action may be performed by a second network node (e.g., a DU or a RU). As used herein, "sending" a communication by the network node 110 to the UE 120 may refer to direct sending (e.g., from the network node 110 to the UE 120) or indirect sending via one or more other network nodes or devices. For example, if the network node 110 is a DU, indirect sending to the UE 120 may include the DU sending the communication to the RU and the RU sending the communication to the UE 120. Similarly, "sending" a communication by the UE 120 to the network node 110 may refer to direct sending (e.g., from the UE 120 to the network node 110), or indirect sending via one or more other network nodes or devices. For example, if the network node 110 is a DU, indirect sending to the network node 110 may include the UE 120 sending the communication to the RU and the RU sending the communication to the DU.

[0116] like Fig. 7AAs shown, and as shown by reference numeral 705, UE 120 may send a capability report and network node 110 may receive the capability report. The capability report may indicate that UE 120 supports performing predictive beam management as described herein. For example, the capability report may indicate that UE 120 supports performing as described in conjunction with Figures 5 and 6 In some aspects, the capability report may indicate that UE 120 supports identifying beam information for performing predictive beam management using a connection between two resource sets, as described in more detail elsewhere herein. In some aspects, UE 120 may be configured to perform one or more operations described herein based at least in part on the capability report indicating that UE 120 supports performing predictive beam management.

[0117] As indicated by reference numeral 710, the network node 110 may send, and the UE 120 may receive, configuration information. In some aspects, the UE 120 may receive the configuration information via one or more of system information signaling, RRC signaling, one or more MAC CEs and / or DCI, etc. In some aspects, the configuration information may include, among other things, an indication of one or more configuration parameters for selection by the UE 120 (e.g., stored by the UE 120 and / or previously indicated by the network node 110 or another network device) and / or explicit configuration information for the UE 120 to configure itself.

[0118] In some aspects, the configuration information may indicate that UE 120 is to perform predictive beam management. For example, the configuration information may indicate that UE 120 is to use an AI / ML model and / or a model inference host deployed at or associated with UE 120 to predict measurement values ​​(e.g., L1 RSRP values) associated with one or more beams. For example, the configuration information may indicate that UE 120 is to use measurement values ​​of other transmit beams of network node 110 (e.g., performed by UE 120) to predict measurement values ​​associated with a transmit beam of network node 110 (e.g., RU).

[0119] In some aspects, the configuration information may indicate a first resource set and a second resource set. In some aspects, the first resource set may include downlink reference signal resources, such as SSB resources or CSI-RS resources, etc. In some aspects, the first resource set may be a CMR for CSI reporting (e.g., which may be indicated via the resourcesForChannelMeasurement information element). In some aspects, the second resource set may include nominal resources. As used herein, "nominal resources" may refer to resources (e.g., time-frequency resources or radio resources) that are indicated or configured for UE 120 but are not used by network node 110 for transmission (or infrequently used for transmission). For example, the second resource set may include one or more downlink reference signal resources (e.g., SSB resources or CSI-RS resources) that are infrequently used or not used for transmission by network node 110. In some examples, the nominal resources may be virtual resources or logical resources (e.g., resources used for beam management (e.g., beam prediction) but not used for transmission or not transmitted by network node 110). Virtual resources may include virtual CMRs that are used for beam management but not transmitted.

[0120] The UE may use a virtual CMR that is not actually transmitted as a prediction target for beam prediction. The network may indicate a CMR to be a virtual resource. The UE may predict virtual resource measurements and predict the correct receive beam for the virtual resource. The purpose of virtual resources is to improve beam prediction, and the purpose of beam prediction is to reduce overhead.

[0121] Virtual QCL Type D resources may include virtual CMR Set A beams that are not actually transmitted but have a beam shape / pointing direction connection with the actually transmitted CMR Set B beams. For example, using SSB-based wide beams, the UE may predict narrow beam L1-RSRP measurements that are expected to be measured by CSI-RS but are not transmitted to reduce UE power consumption and / or downlink RS overhead for measurement.

[0122] In some aspects, a given resource (e.g., from the first set of resources and / or the second set of resources) may be associated with a beam. For example, the network node 110 may associate a given resource with a given beam. In the event that the resource is used by the network node 110 for transmission, the network node 110 may use the resource and the beam for transmission. In some aspects, the first set of resources may be associated with a set B beam of the network node 110, and the second set of resources may be associated with a set A beam of the network node 110. In some aspects, the first set of resources may be a subset of the second set of resources. In some other aspects, the first set of resources may include different resources (e.g., may be mutually exclusive sets).

[0123] In some aspects, the configuration information may include a CSI configuration. For example, the configuration information may include a CSI report setting and / or a CSI resource setting, etc. As another example, the configuration information may include a CSI-ReportConfig configuration and / or a CSI-ResourceConfig configuration, etc. In other words, the configuration information may configure the UE 120 to send a CSI report including information (e.g., measurements) associated with the first resource set and the second resource set. As described above, the first resource set may be a CMR for CSI reporting.

[0124] In some aspects, the configuration information may indicate a reporting quantity configuration for CSI reporting. For example, the UE 120 may be configured with a CSI-ReportConfig, where a higher layer parameter reportQuantity is set to 'none', 'cri-RI-PMI-CQI', 'cri-RI-i1', 'cri-RI-i1-CQI', 'cri-RI-CQI', 'cri-RSRP', 'ssb-Index-RSRP', or 'cri-RI-LI-PMI-CQI', etc. (e.g., as defined by 3GPP or otherwise fixed). The reporting quantity may indicate or configure what is to be included in the CSI report and / or what the UE 120 expects to be configured for the CSI report, etc. In other words, the reporting quantity may indicate what kind of quantity (e.g., SSB RSRP, CQI, precoding matrix indicator (PMI), and / or rank indicator (RI)) the UE 120 should measure and report. For example, a wireless communication standard such as 3GPP may define expectations and / or configurations for CSI reporting for different values ​​of reporting amount. In some aspects, the reporting amount associated with the CSI report to be sent by the UE 120 may be based at least in part on a second resource set (e.g., a nominal resource). For example, the second resource set may be used to define the reporting amount of the CSI configuration. In some aspects, the second resource set may be used as a reference for the reporting amount in the CSI report (e.g., the first resource set may be used as a CMR for the CSI report, and the reporting amount of the CSI report may be defined at least in part based on the second resource set). For example, the UE 120 may receive a configuration for the CSI report (e.g., a CSI report setting, a CSI resource setting, a CSI-ReportConfig, and / or a CSI-ResourceConfig). The configuration may indicate that the first resource set is a channel measurement resource associated with the CSI report, and the second resource set is a reference associated with the reporting amount associated with the CSI report.

[0125] UE 120 may configure itself based at least in part on the configuration information.In some aspects, UE 120 may be configured to perform one or more operations described herein based at least in part on the configuration information.

[0126] As shown by reference numeral 715, the network node 110 may send, and the UE 120 may receive, an indication of one or more connections between the first set of resources and the second set of resources. For example, the one or more connections may be implicit connections. In some aspects, the indication of the one or more connections may be included in the configuration information (e.g., the configuration information and the indication of the one or more connections may be included in the same communication or configuration). In some other aspects, the indication of the one or more connections may be sent to the UE 120 separately from the configuration information.

[0127] For example, a connection associated with a resource included in a first resource set or a second resource set may be defined with respect to one or more resources included in a resource set different from the first resource set or the second resource set. In some aspects, the connection may indicate a relationship between a first spatial direction or a first beam associated with the resource and a second spatial direction or a second beam of one or more resources included in the different resource set. In other words, the connection may implicitly indicate a beam and / or spatial direction associated with a given resource by connecting the given resource to one or more other resources included in the different resource set.

[0128] Figure 7B A spatial overlay relationship between a first spatial direction or a first beam associated with a resource and a second spatial direction or a second beam associated with one or more resources included in the different resource set is shown. For example, the connection may indicate that a first beam width of a first beam associated with a resource may overlap with a second beam width of a second beam. In other words, if the diagram indicates that a first resource (e.g., included in the second resource set) is connected to a second resource (e.g., included in the first resource set), UE 120 may assume that the beam width associated with the first resource is within the beam width associated with the second resource.

[0129] In some aspects, the beamwidth may include an angular spread associated with an attenuation difference from a peak beamforming gain of a beam associated with the beamwidth that satisfies a threshold (e.g., X decibels (dB) of attenuation). In other words, the beamwidth may be defined as the angular spread within X dB of attenuation relative to the peak beamforming gain of the beam. In some aspects, the value of the threshold (e.g., X) may be defined by a wireless communication standard (such as 3GPP) or otherwise fixed. Additionally or alternatively, the value of the threshold (e.g., X) may be included in an indication of one or more connections between a first set of resources and a second set of resources. In some aspects, the threshold may include a first threshold associated with the first set of resources (e.g., X1) and a second threshold associated with the second set of resources (e.g., X2).

