TCI state switching for UE requests for blocked conditions

Abstract

Methods and apparatus for a UE requesting TCI state switching for a blocking condition. The apparatus predicts a blocking condition of a first beam communicating with a network node. The apparatus sends, in response to the predicted blocking condition, a beam switching indication to the network node indicating a scheduled change in TCI state mapped from the first beam to a second beam. The apparatus may schedule a beam change to the second beam based on the predicted blocking condition. The apparatus may correlate a beam change at the UE to the second beam with a corresponding beam change at the network node.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. patent application serial number 17 / 808,923, filed on June 24, 2022, entitled "METHODS FOR UE TO REQUEST GNB TCI STATE SWITCH FOR BLOCKAGE CONDITIONS," which is expressly incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates generally to communication systems, and more particularly to configurations for user equipment (UE) to request a transmission configuration indicator (TCI) state switch for a blocking condition. Background Art

[0004] Wireless communication systems are widely deployed to provide a variety of telecommunication services, such as telephony, video, data, messaging, and broadcast. Typical wireless communication systems may employ multiple access technologies capable of supporting communication with multiple users by sharing available system resources. 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, and time division synchronous code division multiple access (TD-SCDMA) systems.

[0005] These multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different wireless devices to communicate at city, country, region, and even global levels. An example telecommunication standard is 5G New Radio (NR). 5G NR is part of the continuous mobile broadband evolution promulgated by the Third Generation Partnership Project (3GPP) to meet new requirements associated with latency, reliability, security, scalability (e.g., with the Internet of Things (IoT)) and other requirements. 5GNR includes services associated with enhanced mobile broadband (eMBB), massive machine type communication (mMTC), and ultra-reliable low latency communication (URLLC). Certain aspects of 5G NR may be based on 4G Long Term Evolution (LTE) standards. It is necessary to further improve 5G NR technology. In addition, these improvements may also be applicable to other multiple access technologies and telecommunication standards that employ these technologies. Summary of the invention

[0006] A simplified summary of one or more aspects is presented below to provide a basic understanding of these aspects. This summary is not an extensive review of all contemplated aspects. This summary neither identifies the key or important elements of all aspects, nor describes the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to a more detailed description presented later.

[0007] In one aspect of the present disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a device at a UE. The apparatus may be a processor and / or a modem at the UE or the UE itself. The apparatus predicts a blocking condition for a first beam communicating with a network node. The apparatus sends a beam switching indication of a scheduled change from the first beam to a second beam mapping indicating a transmission configuration indicator (TCI) state to the network node in response to the predicted blocking condition.

[0008] In one aspect of the present disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a device at a network node. The apparatus may be a processor and / or a modem at a network node or the network node itself. The apparatus communicates with a UE using a first beam. The apparatus obtains a beam switching indication, the beam switching indication including a scheduled change of a transmission configuration indicator (TCI) state from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam.

[0009] To achieve the aforementioned and related purposes, one or more aspects include the features fully described below and particularly pointed out in the claims. The following description and the accompanying drawings set forth in detail some exemplary features of one or more aspects. However, these features indicate only some of the various ways in which the principles of the various aspects can be employed. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 is a diagram illustrating an example of a wireless communication system and an access network.

[0011] Figure 2A is a diagram illustrating an example of a first frame according to various aspects of the present disclosure.

[0012] Figure 2B is a diagram illustrating an example of DL channels within a subframe according to various aspects of the present disclosure.

[0013] Figure 2C is a diagram illustrating an example of a second frame according to various aspects of the present disclosure.

[0014] Figure 2D is a diagram illustrating an example of UL channels within a subframe according to various aspects of the present disclosure.

[0015] Figure 3 is a diagram illustrating an example of a base station and a user equipment (UE) in an access network.

[0016] Figure 4A is a diagram illustrating an example of a UE.

[0017] Figure 4B is a diagram illustrating an example of a UE.

[0018] Figure 5 is a diagram illustrating an example of a UE communicating with an artificial intelligence (AI) / machine learning (ML) framework.

[0019] Figure 6 is a diagram illustrating an example of an AI / ML algorithm used in conjunction with wireless communications.

[0020] Figure 7 is a call flow diagram of signaling between UE and base station.

[0021] Figure 8 is a flow chart of a method of wireless communication.

[0022] Fig. 9 is a flow chart of a method of wireless communication.

[0023] Fig.10 are diagrams illustrating examples of hardware implementations for example devices and / or network nodes.

[0024] Fig.11 is a flow chart of a method of wireless communication.

[0025] Fig.12 is a flow chart of a method of wireless communication.

[0026] Fig.13 is a diagram illustrating an example of a hardware implementation for an example network node. DETAILED DESCRIPTION

[0027] In wireless communications, multi-antenna beamforming is typically used in frequency range 2 (FR2) or millimeter wave systems. In super 5G systems, in addition to being used in FR2, multi-antenna beamforming can also be used in frequency range 3 (FR3), frequency range 4 (FR4), or frequency range 5 (FR5). Blocking of directional beams used for wireless communications may reduce / degrade link performance, such as in FR2 wireless communication systems. Blocking of the beam may occur due to user interaction with the UE, such as the user's hands, fingers, head, or other body parts blocking the path of the UE and the network node or other UE. Blocking may also occur due to external objects, such as other people, vehicles, buildings, leaves, terrain, etc. blocking the beam direction between the UE and the network node or other UE. Blocking may be relatively slow or fast at the beginning, for example, the time scale of the change may be on the order of tens of milliseconds to hundreds of milliseconds. Beam blocking may degrade link performance, and the degree of degradation may be affected by the blocking pattern.

[0028] The aspects presented herein provide a configuration for a UE to request a TCI state switch for a blocking condition. The aspects presented herein allow a UE to predict a blocking condition for a beam used for the UE to communicate with a network node, so that the UE can schedule a beam switch at the UE based on the predicted blocking condition.

[0029] The specific embodiments described below in conjunction with the accompanying drawings are descriptions of various configurations and do not represent the only configurations in which the concepts described herein can be practiced. In order to provide a thorough understanding of the various concepts, the specific embodiments include specific details. However, these concepts can be practiced without these specific details. In some cases, well-known structures and components are shown in block diagram form to avoid obscuring such concepts.

[0030] Several aspects of telecommunication systems are presented with reference to various apparatuses and methods. These apparatuses and methods are described in the following detailed description and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively referred to as "elements"). These elements may be implemented using electronic hardware, computer software, or any 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.

[0031] As an example, an element, or any part of an element, or any combination of elements can be implemented as a "processing system", which includes one or more processors. Examples of processors include microprocessors, microcontrollers, graphics processing units (GPUs), central processing units (CPUs), application processors, digital signal processors (DSPs), reduced instruction set computing (RISC) processors, systems on chip (SoCs), baseband processors, field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic components, discrete hardware circuits, and other suitable hardware configured to perform various functionalities described throughout the present disclosure. One or more processors in a processing system can execute software. Whether referred to as software, firmware, middleware, microcode, hardware description language, or other terms, software should be broadly interpreted as meaning instructions, instruction sets, codes, code segments, program codes, programs, subroutines, software components, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, or any combination thereof.

[0032] Thus, in one or more example aspects, specific implementations and / or use cases, the described functionality may be implemented in hardware, software, or any combination thereof. If implemented in software, the functionality may be stored or encoded as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media. Storage media may be any available media that can be accessed by a computer. As an example, such computer-readable media may include random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of these types of computer-readable media, or any other medium that can be used to store computer-executable code in the form of instructions or data structures that can be accessed by a computer.

[0033] Although various aspects, specific implementations and / or use cases are described in this application by the illustration of some examples, additional or different aspects, specific implementations and use cases may be generated in many different arrangements and scenarios. The various aspects, specific implementations and / or use cases described herein can be implemented across many different platform types, devices, systems, shapes, sizes and packaging arrangements. For example, various aspects, specific implementations and / or use cases can be generated via integrated chip specific implementations and other devices based on non-module components (e.g., end-user devices, vehicles, communication equipment, computing equipment, industrial equipment, retail / purchase equipment, medical equipment, devices that enable artificial intelligence (AI), etc.). Although some examples may or may not be specifically for use cases or applications, the described examples may have a wide range of applicability. Various aspects, specific implementations and / or use cases can be in the range from chip-level or modular components to non-modular, non-chip-level specific implementations, and further to the range of aggregated, distributed or original equipment manufacturer (OEM) devices or systems in conjunction with one or more technologies herein. In some actual settings, the equipment combined with the various aspects and features described may also include additional components and features for implementing and practicing the claimed and described aspects. For example, the transmission and reception of wireless signals necessarily include multiple components for analog and digital purposes (e.g., hardware components including antennas, RF chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc.) The techniques described herein can be practiced in a wide variety of devices of various sizes, shapes, and configurations, chip-level components, systems, distributed arrangements, aggregated or disaggregated components, end-user devices, etc.

[0034] The deployment of a communication system (such as a 5G NR system) can be arranged in a variety of ways with various components or constituent parts. In a 5G NR system or network, a network node, a network entity, a mobility element of a network, a radio access network (RAN) node, a core network node, a network element or a network equipment (such as a base station (BS), or one or more units (or one or more components) performing base station functionality can be implemented in an aggregated or decomposed architecture. For example, a BS (such as a Node B (NB), an evolved NB (eNB), an NR BS, a 5G NNB, an access point (AP), a transmit receive point (TRP) or a cell, etc.) can be implemented as an aggregated base station (also referred to as an independent BS or a monolithic BS) or a decomposed base station.

