WO2025209693A1

WO2025209693A1 - Method and device for pathloss prediction

Info

Publication number: WO2025209693A1
Application number: PCT/EP2025/053203
Authority: WO
Inventors: Timo Koskela; Juha Pekka Karjalainen; Sami-Jukka Hakola; Keeth Saliya Jayasinghe LADDU; Mihai Enescu
Original assignee: Nokia Technologies Oy
Current assignee: Nokia Technologies Oy
Priority date: 2024-04-04
Filing date: 2025-02-07
Publication date: 2025-10-09
Anticipated expiration: 2026-10-04
Also published as: GB2640160A

Abstract

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

Description

METHOD AND DEVICE FOR PATHLOSS PREDICTION

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority from, and the benefit of, GB Application No. 2404770.6, filed April 4, 2024, the contents of which are hereby incorporated by reference in their entirety.

FIELD

[0002] Various example embodiments of the present disclosure generally relate to the field of telecommunication and in particular, to methods, devices, apparatuses and computer readable storage medium for pathloss prediction for TCI state switching and/or UL transmission.

BACKGROUND

[0003] In the telecommunication industry, artificial intelligence/machine learning (AI/ML) models have been employed in telecommunication systems to improve the performance. For example, the 3rd Generation Partnership Project (3GPP) Release-18 started the study on Artificial Intelligence (AI)/Machine Learning (ML) for New Radio (NR) air interface. The goal is to explore the benefits of augmenting the air interface with features enabling improved support of AI/ML-based algorithms for enhanced performance and/or reduced complexity/overhead. Several use cases are considered to enable the identification of a common AI/ML framework, including functional requirements of AI/ML architecture, which could be used in subsequent projects. It also aims to identify areas where AI/ML could improve the performance of air-interface functions. Communication specification impact will be assessed to improve the overall understanding of what would be required to enable AI/ML techniques for the air interface.

SUMMARY

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

[0005] In a second aspect of the present disclosure, there is provided a method. The method comprises: transmitting, by a first apparatus and to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching; receiving, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission; and determining, based on the received TCI switching command or the received indication, exclusion of at least one path loss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

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

[0007] In a fourth aspect of the present disclosure, there is provided a computer readable medium. The computer readable medium comprises instructions stored thereon for causing an apparatus to perform at least the method according to the second aspect. [0008] It is to be understood that the Summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Some example embodiments will now be described with reference to the accompanying drawings, where:

[0010] FIG. 1 illustrates an example communication environment in which example embodiments of the present disclosure can be implemented;

[0011] FIG. 2 illustrates a flowchart of a signaling flow for pathloss prediction in accordance with some example embodiments of the present disclosure;

[0012] FIG. 3 illustrates a flowchart of a method implemented at a first apparatus in accordance with some example embodiments of the present disclosure;

[0013] FIG. 4 illustrates a simplified block diagram of a device that is suitable for implementing example embodiments of the present disclosure; and

[0014] FIG. 5 illustrates a block diagram of an example computer readable medium in accordance with some example embodiments of the present disclosure.

[0015] Throughout the drawings, the same or similar reference numerals represent the same or similar element.

DETAILED DESCRIPTION

[0016] Principle of the present disclosure will now be described with reference to some example embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. Embodiments described herein can be implemented in various manners other than the ones described below.

[0017] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.

[0018] References in the present disclosure to “one embodiment,” “an embodiment,” “an example embodiment,” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0019] It shall be understood that although the terms “first,” “second,”..., etc. in front of noun(s) and the like 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 limit the order of the noun(s). For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.

[0020] As used herein, “at least one of the following: <a list of two or more elements>” and “at least one of <a list of two or more elements>” and similar wording, where the list of two or more elements are joined by “and” or “or”, mean at least any one of the elements, or at least any two or more of the elements, or at least all the elements.

[0021] As used herein, unless stated explicitly, performing a step “in response to A” does not indicate that the step is performed immediately after “A” occurs and one or more intervening steps may be included.

[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example 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 the terms “comprises”, “comprising”, “has”, “having”, “includes” and/or “including”, when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/ or combinations thereof.

[0023] As used in this application, the term “circuitry” may refer to one or more or all of the following:

(a) hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry) and

(b) combinations of hardware circuits and software, such as (as applicable):

(i) a combination of analog and/or digital hardware circuit(s) with software/firmware and

(ii) any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and

(c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.

[0024] This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and/or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.

[0025] As used herein, the term “communication network” refers to a network following any suitable communication standards, such as New Radio (NR), Long Term Evolution (LTE), LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed Packet Access (HSPA), Narrow Band Internet of Things (NB- loT) and so on. Furthermore, the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1G), the second generation (2G), 2.5G, 2.75G, the third generation (3G), the fourth generation (4G), 4.5G, the fifth generation (5G), the sixth generation (6G) communication protocols, and/or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will of course also be future type communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned system.

[0026] As used herein, the term “network device” refers to a node in a communication network via which a terminal device accesses the network and receives services therefrom. The network device may refer to a base station (BS) or an access point (AP), for example, a node B (NodeB or NB), an evolved NodeB (eNodeB or eNB), an NR NB (also referred to as a gNB), a Remote Radio Unit (RRU), a radio header (RH), a remote radio head (RRH), a relay, an Integrated Access and Backhaul (IAB) node, a low power node such as a femto, a pico, a non-terrestrial network (NTN) or non-ground network device such as a satellite network device, a low earth orbit (LEO) satellite and a geosynchronous earth orbit (GEO) satellite, an aircraft network device, and so forth, depending on the applied terminology and technology. In some example embodiments, radio access network (RAN) split architecture comprises a Centralized Unit (CU) and a Distributed Unit (DU) at an IAB donor node. An IAB node comprises a Mobile Terminal (IAB-MT) part that behaves like a UE toward the parent node, and a DU part of an IAB node behaves like a base station toward the next-hop IAB node.

[0027] The term “terminal device” refers to any end device that may be capable of wireless communication. By way of example rather than limitation, a terminal device may also be referred to as a communication device, user equipment (UE), a Subscriber Station (SS), a Portable Subscriber Station, a Mobile Station (MS), or an Access Terminal (AT). The terminal device may include, but not limited to, a mobile phone, a cellular phone, a smart phone, voice over IP (VoIP) phones, wireless local loop phones, a tablet, a wearable terminal device, a personal digital assistant (PDA), portable computers, desktop computer, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback appliances, vehicle-mounted wireless terminal devices, wireless endpoints, mobile stations, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), USB dongles, smart devices, wireless customer-premises equipment (CPE), an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts), a consumer electronics device, a device operating on commercial and/or industrial wireless networks, and the like. The terminal device may also correspond to a Mobile Termination (MT) part of an IAB node (e.g., a relay node). In the following description, the terms “terminal device”, “communication device”, “terminal”, “user equipment” and “UE” may be used interchangeably.

[0028] As used herein, the term “resource,” “transmission resource,” “resource block,” “physical resource block” (PRB), “uplink resource,” or “downlink resource” may refer to any resource for performing a communication, for example, a communication between a terminal device and a network device, such as a resource in time domain, a resource in frequency domain, a resource in space domain, a resource in code domain, or any other combination of the time, frequency, space and/or code domain resource enabling a communication, and the like. In the following, unless explicitly stated, a resource in both frequency domain and time domain will be used as an example of a transmission resource for describing some example embodiments of the present disclosure. It is noted that example embodiments of the present disclosure are equally applicable to other resources in other domains.

