Method and apparatus for path loss prediction

Abstract

Example embodiments of the present disclosure relate to path loss prediction for TCI state switching and / or UL transmission. A method includes: transmitting, by a first apparatus and to a second apparatus, capability information indicating at least one of: a capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or a capability to perform path loss prediction for predicted beam switch; receiving, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switch command for a target TCI state, or an indication to transmit an uplink transmission; and determining, based on the received TCI switch command or the received indication, to exclude at least one path loss measurement delay from a switch delay time for the target TCI state and / or a transmission delay time for the uplink transmission.

Description

Cross-references to related applications

[0001] This application claims priority and benefit to GB application number 2404770.6, filed on April 4, 2024, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0002] Various exemplary embodiments of this disclosure generally relate to the telecommunications field, and more particularly to methods, apparatus, devices, and computer-readable storage media for path loss prediction for TCI state transitions and / or UL transmissions. Background Technology

[0003] In the telecommunications industry, artificial intelligence / machine learning (AI / ML) models are already being used in telecom systems to improve performance. For example, 3GPP Release 18 initiated research into AI / ML for New Radio (NR) air interfaces. The goal is to explore the benefits of enhancing air interfaces by leveraging features that can improve support for AI / ML-based algorithms to enhance performance and / or reduce complexity / overhead. Several use cases are considered to enable the identification of public AI / ML frameworks that can be used in subsequent projects, including the functional requirements of AI / ML architectures. It also aims to identify areas where AI / ML can improve the performance of air interface functions. The impact of communication specifications will be assessed to improve a comprehensive understanding of what is needed to implement AI / ML technologies for air interfaces. Summary of the Invention

[0004] In a first aspect of this disclosure, a first apparatus is provided. The first apparatus includes at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus to at least: transmit capability information to a second apparatus, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching; receive from the second apparatus at least one of the following: a TCI switching command for a target transmission configuration indicator (TCI) state, or an indication to perform uplink transmission; and, based on the received TCI switching command or the received indication, determine to exclude at least one path loss measurement delay from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

[0005] In a second aspect of this disclosure, a method is provided. The method includes: transmitting capability information from a first device and to a second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for a prediction-based beam switching; receiving from the second device at least one of the following: a TCI switching command for a target transmission configuration indicator (TCI) state, or an indication to perform uplink transmission; and determining, based on the received TCI switching command or the received indication, at least one path loss measurement delay to be excluded from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

[0006] In a third aspect of this disclosure, a first apparatus is provided. The first apparatus includes components for transmitting capability information to a second apparatus, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching; components for receiving from the second apparatus at least one of the following: a TCI switching command for a target transmission configuration indicator (TCI) state, or an indication to transmit uplink transmission; and components for determining, based on the received TCI switching command or the received indication, at least one path loss measurement delay to be excluded from the switching delay time for the target TCI state and / or the transmission delay time for uplink transmission.

[0007] In a fourth aspect of this disclosure, a computer-readable medium is provided. The computer-readable medium includes instructions stored thereon for causing a device to perform at least the method according to the second aspect.

[0008] It should be understood that the summary portion is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0009] Some exemplary embodiments will now be described with reference to the accompanying drawings, in which: Figure 1 An example communication environment in which example embodiments of this disclosure may be implemented is shown; Figure 2 A flowchart of a signaling flow for path loss prediction according to some example embodiments of the present disclosure is shown; Figure 3 A flowchart is shown illustrating a method implemented at a first device according to some exemplary embodiments of the present disclosure; Figure 4A simplified block diagram of a device suitable for implementing example embodiments of the present disclosure is shown; and Figure 5 A block diagram of an example computer-readable medium according to some example embodiments of the present disclosure is shown.

[0010] In all the accompanying drawings, the same or similar reference numerals denote the same or similar elements. Detailed Implementation

[0011] The principles of this disclosure will now be described with reference to some exemplary embodiments. It should be understood that these embodiments are described for illustrative purposes only and to assist those skilled in the art in understanding and implementing this disclosure, and do not imply any limitation on the scope of this disclosure. The embodiments described herein can be implemented in various ways other than those described below.

[0012] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0013] References to "an embodiment," "embodiment," "example embodiment," etc., in this disclosure indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment must include that particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Additionally, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is believed that incorporating other embodiments, whether explicitly described or not, to affect such a feature, structure, or characteristic is within the knowledge of those skilled in the art.

[0014] It should be understood that although terms such as "first," "second," etc., preceding nouns may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another, and they do not restrict the order of the nouns. For example, without departing from the scope of the exemplary embodiments, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0015] As used herein, “at least one of the following: ” and “at least one of ” and similar wording (where the list of two or more elements is connected by “and” or “or”) means at least any one of the elements, or at least any two or more of the elements, or at least all of the elements.

[0016] As used herein, unless explicitly stated otherwise, the execution step “in response to A” does not indicate that the step is performed immediately after “A” occurs, and may include one or more intermediate steps.

[0017] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that, when used herein, the terms “comprises,” “comprising,” “has,” “having,” “includes,” and / or “including” specify the presence of features, elements, and / or components, etc., but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0018] As used in this application, the term "circuit" may refer to one or more of the following: (a) Hardware circuit implementation only (such as implementation in analog and / or digital circuits only) and (b) A combination of hardware circuitry and software, such as (if applicable): (i) A combination of analog and / or digital (multiple) hardware circuits and software / firmware, and (ii) Any part of a hardware processor(s) having software (including (multiple) digital signal processors), software, and (multiple) memories, which work together to enable a device such as a mobile phone or server to perform various functions, and (c) (Multiple) hardware circuits and / or (multiple) processors, such as (multiple) microprocessors or a portion thereof, which require software (e.g., firmware) to operate, but may be absent when the software is not required to operate.

[0019] This definition of "circuit" applies to all uses of the term in this application (including in any claim). As another example, as used in this application, the term "circuit" also covers implementations of hardware circuitry or processors (or processors in general) and their accompanying software and / or firmware. The term "circuit" also covers, for example and if applicable to a particular claim element, baseband integrated circuits or processor integrated circuits for mobile devices or similar integrated circuits in servers, cellular network devices, or other computing or network devices.

[0020] As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as New Radio (NR), Long Term Evolution (LTE), LTE-A Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), Narrowband Internet of Things (NB-IoT), etc. Furthermore, communication between terminal devices and network devices in a communication network can be performed according to any suitable generation of communication protocol, including but not limited to first-generation (1G), second-generation (2G), 2.5G, 2.75G, third-generation (3G), fourth-generation (4G), 4.5G, fifth-generation (5G), sixth-generation (6G) communication protocols and / or any other currently known or future-developed protocols. Embodiments of this disclosure can be applied to various communication systems. Given the rapid development of communications, there will certainly be future types of communication technologies and systems that embody the future types of this disclosure. The scope of this disclosure should not be construed as limited to the aforementioned systems.

[0021] As used herein, the term "network device" refers to a node in a communications network through which terminal devices access the network and receive services. Depending on the terminology and technology applied, a network device can refer to a base station (BS) or access point (AP), such as a Node B (NodeB or NB), an evolved Node B (eNodeB or eNB), an NR NB (also known as a gNB), a remote radio unit (RRU), a radio header (RH), a remote radio header (RRH), a relay, an integrated access and backhaul (IAB) node, a low-power node (such as a femto, pico, or non-terrestrial network (NTN)) or non-terrestrial network equipment (such as satellite network equipment), low Earth orbit (LEO) satellites and geostationary Earth orbit (GEO) satellites, spacecraft network equipment, etc. In some example embodiments, the radio access network (RAN) split architecture includes a centralized unit (CU) and a distributed unit (DU) at the IAB host node. The IAB node includes a mobile terminal (IAB-MT) portion that behaves as a UE facing the parent node, and the DU portion of the IAB node behaves as a base station facing the next-hop IAB node.

