Candidate beam detection

Abstract

Example embodiments of the present disclosure are directed to candidate beam detection A method includes determining an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and determining an evaluation result for the candidate beam set based on the received reference signal.

Description

CANDIDATE BEAM DETECTIONCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority from, and the benefit of, US Provisional Application No. 63 / 703523, filed October 4, 2024, which is hereby incorporated by reference in its entirety.FIELD

[0002] Various example embodiments of the present disclosure generally relate to the field of telecommunication and in particular, to apparatuses, methods, and computer readable storage medium for candidate beam detection.BACKGROUND

[0003] A beam failure recovery procedure is a mechanism for recovering beams when all or part of beams serving user equipment (UE) has failed. The UE needs to perform candidate beam detection and candidate beam selection (CBS) after beam failure in order to recover from the beam failure. In another aspect, Artificial Intelligence / Machine Learning (AI / ML) techniques have been proposed to improve communication performances. For example, an Al / ML model can be used for beam management to predict one or more best beams.SUMMARY

[0004] In a first aspect of the present disclosure, there is provided a first apparatus. The first apparatus comprises at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus at least to: determine an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and receive, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and determine an evaluation result for the candidate beam set based on the received reference signal.

[0005] In a second aspect of the present disclosure, there is provided a method. The method comprises: determining an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and determining an evaluation result for the candidate beam set based on the received reference signal.

[0006] In a third aspect of the present disclosure, there is provided a first apparatus. The first apparatus comprises means for determining an evaluation period for candidate beam detection basedon at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and means for receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and means for determining an evaluation result for the candidate beam set based on the received reference signal.

[0007] In a fourth aspect of the present disclosure, there is provided a computer readable medium. The computer readable medium comprises instructions stored thereon for causing an apparatus to perform at least the method according to the second aspect.

[0008] It is to be understood that the Summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0011] FIG. 2 illustrates a signaling chart of a process of candidate beam detection according to some other example embodiments of the present disclosure;

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

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

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

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

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

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

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

[0019] It shall be understood that although the terms “first,” “second,”..., etc. in front of noun(s) and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another and they do not limit the order of the noun(s). For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and / or” includes any and all combinations of one or more of the listed terms.

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

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

[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “has”, “having”, “includes” and / or “including”, when used herein, specify the presence of stated features, elements, and / or components etc., but do not preclude the presence or addition of one or more other features, elements, components and / or combinations thereof.

[0023] As used in this application, the term “circuitry” may refer to one or more or all of the following:(a) hardware-only circuit implementations (such as implementations in only analog and / or digital circuitry) and(b) combinations of hardware circuits and software, such as (as applicable):(i) a combination of analog and / or digital hardware circuit(s) with software / firmware and(ii) any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and(c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.

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

[0025] As used herein, the term “communication network” refers to a network following any suitable communication standards, such as New Radio (NR), Long Term Evolution (LTE), LTE-Advanced (LTE- A), Wideband Code Division Multiple Access (WCDMA), High-Speed Packet Access (HSPA), Narrow Band Internet of Things (NB-loT) and so on. Furthermore, the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1 G), the second generation (2G), 2.5G, 2.75G, the third generation (3G), the fourth generation (4G), 4.5G, the fifth generation (5G), 5.5G, the sixth generation (6G) communication protocols, and / or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will of course also be future type communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned system.

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

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

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

[0029] As used herein, the term “AI / ML Model” may refer to a data driven algorithm that applies AI / ML techniques to generate a set of outputs based on a set of inputs.

[0030] As used herein, the term “AI / ML model delivery” is a generic term referring to delivery of an AI / ML model from one entity to another entity in any manner. Note: an entity could mean a networknode / function (e.g., gNB, location management function (LMF), etc.), UE, proprietary server, etc.

[0031] As used herein, the term “AI / ML model Inference” may refer to a process of using a trained AI / ML model to produce a set of outputs based on a set of inputs.

[0032] As used herein, the term “AI / ML model testing” may refer to a subprocess of training, to evaluate the performance of a final AI / ML model using a dataset different from one used for model training and validation. Differently from AI / ML model validation, testing does not assume subsequent tuning of the model.

[0033] As used herein, the term “AI / ML model training” may refer to a process to train an AI / ML Model by learning the input / output relationship in a data driven manner and obtain the trained AI / ML Model for inference.

[0034] As used herein, the term “AI / ML model transfer” may refer to delivery of an AI / ML model over the air interface in a manner that is not transparent to 3GPP signalling, either parameters of a model structure known at the receiving end or a new model with parameters. Delivery may contain a full model or a partial model.

[0035] As used herein, the term “AI / ML model validation” may refer to a subprocess of training, to evaluate the quality of an AI / ML model using a dataset different from one used for model training, that helps selecting model parameters that generalize beyond the dataset used for model training.

[0036] As used herein, the term “data collection” may refer to a process of collecting data by the network nodes, management entity, or UE for the purpose of AI / ML model training, data analytics and inference.

[0037] As used herein, the term “federated learning or federated training” may refer to a machine learning technique that trains an AI / ML model across multiple decentralized edge nodes (e.g., UEs, gNBs) each performing local model training using local data samples. The technique requires multiple interactions of the model, but no exchange of local data samples.