[0029] As used herein, the term “model” is referred to as an association between an input and an output learned from training data, and thus a corresponding output may be generated for a given input after the training. The generation of the model may be based on machine learning (ML) techniques. The machine learning techniques may also be referred to as artificial intelligence (Al) techniques. In general, a machine learning model can be built, which receives input information and makes predictions based on the input information. For example, a classification model may predict a class of the input information among a predetermined set of classes. As used herein, “model” may also be referred to as “machine learning model”, “learning model”, “machine learning network”, or “learning network,” which are used interchangeably herein.

[0030] To facilitate understanding of the terminologies, some definitions of the list of terminologies used for AI/ML are provided below.

[0031] AI/ML model: A data driven algorithm that applies AI/ML techniques to generate a set of outputs based on a set of inputs.

[0032] AI/ML model delivery: A generic term referring to delivery of an AI/ML model from one entity to another entity in any manner. Note: An entity could mean a network node/function (e.g., gNB, location management function (LMF), etc.), UE, proprietary server, etc.

[0033] AI/ML model inference: A process of using a trained AI/ML model to produce a set of outputs based on a set of inputs.

[0034] AI/ML model testing: A subprocess of training, to evaluate the performance of a final AI/ML model using a dataset different from one used for model training and validation. Differently from AI/ML model validation, testing does not assume subsequent tuning of the model.

[0035] AI/ML model training: A process to train an AI/ML Model [by learning the input/output relationship] in a data driven manner and obtain the trained AI/ML Model for inference. [0036] AI/ML model transfer: Delivery of an AI/ML model over the air interface in a manner that is not transparent to 3 GPP signalling, either parameters of a model structure known at the receiving end or a new model with parameters. Delivery may contain a full model or a partial model.

[0037] AI/ML model validation: A subprocess of training, to evaluate the quality of an AI/ML model using a dataset different from one used for model training, that helps selecting model parameters that generalize beyond the dataset used for model training.

[0038] Data collection: A process of collecting data by the network nodes, management entity, or UE for the purpose of AI/ML model training, data analytics and inference.

[0039] Functionality identification: A process/method of identifying an AI/ML functionality for the common understanding between the network and the UE. Note: Information regarding the AI/ML functionality may be shared during functionality identification. Where AI/ML functionality resides depends on the specific use cases and sub use cases.

[0040] Model activation: enable an AI/ML model for a specific function.

[0041] Model deactivation: disable an AI/ML model for a specific function.

[0042] Model download: Model transfer from the network to UE.

[0043] Model identification: A process/method of identifying an AI/ML model for the common understanding between the network (NW) and the UE. Note: The process/method of model identification may or may not be applicable. Note: Information regarding the AI/ML model may be shared during model identification.

[0044] Model monitoring: A procedure that monitors the inference performance of the AI/ML model.

[0045] Model parameter update: Process of updating the model parameters of a model. [0046] Model selection: The process of selecting an AI/ML model for activation among multiple models for the same AI/ML enabled feature. Note: Model selection may or may not be carried out simultaneously with model activation.

[0047] Model switching: Deactivating a currently active AI/ML model and activating a different AI/ML model for a specific function.

[0048] Model update: Process of updating the model parameters and/or model structure of a model.

[0049] Model upload: Model transfer from UE to the network.

[0050] Offline field data: The data collected from field and used for offline training of the AI/ML model. [0051] Offline training: An AI/ML training process where the model is trained based on collected dataset, and where the trained model is later used or delivered for inference. Note: This definition only serves as a guidance. There may be cases that may not exactly conform to this definition but could still be categorized as offline training by commonly accepted conventions.

[0052] Online field data: The data collected from field and used for online training of the AI/ML model.

[0053] Online training: An AI/ML training process where the model being used for inference) is (typically continuously) trained in (near) real-time with the arrival of new training samples. Note: the notion of (near) real-time vs. non real-time is context- dependent and is relative to the inference time-scale. Note: This definition only serves as a guidance. There may be cases that may not exactly conform to this definition but could still be categorized as online training by commonly accepted conventions. Note: Fine- tuning/re-training may be done via online or offline training. (This note could be removed when we define the term fine-tuning.)

[0054] Semi-supervised learning: A process of training a model with a mix of labelled data and unlabelled data.

[0055] Supervised learning: A process of training a model from input and its corresponding labels.

[0056] Unsupervised learning: A process of training a model without labelled data.

[0057] UE-side (AI/ML) model: An AI/ML Model whose inference is performed entirely at the UE.

[0058] Network-side (AI/ML) model: An AI/ML Model whose inference is performed entirely at the network.

[0059] One-sided (AI/ML) model: A UE-side (AI/ML) model or a Network-side (AI/ML) model.

[0060] Two-sided (AI/ML) model: A paired AI/ML Model(s) over which joint inference is performed, where joint inference comprises AI/ML Inference whose inference is performed jointly across the UE and the network, i.e, the first part of inference is firstly performed by UE and then the remaining part is performed by the gNB, or vice versa.

[0061] Proprietary-format models: ML models of vendor-/device-specific proprietary format, from 3GPP perspective. They are not mutually recognizable across vendors and hide model design information from other vendors when shared. Note: An example is a device-specific binary executable format.

[0062] Open-format models: ML models of specified format that are mutually recognizable across vendors and allow interoperability, from the 3GPP perspective. They are mutually recognizable between vendors and do not hide model design information from other vendors when shared.

[0063] FIG. 1 illustrates an example communication environment 100 in which example embodiments of the present disclosure can be implemented. It is to be understood that the elements shown in the communication system 100 are intended to represent main functions provided within the system. As such, the blocks shown in FIG. 1 reference specific elements in communication networks that provide these main functions. However, other network elements may be used to implement some or all of the main functions represented. Also, it is to be understood that not all functions of a communication network are depicted in FIG. 1. Rather, functions that facilitate an explanation of illustrative embodiments are represented. Further, the number of the elements shown in FIG. 1 is also for the purpose of illustrative only and there may be any number of elements.

[0064] As shown, the communication environment 100 comprises a plurality of communication devices, including one or more first apparatuses 110-1, 110-2, ..., 110-N (collectively or individually referred to as first apparatuses 110) and one or more second apparatuses 120. In the example of FIG. 1, the second apparatus 120 may include a network device, and the first apparatus 110 may include a terminal device. A serving area of the second apparatus 120 may be called a cell. The first apparatus 110 and the second apparatus 120 may operate in a radio access network (RAN). Although two terminal devices (e.g., first apparatuses) are illustrated, there may be more or less terminal devices within a serving area of a network device, and there may also be more network devices serving the terminal devices in the communication environment 100.

[0065] In the following, for the purpose of illustration, some example embodiments are described with the first apparatus 110 operating as a terminal device and the second apparatus 120 operating as a network device. However, in some example embodiments, operations described in connection with a terminal device may be implemented at a network device or other device, and operations described in connection with a network device may be implemented at a terminal device or other device.

[0066] In some example embodiments, if the first apparatus 110 is a terminal device and the second apparatus 120 is a network device, a link from the second apparatus 120 to the first apparatus 110 is referred to as a downlink (DL), and a link from the first apparatus 110 to the second apparatus 120 is referred to as an uplink (UL). In DL, the second apparatus 120 is a transmitting (TX) device (or a transmitter) and the first apparatus 110 is a receiving (RX) device (or a receiver). In UL, the first apparatus 110 is a TX device (or a transmitter) and the second apparatus 120 is a RX device (or a receiver). [0067] Communications in the communication environment 100 may be implemented according to any proper communication protocol(s), comprising, but not limited to, cellular communication protocols of the first generation (1G), the second generation (2G), the third generation (3G), the fourth generation (4G), the fifth generation (5G), the sixth generation (6G), and the like, wireless local network communication protocols such as Institute for Electrical and Electronics Engineers (IEEE) 802.11 and the like, and/or any other protocols currently known or to be developed in the future. Moreover, the communication may utilize any proper wireless communication technology, comprising 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 (OFDM), Discrete Fourier Transform spread OFDM (DFT-s-OFDM) and/or any other technologies currently known or to be developed in the future.

