Method for guaranteeing communication quality of existing user terminal when applying artificial intelligence / machine learning-based beam prediction

Abstract

Disclosed is a technology which relates to a method for guaranteeing communication quality of an existing UE when applying AI / ML-based beam prediction. An operation method of a user equipment in a wireless communication system comprises the steps of: receiving information for configuring cell parameters; and on the basis of the information for configuring the cell parameters, acquiring at least one beam set associated with an AI / ML model. The information for configuring the cell parameters comprises bitmap information and transmission interval information for the at least one beam set. According to the present invention, even if overhead of an SSB for beam sweeping is reduced by applying an AI / ML-based beam prediction technology, performance degradation of an existing UE may be minimized.

Description

Method to guarantee communication quality of existing user terminals when applying AI / machine learning-based beam prediction

[0001] The present invention relates to a method for guaranteeing the communication quality of an existing UE when applying AI / ML-based beam prediction, and discloses a method for minimizing performance degradation of an existing UE even when reducing the overhead of the SSB for beam sweeping by applying AI / ML-based beam prediction technology.

[0002] 3GPP is discussing the application of Beam Management (BM) technology using AI / ML (Artificial Intelligence / Machine Learning) to NR (New Radio) Air Interfaces.

[0003] Figure 1 is a conceptual diagram illustrating a beam management method using AI / ML according to the prior art.

[0004] Among beam management technologies, BM-Case 1 and BM-Case 2 are being discussed. BM-Case 1 is a beam prediction technology that takes place in space, and BM-Case 2 is a beam prediction technology that takes place in time.

[0005] The primary objective of beam prediction technology, which is currently being discussed in standards, is to reduce the overhead of Synchronization Signal Blocks (SSBs) for beam sweeping. To achieve this, the main goal is to reduce the number of SSBs through spatial beam prediction and decrease the number of SSB burst transmissions through temporal beam prediction within SSB bursts where SSBs are transmitted continuously.

[0006] Figure 2 is a conceptual diagram illustrating the configuration of a beam set according to the prior art.

[0007] Figure 2(a) shows an example of the configuration of Set A and Set B of BM-Case 1, Figure 2(b) shows an example of Case A of BM-Case 2, and Figure 2(c) shows an example of Case B of BM-Case 2.

[0008] Both BM-Case 1 and BM-Case 2 define Set A and Set B for beam prediction. Set B is the set of beams that enter as input to the AI / ML model, and Set A is the set of beams that exit as output to the AI / ML model. Set A is a set of beams that includes all actual beams transmitted by the base station (gNB) in the SSB Burst for beam scanning in existing systems where AI / ML is not used, and Set B is a set of beams defined to reduce the number of beams used during beam scanning in systems where AI / ML is used. Therefore, the number of beams M in Set B is generally less than or equal to the number of beams N in Set A, but Set B is not necessarily a subset of Set A.

[0009] In BM-Case 1, the base station (gNB) can reduce the length of the SSB burst by NM compared to the existing one by sending M SSB blocks within the SSB burst. Upon receiving this, the user terminal (User Equipment, UE) executes an AI / ML model to select the top-K beams with the strongest received signal (RSRP) among the N beams of Set A. Therefore, in BM-Case 1, the number of beams in Set B must be smaller than the number of beams in Set A to reduce SSB overhead.

[0010] BM-Case 2 can be divided into a method of increasing the SSB transmission period (Case B) and a method of stopping SSB transmission for a certain period of time (Case A). In Case A, the base station transmits SSB bursts at a period of Tper during time T1 and then does not transmit SSB bursts during time T2. The User Terminal (UE) or the base station performs Pt beam predictions at a period of Tper during time T2. The beams used in the SSB bursts transmitted during time T1 are Set B, and during time T2, the UE or the base station selects the Top-K beams from Set A using an AI / ML model. In Case A, the number of beams in Set B (M) may be equal to or less than the number of beams in Set A (N).