[0038] As used herein, the term “functionality identification” may refer to a process or method of identifying an AI / ML functionality for the common understanding between the NW and the UE. Note: information regarding the AI / ML functionality may be shared during functionality identification. Where AI / ML functionality resides depends on the specific use cases and sub use cases.

[0039] As used herein, the term “model activation” may refer to enabling an AI / ML model for a specific function. As used herein, the term “model deactivation” may refer to disabling an AI / ML model for a specific function.

[0040] As used herein, the term “model download” may refer to model transfer from the network to UE. As used herein, the term “model identification” may refer to a process / method of identifying an AI / ML model for the common understanding between the NW and the UE. Note: the process / method of model identification may or may not be applicable. Note: information regarding the AI / ML modelmay be shared during model identification.

[0041] As used herein, the term “model monitoring” may refer to a procedure that monitors the inference performance of the AI / ML model. As used herein, the term “model parameter update” may refer to process of updating the model parameters of a model.

[0042] As used herein, the term “model selection” may refer to the process of selecting an AI / ML model for activation among multiple models for the same AI / ML enabled feature. Note: model selection may or may not be carried out simultaneously with model activation.

[0043] As used herein, the term “model switching” may refer to deactivating a currently active AI / ML model and activating a different AI / ML model for a specific function. As used herein, the term “model update” may refer to process of updating the model parameters and / or model structure of a model. As used herein, the term “model upload” may refer to model transfer from UE to the network.

[0044] As used herein, the term “network-side (AI / ML) model” may refer to an AI / ML Model whose inference is performed entirely at the network.

[0045] As used herein, the term “offline field data” may refer to the data collected from field and used for offline training of the AI / ML model. As used herein, the term “offline training” may refer to an AI / ML training process where the model is trained based on collected dataset, and where the trained model is later used or delivered for inference. Note: this definition only serves as a guidance. There may be cases that may not exactly conform to this definition but could still be categorized as offline training by commonly accepted conventions. As used herein, the term “online field data” may refer to the data collected from field and used for online training of the AI / ML model.

[0046] As used herein, the term “online training” may refer to an AI / ML training process where the model being used for inference) is (typically continuously) trained in (near) real-time with the arrival of new training samples. Note: the notion of (near) real-time vs. non real-time is context-dependent and is relative to the inference time-scale. Note: this definition only serves as a guidance. There may be cases that may not exactly conform to this definition but could still be categorized as online training by commonly accepted conventions. Note: fine-tuning / re-training may be done via online or offline training. (This note could be removed when we define the term fine-tuning.)

[0047] As used herein, the term “Reinforcement Learning (RL)” may refer to a process of training an AI / ML model from input (a.k.a. state) and a feedback signal (a.k.a. reward) resulting from the model’s output (a.k.a. action) in an environment the model is interacting with.

[0048] As used herein, the term “semi-supervised learning” may refer to a process of training a model with a mix of labelled data and unlabelled data. As used herein, the term “supervised learning” may refer to a process of training a model from input and its corresponding labels. As used herein, the term “unsupervised learning” may refer to a process of training a model without labelled data.

[0049] As used herein, the term “Two-sided (AI / ML) model” may refer to a paired AI / ML Model(s)over which joint inference is performed, where joint inference comprises AI / ML Inference whose inference is performed jointly across the UE and the network, i.e., the first part of inference is firstly performed by UE and then the remaining part is performed by gNB, or vice versa. As used herein, the term “UE-side (AI / ML) model” may refer to an AI / ML Model whose inference is performed entirely at the UE.

[0050] As used herein, the term “proprietary-format models” may refer to ML models of vendor- / device-specific proprietary format, from 3GPP perspective. They are not mutually recognizable across vendors and hide model design information from other vendors when shared. Note: an example is a device-specific binary executable format.

[0051] As used herein, the term “open-format models” may refer to ML models of specified format that are mutually recognizable across vendors and allow interoperability, from 3GPP perspective. They are mutually recognizable between vendors and do not hide model design information from other vendors when shared.

[0052] FIG. 1 illustrates an example communication environment 100 in which example embodiments of the present disclosure can be implemented. In the communication environment 100, a first apparatus 110 and a second apparatus 120 can communicate with each other. In some example embodiments, the first apparatus 110 may comprise a terminal device (for example, a UE), and the second apparatus 120 may comprise a network device (for example, a gNB).

[0053] In the example of FIG. 1 , the first apparatus 110 may be a UE and the second apparatus 120 may be a base station serving the UE. The serving area of the second apparatus 120 may be called a cell 102.

[0054] It is to be understood that the number of first apparatus 110 and second apparatus 120 shown in FIG. 1 is given for the purpose of illustration without suggesting any limitations. The communication environment 100 may include any suitable number of first apparatus 110 and second apparatus 120. Although not shown, it would be appreciated that one or more additional devices may be located in the cell 102, and one or more additional cells may be deployed in the communication environment 100.