[0022] The term "terminal device" refers to any terminal device capable of wireless communication. By way of example and not limitation, a terminal device may also be referred to as a communication device, user equipment (UE), subscriber station (SS), portable subscriber station, mobile station (MS), or access terminal (AT). Terminal devices may include, but are not limited to, mobile phones, cellular phones, smartphones, Voice over IP (VoIP) phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and recycle bins, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop embedded devices (LEEs), laptop mounted devices (LMEs), USB dongles, smart devices, wireless customer premises equipment (CPEs), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in the context of industrial and / or automated processing chains), consumer electronics devices, devices operating on commercial and / or industrial wireless networks, etc. The terminal device may also correspond to the mobile terminal (MT) portion of an IAB node (e.g., a relay node). In the following description, the terms "terminal device," "communication device," "terminal," "user equipment," and "UE" are used interchangeably.

[0023] As used herein, the terms “resource,” “transmission resource,” “resource block,” “physical resource block” (PRB), “uplink resource,” or “downlink resource” can refer to any resource used to perform communication, such as communication between a terminal device and a network device, including resources in the time domain, frequency domain, spatial domain, code domain, or any other combination of time, frequency, spatial, and / or code domain resources used to enable communication. In the following, unless explicitly stated otherwise, resources in the frequency and time domains will be used as examples of transmission resources used to describe some exemplary embodiments of this disclosure. Note that the exemplary embodiments of this disclosure are equally applicable to other resources in other domains.

[0024] As used herein, the term "model" refers to the association between an input and an output learned from training data, and thus can generate a corresponding output for a given input after training. Model generation can be based on machine learning (ML) techniques. Machine learning techniques can also be referred to as artificial intelligence (AI) techniques. Typically, machine learning models can be built that receive input information and make predictions based on that input information. For example, a classification model can predict the category of input information in a predetermined set of categories. As used herein, "model" can also be referred to as a "machine learning model," "learning model," "machine learning network," or "learning network," and these terms are used interchangeably throughout this document.

[0025] To facilitate understanding of the terminology, some definitions for the AI / ML terminology list are provided below.

[0026] AI / ML Models: Data-driven algorithms that apply AI / ML techniques to generate a set of outputs based on a set of inputs.

[0027] AI / ML Model Delivery: The general term refers to delivering an AI / ML model from one entity to another in any way. Note: Entities can refer to network nodes / functions (e.g., gNB, Location Management Function (LMF), etc.), UEs, proprietary servers, etc. AI / ML model inference: The process of using a trained AI / ML model to produce a set of outputs based on a set of inputs.

[0028] AI / ML Model Testing: A sub-process of training used to evaluate the performance of the final AI / ML model using a different dataset than that used for model training and validation. Unlike AI / ML model validation, testing does not assume subsequent adjustments to the model.

[0029] AI / ML model training: The process of training an AI / ML model in a data-driven manner [by learning input / output relationships] and obtaining a trained AI / ML model for inference.

[0030] AI / ML model transmission: AI / ML models are delivered over the air interface in a manner opaque to 3GPP signaling. These models may contain parameters of a model structure known to the receiving end, or they may be new models with parameters. The transmission may include a complete model or a partial model.

[0031] AI / ML Model Validation: A subprocess of training used to evaluate the quality of AI / ML models using a different dataset than the dataset used for model training. This helps in selecting model parameters that generalize to datasets other than the one used for model training.

[0032] Data collection: The process by which network nodes, management entities, or UEs collect data for use in AI / ML model training, data analysis, and inference.

[0033] Function Identification: The process / method for identifying AI / ML functions for mutual understanding between the network and the UE. Note: Information about AI / ML functions can be shared during function identification. The location where AI / ML functions reside depends on specific use cases and sub-use cases.

[0034] Model Activation: Enables AI / ML models for specific functions.

[0035] Model deactivation: Disables AI / ML models for specific functions.

[0036] Model download: The transfer of the model from the network to the UE.

[0037] Model Identification: The process / method for identifying AI / ML models used for mutual understanding between the network (NW) and the UE. Note: The process / method for model identification may or may not be applicable. Note: Information about the AI / ML model may be shared during model identification.

[0038] Model monitoring: The process of monitoring the inference performance of AI / ML models.

[0039] Model parameter update: The process of updating the model parameters.

[0040] Model selection: The process of selecting the AI / ML model to be activated from among multiple models that share the same AI / ML-supporting features. Note: Model selection may or may not be performed concurrently with model activation.

[0041] Model switching: Deactivate the currently active AI / ML model and activate different AI / ML models for specific functions.

[0042] Model update: The process of updating model parameters and / or model structure.

[0043] Model upload: The transfer of the model from the UE to the network.

[0044] Offline field data: Data collected from fields and used for offline training of AI / ML models.

[0045] Offline training: An AI / ML training process in which a model is trained based on a collected dataset, and the trained model is later used or delivered for inference. Note: This definition is for guidance only. There may be cases that do not perfectly fit this definition but can still be classified as offline training through generally accepted conventions.

[0046] Online field data: Data collected from the field and used for online training of AI / ML models.

[0047] Online training: The AI / ML training process in which the model used for inference is trained (usually continuously) in a (near) real-time manner as new training samples arrive. Note: The concept of (near) real-time versus non-real-time depends on the context and is relative to the inference timescale. Note: This definition is for guidance only. There may be cases that do not fully meet this definition but can still be classified as online training according to generally accepted conventions. Note: Fine-tuning / retraining can be done via online or offline training. (This note can be removed when we define the term fine-tuning.) Semi-supervised learning: The process of training a model using a mixture of labeled and unlabeled data.

[0048] Supervised learning: The process of training a model from inputs and their corresponding labels.

[0049] Unsupervised learning: The process of training a model without labeled data.

[0050] UE-side (AI / ML) model: An AI / ML model in which inference is performed entirely at the UE.

[0051] Network-side (AI / ML) models: AI / ML models in which inference is performed entirely at the network.

[0052] Single-sided (AI / ML) model: UE-side (AI / ML) model or network-side (AI / ML) model.

[0053] AI / ML Model: Paired AI / ML models (multiple), joint inference is performed on the paired AI / ML models, where joint inference includes AI / ML inference. The AI / ML inference is jointly performed by the UE and the network, that is, the first part of the inference is performed by the UE first, and then the remaining part is performed by the gNB, or vice versa.

[0054] Proprietary Format Models: From a 3GPP perspective, these are vendor / device-specific proprietary ML models. They are not mutually identifiable between vendors and hide model design information from other vendors when shared. Note: The example is a device-specific binary executable format.

[0055] Open format models: From a 3GPP perspective, these are specified format ML models that are mutually identifiable across vendors and allow for interoperability. They are mutually identifiable between vendors and do not hide model design information from other vendors when shared.

[0056] Figure 1 An example communication environment 100 in which exemplary embodiments of the present disclosure can be implemented is shown. It should be understood that the elements shown in the communication system 100 are intended to represent the main functions provided within the system. Therefore, Figure 1 The boxes shown refer to specific elements in a communication network that provide these main functions. However, some or all of the main functions represented can be implemented using other network elements. Furthermore, it should be understood that not all functions of a communication network are represented in the boxes. Figure 1 The text is a mix of Chinese and English, and doesn't form a coherent sentence or paragraph. It appears to be a collection of fragments from various sources, possibly related to illustration or explanation. Figure 1 The number of elements shown is for illustrative purposes only, and any number of elements may be present.

[0057] As shown in the figure, the communication environment 100 includes multiple communication devices, including one or more first devices 110-1, 110-2, ..., 110-N (collectively or individually referred to as first devices 110) and one or more second devices 120. Figure 1 In the example, the second device 120 may include network equipment, and the first device 110 may include terminal equipment. The service area of ​​the second device 120 may be referred to as a cell. The first device 110 and the second device 120 may operate in a radio access network (RAN). Although two terminal devices (e.g., the first device) are shown, there may be more or fewer terminal devices in the service area of ​​the network equipment, and there may be more network devices serving the terminal devices in the communication environment 100.

