Beam blocking event prediction

Abstract

The first network node includes a processor. The processor may perform a method and is configured to receive a plurality of reference signals. Each reference signal of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers. The processor is further configured to transmit prediction information indicating a predicted beam blocking event. The prediction information is based on measurement information corresponding to the plurality of reference signals during a time period. The second network node is configured to transmit a plurality of reference signals. Each reference signal of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers. The second network node receives measurement information corresponding to the plurality of reference signals during a time period and transmits prediction information indicating a predicted beam blocking event. The prediction information is based on the measurement information.

Description

Technical Field

[0001] The technology disclosed herein relates generally to beam failures, and more particularly to criteria used to predict beam blocking events and to the use of those criteria in services that predict beam blocking events. Background Art

[0002] The use of millimeter wave (mmWave) communication systems promotes the use of large bandwidths of radio frequency spectrum (e.g., compared to segments of radio frequency spectrum utilized in communication systems below 6 GHz). Therefore, the use of mmWave spectrum and the associated large bandwidth available through such use permit an increase in the amount of data transmitted via mmWave communication systems. However, mmWave has problems that affect data transmission, for example, including problems of atmospheric propagation. In order to overcome the losses associated with atmospheric propagation of mmWave, relatively high-gain directional antenna beams can be formed, which can be used to direct signals from a base station to a given user equipment. The mmWave frequency allows an antenna system (such as a phased array antenna system used in 5G) to provide a plurality of spatial directional beams with narrow beam widths and relatively high gains, wherein the plurality of spatial directional beams can be directed toward a plurality of corresponding numbers of user equipment devices. The use of relatively narrow and relatively high-gain beams can help overcome the atmospheric propagation losses associated with mmWave frequencies. Additionally, mmWave communications may be blocked by obstacles such as buildings, trucks, buses, tunnels, and generally man-made or natural (e.g., trees, mountains) objects. Summary of the invention

[0003] An overview of one or more aspects of the present disclosure is presented below to provide a basic understanding of these aspects. This summary is not an extensive review of all contemplated features of the present disclosure, and neither identifies key or critical elements of all aspects of the present disclosure nor delineates the scope of any or all aspects of the present disclosure. Its sole purpose is to present some concepts of one or more aspects of the present disclosure in a form as a preface to a more detailed description presented later.

[0004] According to one aspect, a first network node is described. The first network node includes a memory and a processor coupled to the memory. In this example, the processor is configured to receive a plurality of reference signals. Each reference signal in the plurality of reference signals corresponds to a corresponding identifier in a plurality of identifiers. The processor is further configured to send prediction information indicating a predicted beam blocking event. According to this aspect, the prediction information is based on measurement information corresponding to the plurality of reference signals during a time period.

[0005] In another aspect, a method at a first network node is disclosed. The method includes receiving a plurality of reference signals. According to this aspect, each reference signal in the plurality of reference signals corresponds to a corresponding identifier in a plurality of identifiers. The method also includes sending prediction information indicating a predicted beam blocking event. The prediction information is based on measurement information corresponding to the plurality of reference signals during a time period.

[0006] In another aspect, a first network node is disclosed. The first network node includes a memory and a processor coupled to the memory. According to this aspect, the processor is configured to send a plurality of reference signals. Each reference signal in the plurality of reference signals corresponds to a corresponding identifier in a plurality of identifiers. The processor is further configured to receive measurement information corresponding to the plurality of reference signals during a time period and send prediction information indicating a predicted beam blocking event. According to this aspect, the prediction information is based on the measurement information.

[0007] These and other aspects will be more fully understood upon reviewing the following detailed description. Other aspects, features, and examples will become apparent upon reviewing the following description of specific exemplary aspects in conjunction with the accompanying drawings. Although features may be disclosed with respect to certain examples and drawings, all examples may include one or more of the advantageous features disclosed herein. In other words, although one or more examples may be disclosed as having certain advantageous features, one or more of such features may also be used according to the various examples disclosed herein. Similarly, although examples may be disclosed herein as device, system, or method examples, it should be understood that such examples may be implemented in various devices, systems, and methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic illustration of a wireless communication system according to some aspects of the present disclosure.

[0009] Figure 2 is a schematic illustration of an example of a Radio Access Network (RAN) according to some aspects of the present disclosure.

[0010] Figure 3 is an expanded view of an example subframe showing an orthogonal frequency division multiplexing (OFDM) resource grid according to some aspects of the present disclosure.

[0011] Figure 4 is a schematic diagram illustrating some aspects of beam management according to some aspects of the present disclosure.

[0012] Figure 5A , Figure 5B and Figure 5Cis a diagram illustrating an example of a downlink beam management procedure between a network entity and a user equipment according to some aspects of the present disclosure, the downlink beam management procedure including a downlink beam refinement procedure.

[0013] Figure 6 is a block diagram depicting the use of a neural network, artificial intelligence, and / or machine learning system in collecting data according to some aspects of the present disclosure.

[0014] Figure 7 is a spectrum diagram depicting beam index versus time as a function of reference signal received power according to one example provided in the present disclosure.

[0015] Fig. 8A and Figure 8B 1 and 2 are respectively a spectrum diagram depicting beam index versus time as a function of reference signal received power and a graph indicating beam blocking versus time according to one example provided in the present disclosure.

[0016] Fig.9A The first spectrum diagram is a mean value of reference signal received power (RSRP) of multiple beam blocking prediction-reference signals over beams and over time according to an example provided in the present disclosure.

[0017] Fig. 9B yes Fig.9A Beam blocking prediction - RSRP of reference signal is in Fig.9A The example depicts a second spectrogram of the standard deviation over the same beam and at the same time.

[0018] Fig.10 is a bird's-eye view of a traffic intersection according to some aspects of the present disclosure.

[0019] Fig.11 is an aerial view of a portion of a four-lane divided highway according to some aspects of the present disclosure.

[0020] Fig.12 is a block diagram illustrating an example of a hardware implementation for a wireless communication device employing a processing system according to some aspects of the present disclosure.

[0021] Fig.13 is a flow chart illustrating an exemplary process at a wireless communication device according to some aspects of the present disclosure.

[0022] Fig.14 is a block diagram illustrating an example of a hardware implementation of a network access node employing a processing system according to some aspects of the present disclosure.

[0023] Fig.15 is a flow chart illustrating an exemplary process at a network access node according to some aspects of the present disclosure. DETAILED DESCRIPTION

[0024] The detailed description and the accompanying drawings disclose various configurations, and do not represent the only configurations in which the concepts described herein can be practiced. For the purpose of providing a thorough understanding of the various concepts, the present disclosure includes specific details. However, these concepts can be practiced without these specific details. In some examples, well-known structures and components are shown in block diagram form to avoid blurring the concepts.

[0025] Although various aspects and examples are described in this disclosure by way of illustration of some examples, additional specific implementations and use cases may be generated in many different configurations, arrangements, and scenarios. The innovations described herein may be implemented across many different platform types, devices, systems, shapes, sizes, and packaging arrangements. For example, various aspects and / or uses may be generated via integrated chip examples and other devices based on non-module components (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / shopping devices, medical devices, AI-enabled devices, etc.). Although some examples may or may not specifically point to use cases or applications, the applicability of various types of the described innovations may occur. Specific implementations may 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 aspects of the described innovations. In some examples, the device in conjunction with the described aspects and features may also necessarily include additional components and features for the implementation and practice of the claimed and described examples. For example, the transmission and reception of wireless signals necessarily include multiple components for analog and digital purposes (e.g., hardware components, including antennas, radio frequency (RF) chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc.). The innovations described herein are intended to be practiced in a wide variety of devices of different sizes, shapes, and configurations, chip-level components, systems, distributed arrangements, disaggregated arrangements (e.g., base stations and / or user equipment (UE)), end-user devices, etc.

[0026] Described herein are methods and apparatus for predicting beam blocking events that may occur specifically, but not exclusively, in connected line-of-sight beam pair links utilized in mmWave spectrum. A beam blocking event may be temporary, with an approximate duration of the prediction. A pre-blocking signature may be identified based on a statistical measure (e.g., a measure of variance) of reference signal received power across time and across beam identifiers across multiple beams. User equipment that can predict beam blocking events based on pre-blocking signatures may avoid wasting overhead that would otherwise be consumed by unnecessarily entering beam failure recovery and / or radio link failure procedures.

[0027] The various concepts presented throughout this disclosure may be implemented across a wide variety of telecommunication systems, network architectures, and communication standards. Figure 1 , various aspects of the present disclosure are illustrated with reference to a wireless communication system 100 as an illustrative example. The wireless communication system 100 includes three interacting domains: a core network 102, a radio access network (RAN) 104, and a user equipment (UE) 106. By means of the wireless communication system 100, the UE 106 may be enabled to perform data communications with an external data network 110, such as (but not limited to) the Internet.

[0028] The RAN 104 may implement any suitable one or more wireless communication technologies to provide radio access to the UE 106. As an example, the RAN 104 may operate according to the 3rd Generation Partnership Project (3GPP) New Radio (NR) specification, commonly referred to as 5G. As another example, the RAN 104 may operate according to a hybrid of 5G NR and Evolved Universal Terrestrial Radio Access Network (eUTRAN) standards, commonly referred to as Long Term Evolution (LTE). 3GPP refers to such a hybrid RAN as the Next Generation RAN or NG-RAN. Of course, many other examples may be utilized within the scope of the present disclosure.

[0029] As illustrated, RAN 104 includes multiple base stations 108. In a broad sense, a base station is a network element in a radio access network that is responsible for radio transmission and reception to or from a UE in one or more cells. In different technologies, standards or contexts, a base station may be referred to as a base transceiver station (BTS), a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), an access point (AP), a node B (NB), an eNode B (eNB), a gNode B (gNB), a transmission and reception point (TRP) or some other suitable terminology by those skilled in the art. In some examples, a base station may include two or more TRPs that may be co-located or non-co-located. Each TRP may communicate on the same or different carrier frequencies in the same or different frequency bands. In an example where RAN 104 operates according to two standards, LTE and 5G NR, one of the base stations may be an LTE base station, and the other base station may be a 5G NR base station.

[0030] The RAN 104 is also illustrated as supporting wireless communications for multiple mobile devices. In the 3GPP standards, a mobile device may be referred to as a user equipment (UE), but those skilled in the art may also refer to it as a mobile station (MS), a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal (AT), a mobile terminal, a wireless terminal, a remote terminal, a handset, a terminal, a user agent, a mobile client, a client, or some other suitable terminology. A UE may be a device (e.g., a mobile device) that provides access to network services to a user.

[0031] Within the present disclosure, a "mobile" device does not necessarily need to have the ability to move, but it can be stationary. The term "mobile device" or "mobile device" refers to a wide variety of devices and technologies. A UE may include a plurality of hardware structural components whose size, shape, and arrangement facilitate communication; such components may include antennas, antenna arrays, RF chains, amplifiers, one or more processors, etc. electrically coupled to each other. For example, some non-limiting examples of mobile devices include mobile stations, cellular (cell) phones, smart phones, session initiation protocol (SIP) phones, laptops, personal computers (PCs), notebooks, netbooks, smartbooks, tablets, personal digital assistants (PDAs), and a wide variety of embedded systems (e.g., corresponding to the "Internet of Things" (IoT)).

[0032] The mobile device may also be a car or other transportation vehicle, a remote sensor or actuator, a robot or robotic device, a satellite radio, a global positioning system (GPS) device, an object tracking device, a drone, a multi-rotor aircraft, a quadcopter, a remote control device, a consumer and / or wearable device (such as glasses, wearable cameras, virtual reality devices, smart watches, health or fitness trackers, digital audio players (e.g., MP3 players), cameras, game consoles, etc.). The mobile device may also be a digital home or smart home device (such as home audio, video and / or multimedia devices), an appliance, a vending machine, a smart lighting device, a home security system, a smart meter, etc. The mobile device may also be a smart energy device, a security device, a solar panel or solar array, a municipal infrastructure device that controls electrical power (e.g., a smart grid), lighting, water supply, etc., an industrial automation and enterprise device, a logistics controller, and / or agricultural equipment, etc. In addition, the mobile device may provide connected medical or telemedicine support, such as health care at a distance. Telemedicine devices may include telemedicine monitoring devices and telemedicine management devices, whose communications may be given priority or access over other types of information, for example, in terms of priority access for transmission of critical service data and / or associated QoS for transmission of critical service data.

[0033] Wireless communication between RAN 104 and UE 106 can be described as utilizing an air interface. Transmission from a base station (e.g., base station 108) to one or more UEs (e.g., similar to UE 106) over an air interface can be referred to as downlink (DL) transmission. According to certain aspects of the present disclosure, the term downlink may refer to point-to-multipoint transmission originating from a base station (e.g., base station 108). Another way to describe this scheme may be to use the term "broadcast channel multiplexing". Transmission from a UE (e.g., UE 106) to a base station (e.g., base station 108) may be referred to as uplink (UL) transmission. According to further aspects of the present disclosure, the term uplink may refer to point-to-point transmission originating from a UE (e.g., UE 106).

[0034] In some examples, access to the air interface may be scheduled, wherein a scheduling entity (e.g., a base station 108) allocates resources for communication between some or all devices and equipment within its service area or cell. Within the present disclosure, as disclosed herein, a scheduling entity may be responsible for scheduling, assigning, reconfiguring, and releasing resources for one or more scheduled entities (e.g., UE 106). That is, for scheduled communications, multiple UEs 106 (which may be scheduled entities) may utilize resources allocated by the scheduling entity 108.

[0035] Base station 108 is not the only entity that can act as a scheduling entity. That is, in some examples, a UE can act as a scheduling entity, scheduling resources for one or more scheduled entities (e.g., one or more other UEs). For example, a UE can communicate directly with other UEs in a peer-to-peer or device-to-device manner and / or in a relay configuration.

[0036] like Figure 1 , the scheduling entity 108 may broadcast downlink traffic 112 to one or more scheduled entities (e.g., one or more UEs 106). Broadly speaking, the scheduling entity 108 is a node or device responsible for scheduling traffic in the wireless communication network, including downlink traffic 112 and, in some examples, uplink traffic 116 from one or more scheduled entities (e.g., one or more UEs 106) to the scheduling entity 108. On the other hand, a scheduled entity (e.g., a UE 106) is a node or device that receives downlink control information 114 (including, but not limited to, scheduling information (e.g., grants), synchronization or timing information, or other control information) from another entity in the wireless communication network, such as the scheduling entity 108. The scheduled entity 106 may also send uplink control information 118 (including, but not limited to, scheduling requests or feedback information or other control information) to the scheduling entity 108.

[0037] In addition, uplink control information 118 and / or downlink control information 114 and / or uplink traffic 116 and / or downlink traffic 112 may be sent on a waveform that may be divided into frames, subframes, time slots and / or symbols by time. As used herein, a symbol may refer to a time unit that carries one resource element (RE) per subcarrier in an orthogonal frequency division multiplexing (OFDM) waveform. A time slot may carry 7 or 14 OFDM symbols. A subframe may refer to a duration of 1 ms. Multiple subframes or time slots may be grouped together to form a single frame or radio frame. In the present disclosure, a frame may refer to a predetermined duration (e.g., 10 ms) for wireless transmission, wherein each frame is composed of, for example, 10 subframes each of which is 1 ms. Of course, these definitions are not required, and any suitable scheme for organizing a waveform may be utilized, and the various time divisions of a waveform may have any suitable duration.

[0038] Generally speaking, base stations 108 may include a backhaul interface for communicating with a backhaul portion 120 of wireless communication system 100. Backhaul portion 120 may provide a link between base stations 108 and core network 102. Additionally, in some examples, a backhaul network may provide interconnections between respective base stations 108. Various types of backhaul interfaces may be employed, such as a direct physical connection using any suitable transport network, a virtual network, etc.

[0039] The core network 102 may be part of the wireless communication system 100 and may be independent of the radio access technology used in the RAN 104. In some examples, the core network 102 may be configured according to 5G standards, such as 5G Core (5GC). In other examples, the core network 102 may be configured according to 4G Evolved Packet Core (EPC) or any other suitable standard or configuration.

