Path loss prediction for power control

Abstract

Example embodiments of the present disclosure relate to methods, devices, apparatuses, and computer-readable storage media for path loss prediction for power control. In one method, a first device obtains at least one transmission configuration indicator (TCI) state for a transmission to a second device, the at least one TCI state being associated with at least one reference signal used to determine a path loss value. The first device selects at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value. The first device determines a transmission power of the transmission based on the path loss value.

Description

Cross-reference to related applications

[0001] This application claims priority and interest in UK application number 2402741.9, filed on 27 February 2024, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0002] Various exemplary embodiments of this disclosure generally relate to the telecommunications field, and more particularly to methods, apparatuses, devices, and computer-readable storage media for path loss prediction in power control. Background Technology

[0003] In communication systems, terminal equipment such as User Equipment (UE) can transmit signals or data to network equipment. The UE can perform uplink (UL) power control on UL transmissions. Several procedures for UL power control have been proposed. As an example, New Radio (NR) Physical Uplink Shared Channel (PUSCH) power control is essentially based on a combination of open-loop and closed-loop power control. Open-loop power control includes support for fractional path loss compensation, where the UE estimates UL path loss based on downlink (DL) measurements and sets the transmission power accordingly. Closed-loop power control is based on explicit Transmission Power Control (TPC) commands provided by the network. Work is underway on path loss estimation for power control. Summary of the Invention

[0004] In a first aspect of this disclosure, a first apparatus is provided. The first apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus to at least: obtain at least one Transmission Configuration Indicator (TCI) state for a transmission to a second apparatus, the at least one TCI state being associated with at least one reference signal for determining a path loss value; select at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value; and determine the transmission power of the transmission based on the path loss value.

[0005] In a second aspect of this disclosure, a second apparatus is provided. The second apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the second apparatus to at least: transmit to a first apparatus an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first apparatus to the second apparatus, the at least one TCI state being associated with at least one reference signal for determining a path loss value; and receive from the first apparatus the transmission, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal.

[0006] In a third aspect of this disclosure, a method is provided. The method includes: obtaining at a first device at at least one Transmission Configuration Indicator (TCI) state for a transmission to a second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; selecting at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value; and determining the transmission power of the transmission based on the path loss value.

[0007] In a fourth aspect of this disclosure, a method is provided. The method includes: transmitting from a second device to a first device an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; and receiving the transmission from the first device, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal.

[0008] In a fifth aspect of this disclosure, an apparatus is provided. The first apparatus includes: means for obtaining at least one Transmission Configuration Indicator (TCI) state for transmission to a second apparatus, the at least one TCI state being associated with at least one reference signal for determining a path loss value; means for selecting at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value; and means for determining the transmission power of the transmission based on the path loss value.

[0009] In a sixth aspect of this disclosure, an apparatus is provided. The first apparatus includes: components for transmitting to a first apparatus an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first apparatus to a second apparatus, the at least one TCI state being associated with at least one reference signal for determining a path loss value; and components for receiving a transmission from the first apparatus, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least one predicted signal power of at least one reference signal or at least one measured signal power of at least one of the reference signals.

[0010] In a seventh aspect of this disclosure, a computer-readable medium is provided. The computer-readable medium includes instructions stored thereon for causing a device to perform a method according to a third or fourth aspect.

[0011] It should be understood that the summary portion is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0012] Some exemplary embodiments will now be described with reference to the accompanying drawings, in which: Figure 1 An example communication environment in which example embodiments of this disclosure may be implemented is shown; Figure 2 The signaling flow for path loss prediction for power control according to some example embodiments of this disclosure is shown; Figure 3 A flowchart of a method for determining transmission power according to some example embodiments of the present disclosure is shown; Figure 4 A flowchart of a method for determining transmission power according to some example embodiments of the present disclosure is shown; Figure 5 A flowchart is shown illustrating a method implemented at a first device according to some exemplary embodiments of the present disclosure; Figure 6 A flowchart is shown illustrating a method implemented at a second device according to some example embodiments of the present disclosure; Figure 7 A simplified block diagram of a device suitable for implementing example embodiments of the present disclosure is shown; and Figure 8 A block diagram of an example computer-readable medium according to some example embodiments of the present disclosure is shown.

[0013] In all the accompanying drawings, the same or similar reference numerals denote the same or similar elements. Detailed Implementation

[0014] The principles of this disclosure will now be described with reference to some exemplary embodiments. It should be understood that these embodiments are described for illustrative purposes only and to assist those skilled in the art in understanding and implementing this disclosure, and do not imply any limitation on the scope of this disclosure. The embodiments described herein can be implemented in various ways other than those described below.

[0015] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0016] References to "an embodiment," "embodiment," "example embodiment," etc., in this disclosure indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment must include that particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when a particular feature, structure, or characteristic is described in connection with an embodiment, it should be understood that, whether explicitly described or not, implementing such a feature, structure, or characteristic in conjunction with other embodiments is within the knowledge of those skilled in the art.

[0017] It should be understood that although the terms “first,” “second,” etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of the exemplary embodiments, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. As used herein, the term “and / or” includes any and all combinations of one or more of the listed terms.

[0018] As used herein, “at least one of the following: a list of two or more elements” and “at least one of the following: a list of two or more elements” and similar wording (where the list of two or more elements is connected by “and” or “or”) means at least any one of the elements, or at least any two or more of the elements, or at least all of the elements.

[0019] As used herein, unless explicitly stated otherwise, the execution step “in response to A” does not indicate that the step is performed immediately after “A” occurs, and may include one or more intermediate steps.

[0020] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that, when used herein, the terms “comprises,” “comprising,” “has,” “having,” “includes,” and / or “including” specify the presence of the stated features, elements, and / or components, but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0021] As used in this application, the term "circuit" may refer to one or more of the following: (a) Hardware circuit implementation only (such as implementation in analog and / or digital circuits only) and (b) A combination of hardware circuitry and software, such as (if applicable): (i) A combination of analog and / or digital hardware circuitry with software / firmware, and (ii) Any part of (multiple) hardware processors (including (multiple) digital signal processors), software, and (one) memory, which work together to enable a device such as a mobile phone or server to perform various functions, and (c) The hardware circuitry and / or processors, such as microprocessors or a portion thereof, that require software (e.g., firmware) to operate, but which may be absent when no software is required to operate.

[0022] This definition of "circuit" applies to all uses of the term in this application (including in any claim). As another example, as used in this application, the term "circuit" also covers implementations of hardware circuitry or processors (or processors in general) and their accompanying software and / or firmware. The term "circuit" also covers, for example and if applicable to a particular claim element, baseband integrated circuits or processor integrated circuits for mobile devices or similar integrated circuits in servers, cellular network devices, or other computing or network devices.

[0023] As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as New Radio (NR), Long Term Evolution (LTE), LTE-A Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), Narrowband Internet of Things (NB-IoT), etc. Furthermore, communication between terminal devices and network devices in the communication network can be performed according to any suitable generation of communication protocol, including but not limited to first-generation (1G), second-generation (2G), 2.5G, 2.75G, third-generation (3G), fourth-generation (4G), 4.5G, fifth-generation (5G) communication protocols and / or any other currently known or future-developed protocols. Embodiments of this disclosure can be applied to a variety of communication systems. Given the rapid development of communications, there will certainly be future types of communication technologies and systems that embody the future types of this disclosure. The scope of this disclosure should not be construed as limited to the aforementioned systems.