[0058] In the following description, for illustrative purposes, some exemplary embodiments are described in which the first device 110 operates as a terminal device and the second device 120 operates as a network device. However, in some exemplary embodiments, the operations described in connection with the terminal device can be implemented at the network device or other devices, and the operations described in connection with the network device can be implemented at the terminal device or other devices.

[0059] In some example embodiments, if the first device 110 is a terminal device and the second device 120 is a network device, the link from the second device 120 to the first device 110 is referred to as a downlink (DL), and the link from the first device 110 to the second device 120 is referred to as an uplink (UL). In the DL, the second device 120 is a transmission (TX) device (or transmitter), and the first device 110 is a reception (RX) device (or receiver). In the UL, the first device 110 is a TX device (or transmitter), and the second device 120 is an RX device (or receiver).

[0060] Communication in communication environment 100 can be implemented according to any suitable communication protocol(s), including but not limited to cellular communication protocols such as first-generation (1G), second-generation (2G), third-generation (3G), fourth-generation (4G), fifth-generation (5G), and sixth-generation (6G), wireless local network communication protocols such as IEEE 802.11, and / or any other currently known or future-developed protocols. Furthermore, communication can utilize any suitable wireless communication technology, including but not limited to: Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Frequency Division Duplex (FDD), Time Division Duplex (TDD), Multiple-Input Multiple-Output (MIMO), Orthogonal Frequency Division Multiple Access (OFDM), Discrete Fourier Transform Extended OFDM (DFT-s-OFDM), and / or any other currently known or future-developed technologies.

[0061] In some example embodiments, different AI / ML models can be configured to implement the same or different algorithms in the communication environment 100. AI / ML model 105 may sometimes be referred to as an AI model or simply an ML model. Inference, testing, training, and / or validation of the AI / ML model can be performed at one or more of the first device 110, the second device 120, and / or other entities. Figure 1 In the example, AI / ML model 105 is shown deployed on the side of the first device 110. AI / ML models can be delivered from one entity to another in any manner. The AI / ML model can be delivered over the air interface in a way that is opaque to 3GPP signaling, or it can be a model with parameters known to the receiving end, or a new model with parameters. The delivery can contain a complete model or a partial model.

[0062] AI / ML-based beam prediction and related functions have been introduced into the NR MIMO framework.

[0063] In some example embodiments related to AI-based beam management (BM), an AI / ML model 105 is configured for beam prediction. BM-specific use cases are proposed for AI-based beam management. BM-use case 1 involves spatial domain DL beam prediction for beam set A based on measurement results from beam set B. BM-use case 2 involves temporal DL beam prediction for beam set A based on historical measurement results from beam set B. DL transport (Tx) beam prediction can be configured for both the UE-side model and the network (NW)-side model.

[0064] For BM-use case 1 and BM-use case 2, the necessity, benefits (multiple) and potential canonical impacts of AI model reasoning are studied from the following additional aspects: how to perform beam indication for beams in set A that are not in set B.

[0065] For BM-use case 1 and BM-use case 2 with UE-side AI / ML models, the potential canonical impacts of AI model inference are studied from the following additional aspects, building on the previous protocol: indications from the network to the UE to the associated set A, such as, where applicable, the association / mapping of beams within set A with beams within set B; and beam indications from the network for UE reception.

[0066] In some example embodiments, at least for BM-use case 1 with a UE-side AI / ML model, beam indication can be performed using the conventional TCI state mechanism for AI model inference.

[0067] In communication systems, UL TCI state handover may require handover conditions related to path loss RS. Combined DL & UL TCI state handover may also require handover conditions related to path loss RS.

[0068] For uplink TCI state switching latency based on Media Access Control Element (MAC-CE), the following requirements apply to UL TCI state switching using either a separate UL TCI state or a combined TCI state using a unified TCI state switching framework.

[0069] In cases where the source RS in UL TCI state or joint TCI state is associated with a PCI different from that of the serving cell, the requirements in this clause shall apply if the cell with the different PCI meets the known cell condition as defined in 8.16.1. If the known cell condition is not met, a longer delay may be expected.

[0070] In the case of joint TCI state switching, the UE is not expected to transmit on UL before completing the DL and UL TCI state switching.

[0071] For individual UL TCI state switching or combined TCI state switching used for PUCCH or PUSCH or semi-persistent / aperiodic / periodic SRS, when beamCorrespondenceWithoutUL-BeamSweeping When set to 1, when a PDSCH carrying a MAC-CE activation command is received in slot n on the serving cell, the UE should perform the following operations as shown in Table 1.

[0072] Table 1

[0073] The unified TCI state framework is defined as a general TCI / QCL framework used for both DL and UL. Within the unified TCI state (Rel17) framework, a single TCI state can be indicated to the UE, and this TCI state, or more precisely, the RS(s) indicated by the TCI state, is used for the transmission and reception assumptions of PDCCH / PDSCH / CSI-RS and / or PUCCH / PUSCH / SRS. By allowing the UE to have up to two joint DL / UL or individual DL and UL indicated TCI states, the use of the unified TCI framework is extended to all S-DCI and M-DCI multi-TRP DL and UL transmission schemes developed in R16-R18.

[0074] Within the unified TCI state framework, beam indication, or more precisely, TCI state indication (i.e., indicating which TCI state is used for the transmission and / or reception assumptions of the signal and channel associated with the TCI state), comprises the following steps: 1. For the serving cell, the unified TCI status type is configured as either combined UL / DL or individual UL / DL. In combined UL / DL, the indicated TCI status is used for both uplink and downlink, while in individual UL / DL, DL and UL are indicated separately (a TCI code point indicated in the DCI can include only DL TCI, only UL TCI, or DL ​​and ULTCI statuses). If the TCI status type is combined, a single TCI status list is configured for the UE using RRC.

[0075] 2. If the TCI state type is separate, configure the DL TCI state list and UL TCI state list for the UE. Configuration is performed using RRC signaling, while the MAC CE selects and activates up to eight (in Rel-17) TCI code points, one of which can be indicated via DCI. As before, a TCI code point can include only the DL TCI state, only the UL TCI state, or both DL and UL TCI states.

[0076] 3. To indicate the TCI state (joint) or individual TCI state (UL and DL), the network provides TCI code points (values ​​in the DCI message), which correspond to the TCI code points of the active TCI code points (multiple) in the MAC CE. Upon receiving a DCI-based beam indication (DCI code point), the UE applies the indicated TCI state to the indicated channel (PDSCH, PDCCH / PUSCH / PUCCH).

[0077] The following are the relevant information elements (IE) for TCI status: IE TCI-State Associating one or two DL reference signals with the corresponding quasi-co-address (QCL) type is shown in Table 2: Table 2: TCI-State Information Element

[0078] QCL-Info The field descriptions are shown in Table 3 below, and some conditions are indicated in Table 4.

[0079] Table 3: TCI-State Information elements

[0080] Table 4

[0081] When switching from a TCI state to a new UL TCI state (in the case of combined DL / UL or both DL / UL alone), the UE may require additional time to estimate the path loss associated with the target TCI state. This is independent of whether the TCI state is known or unknown. For example, when receiving a PDSCH carrying a MAC-CE activation command in slot n on the serving cell, the UE should be able to estimate the path loss in slot n+T. HARQ + +NM (T) first_target-PL-RS +4 T target_PL-RS +2ms) / NR time slot length Spend The target TCI state is used to transmit uplink signals.

[0082] In AI / ML-based beam switching (or prediction-based beam switching), since RS set B (or a second set or measured RS set) is used to predict the target RS in set A, and the UE may not measure set A or measure set A at a low cycle, the UE may not have measured / estimated the path loss for the target TCI state.

[0083] Typically, UEs are required to maintain a limited number of PL estimates, so PL estimates need to be enhanced in order to efficiently utilize prediction-based beam switching.