[0055] In the following, for the purpose of illustration, some example embodiments are described with the first apparatus 110 operating as a terminal device (such as a UE) and the second apparatus 120 operating as a network device (such as a gNB). However, in some example embodiments, operations described in connection with a terminal device may be implemented at a network device or other device, and operations described in connection with a network device may be implemented at a terminal device or other device.

[0056] In some example embodiments, if the first apparatus 110 is a terminal device or included in a terminal device and the second apparatus 120 is a network device or is included in a network device,a link from the second apparatus 120 to the first apparatus 110 is referred to as a downlink (DL), and a link from the first apparatus 110 to the second apparatus 120 is referred to as an uplink (UL). In DL, the second apparatus 120 is a transmitting (TX) device (or a transmitter) and the first apparatus 110 is a receiving (RX) device (or a receiver). In UL, the first apparatus 110 is a TX device (or a transmitter) and the second apparatus 120 is a RX device (or a receiver). In some example embodiments, if the first apparatus 110 is a first terminal device (for example, a UE), and the second apparatus 120 is a second terminal device (for example, another UE), a link between the first apparatus 110 and the second apparatus 120 is referred to as sidelink (SL).

[0057] Communications in the communication environment 100 may be implemented according to any proper communication protocol(s), comprising, but not limited to, cellular communication protocols of the first generation (1 G), the second generation (2G), the third generation (3G), the fourth generation (4G), the fifth generation (5G), the sixth generation (6G), and the like, wireless local network communication protocols such as Institute for Electrical and Electronics Engineers (IEEE) 802.11 and the like, and / or any other protocols currently known or to be developed in the future. Moreover, the communication may utilize any proper wireless communication technology, comprising but not limited to: Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Frequency Division Duplex (FDD), Time Division Duplex (TDD), Multiple-Input Multiple-Output (MIMO), Orthogonal Frequency Division Multiple (OFDM), Discrete Fourier Transform spread OFDM (DFT-s-OFDM) and / or any other technologies currently known or to be developed in the future.

[0058] In the communication environment 100, the first apparatus 110 may perform candidate beam detection (CBD) for purpose of beam failure recovery. In some example embodiments, the first apparatus 110 may be enabled with beam management based on AI / ML. As such, the first apparatus 110 may perform beam prediction based on a result of beam measurement.

[0059] As briefly mentioned above, Al / ML based beam management (BM) is proposed. The beam management includes spatial domain beam prediction (BM-Case1 ) and time domain beam prediction (BM-Case2). The scope of spatial domain beam prediction is to predict the best Tx / Rx beams in different spatial locations. The time domain beam prediction aims to predict the most likely beam to use for next time instants, e.g., beam prediction in the spatial domain.

[0060] Some objectives related to Al / ML based beam management are as follows.

[0061] Some more objectives related to Al / ML based beam management are listed as follows.0062] Specifically, the current requirements on candidate beam selection (CBS) for beam recovery after the beam failure are defined in technical specification (TS) 38.133, Sections 8.5.5 Requirements for SSB based candidate beam detection and 8.5.6 Requirements for CSI-RS based candidate beam detection.

[0063] As required, the UE is supposed to evaluate during a certain time period that the layer 1 based reference signal received power (L1 -RSRP) measured on the configured channel-state information (CSI) reference signal (CSI-RS) resource in the candidate beam set containing CSI-RS configured for a serving cell. The objective is to verify if the L1 -RSRP measured on the configured CSI-RS resource has not been degraded too much and is still better than a certain threshold used to trigger beam failure recovery. The certain period used to evaluate L1 -RSRP is denoted as TEvaluate_CBD_CSI-RS-

[0064] However, with the addition of AI / ML BM feature, the UE is supposed to predict best beams from the Set A beams, and the UE is configured to measure only a few beams (i.e. Set B). Therefore, the network (NW) will often configure only CSI-RS of the Set B beams, thus the CSI-RS periodicity (denoted as TCSI-RS) of set A beams may be increased. If the NW uses same CSI-RS periodicity also for candidate RS resources, it may lead to a higher value of TCSi_RSused for the calculation of TEvaiuate CBD CSI-RS' A higher value of TEvaiuate CBDCSI-RSmaY cause a delayed beam recovery operation and may cause frequent beam failures. n

[0065] In accordance with some example embodiments of the present disclosure, there is provided a solution for candidate beam detection. An evaluation period for candidate beam detection is determined based on at least one of limitation on period for evaluating a radio link quality for the candidate beam detection or two or more periodicities of reference signal (RS) resources in a candidate beam set. During the determined evaluation period, a reference signal is received from a second apparatus on the RS resources in the candidate beam set, and an evaluation result for the candidate beam set is determined based on the received reference signal.

[0066] By setting the limitation on the period for evaluating the radio link quality for the candidate beam detection and / or redefining the periodicity of the RS resources, the evaluation period can be controlled so as not to be too long. In this way, efficient and timely beam detection and beam failure recovery can be achieved.

[0067] Example embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0068] FIG. 2 illustrates a signalling chart of a proces200 of candidate beam detection according to some example embodiments of the present disclosure. As illustrated in FIG. 2, the process 200 involves a first apparatus 210 and a second apparatus 220. In some example embodiment, the first apparatus 210 may be a terminal device (e.g., the UE), or may be included in the terminal device, and second apparatus 220 may be a base station serving the UE (e.g., a gNB or a network device), or may be included in the network device. In some example embodiments, for example in a testing case, the first apparatus 110 may be or be included in a device under test (DUT) or a UE, and the second apparatus 120 may be or be included in a test equipment (TE) or a system simulator (SS).