[0035] A converged base station may be configured to utilize a radio protocol stack physically or logically integrated within a single RAN node. A decomposed base station may be configured to utilize a protocol stack physically or logically distributed between two or more units, such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs). In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed in one or more other RAN nodes. A DU may be implemented to communicate with one or more RUs. Each of a CU, a DU, and a RU may be implemented as a virtual unit, i.e., a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0036] Base station operation or network design may take into account the aggregated nature of base station functionality. For example, a disaggregated base station may be utilized in an integrated access backhaul (IAB) network, an open radio access network (O-RAN (network configuration such as that initiated by the O-RAN Alliance)), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN)). Decomposition may include distributing functionality across two or more units at various physical locations, as well as virtually distributing functionality of at least one unit, which may enable flexibility in network design. Individual units of a disaggregated base station or disaggregated RAN architecture may be configured for wired or wireless communication with at least one other unit.

[0037] Figure 1 1 is a diagram 100 illustrating an example of a wireless communication system and an access network. The illustrated wireless communication system includes a disaggregated base station architecture. The disaggregated base station architecture may include one or more CUs 110 that may communicate directly with a core network 120 via a backhaul link, or indirectly with the core network 120 through one or more disaggregated base station units, such as a near real-time (near RT) RAN intelligent controller (RIC) 125 via an E2 link, or a non-real-time (non-RT) RIC 115 associated with a service management and orchestration (SMO) framework 105, or both. The CU 110 may communicate with one or more DUs 130 via corresponding midhaul links, such as an F1 interface. The DU 130 may communicate with one or more RUs 140 via corresponding fronthaul links. The RU 140 may communicate with corresponding UEs 104 via one or more radio frequency (RF) access links. In some implementations, a UE 104 may be served simultaneously by multiple RUs 140.

[0038] Each of the units (i.e., CU 110, DU 130, RU 140, and near-RT RIC 125, non-RT RIC 115, and SMO framework 105) may include or be coupled to one or more interfaces 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 the communication interface of these units may be configured to communicate with one or more of the other units via a transmission medium. For example, these units may include a wired interface that is configured to receive signals or send signals to one or more of the other units via a wired transmission medium. Additionally, these units may include a wireless interface that may include a receiver, transmitter, or transceiver (such as an RF transceiver) configured to receive and / or send signals to one or more of the other units via a wireless transmission medium.

[0039] In some aspects, CU 110 may host one or more higher layer control functions. Such control functions may include radio resource control (RRC), packet data convergence protocol (PDCP), service data adaptation protocol (SDAP), etc. Each control function may be implemented using an interface that is configured to communicate signals with other control functions hosted by CU 110. CU 110 may be configured to handle user plane functionality (i.e., central unit-user plane (CU-UP)), control plane functionality (i.e., central unit-control plane (CU-CP)), or a combination thereof. In some specific implementations, CU 110 may be logically split 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 110 may be implemented to communicate with DU 130 for network control and signaling.

[0040] DU 130 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RUs 140. In some aspects, DU 130 may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more high physical (PHY) layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation and demodulation, etc.) at least in part according to a functional split such as those defined by 3GPP. In some aspects, DU 130 may also host one or more low PHY layers. Each layer (or module) may be implemented using an interface that is configured to communicate signals with other layers (and modules) hosted by DU 130 or with control functions hosted by CU 110.

[0041] The lower layer functionality may be implemented by one or more RUs 140. In some deployments, the RU 140 controlled by the DU 130 may correspond to a logical node that hosts RF processing functions or low PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, etc.), or both, based at least in part on functional splitting (such as lower layer functional splitting). In such an architecture, the RU 140 may be implemented to handle over-the-air (OTA) communications with one or more UEs 104. In some implementations, real-time and non-real-time aspects of control plane and user plane communications with the RU 140 may be controlled by the corresponding DU 130. In some scenarios, this configuration may enable the DU 130 and CU 110 to be implemented in a cloud-based RAN architecture (such as a vRAN architecture).

[0042] The SMO framework 105 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 105 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 105 may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud) 190) 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 110, DU 130, RU 140, and near-RT RIC 125. In some specific implementations, the SMO framework 105 may communicate with hardware aspects of the 4G RAN (such as an open eNB (O-eNB) 111) via the O1 interface. Additionally, in some specific implementations, the SMO framework 105 may communicate directly with one or more RUs 140 via the O1 interface. The SMO framework 105 may also include a non-RT RIC 115 configured to support the functionality of the SMO framework 105 .

[0043] The non-RT RIC 115 may be configured to include logic functions that enable non-real-time control and optimization of RAN elements and resources, artificial intelligence (AI) / machine learning (ML) (AI / ML) workflows including model training and updating, or policy-based guidance of applications / features in the near-RT RIC 125. The non-RT RIC 115 may be coupled to or communicate with the near-RT RIC 125 (such as via an A1 interface). The near-RT RIC 125 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 110, one or more DUs 130, or both, and the O-eNB with the near-RT RIC 125.

[0044] In some implementations, in order to generate an AI / ML model to be deployed in the near-RT RIC 125, the non-RT RIC 115 may receive parameters or external enrichment information from an external server. Such information may be utilized by the near-RT RIC 125 and may be received from a non-network data source or from a network function at the SMO framework 105 or the non-RT RIC 115. In some examples, the non-RT RIC 115 or the near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the non-RT RIC 115 may monitor long-term trends and patterns of performance and employ AI / ML models to perform corrective actions through the SMO framework 105 (such as via reconfiguration of O1) or via the creation of RAN management policies (such as A1 policies).

[0045] At least one of the CU 110, the DU 130, and the RU 140 may be referred to as a base station 102. Therefore, the base station 102 may include one or more of the CU 110, the DU 130, and the RU 140 (each component is indicated by a dotted line to indicate that each component may be included in the base station 102 or may not be included in the base station). The base station 102 provides an access point to the core network 120 for the UE 104. The base station 102 may include a macro cell (a high-power cellular base station) and / or a small cell (a low-power cellular base station). Small cells include femto cells, pico cells, and micro cells. A network including both small cells and macro cells may be referred to as a heterogeneous network. A heterogeneous network may also include a home evolved Node B (eNB) (HeNB), which may provide services to a restricted group referred to as a closed subscriber group (CSG). The communication link between RU 140 and UE 104 may include uplink (UL) (also known as reverse link) transmission from UE 104 to RU 140 and / or downlink (DL) (also known as forward link) transmission from RU 140 to UE 104. The communication link may use multiple-input multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming and / or transmit diversity. The communication link may be through one or more carriers. For each carrier allocated in a carrier aggregation of up to Yx MHz (x component carriers) for transmission in each direction, the base station 102 / UE 104 may use a spectrum of up to Y MHz (e.g., 5MHz, 10MHz, 15MHz, 20MHz, 100MHz, 600MHz, etc.) bandwidth. These carriers may or may not be adjacent to each other. The allocation of carriers may be equivalent to DL and UL asymmetric (e.g., more or fewer carriers may be allocated to DL than to UL). Component carriers may include a primary component carrier and one or more secondary component carriers. The primary component carrier may be referred to as a primary cell (PCell) and the secondary component carrier may be referred to as a secondary cell (SCell).

[0046] Some UEs 104 may communicate with each other using a device-to-device (D2D) communication link 158. The D2D communication link 158 may use DL / UL wireless wide area network (WWAN) spectrum. The D2D communication link 158 may use one or more sidelink channels, such as a physical sidelink broadcast channel (PSBCH), a physical sidelink discovery channel (PSDCH), a physical sidelink shared channel (PSSCH), and a physical sidelink control channel (PSCCH). The D2D communication may be through a variety of wireless D2D communication systems, such as, for example, Bluetooth, Wi-Fi based on the Institute of Electrical and Electronics Engineers (IEEE) 902.11 standard, LTE, or NR.

[0047] The wireless communication system may also include a Wi-Fi AP 150 that communicates with a UE 104 (also referred to as a Wi-Fi station (STA)) via a communication link 154, for example, in a 5 GHz unlicensed spectrum, etc. When communicating in an unlicensed spectrum, the UE 104 / AP 150 may perform a clear channel assessment (CCA) to determine whether a channel is available prior to communication.

[0048] The electromagnetic spectrum is typically subdivided into various categories, bands, channels, etc. based on frequency / wavelength. In 5G NR, two initial operating bands have been identified as frequency range designations FR1 (610 MHz-7.125 GHz) and FR2 (24.25 GHz-52.6 GHz). Although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as the "sub-6 GHz" band in various documents and articles. A similar naming issue 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).

[0049] 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, so 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 FR2-2 (52.6GHz-71GHz), FR4 (71GHz-114.25GHz) and FR5 (114.25GHz-300GHz). Each of these higher frequency bands falls within the EHF band.

[0050] In view of the above, unless otherwise specified, if the term "6 GHz or less" is used herein, it may broadly refer to frequencies that may be less than 6 GHz, may be within FR1, or may include mid-band frequencies. In addition, unless otherwise specified, if the term "millimeter wave" is used herein, it may broadly refer to frequencies that may include mid-band frequencies, may be within FR2, FR4, FR2-2, and / or FR5, or may be within the EHF band.

[0051] The base station 102 and the UE 104 may each include multiple antennas (such as antenna elements, antenna panels, and / or antenna arrays) to facilitate beamforming. The base station 102 may send a beamformed signal 182 to the UE 104 in one or more transmit directions. The UE 104 may receive the beamformed signal from the base station 102 in one or more receive directions. The UE 104 may also send a beamformed signal 184 to the base station 102 in one or more transmit directions. The base station 102 may receive the beamformed signal from the UE 104 in one or more receive directions. The base station 102 / UE 104 may perform beam training to determine the optimal receive direction and transmit direction for each of the base station 102 / UE 104. The transmit direction and receive direction of the base station 102 may be the same or different. The transmit direction and receive direction of the UE 104 may be the same or different.

[0052] The base station 102 may include and / or be referred to as a gNB, a Node B, an eNB, an access point, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a transmit receive point (TRP), a network node, a network entity, a network equipment, or some other suitable term. The base station 102 may be implemented as an integrated access and backhaul (IAB) node, a relay node, a sidelink node, an aggregated (monolithic) base station with a baseband unit (BBU) (including a CU and a DU) and a RU, or as a decomposed base station including one or more of a CU, a DU, and / or a RU. A set of base stations that may include decomposed base stations and / or aggregated base stations may be referred to as a next generation (NG) RAN (NG-RAN).