[0084] According to some example embodiments of this disclosure, a solution for path loss prediction for a UE-side AI / ML model is provided. A first device (e.g., a terminal device) transmits capability information to a second device (e.g., a network device), the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching. Then, if the first device receives a Transmission Configuration Indicator (TCI) handover command for a target TCI state or an indication to transmit uplink transmission from the second device, the first device can determine to exclude at least one path loss measurement delay from the handover delay time for the target TCI state and / or the transmission delay time for uplink transmission.

[0085] This solution leverages PL estimation to efficiently utilize prediction-based beam switching. This can facilitate increased throughput due to faster switching for the target UL TCI state and the execution of uplink transmissions.

[0086] The exemplary embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0087] Figure 2A flowchart of a signaling flow 200 for path loss prediction according to some example embodiments of the present disclosure is shown. For discussion purposes, refer to... Figure 1 To describe signaling flow 200. For example... Figure 2 As shown, signaling flow 200 relates to a first device 110 and a second device 120. In some example embodiments, the first device 110 may include or may be included in a terminal device, and the second device 120 may include or may be included in a network device (e.g., gNB, gNB CU, or gNB DU, etc.).

[0088] In signaling stream 200, the first device 110 transmits (205) capability information to the second device 120. The capability information indicates at least one of the following: the capability to perform path loss (PL) prediction, an indication to perform UL transmission based on PL prediction, or the capability to perform path loss prediction for prediction-based beam switching. In some example embodiments, the capability information indicating PL-related predictions may be optional. The UE's capability to perform PL prediction or PL prediction-related actions (such as uplink transmission or TCI state switching) may be included or indicated as part of other capability information related to beam management or prediction-related capabilities. As an example, the capability (for path loss prediction) may be included as part of one or more features supporting prediction-based beam management (e.g., AI / ML-based prediction).

[0089] The second device 120 receives (210) capability information and determines whether to switch the first device 110 to the target TCI state or instruct the first device 110 to perform a UL transmission. The second device 120 transmits (215) a TCI switching command for the target TCI state and / or an instruction for transmission to the first device 110.

[0090] The first device 110 receives (220) at least one of the following from the second device 120: a TCI handover command for a target TCI state, or an indication for uplink transmission. Based on the received TCI handover command or the received indication, the first device 110 determines (225) to exclude at least one path loss measurement delay from the handover delay time for the target TCI state and / or the transmission delay time for uplink transmission.

[0091] In some example embodiments, the first device 110 may perform uplink transmission based at least in part on path loss prediction performed (or already performed) for a target reference signal for uplink transmission. In other words, the UE may determine the target downlink reference signal for uplink transmission and perform path loss-related prediction for uplink transmission.

[0092] In some example embodiments, the ability to predict path loss or perform path loss-related predictions may include predicting (L1-)RSRP values ​​that can be used to derive path loss values. The derived path loss values ​​may be for at least one DL RS associated with uplink transmission.

[0093] In some example embodiments, the prediction of RSRP values ​​used for path loss estimation or deriving path loss estimates may include multiple predictions or a single prediction.

[0094] In some example embodiments, the ability to predict path loss or perform path loss-related predictions may include predicting path loss values.

[0095] In some example embodiments, predicted path loss values, or path loss values ​​derived from one or more predicted values ​​(e.g., L1-RSRP), can be used to apply uplink power control for uplink transmissions. Uplink power control can be applied relative to at least one DL RS for uplink transmissions.

[0096] In some example embodiments, the predicted path loss value or the path loss value derived from one or more predicted values ​​(e.g., L1-RSRP) can be used to apply uplink transmission power for uplink transmission.

[0097] In some example embodiments, uplink transmissions may refer to at least one of the following: scheduling request transmission, PUSCH transmission, PUCCH transmission, SRS (Sound Reference Signal Transmission), PRACH (Physical Random Access Channel) transmission, and random access preamble transmission.

[0098] In some example embodiments, capability information indicates the ability to perform PL predictions associated with a configured set of RSs. In one example embodiment, the first device 110 may indicate to the second device 120 whether it is capable of performing PL predictions for one or more RS resources. In some example embodiments, capability information indicates the ability to perform UL-based PL predictions associated with one or more RSs in a configured set of RSs.

[0099] In some example embodiments, the ability to perform PL prediction may refer to the ability to derive a path loss value based on a prediction of at least one measurement or value (e.g., RSRP value) that can be used to derive a path loss value relative to at least one reference signal. In some example embodiments, the ability to perform PL prediction may refer to predicting a path loss value relative to at least one reference signal.

[0100] In some example embodiments, the ability to perform PL prediction or the execution of PL prediction may include predicting uplink transmission power for uplink transmissions, wherein the uplink transmissions may use a downlink reference signal as a reference.

[0101] The set of RSs configured as indicated in the capability information can be a target reference signal used for PL prediction or for the target TCI state.

[0102] In some example embodiments, the TCI state may include a reference signal that can be used for path loss estimation. In some examples, the UE may determine to derive or predict path loss values ​​(and / or uplink transmission power) based on predictions or based on the reference signal included in the TCI state. The reference signal included in the TCI state may be a path loss reference signal. The reference signal included in the TCI may be an SSB or a CSI-RS.

[0103] In some example embodiments, if the UE has determined that it has predicted the path loss value, derived the path loss value based on the prediction, or predicted the uplink transmission power for uplink transmission, it can determine to transmit the uplink signal using the predicted value. In some examples, if the UE has determined that it has predicted or derived the path loss (or uplink transmission power) for uplink transmission (towards the target downlink reference signal), the UE can determine not to perform at least some measurements for path loss estimation.

[0104] In some example embodiments, the configured RS set may include an RS or RS resource list configured by RRC.

[0105] In some example embodiments, the configured RS set may include one or more RSs associated with a first beam set, which will be predicted from beams in a second beam set. In AI / ML-based beam management use cases, the first beam set is sometimes referred to as the prediction set or set A, and in beam management, the second beam set is sometimes referred to as set B. For BM-use case 1, spatial domain DL beam prediction is performed for beam set A based on measurement results from beam set B. For BM-use case 2, temporal DL beam prediction is performed for beam set A based on historical measurement results from beam set B. DL transport (Tx) beam prediction can be configured for both the UE-side model and the network (NW)-side model.

[0106] In some example embodiments, the configured RS set may include at least one RS associated with at least one TCI state in the TCI state list. In some example embodiments, the configured RS set may include at least one RS associated with at least one TCI state in the active TCI state list. In some example embodiments, the configured RS set may include at least one RS associated with at least one UL signal used as a reference for UL transmission.

[0107] In some example embodiments, if the ability to perform PL predictions associated with a configured set of RSs indicates that the first device 110 is capable of performing PL predictions associated with a configured set of RSs, then the first device 110 may subsequently perform PL predictions associated with the configured set of RSs.

[0108] In one example embodiment, the first device 110 may indicate whether it is capable of performing PL prediction for one or more RSs of a configured prediction set (e.g., set A) or whether PL prediction has already been performed for one or more RSs. In one example embodiment, the first device 110 may indicate whether it is capable of performing PL prediction for one or more RSs of a second set (e.g., set B) or whether PL prediction has already been performed for one or more RSs.

[0109] In some example embodiments, the ability to perform PL predictions associated with one or more RSs associated with the first beam set can instruct the first device 110 to perform PL predictions for all RSs associated with the first beam set. That is, the first device 110 can instruct itself to predict PLs for all RSs in the prediction set.

[0110] In some example embodiments, the ability to perform PL predictions associated with one or more RSs associated with the first beam set can instruct the first device 110 to perform PL predictions for a subset of RSs associated with the first beam set. That is, the first device 110 can instruct itself to predict PLs for a subset of RSs in the prediction set.

[0111] In some example embodiments, the ability to perform PL predictions associated with one or more RSs in the first beam set can indicate that the first device 110 is unable to perform PL predictions for at least one RS in the first beam set. That is, the first device 110 can indicate that it is unable to predict PLs for one or more RSs in the prediction set.