[0024] As used herein, the term "network device" or "network access device" refers to a node in a communication network through which terminal devices access the network and receive services. Depending on the terminology and technology applied, network device can refer to a base station (BS) or access point (AP), such as a Node B (NodeB or NB), an evolved Node B (eNodeB or eNB), an NR NB (also known as a gNB), a remote radio unit (RRU), a radio header (RH), a remote radio header (RRH), a relay, an integrated access and backhaul (IAB) node, a low-power node (such as a femto, pico, or non-terrestrial network (NTN)) or non-terrestrial network equipment (such as satellite network equipment), low Earth orbit (LEO) satellites and geostationary Earth orbit (GEO) satellites, spacecraft network equipment, etc. In some example embodiments, the radio access network (RAN) split architecture includes a centralized unit (CU) and a distributed unit (DU) at the IAB host node. An IAB node includes a mobile terminal (IAB-MT) portion that behaves as a UE facing the parent node, and a DU portion that behaves as a base station facing the next-hop IAB node.

[0025] The term "terminal device" refers to any terminal device capable of wireless communication. By way of example and not limitation, a terminal device may also be referred to as a communication device, user equipment (UE), subscriber station (SS), portable subscriber station, mobile station (MS), or access terminal (AT). Terminal devices may include, but are not limited to, mobile phones, cellular phones, smartphones, Voice over IP (VoIP) phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image capture terminal devices (such as digital cameras), gaming terminal devices, music storage and playback devices, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop embedded devices (LEEs), laptop devices (LMEs), USB dongles, smart devices, wireless customer premises equipment (CPEs), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in industrial and / or automated processing chain environments), consumer electronics devices, devices operating on commercial and / or industrial wireless networks, etc. The terminal device may also correspond to the mobile terminal (MT) portion of an IAB node (e.g., a relay node). In the following description, the terms "terminal device," "communication device," "terminal," "user equipment," and "UE" are used interchangeably.

[0026] As used herein, the terms “resource,” “transmission resource,” “resource block,” “physical resource block (PRB),” “uplink resource,” or “downlink resource” can refer to any resource used to perform communication, such as communication between a terminal device and a network device, including resources in the time domain, frequency domain, spatial domain, code domain, or any other resources used to implement communication. In the following, unless explicitly stated otherwise, resources in the frequency and time domains will be used as examples of transmission resources used to describe some exemplary embodiments of this disclosure. Note that the exemplary embodiments of this disclosure are equally applicable to other resources in other domains.

[0027] As used in this paper, the term "model" refers to the association between inputs and outputs learned from training data, and therefore can generate corresponding outputs for a given input after training. Model generation can be based on ML techniques. ML techniques can also be referred to as AI techniques. Typically, ML models can be built that receive input information and make predictions based on that input information. As used in this paper, "model" is equivalent to an artificial intelligence (AI) and / or machine learning (ML) model or a data-driven / data processing algorithm / process.

[0028] In some communication systems, such as next-generation cellular systems, the use of AI / ML technologies has been proposed to improve communication performance. AI / ML models can be applied to New Radio (NR) radio interfaces to assist model functions or communication-related functions, such as reducing channel state information (CSI) overhead, beam management (BM), and positioning.

[0029] In version 18 (Rel-18) or Rel-19, AI-ML can be used for beam prediction or beam management. For AI / ML-based beam management, AI / ML models are used to predict the optimal (multiple) beams based on a finite set of measurements.

[0030] In some mechanisms, two sub-use cases are provided: the first is spatial domain prediction, where beam prediction is based on a finite set of measurements that does not contain any historical information; the second is temporal domain prediction, where future beam prediction is based on a finite set of measurements that includes historical information.

[0031] In some mechanisms, measurements and predictions are based on two beam sets. For the first beam set (called set A), the prediction is made on the complete set of beams on which the operation will take place. For the second beam set (called set B), the measurements are input into the set of beams of the AI / ML model (e.g., Layer 1 (L1) Reference Signal Received Power (RSRP), etc.). Furthermore, set B can be different from set A (spatial and temporal predictions). Alternatively, set B can be a subset of set A (spatial and temporal predictions). Or, set B can be the same as set A (temporal predictions).

[0032] The Radio Access Network (RAN) #102 meeting approved Rel-19 Work Item (WI) on AI / ML for the NR air interface, based on the application of AI / ML technology. Table 1 below shows several enhancements related to AI / ML for beam management.

[0033] Table 1

[0034] This paper presents the inference process for beam management, including beam management predictions for BM-Case 1 and BM-Case 2. The process utilizes measurements from beams in set B as input to the AI / ML model. Additionally, beam identification (ID) information can also be included as input to the AI / ML model. The output of the AI / ML model includes the probability that each beam in set A is the previous (Top-1) beam, the predicted L1-RSRP, or other relevant parameters, depending on the labeling method.

[0035] For BM-Case 1, measurements from set B are used to predict the Top-1 / N beams from set A. Conversely, for BM-Case 2, historical measurements from previous times are used for temporal beam prediction of beams in set A. The process considers various scenarios, including sets A and B being different, set B being a subset of set A, and sets A and B being the same for BM-Case 2.

[0036] Furthermore, Release-18 considers both DL beam prediction and DL beam pair prediction (Tx-Rx). In both BM-Case 1 and BM-Case 2, the UE can use the UE-side AI / ML model and report the prediction results to the NW, or the NW can use the NW-side model to predict the Top-1 / N beams or L1-RSRP values ​​based on the reported set B measurements.

[0037] In the context of beam management, specifically BM-Case 1 and BM-Case 2, various aspects related to enhanced signaling and beam reporting were examined in Release-18, and specification work is currently underway in Release-19.

[0038] Several considerations aim to optimize beam management strategies, particularly in scenarios employing UE-side AI / ML models. First, there is a focus on signaling improvements for measurement configuration and reporting, potentially introducing new signaling mechanisms to efficiently facilitate these processes. For the UE-side AI / ML models in BM-Case 1 and BM-Case 2, the network can indicate set A-set B associations to the UE, such as mapping beams within set B to set A (if relevant). Furthermore, the network can provide the UE with beam indications for reception, including beams in set A that are not present in set B. Traditional mechanisms (e.g., TCI state mechanisms) can be reused for this purpose.

[0039] For BM-Case 1 and BM-Case 2, which have network-side AI / ML models, enhancements to L1 beam reporting are proposed, such as allowing the UE to report measurements of more than four beams in a single reporting instance. Other L1 reporting enhancements may also be considered.

[0040] The predicted L1-RSRP value corresponding to the DL Tx beam or beam pair is an important output, and it is also necessary to consider how to distinguish between the predicted L1-RSRP value and the measured L1-RSRP value. Additionally, the confidence or probability information related to the output inference of the AI / ML model is also relevant. For the output of the AI / ML model, version 18SI considers the following options based on some alternative solutions.

[0041] For Alternative Option 1, it involves the identification of Tx and / or Rx beams of N estimated DL Tx and / or Rx beams and / or the predicted L1-RSRP, such as the top N (Top-N) predicted beams.

[0042] For Alternative Option 2, it involves the Tx and / or Rx beam IDs of N predicted DL Tx and / or Rx beams, as well as other information. The N predicted DLs can be the first N predicted beams.

[0043] For alternative scheme 3, incorporate the Tx and / or Rx beam angles and / or predicted L1-RSRP of N predicted DL Tx and / or Rx beams, for example, the first N predicted beams.

[0044] It should be noted that the use of beam IDs is for discussion purposes only, and all outputs are considered nominal and are for discussion purposes only. The value of N can vary depending on each company's implementation. Additionally, the output from the AI / ML model can differ depending on whether inference occurs on the UE side or the gNB side. The derivation of the first N beam IDs may involve post-processing of the ML model output.

[0045] As mentioned above, Rel-19 will specify DL Tx beam prediction (with two use cases: spatial domain and temporal domain beam prediction), where DL Tx beam prediction can be enabled based on the AI-ML model of the UE and / or gNB. It should be noted that the UE may also need to predict the RSRP of the predicted beam (or CRI or TCI state) and report the predicted beam(s) along with the corresponding RSRP to the gNB. The Rel-18 SI (Research Project) on beam prediction also considers DL beam pair (Tx-Rx) prediction as an option. Similarly, UL beam or beam pair prediction can also be considered.