[0053] The core network 120 may include an access and mobility management function (AMF) 161, a session management function (SMF) 162, a user plane function (UPF) 163, a unified data management (UDM) 164, one or more location servers 168, and other functional entities. AMF 161 is a control node that handles signaling between UE 104 and core network 120. AMF 161 supports registration management, connection management, mobility management, and other functions. SMF 162 supports session management and other functions. UPF 163 supports packet routing, packet forwarding, and other functions. UDM 164 supports the generation of authentication and key agreement (AKA) credentials, user identity handling, access authorization, and subscription management. One or more location servers 168 are illustrated as including a gateway mobile location center (GMLC) 165 and a location management function (LMF) 166. However, in general, the one or more location servers 168 may include one or more location / positioning servers, which may include one or more of the GMLC 165, LMF 166, position determination entity (PDE), serving mobile location center (SMLC), mobile positioning center (MPC), etc. GMLC 165 and LMF 166 support UE location services. GMLC 165 provides an interface for clients / applications (e.g., emergency services) to access UE positioning information. LMF 166 receives measurement and assistance information from NG-RAN and UE 104 via AMF 161 to calculate the location of UE 104. NG-RAN may determine the location of UE 104 using one or more positioning methods. Positioning UE 104 may involve signal measurements, position estimation, and optional speed calculation based on these measurements. Signal measurements may be performed by UE 104 and / or serving base station 102. The measured signals may be based on a satellite positioning system (SPS) 170 (e.g., one or more of a global navigation satellite system (GNSS), a global positioning system (GPS), a non-terrestrial network (NTN), or other satellite positioning / positioning systems), LTE signals, wireless local area network (WLAN) signals, Bluetooth signals, a terrestrial beacon system (TBS), sensor-based information (e.g., an atmospheric pressure sensor, a motion sensor), an NR enhanced cell ID (NR E-CID) method, NR signals (e.g., multi-round trip time (multi-RTT), DL angle of departure (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL angle of arrival (UL-AoA) positioning), and / or one or more of other systems / signals / sensors.

[0054] Examples of UE 104 include cellular phones, smart phones, session initiation protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, tablet computers, smart devices, wearable devices, vehicles, electric meters, gas pumps, large or small kitchen appliances, healthcare equipment, implants, sensors / actuators, displays, or any other similarly functional devices. Some of the UEs 104 may be referred to as IoT devices (e.g., parking meters, gas pumps, toasters, vehicles, heart monitors, etc.). UE 104 may also be referred to as stations, mobile stations, subscriber stations, mobile units, subscriber units, wireless units, remote units, mobile devices, wireless devices, wireless communication devices, remote devices, mobile subscriber stations, access terminals, mobile terminals, wireless terminals, remote terminals, mobile phones, user agents, mobile clients, clients, or some other suitable terminology. In some scenarios, the term UE may also be applied to one or more supporting devices, such as in a device constellation arrangement. One or more of these devices may access the network collectively and / or individually.

[0055] Reference again Figure 1 In certain aspects, the UE 104 may include a switching component 198 configured to: predict a blocking condition for a first beam communicating with a network node; and send a beam switching indication to the network node indicating a scheduled change in TCI state mapping from the first beam to the second beam in response to the predicted blocking condition.

[0056] Reference again Figure 1 In certain aspects, the base station 102 may include a switching component 199 configured to: communicate with the UE using a first beam; and obtain a beam switching indication comprising a scheduled change of a TCI state mapped from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam.

[0057] Although the following description may focus on 5G NR, the concepts described herein may be applicable to other similar areas such as LTE, LTE-A, CDMA, GSM, and other wireless technologies.

[0058] Figure 2A FIG200 is a diagram illustrating an example of a first subframe within a 5G NR frame structure. Figure 2B FIG230 is a diagram illustrating an example of DL channels within a 5G NR subframe. Figure 2C FIG250 is a diagram illustrating an example of a second subframe within a 5G NR frame structure. Figure 2DFIG280 is a diagram illustrating an example of UL channels within a 5G NR subframe. The 5G NR frame structure may be frequency division duplex (FDD), where for a particular set of subcarriers (carrier system bandwidth), subframes within that subcarrier set are dedicated to either DL or UL, or may be time division duplex (TDD), where for a particular set of subcarriers (carrier system bandwidth), subframes within that subcarrier set are dedicated to both DL and UL. Figure 2A , Figure 2C In the example provided, the 5G NR frame structure is assumed to be TDD, where subframe 4 is configured with slot format 28 (most of which are DL), where D is DL, U is UL, and F is flexible between DL / UL, and subframe 3 is configured with slot format 1 (all of which are UL). Although subframes 3 and 4 are shown as having slot formats 1 and 28, respectively, any particular subframe may be configured with any of the various available slot formats 0 to 61. Slot formats 0 and 1 are all DL and all UL, respectively. Other slot formats 2 to 61 include a mix of DL, UL and flexible symbols. The UE is configured with the slot format through the received slot format indicator (SFI) (dynamically configured through DL control information (DCI) or semi-statically / statically configured through radio resource control (RRC) signaling). Note that the following description also applies to the 5G NR frame structure as TDD.

[0059] FIG. 2A to FIG. 2D The frame structure is illustrated, and various aspects of the present disclosure may be applicable to other wireless communication technologies that may have different frame structures and / or different channels. A frame (10ms) may be divided into 10 subframes of equal size (1ms). Each subframe may include one or more time slots. A subframe may also include a microslot, which may include 7, 4 or 2 symbols. Each time slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For a normal CP, each time slot may include 14 symbols, and for an extended CP, each time slot may include 12 symbols. The symbol on the DL may be a CP orthogonal frequency division multiplexing (OFDM) (CP-OFDM) symbol. The symbol on the UL may be a CP-OFDM symbol (for high throughput scenarios) or a discrete Fourier transform (DFT) extended OFDM (DFT-s-OFDM) symbol (also known as a single carrier frequency division multiple access (SC-FDMA) symbol) (for power-limited scenarios; limited to single-stream transmission). The number of slots within a subframe is based on the CP and the parameter set. The parameter set defines the subcarrier spacing (SCS) and effectively defines the symbol length / duration, which is equal to 1 / SCS.

[0060]

[0061] For normal CP (14 symbols / slot), different parameter sets μ0 to 4 allow 1, 2, 4, 8, and 16 slots per subframe, respectively. For extended CP, parameter set 2 allows 4 slots per subframe. Thus, for normal CP and parameter set μ, there are 14 symbols / slot and 2 μ timeslots / subframe. The subcarrier spacing can be equal to 2 μ *15kHz, where μ is parameter set 0 to 4. Therefore, the subcarrier spacing for parameter set μ=0 is 15kHz, and the subcarrier spacing for parameter set μ=4 is 240kHz. The symbol length / duration is inversely related to the subcarrier spacing. FIG. 2A to FIG. 2D An example is provided for a normal CP with 14 symbols per slot and a parameter set μ=2 with 4 slots per subframe. The slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is about 16.67 μs. Within a frame set, there may be one or more different bandwidth parts (BWPs) that are frequency-division multiplexed (see Figure 2B ). Each BWP may have a specific parameter set and CP (normal or extended).

[0062] A resource grid may be used to represent the frame structure. Each slot includes a resource block (RB) (also referred to as a physical RB (PRB)) extending over 12 consecutive subcarriers. The resource grid is divided into a plurality of resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

[0063] like Figure 2A As illustrated, some of the REs carry reference (pilot) signals (RS) for the UE. The RS may include a demodulation RS (DM-RS) (indicated as R for one particular configuration, but other DM-RS configurations are possible) and a channel state information reference signal (CSI-RS) for channel estimation at the UE. The RS may also include a beam measurement RS (BRS), a beam refinement RS (BRRS), and a phase tracking RS (PT-RS).

[0064] Figure 2BExamples of various DL channels within a subframe of a frame are illustrated. A physical downlink control channel (PDCCH) carries DCI within one or more control channel elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), each CCE including six RE groups (REGs), each REG including 12 consecutive REs in an OFDM symbol of an RB. A PDCCH within a BWP may be referred to as a control resource set (CORESET). The UE is configured to monitor PDCCH candidates in a PDCCH search space (e.g., a common search space, a UE-specific search space) during a PDCCH monitoring opportunity on a CORESET, wherein the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs may be located at higher and / or lower frequencies on the channel bandwidth. A primary synchronization signal (PSS) may be within symbol 2 of a particular subframe of a frame. The PSS is used by UE 104 to determine subframe / symbol timing and physical layer identification. A secondary synchronization signal (SSS) may be within symbol 4 of a particular subframe of a frame. The SSS is used by the UE to determine the physical layer cell identity group number and the radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine the physical cell identifier (PCI). Based on the PCI, the UE can determine the location of the DM-RS. The physical broadcast channel (PBCH) carrying the master information block (MIB) can be logically grouped with the PSS and SSS to form a synchronization signal (SS) / PBCH block (also referred to as an SS block (SSB)). The MIB provides the number of RBs in the system bandwidth and the system frame number (SFN). The physical downlink shared channel (PDSCH) carries user data, broadcast system information not sent via the PBCH (such as a system information block (SIB)), and paging messages.

[0065] like Figure 2C As illustrated, some of the REs carry DM-RS (indicated as R for a particular configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE may send a DM-RS for a physical uplink control channel (PUCCH) and a DM-RS for a physical uplink shared channel (PUSCH). The PUSCH DM-RS may be sent in the first or first two symbols of the PUSCH. Depending on whether a short PUCCH or a long PUCCH is sent and depending on the specific PUCCH format used, the PUCCH DM-RS may be sent in different configurations. The UE may send a sounding reference signal (SRS). The SRS may be sent in the last symbol of a subframe. The SRS may have a comb structure, and the UE may send the SRS on one of the teeth of the comb. The SRS may be used by the base station for channel quality estimation to achieve frequency-dependent scheduling of the UL.