[0112] In some example embodiments, the capability to perform PL prediction associated with one or more RSs associated with the first beam set can be indicated by a bitmap, wherein each bit corresponds to an RS in the first beam set and indicates whether the first device 110 is capable of performing PL prediction for the corresponding RS. The signaling indicating the capability may include a bitmap, wherein each bit position in the bitmap corresponds to a specific RS.

[0113] In one example embodiment, the first device 110 may indicate whether it is capable of performing PL prediction for prediction-based beam switching. In one example embodiment, the capability to perform PL prediction for prediction-based beam switching includes the capability to perform PL prediction for TCI state switching.

[0114] If the capability to perform PL prediction for TCI state switching indicates that the first device 110 is capable of performing PL prediction for TCI state switching, then upon receiving a TCI switching command for the target TCI state, the first device 110 may perform PL prediction associated with at least one of the following: RS in the target TCI state, QCL information reference signal in the target TCI state, or QCL source reference of RS in the target TCI state.

[0115] As an example, the first device 110 may indicate to the second device 120 whether it can perform PL prediction for a TCI state switch. Upon receiving a TCI switch command for a target TCI state, the first device 110 may perform PL prediction associated with one or more RSs included in the target TCI state. The one or more RSs included in the target TCI state may include PL RSs or any QCL information RSs in the target TCI state. In some examples, upon receiving a switch command for a target TCI state, the first device 110 may perform PL prediction associated with the QCL source RSs of the RSs included in the target TCI state.

[0116] In some example embodiments, the capability information also indicates the time delay associated with the PL prediction. That is, the PL estimation capability of the first device 110 may include the time delay associated with the PL prediction. Using the time delay of the PL prediction at the first device 110, the second device 120 can determine the expected time of TCI state switching or UL transmission.

[0117] In some example embodiments, the capability information also indicates at least one of the following: the ability to perform PL prediction based on a second beam set (set B), which is used to predict a first beam set, or an indication of at least one RS in the second beam set (set B). The first device 110 may use one or more RSs associated with set B to indicate and / or perform PL prediction. As an example, set B may be used to predict the PL of one or more RSs of set A, such as candidate RS / TCI states for predicted beam switching and for predicting the PL.

[0118] In some example embodiments, if the capability information also indicates that the first device 110 is capable of performing PL prediction associated with at least one RS in the second beam set, then the first device 110 may perform PL prediction associated with at least one RS in the second beam set.

[0119] In one example embodiment, PL prediction can be configured to be performed using RSs in set B (RSs used to predict set A). The first device 110 can receive from the second device 120 a configuration to perform PL prediction using at least one RS from the second beam set. In one example, the first device 110 can indicate whether it can predict PL based on set B, or it can indicate which RS it can predict PL for based on set B.

[0120] In one example embodiment, PL prediction can be performed using a specific set of RSs configured for PL prediction. The first device 110 can perform PL prediction associated with the specific set of RSs configured for PL prediction.

[0121] In some example embodiments, the first device 110 may transmit a request for a specific set of RSs for PL prediction to the second device 120, and then receive the configuration of the specific RS set from the second device 120. For example, for UE-side PL prediction, it may be necessary to configure a specific set of RSs for PL prediction for measurement. For example, the first device 110 may request the specific set of RSs for PL prediction from the second device 120.

[0122] In some example embodiments, the capability information also indicates the ability to perform PL predictions associated with at least one RS in the candidate target TCI states. In one example embodiment, the first device 110 may indicate whether it is capable of performing PL predictions for one or more RSs or path loss RSs included in the candidate target TCI states. The candidate target TCI states may be TCI states in a TCI state list configured by RRC.

[0123] In some example embodiments, upon receiving a TCI switching command for a target TCI state, the first device 110 may perform a PL prediction associated with at least one RS among the candidate target TCI states. For example, upon receiving a control message instructing the activation of a new target TCI state, the first device 110 may perform a PL prediction associated with one or more RSs included in the target TCI state.

[0124] In some example embodiments, upon receiving a TCI switching command for a target TCI state, the first device 110 may perform a PL prediction associated with at least one target RS in the target TCI state. In one example embodiment, upon receiving a control message instructing a switch to the target TCI state, the first device 110 may perform a PL prediction associated with one or more RSs included in the target TCI state. In one example embodiment, upon receiving a control message instructing the activation of a new target TCI state, the first device 110 may perform a PL prediction associated with one or more RSs included in the target TCI state.

[0125] In one example embodiment, the first device 110 may instruct the second device 120 of its ability to perform path loss estimation using prediction. The first device 110 may instruct whether it is capable of performing PL prediction for one or more RSs of a configured prediction set (set A).

[0126] In one example embodiment, the first device 110 may be configured by the second device 120 to perform path loss prediction for one or more RSs included in a set A of RSs (beams). In one example embodiment, the first device 110 may be configured by the second device 120 to perform path loss prediction for one or more configured RSs.

[0127] It should be understood that various information elements in capability information are described, but these information elements may be transmitted in the same or different messages or signaling. The scope of this disclosure is not limited in this respect.

[0128] In some example embodiments, based on the PL prediction determined to be associated with at least one target RS in the target TCI state being executed, the first device 110 may determine a handover delay time by excluding at least one PL measurement delay based on the received TCI handover command. The first device 110 may then handover (230) to the target TCI state with the handover delay time from the reception of the target TCI state. In some example embodiments, the first device 110 may utilize the target TCI state to transmit a first UL signal or channel with the handover delay time from the reception of the target TCI state.

[0129] In some example embodiments, based on a PL prediction determined to be associated with at least one target RS of the UL transmission, the first device 110 may determine the transmission delay time by excluding at least one PL measurement delay based on the received indication. The first device 110 may then transmit the UL transmission (235) to the second device 120 with the transmission delay time. The second device 120 may receive the UL transmission (240) from the first device 110.

[0130] In some example embodiments, if the first device 110 has indicated capability information to the second device 120—for example, if the first device 110 has indicated that it can predict PL for one or more RSs or has already predicted PL for one or more RSs, and the RSs are included in the target TCI state indicated by the second device 120 (the first device 110 is switched to the target TCI state)—then the first device 110 can transmit the first UL signal / channel in the target TCI state, wherein at least one path loss estimation related component that contributes to delay calculation is excluded. The at least one path loss estimation related component may correspond to at least one PL measurement delay.

[0131] In some example embodiments, at least one PL measurement delay is based on at least one of the following: when the target TCI state is unknown, the time from the measurement of the Layer 1 RS Received Power (L1-RSRP) to the transmission of the first PL RS; or when the target TCI state is known, the time from the decoding of the Media Access Control (MAC) Control Element (CE) command by the first device 110 to the transmission of the first PL RS. For example, conventionally, when a PDSCH carrying a MAC-CE activation command is received on the serving cell in time slot n, the UE should be able to [perform the measurement] in time slot n+T. HARQ + + NM (T first_target-PL-RS +4 T target_PL-RS + 2ms) / NR Time slot length In this process, uplink signals are transmitted in the target TCI state. The PL measurement delay to be excluded may include T... first_target-PL-RS T first_target-PL-RS When the target TCI state is unknown, the time from L1-RSRP measurement to the first path loss RS transmission time is either the time from the UE decoding of the MAC CE command to the first path loss RS transmission time when the target TCI state is unknown, or the time from the UE decoding of the MAC CE command to the first path loss RS transmission time when the target TCI state is known.

[0132] In some example embodiments, at least one PL measurement delay is the period of the target PL RS, for example, the period of the target path loss reference signal when the PL-RS is associated with the serving cell. The target path loss reference signal would be the SSB or NZPCSI-RS. The PL measurement delays to be excluded may include 4 T target_PL-RS T target_PL-RS This is the period of the target path loss reference signal when the PL-RS is associated with the serving cell; the target path loss reference signal will be either SSB or NZP CSI-RS. Alternatively, it is the period of the target path loss reference signal when the PL-RS is associated with a PCI different from the serving cell; in this case, the target path loss reference signal will be SSB. In some examples, T... first_target-PL-RS and 4 T target_PL-RS One or both of these can be excluded from delayed computation.