[0046] As briefly mentioned, UL power control operations require path loss estimation or determination. However, currently, there is no framework to enable predicted RSRP and incorporate it into UL power control operations.

[0047] Furthermore, current UEs face limitations in path loss estimation (which is a function of RSRP measurement) because they only need to maintain up to four path loss processes. However, when considering frequency range (FR) 1 or FR2 (or any other frequency range, such as FR3), having only four such processes is insufficient to obtain accurate path loss estimates, as the number of Synchronization Block (SSB) / Channel State Information (CSI) Reference Signal (RS) beams can be multiples of four. Adding such a limitation would also increase the burden on the UE. Therefore, for this reason, and given that beams / RS may be predicted (rather than measured) in at least some cases, path loss prediction is an area that needs to be utilized and enabled.

[0048] To address at least some of the aforementioned or other potential problems, a solution for (enabled) path loss prediction for power control is proposed. According to an example embodiment, a first device (e.g., a terminal device) has at least one Transmission Configuration Indicator (TCI) state for transmission to a second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value. The first device selects at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value. The first device determines the transmission power based on the path loss value. In this way, the transmission power can be determined at least in part based on the predicted signal power, such as a predicted RSRP value. For example, the predicted RSRP value can be used for path loss estimation. This power determination can improve the estimation accuracy of the path loss estimate, thereby determining an appropriate transmission power.

[0049] The following will refer to Figure 1-8 The principles and implementation of this disclosure are described in detail. Figure 1 An example communication environment 100 in which exemplary embodiments of the present disclosure can be implemented is shown. In the communication environment 100, a plurality of communication devices, including a first device 110 and a second device 120, can communicate with each other.

[0050] In some example embodiments, if the first device 110 is a terminal device and the second device 120 is a network device serving the terminal device, the link from the second device 120 to the first device 110 is referred to as a downlink (DL), and the link from the first device 110 to the second device 120 is referred to as an uplink (UL). In the DL, the second device 120 is a transmitting (TX) device (or transmitter), and the first device 110 is a receiving (RX) device (or receiver). In the UL, the first device 110 is a TX device (or transmitter), and the second device 120 is an RX device (or receiver).

[0051] In some example embodiments, multiple-input multiple-output (MIMO) is supported in the communication environment 100. For example, the second device 120 and the first device 110 can communicate with each other via different beams to achieve directional communication. The first device 110 may be configured with at least one beam (corresponding to at least one reference signal (RS) used as a reference for receiving / transmitting data and control channels). For example, the first device 110 may have one or more physical downlink control channel (PDCCH) channels and one or more physical downlink shared channel (PDSCH) channels. One or more PDSCH channels and / or one or more PDSCH channels may be configured to be received on one or more DL beams.

[0052] like Figure 1 As shown, the second device 120 transmits downlink data to the first device 110 via one or more beams. Among these beams, at least one beam can be measured, such as beams 140-1, 140-2, ..., and 140-K (K is an integer greater than or equal to 1). For the purposes of discussion, beams 140-1, 140-2, ..., and 140-K are collectively or individually referred to as the measured beam(s) 140. Other beams, such as beams 130-1, 130-2, ..., and 130-N, can be predicted by a model such as model 115 deployed at the first device 110. For the purposes of discussion, beams 130-1, 130-2, ..., and 130-N are collectively or individually referred to as the predicted beam(s) 130. In some example embodiments, the measured or predicted beams can be broadband beams, such as beam 150-1 or beam 150-2. Beam 150-1 and Beam 150-2 are collectively referred to or individually as (multiple) Beam 150.

[0053] It should be understood that although model 115 is shown deployed at the first device 110, in some example embodiments, model 115 may be deployed at the second device 120, or at another device or apparatus. Alternatively, model 115 may be a dual-sided model deployed at both the first device 110 and the second device 120. The scope of this disclosure is not limited thereto.

[0054] Accordingly, in the uplink, the second device 120 is an RX device (or receiver), and the first device 110 is a TX device (or transmitter), and the first device 110 can transmit uplink data to the second device 120 via one or more beams (not shown).

[0055] exist Figure 1 In the example, the second device 120 has a coverage area, which may be referred to as a service area or cell (not shown). The first device 110 is located in the cell covered by the second device 120. In the communication environment 100, the second device 120 can transmit data and control information to the first device 110, and the first device 110 can also transmit data and control information to the second device 120.

[0056] In some example embodiments, model functions such as AI / ML-based functions can be provided for the first device 110 and / or the second device 120. For example, model 115 can perform the model functions of the first device 110. For instance, the second device 120 can provide multiple beams for the first device 110. The model functions can be AI / ML-based beam management or beam prediction, which predicts beams for the first device 110, such as DL Tx beams. In another example, the model function can be AI / ML-based beam management, which predicts DL Tx Rx beam pairs for the first device 110. For illustrative purposes, some example embodiments will be described below using beam management or beam prediction as model functions. It should be understood that model 115 can also perform different model functions for the first device 110. The scope of this disclosure is not limited thereto.

[0057] AI / ML-based beam management can be spatial and / or temporal beam prediction. Spatial beam prediction (also known as BM-Case 1) is used to predict one or more optimal Tx beams or Tx-Rx beam pairs or their corresponding reference signal received power (RSRP) values ​​at different spatial locations. Temporal beam prediction (also known as BM-Case 2) aims to predict the optimal Tx beam or Tx-Rx beam pair for the next time step. For example, spatial domain (BM-Case 1) beam prediction is performed for the next time step. For illustrative purposes, some example embodiments are described where the model function is spatial and / or temporal beam prediction.

[0058] In some example embodiments, one or more models can derive predicted beam results such as beam management. One or more models can be implemented at a first device 110 (shown as model 115) or a second device 120 (not shown), or both (not shown). The first device 110 and / or the second device 120 can perform beam management or perform training by running inference. For illustrative purposes, some example embodiments will be described below using model 115 implemented at the first device 110.

[0059] It should be understood that Figure 1 The number of devices and their connections shown are for illustrative purposes only and do not imply any limitation. Communication environment 100 may include any suitable number of devices configured to implement the exemplary embodiments of this disclosure.

[0060] In the following description, for illustrative purposes, some exemplary embodiments are described in which the first device 110 operates as a terminal device and the second device 120 operates as a network device. However, in some exemplary embodiments, the operations described in connection with the terminal device can be implemented at the network device or other devices, and the operations described in connection with the network device can be implemented at the terminal device or other devices.

[0061] Communication in communication environment 100 can be implemented according to any suitable communication protocol(s), including but not limited to cellular communication protocols such as first-generation (1G), second-generation (2G), third-generation (3G), fourth-generation (4G), fifth-generation (5G), and sixth-generation (6G), wireless local network communication protocols such as IEEE 802.11, and / or any other currently known or future-developed protocols. Furthermore, communication can utilize any suitable wireless communication technology, including but not limited to: Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Frequency Division Duplex (FDD), Time Division Duplex (TDD), Multiple-Input Multiple-Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM), Discrete Fourier Transform Extended OFDM (DFT-s-OFDM), and / or any other currently known or future-developed technologies.

[0062] Figure 2 Signaling flow 200 for path loss prediction for power control according to some example embodiments of this disclosure is shown. Signaling flow 200 relates to... Figure 1 The first device 110 and the second device 120. For illustrative purposes, the following will be discussed... Figure 1 Signaling flow 200 is described. For discussion purposes, some example embodiments are described, wherein the first device 110 is implemented as a terminal device and the second device 120 is implemented as a network device.