[0040] See now Figure 2 , by way of illustrative example and not limitation, a schematic illustration of a radio access network (RAN) 200 according to some aspects of the present disclosure is provided. In some examples, the RAN 200 may be similar to the one described above and in Figure 1 is the same as the RAN 104 illustrated in .

[0041] The geographic area covered by the RAN 200 may be divided into a number of cellular regions (cells) that may be uniquely identified by a user equipment (UE) based on an identity broadcast from an access point or base station within the geographic area. Figure 2Cells 202, 204, 206, and 208 are illustrated, each of which may include one or more sectors (not shown). A sector is a sub-area of ​​a cell. All sectors within a cell are served by the same base station. A radio link within a sector may be identified by a single logical identifier belonging to the sector. In a cell divided into sectors, multiple sectors within a cell may be formed by multiple groups of antennas, each of which is responsible for communicating with a UE in a portion of the cell.

[0042] Various base station arrangements can be used. Figure 2 , two base stations (base station 210 and base station 212) are shown in cells 202 and 204. A third base station (base station 214) is shown as controlling a remote radio head (RRH) 216 in cell 206. That is, the base station may have an integrated antenna, or may be connected to an antenna or RRH 216 by a feeder cable. In the illustrated example, cells 202, 204, and 206 may be referred to as macro cells because base stations 210, 212, and 214 support cells with large sizes. In addition, base station 218 is shown in cell 208, which may overlap with one or more macro cells. In this example, cell 208 may be referred to as a small cell (e.g., a small cell, a micro cell, a pico cell, a femto cell, a home base station, a home node B, a home eNode B, etc.) because base station 218 supports a cell with a relatively small size. The cell size setting may be performed according to the system design and component constraints.

[0043] It should be understood that RAN 200 may include any number of wireless base stations and cells. In addition, relay nodes may be deployed to extend the size or coverage area of ​​a given cell. Base stations 210, 212, 214, 218 provide wireless access points to the core network for any number of mobile devices. In some examples, base stations 210, 212, 214, and / or 218 may be similar to those described above and in Figure 1 The scheduling entity 108 illustrated in FIG. 1 is the same as or similar to that in FIG.

[0044] Figure 2 Also included is an unmanned aerial vehicle (UAV) 220, which may be a drone or a quadcopter. UAV 220 may be configured to act as a base station, or more specifically, a mobile base station. That is, in some examples, the cell may not necessarily be stationary, and the geographic area of ​​the cell may move depending on the location of a mobile base station (such as UAV 220).

[0045] Within the RAN 200, cells may include UEs that may communicate with one or more sectors of each cell. In addition, each base station 210, 212, 214, 218, and 220 may be configured to provide access to the core network 102 (see FIG. 1 ) for all UEs in the corresponding cell. Figure 1) access point. For example, UEs 222 and 224 may communicate with base station 210; UEs 226 and 228 may communicate with base station 212; UEs 230 and 232 may communicate with base station 214 via RRH 216; UE 234 may communicate with base station 218; and UE 236 may communicate with mobile base station 220. In some examples, UEs 222, 224, 226, 228, 230, 232, 234, 236, 238, 240, and / or 242 may communicate with the base stations described above and Figure 1 202. In some examples, UAV 220 (e.g., a quadcopter) may be a mobile network node and may be configured to act as a UE. For example, UAV 220 may operate within cell 202 by communicating with base station 210.

[0046] In another aspect of RAN 200, sidelink signals may be used between UEs without having to rely on scheduling or control information from a base station. Sidelink communications may be utilized in a device-to-device (D2D) network, a peer-to-peer (P2P) network, a vehicle-to-vehicle (V2V) network, a vehicle-to-everything (V2X) network, and / or other suitable sidelink networks. For example, two or more UEs (e.g., UEs 238, 240, and 242) may communicate with each other using sidelink signals 237 without relaying the communication through a base station. In some examples, UEs 238, 240, and 242 may each act as a scheduling entity or a sender sidelink device and / or a scheduled entity or a receiver sidelink device to schedule resources and communicate sidelink signals 237 between them without relying on scheduling or control information from a base station. In other examples, two or more UEs (e.g., UEs 226 and 228) within the coverage area of ​​a base station (e.g., base station 212) may also communicate sidelink signals 227 via a direct link (sidelink) without routing the communication through base station 212. In this example, base station 212 may allocate resources to UEs 226 and 228 for sidelink communication.

[0047] In order to achieve a low block error rate (BLER) for transmissions over the air interface while still achieving very high data rates, channel coding may be used. That is, wireless communications may typically utilize a suitable error-correcting block code. In a typical block code, an information message or sequence is split into code blocks (CBs), and an encoder (e.g., a codec) at the transmitting device then mathematically adds redundancy to the information message. Utilizing this redundancy in the encoded information message can improve the reliability of the message, enabling correction of any bit errors that may occur due to noise.

[0048] Data decoding can be implemented in a variety of ways. In early 5G NR specifications, user data is decoded using quasi-cyclic low-density parity check (LDPC) with two different basemaps: one basemap is used for large code blocks and / or high code rates, and the other basemap is used for other cases. Control information and the physical broadcast channel (PBCH) are decoded based on nested sequences using polar decoding. For these channels, puncturing, shortening, and repetition are used for rate matching.

[0049] Aspects of the present disclosure may be implemented using any suitable channel codes. Various implementations of base stations and UEs may include appropriate hardware and capabilities (eg, encoders, decoders, and / or codecs) to utilize one or more of these channel codes for wireless communications.

[0050] In the RAN 200, the ability of a UE to communicate while moving (independent of its location) is called mobility. The various physical channels between the UE and the RAN 200 are generally established, maintained, and released under the control of an access and mobility management function (AMF). In some scenarios, the AMF may include: a security context management function (SCMF) and a security anchor function (SEAF) that performs authentication. The SCMF may manage security contexts for both control plane functionality and user plane functionality in whole or in part.

[0051] In various aspects of the present disclosure, the RAN 200 may utilize DL-based mobility or UL-based mobility to implement mobility and handover (i.e., the transfer of a UE's connection from one radio channel to another). In a network configured for DL-based mobility, during a call with a scheduling entity or at any other time, the UE may monitor various parameters of the signal from its serving cell and various parameters of neighboring cells. Based on the quality of these parameters, the UE may maintain communication with one or more of the neighboring cells. During this time, if the UE moves from one cell to another, or if the signal quality from a neighboring cell exceeds the signal quality from the serving cell for a given amount of time, the UE may perform a handover or handover from the serving cell to a neighboring (target) cell. For example, a UE 224 may move from a geographic area corresponding to its serving cell 202 to a geographic area corresponding to a neighboring cell 206. When the signal strength or quality from a neighboring cell 206 exceeds the signal strength and quality of its serving cell 202 for a given amount of time, the UE 224 may send a report message indicating this to its serving base station 210. In response, UE 224 may receive the handover command, and the UE may proceed with the handover to cell 206 .

[0052] In a network configured for UL-based mobility, the network may select a serving cell for each UE using a UL reference signal from each UE. In some examples, base stations 210, 212, and 214 / 216 may broadcast unified synchronization signals (e.g., unified primary synchronization signal (PSS), unified secondary synchronization signal (SSS), and unified physical broadcast channel (PBCH)). UEs 222, 224, 226, 228, 230, and 232 may receive unified synchronization signals, derive carrier frequency and slot timing from these synchronization signals, and send uplink pilots or reference signals in response to the derived timing. The uplink pilot signal sent by a UE (e.g., UE 224) may be received concurrently by two or more cells (e.g., base stations 210 and 214 / 216) within RAN 200. Each of the cells may measure the strength of the pilot signal, and the radio access network (e.g., one or more of the base stations 210 and 214 / 216 and / or a central node within the core network) may determine a serving cell for the UE 224. As the UE 224 moves through the RAN 200, the RAN 200 may continue to monitor the uplink pilot signals sent by the UE 224. When the signal strength or quality of the pilot signal measured by the neighboring cell exceeds the signal strength or quality measured by the serving cell, the RAN 200 may hand over the UE 224 from the serving cell to the neighboring cell with or without notifying the UE 224.

[0053] Although the synchronization signals transmitted by base stations 210, 212 and 214 / 216 may be uniform, the synchronization signal may not identify a specific cell, but may identify a zone of multiple cells operating on the same frequency and / or using the same timing. Using zones in a 5G network or other next generation communication network implements an uplink-based mobility framework and improves the efficiency of both the UE and the network, because the number of mobility messages that need to be exchanged between the UE and the network can be reduced.

[0054] In various specific implementations, the air interface in the radio access network 200 can utilize licensed spectrum, unlicensed spectrum, or shared spectrum. Licensed spectrum generally provides exclusive use of a portion of the spectrum with the help of a mobile network operator purchasing a license from a government regulator. Unlicensed spectrum provides shared use of a portion of the spectrum without the need for a government-granted license. Although it is still generally necessary to comply with some technical rules to access the unlicensed spectrum, access is generally available to any operator or device. Shared spectrum can fall between licensed spectrum and unlicensed spectrum, where some technical rules or restrictions may be required to access the spectrum, but the spectrum can still be shared by multiple operators and / or multiple RATs. For example, a license holder of a portion of a licensed spectrum may provide licensed shared access (LSA) to share the spectrum with other parties (e.g., with appropriate licensee-determined conditions to obtain access).

[0055] 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 (410 MHz-7.125 GHz) and FR2 (24.25 GHz-52.6 GHz). It should be understood that, although a portion of FR1 is greater than 6 GHz, FR1 is often (interchangeably) referred to as the "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).

[0056] The 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 FR4-a or FR4-1 (52.6GHz-71GHz), FR4 (52.6GHz-114.25GHz) and FR5 (114.25GHz-300GHz). Each of these higher frequency bands falls within the EHF band.

[0057] In view of the above aspects, unless otherwise specifically stated, it should be understood that if the term "sub-6 GHz" or the like is used herein, it can be broadly referred to as a frequency that can be less than 6 GHz, can be within FR1, or can include mid-band frequencies. In addition, unless otherwise specifically stated, it should be understood that if the term "millimeter wave" or the like is used herein, it can be broadly referred to as a frequency that can include mid-band frequencies, can be within FR2, FR4, FR4-a or FR4-1 and / or FR5, or can be within the EHF band.

[0058] Devices communicating in the radio access network 200 may utilize one or more multiplexing techniques and multiple access algorithms to enable simultaneous communication of various devices. For example, the 5G NR specification provides multiple access for UL transmissions from UEs 222 and 224 to the base station 210, and multiplexing of DL transmissions from the base station 210 to one or more UEs 222 and 224 using orthogonal frequency division multiplexing (OFDM) with a cyclic prefix (CP). In addition, for UL transmissions, the 5G NR specification provides support for discrete Fourier transform spread OFDM (DFT-s-OFDM) with CP (also known as single carrier FDMA (SC-FDMA)). However, within the scope of the present disclosure, multiplexing and multiple access are not limited to the above schemes, and may be provided using time division multiple access (TDMA), code division multiple access (CDMA), frequency division multiple access (FDMA), sparse code multiple access (SCMA), resource extension multiple access (RSMA), or other suitable multiple access schemes. In addition, multiplexing of DL transmissions from base station 210 to UEs 222 and 224 may be provided using time division multiplexing (TDM), code division multiplexing (CDM), frequency division multiplexing (FDM), orthogonal frequency division multiplexing (OFDM), sparse code multiplexing (SCM), or other suitable multiplexing schemes.

[0059] The equipment in the radio access network 200 can also utilize one or more duplex algorithms. Duplex refers to a point-to-point communication link in which two endpoints can communicate with each other in two directions. Full-duplex means that two endpoints can communicate with each other at the same time. Half-duplex means that only one endpoint can transmit information to the other endpoint at a time. Half-duplex simulation is often implemented for wireless links using time division duplex (TDD). In TDD, the transmissions in different directions on a given channel are separated from each other using time division multiplexing. That is, in some scenarios, the channel is dedicated to the transmission in one direction, and at other times, the channel is dedicated to the transmission in the other direction, where the direction can change very quickly, for example, several times per time slot. In wireless links, full-duplex channels generally rely on physical isolation of transmitters and receivers and suitable interference elimination techniques. Full-duplex simulation is often implemented for wireless links by utilizing frequency division duplex (FDD) or space division duplex (SDD). In FDD, the transmissions in different directions can operate at different carrier frequencies (for example, in paired spectrum). In SDD, transmissions in different directions on a given channel are separated from each other using spatial division multiplexing (SDM). In other examples, full-duplex communication may be implemented within an unpaired spectrum (e.g., within a single carrier bandwidth), where transmissions in different directions occur within different sub-bands of the carrier bandwidth. This type of full-duplex communication may be referred to herein as sub-band full-duplex (SBFD), also known as flexible duplex.

[0060] Reference Figure 3 Various aspects of the present disclosure are described with reference to the OFDM waveforms schematically illustrated in . Various aspects of the present disclosure can be applied to SC-FDMA waveforms in substantially the same manner as described herein. That is, while some examples of the present disclosure may focus on OFDM links for clarity, it should be understood that the same principles can also be applied to SC-FDMA waveforms.

[0061] Reference now Figure 3 , illustrates an expanded view of an exemplary subframe 302 showing an OFDM resource grid according to some aspects of the present disclosure. However, as will be readily appreciated by those skilled in the art, the physical (PHY) transmission structure for any particular application may differ from the examples described herein depending on any number of factors. Here, time is measured in units of OFDM symbols in the horizontal direction; and frequency is measured in units of subcarriers of a carrier in the vertical direction.

[0062] Resource grid 304 can be used to schematically represent the time-frequency resources for a given antenna port. That is, in a multiple-input multiple-output (MIMO) implementation with multiple available antenna ports, a corresponding plurality of resource grids 304 can be used for communication. Resource grid 304 is divided into a plurality of resource elements (REs) 306. RE (which is 1 subcarrier×1 symbol) is the smallest discrete portion of the time-frequency grid and contains a single complex value representing data from a physical channel or signal. Depending on the modulation utilized in a particular implementation, each RE can represent one or more bits of information. In some examples, a block of REs can be referred to as a physical resource block (PRB), or more simply a resource block (RB) 308, which contains any suitable number of consecutive subcarriers in the frequency domain. In one example, an RB can include 12 subcarriers (a number independent of the parameter set used). In some examples, depending on the parameter set, an RB can include any suitable number of consecutive OFDM symbols in the time domain. In the present disclosure, it is assumed that a single RB (such as RB 308) corresponds entirely to communication in a single direction (transmission or reception for a given device).

[0063] A set of contiguous or discontinuous resource blocks may be referred to herein as a resource block group (RBG), a subband, or a bandwidth part (BWP). A set of subbands or BWPs may span the entire bandwidth. Scheduling a scheduled entity (e.g., a UE) for downlink, uplink, or sidelink transmission typically involves scheduling one or more resource elements 306 within one or more subbands or bandwidth parts (BWPs). Thus, a UE typically utilizes only a subset of a resource grid 304. In some examples, an RB may be the smallest resource unit that may be allocated to a UE. Thus, the more RBs scheduled for a UE, and the higher the modulation scheme selected for the air interface, the higher the data rate for the UE. The RBs may be scheduled by a scheduling entity such as a base station (e.g., a gNB, eNB, etc.), or may be self-scheduled by a UE implementing D2D sidelink communication.

[0064] In this illustration, RB 308 is shown as occupying less than the entire bandwidth of subframe 302, with some subcarriers illustrated above and below RB 308. In a given implementation, subframe 302 may have a bandwidth corresponding to any number of one or more RBs 308. Furthermore, in this illustration, RB 308 is shown as occupying less than the entire duration of subframe 302, although this is only one possible example.

[0065] Each 1 ms subframe 302 may consist of one or more adjacent time slots. Figure 3In the example shown, as an illustrative example, a subframe 302 includes four time slots 310. In some examples, a time slot may be defined according to a specified number of OFDM symbols with a given cyclic prefix (CP) length. For example, a time slot may include 7 or 14 OFDM symbols with a nominal CP. Additional examples may include micro-slots (sometimes referred to as shortened transmission time intervals (TTIs)) with shorter durations (e.g., one to three OFDM symbols). These micro-slots or shortened transmission time intervals (TTIs) may be transmitted in some cases by occupying resources that are scheduled for ongoing time slot transmissions for the same UE or different UEs. Any number of resource blocks may be utilized within a subframe or time slot.