[0130] As an example and as Figure 7B As shown, resource 0 included in the second resource set is connected to resource 0 and resource 1 included in the first resource set. As shown by reference numeral 750, the connection may indicate a spatial overlap between the connected resources. For example, Figure 7B As shown, the connection may indicate that the beamwidth of the beam associated with resource 0 included in the second resource set is included within the beamwidth of the beam associated with resource 0 included in the first resource set and within the beamwidth of the beam associated with resource 1 included in the first resource set. Based on this information, the UE 120 may be enabled to infer and / or perform a prediction of the beam associated with resource 0 in the first resource set based at least in part on measurements of resource 0 and resource 1 included in the first resource set, as described in more detail elsewhere herein.

[0131] return Fig. 7A , as shown by reference numeral 720, UE 120 may determine beam characteristics of resources included in the first resource set and the second resource set or spatial associations between these resources. For example, UE 120 may use a connection to identify two or more resources associated with spatial superposition of respective beams of two or more resources (e.g., as combined with Figure 7B ). As another example, UE 120 may determine a linear combination between resources included in the first set of resources and the second set of resources. In other words, UE 120 may use these connections to obtain spatial information and / or beam information associated with resources included in the first set of resources and the second set of resources. UE 120 may use this information to perform one or more predictions associated with beam management, as described elsewhere herein. For example, UE 120 may provide this information and / or an indication of the connection as input to an AI / ML model for predictive beam management.

[0132] As indicated by reference numeral 725, the network node 110 may transmit and the UE 120 may receive one or more signals using resources included in the first resource set. For example, the network node 110 may transmit and the UE 120 may receive one or more SSBs or CSI-RS using resources included in the first resource set. As indicated by reference numeral 730, the UE 120 may perform measurements on signals associated with the first resource set. For example, the UE 120 may perform L1RSRP measurements of signals associated with the first resource set.

[0133] As shown at reference numeral 735, UE 120 may use measurements (e.g., as performed above in connection with reference numeral 730) and connections (e.g., as performed above in connection with reference numeral 715 and / or Figure 7BThe AI / ML model may determine one or more predicted measurements for the second set of resources (as described herein). For example, UE 120 may input measurements performed by UE 120 and an indication of a connection (or beam / spatial information determined by UE 120 based at least in part on the connection) to the AI / ML model. The AI / ML model may output predicted measurement values ​​associated with the second set of resources, as described in more detail elsewhere herein.

[0134] As indicated by reference numeral 740, UE 120 may send, and network node 110 may receive, a CSI report indicating measurement values ​​associated with a first set of resources and a second set of resources. A first one or more measurement values ​​from the measurement values ​​associated with the first set of resources may be measured by UE 120 (e.g., as described above in connection with reference numeral 730). A second one or more measurement values ​​from the measurement values ​​associated with the second set of resources may be predicted by UE 120 based at least in part on the first one or more measurement values ​​and the one or more connections (e.g., as described above in connection with reference numeral 735). In this manner, UE 120 may be enabled to perform predictive beam management without requiring detailed beamforming or spatial information associated with network node 110 (e.g., associated with beamforming performed by network node 110). This may reduce signaling overhead associated with enabling UE 120 to perform predictive beam management.

[0135] In some aspects, based at least in part on performing predictive beam management, resources included in the second set of resources can be used as QCL source resources for the TCI state. For example, the QCL source resources can be QCL type-D QCL (e.g., as defined or otherwise fixed by a wireless communication standard such as 3GPP). For example, QCL type-D can be associated with shared spatial reception parameters between a source reference signal and a target reference signal.

[0136] In some aspects, UE 120 may receive, and network node 110 may send, an indication of a TCI state associated with a QCL source reference associated with at least one resource from the second set of resources. For example, the TCI state may be a known TCI state (e.g., based at least in part on a measurement associated with at least one resource of the second one or more measurement values ​​included in the CSI report) based at least in part on performing predictive beam management.

[0137] For example, a beam may be associated with a TCI state. The TCI state may indicate a directivity or characteristic of the downlink beam, such as one or more QCL attributes of the downlink beam. The QCL attributes may include, for example, Doppler shift, Doppler spread, average delay, delay spread, or spatial reception parameters, etc. The spatial relationship may indicate a directivity or characteristic of the uplink beam (similar to one or more QCL attributes), as described above.

[0138] In some aspects, the UE 120 and / or the network node 110 may perform a TCI state switch. The TCI state switch may involve a known TCI state and an unknown TCI state. The TCI state switch timeline may specify a delay between receiving a reference signal (RS) resource (e.g., CSI-RS, SSB) for an L1RSRP measurement report for a target TCI state (activated TCI state) and completing an active TCI state switch. The RS resource is an RS in an activated TCI state or a QCL with an activated TCI state.

[0139] The TCI state switching timeline for the TCI state switching period may depend on whether the activated TCI state is known or unknown. The TCI state is known if multiple conditions are met. Multiple conditions may include: (Condition #1) whether a TCI state switching command is received within 1280 milliseconds (ms) at the last transmission of RS resources for beam reporting or measurement; (Condition #2) whether the UE has sent at least 1 L1 RSRP report for the target TCI state before the TCI state switching command; (Condition #3) if the TCI state remains detectable during the TCI state switching period (e.g., from the timeslot carrying the TCI state activation MAC CE to the completion of the TCI switch); and (Condition #4) whether the SSB associated with the TCI state remains detectable during the TCI switching period. In the case where the signal-to-noise ratio (SNR) of the RS is greater than or equal to 3dB, the RS may be able to be detected by the UE. This does not necessarily mean that such an RS must be sent. This can be verified by the UE via other RSs (e.g., DMRS). If these conditions are not met, the TCI state is unknown. As described above, UE 120 may consider the TCI state to be known, rather than relying on multiple conditions: (1) UE 120 has been configured / activated / triggered with CSI reporting, where the reporting amount of the CSI reporting is configured / indicated at least in part based on the second resource set; and (2) UE 120 has reported at least one predicted L1 RSRP value associated with resources associated with the TCI state included in the second resource set (e.g., as described above in conjunction with reference numeral 740). This may reduce the overhead associated with configuring the TCI state and / or may enable UE 120 to take into account additional TCI states to be known by performing predictive beam management.

[0140] Thus, the UE 120 may be enabled to perform improved predictive beam management by obtaining beam characteristics (e.g., beam shape and / or beam width) associated with the first set of resources and the second set of resources. In addition, by using an implicit connection between the two resource sets, the UE 120 and / or the network node 110 may save signaling overhead, network resources, processing resources, and / or power associated with indicating beam characteristics (e.g., beam shape and / or beam width) associated with the first set of resources and the second set of resources. For example, by using an implicit connection between the two resource sets, detailed beamforming information or a specific implementation performed at the network node 110 does not need to be disclosed or indicated to the UE 120.

[0141] As indicated above, Fig. 7A and Figure 7B are provided as examples. Other examples can be found in the Fig. 7A and Figure 7B The examples described are different.

[0142] Figure 8 is a diagram illustrating an example 800 of a connection between a CMR and an IMR according to the present disclosure.

[0143] The CMR may include SSB or CSI-RS resources for channel measurement. The UE may apply SSB or QCL type D RS to non-zero power (NZP) CSI-RS resources for channel measurement as a reference RS for determining the QCL type D RS for the corresponding CMR. Interference measurement (e.g., L1 signal to interference plus noise ratio (SINR) measurement) may be based on an instantaneously measured IMR that includes NZP-CSI-RS resources (e.g., CSI-RS beams sent by neighboring cells) or CSI-IM resources (e.g., physical downlink shared channel (PDSCH) sent by neighboring cells). Different beams may be sent to identify the IMR. In addition to the L1-SINR, if interference measurement is performed on the NZP-CSI-RS, the UE may not expect to be configured with more than one NZP-CSI-RS resource in an associated resource set within the resource setting for channel measurement.

[0144] A CMR may have a connection to an IMR or may be associated with an IMR. A CMR may be mapped one-to-one with an IMR, for example, using a CMR and an IMR identifier (ID). That is, the number of CMRs may be equal to the number of IMRs. Example 800 shows an IMR mapped one-to-one to a CMR. If the UE provides a CSI report for a CMR (including all associated IMRs), there may be a large amount of overhead (signaling resources). The network may consume a lot of power to send multiple IMRs and CMRs, and may introduce unwanted interference. The UE may consume a lot of processing resources to perform beam switching, measurements, and analog-to-digital conversion for multiple IMRs and CMRs. The UE may also have to consider different combinations of signal beams and interference beams when performing beam prediction.