[0066] Figure 2DExamples of various UL channels within a subframe of a frame are illustrated. The PUCCH may be located at a position as indicated in one configuration. The PUCCH carries uplink control information (UCI), such as scheduling requests, channel quality indicators (CQI), precoding matrix indicators (PMI), rank indicators (RI), and hybrid automatic repeat request (HARQ) acknowledgement (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACKs and / or negative ACKs (NACKs)). The PUSCH carries data and may be used to carry, among other things, a buffer status report (BSR), a power headroom report (PHR), and / or UCI.

[0067] Figure 3 375. The Controller / Processor 375 is a block diagram of a base station 310 in an access network communicating with a UE 350. In the DL, Internet Protocol (IP) packets may be provided to a controller / processor 375. The controller / processor 375 implements layer 3 and layer 2 functionality. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The controller / processor 375 provides RRC layer functionality associated with broadcasting of system information (e.g., MIB, SIB), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (encryption, decryption, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with delivery of upper layer packet data units (PDUs), error correction through ARQ, concatenation, segmentation and reassembly of RLC service data units (SDUs), re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0068] The transmit (TX) processor 316 and receive (RX) processor 370 implement layer 1 functionality associated with various signal processing functions. Layer 1 (which includes the physical (PHY) layer) may include error detection on the transport channel, forward error correction (FEC) coding / decoding of the transport channel, interleaving, rate matching, mapping onto the physical channel, modulation / demodulation of the physical channel, and MIMO antenna processing. The TX processor 316 handles the mapping to the signal constellation based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-order phase shift keying (M-PSK), M-order quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be separated into parallel streams. Each stream may then be mapped to an OFDM subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined together using an inverse fast Fourier transform (IFFT) to produce a physical channel carrying a time domain OFDM symbol stream. The OFDM stream is spatially pre-coded to generate multiple spatial streams. Channel estimates from a channel estimator 374 may be used to determine coding and modulation schemes, as well as for spatial processing. Channel estimates may be derived based on reference signals and / or channel condition feedback sent by the UE 350. Each spatial stream may then be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier with a corresponding spatial stream for transmission.

[0069] At the UE 350, each receiver 354Rx receives a signal through its corresponding antenna 352. Each receiver 354Rx recovers the information modulated onto the RF carrier and provides the information to a receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement layer 1 functionality associated with various signal processing functions. The RX processor 356 can perform spatial processing on the information to recover any spatial stream destined for the UE 350. If multiple spatial streams are destined for the UE 350, they can be combined into a single OFDM symbol stream by the RX processor 356. The RX processor 356 then uses a fast Fourier transform (FFT) to convert the OFDM symbol stream from the time domain to the frequency domain. The frequency domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbol on each subcarrier and the reference signal are recovered and demodulated by determining the signal constellation point most likely to be sent by the base station 310. These soft decisions can be based on the channel estimate calculated by the channel estimator 358. The soft decisions are then decoded and deinterleaved to recover the data and control signals originally sent on the physical channel by the base station 310. The data and control signals are then provided to a controller / processor 359, which implements layer 3 and layer 2 functionality.

[0070] The controller / processor 359 may be associated with a memory 360 that stores program codes and data. The memory 360 may be referred to as a computer readable medium. In the UL, the controller / processor 359 provides demultiplexing between transport channels and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets. The controller / processor 359 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operations.

[0071] Similar to the functionality described in conjunction with DL transmissions performed by the base station 310, the controller / processor 359 provides RRC layer functionality associated with system information (e.g., MIB, SIB) acquisition, RRC connection, and measurement reporting; PDCP layer functionality associated with header compression / decompression and security (encryption, decryption, integrity protection, integrity verification); RLC layer functionality associated with delivery of upper layer PDUs, error correction through ARQ, concatenation, segmentation and reassembly of RLC SDUs, resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0072] Channel estimates derived by the channel estimator 358 based on a reference signal or feedback sent by the base station 310 may be used by the TX processor 368 to select appropriate coding and modulation schemes and to facilitate spatial processing. The spatial streams generated by the TX processor 368 may be provided to different antennas 352 via separate transmitters 354Tx. Each transmitter 354Tx may modulate an RF carrier with a corresponding spatial stream for transmission.

[0073] UL transmissions are processed at the base station 310 in a manner similar to that described in conjunction with the receiver functionality at the UE 350. Each receiver 318Rx receives a signal through its respective antenna 320. Each receiver 318Rx recovers information modulated onto an RF carrier and provides the information to the RX processor 370.

[0074] The controller / processor 375 may be associated with a memory 376 that stores program codes and data. The memory 376 may be referred to as a computer readable medium. In the UL, the controller / processor 375 provides demultiplexing between transport channels and logical channels, packet reassembly, decryption, header decompression, control signal processing to recover IP packets. The controller / processor 375 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operations.

[0075] At least one of the TX processor 368, the RX processor 356, and the controller / processor 359 may be configured to combine Figure 1 The switching component 198 performs various aspects.

[0076] At least one of the TX processor 316, the RX processor 370, and the controller / processor 375 may be configured to combine Figure 1 The switching component 199 performs various aspects.

[0077] In wireless communications, multi-antenna beamforming is commonly used in frequency range 2 (FR2) or millimeter wave systems. Blockages may severely impair link performance in FR2 systems. Blockages may also have a serious impact in systems exceeding FR2 (e.g., FR4 / 5). Blockages may occur due to users using the UE (such as hands, fingers, heads, or other body parts), who may cause blockages when the UE is being used. Blockages may also occur due to external objects (such as other people, vehicles, buildings, leaves, terrain, etc.). Blockages may be relatively slow or fast at the beginning, with the time scale of the change being on the order of tens of milliseconds to hundreds of milliseconds. Blockages may degrade link performance (e.g., by 2dB to 40dB) based on the blocking pattern, with some models assuming a flat 30dB loss over the blocked coverage area.

[0078] The link degradation time may be defined as the time it takes for the RSSI or RSRP to drop from its steady state value to its minimum value or link loss, whichever occurs first. In some examples, the behavior of RSSI / RSRP degradation in the event of an obstruction may include a time scale of change that may be slow (e.g., RSSI takes hundreds of milliseconds to drop significantly).

[0079] Adaptive / dynamic beam weights may be considered to combat blocking. For adaptive beam weights, consideration of the performance of beam refinement only at the receiver node may be compared to beam refinement at both the transmitter and receiver nodes. Refinement at the transmitter may be based on the addition of two best narrow beams from a codebook of size 32 for an 8×4 array, while refinement at the receiver may be based on a 4×1 array of per-antenna co-phasing to generate a good beamforming structure.

[0080] Aspects presented herein provide a configuration for a UE to request a TCI state switch for a blocking condition. Aspects presented herein allow a UE to predict a blocking condition for a beam used to communicate with a network node, so that the UE can schedule beam switching at the UE based on the predicted blocking condition. At least one advantage of the present disclosure is that, since the hand movements of a user using a UE may be predicted in advance (e.g., in a gaming mode or in a voice call) in part due to the use of the UE, the UE can utilize different UE-side beam weights based on predicted hand movements in order to optimize performance. Associated with any beam change on the UE side is a corresponding beam change at the network node. The UE can determine such a UE-side beam change associated with a TCI state change and signal such a change to the network node.

[0081] Hand or body movement is a physical movement where the time scale of the change can be tens of milliseconds to hundreds of milliseconds. In some aspects, the finger, hand or body movement of a user using a UE can be predicted in advance (e.g., gaming scenarios, voice calls, etc.). For example, Figure 4A As shown in diagram 400 of FIG. 4 , UE 402 may be held in a user's hand and supported by finger 404, wherein beam 406 may communicate with a network node. The user may initiate an application on the UE, causing the orientation of the UE to change. Figure 4B 420, a user may rotate UE 402 and hold the UE using both hands and fingers 404 in response to launching an application on the UE. In such an example, a second beam 408 of the UE may be used to communicate with the network node. As UE 402 repositions in response to launching the application, beam 406 of UE 402 may be blocked by the user's hand or finger 404. The approach for predicting hand movement may be based on ML / AI that correlates past observations with future predictions.

[0082] For optimal performance, different hand movements may be associated with different UE-side beam weights. For a part of the user's body that is affecting the beam direction, the optimal beam weight may depend on the user's hand grip, the air gap between the user's fingers, skin properties, skin / body fat / water content, etc. The optimal beam weight may be a hyper-static codebook solution that explores the space of all possible phase shifters and amplitude control possibilities. Note that due to radio frequency integrated circuit (RFIC) memory constraints, the hybrid / analog beamforming codebook used at the UE is typically derived from a fixed / static codebook of beam weights. The optimal beam weight is not constrained by RFIC memory requirements and can be a general phase shifter and / or amplitude control combination. For better performance, the UE may choose to change the beam based on changes in blocking conditions. Since the UE can predict the blocking condition with a threshold level of accuracy, the UE can schedule beam changes based on such predictions.

[0083] In some aspects, the prediction of a blocking condition may be based on ML or AI. Figure 5 An example of a diagram 500 of a UE 502 communicating with an AI / ML framework 504 is provided. Given a channel matrix H between a base station 506 and the UE 502, if f is the selected beam at the base station, then the optimal beam for maximizing the SNR on the downlink is Hf at the UE, which can be referred to as a matched filter structure. Extending this logic to uplink transmissions, if the UE changes the beam from g1 to g2, then the optimal beam at the base station changes from H T g1 changes to H T g2. When the UE changes its beam in response to a predicted blocking condition, it would be advantageous if the base station also switches its beam according to the beam switching at the UE to obtain optimal performance. The ML / AI framework 504 may learn / track the channel matrix between the base station and the UE over time and may be based on explicit or implicit learning of H, knowledge of UE beam changes, and mapping both to corresponding TCI state changes. In some aspects, the UE may be configured to request from the base station a TCI state change associated with a predicted time scale at which such a TCI state change may occur.