[0066] An expanded view of one of the time slots 310 illustrates that the time slot 310 includes a control region 312 and a data region 314. In general, the control region 312 may carry control channels, and the data region 314 may carry data channels. Of course, a time slot may contain full DL, full UL, or at least one DL portion and at least one UL portion. Figure 3 The structures illustrated in are merely exemplary in nature, and different slot structures may be utilized and may include one or more regions in each of the control region and the data region.

[0067] Although not in Figure 3 Although not illustrated in FIG. 3 , various REs 306 within an RB 308 may be scheduled to carry one or more physical channels, including a control channel, a shared channel, a data channel, etc. Other REs 306 within an RB 308 may also carry pilot signals or reference signals. These pilot signals or reference signals may be provided to a receiving device to perform channel estimation of the corresponding channel, which may enable coherent demodulation / detection of a control channel and / or a data channel within the RB 308.

[0068] In some examples, time slot 310 may be used for broadcast, multicast, groupcast, or unicast communications. For example, broadcast, multicast, or groupcast communications may refer to point-to-multipoint transmissions from one device (e.g., a base station, UE, or other similar device) to other devices. Here, broadcast communications are delivered to all devices, while multicast or groupcast communications are delivered to multiple intended receiving devices. Unicast communications may refer to point-to-point transmissions from one device to a single other device.

[0069] In an example of cellular communication over a cellular carrier via a Uu interface, for DL ​​transmissions, a scheduling entity (e.g., a base station) may allocate one or more REs 306 (e.g., within a control region 312) to one or more scheduled entities (e.g., UEs) to carry DL control information including one or more DL control channels (such as a physical downlink control channel (PDCCH)). The PDCCH carries downlink control information (DCI) including, but not limited to, power control commands (e.g., one or more open-loop power control parameters and / or one or more closed-loop power control parameters), scheduling information, grants, and / or assignments of REs for DL ​​transmissions and UL transmissions. The PDCCH may further carry hybrid automatic repeat request (HARQ) feedback transmissions, such as acknowledgements (ACKs) or negative acknowledgements (NACKs). HARQ is a technique in which the integrity of packet transmissions may be checked for accuracy at the receiving side (e.g., using any suitable integrity check mechanism, such as a checksum or cyclic redundancy check (CRC)). If the integrity of the transmission is confirmed, an ACK may be sent, and if it is not confirmed, a NACK may be sent. In response to the NACK, the sending device may transmit a HARQ retransmission, which may implement trace combining, incremental redundancy, and the like.

[0070] The base station may also allocate one or more REs 306 (e.g., in the control region 312 or the data region 314) to carry other DL signals, such as a demodulation reference signal (DMRS); a phase tracking reference signal (PT-RS); a channel state information (CSI) reference signal (CSI-RS); and a synchronization signal block (SSB). The SSB may be broadcast at regular intervals based on a periodicity (e.g., 5ms, 10ms, 20ms, 40ms, 80ms, or 160ms). The SSB includes a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast control channel (PBCH). The UE may use the PSS and SSS to achieve radio frame, subframe, time slot, and symbol synchronization in the time domain, identify the center of the channel (system) bandwidth in the frequency domain, and identify the physical cell identity (PCI) of the cell.

[0071] The PBCH in the SSB may also include a master information block (MIB) containing various system information and parameters for decoding a system information block (SIB). The SIB may be, for example, SystemInformationType 1 (SIB1), which may include various additional system information. The MIB and SIB1 together provide minimum system information (SI) for initial access. Examples of system information sent in the MIB may include, but are not limited to, subcarrier spacing (e.g., default downlink parameter set), system frame number, configuration of the PDCCH control resource set (CORESET) (e.g., PDCCH CORESET0), cell barring indicator, cell reselection indicator, grid offset, and search space for SIB1. Examples of remaining minimum system information (RMSI) sent in SIB1 may include, but are not limited to, random access search space, paging search space, downlink configuration information, and uplink configuration information. The base station may also send other system information (OSI).

[0072] In an UL transmission, a scheduled entity (e.g., a UE) may utilize one or more REs 306 to a scheduling entity to carry UL control information (UCI) including one or more UL control channels, such as a physical uplink control channel (PUCCH). The UCI may include various packet types and categories, including pilots, reference signals, and information configured to enable or assist in decoding uplink data transmissions. Examples of uplink reference signals may include a sounding reference signal (SRS) and an uplink DMRS. In some examples, the UCI may include a scheduling request (SR), i.e., a request to a scheduling entity to schedule an uplink transmission. In this document, in response to the SR sent on the UCI, the scheduling entity may send downlink control information (DCI), which may schedule resources for uplink packet transmissions. The UCI may also include HARQ feedback, channel state feedback (CSF) (such as a CSI report), or any other suitable UCI.

[0073] In addition to control information, one or more REs 306 (e.g., within the data region 314) may also be allocated for data. Such data may be carried on one or more traffic channels, such as, for DL ​​transmissions, on a physical downlink shared channel (PDSCH); or for UL transmissions, on a physical uplink shared channel (PUSCH). In some examples, one or more REs 306 within the data region 314 may be configured to carry other signals, such as one or more SIBs and DMRS. In some examples, the PDSCH may carry multiple SIBs, not limited to SIB1 disclosed herein. For example, OSI may be provided in these SIBs (e.g., SIB2 and above).

[0074] In an example of sidelink communication on a sidelink carrier via a proximity service (ProSe) PC5 interface, a control region 312 of a time slot 310 may include a physical sidelink control channel (PSCCH) including sidelink control information (SCI) sent by an initiator (sender) sidelink device (e.g., a Tx V2X device or other Tx UE) toward a set of one or more other receiver sidelink devices (e.g., an Rx V2X device or other Rx UE). A data region 314 of the time slot 310 may include a physical sidelink shared channel (PSSCH) including sidelink data sent by an initiator (sender) sidelink device in resources reserved by the sender sidelink device on the sidelink carrier via the SCI. Other information may also be sent via various REs 306 within the time slot 310. For example, HARQ feedback information may be sent from a receiver sidelink device to a sender sidelink device in a physical sidelink feedback channel (PSFCH) within the time slot 310. Additionally, one or more reference signals may be sent within slot 310, such as a sidelink SSB, a sidelink CSI-RS, a sidelink SRS, and / or a sidelink positioning reference signal (PRS).

[0075] These physical channels described above are typically multiplexed and mapped to transport channels for processing at the medium access control (MAC) layer. The transport channels carry blocks of information called transport blocks (TBs). Based on the modulation and coding scheme (MCS) and the number of RBs in a given transmission, the transport block size (TBS), which may correspond to the number of information bits, may be a controlled parameter.

[0076] Figure 1 , Figure 2 and Figure 3 The channels or carriers illustrated are not necessarily all channels or carriers that may be utilized between devices, and other channels or carriers may be utilized in addition to those illustrated, such as other traffic, control, and feedback channels.

[0077] As described herein, different terms may be used in various aspects to describe the communication of information (e.g., any information, signal, etc.). Disclosure of one communication term includes disclosure of other communication terms. For example, a first network node may be described as being configured to send information to a second network node. In this example and consistent with the present disclosure, disclosure that the first network node is configured to send information to the second network node includes disclosure that the first network node is configured to provide, transmit, output, communicate, or send information to the second network node. Similarly, in this example and consistent with the present disclosure, disclosure that the first network node is configured to send information to the second network node includes disclosure that the second network node is configured to receive, obtain, or decode information provided, transmitted, output, communicated, or sent by the first network node.

[0078] As described herein, a node (which may be referred to as a node, a network node, a network entity, or a wireless node) may include, may be, or may be included in (e.g., as a component of) a base station (e.g., any base station described herein), a UE (e.g., any UE described herein), a network controller, an apparatus, a device, a computing system, an integrated access and backhaul (IAB) node, a distributed unit (DU), a central unit (CU), a remote / radio unit (RU) (which may also be referred to as a remote radio unit (RRU)), and / or another processing entity configured to perform any of the techniques described herein. For example, the network node may be a UE. For another example, the network node may be a base station or a network entity. For another example, a first network node may be configured to communicate with a second network node or a third network node. In one aspect of this example, the first network node may be a UE, the second network node may be a base station, and the third network node may be a UE. In another aspect of this example, the first network node may be a UE, the second network node may be a base station, and the third network node may be a base station. In yet other aspects of this example, the first network node, the second network node, and the third network node may be different relative to these examples. Similarly, references to UE, base station, device, equipment, computing system, etc. may include disclosure of UE, base station, device, equipment, computing system, etc. as a network node. For example, a disclosure that a UE is configured to receive information from a base station also discloses that a first network node is configured to receive information from a second network node. Consistent with the present disclosure, once a specific example is expanded according to the present disclosure (e.g., a UE is configured to receive information from a base station also discloses that a first network node is configured to receive information from a second network node), a broader example of a narrower example may be interpreted in reverse, but in a broad, open-ended manner. In the above example where a UE is configured to receive information from a base station also discloses that a first network node is configured to receive information from a second network node, the first network node may refer to a first UE configured to receive information, a first base station, a first device, a first device, a first computing system, a first set of one or more components, a first processing entity, etc.; and the second network node may refer to a second UE, a second base station, a second device, a second device, a second computing system, a second set of one or more components, a second processing entity, etc.

[0079] Figure 4 4 is a schematic diagram 400 illustrating some aspects of beam management according to some aspects of the present disclosure. A user equipment (not shown) may obtain initial access 402 to a network via a base station (not shown). The user equipment may be, for example, in conjunction with a base station. Figure 1 and / or Figure 2 Any user equipment (UE), wireless communication device or scheduled entity shown and described. The base station may be, for example, in combination with Figure 1 and / or Figure 2Any base station, network access node, gNB, or scheduling entity shown and described. In some examples, the base station can be implemented as a converged base station or a decomposed base station. In a decomposed base station architecture, the base station can include one or more of a central unit (CU), a distributed unit (DU), or a radio unit (RU).

[0080] The user equipment may enter a random access channel (RACH) procedure to obtain initial access. The UE and the network access node may enter a synchronization process during the RACH procedure. The network access node may send multiple synchronization signals during the synchronization process. Each synchronization signal may be sent in corresponding multiple downlink beams pointing to corresponding multiple directions. This process may be referred to as beam scanning. In beam scanning, the network access node scans its downlink beam by sending a downlink beam in a specific direction at a specific time, then sending the next downlink beam in the next direction at the next time, etc. Different corresponding synchronization signal blocks (SSBs) or channel state information reference signals (CSI-RS) or beam blocking prediction-reference signals as described herein may be used with each corresponding downlink beam during the beam scanning procedure. The beam scanning procedure may utilize a relatively wide beam, which is referred to herein as a layer 1 (L1) beam.

[0081] The UE may evaluate the quality of the SSB or CSI-RS and select the beam with the best quality from among those beams scanned by the network access node. The UE may inform the network access node of the selection using, for example, a physical random access channel (PRACH) resource mapped to each respective downlink beam. The user equipment may utilize the CSI report to provide the network access node with the identity of the beam with the best quality.

[0082] Regarding the beam blocking prediction-reference signal, the UE may measure and collect RSRP of the beam blocking prediction-reference signal over beams and over time for aspects related to beam failure prediction.

[0083] According to one aspect, a process of beam management referred to herein as P1 / P2 / P3 may be practiced to refine the downlink beam direction. In short, during the P1 process, the network access node scans the L1 beam as described above, and the user equipment selects the best beam and reports the identity of the best beam to the network access node substantially as described above. During the P2 process, the network access node may refine the beam direction by scanning a narrower beam within a narrower range, and the user equipment may again select the best beam and report the identity of the (refined) best beam to the network access node. During the P3 process, if the user equipment supports beamforming, the network access node may fix the best beam identified by the user equipment (e.g., by repeatedly sending the best beam identified by the user equipment), and the user equipment (using its beamforming circuit) may adjust its receive beam to effectively point in the direction of the network access node. There may be another process referred to herein as the U1 / U2 / U3 process, which may be a corresponding process, but is used to refine the uplink beam direction, but for the sake of brevity, its explanation is omitted herein.

[0084] After successfully completing the random access procedure, the UE may enter a connected mode 404 with a network access node. From time to time, a beam failure may be detected and may be recovered from (as indicated by the clockwise arrow linking beam failure recovery procedure 406 and connected mode 404).

[0085] At the time of beam failure detection, the network access node may configure the user equipment with a beam failure detection reference signal that is different from the beam blocking prediction-reference signal. For example, the beam failure detection reference signal (BFD-RS) may be an SSB or a CSI-RS. When the number of beam failure instance indications from the physical layer reaches a configured threshold before the configured timer expires, the user equipment may declare a beam failure. SSB-based beam failure detection may be based on the SSB associated with the initial DL BWP. It may be configured for the initial DL BWP and the DL BWP containing the SSB associated with the initial DL BWP. For other DL BWPs, beam failure detection may be performed based on CSI-RS. For example, the user equipment may trigger a beam failure recovery procedure 406 based on the user equipment detecting a beam failure on the PCell. In some aspects, according to the beam failure recovery procedure, the user equipment may lose a first link associated with a first beam, but may have the ability to establish a second link with a second beam by completing a random access process via a second beam. Thus, the beam failure recovery procedure 406 may include initiating a random access procedure on a primary cell (PCell). Additionally, reference to triggering the beam failure recovery procedure 406 based on detecting a beam failure on the PCell may in some aspects refer to the beam failure recovery procedure 406 being triggered in response to detecting a beam failure on the PCell. Upon completion of the random access procedure, the beam failure recovery procedure 406 associated with the PCell may be considered complete. Similar procedures may be followed for a secondary cell (SCell).

[0086] In some examples, after a beam failure occurs, the user equipment may be unable to recover the link. For example, in an RRC connected mode (e.g., connected mode 404), the user equipment may perform radio link monitoring (RLM) in an active BWP based on reference signals (e.g., SSB and / or CSI-RS). As an example and not limitation, the user equipment may enter the radio link failure procedure 408 in the following circumstances: after the expiration of a radio problem timer that is started after an indication of a radio problem from the physical layer; after the expiration of a timer that is started when a measurement report is triggered for a measurement identity for which a timer has been configured while another radio problem timer is running; after a random access procedure failure; or after a radio link control (RLC) failure. Other criteria may also cause the user equipment to enter the radio link failure procedure 408.

[0087] Figure 5A , Figure 5B and Figure 5C 5 is a diagram illustrating an example of a downlink beam management procedure between a network entity 504 and a UE 502 according to some aspects, the downlink beam management procedure including a downlink beam refinement procedure. The network entity 504 may be Figure 1and / or Figure 2 Any of the base stations (e.g., gNB) or scheduling entities illustrated in FIG. , and UE 502 may be Figure 1 and / or Figure 2 In some examples, the network entity 504 may be implemented as a converged base station or a decomposed base station. In a decomposed base station architecture, the network entity 504 may include one or more of a central unit (CU), a distributed unit (DU), or a radio unit (RU).

[0088] The network entity 504 may generally have the capability to communicate with the UE 502 using one or more transmit beams, and the UE 502 may also have the capability to communicate with the network entity 504 using one or more receive beams. As used herein, the term transmit beam refers to a beam on the network entity 504 that can be used for downlink or uplink communication with the UE 502. Additionally, the term receive beam refers to a beam on the UE 502 that can be used for downlink or uplink communication with the network entity 504.

[0089] exist Figure 5A In the example shown in , the network entity 504 is configured to generate multiple transmit beams 506a-506f, each transmit beam being associated with a different spatial direction. Each of the transmit beams 506a-506f may be referred to by a corresponding beam ID (e.g., an SSB resource indicator (SRI), a beam index value). In addition, the UE 502 is configured to generate multiple receive beams 508a-508e, each receive beam being associated with a different spatial direction. Each of the receive beams 508a-508e may also be referred to by a corresponding beam ID (e.g., via a quasi-co-location (QCL) relationship with an SSB resource indicator (SRI), a CSI-RS resource indicator (CRI), or an SRS resource indicator (SRI)). In some examples, the transmit beams 506a-506h on the network entity 504 and the receive beams 508a-508e on the UE 502 may be spatially directional mmWave beams, such as FR2, FR4-a, FR4-1, FR4, or FR5 beams. It should be noted that although some beams are illustrated as being adjacent to each other, such an arrangement may be different in different aspects. For example, transmit beams 506a-506f transmitted during the same symbol may not be adjacent to each other. In some examples, the network entity 504 and the UE 502 may each transmit more or less beams distributed in all directions (e.g., 360 degrees) and in three dimensions. In addition, the transmit beams 506a-506f may include beams with varying beam widths. For example, the network entity 504 may transmit certain signals (e.g., SSB) on a wider beam and other signals (e.g., CSI-RS) on a narrower beam.