[0063] In operation, the first device 110 acquires (230) at least one TCI state for transmission to the second device 120. This at least one TCI state is associated with at least one reference signal for determining a path loss value. As used herein, the term "reference signal for determining a path loss value" may also be referred to as a "path loss reference signal" or "PL-RS". In embodiments where the first device 110 is a terminal device and the second device 120 is a network device, the transmission to the second device 120 may be referred to as a UL transmission.

[0064] In some example embodiments, at least one reference signal may include or be at least one of the following, or may be associated with at least one of the following: at least one predicted beam, at least one predicted reference signal, or at least one predicted TCI state. For example, the path loss reference signal may correspond to at least one predicted beam, at least one predicted RS, or at least one predicted TCI state from model 115.

[0065] In some example embodiments, the first device 110 may be indicated as at least one TCI state for (multiple) UL transmissions, such as a combined TCI state or a UL TCI state, wherein the TCI state may be associated with a path loss reference signal (PL-RS) corresponding to a predicted beam (e.g., an SSB or CSI-RS beam).

[0066] It should be noted that, depending on the circumstances, the predicted beam may or may not be previously measured (in some cases). For example, assuming a spatial beam prediction AI / ML model and assuming that set B (the set of beams whose measurements are input into the AI / ML model (e.g., via RSRP, etc.)) is distinct from set A (the complete set of beams on which predictions will operate), some beams / RS may not be measured but only predicted. In another case, assuming a temporal beam prediction AI / ML model is employed and assuming that the beams of set A are measured during the observation window (whose measurements are input into the AI / ML model, e.g., via RSRP, etc.) and predicted during the prediction window, this means that predictions associated with the complete set of beams A or the best beam of set A (e.g., predicted RSRP, predicted ID, etc.) are provided as the output of the AI / ML model.

[0067] In some example embodiments, at least one TCI state can be obtained based on the prediction or determination of at least one TCI state. For example, the obtained at least one TCI state may be at least one predicted TCI state. Alternatively or additionally, in some example embodiments, the second device 120 may transmit (210) an indication or configuration of at least one TCI state to the first device 110. The first device 110 may receive (220) the indication and obtain (230) the at least one TCI state based on the indication. The indication or configuration may be transmitted (210) via downlink control information (DCI), media access control (MAC) control element (CE), radio resource control (RRC), or any other suitable message or signaling.

[0068] In some example embodiments, at least one TCI state may include quasi-co-location (QCL) information or source reference signal information. The first device 110 may determine at least one reference signal based on the quasi-co-location information or source reference signal information. That is, at least one path loss reference signal may be determined based on (or may be) the RS provided by the TCI state, for example, through the QCL (quasi-co-location) information (or source RS) included in the TCI state.

[0069] Alternatively or additionally, in some example embodiments, the first device 110 may receive from the second device 120 at least one of the following: configuration of at least one reference signal, or association information between at least one reference signal and at least one TCI state. The first device 110 may determine at least one reference signal based on at least one of the configuration or association information. For example, the first device 110 may have been configured with or may have access to predicted PL information, such as predicted PL-RS(s) and / or measured PL-RS(s), which can be used to predict / determine path loss. For example, the TCI state can be associated with the predicted PL-RS information by configuration or indication. Then, when the first device 110 obtains the TCI state to be used for UL transmission, the first device 110 may determine / update the corresponding path loss based on at least a portion of the predicted RSRP(s) / path loss corresponding to the PL-RS(s). Note that the association information or configuration may be indicated / updated via, for example, RRC, MAC CE, and / or DCI.

[0070] The first device 110 selects (240) at least one of at least a predicted signal power of at least one reference signal or at least one measured signal power of at least one reference signal to determine a path loss value. The first device 110 determines (245) the transmitted power based on the path loss value. For example, the signal power can be RSRP or any other parameter of signal quality. That is, the predicted signal power can be the predicted RSRP(s), and the measured signal power can be the measured RSRP(s). If the path loss(s) RS(s) corresponds to the predicted RS(s) or (multiple) beams, then at least one predicted RSRP(s) can be the predicted RSRP(s) value of the predicted RS(s) or (multiple) beams. If the RSRP(s) is predicted for the RS(s), then the predicted RSRP(s) value(s) can be the predicted RSRP(s) value(s) of the RS(s). It should be noted that the RS(s) associated with the predicted signal power can be the same as or different from the RS(s) associated with the measured signal power. In some example embodiments, by using, for example Figure 1 The AI / ML model in Model 115 is used to determine at least one predicted signal power of at least one reference signal.

[0071] In some example embodiments, at least one predicted signal power or at least one measured signal power can be selected based on at least one of the following: indication information from the second device 120 regarding the selection of at least one predicted signal power or at least one measured signal power, prediction quality of at least one predicted signal power, timing information of at least one predicted signal power, timing information of at least one measured signal power, or the time of transmission. For example, the indication information transmitted by the second device 120 may indicate whether a predicted signal power or a measured signal power should be selected, or it may indicate whether a certain predicted signal power or a certain measured signal power should be selected. As another example, the indication information may indicate a threshold time period or threshold quality for selecting the signal power. The indication information may be transmitted via DCI, MAC CE, or RRC.

[0072] As an example, the prediction quality of the predicted signal power can be indicated by the confidence information of the prediction model (such as model 115) used to predict the signal power of the reference signal. Alternatively or additionally, the prediction quality of the predicted signal power can be indicated by a performance metric obtained through performance monitoring of the prediction model.

[0073] In some example embodiments, if the predicted quality is less than a threshold quality, the first device 110 may select (240) the measured signal power to determine the path loss value. Otherwise, if the predicted quality is greater than or equal to the threshold quality, the first device 110 may select at least (240) the predicted signal power to determine the transmission power. For example, the first device 110 may select (240) the predicted signal power to determine the path loss value, or it may select (240) both the predicted signal power and the measured signal power to determine the path loss value.

[0074] In some example embodiments, at least one predicted signal power includes at least a first predicted signal power at a first time moment, and at least one measured signal power includes at least a first measured signal power at a second time moment. If a first time period between the first time moment and the second time moment is greater than or equal to a first threshold time period, the first device 110 may select (240) at least the first measured signal power to determine a path loss value. For example, the first device 110 may select the first measured signal power and optionally previously measured or predicted signal power(s) to determine a path loss value. If the first time period is less than the first threshold time period, the first device 110 may select (240) at least the first predicted signal power or another measured signal power to determine a path loss value. For example, the first device 110 may select the first predicted signal power and optionally previously measured or predicted signal power to determine a path loss value. For another example, the first device 110 may select the first predicted signal power and the first measured signal power and optionally previously measured or predicted signal power to determine a path loss value.

[0075] Note that threshold time periods can be provided via specifications or higher-level configurations (e.g., via RRC) or by indications (e.g., via MAC CE or DCI). It should be understood that the terms “first,” “second,” etc., used herein are not intended to restrict order or sequence. For example, a first moment can be before, after, or simultaneously with a second moment.

[0076] Alternatively, in some example embodiments, if the first time period between the first time point and the second time point is less than or equal to a first threshold time period, the first device 110 may select (240) at least a first measured signal power to determine the path loss value. For example, the first device 110 may select the first measured signal power and optionally previously measured or predicted signal power(s) to determine the path loss value. If the first time period is longer than the first threshold time period, the first device 110 may select (240) at least a first predicted signal power or another measured signal power to determine the path loss value. For example, the first device 110 may select the first predicted signal power and optionally previously measured or predicted signal power to determine the path loss value. For another example, the first device 110 may select the first predicted signal power and the first measured signal power and optionally previously measured or predicted signal power to determine the path loss value.