[0145] According to various aspects described herein, a UE can further reduce consumption of power and signaling resources by using virtual IMRs that are used for beam management (e.g., beam prediction) but are not actually sent. The virtual IMRs may have a beam shape and / or beam direction related to the actually sent IMRs. The actual IMRs 804 that are actually sent may be referred to as "mother IMRs", as shown in example 802. The UE may use the actual IMRs 804 to predict the quality of the virtual IMRs 806 based at least in part on the actual IMRs 804. The virtual IMRs 806 may have a narrower beam than the actual IMRs 804 (mother IMRs). The UE may use the virtual IMRs 806 in combination with the actual CMRs or virtual CMRs for beam prediction. The UE may also use the actual IMRs 804 in combination with the actual CMRs or virtual CMRs for beam prediction. The UE may send CSI reports based at least in part on fewer IMR transmissions and / or CMR transmissions. In this way, fewer transmissions are required for channel and interference measurements for beam prediction. Save power and signaling resources by sending fewer IMRs. The UE can save processing resources by measuring and reporting fewer actual IMRs.

[0146] The virtual IMR 806 associated with the actual IMR 804 may have measurements or other values ​​that are used for beam prediction but are not sent. The network may send the virtual IMR 806 later (to become the actual IMR). The network may convey the CMR so that the UE can identify the correct beam. Since interference may come from neighboring cells, the UE may not be able to identify the receive beam with the actual IMR. The UE may not measure the actual IMR, but may rely on neighboring cells to predict the interference level in certain directions of the neighboring beams. The UE may not rely on the actual IMR that may come from neighboring base stations or other UEs.

[0147] In some aspects, the UE may virtually predict different CMR and IMR assumptions (combinations and combined values) instead of measuring all CMR and IMR. Therefore, the CSI report may indicate reporting of a combination of virtual CMR, actual CMR, virtual IMR and / or actual IMR, and indicate the associated L1-SINR / CQI / RI predictions. In order to reduce the reporting overhead of such interference assumptions, a reference to the measured actual CMR and IMR interference may be referenced when determining which assumption to consider. References to actual CMR and IMR combinations may be configured or indicated periodically, semi-periodically, or aperiodically to obtain greater flexibility.

[0148] Example 802 illustrates a CSI report setting associated with a CSI resource setting. In some aspects, for at least one CSI resource setting that configures an IMR associated with a CSI report setting for CSI reporting, the IMR configured by the CSI resource setting may be based at least in part on a virtual IMR resource. The CSI resource setting that configures the virtual IMR 806 may additionally include an actual IMR (as a parent IMR) based on a conventional CSI-IM or NZP-CSI-RS and a connection between the actual IMR 804 and the virtual IMR 806. For example, the CSI resource setting may indicate an explicit connection between the actual IMR 804 and the virtual IMR 806 based at least in part on beam pointing directions and / or beam width information associated with the corresponding IMRs. Information about the explicit connection may be configured or indicated via absolute beam pointing directions or beam width information. Such information may first be configured or indicated via an absolute beam pointing direction and / or beam width of the actual IMR 804, and further configured or indicated using a differential beam pointing direction and / or beam width of the virtual IMR 806, which differential beam pointing direction and / or beam width refers to the beam pointing direction and / or beam width associated with the actual IMR 804.

[0149] The connection between the actual IMR 804 and the virtual IMR 806 may be implicitly configured or indicated via a one-to-one mapping or a one-to-many mapping.The UE may predict the interference and noise caused by the virtual IMR based at least in part on signals received from the actual IMR.

[0150] Referring to example 802, in the example, the CSI resource setting may configure an actual IMR 804 and a virtual IMR 806. The actual IMR 804 may be configured as N NZP-CSI-RS resources. A virtual IMR may be configured to be connected to the mth actual IMR (e.g., the nth NZP-CSI-RS resource). The connection may also indicate that the beam pointing direction of the virtual IMR is offset by -15 degrees in azimuth relative to the connected actual IMR, and the beam width of the virtual IMR is half the beam width of the actual IMR.

[0151] As indicated above, Figure 8 are provided as examples. Other examples can be found in the Figure 8 The examples described are different.

[0152] Fig. 9 are diagrams illustrating examples 900 , 902 , and 904 of CMR and IMR combinations according to the present disclosure.

[0153] The network entity may request the UE to provide feedback in a CSI report, wherein the CMR and IMR connection is used to report a value or quantity associated with the CSI report, such as RI, CQI, PMI, L1 measurement, L1-SINR and / or L3-SINR, based at least in part on one of several scenarios. Example 900 illustrates a first scenario based at least in part on a combination of actual CMR and virtual IMR. Example 902 illustrates a second scenario based at least in part on a combination of virtual CMR and actual IMR. Example 904 illustrates a third scenario based at least in part on a combination of virtual CMR and virtual IMR.

[0154] In some aspects, the resources used for the virtual IMR may include frequency resources and / or time-frequency resources. For example, the virtual IMR may be defined using a virtual number of resource elements (REs) per physical resource block (PRB) and a total number of PRBs. The virtual resources may be defined as virtual QCL type D source resources.

[0155] In some aspects, the actual (mother) IMR may be based at least in part on CSI-IM resources or NZP-CSI-RS resources (considered as wider beams). CSI-IMs involving instantaneous downlink interference caused by neighboring cells using narrow transmit beams may be considered as spatial downsampling directions due to instantaneous interference. The UE may predict virtual interference caused in each direction based at least in part on such CSI-IMs. The actual IMR may come from interference from neighboring cells. If the interference comes from different directions, the UE may only measure interference from a limited spatial set to save resources, and then predict interference for the remaining directions.

[0156] As indicated above, Fig. 9 are provided as examples. Other examples can be found in the Fig. 9 The examples described are different.

[0157] Fig.10 1 is a diagram illustrating an example 1000 associated with generating a CSI report based on a virtual IMR according to the present disclosure. Fig.10As shown, a network entity 1010 (e.g., network node 110, CU, DU, and / or RU) may communicate with a UE 1020 (e.g., UE 120). In some aspects, the network entity 1010 and the UE 1020 may be part of a wireless network (e.g., wireless network 100). The UE 1020 and the network entity 1010 may be in communication with each other. Fig.10 The operations shown are performed after a wireless connection has been established.

[0158] In some aspects, 1020UE may generate CSI reports based at least in part on virtual IMRs. Each virtual IMR may represent a logical resource that is used for beam management and is not transmitted. In some aspects, each of the one or more virtual IMRs is a QCL source resource for a TCI state, which corresponds to a QCL for a TCI state of a CMR in the transmitted CMRs.

[0159] Example 1000 illustrates the use of a virtual IMR by a UE 1020. The UE 1020 may be based at least in part on the following: Fig. 9 Alternatively, the UE 1020 may generate a CSI report based at least in part on the virtual IMR and (actual) CMR as shown in the first scenario 900 in FIG. Fig. 9 The CSI report is generated by combining the virtual IMR and the virtual CMR shown in the third scenario 904 in FIG. 1. Each virtual CMR may represent a logical resource that is used for beam management and is not transmitted.

[0160] As shown by reference numeral 1025, the network entity 1010 may send a configuration for generating a CSI report based at least in part on a virtual IMR and a CMR or at least in part on a virtual IMR and a virtual CMR. The UE 1020 may receive a configuration for generating a CSI report based at least in part on a virtual IMR and a CMR or at least in part on a virtual IMR and a virtual CMR. The network entity 1010 may send and the UE 1020 may receive an indication of a virtual IMR and / or a virtual CMR. As shown by reference numeral 1030, the UE 1020 may receive an actually transmitted IMR and / or CMR. For example, the UE 1020 may receive a signal sent by the network entity 1010 on the actually transmitted IMR and / or CMR. The virtual IMR may be connected to these IMRs. The virtual CMR may be connected to these CMRs.

[0161] As shown in reference numeral 1035, UE 1020 may generate a CSI report based at least in part on a virtual IMR. As shown in reference numeral 1040, UE 1020 may send and network entity 1010 may receive a CSI report. The CSI report may also be based on a CMR or a virtual CMR. For example, in association with scenario 1 shown by examples 1042 and 1044, a virtual IMR may be associated with a CMR. The CSI report may be based at least in part on a measurement of the CMR. The CSI report may be based at least in part on an association with the transmitted IMR. The beam shape of each virtual IMR may be associated with the beam shape of the corresponding CMR. Example 1042 shows the CMR as a narrow beam associated with a narrow beam for the IMR, and example 1044 shows the CMR as a wider beam associated with a wider beam for the IMR. In some aspects, the CSI report may be further based at least in part on traffic conditions or traffic payload.