[0090] The network entity 504 and the UE 502 may use a beam management procedure to select one or more transmit beams 506a-506f on the network entity 504 and one or more receive beams 508a-508e on the UE 502 for communicating uplink and downlink signals therebetween. Figure 5A As shown, during initial cell acquisition, the UE 502 may perform a P1 beam management procedure to scan the multiple transmit beams 506a-506f transmitted in a wide range beam scan on the multiple receive beams 508a-508e to select a beam pair link (e.g., one of the transmit beams 506a-506f and one of the receive beams 508a-508e) for a physical random access channel (PRACH) procedure for initial access to the cell. For example, periodic SSB beam scanning may be implemented at certain intervals (e.g., based on SSB periodicity) on the network entity 504. Thus, the network entity 504 may be configured to scan or transmit SSBs on each of the multiple wider transmit beams 506a-506f. The UE may measure a reference signal received power (RSRP) of each of the SSB transmit beams on each of the receive beams of the UE, and select transmit and receive beams based on the measured RSRP. In an example, the selected receive beam may be the receive beam on which the highest RSRP is measured, and the selected transmit beam may have the highest RSRP measured on the selected receive beam. The selected transmit beam and the receive beam form a beam pair link (BPL) for the PRACH procedure. Here, the selected transmit beam may be associated with a specific RACH opportunity that can be used by the UE 502 to send a PRACH preamble. In this way, the network entity 504 is informed of the selected transmit beam.

[0091] After completing the PRACH procedure, if Figure 5BAs shown, the network entity 504 and the UE 502 may perform a P2 beam management procedure for beam refinement. For example, the network entity 504 may be configured to scan or transmit CSI-RS on each of a plurality of narrower transmit beams 510a-510c in a narrow range beam scan for beam refinement. For example, each of the CSI-RS beams may have a narrower beam width than the SSB beam, and thus the transmit beams 510a-510c transmitted during the P2 procedure may each be a sub-beam of the SSB transmit beam selected during the P1 procedure (e.g., within the spatial direction of the SSB transmit beam). The transmission of CSI-RS transmit beams may occur periodically (e.g., as configured by the gNB via radio resource control (RRC) signaling), semi-persistently (e.g., as configured by the gNB via RRC signaling and activated / deactivated via medium access control-control element (MAC-CE) signaling), or aperiodically (e.g., as triggered by the gNB via downlink control information (DCI)). The UE 502 is configured to scan the multiple CSI-RS transmit beams 510a-510c on one or more of the multiple receive beams. Figure 5B In the example shown in , UE 502 scans CSI-RS transmit beams 510a-510c on a single receive beam 508c selected during the P1 procedure. UE 502 then performs beam measurements (e.g., RSRP, signal to interference plus noise ratio (SINR), etc.) on transmit beams 510a-510c on receive beam 508c to determine the respective beam quality of each of transmit beams 510a-510c.

[0092] The UE 502 may then generate and send a layer 1 (L1) measurement report (e.g., L1-RSRP or L1-SINR report) including a corresponding beam ID (e.g., CSI-RS resource indicator (CRI)) and beam measurement results (e.g., RSRP) for one or more of the CSI-RS transmit beams 510a-510c to the network entity 504. The network entity 504 may then select one or more CSI-RS transmit beams on which to communicate with the UE 502. In some examples, the selected CSI-RS transmit beam has the highest RSRP from the L1 measurement report. The transmission of the L1 measurement report may occur periodically (e.g., as configured by the gNB via RRC signaling), semi-persistently (e.g., as configured by the gNB via RRC signaling and activated / deactivated via MAC-CE signaling), or aperiodically (e.g., triggered by the gNB via DCI).

[0093] UE 502 may further refine the receive beam of each selected service CSI-RS transmit beam to form a corresponding refined BPL for each selected service CSI-RS transmit beam. Figure 5C As shown, the UE 502 may perform a P3 beam management procedure to refine the UE beam of the BPL. In an example, the network entity 504 may repeatedly send the selected transmit beam 510b selected during the P2 procedure to the UE 502. The UE 502 may use different receive beams 508b-508d to scan the transmit beam 510b to obtain beam measurements for the selected CSI-RS transmit beam 510b and select the best receive beam to refine the BPL of the transmit beam 510b. In some examples, the selected receive beam to be paired with a particular CSI-RS transmit beam 510b may be the receive beam on which the highest RSRP is measured for the particular CSI-RS transmit beam.

[0094] In some examples, in addition to configuring the UE 502 to perform P2 beam refinement (e.g., CSI-RS beam measurement), the network entity 504 may also configure the UE 502 to perform P1 beam management procedures (e.g., SSB beam measurement) outside of the RACH procedure and provide an L1 measurement report that includes beam measurement results for one or more SSB transmit beams 506a-506f as measured on one or more of the receive beams 508a-508e. In this example, the L1 measurement report may include multiple RSRPs for each transmit beam, where each RSRP corresponds to a specific receive beam to facilitate selection of a BPL. For example, the network entity 504 may configure the UE 502 to perform SSB beam measurements and / or CSI-RS beam measurements for various purposes, such as beam failure detection (BFD), beam failure recovery (BFR), cell reselection, beam tracking (e.g., for mobile UE 502 and / or network entity 504), or other beam optimization purposes.

[0095] In one example, a single CSI-RS transmit beam (e.g., beam 510b) on the network entity 504 and a single receive beam (e.g., beam 508c) on the UE may form a single BPL for communication between the network entity 504 and the UE 502. In another example, multiple CSI-RS transmit beams (e.g., beams 510a, 510b, and 510c) on the network entity 504 and a single receive beam (e.g., beam 508c) on the UE 502 may form respective BPLs for communication between the network entity 504 and the UE 502. In another example, multiple CSI-RS transmit beams (e.g., beams 510a, 510b, and 510c) on the network entity 504 and multiple receive beams (e.g., beams 508c and 508d) on the UE 502 may form multiple BPLs for communication between the network entity 504 and the UE 502. In this example, the first BPL may include the transmit beam 510b and the receive beam 508c, the second BPL may include the transmit beam 510a and the receive beam 508c, and the third BPL may include the transmit beam 510c and the receive beam 508d.

[0096] In addition to the L1 measurement report, the UE 502 may also utilize the beam reference signal to estimate the channel quality of the channel between the network entity 504 and the UE 502. For example, the UE 502 may measure the SINR of each received CSI-RS and generate a CSI report based on the measured SINR. The CSI report may include, for example, a channel quality indicator (CQI), a rank indicator (RI), a precoding matrix indicator (PMI), and / or a layer indicator (LI). The scheduling entity may use the CSI report to select a rank and a precoding matrix and an MCS for the scheduled entity for future downlink transmissions to the scheduled entity. The MCS may be selected from one or more MCS tables, each MCS table being associated with a specific type of coding (e.g., polar coding, LDPC, etc.) or modulation (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), 16 quadrature amplitude modulation (QAM), 64QAM, 256QAM, etc.). The LI may be used to indicate which column of the precoding matrix for the reported PMI corresponds to the strongest layer codeword corresponding to the reported maximum wideband CQI.

[0097] To distinguish between different types of reports (including CSI reports and L1 measurement reports) and different types of measurements, network entity 504 may configure UE 502 with one or more report settings. Each report setting may be associated with a reference signal configuration indicating a configuration of one or more reference signals (e.g., CSI-RS) used to generate a CSI report. In some examples, a report setting may be associated with a combined reference signal configuration.

[0098] In some examples, neural networks, artificial intelligence (AI), and / or machine learning (ML) may be applied to various use cases involving the air interface between user equipment 502 and network entity 504. For example, neural networks / AI / ML may be used to improve performance, reduce or better manage complexity.

[0099] Some use cases may involve one or more processes for beam failure prediction and / or identifying a given beam failure event as a temporary beam failure event; where, due to the temporary nature of the beam failure event, there is a probability that the UE 502 will not need to enter a beam failure recovery process or a radio link failure process.

[0100] For example, the possible use of a neural network / AI / ML in conjunction with a beam failure event prediction and / or a process for identifying a given beam failure event as a temporary beam failure event can enhance the continuity of communications by predicting (e.g., determining, concluding) that a given beam failure event may be due to a temporary obstruction of a transmit and receive beam pair link. For example, and not limitation, the temporary obstruction may be caused by the line of sight between the UE 502 and the network entity 504 being temporarily blocked due to a truck or bus passing between the UE and the network entity. In another example, and without any limitation, the temporary obstruction may be caused by the line of sight between the UE 502 and the network entity 504 being temporarily blocked due to the trajectory of the UE 502, wherein the trajectory may cause a man-made object (e.g., a building, a billboard, a tunnel, an overpass, etc.) or a natural object (e.g., a tree, a mountain, a canyon, etc.) to temporarily interrupt the line of sight between the UE 502 and the network entity 504.

[0101] In these examples, the beam may be a mmWave beam, and the temporary blocking may be due, at least in part, to characteristics of mmWave. For example, these characteristics may include, but are not limited to, a reduced ability of mmWave signals (e.g., user traffic and / or control messaging) to penetrate man-made and natural objects, and greater attenuation of mmWave signals over a given distance when compared to attenuation of non-mmWave signals (e.g., sub-6 GHz signals) over the same given distance. The ability to predict whether a given signal loss is due to a temporary beam blocking event may reduce the amount of time that would otherwise be spent in a UE determining that it is necessary to enter a beam failure recovery procedure (such as in conjunction with Figure 4 beam failure recovery procedure 406 process shown and described) or a radio link failure process (such as in conjunction with Figure 4 The overhead incurred in the case of a radio link failure procedure 408 process) as shown and described.

[0102] Neural networks / AI / ML can also be used in conjunction with beam management. For example, neural networks / AI / ML can assist in beam failure prediction in the time domain and / or in the spatial domain to reduce overhead and latency and / or improve beam selection accuracy.

[0103] Figure 6 is a block diagram depicting the use of a neural network / AI / ML system 600 in collecting data according to some aspects of the present disclosure. Figure 6 , data collection 602 may be a circuit / function that provides input data to a model training 604 and a model inference 606 circuit / function.

[0104] Examples of input data may include, but are not limited to, measurements from a UE or a different network entity, feedback 620 from an actioner 608 circuit / function, and inference output 616 from a neural network / AI / ML model inference 606 circuit / function obtained via an actioner 608 circuit / function. As used herein, an actioner 608 circuit / function may select a given action (e.g., may indicate that the received data has a high probability of corresponding to data indicating a temporary beam blocking event).

[0105] Training data 610 may be data used as input to a neural network / AI / ML model training 604 circuit / function.

[0106] Inference data 612 may be used as input to neural network / AI / ML model inference 606 circuits / functions.

[0107] Model training 604 may be a circuit / function that performs ML model training, validation, and testing, which may generate model performance metrics as part of a model testing procedure. If necessary, the model training 604 circuit / function may also be responsible for data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the training data 610 delivered by the data collection 602 circuit / function.

[0108] Model deployment / update 614 may be used to first deploy a trained, validated, and tested neural network / AI / ML model to the model inference 606 circuit / function or to deliver an updated model to the model inference 606 circuit / function.

[0109] The model inference 606 circuit / function may provide a neural network / AI / ML model inference output (e.g., a prediction or decision). In some examples, the model inference 606 circuit / function may provide model performance feedback to the model training 604 circuit / function. If necessary, the model inference 606 circuit / function may also be responsible for data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the inference data 612 delivered by the data collection 602 circuit / function.

[0110] Figure 6 The output of the neural network / AI / ML system 600 may be an inference output 616 of the neural network / AI / ML model produced by the model inference 606 circuit / function. According to some aspects, the details of the inference output 616 may be use case specific.

[0111] If certain information derived from the model inference 606 circuit / function is applicable to improving the neural network / AI / ML model trained in the model training 604 circuit / function, then model performance feedback 618 may be applied. Feedback 620 from the actor 608 circuit / function or other network entities (e.g., via the data collection 602 circuit / function) may be used at the model inference 606 circuit / function to create model performance feedback 618.

[0112] The actor 608 circuit / function may receive output from the model inference 606 circuit / function and may trigger or perform a corresponding action. The actor 608 circuit / function may trigger an action involving other entities or itself.

[0113] According to some aspects of the present disclosure, predictive beam management based on neural networks / AI / ML may be employed. Because beam quality and failures are identified via measurements, neural networks / AI / ML are well suited for beam management aspects. Without neural networks / AI / ML, improvements in beam management may be associated with additional power requirements and additional overhead to achieve improved performance. In some solutions without neural networks / AI / ML, beam accuracy may be limited due to power and / or overhead limitations. For non-neural network / AI / ML aspects, latency and / or throughput may be adversely affected by beam failures and / or radio link failure processes (i.e., beam recovery efforts). However, the use of neural networks / AI / ML in predictive beam management (e.g., in the time domain and / or spatial domain) can reduce power usage, reduce overhead, and improve performance related to accuracy, latency, and / or throughput.

[0114] Neural network / AI / ML approaches for predictive beam management in general and mmWave blockage prediction in particular can be categorized as follows:

[0115] Category I - Use sensory data such as cameras, radar, lidar, etc. as input to AI / ML processes;

[0116] Category II - using out-of-band measurements (e.g., FR1 band measurements) as input to the AI / ML process; and

[0117] Category III - uses in-band (e.g., mmWave) measurements and relies on “wireless signatures” (also referred to herein as “pre-blocking signatures”) as input to the neural network / AI / ML process.

[0118] The foregoing categories are presented as examples and not limitations. Additional categories or combinations of categories are within the scope of the present disclosure.

[0119] An example of Category III described above may involve performing beam scanning using the beam blocking prediction-reference signal described above (e.g., in combination with Figure 4 5). Beam scanning may be performed at the transmitter / receiver with some periodicity and may also involve reliance on changes in RSRP measurements across beams and at a particular time (e.g., duration, period) of the beam blocking prediction-reference signal. Collecting RSRP measurements across beams and over time may be used to create a spectrogram that may be applied as input to, for example, a neural network / AI / ML system. The neural network / AI / ML system may be similar to, for example, a combination of Figure 6 The neural network / AI / ML system 600 shown and described. The neural network / AI / ML system may be based on a convolutional neural network (CNN) or a recurrent neural network (RNN) or both.

[0120] Using RSRP measurement data (in spectrogram form or another form) as input, a neural network / AI / ML system may be trained to perform any of the following actions: 1) predict a blocking event (e.g., the occurrence of a blocking event); 2) predict a blocking instance (e.g., the time of occurrence of a blocking event); 3) predict a blocking severity (e.g., the duration of a blocking event); and / or predict a bearing (e.g., direction or position and / or direction of movement) of an object corresponding to (or predicted to correspond to) a predicted beam blocking event. For example, a bearing of approximately 270 degrees and approaching may indicate that an object is coming approximately from the west (if the bearing is given relative to the Earth's magnetic field) or from the left (if the bearing is given relative to the UE and the UE's forward direction is aligned with zero degrees) and indicates that the object is coming toward the UE (such as in an example where a bus is crossing a traffic intersection from left to right and perpendicular to a vehicle / UE waiting to cross the traffic intersection).