[0068] In some example embodiments, different AI/ML models may be configured to implement the same different algorithms in the communication environment 100. An AI/ML model 105 may sometimes be referred to as an Al model or an ML model for short. Inference, testing, training, and/or validation of an AI/ML model may be performed at one or more of the first apparatuses 110, the second apparatus 120, and/or other entities. In the example of FIG. 1, an AI/ML model 105 is illustrated to be deployed at the side of the first apparatus 110. An AI/ML model may be delivered from one entity to another entity in any manner. Delivery of an AI/ML model over the air interface in a manner that is not transparent to 3 GPP signalling, either parameters of a model structure known at the receiving end or a new model with parameters. Delivery may contain a full model or a partial model.

[0069] AI/ML based beam prediction and related functionality are introduced in the NR MIMO framework.

[0070] In some example embodiments related to Al-based beam management (BM), the AI/ML model 105 is configured for beam prediction. For Al-based beam management, there are proposed BM-specific use cases. BM-Case 1 is related to spatial-domain DL beam prediction for Set A of beams based on measurement results of Set B of beams. BM-Case2 is related to temporal DL beam prediction for Set A of beams based on the historic measurement results of Set B of beams. DL transmit (Tx) beam prediction can be configured for both UE-sided model and network (NW)-sided model.

[0071] For BM-Casel and BM-Case2, study necessity, benefit(s) and potential specification impact from the following additional aspects for Al model inference: how to perform beam indication of beams in Set A not in Set B.

[0072] For BM-Casel and BM-Case2 with a UE-side AI/ML model, study potential specification impact of Al model inference from the following additional aspects on top of previous agreements: indication of the associated Set A from network to UE, e.g., association/mapping of beams within Set A and beams within Set B if applicable; and beam indication from network for UE reception.

[0073] In some example embodiments, at least for BM-Casel with a UE-side AI/ML model, for Al model inference, the legacy TCI state mechanism can be used to perform beam indication of beams.

[0074] In the communication systems, the path loss RS related switching condition may be required for UL TCI state switching. The path loss RS related switching condition may be required for joint DL&UL TCI state switching.

[0075] For media access control control element (MAC-CE) based uplink TCI state switch delay, the following requirements apply for UL TCI state switch using separate UL TCI state or joint TCI state of unified TCI state switch framework.

[0076] In case that 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 different PCI satisfies the known cell condition defined in 8.16.1. If the known cell condition is not met, longer delay may be expected.

[0077] In case of joint TCI state switch, UE is not expected to transmit on UL before UE completes the DL and UL TCI state switch.

[0078] For separate UL TCI state switch or joint TCI state switch for PUCCH or PUSCH, or semi-persistent/aperiodic/periodic SRS, when beamCorrespondenceWithoutUL-BeamSweeping is set to 1, upon receiving PDSCH carrying MAC-CE activation command in slot n on serving cell, the UE shall perform the following operations as in Table 1.

Table 1

[0079] A unified TCI state framework is defined as where a common TCI/QCL framework is for both DL and UL. In unified TCI State (Rell7) framework, a single TCI state can be indicated to UE and this TCI state or rather RS(s) indicated by the TCI State are used for transmission and reception assumptions for PDCCH/PDSCH/CSI-RS and/or PUCCH/PUSCH/SRS. The use of unified TCI framework is extended to all S-DCI and M-DCI multi-TRP DL and UL transmission schemes developed in R16-R18 by allowed UE to have up to two joint DL/UL or separate DL and UL indicated TCI states.

[0080] In unified TCI state framework, the beam indication or rather TCI state indication (i.e. indication which TCI state is used for transmission and/or reception assumptions for signals and channels associated with the TCI State) has following steps:

1. For a serving cell, the unified TCI State type is configured to be either joint UL/DL or separate UL/DL. In joint UL/DL the indicated TCI State is used for uplink and downlink, and in separate the DL and UL are indicated separately (one TCI codepoint that is indicated in DCI may comprise DL TCI only, UL TCI only or DL and UL TCI states). If the TCI state type is joint, UE is configured with a single list of TCI states using RRC.

2. If the TCI state type is separate, UE is configured with a DL TCI State list and UL TCI State list. Configuration is done using RRC signaling while MAC CE selects and activates up to eight (in Rel-17) TCI codepoints of which one may become indicated via DCI. As said earlier, one TCI codepoint may comprise DL TCI state only, UL TCI state only or both DL and UL TCI states.

3. To indicate a TCI state (joint) or separate TCI States (UL and DL) network provides a TCI codepoint (a value in a DCI message) that corresponds to the TCI codepoint in the MAC CE that activated the TCI codepoint(s). Upon receiving the DCI based beam indication (a DCI codepoint) UE applies the indicated TCI States for the indicated channels (PDSCH, PDCCH/PUSCH/PUCCH).

[0081] The relevant Information Elements (IES) for TCI state are presented below: [0082] The IE TCI-State associates one or two DL reference signals with a corresponding quasi-colocation (QCL) type, as in Table 2:

Table 2: TCI-State information element

[0083] QCL-Info field descriptions are as follows in Table 3 and some conditions are indicated in Table 4.

Table 3 : TCI-State information element

Table 4

[0084] In TCI state switching to the new UL TCI State (in case of both joint DL/UL or separate DL/UL), the UE may require additional time for estimating the path loss associated with the target TCI State. This is regardless of whether the TCI state is known or unknown. For example, upon receiving PDSCH carrying MAC-CE activation command in slot n on serving cell, the UE shall be able to transmit uplink signal with the target TCI state in the slot RS + 2ms) / NR slot length.

[0085] In AI/ML based beam switching (or prediction-based beam switching), the UE may not have measured/estimated the path loss for the target TCI state since the RS set B (or the second set or the measurement RS set) is used to predict a target RS from the set A and the UE may not measure or measures the set A with low periodicity.

[0086] Typically, the UE is required to maintain for limited number of PL estimates, thus in order to efficiently leverage the prediction-based beam switching, the PL estimation requires enhancements.

[0087] In accordance with some example embodiments of the present disclosure, there is provided a solution for pathloss prediction for UE-side AI/ML model. A first apparatus (e.g., a terminal device) transmits to a second apparatus (e.g., a network device), capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching. Then if the first apparatus receives a transmission configuration indicator (TCI) switching command to a target TCI state or an indication to transmit an uplink transmission form the second apparatus, the first apparatus can determine to exclude at least one pathloss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

[0088] Through the solution, the PL estimation can be leveraged, so as to efficiently leverage the prediction-based beam switching. This can facilitate increased throughput due to faster switch for target UL TCI state and for performing uplink transmission.

[0089] Example embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0090] FIG. 2 illustrates a flowchart of a signaling flow 200 for pathloss prediction in accordance with some example embodiments of the present disclosure. For the purpose of discussion, reference is made to FIG. 1 to describe the signaling flow 200. As shown in FIG. 2, the signaling flow 200 involves the first apparatus 110 and the second apparatus 120. In some example embodiments, the first apparatus 110 may comprise or may be comprised in a terminal device, and the second apparatus 120 may be comprise or may be comprised in a network device (e.g., gNB, gNB CU or gNB DU, etc.). [0091] In the signaling flow 200, the first apparatus 110 transmits (205), to the second apparatus 120, capability information. The capability information indicates at least one of the following: capability of performing pathloss (PL) prediction, an indication of performing UL transmission based on PL prediction or capability of performing pathloss prediction for prediction-based beam switching. In some example embodiments, the capability information indicating PL related prediction may be optional. The UEs capability for performing 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 capability. As an example the capability (for pathloss prediction) may be included as part of supporting one or more features of prediction based beam management ( e.g. AI/ML based prediction).