[0133] In some example embodiments, a PL prediction period can be configured for the first device 110. The first device 110 can receive the configuration of the PL prediction period from the second device 120.

[0134] In some example embodiments, the first device 110 may be triggered by the network side to perform PL prediction. The first device 110 may receive a trigger for performing PL prediction from the second device 120.

[0135] In one example embodiment, the first device 110 in any of the embodiments herein may be a MAC CE, RRC message, or uplink control message provided using PUSCH / PUCCH signaling. The first device 110 may receive from the second device 120 a configuration for performing PL prediction on an RS sequence associated with a TCI state sequence.

[0136] In one example embodiment, capability information is transmitted in a MAC CE, RRC message, or UL control message.

[0137] In some example embodiments, at least one target RS includes at least one of the following: a Synchronization Signal Block (SSB), a Channel State Information RS (CSI-RS), or an RS associated with QCL type D when the target TCI state includes two RSs. In one example, the predicted RS for path loss estimation may be one of the SSB / CSI-RS. In another example, the predicted RS for path loss estimation may be one of the SSB / CSI-RS, and if the target TCI includes two RSs, the predicted RS is QCL type D.

[0138] In some example embodiments, the first device 110 has a UE-side ML model and can use the ML model to perform PL prediction associated with at least one target RS in the target TCI state. The ML model can be, for example, a neural network for PL prediction.

[0139] In one example, the first device 110 can be configured to perform PL estimation for an RS sequence associated with a TCI state sequence.

[0140] Figure 3 A flowchart of an example method 300 implemented at a first device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 The angle description method 300 of the first device 110 in the middle.

[0141] At block 310, the first device 110 transmits capability information to the second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching.

[0142] At block 320, the first device 110 receives from the second device at least one of the following: a TCI switching command for the target transmission configuration indicator (TCI) state, or an indication for transmission uplink transmission.

[0143] At block 330, the first device 110 determines, based on the received TCI switching command or the received indication, to exclude at least one path loss measurement delay from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

[0144] In some example embodiments, method 300 further includes: performing a path loss prediction based on determining that it is associated with at least one target reference signal in the target TCI state; determining a handover delay time based on the received TCI handover command by excluding at least one path loss measurement delay; and switching to the target TCI state with the handover delay time from the reception of the target TCI state.

[0145] In some example embodiments, method 300 further includes: performing a path loss prediction based on determining at least one target reference signal associated with the uplink transmission, determining a transmission delay time based on the received indication by excluding at least one path loss measurement delay, and transmitting the uplink transmission to a second device with the transmission delay time.

[0146] In some example embodiments, capability information indicates the ability to perform path loss prediction associated with a configured set of reference signals; and / or the capability information also indicates the ability to perform uplink transmission-based path loss prediction associated with one or more reference signals in the configured set of reference signals.

[0147] In some example embodiments, the configured set of reference signals includes at least one of the following: a list of reference signals configured by Radio Resource Control (RRC), one or more reference signals associated with a first beam set, the first beam set being predicted from beams in a second beam set, at least one reference signal associated with at least one TCI state in a TCI state list, at least one reference signal associated with at least one TCI state in an active TCI state list, or at least one reference signal associated with at least one uplink signal, the at least one uplink signal being used as a reference for uplink transmission.

[0148] In some example embodiments, method 300 further includes performing path loss prediction associated with a configured set of reference signals.

[0149] In some example embodiments, the ability to perform path loss prediction associated with one or more reference signals associated with the first beam set indicates at least one of the following: the first device is capable of performing path loss prediction for all reference signals associated with the first beam set; the first device is capable of performing path loss prediction for a subset of reference signals associated with the first beam set; the first device is incapable of performing path loss prediction for at least one reference signal in the first beam set; and a bitmap, wherein each bit corresponds to a reference signal in the first beam set and indicates whether the first device is capable of performing path loss prediction for the corresponding reference signal.

[0150] In some example embodiments, the ability to perform path loss prediction for prediction-based beam switching includes the ability to perform path loss prediction for TCI state switching.

[0151] In some example embodiments, method 300 further includes: upon receiving a TCI switching command for a target TCI state, performing path loss prediction associated with at least one of the following: a reference signal included in the target TCI state, a quasi-co-location (QCL) information reference signal in the target TCI state, or a QCL source reference of a reference signal in the target TCI state.

[0152] In some example embodiments, the capability information also indicates the time delay associated with the path loss prediction.

[0153] In some example embodiments, the capability information also indicates at least one of the following: the ability to perform path loss prediction based on a second beam set used to predict a first beam set, or an indication of at least one reference signal in the second beam set.

[0154] In some example embodiments, method 300 further includes performing path loss prediction associated with at least one reference signal in the second beam set.

[0155] In some example embodiments, method 300 further includes receiving a configuration from a second means for performing path loss prediction using at least one reference signal from a second beam set.

[0156] In some example embodiments, the first device is also configured to perform path loss prediction associated with a particular set of reference signals configured for path loss prediction.

[0157] In some example embodiments, the first device is also configured to: transmit a request to the second device for a specific set of reference signals for path loss prediction; and configure to receive the specific set of reference signals from the second device.

[0158] In some example embodiments, the capability information also indicates the ability to perform path loss prediction associated with at least one reference signal in the candidate target TCI state.

[0159] In some example embodiments, the first device is further configured to: perform path loss prediction associated with at least one reference signal among the candidate target TCI states, based on a received TCI switching command for a target TCI state.

[0160] In some example embodiments, the first device is further configured to: perform path loss prediction associated with at least one target reference signal in the target TCI state, based on a received TCI switching command for the target TCI state.

[0161] In some example embodiments, method 300 further includes: using the target TCI state to transmit a first uplink signal or channel with a switching delay time from the reception of the target TCI state.

[0162] In some example embodiments, at least one path loss measurement delay is based on at least one of the following: when the target TCI state is unknown, the time from the measurement of the Layer 1 Reference Signal Received Power (L1-RSRP) to the transmission of the first path loss reference signal; when the target TCI state is known, the time from the decoding of the Media Access Control (MAC) Control Element (CE) command by the first device to the transmission of the first path loss reference signal; or the period of the target path loss reference signal.

[0163] In some example embodiments, method 300 further includes receiving from the second device at least one of the following: a configuration of a path loss prediction period, a triggering of path loss prediction, or a configuration for performing path loss prediction for a reference signal sequence associated with a TCI state sequence.

[0164] In some example implementations, capability information is transmitted in MAC CE, RRC messages, or uplink control messages.

[0165] In some example embodiments, at least one target reference signal includes at least one of the following: a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), or a reference signal associated with QCL type D when the target TCI state includes two reference signals.

[0166] In some example embodiments, the first device is further configured to use a machine learning model to perform path loss prediction associated with at least one target reference signal in the target TCI state.

[0167] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0168] In some example embodiments, a first means capable of performing any of method 300 (e.g., Figure 1 The first device 110 (TO DO: Please confirm with the investigator) may include components for performing the corresponding operations of method 300. The components may be implemented in any suitable form. For example, the components may be implemented in a circuit system or a software module. The first device may be implemented as... Figure 1 The first device 110 or included in Figure 1 In the first device 110.

[0169] In some example embodiments, the first device includes: a component for transmitting capability information to the second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching; a component for receiving from the second device at least one of the following: a TCI switching command for a target transmission configuration indicator (TCI) state, or an indication to transmit uplink transmission; and a component for determining, based on the received TCI switching command or the received indication, at least one path loss measurement delay to exclude from the switching delay time for the target TCI state and / or the transmission delay time for uplink transmission.

[0170] In some example embodiments, the first apparatus further includes: components for performing a path loss prediction based on determining at least one target reference signal associated with the target TCI state, determining a handover delay time by excluding at least one path loss measurement delay based on the received TCI handover command, and components for switching to the target TCI state with a handover delay time from the reception of the target TCI state.