[0121] Figure 7 7 is a spectrum diagram 700 depicting beam index values ​​(eg, beam identifiers) versus time (in samples) as a function of reference signal received power (RSRP) according to one example provided in the present disclosure. Figure 7 Additionally depicted is the application of the spectrogram 700 to a neural network / AI / ML system 702 and a predicted output 704 of the neural network / AI / ML system 702 regarding blocking in accordance with aspects of the present disclosure. Figure 7In the example of , beam index values ​​from 0 to 70 with a step size of 10 are depicted on the vertical axis. A decreasing beam index value indicates an azimuth direction moving counterclockwise (i.e., left) relative to an undefined reference beam index value, while an increasing beam index value indicates an azimuth direction moving clockwise (i.e., right) relative to an undefined reference beam index value. Time (in samples) is depicted on the horizontal axis. A key 706 is provided to correlate the pattern of data in the spectrogram 700 with a value of reference signal received power (RSRP). The neural network / AI / ML system 702 may be similar to the one incorporating Figure 6 Neural network / AI / ML system 600 as shown and described.

[0122] exist Figure 7 , for all times presented (e.g., 0 to 45 samples) except during beam blocking event 708, RSRP is highest for beam index values ​​between about 29 and 31. Outside of these beam index values, i.e., in the right and left directions of the transmit antenna beams associated with beam index values ​​between about 29 and 31, RSRP varies between about 0.25 and 0.1 (e.g., milliwatts, dBm, another power metric, or a value proportional to a power metric). For each of the antenna beams associated with beam index values ​​between about 0-12 and 34-70, the variation in power level from about 0 samples to 10 samples remains approximately constant.

[0123] For each of the antenna beams associated with beam index values ​​between about 0-10 and 32-70, the change in power level over time from about 10 samples to 19 samples remains approximately constant. However, within a period from about 10 to 19 samples, the RSRP values ​​among antenna beam index values ​​11-28 are perturbed; for each beam index value, the RSRP values ​​are no longer constant or substantially constant. Instead, for each beam index value within a period from about 10 to 19 samples, the RSRP values ​​associated with each of the beam index values ​​11-28 range from about 0.4 to 0.1.

[0124] From about 19 samples to about 36 samples, the RSRP associated with all beam index values ​​0-70 drops to less than or equal to 0.05. The period between about 19-36 samples may be referred to as a beam blocking event 708. In this example, a man-made or natural object may have interrupted the line of sight of the transmit and receive beam pair link utilized between the UE and the network node. In some examples, the beam blocking event 708 may be caused by, for example, a bus, truck, car, motorcycle, bicycle, pedestrian, or an object carried by a pedestrian, or even the user's own body becoming between the UE and the network node. In some examples, the beam blocking event 708 may be caused by, for example, a trajectory or geographic path taken by the UE, where the trajectory or geographic path causes a man-made or natural object (such as a building, wall, basement, tunnel, mountain, canyon, etc.) to become between the UE and the network node. The foregoing enumeration is exemplary and not limiting.

[0125] In each example, regardless of what caused the beam blocking event 708, the blocking was temporary in nature. That is, the beam blocking event 708 lasted for a finite number of samples in the time domain. Evidence of the temporary nature of the illustrated blocking 798 event can be found in the spectrogram 700 during a period between about 36 and 46 samples and across all beam index values. During this period, and across all beam index values, the RSRP values ​​return to or substantially return to the values ​​and distribution observed between 0 and about 9 samples.

[0126] Note that beam blocking event 708 is preceded by a perturbation in the measured RSRP values ​​associated with antenna beam index values ​​11-28 over a period of from about 10 to 19 samples. According to aspects herein, these perturbations may be referred to as "radio signatures" (also referred to herein as "pre-blocking signatures" 710). Note also that the pre-blocking signature 710 associated with the cause of a given beam blocking event 708 may be similar to other pre-blocking signatures (not shown) of other blocking events (not shown) having similar causes. For example, regardless of the geographic location on the earth or the relative orientation of the UE to the base station (e.g., north, south, east, west), a truck (e.g., a tractor-trailer combination with a standard-sized cargo container) approaching a UE from the left (e.g., the vehicle itself or an occupant in the vehicle with the UE) and passing in front of the UE, thereby blocking the line of sight between the UE and the associated base station may have a relatively similar pre-blocking characteristic mark 710 as a comparable truck (e.g., a comparable tractor-trailer combination with a comparable standard-sized cargo container) passing in front of a comparable UE at some other geographic location and similarly blocking the line of sight between the comparable UE and the UE's associated comparable base station.

[0127] Certain criteria for prediction of beam failure can be established according to some aspects described herein. For example, existing beam failure detection events (such as making the connection mode (such as combined with Figure 4 404) of the connection mode shown and described above) starts a beam failure recovery procedure (such as in conjunction with Figure 4 The beam failure recovery procedure 406 process shown and described) may be a reactive procedure that may be defined in the specification and followed by the manufacturer of the UE. In one example, the specification may specify that the UE will compare the PDCCH Block Error Rate (BLER) for the Beam Failure Detection Reference Signal (BFD-RS) to a first threshold (to detect beam failure instances) and compare the number of beam failure instances to a second threshold over a given period. BLER is a physical layer error estimation technique that involves obtaining a ratio of the number of transport blocks received in error to the total number of blocks sent over a certain number of frames.

[0128] However, to proactively predict beam failure events, the process described above and defined in the specification may not be sufficient. In general, thresholding criteria tests / evaluations (such as the aforementioned BLER BFD-RS process) may not be sufficient to predict blocking events, such as Figure 7 A beam blocking event 708 is illustrated.

[0129] In contrast, as described herein, a base station may configure a set of reference signals, similar to but different from the existing BFD-RS. The set of reference signals may be referred to herein as beam blocking prediction-reference signals. According to some aspects, a base station may use beam blocking prediction-reference signals for beam scanning. The beam blocking prediction-reference signal may be implemented by the base station through CSI-RS configuration. In one example, the beam blocking prediction-reference signal may be implemented through CSI-RS resource configuration, which may implement scanning on multiple beams. In another example, a CSI-RS with repetitions (for beam blocking prediction-reference signals) may be configured so that the UE may use different receive beams for measurements and create a spectrogram based on those measurements over time. For transmit beam scanning or receive beam scanning, a wireless communication device may obtain a pattern (e.g., a spectrogram) created over time, which may be used for blocking prediction. As described above, an impending blocking event (such as beam blocking event 708) may produce changes (perturbations) in beam blocking prediction-reference signal RSRP measurements across beams and across time. Such changes may be identified as wireless signatures or pre-blocking signatures, such as pre-blocking signature 710. However, such pre-blocking signatures may be difficult to detect and decipher. According to various aspects described herein, for example, a neural network / AI / ML system (e.g., as combined with Figure 6The neural network / AI / ML system 600 shown and described may be trained to learn an occlusion prediction task based on identification of pre-occlusion feature markers.

[0130] Fig. 8A and Figure 8B A spectrogram 800 depicting beam index versus time as a function of reference signal received power and a graph 802 indicating beam blocking or the absence of beam blocking (ie, no blocking) versus time, respectively, according to one example provided in the present disclosure. Fig. 8A and Figure 8B The time scale of Fig. 8A and Figure 8B The time axes correspond to or overlap with each other).

[0131] Fig. 8A The spectrum 800 may be similar to that of Figure 7 Therefore, for the sake of brevity, a detailed description of the spectrum 800 will be omitted. However, in general, the spectrum 800 includes a beam blocking event 808 (similar to the one shown in conjunction with Figure 7 The beam blocking event 708 shown and described above and the pre-blocking signature 810 (similar to that shown in conjunction with Figure 7 In FIG. 8 , perturbations in the RSRP measurements of the beam blocking prediction-reference signal across beams and across time (eg, pre-blocking signatures 810 ) are surrounded by boxes to highlight and easily identify these perturbations.

[0132] Combination Fig. 8A and Figure 8B A pair of time windows are introduced. The first time window may be referred to as an observation window 804. The observation window 804 has a time window denoted as T o The observation window 804 may represent a duration of T o , during which the UE's neural network / AI / ML circuitry may monitor a pre-blocking signature (such as pre-blocking signature 810). Monitoring the pre-blocking signature may include monitoring across beams and across time (e.g., across a duration T o ) of the corresponding beam blocking prediction-reference signal changes. The UE may monitor the RSRP of the corresponding beam blocking prediction-reference signal across beams and across time during the observation window 804. For example, the UE may provide this data, for example, as training data 610, to the UE in conjunction with Figure 6 The model shown and described trains 604 circuits / functions.

[0133] The second time window may be referred to as a prediction window 806. The prediction window 806 has a value denoted as T p The prediction window 806 may represent a duration (eg, a period) T pDuring this time, the AI / ML module can perform predictions related to beam failure events. Figure 8B As depicted in the example of , a state change from unobstructed to blocked may occur during prediction window 806 .

[0134] According to some aspects of the present invention, the base station may configure a statistical metric as a criterion for blocking event prediction. The UE may perform measurements during the observation window 804. The UE may use, for example, the statistical metric to predict information related to blocking events that may occur during the prediction window 806. Statistical properties (e.g., mean, standard deviation, variance, etc.) of RSRP measurements of corresponding beam blocking prediction-reference signals across beams and across time may assist in locating / detecting / identifying pre-blocking signatures, such as pre-blocking signatures 810. As an example, the criterion set forth by the base station may be in the form of a variance (e.g., statistical property) of RSRP measurements of corresponding beam blocking prediction-reference signals across beams and across time during the observation window. According to some aspects, the length of the observation window may be configured by the base station and / or suggested by the UE.

[0135] Fig.9A 900 is a first spectrum diagram of the average RSRP of a beam blocking prediction-reference signal over beams and over time according to one example provided in the present disclosure. Fig. 9B yes Fig.9A Beam blocking prediction - RSRP of reference signal is Fig.9A A second spectrum 902 of the standard deviation over the same beam and at the same time is depicted in the example of FIG. Fig.9A and Fig. 9B In both, beam index values ​​are presented on the vertical axis and time (in samples) is presented on the horizontal axis. The time of a blocking event (ie the start of the occurrence of a blocking event) is zero. Time is presented as a negative value to indicate the time before the blocking event. Fig.9A and Fig. 9B The vertical and horizontal axes of coincide with each other; that is, Fig.9A and Fig. 9B The same set of base index values ​​(0-35) over the same time (negative 36-0) are depicted.

[0136] Fig.9A The mean and Fig. 9B The standard deviation values ​​shown are considered statistical measures in this article. In general, and as shown from Fig.9A and Fig. 9B As observed in the example, Fig.9A The variance of the mean in the first region 906 is less than Fig. 9B That is, the disturbance of the mean in the first region 906 is less than the disturbance of the standard deviation value in the corresponding region 908. Fig.9A and Fig. 9B In both, the variance (of the mean and standard deviation values) of the reference signal received power increases as time grows closer to the blocking event; that is, as time grows closer to 0 (the start of the blocking event). Note that the mean is the average of a group of values, the standard deviation is the magnitude of a group of numbers from the mean, and the variance measures how much each point differs from the mean on average. While the standard deviation is the square root of the variance, the variance is the average of all data points within the group.

[0137] Fig.10 1 is an aerial view of a traffic intersection 1000 according to some aspects of the present disclosure. Base station 1002 is depicted in the distance northwestward of vehicle / UE 1004. Vehicle / UE 1004 is stopped at traffic intersection 1000. For ease of explanation and illustrative purposes, vehicle / UE 1004 itself may be considered a UE, or a wireless communication device held by an occupant within the vehicle may be a UE. Once traffic is no longer expected to cross traffic intersection 1000, vehicle / UE 1004 may intend to move forward (as indicated by the dashed arrow in front of vehicle / UE 1004). Base station 1002 and vehicle / UE 1004 are in connected mode. Directional transmit antenna beam 1006g serves vehicle / UE 1004. The corresponding receive beam from vehicle / UE 1004 is not illustrated to avoid cluttering the drawing. The directional transmit antenna beam 1006g is one of the multiple directional transmit antenna beams 1006a-1006j. The multiple directional antenna beams 1006a-1006j may operate in the mmWave frequency band. Therefore, each of the multiple directional transmit antenna beams 1006a-1006j may be blocked by the base station 1002 and the UE (such as Fig.10 The impact of objects (natural or man-made) on the line of sight between the vehicle / UE 1004).

[0138] Fig.10 Also depicted is a tractor-trailer towing a standard-sized cargo container (collectively referred to as tractor-trailer 1008). Tractor-trailer 1008 is advancing through the intersection, as depicted by the solid arrow illustrated in front of tractor-trailer 1008. Fig.10 At the moment shown, the tractor-trailer 1008 does not block the line of sight between the base station 1002 and the vehicle / UE 1004. Therefore, a two-way radio link between the base station 1002 and the vehicle / UE 1004 is maintained via the directional transmit antenna beam 1006g (and a corresponding receive antenna beam (not shown) of the vehicle / UE 1004).

[0139] The base station 1002 may cause beam scanning to occur. The beam scanning may transmit a plurality of beam blocking prediction-reference signals via a corresponding one of the plurality of directional transmit antenna beams 1006a-1006j, each beam blocking prediction-reference signal being associated with a corresponding beam index value (eg, beam identifier).

[0140] The vehicle / UE 1004 may measure and collect RSRP across beams and across time for the beam blocking prediction-reference signal. The vehicle / UE 1004 may obtain (e.g., generate, derive, format, prepare) a spectrum map (e.g., similar to as described in conjunction with Figure 7 , Fig. 8A , Fig.9A and / or Fig. 9B Spectra 700, 800, 900 and / or 902 shown and described above). Similar to Figure 7 , Fig. 8A , Fig.9A and / or Fig. 9B , Figure 7 and Fig. 8A Beam failure prediction in - RSRP power of reference beam, Fig.9A The mean RSRP and / or Fig. 9B The standard deviation of the RSRP in may remain constant or substantially constant in the time samples before the tractor-trailer 1008 advances to the traffic intersection 1000. For example, Figure 7 and Fig. 8A The beam index 30 may correspond to Fig.10 The directional antenna beam 1006g. Therefore, Figure 7 and Fig. 8A The RSRP for beam indices 29-31 in may be higher than all other RSRPs associated with all other directional antenna beams.

[0141] However, and as Figure 7 , Fig. 8A , Fig.9A and / or Fig. 9B exemplified, Figure 7 A and Fig. 8A Beam blocking prediction across beams and across time in - the power of the RSRP of the reference signal and Fig.9A The mean RSRP and / or Fig. 9B The standard deviation of RSRP in becomes increasingly perturbed during the ten time samples before the body of the tractor-trailer 1008 completely enters the intersection 1000 and blocks the line of sight between the base station 1002 and the vehicle / UE 1004. Figure 7 Beam blocking event 708, Fig. 8A The 808 and Fig.9A and Fig. 9BThe disturbance in the ten time samples before the start of the blocking event at time instance zero in ) may represent the tractor-trailer 1008. Figure 7 The pre-blocking characteristic mark 710 and Fig. 8A 810 Fig.9A 904 and Fig. 9B 906. Of course, the use of ten time samples is only an example, i.e., the pre-blocking signature may start more or less than ten time samples before a given blocking event. By identifying the pre-blocking signature, a UE that measures and collects RSRP values ​​of beam blocking prediction-reference signals sent from any given base station in a beam scan may be able to predict the occurrence of similar blocking events, the start time of similar blocking events, the severity of similar blocking events (e.g., in terms of duration), and the position of an object corresponding to a similar beam blocking event (in terms of time). Fig.10 In the example of FIG. 1004 , the blocking event travels from left to right across in front of the vehicle / UE 1004 ).

[0142] Fig.11 1 is an aerial view of a portion of a four-lane divided highway 1100 in accordance with some aspects of the present disclosure. A base station 1102 is depicted in the distance northwestward of a vehicle / UE 1104. The vehicle / UE 1104 is traveling in a northbound direction in the right lane 1112 of the northbound portion of the four-lane divided highway 1100. For ease of explanation and for illustrative purposes, the vehicle / UE 1104 itself may be considered a UE, or a wireless communication device held by an occupant within the vehicle may be a UE. The speed of the vehicle / UE 1104 is represented by the length of the solid arrow in front of the vehicle / UE 1104. The base station 1102 and the vehicle / UE 1104 are in a connected mode. A directional transmit antenna beam 1106g serves the vehicle / UE 1104. The corresponding receive beam from the vehicle / UE 1104 is not illustrated to avoid cluttering the drawing. The directional transmit antenna beam 1106g is one of the multiple directional transmit antenna beams 1106a-1106j. The multiple directional transmit antenna beams 1106a-1106j may operate in the mmWave frequency band. Therefore, each of the multiple directional transmit antenna beams 1106a-1106j may be blocked by the base station 1102 and the UE (such as Fig.11 The impact of objects (natural or man-made) in the line of sight between the vehicle / UE1104).