[0084] Figure 6 is an example of an AI / ML algorithm 600 that can be used in conjunction with wireless communication. The AI / ML algorithm 600 can include various functions, including data collection 602, model training function 604, model inference function 606, and participants 608.

[0085] Data collection 602 may be a function that provides input data to the model training function 604 and the model inference function 606. The data collection 602 function may include any form of data preparation, and it may not be specific to the specific implementation of the AI / ML algorithm (e.g., data preprocessing and cleaning, formatting, and transformation). Examples of input data may include, but are not limited to, channel matrix measurements from a UE or network node, feedback from a participant 608, and output from another AI / ML model. Data collection 602 may include training data and inference data, where the training data refers to data to be transmitted as input to the AI / ML model training function 604, and the inference data refers to data transmitted as input to the AI / ML model inference function 606.

[0086] The model training function 604 may be a function that performs ML model training, validation, and testing, which may generate model performance metrics as part of the model testing procedure. The model training function 604 may also be responsible for data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the training data delivered or received from the data collection 602 function. The model training function 604 may deploy or update the trained, validated, and tested AI / ML models to the model inference function 606, and receive model performance feedback from the model inference function 606.

[0087] The model inference function 606 may be a function that provides an AI / ML model inference output (e.g., a prediction or decision). The model inference function 606 may also perform data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the inference data delivered from the data collection 602 function. The output of the model inference function 606 may include the inference output of the AI / ML model produced by the model inference function 606. The details of the inference output may be use case specific. As an example, the output may include an estimated channel matrix over time.

[0088] Model performance feedback may refer to information derived from the model inference function 606 that may be suitable for improving the AI / ML model trained in the model training function 604. Feedback from participants 608 or other network entities (via the data collection 602 function) may be implemented for the model inference function 606 to create model performance feedback.

[0089] Participants 608 may be functions that receive output from model inference function 606 and trigger or perform corresponding actions. Participants may trigger actions for network entities including other network entities or themselves. Participants 608 may also provide feedback information for model training function 604 or model inference function 606 to export training or inference data or performance feedback. Feedback may be sent back to data collection 602.

[0090] The network may use machine learning algorithms, deep learning algorithms, neural networks, reinforcement learning, regression, boosting, or advanced signal processing methods for various aspects of wireless communications, including TCI state-based DCI selection to identify neighbor TCI candidates for autonomous TCI candidate set updates.

[0091] In some aspects described herein, the network may train one or more neural networks to learn the dependence of the quality of the measurement on various parameters. In addition, examples of machine learning models or neural networks that may be included in the network entity include artificial neural networks (ANNs); decision tree learning; convolutional neural networks (CNNs); deep learning architectures, in which the output of a first layer of neurons becomes the input of a second layer of neurons, etc.; support vector machines (SVMs), for example, which include a separating hyperplane (e.g., a decision boundary) for classifying data; regression analysis; Bayesian networks; genetic algorithms; deep convolutional networks (DCNs), which are configured with additional pooling and normalization layers; and deep belief networks (DBNs).

[0092] A machine learning model, such as an artificial neural network (ANN), may include a set of interconnected artificial neurons (e.g., a neuron model) and may be a computing device or may represent a method to be performed by a computing device. The connections of the neuron model may be modeled as weights. The machine learning model may provide predictive models, adaptive control, and other applications by training via a data set. The model may be adaptive based on external or internal information processed by the machine learning model. Machine learning may provide nonlinear statistical data models or decision making, and may model complex relationships between input data and output information.

[0093] The machine learning model may include multiple layers and / or operations, which may be formed by cascading one or more of the cited operations. Examples of operations that may be involved include: extraction of various features of data, convolution operations, fully connected operations that may be activated or deactivated, compression, decompression, quantization, flattening, etc. As used herein, the "layer" of the machine learning model may be used to represent operations on input data. For example, convolution layers, fully connected layers, etc. may be used to refer to associated operations on data input to the layer. Convolution AxB operations refer to operations that convert multiple input features A into multiple output features B. "Kernel size" may refer to the number of neighboring coefficients combined in a dimension. As used herein, "weights" may be used to represent one or more coefficients used in operations for combining individual rows and / or columns of input data in each layer. For example, a fully connected layer operation may have an output y, which is determined at least in part based on the product of the input matrix x and the weight A (which may be a matrix) and the sum of the bias value B (which may be a matrix). The term "weight" may be generally used herein to refer to both weights and bias values. Weights and biases are examples of parameters of a trained machine learning model. Different layers of a machine learning model can be trained independently.

[0094] Machine learning models may include various connectivity patterns, for example, including any of feedforward networks, hierarchies, recursive architectures, feedback connections, etc. The connections between layers of a neural network may be fully connected or locally connected. In a fully connected neural network, a neuron in a first layer may communicate its output to each neuron in a second layer, and each neuron in a second layer may receive input from each neuron in the first layer. In a locally connected network, a neuron in a first layer may be connected to a limited number of neurons in a second layer. In some aspects, a convolutional network may be locally connected and configured with a shared connection strength associated with the input of each neuron in the second layer. A locally connected layer of a network may be configured so that each neuron in the layer has the same or similar connectivity pattern, but with different connection strengths.

[0095] A machine learning model or neural network may be trained. For example, a machine learning model may be trained based on supervised learning. During training, the machine learning model may be presented with inputs that the model uses to calculate to produce an output. The actual output may be compared to the target output, and the difference may be used to adjust the parameters of the machine learning model (such as weights and biases) to provide an output closer to the target output. Before training, the output may be incorrect or less accurate, and the error or difference between the actual output and the target output may be calculated. The weights of the machine learning model may then be adjusted so that the output is more closely aligned with the target. In order to adjust the weights, the learning algorithm may calculate a gradient vector for the weights. The gradient may indicate the amount by which the error will increase or decrease if the weights are slightly adjusted. At the top layer, the gradient may directly correspond to the value of the weights connecting the activated neurons in the penultimate layer and the neurons in the output layer. In the lower layers, the gradient may depend on the value of the weights and the calculated error gradients of the higher layers. The weights may then be adjusted to reduce the error or move the output closer to the target. This way of adjusting the weights may be referred to as back propagation through a neural network. The process may continue until the achievable error rate stops decreasing, or until the error rate has reached a target level.

[0096] These machine learning models may include computational complexity and a large number of processors for training machine learning models. The output of one node is connected as an input to another node. The connection between nodes may be referred to as an edge, and weights may be applied to the connection / edge to adjust the output from one node, which is used as an input to another node. Nodes may apply thresholds to determine whether or when to provide output to a connected node. The output of each node may be calculated as a nonlinear function of the sum of the inputs to the node. A neural network may include any number of nodes and any type of connection between the nodes. A neural network may include one or more hidden nodes. Nodes may be aggregated into layers, and different layers of a neural network may perform different kinds of transformations on the input. A signal may travel from an input at the first layer through multiple layers of a neural network to an output at the last layer of the neural network, and may traverse these layers multiple times.

[0097] Figure 7 700 is a call flow diagram of signaling between UE 702 and base station 704. Although example aspects are described with respect to base station 704, one or more of these aspects may be performed by a base station in a converged form or by a component of a decomposed base station, such as a CU, DU, or RU. Base station 704 may be configured to provide at least one cell. UE 702 may be configured to communicate with base station 704. For example, in Figure 1 In the context of , base station 704 may correspond to base stations 102, 310, and / or 506. Additionally, UE 702 may correspond to at least UE 104, 350, 402, and / or UE 502.

[0098] At 706, the base station 704 and the UE 702 may communicate with each other. The base station 704 may communicate with the UE 702 using the first beam. The UE 702 may communicate with the UE 704 using the first beam.

[0099] At 708, the UE may predict a blocking condition for the first beam communicating with the base station 704, and the UE may indicate the blocking condition to the network. The prediction may be based on a combination of FIG. 4A to FIG. 6 Any of the aspects described. In some aspects, the beam switching indication may indicate a corresponding beam at the base station 704 corresponding to the second beam of the UE 702. The corresponding beam at the base station may be determined based on a correlation between the beam change at the UE and the corresponding beam at the base station. In some aspects, the blocking condition may be based at least on physical movement of a user using the UE or physical movement of the UE. For example, a finger, hand, or body part of a user may change position during the process of using the UE, so that the repositioning of the finger, hand, or body part of the user may cause a blocking condition, for example, as combined with Figure 4A and Figure 4B Descriptive.

[0100] At 710, UE 702 may schedule a beam change to a second beam based on the predicted blocking condition. The UE may select the second beam from a set of beams based on the predicted blocking condition. For example, some beams may perform differently under different blocking conditions, such that the UE selects a beam that performs best under the predicted blocking condition.

[0101] At 712, the UE 702 may correlate the beam change at the UE to the second beam with the corresponding beam change at the base station 704. The correlation between the second beam at the UE and the corresponding beam change at the base station may be based on observing communications between the UE and the base station to estimate a channel matrix between the UE and the network node. In some aspects, the correlation between the second beam at the UE and the corresponding beam change at the base station may be based on a machine learning (ML) or artificial intelligence (AI) framework, for example, the machine learning (ML) or artificial intelligence (AI) framework may include combining Figure 5 and / or Figure 6 Any of the aspects described. The ML or AI framework may utilize prior observations of communications between the UE and the base station to predict a blocking condition. In some aspects, the ML or AI framework and associated optimizations are performed at the UE. In some aspects, the ML or AI framework and associated optimizations are performed within a second network node in communication with the UE.