[0171] In some example embodiments, the first device further includes: components for performing a path loss prediction based on determining at least one target reference signal associated with the uplink transmission, determining a transmission delay time by excluding at least one path loss measurement delay based on the received instruction, and components for transmitting the uplink transmission to the second device with the transmission delay time.

[0172] In some example embodiments, capability information indicates the ability to perform path loss prediction associated with a configured set of reference signals; and / or the capability information also indicates the ability to perform uplink transmission-based path loss prediction associated with one or more reference signals in the configured set of reference signals.

[0173] In some example embodiments, the configured set of reference signals includes at least one of the following: a list of reference signals configured by Radio Resource Control (RRC), one or more reference signals associated with a first beam set, the first beam set being predicted from beams in a second beam set, at least one reference signal associated with at least one TCI state in a TCI state list, at least one reference signal associated with at least one TCI state in an active TCI state list, or at least one reference signal associated with at least one uplink signal, the at least one uplink signal being used as a reference for uplink transmission.

[0174] In some example embodiments, the first apparatus further includes a component for performing path loss prediction associated with a configured set of reference signals.

[0175] In some example embodiments, the ability to perform path loss prediction associated with one or more reference signals associated with the first beam set indicates at least one of the following: the first device is capable of performing path loss prediction for all reference signals associated with the first beam set; the first device is capable of performing path loss prediction for a subset of reference signals associated with the first beam set; the first device is incapable of performing path loss prediction for at least one reference signal in the first beam set; and a bitmap, wherein each bit corresponds to a reference signal in the first beam set and indicates whether the first device is capable of performing path loss prediction for the corresponding reference signal.

[0176] In some example embodiments, the ability to perform path loss prediction for prediction-based beam switching includes the ability to perform path loss prediction for TCI state switching.

[0177] In some example embodiments, the first apparatus further includes: a component for performing path loss prediction associated with at least one of the following, based on a received TCI switching command for a target TCI state: a reference signal included in the target TCI state, a quasi-co-location (QCL) information reference signal in the target TCI state, or a QCL source reference of the reference signal in the target TCI state.

[0178] In some example embodiments, the capability information also indicates the time delay associated with the path loss prediction.

[0179] In some example embodiments, the capability information also indicates at least one of the following: the ability to perform path loss prediction based on a second beam set used to predict a first beam set, or an indication of at least one reference signal in the second beam set.

[0180] In some example embodiments, the first device further includes a component for performing path loss prediction associated with at least one reference signal in the second beam set.

[0181] In some example embodiments, the first device further includes: a component for receiving configuration from the second device, configured to perform path loss prediction using at least one reference signal from the second beam set.

[0182] In some example embodiments, the first apparatus further includes: a component for performing path loss prediction associated with a particular set of reference signals configured for path loss prediction.

[0183] In some example embodiments, the first device further includes: components for transmitting a request to the second device for a specific set of reference signals for path loss prediction; and components for configuring the specific set of reference signals to be received from the second device.

[0184] In some example embodiments, the capability information also indicates the ability to perform path loss prediction associated with at least one reference signal in the candidate target TCI state.

[0185] In some example embodiments, the first apparatus further includes a component for performing path loss prediction associated with at least one reference signal among candidate target TCI states based on a received TCI switching command for a target TCI state.

[0186] In some example embodiments, the first apparatus further includes a component for performing path loss prediction associated with at least one target reference signal in the target TCI state based on receiving a TCI switching command for the target TCI state.

[0187] In some example embodiments, the first apparatus further includes a component for transmitting a first uplink signal or channel using the target TCI state with a switching delay time from the reception of the target TCI state.

[0188] In some example embodiments, at least one path loss measurement delay is based on at least one of the following: when the target TCI state is unknown, the time from the measurement of the Layer 1 Reference Signal Received Power (L1-RSRP) to the transmission of the first path loss reference signal; when the target TCI state is known, the time from the decoding of the Media Access Control (MAC) Control Element (CE) command by the first device to the transmission of the first path loss reference signal; or the period of the target path loss reference signal.

[0189] In some example embodiments, the first device further includes a component for receiving at least one of the following from the second device: a configuration of a path loss prediction period, a triggering of path loss prediction, or a configuration for performing path loss prediction for a reference signal sequence associated with a TCI state sequence.

[0190] In some example implementations, capability information is transmitted in MAC CE, RRC messages, or uplink control messages.

[0191] In some example embodiments, at least one target reference signal includes at least one of the following: a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), or a reference signal associated with QCL type D when the target TCI state includes two reference signals.

[0192] In some example embodiments, the first device further includes a component for using a machine learning model to perform path loss prediction associated with at least one target reference signal in the target TCI state.

[0193] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0194] Figure 4 This is a simplified block diagram of a device 400 suitable for implementing an example embodiment of the present disclosure. The device 400 can be provided to implement a communication device, for example, such as... Figure 1The first device 110 or the second device 120 shown. As shown, the device 400 includes one or more processors 410, one or more memories 420 coupled to the processors 410, and one or more communication modules 440 coupled to the processors 410.

[0195] Communication module 440 is used for bidirectional communication. Communication module 440 has one or more communication interfaces to facilitate communication with one or more other modules or devices. The communication interface can represent any interface required for communication with other network elements. In some example embodiments, communication module 440 may include at least one antenna.

[0196] As a non-limiting example, processor 410 can be any type suitable for a local technology network and can include one or more of the following: general-purpose computer, special-purpose computer, microprocessor, digital signal processor (DSP), and processor based on a multi-core processor architecture. Device 400 can have multiple processors, such as application-specific integrated circuit chips that are time-dependent on a clock of a synchronous main processor.

[0197] Memory 420 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 424, electrically programmable read-only memory (EPROM), flash memory, hard disk, optical disc (CD), digital video disc (DVD), optical disc, laser disc, and other magnetic and / or optical storage. Examples of volatile memories include, but are not limited to, random access memory (RAM) 422 and other volatile memories that will not persist for the duration of a power outage.

[0198] Computer program 430 includes computer-executable instructions that are executed by an associated processor 410. The instructions of program 430 may include instructions for performing operations / actions of some example embodiments of this disclosure. Program 430 may be stored in memory (e.g., ROM 424). Processor 410 can perform any suitable actions and processes by loading program 430 into RAM 422.

[0199] The exemplary embodiments of this disclosure can be implemented by program 430, such that device 400 can perform as described in the reference. Figures 2 to 3 Any process discussed in this disclosure. Exemplary embodiments of this disclosure may also be implemented by hardware or by a combination of software and hardware.

[0200] In some example embodiments, program 430 may be tangibly contained in a computer-readable medium, which may be included in device 400 (such as memory 420) or other storage device accessible by device 400. Device 400 may load program 430 from the computer-readable medium into RAM 422 for execution. In some example embodiments, the computer-readable medium may include any type of non-transitory storage medium, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. As used herein, the term "non-transitory" is a limitation on the medium itself (i.e., tangible, not tactile), rather than a limitation on the persistence of data storage (e.g., RAM and ROM).

[0201] Figure 5 An example of a computer-readable medium 500 is shown, which may be in the form of a CD, DVD, or other optical storage disc. A program 430 is stored on the computer-readable medium 500.

[0202] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are illustrated and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, as non-limiting examples, the blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0203] Some exemplary embodiments of this disclosure also provide at least one computer program product tangibly stored on a computer-readable medium, such as a non-transitory computer-readable medium. The computer program product includes computer-executable instructions that execute in a device on a target physical or virtual processor, such as those included in a program module, to perform any of the methods described above. Typically, a program module includes routines, programs, libraries, objects, classes, components, data structures, etc., that perform a particular task or implement a particular abstract data type. In various embodiments, the functionality of a program module can be combined or split among program modules as needed. The machine-executable instructions for a program module can execute within a local or distributed device. In a distributed device, the program module can reside in both local and remote storage media.

[0204] Program code used to perform the methods of this disclosure may be written in any combination of one or more programming languages. The program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a stand-alone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0205] In the context of this disclosure, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, etc.