[0143] Fig.11Also depicted is a tractor-trailer towing a standard-sized cargo container (collectively referred to as tractor-trailer 1108). Tractor-trailer 1108 is also traveling in the northbound direction but in left lane 1115 of the northbound portion of four-lane divided highway 1100. The speed of tractor-trailer 1008 is represented by the length of the arrow in front of tractor-trailer 1008. Fig.11 At the time shown, tractor-trailer 1108 is level with vehicle / UE 1104 but is accelerating to pass vehicle / UE 1104 (as shown by the representative difference between the lengths (e.g., magnitudes of respective speeds) of respective arrows preceding tractor-trailer 1108 and vehicle / UE 1104). Fig.11 At the moment shown, the body of the tractor-trailer 1108 does not block the line of sight between the base station 1102 and the vehicle / UE 1104. Therefore, a two-way radio link between the base station 1102 and the vehicle / UE 1104 is maintained via the directional transmit antenna beam 1106g (and a corresponding receive antenna beam (not shown) of the vehicle / UE 1104).

[0144] The base station 1102 may cause beam scanning to occur. The beam scanning may transmit a plurality of beam blocking prediction-reference signals via a corresponding one of the plurality of directional transmit antenna beams 1106a-1006j, each beam blocking prediction-reference signal being associated with a corresponding beam index value (eg, beam identifier).

[0145] The vehicle / UE 1104 may measure and collect RSRP of the beam blocking prediction-reference signal over time and over beams. The vehicle / UE 1104 may obtain (e.g., generate, derive, format, prepare) a spectrum diagram similar to that described in conjunction with Figure 7 and Fig. 8A Spectrum 700 and / or spectrum 800 as shown and described. Similar to Figure 7 and Fig. 8A , beam failure prediction - the RSRP of the reference beam may remain constant or substantially constant in the time samples before the tractor trailer 1108 overtakes the vehicle / UE 1104. For example, Figure 7 and Fig. 8A The beam index 30 may correspond to Fig.11 Thus, the RSRP for beam indexes 29-31 may be higher than all other RSRPs associated with all other directional antenna beams.

[0146] However, and as Figure 7 and Fig. 8A The examples are shown (and are used for illustrative and non-limiting purposes) Figure 7 and Fig. 8A), the cross-beam and cross-time RSRP of the beam blocking prediction-reference signal becomes increasingly perturbed during the ten time samples before the body of the tractor-trailer 1108 is beside and overtaking the vehicle / UE 1004, such that the body of the tractor-trailer 1108 blocks the line of sight between the base station 1102 and the vehicle / UE 1104. During a blocking event (e.g., Figure 7 The beam blocking event 708 and Fig. 8A The disturbance in the ten time samples before the start of the tractor-trailer 1108 may represent the Figure 7 The blocking pre-characteristic mark 710 and Fig. 8A As mentioned above, the use of ten time samples is only an example. The pre-blocking feature marker may start more or less than ten time samples before a given blocking event.

[0147] By identifying the pre-blocking signature, a UE that measures and collects RSRP values ​​of beam blocking prediction-reference signals sent from any given base station in a beam scan may be able to predict the occurrence of a similar blocking event, the start time of a similar blocking event, the severity of the similar blocking event (e.g., in terms of duration), and the position of an object corresponding to the similar beam blocking event (e.g., in terms of time). Fig.11 In the example of FIG. 1 , the blocking event travels from the rear to the front of the vehicle / UE 1104 and along the left half of the vehicle / UE).

[0148] According to one aspect, determining and reporting a potential (future) blocking event may include configuring the UE to compare a statistical metric (e.g., variance) configured by the base station with a threshold value. If the statistical metric is greater than the threshold value for more than a given number of times (e.g., for more than a given number of time samples), the UE may report information related to the predicted blocking event.

[0149] Based on whether the UE observes and reports a beam blocking event (eg, after an actual beam blocking event corresponding to a predicted blocking event is achieved), the base station may adjust the value of the statistical metric.

[0150] For example, the statistical metric, the duration of the observation window, the number of consecutive times (number of time samples) that the configured criteria are not met, etc. can be configured through RRC messaging. In one example, the criteria stated by the base station can be in the form of PDCCH-BLER variation across time across beam blocking prediction-reference signal beams.

[0151] According to another aspect, the base station may configure the UE with a beam blocking prediction-reference signal and may also configure a neural network (e.g., similar to Figure 6The format of the output of the neural network / AI / ML system 600) according to this aspect may be included in the specific implementation of the UE. For example, the UE may mark the output of the neural network following existing procedures for beam failure detection and recovery. In some examples, for example, this aspect may be implemented as a signal processing aspect implemented at the UE instead of the neural network.

[0152] According to another aspect, a base station may share a blocking prediction neural network with multiple UEs. Each UE may monitor a beam blocking prediction-reference signal and label the output of the neural network as instructed by the base station. The blocking prediction neural network may be trained in a federated learning environment. In other words, the neural network may be trained using data from multiple UEs (i.e., from a federation of UEs). According to this aspect, a UE may obtain a series of spectrograms along with their corresponding labels.

[0153] According to aspects related to a federated learning context, a blocking prediction neural network may be shared with a set of UEs that experience similar monitored measurements. A federated learning context may benefit from such an organization because different sets of UEs (i.e., different member UEs of a federation) may experience a greater number of blocking events than a single UE or a single set of UEs. In addition, multiple UEs and / or multiple sets of UEs may have a certain amount of realized blocking events (e.g., actual blocking events) that may be used to train the neural network.

[0154] For example, in the training phase, the base station may share a blocking prediction neural network with a group of similar UEs. The base station may inform the group of similar UEs based on the use of a joint learning process when convergence is reached. At convergence, the neural network may be considered a trained neural network. The group of similar UEs may then use the trained neural network in the inference phase. In other words, the base station may configure the UE with a neural network instead of defining a criterion (e.g., a statistical criterion), and the output of the neural network may provide a blocking prediction task, as opposed to an explicit metric or criterion.

[0155] According to another aspect, in all aspects described above, information about a blocking event (e.g., information related to a blocking event) may be determined on the UE side, and the result of the determination (e.g., a prediction of a blocking event) may be reported to the base station. An alternative approach may be that the base station may configure the UE to report statistics of beam measurements (across beams and across time) and feature vectors (which may be generated by a machine language module).

[0156] Fig.12 1 is a block diagram illustrating an example of a hardware implementation of a wireless communication device 1200 employing a processing system 1202 according to some aspects of the present disclosure. For example, the wireless communication device 1200 may be such as Figure 1 , Figure 2 , Figure 5A , Figure 5B , Figure 5C , Fig.10 and / or Fig.11 A scheduled entity (e.g., UE) illustrated by any one or more of .

[0157] According to various aspects of the present disclosure, an element or any portion of an element or any combination of elements may be implemented with a processing system 1202 including one or more processors, such as a processor 1204. Examples of processor 1204 include a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a state machine, gated logic, discrete hardware circuits, and other suitable hardware configured to perform various functionalities described throughout the present disclosure. In various examples, the wireless communication device 1200 may be configured to perform any one or more of the functions described herein. That is, the processor 1204 as utilized in the wireless communication device 1200 may be used to implement, for example, Figure 4 and / or Figure 6 Any one or more of the methods or processes shown and described in any one or more of the embodiments.

[0158] In some examples, processor 1204 may be implemented via a baseband or modem chip, and in other implementations, processor 1204 may include multiple devices distinct and other than a baseband or modem chip (e.g., in such scenarios that may work together to implement the examples discussed herein). And as mentioned above, various hardware arrangements and components outside of a baseband modem processor may be used in implementations, including RF chains, power amplifiers, modulators, buffers, interleavers, adders / summers, etc.

[0159] The processor 1204 may be configured to receive the first signal and send the second signal. In some aspects, the reference to the processor being configured to receive the first signal may refer to the processor being configured to obtain first information corresponding to the first signal. For example, the first information may be demodulated information, decoded information, or any information corresponding to the first signal. As another example, the first information may refer to information output from a receiver, transceiver, RF circuit, etc. residing between the processor and the antenna. In some aspects, the reference to the processor being configured to send the second signal may refer to the processor being configured to cause the second signal to be sent. For example, in order to cause the second signal to be sent, the processor may be configured to cause a transmitter, a transceiver, an RF circuit, etc. to send the second signal.

[0160] The processing system 1202 may be implemented with a bus architecture, represented generally by bus 1206. The bus 1206 may include any number of interconnecting buses and bridges, depending on the specific application of the processing system 1202 and the overall design constraints. The bus 1206 communicatively couples together various circuits including one or more processors (represented generally by processor 1204), memory 1208, and computer-readable media (represented generally by computer-readable media 1210). The bus 1206 may also link various other circuits, such as timing sources, peripherals, voltage regulators, and power management circuits, which are well known in the art and, therefore, will not be described further.

[0161] The bus interface 1212 provides an interface between the bus 1206 and the transceiver 1214. The transceiver 1214 can be a wireless transceiver. The transceiver 1214 can provide a component for communicating with various other devices through a transmission medium (e.g., an air interface). The transceiver 1214 can also be coupled to one or more antenna arrays (hereinafter antenna array 1216). The bus interface 1212 also provides an interface between the bus 1206 and a user interface 1218 (e.g., a keypad, a display, a touch screen, a speaker, a microphone, control features, etc.). Of course, such a user interface 1218 is optional and can be omitted in some examples. In addition, the bus interface 1212 also provides an interface between the bus 1206 and the power supply 1220 of the wireless communication device 1200.

[0162] The processor 1204 is responsible for managing the bus 1206 and general processing, including executing software stored on the computer-readable medium 1210. The software, when executed by the processor 1204, causes the processing system 1202 to perform the various functions described below for any particular device. The computer-readable medium 1210 and the memory 1208 may also be used to store data that is manipulated by the processor 1204 when executing the software.

[0163] Software should be construed broadly to mean instructions, instruction sets, codes, code segments, program code, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. The software may reside on a computer readable medium 1210. The software, when executed by the processor 1204, may cause the processing system 1202 to perform the various processes and functions described herein for any particular apparatus.

[0164] Computer readable medium 1210 may be a non-transitory computer readable medium and may be referred to as a computer readable storage medium or a non-transitory computer readable medium. Non-transitory computer readable medium may store computer executable code (e.g., processor executable code). Computer executable code may include code for causing a computer (e.g., a processor) to implement one or more of the functions described herein. Non-transitory computer readable media include, for example, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips), optical disks (e.g., compact disks (CDs) or digital versatile disks (DVDs)), smart cards, flash memory devices (e.g., cards, sticks or key drives), random access memory (RAM), read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), registers, removable disks, and any other suitable medium for storing software and / or instructions that can be accessed and read by a computer. Computer readable medium 1210 may reside in processing system 1202, outside processing system 1202, or distributed across multiple entities including processing system 1202. Computer readable medium 1210 may be embodied in a computer program product or article of manufacture. By way of example, a computer program product or article of manufacture may include a computer readable medium in packaging materials. In some examples, computer readable medium 1210 may be part of memory 1208. Those skilled in the art will recognize how to best implement the described functionality presented throughout this disclosure, depending on the specific application and the overall design constraints imposed on the overall system.

[0165] In some aspects of the present disclosure, processor 1204 may include communication and processing circuitry 1241 that is configured for various functions, including, for example, communicating with other wireless communication devices (e.g., a scheduling entity, a scheduled entity), a network core (e.g., a 5G core network), or any other entity (such as, for example, a local infrastructure, or an entity that communicates with the wireless communication device 1200 via the Internet (such as a network provider)). In some examples, communication and processing circuitry 1241 may include one or more hardware components that provide a physical structure that performs processes related to wireless communication (e.g., signal reception and / or signal transmission) and signal processing (e.g., processing received signals and / or processing signals for transmission). For example, communication and processing circuitry 1241 may include one or more transmit / receive chains.

[0166] In some implementations where communication involves receiving information, the communication and processing circuitry 1241 may obtain or identify information from a component of the wireless communication device 1200 (e.g., from a transceiver 1214 that receives information via radio frequency signaling or some other type of signaling suitable for an applicable communication medium), process (e.g., decode) the information, and output the processed information. For example, the communication and processing circuitry 1241 may output the information to another component of the processor 1204, to the memory 1208, or to the bus interface 1212. In some examples, the communication and processing circuitry 1241 may receive one or more of a signal, a message, other information, or any combination thereof. In some examples, the communication and processing circuitry 1241 may receive information via one or more channels. In some examples, the communication and processing circuitry 1241 may include functionality for components for receiving. In some examples, the communication and processing circuitry 1241 may include functionality for components for processing, including components for demodulating, components for decoding, and the like.

[0167] In some implementations where communication involves transmitting (e.g., sending) information, the communication and processing circuitry 1241 may obtain or identify information (e.g., from another component of the processor 1204, the memory 1208, or the bus interface 1212), process (e.g., modulate, encode, etc.) the information, and output the processed information. For example, according to some aspects of the present disclosure, the communication and processing circuitry 1241 may obtain data stored in the memory 1208 and may process the obtained data.

[0168] In some examples, the communication and processing circuitry 1241 may obtain information and output the information to the transceiver 1214 (e.g., sending the information via radio frequency signaling or some other type of signaling suitable for the applicable communication medium). In some examples, the communication and processing circuitry 1241 may transmit one or more of a signal, a message, other information, or any combination thereof. In some examples, the communication and processing circuitry 1241 may transmit information via one or more channels. In some examples, the communication and processing circuitry 1241 may include functionality for components for transmitting (e.g., components for sending). In some examples, the communication and processing circuitry 1241 may include functionality for components for generating (including components for modulating, components for encoding, etc.). In some examples, the communication and processing circuitry 1241 may be configured to receive and process uplink traffic and uplink control messages (e.g., similar to) via the antenna array 1216 and the transceiver 1214. Figure 1 126 and uplink control 128) and processes and sends downlink traffic and downlink control messages (e.g., similar to Figure 1 downlink traffic 122 and downlink control 124).

[0169] The communication and processing circuitry 1241 may be further configured to execute communication and processing instructions 1251 (eg, software) stored on the computer-readable medium 1210 to implement one or more functions described herein.

[0170] In some aspects of the present disclosure, the processor 1204 may include a reference signal circuit 1242. The reference signal circuit 1242 may be configured for various functions, including, for example, receiving a plurality of reference signals, wherein each of the plurality of reference signals corresponds to a corresponding identifier in a plurality of identifiers. According to some aspects, the plurality of reference signals may include a beam blocking prediction-reference signal. As an example and not limitation and as described above, in some examples, the beam blocking prediction-reference signal may be different from a BFD-RS. The reference signal circuit 1242 may be configured to execute reference signal instructions 1252 (e.g., software) stored on the computer-readable medium 1210 to implement one or more functions described herein.

[0171] In some aspects of the present disclosure, the processor 1204 may include a beam blocking event prediction circuit 1243. The beam blocking event prediction circuit 1243 may be configured for various functions, including, for example, sending prediction information indicating a predicted beam blocking event, wherein the prediction information may be based on measurement information corresponding to a plurality of reference signals during a time period. According to some aspects, the beam blocking event prediction circuit 1243 may obtain measurement information during the time period. The time period may be referred to herein as an observation window, such as the observation window 804, as described in conjunction with Fig. 8A and Figure 8B In some examples, to obtain measurement information during the time period, processor 1204 may be configured to perform one or more measurements during the time period to generate measurement information. According to some aspects, the measurement information may include corresponding reference signal received power (RSRP) information for each corresponding reference signal in the plurality of reference signals.

[0172] According to some aspects, the beam blocking event prediction circuit 1243 can be configured for various additional functions, including, for example, receiving prediction configuration information, wherein the prediction configuration information can include information indicating at least one of the following: the length of the time period, a statistical metric used to predict the predicted beam blocking event, a threshold value that can be compared with the statistical metric, the predicted occurrence of the beam blocking event, the instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or the position of the object corresponding to the predicted beam blocking event. In some examples, the measurement information can be based on the prediction configuration information. In some examples, the prediction information can be based on the prediction configuration information. In some examples, the measurement information can include a plurality of reference signal received power measurements corresponding to a corresponding plurality of beam identification values ​​that vary over time, wherein the processor 1204 can be configured to compare the statistical metric associated with the plurality of reference signal received power measurements with the threshold value, and wherein, to send the prediction information, the processor 1204 can be configured to send the prediction information based on the comparison.