[0069] As shown in FIG. 2, the first apparatus 210 determines (202) the evaluation period for candidate beam detection based on one or more parameters. The one or more parameters may include the imitation on the period for evaluating the radio link quality for the candidate beam detection.

[0070] In some example embodiments, the limitation may include an upper limit for the evaluation period. The limitation may be predefined or configured by the second apparatus 220 to the first apparatus 210. The first apparatus 210 may further determine a first periodicity based on a periodicity of the RS resources in the candidate beam set, and determine a smaller one of the first periodicity and the upper limit as the evaluation period.

[0071] For example, if the first periodicity is less than the upper limit, the first periodicity may be determined as the evaluation period. For another example, if the first periodicity is larger than the upper limit, the upper limit may be determined as the evaluation period.

[0072] To better understand the use of the limitation on the evaluation period, an example is now described. In case of non-DRX or when DRX cycle is less than or equal to 320ms, the evaluation period TEvaluate CBD_CSI-RS may be expressed by:TEvaiuate_CBD_csi-RS — Max(25, Ceil(MCBDX P X N X PCBD)XTCSI-RS) (1) where if the CSI-RS resource configured in the set q is transmitted with Density = 3 and over the bandwidth greater than or equal to 24 PRBs, MCBD= 3.

[0073] When candidate beam detection RS is not overlapped with GAP and also not overlapped with synchronization signal block (SSB)-based measurement timing configuration (SMTC) occasion, P = 1.

[0074] For other cases in FR2-1, N=8.

[0075] For each CSI-RS resource in the set q configured for primary cell (PCell) or primary secondary cell (PSCell) in EN-DC (evolved UTRA-NR dual connectivity) or NE-DC or standalone operation mode (SA), or PCell in NR-DC, PCBD= 1.

[0076] Thus, with the above values, TEvaluate CBD_CSI-RS would be:TEvaiuate_CBD_csi-RS=Max(25, 24 X TCS_RS). (2)

[0077] From the above equation, it may be seen that, a higher value of TCSi_RSwill significantly increase the value of TEvaluate CBD_CSI-RS ■ For example, when TCSi_RS= 160 ms , TEvaluate CBD CSI-RS = 3840 ms. In other words, the verification will be done on a duration of almost 4s, which may be too risky and may cause frequent beam failures.

[0078] In some embodiments of the present disclosure, to keep the value of TEvaluate CBD_CSI-RS within the acceptable limit, an additional parameter X (which is an example of the upper limit) is introduced. As such, in some example embodiments of the present disclosure, TEvaluate CBD_CSI-RS may be expressed by:TEvaiuate_CBD_csi-RS=Min (Max(25, Ceil(MCBD x P x N x PCBD)XTCSI-RS)< X) (3) where X is the upper limit allowed for the timer required to verify L1-RSRP values of the configured CSI-RS resources. For example, the value of X may need to be agreed in RAN4. An example of X may be 960ms, which is merely an example without any limitation. In this case, the first apparatus may evaluate whether the L1 -RSRP measured on the configured CSI-RS resource in set qtestimated over TEvaiuate_CBD_csi-RS period becomes better than the threshold Qin LRwithin 960ms even for higher values of TCSI-RS-

[0079] Alternatively, or in addition, in some example embodiments, the one or more parameters may include two or more periodicities of RS resources in a candidate beam set, for example, the set q

[0080] In some example embodiments, based on the two or more periodicities of the RS resources in the candidate beam set q , the first apparatus 210 may determine a second periodicity, and derive the evaluation period based on the second periodicity. As an example, the second periodicity may be determined as an average of the two or more periodicities. As another example, the second periodicity may be the shortest periodicity of the two or more periodicities.

[0081] To better understand the use of the different periodicities of RS resources, an example is now described. The RS resources in set q may follow at least two different periodicities. For example, the set q have RS resources from both Set A and Set B. Since the transmission periodicity of Set A and Set B may be different, it may refer to different values of TCSi_RSfor RS resources in set q .

[0082] In this case, in order to keep the value of TEvaluate CBD_CSI-RS within the acceptable limit,expressed by:TEvaiuate_CBD_csi-RS=Max(25, Ceil(where TCSI-RS qlis the set of TCSi_RSvalues of different CSI-RS resources in the set q .

[0083] In some example embodiments, the limitation on the evaluation period and the different periodicities of RS resources may be used in combination to determine the evaluation period. As an example, the first periodicity as described above may be determined based on the shortest periodicity of the two or more periodicities of the RS resources.

[0084] For example, in order to keep the value of TEvaluate CBD_CSI-RS within the acceptable limit, d by:Cetl(MCBDX P X N X PcBD)xMin(Tcsi-RS,ql))< X) (5) where TCSI-RS qlis the set of TCSi_RSvalues of different CSI-RS resources in the set q .