[0092] The second apparatus 120 receives (210) the capability information and determine whether to switch the first apparatus 110 to a target TCI state or to indicate the first apparatus 110 to perform an UL transmission. The second apparatus 120 transmits (215), to the first apparatus 110, a TCI switching command to a target TCI state and/or an indication to transmit the transmission.

[0093] The first apparatus 110 receives (220), from the second apparatus 120, at least one of the TCI switching command to the target TCI state, or the indication to transmit an uplink transmission. The first apparatus 110 determines (225), based on the received TCI switching command or the received indication, exclusion of at least one pathloss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

[0094] In some example embodiments, the first apparatus 110 may perform an uplink transmission, at least partly, based on the performing (or performed) a pathloss prediction for the target reference signal for the uplink transmission. In other words, the UE may determine the target downlink reference signal for uplink transmission and perform path loss related prediction for the uplink transmission.

[0095] In some example embodiments, the path loss prediction or the capability of performing path loss related prediction may comprise of predicting (Ll-)RSRP value that may be used to derive a path loss value. The derived path loss value may be for at least one DL RS associated with uplink transmission.

[0096] In some example embodiments the prediction of an RSRP value used for path loss estimation or deriving the path loss estimate may comprise of multiple predictions or a single prediction.

[0097] In some example embodiments, the path loss prediction or the capability of performing path loss related prediction may comprise of predicting a path loss value.

[0098] In some example embodiments, the predicted path loss value or the derived path loss value based on the one or more predicted value ( e.g. Ll-RSRP) may be used to apply uplink power control for an uplink transmission. The uplink power control for an uplink transmission may be applied with respect to the at least one DL RS.

[0099] In some example embodiments, the predicted path loss value or the derived path loss value based on the one or more predicted value ( e.g. Ll-RSRP) may be used to apply uplink transmission power for the uplink transmission.

[0100] In some example embodiments, the uplink transmission may refer to at least one of the following: scheduling request transmission, PUSCH transmission, PUCCH transmission, SRS (sounding reference signal transmission), PRACH (Physical random access channel) transmission, Random access preamble transmission.

[0101] In some example embodiments, the capability information indicates capability of performing PL prediction associated with a configured set of RSs. In one example embodiment, the first apparatus 110 may indicate to the second apparatus 120 whether it is able to perform PL prediction for the one or more RS resources. In some example embodiments, the capability information indicates capability of performing UL transmission based PL prediction associated with one or more of set of configured RSs.

[0102] In some example embodiments, the capability of performing PL prediction may refer to capability of deriving path loss value based on prediction of at least one measurement result or value (e.g. RSRP value) that may be used to derive the path loss value with respect to at least one reference signal. In some example embodiments, the capability of performing PL prediction may refer to prediction of a path loss value with respect to the at least one reference signal.

[0103] In some example embodiments, the capability of performing PL prediction or the performing of PL prediction may comprise of prediction of uplink transmission power for an uplink transmission, wherein the uplink transmission may use a downlink reference signal as reference.

[0104] The configured set of RSs indicated in the capability information may be target reference signals for the PL prediction or for the target TCI state.

[0105] In some example embodiments, a TCI state may comprise or include a reference signal that may be used for path loss estimation. In some examples, the UE may determine to derive based on prediction or predict a path loss value (and or uplink transmission power) based on the reference signal included in the TCI state. The reference signal included in the TCI state may a path loss reference signal. The reference signal included in the TCI may be an SSB or CSI-RS.

[0106] In some example embodiments, if the UE has determined that is has predicted a path loss value or derived path loss value based on prediction or prediction uplink transmission power for an uplink transmission, it may determine to transmit the uplink signal using the predicted value. In some example, the UE may determine not to perform at least some measurements for path loss estimation if it has determined that is has predicted or derived the path loss (or uplink transmission power) for the uplink transmission (towards a target downlink reference signal).

[0107] In some example embodiments, the configured set of RSs may comprise a radio resource control (RRC) configured list of RSs or RS resources.

[0108] In some example embodiments, the configured set of RSs may comprise one or more RSs associated with a first set of beams which are to be predicted from beams in a second set of beams. The first set of beams is sometimes referred to as a prediction set or Set A in the AI/ML-based beam management use cases, and the second set of beams is sometimes referred to Set B in the beam management. For BM-Case 1, spatial-domain DL beam prediction for Set A of beams is performed based on measurement results of Set B of beams. For BM-Case2, temporal DL beam prediction for Set A of beams is performed based on the historic measurement results of Set B of beams. DL transmit (Tx) beam prediction can be configured for both UE-sided model and network (NW)-sided model.

[0109] In some example embodiments, the configured set of RSs may comprise at least one RS associated with at least one TCI state of a list of TCI states. In some example embodiments, the configured set of RSs may comprise at least one RS associated with at least one TCI state of a list of active TCI states. In some example embodiments, the configured set of RSs may comprise at least one RS associated with at least one UL signal used as reference for UL transmission.

[0110] In some example embodiments, if the capability of performing PL prediction associated with a configured set of RSs indicates that the first apparatus 110 is capable of performing PL prediction associated with the configured set of RSs, the first apparatus 110 may then perform the PL prediction associated with the configured set of RSs.

[OHl] In one example embodiment, the first apparatus 110 may indicate whether it is able to perform or has performed PL prediction for the one or more RSs of the configured prediction set (e.g., Set A). In one example embodiment, the first apparatus 110 may indicate whether it is able to perform or has performed PL prediction for the one or more RSs of the second set (e.g., Set B).

[0112] In some example embodiments, the capability of performing PL prediction associated with one or more RSs associated with the first set of beams may indicate that the first apparatus 110 is capable of performing PL prediction for all RSs associated with the first set of beams. That is, the first apparatus 110 may indicate that it is able to predict PL for all the RSs in the prediction set.

[0113] In some example embodiments, the capability of performing PL prediction associated with one or more RSs associated with the first set of beams may indicate that the first apparatus 110 is capable of performing PL prediction for a subset of RSs associated with the first set of beams. That is, the first apparatus 110 may indicate that it is able to predict PL for a subset of the RSs in the prediction set.

[0114] In some example embodiments, the capability of performing PL prediction associated with one or more RSs associated with the first set of beams may indicate that the first apparatus 110 is incapable of performing PL prediction for at least one RS in the first set of beams. That is, the first apparatus 110 may indicate that it is not able to predict PL for one or more RS in the prediction set.

[0115] In some example embodiments, the capability of performing PL prediction associated with one or more RSs associated with the first set of beams may indicate that a bitmap with each bit corresponding to a RS in the first set of beams and indicating whether the first apparatus 110 is capable of performing PL prediction for the corresponding RS or not. The signaling of the capability indication may comprise of a bit map wherein each bit position in the bitmap corresponds to the specific RSs.

[0116] In one example embodiment, the first apparatus 110 may indicate whether it is able to perform PL prediction for prediction based beam switching. In one example embodiment, the capability of performing PL prediction for prediction-based beam switching comprises capability of performing PL prediction for TCI state switching.

[0117] If the capability of performing PL prediction for TCI state switching indicates that the first apparatus 110 is capable of performing PL prediction for TCI state switching, in accordance with reception of the TCI switching command to the target TCI state, the first apparatus 110 may perform the PL prediction associated with at least one of the following: a RS included in the target TCI state, a QCL information reference signal in the target TCI state, or a QCL source reference of a RS in the target TCI state.