[0077] In some example embodiments, at least one measured signal power includes at least the first measured signal power at the second time point. If the second time period between the second time point and the transmission time is less than or equal to a second threshold time period, the first device 110 may select at least (240) a first predicted signal power or another measured signal power to determine a path loss value. For example, the first device 110 may select the first predicted signal power and optionally a previously measured or predicted signal power to determine a path loss value. If the second time period between the second time point and the time associated with the transmission is greater than the second threshold time period, the first device 110 may select (240) the measured signal power to determine a path loss value. For example, the first device 110 may select the first measured signal power and optionally a previously measured or predicted signal power to determine a path loss value. For another example, the first device 110 may select the first predicted signal power and the first measured signal power and optionally a previously measured or predicted signal power to determine a path loss value. Note that the threshold time period may be provided by specification or by higher-level configuration (e.g., via RRC) or by indication (e.g., via MAC CE or DCI).

[0078] Alternatively, in some example embodiments, if the second time period between the second moment and the moment of transmission is greater than or equal to the second threshold time period, the first device 110 may select (240) at least a first predicted signal power or another measured signal power to determine the path loss value. For example, the first device 110 may select the first predicted signal power and optionally a previously measured or predicted signal power to determine the path loss value. If the second time period between the second moment and the moment associated with transmission is less than the second threshold time period, the first device 110 may select (240) a measured signal power to determine the path loss value. For example, the first device 110 may select the first measured signal power and optionally a previously measured or predicted signal power to determine the path loss value. For another example, the first device 110 may select the first predicted signal power and the first measured signal power and optionally a previously measured or predicted signal power to determine the path loss value. Note that the threshold time period may be provided by specification or by higher-level configuration (e.g., via RRC) or by indication (e.g., via MAC CE or DCI).

[0079] It should be understood that these rules or thresholds used to select signal power can be provided through specifications or through higher-level configuration (e.g., via RRC) or through indications (e.g., via MAC CE or DCI). These rules or conditions can vary. Any suitable rules or conditions can be applied. The scope of this disclosure is not limited thereto.

[0080] In some example embodiments, selecting at least one measured signal power includes or implies that the first device 110 measures at least one reference signal. That is, the signal power of at least one measured signal may not always be available, and selecting measurement rather than prediction means that the first device 110 measures the corresponding RS (assuming that the corresponding RS is transmitted by the second device 120).

[0081] In some example embodiments, the first device 110 may determine a path loss value based on a predicted set of signal power and an optional set of measured signal power. The predicted set of signal power may be filtered. The measured set of signal power may also be filtered. Filtering may correspond to a higher or lower layer function that filters or averages (e.g., over time) the signal power, such as an RSRP value.

[0082] As an example, the first device 110 may determine the filtered signal power of the reference signal based on a first predicted signal power of the reference signal at a third time and a second predicted signal power of the reference signal at a fourth time. The first device 110 may determine the path loss value based at least in part on the filtered signal power. The filtering of the signal power may be high-level filtering or low-level filtering. It should be understood that there may be more than two predicted signal powers and / or two or more measured signal powers to be filtered.

[0083] In some example embodiments, the time period between the third and fourth moments is less than or equal to a third threshold time period. For example, if the time period between the third and fourth moments is greater than the third threshold time period, the first device 110 may not perform filtering, but instead use the latest predicted signal power of the first and second predicted signal powers to determine the transmission power.

[0084] In some example embodiments, the first device 110 may discard at least one of a first predicted signal power or a second predicted signal power. The first device 110 may determine a path loss value based on the filtered signal power without using the discarded predicted signal power. For example, the path loss may be determined at least in part based on the RSRP of the higher-layer filtering, and therefore, in at least some cases, predicted RSRP(s)(s) values(s) can be discarded from the input to update or determine the RSRP of the higher-layer filtering.

[0085] In some example embodiments, the first device 110 may determine a path loss value associated with transmission based on at least one of the selected (240), at least one predicted signal power of the reference signal, or at least one measured signal power of the reference signal. The first device 110 may determine (245) the transmission power based on the path loss value. The reference... Figure 3 and Figure 4 Further details regarding the determination of transmission power are described.

[0086] In some example embodiments, the first device 110 transmits (250) the transmission to the second device 120 based on the transmission power. The second device 120 receives (260) the transmission based on the transmission power.

[0087] These embodiments enable UL power control (PC) operation within a beam prediction framework. This solution may not require additional overhead or processes to maintain path loss measurements. This reduces or eliminates the need for PL-RS updates and the latency caused by such updates. Furthermore, this solution can be applied on top of a beam prediction framework, or it can be applied independently of the framework.

[0088] As described, the first device 110 can determine the transmission power at least in part based on the predicted signal power (such as the predicted RSRP values). Figure 3 A flowchart of a method 300 for determining transmission power according to some example embodiments of the present disclosure is shown. For discussion purposes, [the following will be discussed]. Figure 1 Method 300 is described by the angle of the first device 110 in the middle.

[0089] In block 310, the first device 110 obtains a TCI state corresponding to the path loss RS associated with a transmission to the second device 120 (such as an uplink transmission / channel / signal (e.g., PUCCH, PUSCH, SRS, PRACH)). The path loss reference signal may correspond to a predicted beam, predicted RS, or predicted TCI state, or even predicted quasi-colocation information from model 115. In some example embodiments, the first device 110 may be indicated as a TCI state for (multiple) UL transmissions, such as a combined TCI state or a UL TCI state, wherein the TCI state may be associated with a path loss reference signal corresponding to a predicted beam (e.g., an SSB or CSI-RS beam).

[0090] It should be noted that, depending on the circumstances, the predicted beams may or may not be previously measured (in some cases). For example, suppose set B (the set of beams / RS whose measurements are input into an AI / ML model (e.g., via RSRP, etc.)) is different from set A (the complete set of beams predicted to operate on it), then some beams / RS may not be measured, but only predicted.

[0091] At block 320, the first device 110 determines that the path loss RS corresponds to the predicted RS. For example, the predicted RS can be predicted by model 115. For the predicted beam, the predicted RS, or the predicted TCI state, signal power such as RSRP values ​​can be predicted by model 115. Alternatively, for the path loss RS, an RSRP value is predicted for the corresponding beam.

[0092] At block 330, the first device 110 can determine or update the path loss corresponding to the TCI state based on the predicted RSRP of the predicted RS. For example, the first device 110 can use at least the predicted RSRP(s) to determine the power of the UL transmission associated with the TCI state.

[0093] At block 340, the first device 110 may determine the transmission power of the UL transmission(s) based at least in part on the path loss determined at block 330. In an example embodiment, the first device 110 may determine the power of the UL transmission based on a determined or updated path loss corresponding to the path loss RS based on the predicted RSRP. For example, the path loss may be determined based solely on the predicted RSRP(s)(s) and not on previously measured RSRP(s). Alternatively or additionally, the path loss may depend on both the predicted RSRP(s) ...

[0094] In some example embodiments, the predicted and / or measured RSRP values(s) can be filtered, for example, by higher-level filtering or lower-level filtering. Path loss can be determined at least in part based on the higher-level filtered RSRP, and therefore the predicted RSRP(s)(s) are used as input to update or determine the higher-level filtered RSRP. In variations, path loss can be determined based on a lower-level filtered or unfiltered function of the RSRP(s) ...

[0095] The first device 110 can determine the power of UL transmissions (such as Physical Uplink Shared Channel (PUSCH) transmissions) based on path loss, following the process described in the standard. In summary, the first device 110 indicates or determines closed-loop parameters (closed-loop index, TPC command) and open-loop parameters (path loss reference RS, p0, α). The TPC command is carried in the DCI that schedules the PUSCH transmission. Furthermore, the TPC command (and the corresponding closed-loop index) can be jointly carried to multiple first devices 110 using a group of common DCIs in DCI format 2-2.