[0085] Continuing with FIG. 2, during the determined evaluation period, the second apparatus 220 transmits (204) a reference signal to the first apparatus 210 based on the RS resources in the candidate beam set. The first apparatus 210 receives (206) the reference signal from the second apparatus 220. Based on the received reference signal, the first apparatus 210 determines (208) the evaluation result for the candidate beam set.

[0086] In this way, the evaluation for CBD is performed within a period with a reasonable time length. Efficiency of beam failure recovery thus can be ensured.

[0087] In some example embodiments, at least some beams in the candidate beam set may be actually transmitted during the evaluation period. Accordingly, the first apparatus 110 may determine which beams in the candidate beam set is to be transmitted and perform evaluation on RS resources corresponding to the transmitted beams. To this end, in some example embodiments, the first apparatus 210 may select one or more RS resources for evaluation from the RS resources in the candidate beam set, and receive the RS from the second apparatus 220 on the one or more selected RS resources.

[0088] In some example embodiments, the first apparatus 210 may receive information indicating beams in the candidate beam set from the second apparatus 220, and select RS resources corresponding to the indicated beams as the one or more RS resources.

[0089] In an example, in clause 8.5.6. 1 of TS38.331 , it is mandatory the CSI-RS resources configured for candidate beam detection in the set qtare actually transmitted withing UE active DL BWP during the entire evaluation period, i.e. TEvaluate CBD_CSI-RS- Since, in case of AI / ML BM, Set A may have predicted beams which are not necessarily transmitted and some of Set A beams can be part of the set qr. Therefore, the condition of actual transmission should be removed from clause8.5.6.1 of TS38.331 for AI / ML BM use case.