[0118] As an example, the first apparatus 110 may indicate to the second apparatus 120 whether it is able to perform prediction of PL for TCI state switching. Upon receiving the TCI switching command to the target TCI state, the first apparatus 110 may perform PL prediction associated one or more RSs included in the target TCI state. The one or more RSs included in the target TCI state may include PL RS or any of QCL information RS in the target TCI state. In some examples, upon receiving the switching command to the target TCI state, the first apparatus 110 may perform PL prediction associated QCL source RS of an RS included in the target TCI state.

[0119] In some example embodiments, the capability information further indicates a time delay associated with the PL prediction. That is, the PL estimation capability by the first apparatus 110 may comprise of time delay associated with the PL prediction. With the time delay of the PL prediction at the first apparatus 110, the second apparatus 120 may determine the expected time of the TCI state switching or the UL transmission.

[0120] In some example embodiments, the capability information further indicates at least one of the following: capability of performing PL prediction based on a second set of beams (Set B) which are used to predict a first set of beams, or an indication of at least one RS in the second set of beams (Set B). The first apparatus 110 may indicate and/or perform the PL prediction using one or more RSs associated with the Set B. As an example, the set B may be used predict the PL for one or more RSs of Set A, such as the candidate RSs/TCI states for prediction based beam switching and for which the PL is predicted.

[0121] In some example embodiments, if the capability information further indicates that the first apparatus 110 is capable of performing PL prediction associated with at least one RS for the second set of beams, the first apparatus 110 may perform the PL prediction associated with the at least one RS in the second set of beams.

[0122] In one example embodiment, the PL prediction may be configured to be performed using the RS in the set B (used to predict RS of set A). The first apparatus 110 may receive, from the second apparatus 120, a configuration of performing PL prediction using the at least one RS in the second set of beams. In one example the first apparatus 110 may indicate whether it is able to predict PL based on set B, or, it may indicate which RS it can predict PL for based on Set B.

[0123] In one example embodiment, the PL prediction may be performed using a specific set of RS for the PL prediction. The first apparatus 110 may perform the PL prediction associated with a specific set of RSs that are configured for PL prediction.

[0124] In some example embodiments, the first apparatus 110 may transmit, to the second apparatus 120, a request for a specific set of RSs for PL prediction, and then receive, from the second apparatus 120, a configuration of the specific set of RS. As an example, for UE-sided PL prediction, it may require specific set of RS for prediction of PL to be configured for measurement. As an example, the first apparatus 110 may request the specific set of RS for PL prediction from the second apparatus 120.

[0125] In some example embodiments, the capability information further indicates capability of performing PL prediction associated with at least one RS in a candidate target TCI state. In one example embodiment, the first apparatus 110 may indicate whether it is able to perform PL prediction for the one or more RS or pathloss RS included in a candidate target TCI state. A candidate target TCI state may be a TCI state in an RRC configured list of TCI states.

[0126] In some example embodiments, in accordance with reception of the TCI switching command to the target TCI state, the first apparatus 110 may perform the PL prediction associated with the at least one RS in a candidate target TCI state. For example, upon receiving a control message that indicates the activation of a new target TCI state, the first apparatus 110 may perform PL prediction associated with one or more RS included in the target TCI state.

[0127] In some example embodiments, in accordance with reception of the TCI switching command to the target TCI state, the first apparatus 110 may perform the PL prediction associated with at least one target RS in the target TCI state. In one example embodiment, upon receiving control message that indicates the switch to target TCI State the first apparatus 110 may perform PL prediction associated with one or more RS included in the target TCI state. In one example embodiment, upon receiving control message that indicates the activation of a new target TCI State the first apparatus 110 may perform PL prediction associated with one or more RS included in the target TCI state.

[0128] In one example embodiment, the first apparatus 110 may indicate to the second apparatus 120 the capability for performing path loss estimation using a prediction. The first apparatus 110 may indicate whether it is able to perform PL prediction for the one or more RS of the configured prediction set (Set A).

[0129] In one example embodiment, the first apparatus 110 may be configured by the second apparatus 120 to perform path loss prediction for one or more RS included in the set A of RS (beams). In one example embodiment, the first apparatus 110 may be configured by the second apparatus 120 to perform path loss prediction for one or more configured RSs.

[0130] It would be appreciated that various information elements in the capability information are described, but those information elements may be transmitted in the same or different messages or signaling. The scope of the present disclosure is not limited in this regard.

[0131] In some example embodiments, in accordance with a determination that PL prediction associated with at least one target RS in the target TCI state is performed, the first apparatus 110 may determine, based on the received TCI switching command, the switching delay time by excluding the at least one PL measurement delay. Then the first apparatus 110 may switch (230) to the target TCI state with the switching delay time from the reception of the target TCI state. In some example embodiments, the first apparatus 110 may transmit a first UL signal or channel with the target TCI state with the switching delay time from the reception of the target TCI state.

[0132] In some example embodiments, in accordance with a determination that PL prediction associated with at least one target RS of the UL transmission is performed, the first apparatus 110 may determine, based on the received indication, a transmission delay time by excluding at least one PL measurement delay. Then the first apparatus 110 may transmit (235), to the second apparatus 120, the UL transmission with the transmission delay time. The second apparatus 120 may receive (240) the UL transmission from the first apparatus 110.

[0133] In some example embodiments, if the first apparatus 110 has indicated the capability information to the second apparatus 120, for example, if the first apparatus 110 has indicated that it is able or it has predicted PL for one or more RSs and the RSs is included in target TCI state indicated (the first apparatus 110 is switched to the target TCI state) by the second apparatus 120, the first apparatus 110 is capable of transmitting the first UL signal/channel with target TCI state excluding at least one path loss estimation related component that contributes to the delay calculation. The at least one path loss estimation related component may be corresponding to the at least one PL measurement delay.

[0134] In some example embodiments, the at least one PL measurement delay is based on a time to first PL RS transmission after Layer 1 RS received power (Ll-RSRP) measurement when target TCI state is unknown, or a time to first PL RS transmission after a media access control (MAC) control element (CE) command is decoded by the first apparatus 110 when the target TCI state is known. For example, conventionally, upon receiving PDSCH carrying MAC-CE activation command in slot n on serving cell, the UE shall be able to transmit uplink signal with the target TCI state in the slot U+THARQ + (Tfirst target-PL-Rs + 4*Ttarget PL-RS + 2ms) / NR slot length. A PL measurement delay to be excluded may include Tfi_rst_target-PL-Rs, which is time to first pathloss RS transmission after Ll-RSRP measurement when target TCI state is unknown, or is time to first pathloss RS transmission after MAC CE command is decoded by the UE for known TCI State.

[0135] In some example embodiments, the at least one PL measurement delay is a periodicity of a target PL RS, e.g., the periodicity of the target pathloss reference signal which would be SSB or NZP CSI-RS when PL-RS is associated with serving cell. A PL measurement delay to be excluded may include 4*T_tar_get PL-RS, where Ttarget PL-RS is the periodicity of the target pathloss reference signal which would be SSB or NZP CSI-RS when PL-RS is associated with serving cell or the periodicity of the target pathloss reference signal which would be SSB when PL-RS is associated with PCI different from serving cell. In some examples, either one or both of Tfirst _tar_get-PL-Rs and 4* Ttarget PL-RS may be excluded from the delay calculation.

[0136] In some example embodiments, the first apparatus 110 may be configured with a PL prediction period. The first apparatus 110 may receive, from the second apparatus 120, a configuration of a PL prediction period.