[0173] The beam blocking event prediction circuit 1243 may be configured to execute beam blocking event prediction instructions 1253 (eg, software) stored on the computer-readable medium 1210 to implement one or more functions described herein.

[0174] In some aspects of the present disclosure, the processor 1204 may include a neural network / artificial intelligence (AI) / machine learning (ML) circuit 1244. Some or all of the neural network / AI / ML circuit 1244 may be optional. The neural network / AI / ML circuit 1244 may be configured for various functions, including, for example, providing measurement information to a model and obtaining prediction information as an output from the model. In some examples, the neural network / AI / ML circuit 1244 may be configured to receive the model or information indicative of the model from a second network node. In such examples, the second network node may be a base station (e.g., a network access node, a scheduling entity, a gNB). According to some aspects, the model may include a neural network. According to some aspects, neural network training of the neural network may utilize a plurality of spectrograms from the first network node and / or at least one of the plurality of other network nodes. Each of the plurality of spectrograms may include a respective set of respective beam measurements for each respective reference signal associated with each respective beam identifier that varies over time. Of course, the respective set of respective beam measurements for each respective reference signal associated with each respective beam identifier that varies over time need not be provided in the form of a spectrogram. For example, the neural network may directly receive a corresponding set of corresponding beam measurements for each corresponding reference signal associated with each corresponding beam identifier that varies over time, rather than formatting the data into a spectrogram format. In some aspects, to provide the measurement information to the model, the neural network / AI / ML circuit 1244 may be configured to send the measurement information to a second network node. In this case, as in the previous example, the second network node may be a base station (e.g., a network access node, a scheduling entity, a gNB).

[0175] According to some aspects, the prediction information indicating the predicted beam blocking event may include at least one of: information indicating an instance of the predicted beam blocking event, information indicating the severity of the predicted beam blocking event, or information indicating the position of an object corresponding to the predicted beam blocking event. In some examples, the information indicating the instance of the predicted beam blocking event may correspond to a prediction of the start of the predicted beam blocking event in the time domain. In some examples, the information indicating the severity of the predicted beam blocking may correspond to the duration of the predicted beam blocking event. In some examples, the information indicating the position of the object corresponding to the predicted beam blocking event may include information indicating a motion relative to the first network node.

[0176] Neural network / AI / ML circuitry 1244 may be configured to execute neural network / AI / ML instructions 1254 (eg, software) stored on computer-readable medium 1210 to implement one or more functions described herein.

[0177] According to some aspects, the processor 1204 (e.g., via the communication and processing circuit 1241, the reference signal circuit 1242, the beam blocking event prediction circuit 1243, or any combination thereof) may be configured to receive prediction configuration information, wherein the prediction configuration information includes information indicating a format of the prediction information, and wherein the prediction information complies with the format. In some examples, the prediction information indicating the predicted beam blocking event may include information indicating when the predicted beam blocking event is predicted to occur. In some examples, the prediction information indicating the predicted beam blocking event may include information indicating the duration of the predicted beam blocking event. In some examples, the prediction information indicating the predicted beam blocking event may include information indicating a direction of motion relative to the first network node corresponding to the predicted beam blocking event.

[0178] Furthermore, in order to send the prediction information, the processor 1204 may be configured to send the prediction information based on at least one of: a predicted time when the beam blocking event is predicted to occur, a predicted duration of the predicted beam blocking event, or a predicted direction of movement relative to the first network node corresponding to the predicted beam blocking event.

[0179] Fig.13 1 is a flow chart illustrating an exemplary process 1300 (e.g., a method of wireless communication) at a wireless communication device (e.g., a scheduled entity, a user equipment (UE)) according to some aspects of the present disclosure. For example, process 1300 may occur in a wireless communication network (such as Figure 1 and / or Figure 2 As described below, some or all of the illustrated features may be omitted in certain implementations within the scope of the present disclosure, and some of the illustrated features may not be required in all implementations. In some examples, process 1300 may be performed in conjunction with Fig.12 The wireless communication device 1200 shown and described is performed. In some examples, the process 1300 can be performed by any suitable device or component for performing the functions or algorithms described herein.

[0180] At block 1302, a wireless communication device may receive a plurality of reference signals, each of which may correspond to a respective identifier of a plurality of identifiers. Fig.12 As shown and described, reference signal circuitry 1242 , in some examples in combination with transceiver 1214 and antenna array 1216 , may provide means for receiving a plurality of reference signals, each of the plurality of reference signals corresponding to a respective identifier of a plurality of identifiers.

[0181] As above combined Fig.12According to some aspects, the multiple reference signals may include one or more beam failure detection-reference signals (BFD-RS) of the first type, one or more BFD-RS of the second type, or a combination thereof. In some examples, the first type of BFD-RS may be a BFD-RS, and the second type of BFD-RS may be a beam blocking prediction-reference signal. An example of a beam blocking prediction-reference signal (e.g., a reference signal for the purpose of predicting a blocking event) may be a periodic CSI-RS resource configured by a gNB. The wireless communication device may measure the RSRP of these periodic CSI-RS resources and may use the RSRP variation of the periodic CSI-RS across beams and across time to predict an upcoming blocking event. One difference between BFD-RS and beam blocking prediction-reference signals may be that, in order for the wireless communication device to predict a blocking event, the wireless communication device may need to measure more beams (i.e., beams that transmit BFD-RS and / or beam blocking prediction-reference signals) than it may need to measure in conjunction with detecting a beam failure event. During beam blocking prediction, an increased number of beams may be utilized to collect spatiotemporal variations of RSRP that may be used together to predict a given blocking event, rather than utilizing a smaller number of beams to determine real-time blocking events (e.g., beam failures) that may require fewer BFD-RS beam measurements. In other words, beam blocking prediction may require configuring a greater number of reference signals (such as BFD-RS, beam blocking prediction-reference signals, or a combination thereof) for beam blocking prediction than the wireless communication device may use for beam failure detection. According to some aspects, the plurality of reference signals may include a plurality of beam blocking prediction-reference signals.

[0182] At block 1304, the wireless communication device may send prediction information indicating a predicted beam blocking event, wherein the prediction information may be based on measurement information corresponding to a plurality of reference signals during a time period. Fig.12 As shown and described, the beam blocking event prediction circuit 1243 in some examples in combination with the transceiver 1214 and the antenna array 1216 may provide components for sending prediction information indicating a predicted beam blocking event, wherein the prediction information may be based on measurement information corresponding to multiple reference signals during a time period.

[0183] As above combined Fig.12According to some aspects, the method may include receiving prediction configuration information, wherein the prediction configuration information may include information indicating at least one of the following: the length of the time period, a statistical metric used to predict a predicted beam blocking event, a threshold value compared with the statistical metric, the occurrence of a predicted beam blocking event, an instance of a predicted beam blocking event, the severity of a predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event. In some examples, the measurement information may be based on the prediction configuration information. In some examples, the prediction information may be based on the prediction configuration information. In some examples, the measurement information may include a plurality of reference signal received power measurements corresponding to a plurality of corresponding beam identification values ​​that vary over time. For example, the communication and processing circuit 1241 may provide a component for receiving prediction configuration information in combination with the transceiver 1214 and the antenna array 1216 in some examples, wherein the prediction configuration information may include information indicating at least one of the following: the length of the time period, a statistical metric used to predict a predicted beam blocking event, a threshold value compared with the statistical metric, the occurrence of a predicted beam blocking event, an instance of a predicted beam blocking event, the severity of a predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event. Further, the method may include comparing a statistical metric associated with a plurality of reference signal received power measurements with a threshold and sending prediction information based on the comparison. For example, the beam blocking event prediction circuitry in some examples in combination with the transceiver 1214 and the antenna array 1216 may provide a component for comparing a statistical metric associated with a plurality of reference signal received power measurements with a threshold and sending prediction information based on the comparison.

[0184] According to some aspects, the method may include providing measurement information to a model and obtaining prediction information as an output from the model. In some examples, the method may include receiving the model or information indicative of the model from a second network node. In such examples, the second network node may be a base station (e.g., a network access node, a scheduling entity, a gNB). According to some aspects, the model may include a neural network. According to some aspects, neural network training of the neural network may utilize multiple spectra from the first network node and / or at least one of the multiple other network nodes. Each of the multiple spectra may include a corresponding set of corresponding beam measurements for each corresponding reference signal associated with each corresponding beam identifier that varies over time. Of course, as described above, the corresponding set of corresponding beam measurements for each corresponding reference signal associated with each corresponding beam identifier that varies over time may be provided in a form other than a spectrogram. The method may include sending measurement information to the second network node. For example, in combination with Fig.12As shown and described, the neural network / AI / ML circuit 1244 may provide components for providing measurement information to a model and obtaining prediction information as output from the model, and components for receiving the model or information indicative of the model from a second network node.

[0185] Fig.14 1 is a block diagram illustrating an example of a hardware implementation of a network access node 1400 (e.g., a base station, a scheduling entity, a gNB, etc.) using a processing system 1402 according to some aspects of the present disclosure. The network access node 1400 can be, for example, any base station, a scheduled entity, a gNB, etc., such as Figure 1 , Figure 2 Figure 5 Fig.10 and / or Fig.11 According to various aspects of the present disclosure, an element or any portion of an element or any combination of elements may be implemented using a processing system 1402 including one or more processors (such as processor 1404). The processing system 1402 may be combined with Fig.12 The processing system 1202 illustrated and described is substantially the same, and includes a bus interface 1412, a bus 1406, a memory 1408, a processor 1404, a communication and processing circuit 1441, and a computer-readable medium 1006. In addition, the scheduled entity 1004 may include a user interface 1012, a transceiver 1414, an antenna array 1416, and a power supply 1420, which are substantially similar to those described above in conjunction with Fig.12 Therefore, for the sake of brevity, their description will not be repeated.

[0186] In some aspects of the present disclosure, the processor 1404 may include a reference signal circuit 1442. The reference signal circuit 1442 may be configured for various functions, including, for example, sending a plurality of reference signals, each of which may correspond to a respective identifier of a plurality of identifiers. The reference signal circuit 1242 or the communication and processing circuit 1241 may be configured for other functions, including, for example, receiving measurement information corresponding to the plurality of reference signals during a time period. The reference signal circuit 1442 may be configured to execute reference signal instructions 1452 (e.g., software) stored on the computer-readable medium 1410 to implement one or more functions described herein.

[0187] In some aspects of the disclosure, the processor 1404 may include a beam blocking event prediction circuit 1443. The beam blocking event prediction circuit 1443 may be configured for various functions, including, for example, sending prediction information indicating a predicted beam blocking event, wherein the prediction information may be based on measurement information. According to other aspects, the beam blocking event prediction circuit 1443 may additionally or alternatively be configured to send prediction configuration information, wherein the prediction configuration information may include information indicating at least one of the following: a length of a time period, a statistical measure used to predict a predicted beam blocking event, a threshold value to compare with the statistical measure, an occurrence of a predicted beam blocking event, an instance of a predicted beam blocking event, a severity of a predicted beam blocking event, or an orientation of an object corresponding to a predicted beam blocking event. The beam blocking event prediction circuit 1443 may be configured to execute beam blocking event prediction instructions 1453 (e.g., software) stored on the computer-readable medium 1410 to implement one or more functions described herein.

[0188] In some aspects of the present disclosure, processor 1404 may include neural network / AI / ML circuitry 1444. In some examples, neural network / AI / ML circuitry 1444 may be optional. Neural network / AI / ML circuitry 1444 may be configured for various functions, including, for example, sending a model or information indicative of the model to a first network node. In some aspects, the model includes a neural network. Neural network / AI / ML circuitry 1444 may be configured to execute neural network / AI / ML instructions 1454 (e.g., software) stored on computer-readable medium 1410 to implement one or more functions described herein.

[0189] Fig.15 1 is a flow chart illustrating an exemplary process 1500 (e.g., a method of wireless communication) at a network access node (e.g., a base station, a scheduling entity) according to some aspects of the present disclosure. For example, process 1500 may occur in a wireless communication network (such as Figure 1 and / or Figure 2 As described below, some or all of the illustrated features may be omitted in certain implementations within the scope of the present disclosure, and some of the illustrated features may not be required in all implementations. In some examples, process 1500 may be performed in conjunction with Fig.14 The process 1500 is shown and described as being performed by the network access node 1400. In some examples, the process 1500 may be performed by any suitable device or component for performing the functions or algorithms described herein.

[0190] At block 1502, a network access node may transmit a plurality of reference signals, wherein each reference signal in the plurality of reference signals corresponds to a respective identifier in a plurality of identifiers. Fig.14As shown and described, reference signal circuitry 1442 in some examples, in combination with transceiver 1414 and antenna array 1416 , may provide means for transmitting a plurality of reference signals, wherein each of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers.

[0191] At block 1504, the network access node may receive measurement information corresponding to a plurality of reference signals during a time period. Fig.14 As shown and described, reference signal circuit 1442 in some examples, in combination with transceiver 1414 and antenna array 1416 , may provide means for receiving measurement information corresponding to multiple reference signals during a time period.

[0192] At block 1506, the network access node may send prediction information indicating a predicted beam blocking event, wherein the prediction information may be based on the measurement information. Fig.14 As shown and described, the beam blocking event prediction circuit 1443 in some examples in combination with the transceiver 1414 and the antenna array 1416 may provide components for sending prediction information indicative of a predicted beam blocking event, where the prediction information may be based on measurement information.

[0193] According to some aspects, the network access node can be configured to send the model or information indicative of the model to the second network node. In some examples, the model includes a neural network. For example, all of the Fig.14 As shown and described, neural network / AI / ML circuit 1444, in some examples, in combination with transceiver 1414 and antenna array 1416, may provide means for sending the model or information indicative of the model to a second network node. According to some examples, the second network node may be a user equipment. In some examples, the second network node may be a UE.

[0194] Of course, in the above example, combined with Fig.12 The processor 1204 shown and described in conjunction with Fig.14 The circuits included in the processor 1404 shown and described are provided only as examples. Other components for performing the processes or functions described may be included in various aspects of the present disclosure, including but not limited to storage on a computer-readable medium such as Fig.12 Computer readable medium 1210 and / or Fig.14 Computer readable medium 1410) or Figure 1 , Figure 2 , Figure 6 , Fig.10 , Fig.11 , Fig.12 and / or Fig.14 Any other suitable device or component described in any of the above and using, for example, Figure 4 Figure 5 Figure 7 , Fig. 8A , Figure 8B , Fig.9A , Fig. 9B , Fig.13 and / or Fig.15 Instructions of the described processes and / or algorithms.

[0195] The following provides an overview of various aspects of the disclosure:

[0196] Aspect 1: A first network node, comprising: a memory; and a processor, the processor being coupled to the memory, wherein the processor is configured to: receive a plurality of reference signals, wherein each of the plurality of reference signals corresponds to a corresponding identifier among a plurality of identifiers; and send prediction information indicating a predicted beam blocking event, wherein the prediction information is based on measurement information corresponding to the plurality of reference signals during a time period.

[0197] Aspect 2: The first network node according to aspect 1, wherein the processor is configured to: obtain the measurement information during the time period.

[0198] Aspect 3: The first network node according to aspect 2, wherein in order to obtain the measurement information during the time period, the processor is configured to perform one or more measurements during the time period to generate the measurement information.

[0199] Aspect 4: A first network node according to any one of aspects 1 to 3, wherein the multiple reference signals include one or more beam failure detection reference signals (BFD-RS) of a first type, one or more BFD-RS of a second type, or a combination thereof.

[0200] Aspect 5: The first network node according to any one of aspects 1 to 4, wherein the measurement information comprises corresponding reference signal received power (RSRP) information of each corresponding reference signal in the plurality of reference signals.