[0090] To better understand the embodiments of the present disclosure, an example is given in the following Table. Requirements for CSI-RS based candidate beam detection are defined in TS. 38.133, Sections 8.5.6, which are as follows.The value of TEvaiuate_cBD_csi-Rs is defined in Table 2 or 3 or 4 for FR2 with scaling factor N, whereN = [2,4,6] for PCell in FR2-1 if the UE supports [capability of fast beam sweeping for layer 1 measurement] according to the conditions in clause 3.6.xN=8 for other cases in FR2-1 , andN=12 for FR2-2.For a UE supporting [support for Case 1 requirements] and when concurrent measurement gap(s) with Pre-MG(s) are configured, or a UE supporting [support for Case 2 requirements] and when concurrent measurement gap(s) with NCSG(s) are configured, or a UE supporting concurrentMeasGap-r17 or [musim-GapPreference-r17] or both concurrentMeasGap-r17 and [musim-GapPreference-r17] and when concurrent gaps or periodic MUSIM gaps or both concurrent GAPs and periodic MUSIM gaps are configured,• an CSI-RS resource occasion for candidate beam detection is not considered to be overlapped by a gap occasion if the gap occasion is dropped according to 9.1.8 and 9.1.10,• P value for a CBD-RS resource to be measured is defined as• " Ntotal / Noutside_MG in FR1• ■ P sharing factor * Ntotal / Noutside_MG in FR2 With Navailable=0• - Ntotai / Navaiiabie in FR2 with Navailable > 0For a window W of duration max(Ti.i, xRP_max), where xRPjnax is the maximum xRP across all configured per-UE measurement gaps or periodic MUSIM gap(s) or NCSGs and per-FR measurement gaps or NCSGs, and, in case of Pre-MG, all activated per-UE measurement gaps and per-FR measurement gaps, within the same FR as serving cell, and starting at the beginning of any CBD-RS resource occasion:• - Ntotai is the total number of CBD-RS resource occasions within the window W, including those overlapped with GAP occasions, MUSIM gap occasions or SMTC occasions within the window W, and• - Noutside.MG is the number of CBD-RS resource occasions that are not overlapped with any non-dropped GAP occasion nor non-dropped MUSIM gap occasion within the window W, and• - Navaiiabie is the number of CBD-RS resource occasions that are not overlapped with anynon-dropped GAP occasion nor non-dropped MUSIM gap occasion nor any SMTC occasion within the window W, and• - an CSI-RS resource occasion for candidate beam detection is considered to be overlapped with the MUSIM gap if it overlaps a MUSIM gap occasion, and- i is periodicity of the target CBD-RS.• - xRP = MGRP when configured GAP is activated Pre-MG or MG, and xRP = VIRP when configured GAP is NCSG.Otherwise, for a UE neither supporting concurrentMeasGap-r17 nor [support for Case 1 requirements] nor [support for Case 2 requirements] nor supporting [musim-GapPreference-r17] or when neither of the above configurations applies, i.e. concurrent measurement gaps, concurrent measurement gap(s) with Pre-MG(s), concurrent measurement gap(s) with NCSG(s), and periodic MUSIM gaps,For FR1 ,P = when in the monitored cell there are GAPs configured for intra-frequency, inter-frequency or inter-RAT measurements, which are overlapping with some but not all occasions of the CSI-RS; andP = 1 when in the monitored cell there are no GAPs overlapping with any occasion of the CSI- RS.For FR2,P = 1 , when candidate beam detection RS is not overlapped with GAP and also not overlapped with SMTC occasion.P = T *. o e when candidate beam detection RS is partially overlapped with GAP and xRP candidate beam detection RS is not overlapped with SMTC occasion (TCSI-RS < xRP)P = - ^ when candidate beam detection RS is not overlapped with GAP andcandidate beam detection RS is partially overlapped with SMTC occasion (TCSI-RS < TsMTCperiod).P =Psharing factor, when candidate beam detection RS is not overlapped with GAP and candidate beam detection RS is fully overlapped with SMTC occasion (TCSI-RS = TsMTCperiod).P when candidate beam detection RS is partially overlapped withGAP and candidate beam detection RS is partially overlapped with SMTC occasion (TCSI-RS < TsMTCperiod) and SMTC occasion is not overlapped with GAP and• - TsMTCperiod XRP Or• - TsMTCperiod = xRP and TCSI-RS < 0.5 x TsMTCperiodP =Psh_a_T^C_fS,1^fa^RSo^r. when candidate beam detection RS is partially overlapped with GAP and xRP candidate beam detection RS is partially overlapped with SMTC occasion (TCSI-RS < TsMTCperiod) and SMTC occasion is not overlapped with GAP and TsMTCperiod = xRP and TCSI-RS = 0.5 x TsMTCperiodP = - when candidate beam detection RS is partially overlapped withGAP and candidate beam detection RS is partially overlapped with SMTC occasion (TCSI-RS < TsMTCperiod) and SMTC occasion is partially or fully overlapped with GAPP = when candidate beam detection RS is partially overlapped with GAP andcandidate beam detection RS is fully overlapped with SMTC occasion (TCSI-RS = TsMTCperiod) and SMTC occasion is partially overlapped with GAP (TsMTCperiod < xRP) where,Psharing factor = 1 , if the CBD-RS resource outside GAP is• - not overlapped with the SSB symbols indicated by SSB-ToMeasure and 1 data symbol before each consecutive SSB symbols indicated by SSB-ToMeasure and 1 data symbol after each consecutive SSB symbols indicated by SSB-ToMeasure, given that SSB-ToMeasure is configured, where the SSB-ToMeasure is the union set of SSB-ToMeasure from all the configured measurement objects merged on the same serving carrier, and,• - not overlapped by the RSSI symbols indicated by ss-RSSI-Measurement and 1 data symbol before each RSSI symbol indicated by ss-RSSI-Measurement and 1 data symbol after each RSSI symbol indicated by ss-RSSI-Measurement, given that ss-RSSI-Measurement is configured.P sharing factor=3, otherwise.If the high layer in TS 38.331 signaling of smtc2 is present, TsMTCperiod follows smtc2 Otherwise TsMTCperiod follows smtcl. TsMTCperiod is the shortest SMTC period among all CCs in the same FR2band, provided the SMTC offset of all CCs in FR2 have the same offset.• - When a GAP is configured only and the GAP is not NCSG,• - a CBD-RS resource or an SMTC occasion is considered to be overlapped with the GAP if it overlaps the GAP occasion, and• - xRP = MGRPOtherwise, when NCSG GAP only is configured,• - a CBD-RS resource or an SMTC occasion is considered to be overlapped with the GAP if it overlaps the VI L1 or VI L2 of NCSG, or it overlaps the ML of NCSG in FR2, and there exists a target carrier to be measured within NCSG that is intra-frequency carrier or inter-frequency carrier in the same band as the serving cell, or interfrequency carrier in different band as the serving cell and UE does not support IBM between the target carrier and the serving cell,• - and- xRP = VIRP• - If the UE is configured with Pre-MG only, an CBD-RS resource or an SMTC occasion is only considered to be overlapped by the Pre-MG if the Pre-MG is activated.When concurrent gaps or concurrent measurement gap(s) with Pre-MG(s) or concurrent measurement gap(s) with NCSG(s) are configured, a CBD-RS resource or an SMTC occasion is not considered to be overlapped by a GAP occasion if the GAP occasion is dropped according to clause 9.1.8, clause 9.1.12, clause 9.1.13, respectively.Note: The overlap between CSI-RS for CBD and SMTC means that CSI-RS for CBD is within the SMTC window duration.Longer evaluation period would be expected if the combination of the CBD-RS resource, SMTC occasion and GAP configurations does not meet previous conditions.Longer evaluation period would be expected if the CSI-RS is on the same OFDM symbols with RLM, BFD, BM-RS, or other CBD-RS, according to the measurement restrictions defined in clause 8.5.6.3.When the configured aperiodic MUSIM gap is overlapping with CSI-RS resource occasion forTable 1 : Evaluation period TEvaiuate_cBD_csi-Rs for FR1Table 2: Evaluation period TEvaiuate_cBD_csi-Rs for FR2Table 3: Evaluation period TEvaiuate_cBD_csi-Rs for FR2Table 4: Evaluation period TEvaiuate_cBD_csi-Rs for FR2

[0091] It is noted that any of Tables 2, 3 and 4 shows example change to Table 8.5.6.2-2 in TS.38.133, Sections 8.5.6. As can be seen, Table 2 shows an example of using the upper limit X todetermine the evaluation period. Table 3 shows an example of using the shortest RS resource periodicity to determine the evaluation period. Table 4 shows an example of using the upper limit X and the shortest RS resource periodicity in combination to determine the evaluation period. It is to be noted that the upper limit X may have any suitable value. The value for the upper limit X shown in the above Tables and also mentioned elsewhere in the present disclosure is merely an example without any limitation.