[0137] In some example embodiments, the first apparatus 110 may be triggered by network side to perform PL prediction. The first apparatus 110 may receive, from the second apparatus 120, a trigger to perform the PL prediction.

[0138] In one example embodiment, the first apparatus 110 indication in any of the embodiments herein may be a MAC CE, RRC message, or uplink control message provided using PUSCH / PUCCH signaling. The first apparatus 110 may receive, from the second apparatus 120, a configuration to performing PL prediction for a sequence of RSs associated with a sequence of TCI states.

[0139] In one example embodiment, the capability information is transmitted in a MAC CE, a RRC message, or an UL control message.

[0140] In some example embodiments, the at least one target RS comprises at least one of the following: a synchronization signal block (SSB), a channel state information RS (CSI-RS), or a RS associated with a QCL Type D when the target TCI state includes two RSs. In one example the predicted RS for path loss estimation may one of SSB/CSI-RS. In one example the predicted RS for path loss estimation may one of SSB/CSI-RS and if the target TCI include two RS, the predicted RS is the QCL Type D.

[0141] In some example embodiments, the first apparatus 110 has a UE-side ML model and may perform, using the ML model, the PL prediction associated with at least one target RS in the target TCI state. The ML model may be, e.g., a neural network for PL prediction.

[0142] In one example, the first apparatus 110 may be configured to perform PL estimation for a sequence of RS associated with the sequence of TCI states.

[0143] FIG. 3 shows a flowchart of an example method 300 implemented at a first apparatus in accordance with some example embodiments of the present disclosure. For the purpose of discussion, the method 300 will be described from the perspective of the first apparatus 110 in FIG. 1.

[0144] At block 310, the first apparatus 110 transmits, to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching.

[0145] At block 320, the first apparatus 110 receives, from the second apparatus, at least one of a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission.

[0146] At block 330, the first apparatus 110 determines, based on the received TCI switching command or the received indication, exclusion of at least one path loss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

[0147] In some example embodiments, the method 300 further comprises: in accordance with a determination that pathloss prediction associated with at least one target reference signal in the target TCI state is performed, determining, based on the received TCI switching command, the switching delay time by excluding the at least one pathloss measurement delay, and switching to the target TCI state with the switching delay time from the reception of the target TCI state.

[0148] In some example embodiments, the method 300 further comprises: in accordance with a determination that pathloss prediction associated with at least one target reference signal of the uplink transmission is performed, determining, based on the received indication, a transmission delay time by excluding at least one pathloss measurement delay, and transmitting, to the second apparatus, the uplink transmission with the transmission delay time.

[0149] In some example embodiments, the capability information indicates capability of performing pathloss prediction associated with a configured set of reference signals; and/or wherein the capability information further indicates capability of performing uplink transmission based pathloss prediction associated with one or more of set of configured reference signals.

[0150] In some example embodiments, the configured set of reference signals comprises at least one of the following: a radio resource control (RRC) configured list of reference signals, one or more reference signals associated with a first set of beams which are to be predicted from beams in a second set of beams, at least one reference signal associated with at least one TCI state of a list of TCI states, at least one reference signal associated with at least one TCI state of a list of active TCI states, or at least one reference signal associated with at least one uplink signal used as reference for uplink transmission. [0151] In some example embodiments, the method 300 further comprises: performing the pathloss prediction associated with the configured set of reference signals.

[0152] In some example embodiments, the capability of performing pathloss prediction associated with one or more reference signals associated with the first set of beams indicates at least one of the following: the first apparatus is capable of performing pathloss prediction for all reference signals associated with the first set of beams, the first apparatus is capable of performing pathloss prediction for a subset of reference signals associated with the first set of beams, the first apparatus is incapable of performing pathloss prediction for at least one reference signal in the first set of beams, a bitmap with each bit corresponding to a reference signal in the first set of beams and indicating whether the first apparatus is capable of performing pathloss prediction for the corresponding reference signal or not.

[0153] In some example embodiments, the capability of performing pathloss prediction for prediction-based beam switching comprises capability of performing pathloss prediction for TCI state switching.

[0154] In some example embodiments, the method 300 further comprises: in accordance with reception of the TCI switching command to the target TCI state, performing the pathloss 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.

[0155] In some example embodiments, the capability information further indicates a time delay associated with the pathloss prediction.

[0156] In some example embodiments, the capability information further indicates at least one of the following: capability of performing pathloss prediction based on a second set of beams which are used to predict a first set of beams, or an indication of at least one reference signal in the second set of beams.

[0157] In some example embodiments, the method 300 further comprises: performing the pathloss prediction associated with the at least one reference signal in the second set of beams.

[0158] In some example embodiments, the method 300 further comprises: receiving, from the second apparatus, a configuration of performing pathloss prediction using the at least one reference signal in the second set of beams.

[0159] In some example embodiments, the first apparatus is further cause to: perform the pathloss prediction associated with a specific set of reference signals that are configured for pathloss prediction.

[0160] In some example embodiments, the first apparatus is further cause to: transmit, to the second apparatus, a request for a specific set of reference signals for pathloss prediction; and receive, from the second apparatus, a configuration of the specific set of reference signal.

[0161] In some example embodiments, the capability information further indicates capability of performing pathloss prediction associated with at least one reference signal in a candidate target TCI state.

[0162] In some example embodiments, the first apparatus is further cause to: in accordance with reception of the TCI switching command to the target TCI state, perform the pathloss prediction associated with the at least one reference signal in a candidate target TCI state.

[0163] In some example embodiments, the first apparatus is further cause to: in accordance with reception of the TCI switching command to the target TCI state, perform the pathloss prediction associated with at least one target reference signal in the target TCI state.

[0164] In some example embodiments, the method 300 further comprises: transmitting a first uplink signal or channel with the target TCI state with the switching delay time from the reception of the target TCI state.

[0165] In some example embodiments, the at least one pathloss measurement delay is based on at least one of the following: a time to first pathloss reference signal transmission after Layer 1 reference signal received power (Ll-RSRP) measurement when target TCI state is unknown, a time to first pathloss reference signal transmission after a media access control (MAC) control element (CE) command is decoded by the first apparatus when the target TCI state is known, or a periodicity of a target pathloss reference signal.

[0166] In some example embodiments, the method 300 further comprises: receiving, from the second apparatus, at least one of: a configuration of a pathloss prediction period, a trigger to perform the pathloss prediction, or a configuration to performing pathloss prediction for a sequence of reference signals associated with a sequence of TCI states. [0167] In some example embodiments, the capability information is transmitted in a MAC CE, a RRC message, or an uplink control message.

[0168] In some example embodiments, the at least one target reference signal comprises 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 a QCL Type D when the target TCI state includes two reference signals.

[0169] In some example embodiments, the first apparatus is further cause to: perform, using a machine learning model, the pathloss prediction associated with at least one target reference signal in the target TCI state.

[0170] In some example embodiments, the first apparatus is or is comprised in a terminal device, and the second apparatus is or is comprised in a network device.

[0171] In some example embodiments, a first apparatus capable of performing any of the method 300 (for example, the first apparatus 110 in FIG. 1 [TO DO : may comprise means for performing the respective operations of the method 300. The means may be implemented in any suitable form. For example, the means may be implemented in a circuitry or software module. The first apparatus may be implemented as or included in the first apparatus 110 in FIG. 1.

[0172] In some example embodiments, the first apparatus comprises means for transmitting, to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching; means for receiving, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission; and means for determining, based on the received TCI switching command or the received indication, exclusion of at least one path loss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission. [0173] In some example embodiments, the first apparatus further comprises: means for, in accordance with a determination that pathloss prediction associated with at least one target reference signal in the target TCI state is performed, determining, based on the received TCI switching command, the switching delay time by excluding the at least one pathloss measurement delay, and means for switching to the target TCI state with the switching delay time from the reception of the target TCI state.