[0096] The main power control parameters upon which PUSCH transmission power depends are the following elements: closed-loop index (also known as PC adjustment state), TPC commands (fb, f, c, absolute or cumulative TPC commands), path loss reference RS (reference signal), p0 (also represented as P0_UE_PUSCH), and α (used for partial or full path loss compensation). DETLA_TF (i.e., (Sometimes referred to as the power adjustment component) essentially models how the required received power changes when the number of information, such as bits per resource element (BPRE), changes due to different modulation schemes and channel coding rates.

[0097] Specifically, as shown in Table 2, PUSCH power is determined based on the following: The estimated path loss in Table 2 can be the path loss determined at least based on the predicted RSRP(s) values(s).

[0098] Table 2

[0099] In some example embodiments, the probe reference signal (SRS) power control is somewhat similar to the PUSCH power control. Specifically, as shown in Table 3, the SRS transmission power is determined based on the following: The estimated path loss in Table 3 can be the path loss determined at least based on predicted RSRP(s) values(s).

[0100] Table 3

[0101] In some example implementations, the Physical Uplink Control Channel (PUCCH) transmission power is determined based on the following shown in Table 4. The estimated path loss in Table 4 may be the path loss determined at least based on the predicted RSRP(s) values(s).

[0102] Table 4

[0103] Note that PL refers to the path loss component / parameter, and is defined as follows. =Reference Signal Power - RSRP of Higher Layer Filtering, where reference Signal Power is provided by higher layers, and RSRP is defined for the reference serving cell, and the higher layer filter configuration provided by QuantityConfig is defined for the reference serving cell. Examples of these parameters are shown in Table 5 below. The estimated path loss in Table 5 can be the path loss determined at least based on the predicted RSRP(s) values(s).

[0104] Table 5

[0105] These embodiments enable UL power control (PC) operation within a beam prediction framework. This solution may not require additional overhead or processes to maintain path loss measurements. This reduces or eliminates the need for PL-RS updates and the latency caused by such updates. Furthermore, this solution can be applied on top of a beam prediction framework, or it can be applied independently of the framework.

[0106] Already about Figure 3 Several example embodiments regarding the determination of transmission power are described. Figure 4 Another flowchart of a method 400 for determining transmission power according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 400 is described by the angle of the first device 110 in the middle.

[0107] At box 410, the first device 110 can determine the prediction accuracy (or prediction quality). For example, the prediction accuracy can be based on the confidence or probability information of model 115, or the performance monitoring process of model 115.

[0108] At box 420, the first device 110 can determine whether the prediction accuracy is higher than a threshold. If the prediction accuracy is higher than the threshold, then at box 430, the first device 110 can use the predicted RSRP(s) to determine path loss. For example, the first device 110 can use the predicted RSRP(s) as input to the RSRP of the higher-layer filter.

[0109] If the prediction accuracy is below or equal to a threshold, then at box 440, the first device 110 can discard the predicted RSRP(s) from the input used for path loss determination. For example, the first device 110 can use the measured RSRP(s) to perform path loss determination.

[0110] In some example embodiments, the path loss reference signal corresponds to a beam, for which beam ID / (multiple) RSRP values ​​are predicted. If the confidence or probability or quality information associated with the output inference of the AI / ML model indicates low-quality prediction and / or the performance monitoring process indicates low performance metrics or relevant key performance indicators (KPIs) (such as beam prediction accuracy, RSRP difference, etc.), then the first device 110 uses only the measured RSRP values ​​(at least excluding the predicted RSRP values) to determine the power of the UL transmission associated with the TCI state.

[0111] It should be noted that whenever the output inference of the AI / ML model indicates high-quality predictions and / or the performance monitoring process indicates high-performance metrics, the path loss can depend on both the measured RSRP value(s) and the predicted RSRP value. For example, if the KPI or performance metric (such as prediction accuracy, confidence level, etc.) is above a threshold.

[0112] If inference indicates low-quality predictions and / or the performance monitoring process indicates low-performance metrics, such as if KPIs or performance metrics (e.g., prediction accuracy, confidence level, etc.) are below a threshold, path loss can be determined based solely on the measured RSRP(s) and not on the predicted RSRP(s). In this case, at least some of the predicted RSRP(s) (which correspond to low-quality predictions and / or low-performance metrics) can be discarded.

[0113] Path loss can be determined at least in part based on the RSRP of the higher-level filter, and therefore, in at least some cases, predicted RSRP values ​​(multiple) can be discarded from the input to update or determine the RSRP of the higher-level filter.

[0114] These embodiments enable UL power control (PC) operation within a beam prediction framework. This solution may not require additional overhead or processes to maintain path loss measurements. This reduces or eliminates the need for PL-RS updates and the latency caused by such updates. Furthermore, this solution can be applied on top of a beam prediction framework, or it can be applied independently of the framework.

[0115] It should be understood that signaling flows, method 300, and / or method 400 can be executed individually or in any combination. These signaling flows and / or methods can improve path loss estimation. Therefore, UL power control can be enhanced.

[0116] Figure 5 A flowchart of an example method 500 implemented at a first device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 500 is described by the angle of the first device 110 in the middle.

[0117] In block 510, the first device 110 obtains at least one TCI state for transmission to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value.

[0118] At block 520, the first device 110 selects at least one of at least a predicted signal power of at least one reference signal or at least one measured signal power of at least one reference signal to determine the path loss value.

[0119] At box 530, the first device 110 determines the transmission power based on the path loss value.

[0120] In some example embodiments, at least one of the predicted signal power or at least one of the measured signal power is selected based on at least one of the following: indication information from the second device regarding the selection of at least one of the predicted signal power or at least one of the measured signal power, the prediction quality of at least one predicted signal power, the timing information of at least one predicted signal power, the timing information of at least one measured signal power, or the time of transmission.

[0121] In some example embodiments, the prediction quality of the predicted signal power is indicated by at least one of the following: confidence information of the prediction model used to predict the signal power of the reference signal, or a performance metric obtained through performance monitoring of the prediction model.

[0122] In some example embodiments, method 500 further includes: selecting at least one measured signal power to determine a path loss value based on the predicted quality being less than a threshold quality; and selecting at least one predicted signal power to determine a path loss value based on the predicted quality being greater than or equal to the threshold quality.

[0123] In some example embodiments, at least one predicted signal power includes at least a first predicted signal power at a first time moment, at least one measured signal power includes at least a first measured signal power at a second time moment, and the method 500 further includes: selecting at least a first measured signal power or another measured signal power to determine a path loss value based on a first time period between the first time moment and the second time moment being greater than or equal to a first threshold time period; and selecting at least a first predicted signal power or another measured signal power to determine a path loss value based on a first time period being less than a first threshold time period.

[0124] In some example embodiments, at least one predicted signal power includes at least a first predicted signal power at a first time moment, at least one measured signal power includes at least a first measured signal power at a second time moment, and the method 500 further includes: selecting at least a first measured signal power to determine a path loss value based on a first time period between the first time moment and the second time moment being less than or equal to a first threshold time period; and selecting at least a first predicted signal power or another measured signal power to determine a path loss value based on a first time period being greater than the first threshold time period.

[0125] In some example embodiments, at least one measured signal power includes at least the first measured signal power at the second time point, and method 500 further includes: selecting at least the first measured signal power to determine a path loss value based on a second time period between the second time point and the transmission time point being less than or equal to a second threshold time period; and selecting at least one predicted signal power to determine a path loss value based on a second time period being greater than the second threshold time period.

[0126] In some example embodiments, at least one measured signal power includes at least the first measured signal power at the second time point, and method 500 further includes: selecting at least the first measured signal power to determine a path loss value based on a second time period between the second time point and the transmission time point being greater than or equal to a second threshold time period; and selecting at least one predicted signal power to determine a path loss value based on the second time period being less than the second threshold time period.

[0127] In some example embodiments, selecting at least one measured signal power includes or implies that the first device measures at least one reference signal.