[0092] FIG. 3 shows a flowchart of an example method 300 implemented at a first apparatus in accordance with some example embodiments of the present disclosure. For the purpose of discussion, the method 300 will be described from the perspective of the first apparatus 110 in FIG. 1.

[0093] At block 310, the first apparatus determines an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set.

[0094] At block 320, the first apparatus receives, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set.

[0095] At block 330, the first apparatus determines an evaluation result for the candidate beam set based on the received reference signal.

[0096] In some example embodiments, the method 300 includes: determining a first periodicity based on a periodicity of the RS resources in the candidate beam set; and determining, as the evaluation period, a smaller one of the first periodicity and the upper limit.

[0097] In some example embodiments, the method 300includes: determining a second periodicity based on the two or more periodicities of the RS resources in the candidate beam set; and deriving the evaluation period based on the second periodicity.

[0098] In some example embodiments, the method 300includes: determining the shortest periodicity of the two or more periodicities as the second periodicity.

[0099] In some example embodiments, the candidate beam set includes a first set of beams for beam prediction and a second set of beams for beam measurement, the beam prediction being performed based on a result of the beam measurement.

[0100] In some example embodiments, the first periodicity is determined based on the shortest periodicity of the two or more periodicities of the RS resources.

[0101] In some example embodiments, the method 300includes: selecting one or more RS resources for evaluation from the RS resources in the candidate beam set; and receiving the RS from the second apparatus on the one or more RS resources.

[0102] In some example embodiments, the method 300includes: receiving, from the second apparatus, information indicating beams in the candidate beam set to transmit to the first apparatus;and selecting, as the one or more RS resources, RS resources corresponding to the indicated beams.

[0103] In some example embodiments, the limitation is predefined or configured by the second apparatus to the first apparatus.

[0104] In some example embodiments, the first apparatus is or is comprised in a terminal device, and the second apparatus is or is comprised in a network device.

[0105] In some example embodiments, a first apparatus capable of performing any of the method 300 may comprise means for performing the respective operations of the method 300. The means may be implemented in any suitable form. For example, the means may be implemented in a circuitry or software module. The first apparatus may be implemented as or included in the first apparatus 110 in FIG. 1.

[0106] In some example embodiments, the first apparatus includes means for determining an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and means for receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and means for determining an evaluation result for the candidate beam set based on the received reference signal.

[0107] In some example embodiments, the first apparatus includes: means for determining a first periodicity based on a periodicity of the RS resources in the candidate beam set; and means for determining, as the evaluation period, a smaller one of the first periodicity and the upper limit.

[0108] In some example embodiments, the first apparatus includes: means for determining a second periodicity based on the two or more periodicities of the RS resources in the candidate beam set; and means for deriving the evaluation period based on the second periodicity.

[0109] In some example embodiments, the first apparatus includes: means for determining the shortest periodicity of the two or more periodicities as the second periodicity.

[0110] In some example embodiments, the candidate beam set includes a first set of beams for beam prediction and a second set of beams for beam measurement, the beam prediction being performed based on a result of the beam measurement.

[0111] In some example embodiments, the first periodicity is determined based on the shortest periodicity of the two or more periodicities of the RS resources.

[0112] In some example embodiments, the first apparatus includes: means for selecting one or more RS resources for evaluation from the RS resources in the candidate beam set; and means for receiving the RS from the second apparatus on the one or more RS resources.

[0113] In some example embodiments, the first apparatus includes: means for receiving, from the second apparatus, information indicating beams in the candidate beam set to transmit to the firstapparatus; and means for selecting, as the one or more RS resources, RS resources corresponding to the indicated beams.

[0114] In some example embodiments, the limitation is predefined or configured by the second apparatus to the first apparatus.

[0115] In some example embodiments, the first apparatus is or is comprised in a terminal device, and the second apparatus is or is comprised in a network device.

[0116] FIG. 4 is a simplified block diagram of a device 400 that is suitable for implementing example embodiments of the present disclosure. The device 400 may be provided to implement a communication device, for example, the terminal device 110 or the network device 120 as shown in FIG. 1. As shown, the device 400 includes one or more processors 410, one or more memories 420 coupled to the processor 410, and one or more communication modules 440 coupled to the processor 410.

[0117] The communication module 440 is for bidirectional communications. The communication module 440 has one or more communication interfaces to facilitate communication with one or more other modules or devices. The communication interfaces may represent any interface that is necessary for communication with other network elements. In some example embodiments, the communication module 440 may include at least one antenna.

[0118] The processor 410 may be of any type suitable to the local technical network and may include one or more of the following: general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples. The device 400 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.