[0102] At 714, the UE 702 may send a beam switching indication. The UE may send the beam switching indication to the base station 704. The base station 704 may receive the beam switching indication from the UE 702. The beam switching indication may indicate a scheduled change of the TCI state from a first beam mapping to a second beam in response to the predicted blocking condition. In some aspects, the beam switching indication may include a request to switch the beam to a corresponding beam at the base station in association with a predicted time scale. The predicted time scale may correspond to a predicted start time of the blocking condition. The predicted time scale may take into account a switching time to switch the beam at the base station in order to correspond to the beam switch at the UE.

[0103] At 716, UE 702 may switch to the second beam. The UE may switch to the second beam in response to transmitting the beam switch indication.

[0104] At 718, the base station 704 may output an ACK. The base station 704 may output the ACK to the UE 702. The UE 702 may receive the ACK from the base station 704. The base station may output an ACK confirming the switch to the corresponding beam corresponding to the second beam at the UE.

[0105] At 720, UE 702 may monitor for an ACK from base station 704. The UE may monitor for an ACK from the base station to confirm switching to the corresponding beam at the network node. Then, at 722, the UE and / or the base station may send and / or receive communications based on the second beam. In some aspects, the UE may continue to communicate with the network node using the second beam regardless of whether the UE receives an ACK from the network node.

[0106] Figure 8 800 is a flow chart of a method of wireless communication. The method may be performed by a UE (e.g., UE 104; device 1004). One or more of the illustrated operations may be omitted, swapped, or performed simultaneously. The method may allow the UE to determine a TCI state change at the UE based on a predicted blocking condition.

[0107] At 802, the UE may predict a blocking condition for a first beam. For example, 802 may be performed by the switching component 198 of the device 1004. The UE may predict a blocking condition for a first beam communicating with a network node. In some aspects, the beam switching indication may indicate a corresponding beam at the network node corresponding to the second beam of the UE. The corresponding beam at the network node may be determined based on a correlation between a beam change at the UE and a corresponding beam at the network node. In some aspects, the blocking condition may be based at least on physical movement of a user using the UE or physical movement of the UE. For example, a finger, hand, or body part of a user may change position during the process of using the UE, such that the repositioning of the finger, hand, or body part of the user may cause a blocking condition. Example aspects of blocking may be combined with Figure 4A and Figure 4B This prediction can be based on the combination of Figures 5 to 7 Any of the aspects described.

[0108] At 804, the UE may send a beam switching indication. For example, 804 may be performed by the switching component 198 of the device 1004. The UE may send the beam switching indication to the network node. The beam switching indication may indicate a scheduled change of the TCI state from a first beam mapping to a second beam in response to the predicted blocking condition. In some aspects, the beam switching indication may include a request to switch the beam to a corresponding beam at the network node in association with a predicted time scale. The predicted time scale may correspond to the predicted start time of the blocking condition. The predicted time scale may take into account the switching time of switching the beam at the network node in order to correspond to the beam switching at the UE. Figure 7 An example of a UE sending a beam switching indication is illustrated.

[0109] Fig. 9900 is a flow chart of a method of wireless communication. The method may be performed by a UE (e.g., UE 104; device 1004). One or more of the illustrated operations may be omitted, swapped, or performed simultaneously. The method may allow the UE to determine a TCI state change at the UE based on a predicted blocking condition.

[0110] At 902, the UE may predict a blocking condition for a first beam. For example, 902 may be performed by the switching component 198 of the device 1004. The UE may predict a blocking condition for a first beam communicating with a network node. In some aspects, the beam switching indication may indicate a corresponding beam at the network node corresponding to the second beam of the UE. The corresponding beam at the network node may be determined based on a correlation between a beam change at the UE and a corresponding beam at the network node. In some aspects, the blocking condition may be based at least on physical movement of a user using the UE or physical movement of the UE. For example, a finger, hand, or body part of a user may change position during the process of using the UE, such that the repositioning of the finger, hand, or body part of the user may cause a blocking condition. Example aspects of blocking may be combined with Figure 4A and Figure 4B This prediction can be based on the combination of Figures 5 to 7 Any of the aspects described.

[0111] At 904, the UE may schedule a beam change to a second beam. For example, 904 may be performed by the switching component 198 of the device 1004. The UE may schedule a beam change to a second beam based on the predicted blocking condition. The UE may select the second beam from a set of beams based on the predicted blocking condition. For example, some beams may perform differently under different blocking conditions, so that the UE selects a beam that performs best under the predicted blocking condition. Figure 7 Example aspects of UE scheduling beam changes are illustrated.

[0112] At 906, the UE may correlate a beam change to a second beam at the UE with a corresponding beam change at a network node. For example, 906 may be performed by the switching component 198 of the device 1004. The correlation between the second beam at the UE and the corresponding beam change at the network node may be based on observing the communication between the UE and the network node to estimate the channel matrix between the UE and the network node. In some aspects, the correlation between the second beam at the UE and the corresponding beam change at the network node may be based on an ML or AI framework. The ML or AI framework may predict a blocking condition using prior observations of the communication between the UE and the network node. In some aspects, the ML or AI framework and associated optimization are performed at the UE. In some aspects, the ML or AI framework and associated optimization are performed within a second network node that communicates with the UE. Figure 5 and Figure 7Example aspects of a UE correlating beams are illustrated.

[0113] At 908, the UE may send a beam switching indication. For example, 908 may be performed by the switching component 198 of the device 1004. The UE may send the beam switching indication to the network node. The beam switching indication may indicate a scheduled change of the TCI state from a first beam mapping to a second beam in response to the predicted blocking condition. In some aspects, the beam switching indication may include a request to switch the beam to a corresponding beam at the network node in association with a predicted time scale. The predicted time scale may correspond to the predicted start time of the blocking condition. The predicted time scale may take into account the switching time of switching the beam at the network node in order to correspond to the beam switching at the UE. Figure 7 An example of a UE sending a beam switching indication is illustrated.

[0114] At 910, the UE may switch to the second beam. For example, 910 may be performed by the switching component 198 of the device 1004. The UE may switch to the second beam in response to transmitting the beam switching indication. Figure 7 An example of UE switching to a different beam is illustrated.

[0115] At 912, the UE may monitor for an ACK from the network node. For example, 912 may be performed by the switching component 198 of the device 1004. The UE may monitor for an ACK from the network node to confirm switching to the corresponding beam at the network node. The UE may continue to communicate with the network node using the second beam regardless of whether the UE receives an ACK from the network node. Figure 7 An example in which the UE monitors ACK is illustrated.

[0116] Fig.101000 is a diagram illustrating an example of a hardware implementation for an apparatus 1004. The apparatus 1004 may be a UE, may be a component of a UE, or may implement UE functionality. In some aspects, the apparatus 904 may include a cellular baseband processor 1024 (also referred to as a modem) coupled to one or more transceivers 1022 (e.g., a cellular RF transceiver). The cellular baseband processor 1024 may include on-chip memory 1024'. In some aspects, the apparatus 1004 may also include one or more subscriber identity module (SIM) cards 1020 and an application processor 1006 coupled to a secure digital (SD) card 1008 and a screen 1010. The application processor 1006 may include on-chip memory 1006'. In some aspects, the device 1004 may also include a Bluetooth module 1012, a WLAN module 1014, an SPS module 1016 (e.g., a GNSS module), one or more sensor modules 1018 (e.g., an atmospheric pressure sensor / altimeter; a motion sensor such as an inertial management unit (IMU), a gyroscope, and / or an accelerometer; light detection and ranging (LIDAR), radio-aided detection and ranging (RADAR), sound navigation and ranging (SONAR), a magnetometer, audio, and / or other technologies for positioning), an additional memory module 1026, a power source 1030, and / or a camera 1032. The Bluetooth module 1012, the WLAN module 1014, and the SPS module 1016 may include an on-chip transceiver (TRX) (or in some cases, only a receiver (RX)). The Bluetooth module 1012, the WLAN module 1014, and the SPS module 1016 may include their own dedicated antennas and / or communicate using an antenna 1080. The cellular baseband processor 1024 communicates with the UE 104 and / or with the RU associated with the network node 1002 through the transceiver 1022 via one or more antennas 1080. The cellular baseband processor 1024 and the application processor 1006 may each include a computer-readable medium / memory 1024', 1006', respectively. The additional memory module 1026 may also be considered a computer-readable medium / memory. Each computer-readable medium / memory 1024', 1006', 1026 may be non-transitory. The cellular baseband processor 1024 and the application processor 1006 are each responsible for general processing, including executing software stored on a computer-readable medium / memory. The software, when executed by the cellular baseband processor 1024 / application processor 1006, enables the cellular baseband processor 1024 / application processor 1006 to perform the various functions described above. The computer-readable medium / memory may also be used to store data manipulated by the cellular baseband processor 1024 / application processor 1006 when executing the software.The cellular baseband processor 1024 / application processor 1006 may be a component of the UE 350 and may include the memory 360 and / or at least one of the TX processor 368, the RX processor 356, and the controller / processor 359. In one configuration, the device 1004 may be a processor chip (modem and / or application) and include only the cellular baseband processor 1024 and / or the application processor 1006, and in another configuration, the device 1004 may be the entire UE (e.g., see. Figure 3 350) and includes additional modules of device 1004.