[0128] In some example embodiments, at least one predicted signal power includes at least a first predicted signal power at a third time and a second predicted signal power at a fourth time, and the method 500 further includes: determining the filtered signal power of the reference signal based at least on the first predicted signal power and the second predicted signal power; and determining the path loss value based at least in part on the filtered signal power.

[0129] In some example embodiments, the time interval between the third and fourth moments is less than or equal to the third threshold time interval.

[0130] In some example embodiments, method 500 further includes: discarding at least one of a first predicted signal power or a second predicted signal power; and determining a path loss value based on the filtered signal power without using the discarded predicted signal power.

[0131] In some example embodiments, method 500 further includes: performing a transmission to a second device based on the transmission power.

[0132] In some example embodiments, at least one TCI state is obtained based on at least one of the following: an indication of at least one TCI state from a second device, or a prediction of at least one TCI state.

[0133] In some example embodiments, at least one TCI state includes quasi-co-location information or source reference signal information, and the first device 110 can determine at least one reference signal based on the quasi-co-location information or source reference signal information.

[0134] In some example embodiments, method 500 further includes: receiving from the second means at least one of the following: configuration of at least one reference signal, or association information between at least one reference signal and at least one TCI state; and determining at least one reference signal based on at least one of the configuration or association information.

[0135] In some example embodiments, at least one reference signal is associated with at least one of the following: at least one predicted beam, at least one predicted reference signal, or at least one predicted TCI state.

[0136] In some example embodiments, at least one predicted signal power of at least one reference signal is determined by using an AI / ML model.

[0137] Figure 6 A flowchart of an example method 600 implemented at a second device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 600 is described by the angle of the second device 120 in the middle.

[0138] In block 610, the second device 120 transmits to the first device an indication of at least one TCI state for transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value.

[0139] In block 620, the second device 120 receives the transmission from the first device, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal.

[0140] In some example embodiments, the indication of at least one TCI state includes quasi-co-location information or source reference signal information, and at least one reference signal is based on the quasi-co-location information or source reference signal information.

[0141] In some example embodiments, method 600 may further include transmitting to the first device at least one of the following: configuration of at least one reference signal, or association information between at least one reference signal and at least one TCI state.

[0142] In some example embodiments, method 600 may further include transmitting to a first device indication information regarding the selection of at least one of at least a predicted signal power or at least one measured signal power.

[0143] In some example embodiments, at least one reference signal includes or is associated with at least one of the following: at least one predicted beam, at least one predicted reference signal, or at least one predicted TCI state.

[0144] In some example embodiments, a first device capable of performing any method 500 (e.g., Figure 1 The first device 110 may include a component for performing the corresponding operation of method 500. This component may be implemented in any suitable form. For example, the component may be implemented by a circuit or a software module. The first device may be implemented as or included in... Figure 1 In the first device 110.

[0145] In some example embodiments, the first device includes: components for obtaining at least one Transmission Configuration Indicator (TCI) state for transmission to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; components for selecting at least one of at least one predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal to determine the path loss value; and components for determining the transmission power of the transmission based on the path loss value.

[0146] In some example embodiments, the first device further includes components for performing other operations in some example embodiments of method 500 or the first device 110. In some example embodiments, the components include: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first device to perform a corresponding operation.

[0147] In some example embodiments, a second device capable of performing any method 600 (e.g., Figure 1 The second device 120 may include components for performing the corresponding operations of method 600. These components may be implemented in any suitable form. For example, the components may be implemented by circuitry or software modules. The second device may be implemented as or included in... Figure 1 The second device 120 in the middle.

[0148] In some example embodiments, the second device includes: a component for transmitting to the first device an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; and a component for receiving a transmission from the first device, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least one predicted signal power of at least one reference signal or at least one measured signal power of at least one reference signal.

[0149] In some example embodiments, the second device further includes components for performing other operations in some example embodiments of method 600 or the second device 120. In some example embodiments, the components include: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the second device to perform a corresponding operation.

[0150] Figure 7 This is a simplified block diagram of a device 700 suitable for implementing an example embodiment of the present disclosure. The device 700 can be provided to implement a communication device, such as... Figure 1 The first device 110 or the second device 120 shown. As shown, the device 700 includes one or more processors 710, one or more memories 720 coupled to the processors 710, and one or more communication modules 740 coupled to the processors 710.

[0151] Communication module 740 is used for bidirectional communication. Communication module 740 has one or more communication interfaces to facilitate communication with one or more other modules or devices. The communication interface can represent any interface required for communication with other network elements. In some example embodiments, communication module 740 may include at least one antenna.

[0152] As a non-limiting example, processor 710 can be any type suitable for a local technology network and can include one or more of the following: general-purpose computer, special-purpose computer, microprocessor, digital signal processor (DSP), and processor based on a multi-core processor architecture. Device 700 can have multiple processors, such as application-specific integrated circuit chips that are time-dependent on a clock of a synchronous main processor.

[0153] Memory 720 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 724, electrically programmable read-only memory (EPROM), flash memory, hard disk, optical disc (CD), digital video disc (DVD), optical disc, laser disc, and other magnetic and / or optical storage. Examples of volatile memories include, but are not limited to, random access memory (RAM) 722 and other volatile memories that do not retain data during power loss.

[0154] Computer program 730 includes computer-executable instructions that are executed by an associated processor 710. The instructions of program 730 may include instructions for performing operations / actions of some example embodiments of this disclosure. Program 730 may be stored in memory (e.g., ROM 724). Processor 710 can perform any suitable actions and processes by loading program 730 into RAM 722.

[0155] The exemplary embodiments of this disclosure can be implemented by program 730, enabling device 700 to perform as described in the reference. Figures 2 to 6 Any process discussed in this disclosure. Exemplary embodiments of this disclosure may also be implemented by hardware or by a combination of software and hardware.

[0156] In some example embodiments, program 730 may be tangibly contained in a computer-readable medium, which may be included in device 700 (such as memory 720) or other storage devices accessible by device 700. Device 700 may load program 730 from the computer-readable medium into RAM 722 for execution. In some example embodiments, the computer-readable medium may include any type of non-transitory storage medium, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. As used herein, the term "non-transitory" is a limitation on the medium itself (i.e., tangible, not tactile), rather than a limitation on the persistence of data storage (e.g., RAM and ROM).

[0157] Figure 8 An example of a computer-readable medium 800 is shown, which may be in the form of a CD, DVD, or other optical storage disc. A program 730 is stored on the computer-readable medium 800.

[0158] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are illustrated and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, as non-limiting examples, the blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0159] Some exemplary embodiments of this disclosure also provide at least one computer program product tangibly stored on a computer-readable medium, such as a non-transitory computer-readable medium. The computer program product includes computer-executable instructions that execute in a device on a target physical or virtual processor, such as those included in a program module, to perform any of the methods described above. Typically, a program module includes routines, programs, libraries, objects, classes, components, data structures, etc., that perform a particular task or implement a particular abstract data type. In various embodiments, the functionality of a program module can be combined or split among program modules as needed. The machine-executable instructions for a program module can execute within a local or distributed device. In a distributed device, the program module can reside in both local and remote storage media.

[0160] Program code used to perform the methods of this disclosure may be written in any combination of one or more programming languages. The program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a stand-alone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0161] In the context of this disclosure, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, etc.

[0162] Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination thereof. More specific examples of computer-readable storage media will include electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0163] Furthermore, although operations are described in a specific order, this should not be construed as requiring that such operations be performed in the specific order shown or sequentially, or that all shown operations be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the discussion above, these details should not be construed as limiting the scope of this disclosure, but rather as descriptions of features that may be specific to particular embodiments. Unless explicitly stated otherwise, certain features described in the context of a single embodiment may also be implemented in combination in a single embodiment. Conversely, unless explicitly stated otherwise, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0164] Although this disclosure has been described in language specific to structural features and / or methodological actions, it should be understood that the disclosure as defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are disclosed as exemplary forms for implementing the claims.