[0162] In some aspects, the UE 1020 may determine (among one or more possible combinations such as IMR#1-CMR#1, IMR#2-CMR#2, IMR#3-CMR#3, etc.) a combination of CMR and IMR that provides a signal strength and / or quality that meets (e.g., reaches or exceeds) a threshold (e.g., a minimum RSRP or a minimum SINR). The UE 1020 may predict one or more measurements (e.g., RSRP, RI, CQI, PMI, L1-SINr, and / or L3-SINR) based at least in part on the combination. The UE 1020 may send a prediction indication of the predicted measurement.

[0163] The number of CMRs may be equal to the number of virtual IMRs, as shown in example 1042. When reporting a CSI-RS resource indicator (CRI) or an SSB resource indicator (SSBRI), CRI / SSBRI k (k>0) may correspond to the (k+1)th actual CMR and the (k+1)th virtual IMR. Alternatively, the number of CMRs may not be equal to the number of virtual IMRs, as shown in example 1044. UE 1020 may report CRI / SSBRI associated with actual CMRs, further report identifiers associated with virtual IMRs, and finally report other quantities whose SINR is determined by a combination of the reported CMRs and IMRs.

[0164] In an example associated with example 1044, the number of CMRs and the number of IMRs (as parent IMRs of virtual IMRs) may be the same, and each CMR and IMR may be associated or one-to-one mapped. The UE 1020 may first identify (and optionally also report together with the L1-SINR / CQI) one or more combinations of CMRs and IMRs that may provide the best (e.g., maximum) L1-SINR, RI, or CQI. The UE 1020 may further predict one or more sets of reported quantities for each of such combinations, wherein each set of quantities is determined at least in part based on the assumption that the CMR is used as a CMR in the associated combination, and the IMR is used as a virtual IMR connected to the parent actual IMR associated with the combination. The UE 1020 may report one or more sets of predicted quantities for such identified combinations, (optionally) together with the associated CMR-ID and the associated virtual IMR-ID.

[0165] In another example associated with scenario 3 illustrated by examples 1046 and 1048, a virtual IMR may be associated with a virtual CMR. UE 1020 may determine (between one or more possible combinations) a combination of a virtual CMR and an IMR that provides a signal strength and / or quality that satisfies a threshold. UE 1020 may predict one or more measurements based at least in part on the combination. UE 1020 may send a prediction indication of the predicted measurement. In some aspects, each of the one or more virtual IMRs may be a QCL source resource for a TCI state, the QCL source resource corresponding to a QCL for a TCI state of a virtual CMR in the one or more virtual CMRs.

[0166] The number of virtual CMRs may be equal to the number of virtual IMRs, as shown in example 1046. When reporting a joint resource identifier, identifier k (k>0) may correspond to the (k+1)th virtual CMR and the (k+1)th virtual IMR. Alternatively, the number of virtual CMRs may not be equal to the number of virtual IMRs, as shown in example 1048. UE 1020 may report identifiers associated with virtual CMRs, further report identifiers associated with virtual IMRs, and ultimately report other quantities whose SINRs are determined by a combination of the reported CMRs and IMRs.

[0167] In an example, the number of CMRs (parent CMRs of virtual CMRs) and the number of IMRs (parent IMRs of virtual IMRs) may be the same, and each CMR and IMR may be associated or one-to-one mapped. The UE 1020 may first identify (and optionally also report with L1-SINR / CQI) one or more combinations of CMRs and IMRs that may provide the best (e.g., maximum) L1-SINR, RI, or CQI. The UE 1020 may further predict one or more sets of reported quantities for each of such combinations, wherein each set of quantities is determined at least in part based on the assumption that the IMR is used as a virtual IMR connected to a parent IMR associated with the combination, and the CMR is used as a virtual CMR connected to a parent CMR associated with the combination. The UE 1020 may report one or more sets of predicted quantities for such identified combinations, (optionally) together with the associated virtual CMR-ID and the associated virtual IMR-ID.

[0168] As indicated above, Fig.10 are provided as examples. Other examples can be found in the Fig.10 The examples described are different.

[0169] Fig.11 is a diagram illustrating an example 1100 associated with generating a CSI report based on an actual IMR according to the present disclosure.

[0170] In some aspects, 1020UE may be based at least in part on Fig. 9 1020 may generate a CSI report based at least in part on a combination of an IMR and a virtual CMR.

[0171] As indicated by reference numeral 1105, the network entity 1010 may send a configuration for generating a CSI report based at least in part on the IMR and the virtual CMR. The UE 1020 may receive a configuration for generating a CSI report based at least in part on the IMR and the virtual CMR. The network entity 1010 may send and the UE 1020 may receive an indication of the virtual CMR. As indicated by reference numeral 1110, the UE 1020 may receive the actually transmitted IMR and / or CMR. For example, the UE 1020 may receive a signal sent by the network entity 1010 on the actually transmitted IMR and / or CMR. The virtual CMR may be connected to these CMRs.

[0172] As indicated by reference numeral 1115, UE 1020 may generate a CSI report based at least in part on the IMR and the virtual CMR. As indicated by reference numeral 1120, UE 1020 may send and network entity 1010 may receive the CSI report.

[0173] In some aspects, associated with scenario 2 illustrated by examples 1122 and 1124, UE 1020 may determine a combination of virtual CMR and IMR that provides a signal strength and / or quality that meets (e.g., reaches or exceeds) a threshold (e.g., minimum RSRP, minimum SINR). UE 1020 may predict one or more measurements (e.g., RSRP, RI, CQI, PMI, L1-SINr, L3-SINR) based at least in part on the combination. UE 1020 may send a prediction indication of the predicted measurement.

[0174] The number of virtual CMRs may be equal to the number of IMRs, as shown in example 1122. When reporting CRI or SSBRI, CRI / SSBRI k (k>0) may correspond to the (k+1)th actual CMR and the (k+1)th virtual IMR. Alternatively, the number of virtual CMRs may not be equal to the number of IMRs, as shown in example 1124. UE 1020 may report identifiers associated with virtual CMRs, further report identifiers associated with IMRs, and finally report other quantities whose SINRs are determined by a combination of the reported virtual CMRs and IMRs.

[0175] In an example associated with example 1124, the number of CMRs (as parent CMRs of virtual CMRs) and the number of IMRs may be the same, and each CMR and IMR may be associated or one-to-one mapped. The UE 1020 may first identify (and optionally also report together with the L1-SINR / CQI) one or more combinations of CMRs and IMRs that may provide the best (e.g., maximum) L1-SINR, RI, or CQI. The UE 1020 may further predict one or more sets of reported quantities for each of such combinations, wherein each set of quantities is determined at least in part based on the assumption that the IMR is used in the associated combination and the CMR is used as a virtual CMR connected to the parent actual CMR associated with the combination. The UE 1020 may report one or more sets of predicted quantities for such identified combinations, (optionally) together with the associated CMR-ID and the associated virtual IMR-ID.

[0176] As indicated above, Fig.11 are provided as examples. Other examples can be found in the Fig.11 The examples described are different.

[0177] In some aspects, a CSI report may indicate one or more resource sets or interference hypothesis (value) sets associated with one or more combinations of CMR / virtual CMR and IMR / virtual IMR based at least in part on a CSI report configuration. In an example, the number of virtual CMR / IMRs may be addressed in a CSI report. The number of hypothesis sets associated with a certain identified combination may be addressed in a CSI report and may be based at least in part on a report configuration or indication. For example, 4 sets may be addressed for the actual IMR and actual CMR combination that provides the strongest L1-SINR, while 1 set may be addressed for the remaining combinations. The configuration or indication may be an RRC configuration for a CSI report setting associated with a CSI report indicated by a MAC CE that activates semi-persistent CSI reporting, an RRC configuration configured by an aperiodic CSI trigger state associated with an AP CSI report, or a DCI indicated when an aperiodic CSI report is triggered by a DCI.

[0178] In some aspects, the QCL assumptions for the virtual IMR may be used to determine other reporting quantities (e.g., measurements). The QCL type D of the one-to-one mapped IMR may be expected to be the same as the paired CMR. When determining the reporting quantities for the CSI report, considering a specific actual / virtual CMR and IMR combination, the QCL type D associated with the virtual IMR may be expected to be the same as the QCL type D source of the paired CMR. For example, when considering a combination of an actual CMR and a virtual IMR, the QCL type D for the virtual IMR may be the QCL type D of the actual CMR. That is, when predicting interference or noise caused by the virtual IMR, the UE 1020 may expect to use a receive spatial filter for receiving the actual CMR under consideration. In another example, when considering a combination of a virtual CMR and a virtual IMR, the QCL type D for the virtual IMR may be the QCL type D of the virtual CMR. For example, UE 1020 may receive an indication from network entity 1010 that the QCL type D source of the virtual CMR is the parent actual CMR, and UE 1020 may anticipate using a receive spatial filter for receiving the parent actual CMR when predicting interference or noise caused by the virtual IMR.