[0119] The memory 420 may include one or more non-volatile memories and one or more volatile memories. Examples of the non-volatile memories include, but are not limited to, a Read Only Memory (ROM) 424, an electrically programmable read only memory (EPROM), a flash memory, a hard disk, a compact disc (CD), a digital video disk (DVD), an optical disk, a laser disk, and other magnetic storage and / or optical storage. Examples of the volatile memories include, but are not limited to, a random-access memory (RAM) 422 and other volatile memories that will not last in the power-down duration.

[0120] A computer program 430 includes computer executable instructions that are executed by the associated processor 410. The instructions of the program 430 may include instructions for performing operations / acts of some example embodiments of the present disclosure. The program 430 may be stored in the memory, e.g., the ROM 424. The processor 410 may perform any suitable actions and processing by loading the program 430 into the RAM 422.

[0121] The example embodiments of the present disclosure may be implemented by means of the program 430 so that the device 400 may perform any process of the disclosure as discussed with reference to FIG. 2 to FIG. 3. The example embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.

[0122] In some example embodiments, the program 430 may be tangibly contained in a computer readable medium which may be included in the device 400 (such as in the memory 420) or other storage devices that are accessible by the device 400. The device 400 may load the program 430 from the computer readable medium to the RAM 422 for execution. In some example embodiments, the computer readable medium may include any types of non-transitory storage medium, such as ROM, EPROM, a flash memory, a hard disk, CD, DVD, and the like. The term “non-transitory,” as used herein, is a limitation of the medium itself (i.e. , tangible, not a signal) as opposed to a limitation on data storage persistency (e.g., RAM vs. ROM).

[0123] FIG. 5 shows an example of the computer readable medium 500 which may be in form of CD, DVD or other optical storage disk. The computer readable medium 500 has the program 430 stored thereon.

[0124] Generally, various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, and other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. Although various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representations, it is to be understood that the block, apparatus, system, technique or method described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

[0125] Some example embodiments of the present disclosure also provide at least one computer program product tangibly stored on a computer readable medium, such as a non-transitory computer readable medium. The computer program product includes computer-executable instructions, such as those included in program modules, being executed in a device on a target physical or virtual processor, to carry out any of the methods as described above. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or split between program modules as desired in various embodiments. Machineexecutable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.

[0126] Program code for carrying out methods of the present disclosure may be written in anycombination of one or more programming languages. The program code may be provided to a processor or controller of a general-purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0127] In the context of the present disclosure, the computer program code or related data may be carried by any suitable carrier to enable the device, apparatus or processor to perform various processes and operations as described above. Examples of the carrier include a signal, computer readable medium, and the like.

[0128] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0129] Further, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, although several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Unless explicitly stated, certain features that are described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, unless explicitly stated, various features that are described in the context of a single embodiment may also be implemented in a plurality of embodiments separately or in any suitable subcombination.

[0130] Although the present disclosure has been described specific to structural features and / or methodological acts, it is to be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

WHAT IS CLAIMED IS:1 . A first apparatus comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus at least to: determine an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and receive, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and determine an evaluation result for the candidate beam set based on the received reference signal.

2. The first apparatus of claim 1 , wherein the limitation comprises an upper limit for the evaluation period, and the first apparatus is caused to: determine a first periodicity based on a periodicity of the RS resources in the candidate beam set; and determine, as the evaluation period, a smaller one of the first periodicity and the upper limit.

3. The first apparatus of claim 1 , wherein the first apparatus is caused to: determine a second periodicity based on the two or more periodicities of the RS resources in the candidate beam set; and derive the evaluation period based on the second periodicity.

4. The first apparatus of claim 3, wherein the first apparatus is caused to: determine the shortest periodicity of the two or more periodicities as the second periodicity.

5. The first apparatus of claim 3, wherein the candidate beam set comprises a first set of beams for beam prediction and a second set of beams for beam measurement, the beam prediction being performed based on a result of the beam measurement.

6. The first apparatus of claim 2, wherein the first periodicity is determined based on the shortestperiodicity of the two or more periodicities of the RS resources.

7. The first apparatus of claim 1 , wherein the first apparatus is caused to: select one or more RS resources for evaluation from the RS resources in the candidate beam set; and receive the RS from the second apparatus on the one or more RS resources.

8. The first apparatus of claim 7, wherein the first apparatus is caused to: receive, from the second apparatus, information indicating beams in the candidate beam set to transmit to the first apparatus; and select, as the one or more RS resources, RS resources corresponding to the indicated beams.

9. The first apparatus of claim 1 , wherein the limitation is predefined or configured by the second apparatus to the first apparatus.

10. The first apparatus of claim 1 , wherein the first apparatus is or is comprised in a terminal device, and the second apparatus is or is comprised in a network device.

11. A method comprising: determining, at a first apparatus, an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; determining an evaluation result for the candidate beam set based on the received reference signal.

12. A first apparatus comprising: means for determining an evaluation period for candidate beam detection based on at least one of: limitation on a period for evaluating a radio link quality for the candidate beam detection, or two or more periodicities of reference signal, RS, resources in a candidate beam set; and means for receiving, during the determined evaluation period, a reference signal from a second apparatus based on the RS resources in the candidate beam set; and means for determining an evaluation result for the candidate beam set based on the receivedreference signal.

13. A computer readable medium comprising instructions stored thereon for causing an apparatus at least to perform the method of claim 11 .

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