[0117] As discussed above, component 198 is configured to: predict a blocking condition for a first beam communicating with a network node; and send a beam switching indication to the network node indicating a scheduled change of TCI state mapping from the first beam to the second beam in response to the predicted blocking condition. Component 198 may be further configured to perform a combined Figure 8 or Fig. 9 The flowchart description in or Figure 7 The communication process in the UE is performed and / or by Figure 5 Any of the aspects performed by the UE in the . Component 198 may be within the cellular baseband processor 1024, the application processor 1006, or within both the cellular baseband processor 1024 and the application processor 1006. Component 198 may be one or more hardware components specifically configured to perform the described process / algorithm, implemented by one or more processors configured to perform the described process / algorithm, stored in a computer-readable medium for implementation by one or more processors, or some combination thereof. As shown, the device 1004 may include a variety of components configured for various functions. In one configuration, the device 1004 and in particular the cellular baseband processor 1024 and / or the application processor 1006 include a component for predicting a blocking condition for a first beam communicating with a network node. The device includes a component for sending a beam switching indication of a scheduled change from a first beam to a second beam indicating a TCI state to the network node in response to the predicted blocking condition. The device also includes a component for correlating a beam change to a second beam at the UE with a corresponding beam change at the network node. The apparatus further comprises means for scheduling a beam change to a second beam based on the predicted blocking condition. The apparatus further comprises means for switching to the second beam in response to sending a beam switching indication. The apparatus further comprises means for monitoring an ACK from a network node confirming switching to a corresponding beam at the network node. The apparatus further comprises means configured to perform a combined Figure 8 or Fig. 9 The flowchart description in or Figure 7 The communication process in the UE is performed and / or by Figure 5A means for any of the aspects performed by a UE in the apparatus 1004. A means may be a component 198 of the apparatus 1004 configured to perform the functions recited by the means. As described above, the apparatus 1004 may include a TX processor 368, an RX processor 356, and a controller / processor 359. Thus, in one configuration, a means may be a TX processor 368, an RX processor 356, and / or a controller / processor 359 configured to perform the functions recited by the means.

[0118] Fig.11 1100 is a flow chart of a method of wireless communication. The method may be performed by a base station (e.g., base station 102; network node 1302). One or more of the illustrated operations may be omitted, swapped, or performed simultaneously. The method may allow a network node to receive a TCI state change at a UE based on a predicted blocking condition at the UE.

[0119] At 1102, a network node can communicate with a UE. For example, 1102 can be performed by a switching component 199 of the network node 1302. The network node can communicate with the UE using a first beam. Figure 7 An example of a network node communicating with a UE is illustrated.

[0120] At 1104, the network node may obtain a beam switching indication that includes a scheduled change of a TCI state mapped from a first beam to a second beam for the UE based on a predicted blocking condition for the first beam. For example, 1104 may be performed by a switching component 199 of the network node 1302. In some aspects, the beam switching indication may indicate a corresponding beam at the network node corresponding to the second beam of the UE. In some aspects, the corresponding beam at the network node may be determined based on a correlation between the second beam at the UE and the corresponding beam at the network node corresponding to the second beam at the UE. In some aspects, the beam switching indication may include a request to switch the beam to the corresponding beam at the network node in association with a predicted time scale. The predicted time scale may correspond to a start time of the predicted blocking condition. Figure 7 An example in which a network node receives a beam switching indication from a UE is illustrated.

[0121] Fig.12 1200 is a flow chart of a method of wireless communication. The method may be performed by a base station (e.g., base station 102; network node 1302). One or more of the illustrated operations may be omitted, swapped, or performed simultaneously. The method may allow a network node to receive a TCI state change at a UE based on a predicted blocking condition at the UE.

[0122] At 1202, a network node can communicate with a UE. For example, 1202 can be performed by a switching component 199 of the network node 1302. The network node can communicate with the UE using a first beam. Figure 7 An example of a network node communicating with a UE is illustrated.

[0123] At 1204, the network node may obtain a beam switching indication that includes a scheduled change of a TCI state mapped from a first beam to a second beam for the UE based on a predicted blocking condition for the first beam. For example, 1204 may be performed by a switching component 199 of the network node 1302. In some aspects, the beam switching indication may indicate a corresponding beam at the network node corresponding to the second beam of the UE. In some aspects, the corresponding beam at the network node may be determined based on a correlation between the second beam at the UE and the corresponding beam at the network node corresponding to the second beam at the UE. In some aspects, the beam switching indication may include a request to switch the beam to the corresponding beam at the network node in association with a predicted time scale. The predicted time scale may correspond to a start time of the predicted blocking condition. Figure 7 An example in which a network node receives a beam switching indication from a UE is illustrated.

[0124] At 1206, the network node may output an ACK. For example, 1206 may be performed by the switching component 199 of the network node 1302. The network node may output an ACK to the UE. The network node may output an ACK confirming the switching to the corresponding beam corresponding to the second beam at the UE. Figure 7 An example is illustrated in which the network node outputs an ACK to the UE to confirm switching to a corresponding beam corresponding to a second beam at the UE.

[0125] Fig.131300 is a diagram illustrating an example of a hardware implementation for a network node 1302. The network node 1302 may be a BS, may be a component of a BS, or may implement BS functionality. The network node 1302 may include at least one of a CU 1310, a DU 1330, or a RU 1340. For example, depending on the layer functionality handled by the component 199, the network node 1302 may include a CU 1310; both a CU 1310 and a DU 1330; each of the CU 1310, the DU 1330, and the RU 1340; the DU 1330; both a DU 1330 and a RU 1340; or the RU 1340. The CU 1310 may include a CU processor 1312. The CU processor 1312 may include an on-chip memory 1312'. In some aspects, the CU 1310 may also include an additional memory module 1314 and a communication interface 1318. CU 1310 communicates with DU 1330 via a midhaul link such as an F1 interface. DU 1330 may include a DU processor 1332. DU processor 1332 may include on-chip memory 1332'. In some aspects, DU 1330 may also include an additional memory module 1334 and a communication interface 1338. DU 1330 communicates with RU 1340 via a fronthaul link. RU 1340 may include a RU processor 1342. RU processor 1342 may include on-chip memory 1342'. In some aspects, RU 1340 may also include an additional memory module 1344, one or more transceivers 1346, an antenna 1380, and a communication interface 1348. RU 1340 communicates with UE 104. On-chip memory 1312', 1332', 1342' and additional memory modules 1314, 1334, 1344 may each be considered a computer-readable medium / memory. Each computer readable medium / memory may be non-transitory. Each of processors 1312, 1332, 1342 is responsible for general processing, including executing software stored on the computer readable medium / memory. The software, when executed by the corresponding processor, causes the processor to perform the various functions described above. The computer readable medium / memory may also be used to store data manipulated by the processor when executing the software.

[0126] As discussed above, component 199 is configured to: communicate with the UE using a first beam; and obtain a beam switching indication, the beam switching indication including a scheduled change of TCI state mapping from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam. Component 199 may be further configured to perform a combined Fig.11 or Fig.12 The flowchart description in or Figure 7 The communication process in the communication process is performed by the base station and / or by Figure 5Any of the aspects performed by a base station in . Component 199 may be within one or more processors of one or more of CU 1310, DU 1330, and RU 1340. Component 199 may be one or more hardware components specifically configured to perform the process / algorithm, implemented by one or more processors configured to perform the process / algorithm, stored in a computer-readable medium for implementation by one or more processors, or some combination thereof. Network node 1302 may include multiple components configured for various functions. In one configuration, network node 1302 includes a component for communicating with a UE using a first beam. The network node includes a component for obtaining a beam switching indication, the beam switching indication including a scheduled change of a TCI state mapped from a first beam to a second beam for the UE based on a predicted blocking condition for the first beam. The network node also includes a component for outputting an ACK confirming the switch to a corresponding beam corresponding to the second beam at the UE. The network node may also include a component configured to perform a combined Fig.11 or Fig.12 The flowchart description in or Figure 7 The communication process in the communication process is performed by the base station and / or by Figure 5 A means for any of the aspects performed by a base station in the network node 1302. A means may be a component 199 of the network node 1302 configured to perform the functions recited by the means. As described above, the network node 1302 may include a TX processor 316, an RX processor 370, and a controller / processor 375. Thus, in one configuration, a means may be a TX processor 316, an RX processor 370, and / or a controller / processor 375 configured to perform the functions recited by the means.

[0127] It should be understood that the specific order or hierarchy of the blocks in the disclosed process / flowchart is merely an illustration of the exemplary method. It should be understood that the specific order or hierarchy of the blocks in the process / flowchart may be rearranged based on design preferences. Further, some blocks may be combined or omitted. The attached method claims provide the elements of the various blocks in a sample order, but are not limited to the specific order or hierarchy provided.

[0128] The foregoing description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not limited to the various aspects described herein, but should be given the full scope consistent with the language claims. Unless otherwise specified, reference to an element in the singular form does not mean "one and only one", but "one or more". Terms such as "if", "when" and "while" do not mean a direct temporal relationship or reaction. That is, these phrases, such as "when ......", do not mean an immediate action in response to the occurrence of an action or during the occurrence of an action, but simply imply that if the conditions are met, then the action will occur, but no specific or immediate time limit is required for the occurrence of the action. The word "exemplary" is used herein to mean "used as an example, instance or illustration". Any aspect described as "exemplary" herein is not necessarily interpreted as being preferred or having advantages over other aspects. Unless otherwise specified, the term "some" refers to one or more. Combinations such as "at least one of A, B, or C", "one or more of A, B, or C", "at least one of A, B and C", "one or more of A, B, and C", and "A, B, C, or any combination thereof" include any combination of A, B, and / or C, which may include multiple A, multiple B, or multiple C. Specifically, combinations such as "at least one of A, B, or C", "one or more of A, B, or C", "at least one of A, B, and C", "one or more of A, B, and C", and "A, B, C, or any combination thereof" may be only A, only B, only C, A and B, A and C, B and C, or A and B and C, where any such combination may contain one or more members of A, B, or C. A set should be interpreted as a set of elements, where the number of elements is one or more. Thus, for a set of X, X will include one or more elements. If the first device receives data from the second device or sends data to the second device, the data may be received / sent directly between the first device and the second device, or indirectly between the first device and the second device through a collection of devices. All structural and functional equivalents of the elements of the various aspects described throughout the present disclosure that are known or will later be known to a person of ordinary skill in the art are expressly incorporated herein by reference and are covered by the claims. In addition, nothing disclosed herein is intended to be dedicated to the public, regardless of whether such disclosure is explicitly stated in the claims. Words such as "module", "mechanism", "element", "device", etc. cannot replace the word "component". Therefore, no claim element will be understood as a component plus function unless the element is explicitly stated using the phrase "component for..."