[0179] In some aspects, the QCL assumption for the virtual IMR may be used to predict the interference of the virtual IMR based at least in part on the mother IMR. It is noted that in order to better estimate the interference caused by the virtual IMR based on the mother IMR, rather than measuring the mother IMR based on the spatial receive filter associated with the corresponding CMR, the UE may better use the spatial receive filter to directly measure the mother IMR. When predicting the interference associated with the virtual IMR based on the actual IMR, the QCL type D associated with the actual IMR may be different from the actual / virtual CMR associated with the IMR. That is, the QCL type D associated with the actual IMR may be different from the QCL type D assumption.

[0180] In some aspects, the CSI report may indicate the uncertainty level of one or more values ​​in the CSI report. These values ​​may be associated with other reporting quantities (e.g., measurements). When virtual CMR and virtual IMR involve calculating SINR when reporting reporting quantities (including at least RI / CQI / PMI / LI / L1-SINR / L3-SINR), UE 1020 may additionally report the uncertainty level associated with such reporting quantities. For example, a conventional CQI may be determined based on actual measurements or predictions. Therefore, if a prediction is involved, it would be beneficial for UE 1020 to report the uncertainty level associated with the report. In another example, the uncertainty level may be represented by a variance or standard deviation associated with a predicted reporting quantity (e.g., average CQI and standard CQI).

[0181] By using virtual IMR and / or virtual CMR, the UE and the network may save power, processing resources, and signaling resources.

[0182] Fig.12 1 is a diagram illustrating an example process 1200 performed, for example, by a UE according to the present disclosure. Example process 1200 is an example in which a UE (eg, UE 120, UE 1020) performs operations associated with CSI reporting using a virtual IMR.

[0183] like Fig.12 As shown, in some aspects, process 1200 may include generating a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource that is used for beam management and is not transmitted (block 1210). Fig.16 The communication manager 1608 and / or reporting component 1610 depicted in FIG. 1 may generate a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource that is used for beam management and is not transmitted, as described above.

[0184] like Fig.12As further shown, in some aspects, process 1200 may include sending the CSI report (block 1220). For example, a UE (e.g., using Fig.16 The communication manager 1608 and / or the sending component 1604 depicted in FIG. 1 may send a CSI report as described above.

[0185] Process 1200 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0186] In a first aspect, process 1200 includes receiving a virtual IMR indication for the one or more virtual IMRs.

[0187] In a second aspect, alone or in combination with the first aspect, generating the CSI report includes generating the CSI report further based at least in part on a traffic payload.

[0188] In a third aspect, alone or in combination with one or more of the first and second aspects, the one or more virtual IMRs are associated with one or more CMRs being transmitted, and generating the CSI report includes: generating the CSI report further based at least in part on measurements of the one or more CMRs.

[0189] In a fourth aspect, alone or in combination with one or more of the first to third aspects, a beam shape of each virtual IMR is associated with a beam shape of a corresponding CMR.

[0190] In a fifth aspect, alone or in combination with one or more of the first to fourth aspects, generating the CSI report includes: generating the CSI report further based at least in part on an association with the transmitted one or more IMRs.

[0191] In a sixth aspect, alone or in combination with one or more of the first to fifth aspects, process 1200 includes determining a combination of transmitted CMRs and IMRs that provides a signal strength or quality that satisfies a threshold.

[0192] In a seventh aspect, either alone or in combination with one or more of the first to sixth aspects, process 1200 includes: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0193] In an eighth aspect, alone or in combination with one or more of the first to seventh aspects, process 1200 includes predicting interference of one or more virtual IMRs based at least in part on the one or more IMRs.

[0194] In a ninth aspect, alone or in combination with one or more of the first to eighth aspects, the process 1200 includes determining a combination of a virtual IMR and a transmitted CMR that provides a signal strength or quality that satisfies a threshold.

[0195] In a tenth aspect, either alone or in combination with one or more of the first to ninth aspects, process 1200 comprises: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0196] In the eleventh aspect, alone or in combination with one or more of the first to tenth aspects, each of the one or more virtual IMRs is a QCL source resource for a TCI state, which QCL source resource corresponds to the QCL of the TCI state of the CMR in the one or more CMRs being transmitted.

[0197] In a twelfth aspect, alone or in combination with one or more of the first to eleventh aspects, the number of the one or more CMRs is equal to the number of the one or more virtual IMRs.

[0198] In a thirteenth aspect, alone or in combination with one or more of the first to twelfth aspects, the number of the one or more CMRs is not equal to the number of the one or more virtual IMRs.

[0199] In a fourteenth aspect, alone or in combination with one or more of the first to thirteenth aspects, the one or more virtual IMRs are associated with one or more virtual CMRs, each virtual CMR represents a logical resource used for beam management and not transmitted, and generating the CSI report includes: further generating the CSI report based at least in part on the one or more virtual CMRs.

[0200] In a fifteenth aspect, alone or in combination with one or more of the first to fourteenth aspects, the number of the one or more virtual CMRs is equal to the number of the one or more virtual IMRs.

[0201] In a sixteenth aspect, alone or in combination with one or more of the first to fifteenth aspects, the number of the one or more virtual CMRs is not equal to the number of the one or more virtual IMRs.

[0202] In a seventeenth aspect, alone or in combination with one or more of the first to sixteenth aspects, the process 1200 includes determining a combination of a virtual CMR and a virtual IMR that provides a signal strength or quality that satisfies a threshold.

[0203] In an eighteenth aspect, either alone or in combination with one or more of the first to seventeenth aspects, process 1200 comprises: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0204] In a nineteenth aspect, alone or in combination with one or more of the first to eighteenth aspects, the CSI report indicates one or more resource sets or interference hypothesis sets associated with the determined combination based at least in part on a reporting configuration.

[0205] In the twentieth aspect, either alone or in combination with one or more of the first to nineteenth aspects, each of the one or more virtual IMRs is a QCL source resource for a TCI state, which QCL source resource corresponds to a QCL for the TCI state of a virtual CMR in the one or more virtual CMRs.

[0206] In a twenty-first aspect, alone or in combination with one or more of the first to twentieth aspects, the CSI report indicates an uncertainty level of one or more values ​​in the CSI report.

[0207] although Fig.12 An example block diagram of process 1200 is shown, but in some aspects, process 1200 may include Fig.12 Additional blocks, fewer blocks, different blocks, or blocks arranged in a different manner than those depicted in the process 1200. Additionally or alternatively, two or more blocks of the blocks of process 1200 may be performed in parallel.

[0208] Fig.13 1 is a diagram illustrating an example process 1300 performed, for example, by a UE according to the present disclosure. The example process 1300 is an example in which a UE (eg, UE 120, UE 1020) performs operations associated with CSI reporting using actual IMRs and virtual CMRs.

[0209] like Fig.13 As shown, in some aspects, process 1300 may include generating a CSI report based at least in part on one or more transmitted IMRs and one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted (block 1310). Fig.16 The communication manager 1608 and / or reporting component 1610 depicted in the figure may generate a CSI report based at least in part on one or more IMRs that are transmitted and one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted, as described above.

[0210] like Fig.13As further shown, in some aspects, process 1300 may include sending the CSI report (block 1320). For example, a UE (e.g., using Fig.16 The communication manager 1608 and / or the sending component 1604 depicted in FIG. 1 may send a CSI report as described above.

[0211] Process 1300 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0212] In a first aspect, the number of the one or more virtual CMRs is equal to the number of the one or more IMRs.

[0213] In a second aspect, alone or in combination with the first aspect, the number of the one or more virtual CMRs is not equal to the number of the one or more IMRs.

[0214] In a third aspect, alone or in combination with one or more of the first and second aspects, process 1300 includes determining a combination of a virtual CMR and an IMR that provides a signal strength or quality that satisfies a threshold.

[0215] In a fourth aspect, alone or in combination with one or more of the first to third aspects, process 1300 includes: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0216] In a fifth aspect, either alone or in combination with one or more of the first to fourth aspects, each of the one or more IMRs is a QCL source resource for a TCI state, which QCL source resource corresponds to a QCL for the TCI state of a virtual CMR in the one or more virtual CMRs.

[0217] although Fig.13 Example blocks of process 1300 are shown, but in some aspects, process 1300 may include Fig.13 Additional blocks, fewer blocks, different blocks, or blocks arranged in a different manner than those depicted in the process 1300. Additionally or alternatively, two or more blocks of the blocks of process 1300 may be performed in parallel.

[0218] Fig.14 is a diagram illustrating an example process 1400, for example, performed by a network entity according to the present disclosure. The example process 1400 is an example in which a network entity (eg, network node 110, network entity 1010) performs operations associated with CSI reporting using a virtual IMR.