[0206] Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination thereof. More specific examples of computer-readable storage media will include electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0207] Furthermore, although operations are described in a specific order, this should not be construed as requiring that such operations be performed in the specific order shown or sequentially, or that all shown operations be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the discussion above, these details should not be construed as limiting the scope of this disclosure, but rather as descriptions of features that may be specific to particular embodiments. Unless explicitly stated otherwise, certain features described in the context of a single embodiment may also be implemented in combination in a single embodiment. Conversely, unless explicitly stated otherwise, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0208] Although this disclosure has been described in language specific to structural features and / or methodological actions, it should be understood that the disclosure as defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are disclosed as exemplary forms for implementing the claims.

Claims

1. A first device, comprising: At least one processor; as well as At least one memory stores instructions that, when executed by the at least one processor, cause the first device to at least: Transmit capability information to the second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching. Receive at least one of the following from the second device: - A TCI switching command for the target transport configuration indicator (TCI) status, or - Instructions for transmitting uplink data; and Based on the received TCI switching command or the received indication, at least one path loss measurement delay is determined to be excluded from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

2. The first device according to claim 1, wherein the first device is configured to: Path loss prediction is performed based on the determination of at least one target reference signal associated with the target TCI state. Based on the received TCI handover command, the handover delay time is determined by excluding the delay of the at least one path loss measurement. The system switches to the target TCI state with a switching delay time from the reception of the target TCI state.

3. The first device according to claim 1, wherein the first device is configured to: Path loss prediction is performed based on the path loss prediction associated with at least one target reference signal determined for the uplink transmission. Based on the received indication, the transmission delay time is determined by excluding at least one path loss measurement delay, and The uplink transmission is transmitted to the second device with the aforementioned transmission delay time.

4. The first apparatus of claim 1, wherein the capability information indicates the capability to perform path loss prediction associated with a configured set of reference signals; and / or The capability information also indicates the ability to perform uplink transmission-based path loss prediction associated with one or more reference signals in the configured set of reference signals.

5. The first apparatus according to claim 4, wherein the configured set of reference signals includes at least one of the following: The list of reference signals configured by Radio Resource Control (RRC). One or more reference signals associated with a first beam set, which is predicted from beams in a second beam set. At least one reference signal associated with at least one TCI state in the TCI state list. At least one reference signal associated with at least one TCI state in the active TCI state list, or At least one reference signal associated with at least one uplink signal, which is used as a reference for uplink transmission.

6. The first apparatus of claim 4 or 5, wherein the capability indication for performing path loss prediction associated with a configured set of reference signals: the first apparatus is capable of performing path loss prediction associated with the configured set of reference signals, and the first apparatus is further configured such that: Perform the path loss prediction associated with the set of reference signals configured.

7. The first apparatus of claim 5, wherein the capability to perform path loss prediction associated with one or more reference signals associated with the first beam set indicates at least one of the following: The first device is capable of performing path loss prediction for all reference signals associated with the first beam set. The first device is capable of performing path loss prediction for a subset of reference signals associated with the first beam set. The first device is unable to perform path loss prediction for at least one reference signal in the first beam set. A bitmap, wherein each bit corresponds to a reference signal in the first beam set and indicates whether the first device is capable of performing path loss prediction for the corresponding reference signal.

8. The first apparatus according to any one of claims 1 to 7, wherein the capability to perform path loss prediction for predicted beam switching includes: The ability to predict path loss during TCI state transitions.

9. The first apparatus of claim 8, wherein the capability to perform path loss prediction for TCI state transitions indicates that the first apparatus is capable of performing path loss prediction for TCI state transitions, and wherein the first apparatus is configured such that: Based on the received TCI switching command for the target TCI state, perform the path loss prediction associated with at least one of the following: The reference signal included in the target TCI state, The quasi-co-address (QCL) information reference signal in the target TCI state, or The QCL source reference of the reference signal in the target TCI state.

10. The first apparatus according to any one of claims 1 to 9, wherein the capability information further indicates a time delay associated with the path loss prediction.

11. The first device according to any one of claims 1 to 10, wherein the capability information further indicates at least one of the following: Based on the ability to perform path loss prediction using the second beam set, the second beam set is used to predict the first beam set, or Indication of at least one reference signal in the second beam set.

12. The first apparatus of claim 11, wherein the capability information further indicates that the first apparatus is capable of performing path loss prediction associated with at least one reference signal for the second beam set, and wherein the first apparatus is further configured to: Perform the path loss prediction associated with at least one reference signal in the second beam set.

13. The first device according to claim 11 or 12, wherein the first device is further configured to: Receive configuration from the second device for performing path loss prediction using at least one reference signal from the second beam set.

14. The first device according to any one of claims 1 to 13, wherein the first device is further configured to: Perform the path loss prediction associated with a specific set of reference signals configured for path loss prediction.

15. The first device according to claim 14, wherein the first device is further configured to: Transmit a request to the second device for a specific set of reference signals used for path loss prediction; and Configuration for receiving the specific set of reference signals from the second device.

16. The first apparatus according to any one of claims 1 to 15, wherein the capability information further indicates the capability to perform path loss prediction associated with at least one reference signal in the candidate target TCI state.

17. The first device according to claim 16, wherein the first device is further configured to: Based on the received TCI switching command for the target TCI state, the path loss prediction associated with at least one reference signal in the candidate target TCI state is performed.

18. The first device according to any one of claims 1 to 17, wherein the first device is further configured to: Based on the received TCI switching command for the target TCI state, the path loss prediction associated with at least one target reference signal in the target TCI state is performed.

19. The first device according to any one of claims 1 to 18, wherein the first device is configured to: The first uplink signal or channel is transmitted using the target TCI state, with the switching delay time from the reception of the target TCI state.

20. The first apparatus according to any one of claims 1 to 19, wherein the at least one path loss measurement delay is based on at least one of the following: When the target TCI state is unknown, the time from the measurement of the Layer 1 reference signal received power (L1-RSRP) to the transmission of the first path loss reference signal is: When the target TCI state is known, the time from when the Media Access Control (MAC) control element (CE) command is decoded by the first device to when the first path loss reference signal is transmitted, or The period of the target path loss reference signal.

21. The first device according to any one of claims 1 to 20, wherein the first device is further configured to: Receive at least one of the following from the second device: Configuration of the path loss prediction period. Triggering the execution of the path loss prediction, or Configuration for performing path loss prediction on a reference signal sequence associated with a TCI state sequence.

22. The first apparatus according to any one of claims 1 to 21, wherein the capability information is transmitted in a MAC CE, RRC message or an uplink control message.

23. The first device according to any one of claims 1 to 22, wherein the at least one target reference signal comprises at least one of the following: Synchronization Signal Block (SSB). Channel State Information Reference Signal (CSI-RS), or When the target TCI state includes two reference signals, the reference signal associated with QCL type D.

24. The first device according to any one of claims 1 to 23, wherein the first device is further configured to: A machine learning model is used to perform the path loss prediction associated with at least one target reference signal in the target TCI state.

25. The first device according to any one of claims 1 to 24, wherein the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

26. A method comprising: The first device transmits capability information to the second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching. Receive at least one of the following from the second device: - A TCI switching command for the target transport configuration indicator (TCI) status, or - Instructions for transmitting uplink data; and Based on the received TCI switching command or the received indication, at least one path loss measurement delay is determined to be excluded from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

27. A first device, comprising: A component for transmitting capability information to a second device, the capability information indicating at least one of the following: the capability to perform path loss prediction, an indication to perform uplink transmission based on path loss prediction, or the capability to perform path loss prediction for prediction-based beam switching. Components for receiving at least one of the following from the second device: - A TCI switching command for the target transport configuration indicator (TCI) status, or - Indication for uplink transmission; as well as A component for determining, based on the received TCI switching command or the received indication, to exclude at least one path loss measurement delay from the switching delay time for the target TCI state and / or the transmission delay time for the uplink transmission.

28. A computer-readable medium comprising instructions stored thereon for causing a device to perform at least the method according to claim 26.

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