[0174] In some example embodiments, the first apparatus further comprises: means for, in accordance with a determination that pathloss prediction associated with at least one target reference signal of the uplink transmission is performed, determining, based on the received indication, a transmission delay time by excluding at least one pathloss measurement delay, and means for transmitting, to the second apparatus, the uplink transmission with the transmission delay time.

[0175] In some example embodiments, the capability information indicates capability of performing pathloss prediction associated with a configured set of reference signals; and/or wherein the capability information further indicates capability of performing uplink transmission based pathloss prediction associated with one or more of set of configured reference signals.

[0176] In some example embodiments, the configured set of reference signals comprises at least one of the following: a radio resource control (RRC) configured list of reference signals, one or more reference signals associated with a first set of beams which are to be predicted from beams in a second set of beams, at least one reference signal associated with at least one TCI state of a list of TCI states, at least one reference signal associated with at least one TCI state of a list of active TCI states, or at least one reference signal associated with at least one uplink signal used as reference for uplink transmission. [0177] In some example embodiments, the first apparatus further comprises: means for performing the pathloss prediction associated with the configured set of reference signals. [0178] In some example embodiments, the capability of performing pathloss prediction associated with one or more reference signals associated with the first set of beams indicates at least one of the following: the first apparatus is capable of performing pathloss prediction for all reference signals associated with the first set of beams, the first apparatus is capable of performing pathloss prediction for a subset of reference signals associated with the first set of beams, the first apparatus is incapable of performing pathloss prediction for at least one reference signal in the first set of beams, a bitmap with each bit corresponding to a reference signal in the first set of beams and indicating whether the first apparatus is capable of performing pathloss prediction for the corresponding reference signal or not.

[0179] In some example embodiments, the capability of performing pathloss prediction for prediction-based beam switching comprises capability of performing pathloss prediction for TCI state switching.

[0180] In some example embodiments, the first apparatus further comprises: means for in accordance with reception of the TCI switching command to the target TCI state, performing the pathloss 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.

[0181] In some example embodiments, the capability information further indicates a time delay associated with the pathloss prediction.

[0182] In some example embodiments, the capability information further indicates at least one of the following: capability of performing pathloss prediction based on a second set of beams which are used to predict a first set of beams, or an indication of at least one reference signal in the second set of beams.

[0183] In some example embodiments, the first apparatus further comprises: means for performing the pathloss prediction associated with the at least one reference signal in the second set of beams.

[0184] In some example embodiments, the first apparatus further comprises: means for receiving, from the second apparatus, a configuration of performing pathloss prediction using the at least one reference signal in the second set of beams.

[0185] In some example embodiments, the first apparatus further comprises: means for performing the pathloss prediction associated with a specific set of reference signals that are configured for pathloss prediction.

[0186] In some example embodiments, the first apparatus further comprises: means for transmitting, to the second apparatus, a request for a specific set of reference signals for pathloss prediction; and means for receiving, from the second apparatus, a configuration of the specific set of reference signal.

[0187] In some example embodiments, the capability information further indicates capability of performing pathloss prediction associated with at least one reference signal in a candidate target TCI state.

[0188] In some example embodiments, the first apparatus further comprises: means for, in accordance with reception of the TCI switching command to the target TCI state, performing the pathloss prediction associated with the at least one reference signal in a candidate target TCI state.

[0189] In some example embodiments, the first apparatus further comprises: means for, in accordance with reception of the TCI switching command to the target TCI state, performing the pathloss prediction associated with at least one target reference signal in the target TCI state.

[0190] In some example embodiments, the first apparatus further comprises: means for transmitting a first uplink signal or channel with the target TCI state with the switching delay time from the reception of the target TCI state.

[0191] In some example embodiments, the at least one pathloss measurement delay is based on at least one of the following: a time to first pathloss reference signal transmission after Layer 1 reference signal received power (Ll-RSRP) measurement when target TCI state is unknown, a time to first pathloss reference signal transmission after a media access control (MAC) control element (CE) command is decoded by the first apparatus when the target TCI state is known, or a periodicity of a target pathloss reference signal.

[0192] In some example embodiments, the first apparatus further comprises: means for receiving, from the second apparatus, at least one of: a configuration of a pathloss prediction period, a trigger to perform the pathloss prediction, or a configuration to performing pathloss prediction for a sequence of reference signals associated with a sequence of TCI states.

[0193] In some example embodiments, the capability information is transmitted in a MAC CE, a RRC message, or an uplink control message.

[0194] In some example embodiments, the at least one target reference signal comprises 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 a QCL Type D when the target TCI state includes two reference signals. [0195] In some example embodiments, the first apparatus further comprises: means for performing, using a machine learning model, the pathloss prediction associated with at least one target reference signal in the target TCI state.

[0196] In some example embodiments, the first apparatus is or is comprised in a terminal device, and the second apparatus is or is comprised in a network device.

[0197] FIG. 4 is a simplified block diagram of a device 400 that is suitable for implementing example embodiments of the present disclosure. The device 400 may be provided to implement a communication device, for example, the first apparatus 110 or the second apparatus 120 as shown in FIG. 1. As shown, the device 400 includes one or more processors 410, one or more memories 420 coupled to the processor 410, and one or more communication modules 440 coupled to the processor 410.

[0198] The communication module 440 is for bidirectional communications. The communication module 440 has one or more communication interfaces to facilitate communication with one or more other modules or devices. The communication interfaces may represent any interface that is necessary for communication with other network elements. In some example embodiments, the communication module 440 may include at least one antenna.

[0199] The processor 410 may be of any type suitable to the local technical network and may include one or more of the following: general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples. The device 400 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.

[0200] The memory 420 may include one or more non-volatile memories and one or more volatile memories. Examples of the non-volatile memories include, but are not limited to, a Read Only Memory (ROM) 424, an electrically programmable read only memory (EPROM), a flash memory, a hard disk, a compact disc (CD), a digital video disk (DVD), an optical disk, a laser disk, and other magnetic storage and/or optical storage. Examples of the volatile memories include, but are not limited to, a randomaccess memory (RAM) 422 and other volatile memories that will not last in the powerdown duration.

[0201] A computer program 430 includes computer executable instructions that are executed by the associated processor 410. The instructions of the program 430 may include instructions for performing operations/acts of some example embodiments of the present disclosure. The program 430 may be stored in the memory, e.g., the ROM 424. The processor 410 may perform any suitable actions and processing by loading the program 430 into the RAM 422.

[0202] The example embodiments of the present disclosure may be implemented by means of the program 430 so that the device 400 may perform any process of the disclosure as discussed with reference to FIG. 2 to FIG. 3. The example embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.

[0203] In some example embodiments, the program 430 may be tangibly contained in a computer readable medium which may be included in the device 400 (such as in the memory 420) or other storage devices that are accessible by the device 400. The device 400 may load the program 430 from the computer readable medium to the RAM 422 for execution. In some example embodiments, the computer readable medium may include any types of non-transitory storage medium, such as ROM, EPROM, a flash memory, a hard disk, CD, DVD, and the like. The term “non-transitory,” as used herein, is a limitation of the medium itself (i.e., tangible, not a signal) as opposed to a limitation on data storage persistency (e.g., RAM vs. ROM).

[0204] FIG. 5 shows an example of the computer readable medium 500 which may be in form of CD, DVD or other optical storage disk. The computer readable medium 500 has the program 430 stored thereon.