[0219] like Fig.14As shown, in some aspects, process 1400 may include: sending a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted (block 1410). For example, a network entity (e.g., using Fig.17 The communication manager 1708 and / or the sending component 1704 depicted in the figure may send a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource used for beam management and not transmitted: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted, as described above.

[0220] like Fig.14 As further shown, in some aspects, process 1400 may include receiving the CSI report (block 1420). For example, a network entity (e.g., using Fig.17 The communication manager 1708 and / or receiving component 1702 depicted in can receive the CSI report as described above.

[0221] Process 1400 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0222] although Fig.14 Example blocks of process 1400 are shown, but in some aspects, process 1400 may include Fig.14 Additional blocks, fewer blocks, different blocks, or blocks arranged in a different manner than those depicted in the process 1400. Additionally or alternatively, two or more blocks of the blocks of process 1400 may be performed in parallel.

[0223] Fig.15 is a diagram illustrating an example process 1500 performed, for example, by a network entity according to the present disclosure. The example process 1500 is an example in which a network entity (eg, network node 110, network entity 1010) performs operations associated with CSI reporting using actual IMRs and virtual CMRs.

[0224] like Fig.15As shown, in some aspects, process 1500 may include: sending a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent (block 1510). For example, a network entity (e.g., using Fig.17 The communication manager 1708 and / or the sending component 1704 depicted in the figure may send a configuration for generating a CSI report based at least in part on one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent, as described above.

[0225] like Fig.15 As further shown, in some aspects, process 1500 may include receiving the CSI report (block 1520). For example, a network entity (e.g., using Fig.17 The communication manager 1708 and / or receiving component 1702 depicted in can receive the CSI report as described above.

[0226] Process 1500 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0227] although Fig.15 Example blocks of process 1500 are shown, but in some aspects, process 1500 may include Fig.15 Additional blocks, fewer blocks, different blocks, or blocks arranged in a different manner than those depicted in the process 1500. Additionally or alternatively, two or more blocks of the blocks of process 1500 may be performed in parallel.

[0228] Fig.16 1 is a diagram of an example apparatus 1600 for wireless communication according to the present disclosure. Apparatus 1600 may be a UE (e.g., UE 120, UE 1020), or a UE may include apparatus 1600. In some aspects, apparatus 1600 includes a receiving component 1602 and a transmitting component 1604 that may communicate with each other (e.g., via one or more buses and / or one or more other components). As shown, apparatus 1600 may communicate with another apparatus 1606 (such as a UE, a base station, or another wireless communication device) using receiving component 1602 and transmitting component 1604. As further shown, apparatus 1600 may include a communication manager 1608. Communication manager 1608 may control and / or otherwise manage one or more operations of receiving component 1602 and / or transmitting component 1604. In some aspects, communication manager 1608 may include a communication manager 1608 in conjunction with Figure 2One or more antennas, modems, controllers / processors, memories, or combinations thereof of the UE described herein. The communication manager 1608 may be or be similar to Figure 1 and Figure 2 For example, in some aspects, the communication manager 1608 can be configured to perform one or more of the functions described as being performed by the communication manager 140. In some aspects, the communication manager 1608 can include a receiving component 1602 and / or a sending component 1604. The communication manager 140 can include one or more of a reporting component 1610 and / or a prediction component 1612, among others.

[0229] In some aspects, the apparatus 1600 may be configured to perform the Figures 1 to 11 Additionally or alternatively, the apparatus 1600 may be configured to perform one or more processes described herein, such as Fig.12 The process 1200 Fig.13 In some aspects, Fig.16 The device 1600 and / or one or more components shown may include a combination of Figure 2 Additionally or alternatively, Fig.16 One or more of the components shown may be combined with Figure 2 Additionally or alternatively, one or more components in the set of components may be implemented at least in part as software stored in a memory. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and can be executed by a controller or processor to perform the function or operation of the component.

[0230] The receiving component 1602 may receive communications from the device 1606, such as reference signals, control information, data communications, or combinations thereof. The receiving component 1602 may provide the received communications to one or more other components of the device 1600. In some aspects, the receiving component 1602 may perform signal processing (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) on the received communications and may provide the processed signals to one or more other components of the device 1600. In some aspects, the receiving component 1602 may include combining Figure 2 One or more antennas, modems, demodulators, MIMO detectors, receive processors, controllers / processors, memories, or combinations thereof of a described UE.

[0231] Transmit component 1604 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1606. In some aspects, one or more other components of device 1600 may generate communications and may provide the generated communications to transmit component 1604 for transmission to device 1606. In some aspects, transmit component 1604 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1606. In some aspects, transmit component 1604 may include combining Figure 2 One or more antennas, modems, modulators, transmit MIMO processors, transmit processors, controllers / processors, memories, or combinations thereof of the described UE. In some aspects, the transmit component 1604 can be co-located with the receive component 1602 in a transceiver.

[0232] In some aspects, reporting component 1610 can generate a CSI report based at least in part on one or more virtual IMRs, each virtual IMR representing a logical resource used for beam management and not transmitted.Transmitting component 1604 can transmit the CSI report.

[0233] The receiving component 1602 can receive a virtual IMR indication of the one or more virtual IMRs. The predicting component 1612 can determine a combination of an IMR and a transmitted CMR that provides a signal strength or quality that satisfies a threshold. The predicting component 1612 can predict one or more measurements based at least in part on the determined combination. The sending component 1604 can send a predicted indication of the predicted one or more measurements.

[0234] Prediction component 1612 can predict interference of one or more virtual IMRs based at least in part on the one or more IMRs.Prediction component 1612 can determine a combination of virtual IMRs and transmitted CMRs that provides a signal strength or quality that satisfies a threshold.

[0235] Predicting component 1612 can predict one or more measurements based at least in part on the determined combination.Sending component 1604 can send a predicted indication of the predicted one or more measurements.

[0236] Prediction component 1612 can determine a combination of virtual CMRs and virtual IMRs that provide a signal strength or quality that meets a threshold. Prediction component 1612 can predict one or more measurements based at least in part on the determined combination. Transmission component 1604 can transmit a prediction indication of the predicted one or more measurements.

[0237] In some aspects, reporting component 1610 can generate a CSI report based at least in part on the transmitted one or more IMRs and one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. Transmitting component 1604 can transmit the CSI report.

[0238] Prediction component 1612 can determine a combination of virtual CMR and IMR that provides a signal strength or quality that meets a threshold. Prediction component 1612 can predict one or more measurements based at least in part on the determined combination. Transmission component 1604 can transmit a prediction indication of the predicted one or more measurements.

[0239] Fig.16 The number and arrangement of components shown are provided as examples. In practice, there may be Fig.16 Additional components, fewer components, different components, or components arranged in a different manner than those shown. Fig.16 Two or more components shown may be implemented in a single component, or Fig.16 The single component shown may be implemented as multiple distributed components. Additionally or alternatively, Fig.16 The illustrated set of component(s) may be described as being executable by Fig.16 Another collection of components shown performs one or more functions.

[0240] Fig.17 1700 is a diagram of an example apparatus 1700 for wireless communication according to the present disclosure. Apparatus 1700 may be a network entity (e.g., network node 110, network entity 1010), or a network entity may include apparatus 1700. In some aspects, apparatus 1700 includes a receiving component 1702 and a transmitting component 1704 that may communicate with each other (e.g., via one or more buses and / or one or more other components). As shown, apparatus 1700 may communicate with another apparatus 1706 (such as a UE, a base station, or another wireless communication device) using receiving component 1702 and transmitting component 1704. As further shown, apparatus 1700 may include a communication manager 1708. Communication manager 1708 may control and / or otherwise manage one or more operations of receiving component 1702 and / or transmitting component 1704. In some aspects, communication manager 1708 may include a communication manager 1708 in conjunction with receiving component 1702 and / or transmitting component 1704. Figure 2 One or more antennas, modems, controllers / processors, memories, or combinations thereof of the network entities described. The communication manager 1708 may be or be similar to Figure 1 and Figure 2For example, in some aspects, the communications manager 1708 can be configured to perform one or more of the functions described as being performed by the communications manager 150. In some aspects, the communications manager 1708 can include a receiving component 1702 and / or a sending component 1704. The communications manager 1708 can include a reporting component 1710, among other things.

[0241] In some aspects, the apparatus 1700 may be configured to perform the Figures 1 to 11 Additionally or alternatively, the apparatus 1700 may be configured to perform one or more processes described herein, such as Fig.14 The process of 1400 Fig.15 In some aspects, Fig.17 The device 1700 and / or one or more components shown may include a combination of Figure 2 Additionally or alternatively, Fig.17 One or more of the components shown may be combined with Figure 2 Additionally or alternatively, one or more components in the set of components may be implemented at least in part as software stored in a memory. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and can be executed by a controller or processor to perform the function or operation of the component.