[0201] Aspect 6: A first network node according to any one of Aspects 1 to 5, wherein the processor is configured to: receive prediction configuration information, wherein the prediction configuration information includes information indicating at least one of the following: the length of the time period, a statistical metric used to predict the predicted beam blocking event, a threshold for comparison with the statistical metric, the occurrence of the predicted beam blocking event, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event.

[0202] Aspect 7: The first network node according to any one of aspects 1 to 6, wherein the measurement information is based on the predicted configuration information.

[0203] Aspect 8: The first network node according to any one of aspects 1 to 7, wherein the prediction information is based on the prediction configuration information.

[0204] Aspect 9: A first network node according to any one of Aspects 1 to 8, wherein the measurement information includes multiple reference signal received power measurements corresponding to corresponding multiple beam identification values ​​that vary over time, wherein the processor is configured to compare the statistical metric associated with the multiple reference signal received power measurements with the threshold, and wherein, in order to send the prediction information, the processor is configured to send the prediction information based on the comparison.

[0205] Aspect 10: The first network node according to any one of aspects 1 to 9, wherein the processor is configured to: provide the measurement information to a model; and obtain the prediction information as an output from the model.

[0206] Aspect 11: The first network node according to any one of aspects 1 to 10, wherein the processor is configured to: receive the model or information indicative of the model from a second network node.

[0207] Aspect 12: The first network node according to any one of aspects 1 to 11, wherein the model comprises a neural network.

[0208] Aspect 13: A first network node according to any one of Aspects 1 to 12, wherein neural network training of the neural network utilizes multiple spectra from the first network node or at least one of multiple other network nodes, each of the multiple spectra comprising a corresponding set of corresponding beam measurements for each corresponding reference signal associated with each corresponding beam identifier that varies over time.

[0209] Aspect 14: The first network node according to any one of aspects 1 to 13, wherein, in order to provide the measurement information to the model, the processor is configured to: send the measurement information to a second network node.

[0210] Aspect 15: A first network node according to any one of Aspects 1 to 14, wherein the prediction information indicating the predicted beam blocking event includes at least one of the following: information indicating an instance of the predicted beam blocking event, information indicating the severity of the predicted beam blocking event, or information indicating the orientation of an object corresponding to the predicted beam blocking event.

[0211] Aspect 16: The first network node according to any one of aspects 1 to 15, wherein the information indicative of the instance of the predicted beam blocking event corresponds to a prediction of the start of the predicted beam blocking event in the time domain.

[0212] Aspect 17: The first network node according to any one of aspects 1 to 16, wherein the information indicative of the severity of the predicted beam blocking event corresponds to a duration of the predicted beam blocking event.

[0213] Aspect 18: A first network node according to any one of Aspects 1 to 17, wherein the information indicating the position of the object corresponding to the predicted beam blocking event includes information indicating a direction of movement relative to the first network node corresponding to the predicted beam blocking event.

[0214] Aspect 19: The first network node according to any one of aspects 1 to 18, wherein the processor is configured to: receive prediction configuration information, wherein the prediction configuration information includes information indicating a format of the prediction information, wherein the prediction information complies with the format.

[0215] Aspect 20: The first network node according to any one of aspects 1 to 19, wherein the prediction information indicating the predicted beam blocking event comprises information indicating when the predicted beam blocking event is predicted to occur.

[0216] Aspect 21: The first network node according to any one of aspects 1 to 20, wherein the prediction information indicating the predicted beam blocking event comprises information indicating a duration of the predicted beam blocking event.

[0217] Aspect 22: The first network node according to any one of aspects 1 to 21, wherein the prediction information indicating the predicted beam blocking event comprises information indicating a position of an object corresponding to the predicted beam blocking event.

[0218] Aspect 23: A first network node according to any one of Aspects 1 to 22, wherein, in order to send the prediction information, the processor is configured to send the prediction information based on at least one of: the time when the predicted beam blocking event is predicted to occur, the predicted duration of the predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event.

[0219] Aspect 24: A method at a first network node, the method comprising: receiving multiple reference signals, wherein each reference signal of the multiple reference signals corresponds to a corresponding identifier of a plurality of identifiers; and sending prediction information indicating a predicted beam blocking event, wherein the prediction information is based on measurement information corresponding to the multiple reference signals during a time period.

[0220] Aspect 25: According to the method according to Aspect 24, the method also includes: receiving prediction configuration information, wherein the prediction configuration information includes information indicating at least one of the following: the length of the time period, a statistical metric used to predict the predicted beam blocking event, a threshold for comparison with the statistical metric, the occurrence of the predicted beam blocking event, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event.

[0221] Aspect 26: The method according to aspect 24 or 25, further comprising: providing the measurement information to a model; and obtaining the prediction information as an output from the model.

[0222] Aspect 27: A first network node, comprising: a memory; and a processor, the processor being coupled to the memory, wherein the processor is configured to: send multiple reference signals, wherein each of the multiple reference signals corresponds to a corresponding identifier among multiple identifiers; receive measurement information corresponding to the multiple reference signals during a time period; and send prediction information indicating a predicted beam blocking event, wherein the prediction information is based on the measurement information.

[0223] Aspect 28: The first network node according to Aspect 27, wherein the processor is configured to: send prediction configuration information, wherein the prediction configuration information includes information indicating at least one of the following: the length of the time period, a statistical metric used to predict the predicted beam blocking event, a threshold for comparison with the statistical metric, the occurrence of the predicted beam blocking event, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or the orientation of an object corresponding to the predicted beam blocking event.

[0224] Aspect 29: The first network node according to aspect 27 or 28, wherein the processor is configured to: send the model or information indicative of the model to the second network node.

[0225] Aspect 30: The first network node according to any one of Aspects 27 to 29, wherein the model comprises a neural network.

[0226] Several aspects of wireless communication networks have been presented with reference to exemplary implementations. As those skilled in the art will readily appreciate, various aspects described throughout this disclosure may be extended to other telecommunication systems, network architectures, and communication standards.

[0227] For example, various aspects may be implemented within other systems defined by 3GPP, such as Long Term Evolution (LTE), Evolved Packet System (EPS), Universal Mobile Telecommunications System (UMTS), and / or Global System for Mobile (GSM). Various aspects may also be extended to systems defined by the 3rd Generation Partnership Project 2 (3GPP2), such as CDMA 2000 and / or Evolution-Data Optimized (EV-DO). Other examples may be implemented within systems employing IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Ultra Wideband (UWB), Bluetooth, and / or other suitable systems. The actual telecommunication standard, network architecture, and / or communication standard employed will depend on the specific application and the overall design constraints imposed on the system.

[0228] Within the present disclosure, the word "exemplary" is used to mean "serving as an example, instance, or illustration". Any specific implementation or aspect described herein as "exemplary" is not necessarily to be construed as superior or superior to other aspects of the present disclosure. Likewise, the term "aspect" does not require that all aspects of the present disclosure include the discussed features, advantages, or modes of operation. The term "coupled" is used herein to refer to a direct or indirect coupling between two objects. For example, if object A physically contacts object B, and object B contacts object C, objects A and C may still be considered to be coupled to each other, even if they are not in direct physical contact with each other. For example, a first object may be coupled to a second object, even if the first object has never been in direct physical contact with the second object. The terms "circuit" are used broadly, and they are intended to include both hardware implementations of electronic devices and conductors (which, when connected and configured, implement the execution of the functions described in the present disclosure, without limitation on the type of electronic circuits) and software implementations of information and instructions (which, when executed by a processor, implement the execution of the functions described in the present disclosure).

[0229] Figures 1 to 15 One or more of the illustrated components, steps, features and / or functions may be rearranged and / or combined into a single component, step, feature or function or embodied in several components, steps or functions. Additional elements, components, steps and / or functions may also be added without departing from the novel features disclosed herein. Figures 1 to 15The illustrated apparatus, devices and / or components may be configured to perform one or more of the methods, features or steps described herein. The novel algorithms described herein may also be effectively implemented in software and / or embedded in hardware.

[0230] The specific order or hierarchy of steps in the disclosed methods is an illustration of an exemplary process. In some examples, the specific order or hierarchy of steps in these methods can be rearranged. Any method disclosed herein presents elements of the various steps in a sample order and is not limited to the specific order or hierarchy presented unless specifically stated herein. Although some examples illustrated herein only depict time domain and frequency domain, additional domains such as spatial domain are also contemplated in the present disclosure.

[0231] The present disclosure enables 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 intended to be limited to the various aspects shown herein, but to be given the full scope consistent with the language of the claims, wherein unless specifically stated so, reference to an element in the singular form does not mean "one and only one", but "one or more". Unless otherwise specified, the term "some" refers to one or more. A phrase referring to "at least one" in a list of items refers to any combination of those items, including a single member. As an example, "at least one of a, b, or c" is intended to cover: a; b; c; a and b; a and c; b and c; and a, b, and c. Structures A and / or B are intended to cover: A; B; and A and B. As used herein, the word "obtain" may mean, for example, obtaining, calculating, constructing, deriving, determining, receiving, and / or retrieving. The foregoing list is exemplary and non-restrictive.

[0232] As used herein, the term "or" is an inclusive "or" unless restrictive language is used with respect to the listed alternatives. For example, references to "X is based on A or B" should be interpreted as including within its scope X based on A, X based on B, and X based on A and B. In this regard, references to "X is based on A or B" refer to "at least one of A or B" or "one or more of A or B" because "or" is inclusive. Similarly, references to "X is based on A, B, or C" should be interpreted as including within its scope X based on A, X based on B, X based on C, X based on A and B, X based on A and C, X based on B and C, and X based on A, B, and C. In this regard, references to "X is based on A, B, or C" refer to "at least one of A, B, or C" or "one or more of A, B, or C" because "or" is inclusive. As an example of restrictive language, a reference to "X is based on only one of A or B" should be interpreted to include within its scope X being based on A and X being based on B, but not including X being based on both A and B. Furthermore, as used herein, the phrase "based on" should not be interpreted as a reference 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 on at least A" unless specifically stated differently. Likewise, as used herein, the phrase "set" should be understood to include the possibility of a set having one member. That is, the phrase "set" should be understood in the same manner as "one or more" or "at least one."

[0233] All structural and functional equivalents that are known or later become known to the elements of the various aspects described throughout this disclosure are expressly incorporated herein by reference and are intended to be covered by the claims. Nothing disclosed herein is dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. No claim element should be interpreted under the provisions of 35 U.S.C. §112(f) unless the element is expressly recited using the phrase "means for..." or, in the case of a method claim, the phrase "step for..." is used to recite the element.

Claims

1. A first network node, the first network node comprising: Memory; and a processor coupled to the memory, wherein the processor is configured to: receiving a plurality of reference signals, wherein each reference signal of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers; as well as Prediction information indicating a predicted beam blocking event is transmitted, wherein the prediction information is based on measurement information corresponding to the plurality of reference signals during a time period.

2. The first network node according to claim 1, wherein the processor is configured to: The measurement information during the time period is obtained. 3 . The first network node according to claim 2 , wherein in order to obtain the measurement information during the time period, the processor is configured to perform one or more measurements during the time period to generate the measurement information.

4. The first network node of claim 1, wherein the plurality of reference signals comprises one or more beam failure detection reference signals (BFD-RS) of a first type, one or more BFD-RS of a second type, or a combination thereof. 5 . The first network node according to claim 1 , wherein the measurement information comprises corresponding reference signal received power (RSRP) information of each corresponding reference signal of the plurality of reference signals.

6. The first network node according to claim 1, wherein the processor is configured to: Receiving prediction configuration information, wherein the prediction configuration information includes information indicating at least one of: the length of the time period, a statistical measure used to predict the predicted beam blocking event, a threshold value to which the statistical measure is compared, The predicted beam blocking event occurs, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or The orientation of the object corresponding to the predicted beam blockage event. The first network node according to claim 6 , wherein the measurement information is based on the predicted configuration information.

8. The first network node of claim 6, wherein the prediction information is based on the prediction configuration information.

9. The first network node of claim 6, wherein the measurement information comprises a plurality of reference signal received power measurements corresponding to a respective plurality of beam identification values ​​varying over time, wherein the processor is configured to compare the statistical metric associated with the plurality of reference signal received power measurements with the threshold, and wherein, To send the prediction information, the processor is configured to send the prediction information based on the comparison.

10. The first network node according to claim 1, wherein the processor is configured to: providing the measurement information to a model; and The prediction information is obtained as an output from the model.

11. The first network node according to claim 10, wherein the processor is configured to: The model or information indicative of the model is received from a second network node.

12. The first network node of claim 10, wherein the model comprises a neural network.

13. A first network node according to claim 12, wherein neural network training of the neural network utilizes multiple spectra from the first network node or at least one of multiple other network nodes, each of the multiple spectra comprising a corresponding set of corresponding beam measurements for each corresponding reference signal associated with each corresponding beam identifier that varies over time.

14. The first network node according to claim 10, wherein: In order to provide the measurement information to the model, the processor is configured to: The measurement information is sent to the second network node.

15. The first network node according to claim 1, wherein the prediction information indicating the predicted beam blocking event comprises at least one of: information indicative of an instance of said predicted beam blocking event, information indicating the severity of the predicted beam blocking event, or Information indicative of a position of an object corresponding to the predicted beam blockage event.

16. The first network node of claim 15, wherein the information indicative of the instance of the predicted beam blocking event corresponds to a prediction of a start of the predicted beam blocking event in the time domain.

17. The first network node of claim 15, wherein the information indicative of the severity of the predicted beam blocking event corresponds to a duration of the predicted beam blocking event.

18. The first network node of claim 15, wherein the information indicative of the position of the object corresponding to the predicted beam blocking event comprises information indicative of a direction of motion relative to the first network node corresponding to the predicted beam blocking event.

19. The first network node of claim 1, wherein the processor is configured to: Prediction configuration information is received, wherein the prediction configuration information includes information indicating a format of the prediction information, wherein the prediction information complies with the format.

20. The first network node of claim 1, wherein the prediction information indicative of the predicted beam blocking event comprises information indicating when the predicted beam blocking event is predicted to occur.

21. The first network node of claim 1, wherein the prediction information indicative of the predicted beam blocking event comprises information indicative of a duration of the predicted beam blocking event.

22. The first network node of claim 1, wherein the prediction information indicative of the predicted beam blocking event comprises information indicative of a position of an object corresponding to the predicted beam blocking event.

23. The first network node according to claim 1, wherein: To send the prediction information, the processor is configured to send the prediction information based on at least one of the following: The predicted beam blocking event is predicted to occur at a time, the predicted duration of the predicted beam blocking event, or The orientation of the object corresponding to the predicted beam blockage event.

24. A method at a first network node, the method comprising: receiving a plurality of reference signals, wherein each reference signal of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers; as well as Prediction information indicating a predicted beam blocking event is transmitted, wherein the prediction information is based on measurement information corresponding to the plurality of reference signals during a time period.

25. The method according to claim 24, further comprising: Receiving prediction configuration information, wherein the prediction configuration information includes information indicating at least one of: the length of the time period, a statistical measure used to predict the predicted beam blocking event, a threshold value to which the statistical measure is compared, The predicted beam blocking event occurs, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or The orientation of the object corresponding to the predicted beam blockage event.

26. The method according to claim 24, further comprising: providing the measurement information to a model; as well as The prediction information is obtained as an output from the model.

27. A first network node, the first network node comprising: Memory; and a processor coupled to the memory, wherein the processor is configured to: transmitting a plurality of reference signals, wherein each reference signal of the plurality of reference signals corresponds to a respective identifier of a plurality of identifiers; receiving measurement information corresponding to the plurality of reference signals during a time period; as well as Prediction information indicating a predicted beam blocking event is sent, wherein the prediction information is based on the measurement information.

28. The first network node according to claim 27, wherein the processor is configured to: Sending prediction configuration information, wherein the prediction configuration information includes information indicating at least one of the following: the length of the time period, a statistical measure used to predict the predicted beam blocking event, a threshold value to which the statistical measure is compared, The predicted beam blocking event occurs, an instance of the predicted beam blocking event, the severity of the predicted beam blocking event, or The orientation of the object corresponding to the predicted beam blockage event.

29. The first network node according to claim 27, wherein the processor is configured to: The model or information indicative of the model is sent to the second network node.

30. The first network node of claim 29, wherein the model comprises a neural network.

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