Claims

1. A first device, comprising: At least one processor; as well as At least one memory storing instructions that, when executed by the at least one processor, cause the first device to: At least one Transmission Configuration Indicator (TCI) state is obtained for transmission to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; The path loss value is determined by selecting at least one of the predicted signal power of the at least one reference signal or at least one measured signal power of the at least one reference signal; as well as The transmission power is determined based on the path loss value.

2. The first apparatus of claim 1, wherein the at least one of the at least predicted signal power or the at least one measured signal power is selected based on at least one of the following: Instructions from the second device regarding the selection of at least one of the at least predicted signal power or the at least one measured signal power. The prediction quality of the at least one predicted signal power, The timing information of at least one predicted signal power The timing information of the at least one measured signal power, or The timing of the transmission.

3. The first apparatus of claim 2, wherein the prediction quality of the at least one predicted signal power is indicated by at least one of the following: Confidence information of the prediction model used to predict the signal power of the reference signal, or Performance metrics are obtained through performance monitoring of the prediction model.

4. The first device according to claim 2 or 3, wherein the first device is further caused to: Based on the predicted quality being less than a threshold quality, the path loss value is determined by selecting the signal power measured at least one of the above-mentioned measurements; and Based on the predicted quality being higher than or equal to the threshold quality, the path loss value is determined by selecting the signal power of at least one predicted signal.

5. The first device according to any one of claims 2-4, wherein the at least one predicted signal power includes at least a first predicted signal power at a first time moment, the at least one measured signal power includes at least a first measured signal power at a second time moment, and the first device is further caused to: Based on the fact that a first time period between the first time point and the second time point is greater than or equal to a first threshold time period, at least the first measured signal power or another measured signal power is selected to determine the path loss value; and Based on the fact that the first time period is less than the first threshold time period, at least the first predicted signal power is selected to determine the path loss value.

6. The first device according to any one of claims 2-4, wherein the at least one predicted signal power includes at least a first predicted signal power at a first time moment, the at least one measured signal power includes at least a first measured signal power at a second time moment, and the first device is further caused to: Based on the fact that a first time period between the first time point and the second time point is less than or equal to a first threshold time period, at least the first measured signal power or another measured signal power is selected to determine the path loss value; and Based on the first time period being greater than the first threshold time period, at least the first predicted signal power is selected to determine the path loss value.

7. The first device according to any one of claims 2-6, wherein the at least one measured signal power includes at least the signal power measured at the first time point at the second moment, and the first device is further caused to: Based on the fact that a second time period between the second time point and the time point of transmission is less than or equal to a second threshold time period, at least the signal power measured first is selected to determine the path loss value; and Based on the second time period being greater than the second threshold time period, the path loss value is determined by selecting at least one predicted signal power.

8. The first device according to any one of claims 2-6, wherein the at least one measured signal power includes at least the signal power measured at the first time point at the second moment, and the first device is further caused to: Based on the second time period between the second time point and the time point of transmission being greater than or equal to a second threshold time period, at least the signal power measured first is selected to determine the path loss value; and Based on the fact that the second time period is less than the second threshold time period, the path loss value is determined by selecting the at least one predicted signal power.

9. The first apparatus according to any one of claims 2-8, wherein the selection of the signal power of the at least one measurement includes or implies that the first apparatus measures the at least one reference signal.

10. The first apparatus according to any one of claims 1-9, wherein the at least one predicted signal power includes at least a first predicted signal power at a third time and a second predicted signal power at a fourth time, and the first apparatus is further caused to: The filtered signal power of the reference signal is determined based at least on the first predicted signal power and the second predicted signal power; and The path loss value is determined at least in part based on the filtered signal power.

11. The first apparatus according to claim 10, wherein the time interval between the third time interval and the fourth time interval is less than or equal to a third threshold time interval.

12. The first device according to claim 10 or 11, wherein the first device is further caused to: Discard at least one of the first predicted signal power or the second predicted signal power; and The path loss value is determined based on the filtered signal power without using the discarded predicted signal power.

13. The first device according to any one of claims 1-12, wherein the first device causes: The transmission to the second device is performed based on the transmission power.

14. The first device according to any one of claims 1-13, wherein the at least one TCI state is obtained based on at least one of the following: An indication of the at least one TCI state or a prediction of the at least one TCI state from the second device.

15. The first apparatus according to any one of claims 1-14, wherein the at least one TCI state includes quasi-co-address information or source reference signal information, and the first apparatus is caused to: The at least one reference signal is determined based on the quasi-co-location information or the source reference signal information.

16. The first device according to any one of claims 1-15, wherein the first device causes: Receive from the second device at least one of the following: the configuration of the at least one reference signal, or the association information between the at least one reference signal and the at least one TCI state; and The at least one reference signal is determined based on at least one of the configuration or the associated information.

17. The first apparatus according to any one of claims 1-16, wherein the at least one reference signal comprises or is associated with at least one of the following: at least one predicted beam, at least one predicted reference signal, or at least one predicted TCI state.

18. The first apparatus according to any one of claims 1-17, wherein the at least one predicted signal power of the at least one reference signal is determined by using artificial intelligence (AI) and / or machine learning (ML).

19. A second device, comprising: At least one processor; as well as At least one memory storing instructions, which, when executed by the at least one processor, cause the second device to: Transmit to a first device an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; as well as The transmission is received from the first device, wherein the transmission power is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least a predicted signal power of the at least one reference signal or at least a measured signal power of the at least one reference signal.

20. The second apparatus of claim 19, wherein the indication of the at least one TCI state includes quasi-co-location information or source reference signal information, and the at least one reference signal is based on the quasi-co-location information or source reference signal information.

21. The second device according to claim 19 or 20, wherein the second device is caused to: Transmit at least one of the following to the first device: the configuration of the at least one reference signal, or the association information between the at least one reference signal and the at least one TCI state.

22. The second device according to any one of claims 19-21, wherein the second device causes: Transmit instruction information to the first device regarding the selection of at least one of the at least predicted signal power or the at least one measured signal power.

23. The second apparatus according to any one of claims 19-21, wherein the at least one reference signal comprises or is associated with at least one of the following: at least one predicted beam, at least one predicted reference signal, or at least one predicted TCI state.

24. A method comprising: At the first device, at least one Transmission Configuration Indicator (TCI) state for transmission to the second device is obtained, the at least one TCI state being associated with at least one reference signal for determining a path loss value; Select at least one of the predicted signal power of the at least one reference signal or the measured signal power of the at least one reference signal to determine the path loss value; as well as The transmission power is determined based on the path loss value.

25. A method comprising: The second device transmits to the first device an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value. as well as The transmission is received from the first device, wherein the transmission power is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least a predicted signal power of the at least one reference signal or at least a measured signal power of the at least one reference signal.

26. A first device, comprising: A component for obtaining at least one Transmission Configuration Indicator (TCI) state for transmission to a second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; Components for selecting at least one of the predicted signal power of the at least one reference signal or the measured signal power of the at least one reference signal to determine the path loss value; as well as A component used to determine the transmission power of the transmission based on the path loss value.

27. A second device, comprising: A component for transmitting to a first device an indication of at least one Transmission Configuration Indicator (TCI) state for a transmission from the first device to the second device, the at least one TCI state being associated with at least one reference signal for determining a path loss value; as well as A component for receiving the transmission from the first device, wherein the transmission power of the transmission is determined based on the path loss value, and wherein the path loss value is determined based on at least one of at least a predicted signal power of the at least one reference signal or at least a measured signal power of the at least one reference signal.

28. A computer-readable medium comprising instructions stored thereon for causing a device to perform at least the method of claim 24 or the method of claim 25.

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