[0242] The receiving component 1702 may receive communications, such as reference signals, control information, data communications, or combinations thereof, from the device 1706. The receiving component 1702 may provide the received communications to one or more other components of the device 1700. In some aspects, the receiving component 1702 may perform signal processing (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) on the received communications and may provide the processed signals to one or more other components of the device 1700. In some aspects, the receiving component 1702 may include combining Figure 2 One or more antennas, modems, demodulators, MIMO detectors, receive processors, controllers / processors, memories, or combinations thereof of the described network entities.

[0243] Transmit component 1704 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1706. In some aspects, one or more other components of device 1700 may generate communications and may provide the generated communications to transmit component 1704 for transmission to device 1706. In some aspects, transmit component 1704 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1706. In some aspects, transmit component 1704 may include combining Figure 2 One or more antennas, modems, modulators, transmit MIMO processors, transmit processors, controllers / processors, memories, or combinations thereof of the described network entities. In some aspects, the transmit component 1704 can be co-located with the receive component 1702 in a transceiver.

[0244] In some aspects, the sending component 1704 can send a configuration for generating a CSI report based at least in part on one or more virtual IMRs and one or more of the following: one or more CMRs, or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted. The reporting component 1710 can generate the report. The receiving component 1702 can receive the CSI report.

[0245] In some aspects, the sending component 1704 can send a configuration for generating a CSI report based at least in part on the one or more IMRs and one or more virtual CMRs that are sent, each virtual CMR representing a logical resource that is used for beam management and is not sent. The reporting component 1710 can generate the report. The receiving component 1702 can receive the CSI report.

[0246] Fig.17 The number and arrangement of components shown are provided as examples. In practice, there may be Fig.17 Additional components, fewer components, different components, or components arranged in a different manner than those shown. Fig.17 Two or more components shown may be implemented in a single component, or Fig.17 The single component shown may be implemented as multiple distributed components. Additionally or alternatively, Fig.17 The assembly of components (one or more components) shown may be described as being executable by Fig.17 Another collection of components shown performs one or more functions.

[0247] The following provides an overview of some aspects of the disclosure:

[0248] Aspect 1: A method of wireless communication performed by a device of a user equipment (UE), the method comprising: generating a channel state information (CSI) report based at least in part on one or more virtual interference measurement resources (IMRs), each virtual IMR representing a logical resource used for beam management and not transmitted; and sending the CSI report.

[0249] Aspect 2: The method according to aspect 1, further comprising: receiving a virtual IMR indication for the one or more virtual IMRs.

[0250] Aspect 3: The method according to aspect 1 or 2, wherein generating the CSI report includes: generating the CSI report further based at least in part on a traffic payload.

[0251] Aspect 4: A method according to any one of Aspects 1 to 3, wherein the one or more virtual IMRs are associated with one or more channel measurement resources (CMRs) transmitted, and wherein generating the CSI report includes: further generating the CSI report based at least in part on the measurement of the one or more CMRs.

[0252] Aspect 5: The method according to aspect 4, wherein the beam shape of each virtual IMR is associated with the beam shape of the corresponding CMR.

[0253] Aspect 6: The method according to aspect 4 or 5, wherein generating the CSI report includes: generating the CSI report based further at least in part on an association with one or more transmitted IMRs.

[0254] Aspect 7: The method according to aspect 6, further comprising: determining a combination of the IMR and the transmitted CMR that provides a signal strength or quality that satisfies a threshold.

[0255] Aspect 8: The method according to aspect 7, the method further comprising: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0256] Aspect 9: The method according to aspect 6, further comprising: predicting interference of one or more virtual IMRs based at least in part on the one or more IMRs.

[0257] Aspect 10: According to the method of any one of aspects 1 to 3, the method further comprises: determining a combination of a virtual IMR and a transmitted channel measurement resource (CMR) that provides a signal strength or quality that satisfies a threshold.

[0258] Aspect 11: The method according to aspect 10, the method further comprising: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0259] Aspect 12: A method according to any one of Aspects 1 to 11, wherein each of the one or more virtual IMRs is a quasi-co-site (QCL) source resource for sending a configuration indicator (TCI) state, and the quasi-co-site (QCL) source resource corresponds to the QCL of the TCI state of the CMR in one or more channel measurement resources (CMRs) being sent.

[0260] Aspect 13: The method according to aspect 12, wherein the number of the one or more CMRs is equal to the number of the one or more virtual IMRs.

[0261] Aspect 14: The method according to aspect 12, wherein the number of the one or more CMRs is not equal to the number of the one or more virtual IMRs.

[0262] Aspect 15: A method according to any one of Aspects 1 to 3, wherein the one or more virtual IMRs are associated with one or more virtual channel measurement resources (CMRs), each virtual CMR represents a logical resource used for beam management and not transmitted, and wherein generating the CSI report includes: further generating the CSI report based at least in part on the one or more virtual CMRs.

[0263] Aspect 16: The method according to aspect 15, wherein the number of the one or more virtual CMRs is equal to the number of the one or more virtual IMRs.

[0264] Aspect 17: The method according to aspect 15, wherein the number of the one or more virtual CMRs is not equal to the number of the one or more virtual IMRs.

[0265] Aspect 18: The method according to aspect 17, further comprising: determining a combination of a virtual CMR and a virtual IMR that provides a signal strength or quality that satisfies a threshold.

[0266] Aspect 19: The method according to aspect 18, the method further comprising: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0267] Aspect 20: The method according to aspect 18 or 19, wherein the CSI report indicates one or more resource sets or interference hypothesis sets associated with the determined combination based at least in part on a reporting configuration.

[0268] Aspect 21: A method according to Aspect 15, wherein each of the one or more virtual IMRs is a quasi-co-site (QCL) source resource for sending a configuration indicator (TCI) state, and the quasi-co-site (QCL) source resource corresponds to the QCL of the TCI state of the virtual CMR in the one or more virtual CMRs.

[0269] Aspect 22: The method according to any one of aspects 1 to 21, wherein the CSI report indicates an uncertainty level of one or more values ​​in the CSI report.

[0270] Aspect 23: A method of wireless communication performed by a device of a user equipment (UE), the method comprising: generating a channel state information (CSI) report based at least in part on one or more interference measurement resources (IMRs) and one or more virtual channel measurement resources (CMRs) being sent, each virtual CMR representing a logical resource used for beam management and not being sent; and sending the CSI report.

[0271] Aspect 24: The method according to aspect 23, wherein the number of the one or more virtual CMRs is equal to the number of the one or more IMRs.

[0272] Aspect 25: The method according to aspect 23, wherein the number of the one or more virtual CMRs is not equal to the number of the one or more IMRs.

[0273] Aspect 26: The method according to any one of aspects 23 to 25, further comprising: determining a combination of a virtual CMR and an IMR that provides a signal strength or quality that satisfies a threshold.

[0274] Aspect 27: The method according to aspect 26, the method further comprising: predicting one or more measurements based at least in part on the determined combination; and sending a prediction indication of the predicted one or more measurements.

[0275] Aspect 28: A method according to any one of Aspects 23 to 27, wherein each of the one or more IMRs is a quasi-co-site (QCL) source resource for sending a configuration indicator (TCI) status, and the quasi-co-site (QCL) source resource corresponds to the QCL for the TCI status of a virtual CMR in the one or more virtual CMRs.

[0276] Aspect 29: A method of wireless communication performed by a device of a network entity, the method comprising: sending a configuration for generating a channel state information (CSI) report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource used for beam management and not transmitted: one or more channel measurement resources (CMRs), or one or more virtual CMRs, each virtual CMR representing a logical resource used for beam management and not transmitted; and receiving the CSI report.

[0277] Aspect 30: A method of wireless communication performed by a device of a network entity, the method comprising: sending a configuration for generating a channel state information (CSI) report based at least in part on one or more interference measurement resources (IMRs) and one or more virtual channel measurement resources (CMRs) being sent, each virtual CMR representing a logical resource used for beam management and not being sent; and receiving the CSI report.

[0278] Aspect 31: An apparatus for performing wireless communications at a device, the apparatus comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method according to one or more of Aspects 1 to 30.

[0279] Aspect 32: A device for wireless communication, the device comprising a memory and one or more processors, the one or more processors coupled to the memory, the one or more processors configured to execute the method according to one or more of aspects 1 to 30.

[0280] Aspect 33: An apparatus for wireless communication, the apparatus comprising at least one component for performing the method according to one or more of aspects 1 to 30.

[0281] Aspect 34: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform the method according to one or more of aspects 1 to 30.