[0205] Generally, various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, and other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. Although various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representations, it is to be understood that the block, apparatus, system, technique or method described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

[0206] Some example embodiments of the present 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, such as those included in program modules, being executed in a device on a target physical or virtual processor, to carry out any of the methods as described above. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or split between program modules as desired in various embodiments. Machine-executable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.

[0207] Program code for carrying out methods of the present 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 the program code, when executed by the processor or controller, cause the functions/operations specified in the flowcharts and/or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0208] In the context of the present disclosure, the computer program code or related data may be carried by any suitable carrier to enable the device, apparatus or processor to perform various processes and operations as described above. Examples of the carrier include a signal, computer readable medium, and the like.

[0209] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a randomaccess memory (RAM), a read-only memory (ROM), an erasable programmable readonly memory (EPROM or Flash memory), an optical fiber, a portable compact disc readonly memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0210] Further, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, although several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Unless explicitly stated, certain features that are described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, unless explicitly stated, various features that are described in the context of a single embodiment may also be implemented in a plurality of embodiments separately or in any suitable sub-combination. [0211] Although the present disclosure has been described in languages specific to structural features and/or methodological acts, it is to be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

WHAT IS CLAIMED IS:

1. A first apparatus comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus at least to: transmit, to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching; receive, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission; and determine, based on the received TCI switching command or the received indication, exclusion of at least one pathloss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

2. The first apparatus of claim 1, wherein the first apparatus is caused to: in accordance with a determination that pathloss prediction associated with at least one target reference signal in the target TCI state is performed, determine, based on the received TCI switching command, the switching delay time by excluding the at least one pathloss measurement delay, and switch to the target TCI state with the switching delay time from the reception of the target TCI state.

3. The first apparatus of claim 1, wherein the first apparatus is caused to: in accordance with a determination that pathloss prediction associated with at least one target reference signal of the uplink transmission is performed, determine, based on the received indication, a transmission delay time by excluding at least one pathloss measurement delay, and transmit, to the second apparatus, the uplink transmission with the transmission delay time.

4. The first apparatus of claim 1, wherein the capability information indicates capability of performing pathloss prediction associated with a configured set of reference signals; and/or wherein the capability information further indicates capability of performing uplink transmission based pathloss prediction associated with one or more of set of configured reference signals.

5. The first apparatus of claim 4, wherein the configured set of reference signals comprises at least one of the following: a radio resource control (RRC) configured list of reference signals, one or more reference signals associated with a first set of beams which are to be predicted from beams in a second set of beams, at least one reference signal associated with at least one TCI state of a list of TCI states, at least one reference signal associated with at least one TCI state of a list of active TCI states, or at least one reference signal associated with at least one uplink signal used as reference for uplink transmission.

6. The first apparatus of claim 4 or 5, wherein the capability of performing pathloss prediction associated with a configured set of reference signals indicates that the first apparatus is capable of performing pathloss prediction associated with the configured set of reference signals first apparatus is further caused to: perform the pathloss prediction associated with the configured set of reference signals.

7. The first apparatus of claim 5, wherein the capability of performing pathloss prediction associated with one or more reference signals associated with the first set of beams indicates at least one of the following: the first apparatus is capable of performing pathloss prediction for all reference signals associated with the first set of beams, the first apparatus is capable of performing pathloss prediction for a subset of reference signals associated with the first set of beams, the first apparatus is incapable of performing pathloss prediction for at least one reference signal in the first set of beams, a bitmap with each bit corresponding to a reference signal in the first set of beams and indicating whether the first apparatus is capable of performing pathloss prediction for the corresponding reference signal or not.

8. The first apparatus of any of claims 1 to 7, wherein the capability of performing pathloss prediction for prediction-based beam switching comprises capability of performing pathloss prediction for TCI state switching.

9. The first apparatus of claim 8, wherein the capability of performing pathloss prediction for TCI state switching indicates that the first apparatus is capable of performing pathloss prediction for TCI state switching, and wherein the first apparatus is caused to: in accordance with reception of the TCI switching command to the target TCI state, perform the pathloss 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.

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

11. The first apparatus of any of claims 1 to 10, wherein the capability information further indicates at least one of the following: capability of performing pathloss prediction based on a second set of beams which are used to predict a first set of beams, or an indication of at least one reference signal in the second set of beams.

12. The first apparatus of claim 11, wherein the capability information further indicates that the first apparatus is capable of performing pathloss prediction associated with at least one reference signal for the second set of beams, and wherein the first apparatus is further caused to: perform the pathloss prediction associated with the at least one reference signal in the second set of beams.

13. The first apparatus of claim 11 or 12, wherein the first apparatus is further caused to: receive, from the second apparatus, a configuration of performing pathloss prediction using the at least one reference signal in the second set of beams.

14. The first apparatus of any of claims 1 to 13, wherein the first apparatus is further cause to: perform the pathloss prediction associated with a specific set of reference signals that are configured for pathloss prediction.

15. The first apparatus of claim 14, wherein the first apparatus is further cause to: transmit, to the second apparatus, a request for a specific set of reference signals for pathloss prediction; and receive, from the second apparatus, a configuration of the specific set of reference signal.

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

17. The first apparatus of claim 16, wherein the first apparatus is further cause to: in accordance with reception of the TCI switching command to the target TCI state, perform the pathloss prediction associated with the at least one reference signal in a candidate target TCI state.

18. The first apparatus of any of claims 1 to 17, wherein the first apparatus is further cause to: in accordance with reception of the TCI switching command to the target TCI state, perform the pathloss prediction associated with at least one target reference signal in the target TCI state.

19. The first apparatus of any of claims 1 to 18, wherein the first apparatus is caused to: transmit a first uplink signal or channel with the target TCI state with the switching delay time from the reception of the target TCI state.

20. The first apparatus of any of claims 1 to 19, wherein the at least one pathloss measurement delay is based on at least one of the following: a time to first pathloss reference signal transmission after Layer 1 reference signal received power (Ll-RSRP) measurement when target TCI state is unknown, a time to first pathloss reference signal transmission after a media access control (MAC) control element (CE) command is decoded by the first apparatus when the target TCI state is known, or a periodicity of a target pathloss reference signal.

21. The first apparatus of any of claims 1 to 20, wherein the first apparatus is further caused to: receive, from the second apparatus, at least one of: a configuration of a pathloss prediction period, a trigger to perform the pathloss prediction, or a configuration to performing pathloss prediction for a sequence of reference signals associated with a sequence of TCI states.

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

23. The first apparatus of any of claims 1 to 22, wherein the at least one target reference signal comprises at least one of the following: a synchronization signal block (SSB), a channel state information reference signal (CSLRS), or a reference signal associated with a QCL Type D when the target TCI state includes two reference signals.

24. The first apparatus of any of claims 1 to 23, wherein the first apparatus is further cause to: perform, using a machine learning model, the pathloss prediction associated with at least one target reference signal in the target TCI state.

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

26. A method comprising: transmitting, by a first apparatus and to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching; receiving, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission; and determining, based on the received TCI switching command or the received indication, exclusion of at least one pathloss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

27. A first apparatus comprising: means for transmitting, to a second apparatus, capability information indicating at least one of the following: capability of performing pathloss prediction, an indication of performing uplink transmission based on pathloss prediction or capability of performing pathloss prediction for prediction-based beam switching; means for receiving, from the second apparatus, at least one of: a transmission configuration indicator (TCI) switching command to a target TCI state, or an indication to transmit an uplink transmission; and means for determining, based on the received TCI switching command or the received indication, exclusion of at least one pathloss measurement delay from a switching delay time for the target TCI state and/or a transmission delay time for the uplink transmission.

28. A computer readable medium comprising instructions stored thereon for causing an apparatus at least to perform the method of claim 26.