[0129] As used herein, the phrase "based on" should not be interpreted as referring to a closed set of information, one or more conditions, one or more factors, etc. In other words, the phrase "based on A" (where "A" can be information, a condition, a factor, etc.) should be interpreted as "based at least on A" unless specifically stated differently.

[0130] The following aspects are merely illustrative and may be combined with other aspects or teachings described herein without limitation.

[0131] Aspect 1 is a method for performing wireless communications at a UE, the method comprising: predicting a blocking condition for a first beam communicating with a network node; and sending a beam switching indication of a scheduled change of mapping a transmission configuration indicator (TCI) state from the first beam to a second beam to the network node in response to the predicted blocking condition.

[0132] Aspect 2 is a method according to aspect 1, the method further comprising the beam switching indication indicating a corresponding beam of the second beam corresponding to the UE at the network node.

[0133] Aspect 3 is a method according to any one of aspects 1 and 2, the method also comprising correlating a beam change at the UE to the second beam with a corresponding beam change at the network node.

[0134] Aspect 4 is a method according to any one of Aspects 1 to 3, the method also including estimating a channel matrix between the UE and the network node based on observing the correlation between the second beam at the UE and the corresponding beam change at the network node.

[0135] Aspect 5 is a method according to any one of aspects 1 to 4, the method also including that the correlation between the second beam at the UE and the corresponding beam change at the network node is based on an ML or AI framework.

[0136] Aspect 6 is a method according to any one of aspects 1 to 5, the method further comprising the ML or AI framework predicting the blocking condition using prior observations of communications between the UE and the network node.

[0137] Aspect 7 is a method according to any one of aspects 1 to 6, the method further comprising the ML or AI framework and associated optimization being performed at the UE.

[0138] Aspect 8 is a method according to any one of aspects 1 to 7, the method further comprising the ML or AI framework and associated optimization being performed within a second network node in communication with the UE.

[0139] Aspect 9 is a method according to any one of Aspects 1 to 8, the method also including determining the corresponding beam at the network node based on a correlation between a beam change at the UE and the corresponding beam at the network node.

[0140] Aspect 10 is a method according to any one of aspects 1 to 9, the method further comprising scheduling a beam change to the second beam based on the predicted blocking condition.

[0141] Aspect 11 is a method according to any one of aspects 1 to 10, the method further comprising the blocking condition being based at least on physical movement of a user using the UE or physical movement of the UE.

[0142] Aspect 12 is a method according to any one of Aspects 1 to 11, the method also comprising switching to the second beam in response to sending the beam switching indication; and monitoring an ACK from the network node confirming the switching to the corresponding beam at the network node.

[0143] Aspect 13 is a method according to any one of aspects 1 to 12, the method also comprising the beam switching indication comprising a request to switch the beam to a corresponding beam at the network node in association with a predicted time scale.

[0144] Aspect 14 is a method according to any one of aspects 1 to 13, the method further comprising the predicted time scale corresponding to a start time of the predicted blocking condition.

[0145] Aspect 15 is an apparatus for wireless communication at a UE, the apparatus comprising at least one processor coupled to a memory and at least one transceiver, the at least one processor being configured to implement any one of aspects 1 to 14.

[0146] Aspect 16 is an apparatus for wireless communication at a target UE, the apparatus comprising means for implementing any one of aspects 1 to 14.

[0147] Aspect 17 is a computer-readable medium storing computer-executable code, wherein the code, when executed by a processor, causes the processor to implement any one of aspects 1 to 14.

[0148] Aspect 18 is a method for wireless communication at a network node, the method comprising using a first beam to communicate with a UE; and obtaining a beam switching indication, the beam switching indication comprising a scheduled change of a TCI state mapped from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam.

[0149] Aspect 19 is a method according to aspect 18, the method further comprising the beam switching indication indicating a corresponding beam of the second beam corresponding to the UE at the network node.

[0150] Aspect 20 is a method according to any one of Aspects 18 and 19, the method also including determining the corresponding beam at the network node based on the correlation between the second beam at the UE and the corresponding beam at the network node corresponding to the second beam at the UE.

[0151] Aspect 21 is a method according to any one of aspects 18 to 20, the method also comprising outputting an ACK confirming switching to a corresponding beam corresponding to the second beam at the UE.

[0152] Aspect 22 is a method according to any one of aspects 18 to 21, the method also comprising the beam switching indication comprising a request to switch the beam to a corresponding beam at the network node in association with a predicted time scale.

[0153] Aspect 23 is a method according to any one of aspects 18 to 22, the method further comprising the predicted time scale corresponding to a predicted start time of the blocking condition.

[0154] Aspect 24 is an apparatus for wireless communication at a network node, the apparatus comprising at least one processor coupled to a memory and at least one transceiver, the at least one processor configured to implement any one of aspects 18 to 23.

[0155] Aspect 25 is an apparatus for wireless communication at a network node, the apparatus comprising means for implementing any one of aspects 18 to 23.

[0156] Aspect 26 is a computer readable medium storing computer executable code, wherein the code, when executed by a processor, causes the processor to implement any one of aspects 18 to 23.

Claims

1. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: Memory; and at least one processor coupled to the memory and based at least in part on the information stored in the memory, the at least one processor configured to: predicting a blockage condition for a first beam communicating with a network node; as well as A beam switching indication is sent to the network node in response to a predicted blocking condition indicating a scheduled change of a transmission configuration indicator (TCI) state mapping from the first beam to a second beam. 2 . The apparatus of claim 1 , further comprising a transceiver coupled to the at least one processor.

3. The apparatus according to claim 1, wherein the beam switching indication indicates a corresponding beam at the network node corresponding to the second beam of the UE.

4. The apparatus of claim 1 , wherein the at least one processor is configured to: A beam change at the UE to the second beam is correlated with a corresponding beam change at the network node.

5. The apparatus of claim 4, wherein the correlation between the second beam at the UE and the corresponding beam change at the network node is based on estimating a channel matrix between the UE and the network node based on observing communications between the UE and the network node.

6. The apparatus of claim 4, wherein the correlation between the second beam at the UE and the corresponding beam change at the network node is based on a machine learning (ML) or artificial intelligence (AI) framework.

7. The apparatus of claim 6, wherein the ML or AI framework utilizes prior observations of communications between the UE and the network node to predict the blocking condition.

8. The apparatus of claim 6, wherein the ML or AI framework and associated optimizations are performed at the UE.

9. The apparatus of claim 6, wherein the ML or AI framework and associated optimizations are performed within a second network node in communication with the UE.

10. The apparatus of claim 3, wherein the corresponding beam at the network node is determined based on a correlation between a beam change at the UE and the corresponding beam at the network node.

11. The apparatus of claim 1 , wherein the at least one processor is configured to: A beam change to the second beam is scheduled based on the predicted blocking condition.

12. The apparatus of claim 1, wherein the blocking condition is based at least on physical movement of a user using the UE or physical movement of the UE.

13. The apparatus of claim 1 , wherein the at least one processor is configured to: switching to the second beam in response to sending the beam switching indication; and Monitoring an acknowledgment from the network node is switched to an acknowledgment (ACK) of a corresponding beam at the network node.

14. The apparatus of claim 1, wherein the beam switching indication comprises a request to switch a beam to a corresponding beam at the network node in association with a predicted time scale. The apparatus of claim 14 , wherein the predicted time scale corresponds to a start time of the predicted blocking condition.

16. A method of wireless communication at a user equipment (UE), the method comprising: predicting a blockage condition for a first beam communicating with a network node; as well as A beam switching indication is sent to the network node in response to a predicted blocking condition indicating a scheduled change of a transmission configuration indicator (TCI) state mapping from the first beam to a second beam.

17. The method according to claim 16, further comprising: A beam change at the UE to the second beam is correlated with a corresponding beam change at the network node.

18. The method according to claim 16, further comprising: A beam change to the second beam is scheduled based on the predicted blocking condition.

19. The method according to claim 16, further comprising: switching to the second beam in response to sending the beam switching indication; as well as Monitoring an acknowledgment from the network node is switched to an acknowledgment (ACK) of a corresponding beam at the network node.

20. An apparatus for wireless communication at a network node, the apparatus comprising: Memory; and at least one processor coupled to the memory and based at least in part on the information stored in the memory, the at least one processor configured to: communicating with a user equipment (UE) using a first beam; as well as A beam switching indication is obtained, the beam switching indication comprising a scheduled change of a transmission configuration indicator (TCI) state mapped from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam.

21. The apparatus of claim 20, further comprising a transceiver coupled to the at least one processor.

22. The apparatus of claim 20, wherein the beam switching indication indicates a corresponding beam at the network node that corresponds to the second beam of the UE.

23. The apparatus of claim 20, wherein the corresponding beam at the network node is determined based on a correlation between the second beam at the UE and the corresponding beam at the network node corresponding to the second beam at the UE.

24. The apparatus of claim 20, wherein the at least one processor is configured to: The output acknowledgement switches to an acknowledgement (ACK) of a corresponding beam corresponding to the second beam at the UE.

25. The apparatus of claim 20, wherein the beam switching indication comprises a request to switch a beam to a corresponding beam at the network node in association with a predicted time scale.

26. The apparatus of claim 25, wherein the predicted time scale corresponds to a predicted start time of the blocking condition.

27. A method for wireless communication at a network node, the method comprising: communicating with a user equipment (UE) using a first beam; as well as A beam switching indication is obtained, the beam switching indication comprising a scheduled change of a transmission configuration indicator (TCI) state mapped from the first beam to a second beam for the UE based on a predicted blocking condition for the first beam.

28. The method of claim 27, wherein the beam switching indication indicates a corresponding beam at the network node that corresponds to the second beam of the UE.

29. The method of claim 27, wherein the corresponding beam at the network node is determined based on a correlation between the second beam at the UE and the corresponding beam at the network node corresponding to the second beam at the UE.

30. The method of claim 27, further comprising: The output acknowledgement switches to an acknowledgement (ACK) of a corresponding beam corresponding to the second beam at the UE.

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