[0282] Aspect 35: A non-transitory computer-readable medium storing an instruction set for wireless communication, the instruction set comprising one or more instructions, which, when executed by one or more processors of a device, causes the device to perform a method according to one or more of aspects 1 to 30.

[0283] 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 various aspects.

[0284] As used herein, the term "component" is intended to be broadly interpreted as hardware, and / or a combination of hardware and software. Whether referred to as software, firmware, middleware, microcode, hardware description language or other names, "software" should be broadly interpreted as meaning instructions, instruction sets, codes, code segments, program codes, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, processes and / or functions, etc. As used herein, "processor" is implemented by a combination of hardware and / or hardware and software. It will be apparent that the system and / or method described herein can be implemented by a combination of hardware and / or hardware and software in different forms. The actual dedicated control hardware or software code used to implement these systems and / or methods does not limit various aspects. Therefore, the operation and behavior of the system and / or method are not described herein with reference to specific software codes, because it will be understood by those skilled in the art that software and hardware can be designed to implement the system and / or method at least in part based on the description herein.

[0285] As used herein, "satisfying a threshold" may refer to a value being greater than a threshold, greater than or equal to a threshold, less than a threshold, less than or equal to a threshold, equal to a threshold, not equal to a threshold, etc., depending on the context.

[0286] Although the specific combination of features is stated in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. Many of these features can be combined in a manner that is not specifically stated in the claims and / or is not disclosed in the specification. The disclosure of various aspects includes each dependent claim combined with each other claim in the claim set. As used herein, the phrase "at least one of" the list of items refers to any combination of these items (it includes a single member). 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, and any combination with multiple identical elements (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 sorting of a, b and c).

[0287] Any element, action or instruction used herein should not be interpreted as critical or essential unless explicitly stated as such. In addition, as used herein, the article "one" is intended to include one or more items and can be used interchangeably with "one or more". In addition, as used herein, the article "said" is intended to include one or more items connected to the article "said" and can be used interchangeably with "one or more". In addition, as used herein, the terms "set" and "group" are intended to include one or more items and can be used interchangeably with "one or more". If only one item is intended to be referred to, the phrase "only one" or similar terms will be used. In addition, as used herein, the terms "have", "have", "have" and the like are intended to be open terms that do not limit the elements they modify (for example, "an element having" A may also have B). In addition, the phrase "based on" is intended to mean "based at least in part on", unless otherwise explicitly stated. In addition, as used herein, the term "or" is intended to be open when used in a series and can be used interchangeably with "and / or", unless otherwise explicitly stated (for example, if used in conjunction with "either" or "only one"

Claims

1. A device for a user equipment (UE) for wireless communication, the device comprising: Memory; and one or more processors, the one or more processors coupled to the memory, the one or more processors configured to: generating a channel state information (CSI) report based at least in part on one or more virtual interference measurement resources (IMRs), each virtual IMR representing a logical resource used for beam management and not transmitted; as well as Send the CSI report. 2 . The apparatus of claim 1 , wherein the one or more processors are configured to receive a virtual IMR indication for the one or more virtual IMRs.

3. The apparatus of claim 1 , wherein the one or more processors for generating the CSI report are configured to generate the CSI report based further at least in part on a traffic payload.

4. The apparatus of claim 1 , wherein the one or more virtual IMRs are associated with one or more channel measurement resources (CMRs) that are transmitted, and wherein the one or more processors for generating the CSI report are configured to generate the CSI report based further at least in part on measurements of the one or more CMRs. The apparatus of claim 4 , wherein a beam shape of each virtual IMR is associated with a beam shape of a corresponding CMR.

6. The apparatus of claim 4, wherein the one or more processors for generating the CSI report are configured to generate the CSI report based further at least in part on an association with one or more transmitted IMRs. 7 . The apparatus of claim 6 , wherein the one or more processors are configured to determine a combination of an IMR and a transmitted CMR that provides a signal strength or quality that satisfies a threshold.

8. The apparatus of claim 7, wherein the one or more processors are configured to: predicting one or more measurements based at least in part on the determined combination; and A predicted indication of the predicted one or more measurements is sent.

9. The apparatus of claim 6, wherein the one or more processors are configured to predict interference of one or more virtual IMRs based at least in part on the one or more IMRs.

10. The apparatus of claim 1, wherein the one or more processors are configured to determine a combination of a virtual IMR and a transmitted channel measurement resource (CMR) that provides a signal strength or quality that meets a threshold.

11. The apparatus of claim 10, wherein the one or more processors are configured to: predicting one or more measurements based at least in part on the determined combination; and A predicted indication of the predicted one or more measurements is sent.

12. The apparatus of claim 1, wherein each of the one or more virtual IMRs is a quasi-co-site (QCL) source resource for sending a configuration indicator (TCI) state, the quasi-co-site (QCL) source resource corresponding to a QCL for a TCI state of a channel measurement resource (CMR) in one or more channel measurement resources (CMRs) being sent. 13 . The apparatus of claim 12 , wherein a number of the one or more CMRs is equal to a number of the one or more virtual IMRs. 14 . The apparatus of claim 12 , wherein a number of the one or more CMRs is not equal to a number of the one or more virtual IMRs.

15. The apparatus of claim 1 , wherein the one or more virtual IMRs are associated with one or more virtual channel measurement resources (CMRs), each virtual CMR representing a logical resource that is used for beam management and is not transmitted, and wherein the one or more processors for generating the CSI report are configured to further generate the CSI report based at least in part on the one or more virtual CMRs. 16 . The apparatus of claim 15 , wherein the number of the one or more virtual CMRs is equal to the number of the one or more virtual IMRs. 17 . The apparatus of claim 15 , wherein the number of the one or more virtual CMRs is not equal to the number of the one or more virtual IMRs.

18. The apparatus of claim 17, wherein the one or more processors are configured to determine a combination of a virtual CMR and a virtual IMR that provides a signal strength or quality that satisfies a threshold.

19. The apparatus of claim 18, wherein the one or more processors are configured to: predicting one or more measurements based at least in part on the determined combination; and A predicted indication of the predicted one or more measurements is sent.

20. The apparatus of claim 18, wherein the CSI report indicates one or more resource sets or interference hypothesis sets associated with the determined combination based at least in part on a reporting configuration.

21. The apparatus of claim 15, wherein each of the one or more virtual IMRs is a quasi-co-located (QCL) source resource for transmitting a configuration indicator (TCI) state, the quasi-co-located (QCL) source resource corresponding to a QCL for a TCI state of a virtual CMR of the one or more virtual CMRs.

22. The apparatus of claim 1, wherein the CSI report indicates an uncertainty level of one or more values ​​in the CSI report.

23. An apparatus of a user equipment (UE) for wireless communication, the apparatus comprising: Memory; and one or more processors, the one or more processors coupled to the memory, the one or more processors configured to: generating a channel state information (CSI) report based at least in part on the transmitted one or more interference measurement resources (IMRs) and one or more virtual channel measurement resources (CMRs), each virtual CMR representing a logical resource used for beam management and not transmitted; and Send the CSI report.

24. The apparatus of claim 23, wherein the number of the one or more virtual CMRs is equal to the number of the one or more IMRs.

25. The apparatus of claim 23, wherein a number of the one or more virtual CMRs is not equal to a number of the one or more IMRs.

26. The apparatus of claim 23, wherein the one or more processors are configured to determine a combination of virtual CMR and IMR that provides a signal strength or quality that meets a threshold.

27. The apparatus of claim 26, wherein the one or more processors are configured to: predicting one or more measurements based at least in part on the determined combination; and A predicted indication of the predicted one or more measurements is sent.

28. An apparatus according to claim 23, wherein each of the one or more IMRs is a quasi-co-site (QCL) source resource for sending a configuration indicator (TCI) state, and the quasi-co-site (QCL) source resource corresponds to the QCL of the TCI state of a virtual CMR in the one or more virtual CMRs.

29. An apparatus of a network entity for wireless communication, the apparatus comprising: Memory; and one or more processors, the one or more processors coupled to the memory, the one or more processors configured to: Sending a configuration for generating a channel state information (CSI) report based at least in part on one or more virtual IMRs and one or more of the following, each virtual IMR representing a logical resource used for beam management and not transmitted: One or more channel measurement resources (CMRs), or one or more virtual CMRs, each virtual CMR representing a logical resource that is used for beam management and is not transmitted; and The CSI report is received.

30. An apparatus of a network entity for wireless communication, the apparatus comprising: Memory; and one or more processors, the one or more processors coupled to the memory, the one or more processors configured to: transmitting a configuration for generating a channel state information (CSI) report based at least in part on the transmitted one or more interference measurement resources (IMRs) and one or more virtual channel measurement resources (CMRs), each virtual CMR representing a logical resource used for beam management and not transmitted; and The CSI report is received.

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