[0011] In Case B, when the AI / ML model is not applied, the period during which the base station transmits SSBs is X ms, and when the AI / ML model is applied, the period during which the base station transmits SSBs is Y ms. Additionally, when the AI / ML model is applied, the number of SSBs included in the SSB burst by the base station is M, and the number of beams M in Set B can be less than or equal to the number of beams N in Set A.

[0012] Current beam prediction technology aims to reduce resources for beam sweeping, which inevitably leads to performance degradation. According to TR38.843, a signal strength reduction of at least 1 to 2 dB occurs in L1-RSRP, and in many cases, a reduction of 6 dB in L1-RSRP may occur.

[0013] In railways, rolling stock, and smart factories, there are mobile UEs that require highly reliable communication for safety purposes; therefore, it is necessary to determine whether to apply beam prediction based on the location of the UE and whether safety-related traffic occurs. Additionally, since performance degradation is expected to be more severe for existing UEs, techniques to minimize performance degradation of existing UEs are required.

[0014] Published Patent No. 10-2024-0058790, disclosed on May 3, 2024, relates to “a method and apparatus for model management in beam management using artificial intelligence and machine learning.” It discloses a method for measuring a new beam set more quickly and efficiently by pre-setting a reference signal resource mapped to relevant beam information in AI / ML model management and dynamically transmitting and receiving an appropriate reference signal resource according to a transition of a model / state / scenario, etc. The method discloses a method comprising the steps of: receiving configuration information for one or more reference signal (RS) resource sets configured to correspond to one or more AI / ML models or functionalities used for a predetermined purpose; receiving instruction information for one reference signal resource set selected from one or more reference signal resource sets; and measuring the signal strength or signal quality of the reference signal based on one reference signal resource set.

[0015] (Prior Art 1) Korean Patent Publication No. 10-2024-0058790 “Method and apparatus for model management in beam management using artificial intelligence and machine learning” (Published May 3, 2024)

[0016] AI / ML-based beam prediction technology is being developed in 5G-Advanced, and the purpose of this technology is to reduce the overhead of the Synchronization Signal Block (SSB) for beam sweeping. To achieve this, the goal is to widen the transmission interval of the SSB Burst or reduce the number of beams within the SSB Burst, which is expected to lead to performance degradation of existing User Equipment (UE).

[0017] In the case of railways or rolling stock, since the replacement cycle of UEs is long and they handle safety-related information, it is necessary to minimize the performance degradation of existing UEs. Therefore, the objective of the present invention is to provide a method that minimizes the performance degradation of existing UEs even while reducing the overhead of the SSB for beam sweeping.

[0018] The problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by a person skilled in the art from the description below.

[0019] According to one aspect of the proposed invention, a method of operation of a terminal in a wireless communication system comprises the steps of receiving information for setting cell parameters and acquiring at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model based on the information for setting cell parameters. In this case, the information for setting cell parameters includes bitmap information and transmission interval information for the at least one beam set.

[0020] According to an additional aspect, the at least one beam set comprises at least one first beam set associated with the input of the AI / ML model and at least one second beam set associated with the output of the AI / ML model.

[0021] According to an additional aspect, the bitmap information is set for beams corresponding to at least one of the at least one first beam set and the at least one second beam set, and the transmission interval information represents at least one of i) the transmission interval of the at least one first beam set, ii) the transmission interval of the second beam set, and iii) the transmission interval between the at least one first beam set.

[0022] According to an additional aspect, the at least one first beam set comprises a plurality of first beam sets, and the union of the plurality of first beam sets is included in or equal to the second beam set.

[0023] According to an additional aspect, the information for setting the cell parameters includes information indicating the application of overhead reduction using the AI / ML model.

[0024] According to an additional aspect, the at least one beam set includes a plurality of first beam sets associated with the input of the AI / ML model, and the information for setting the cell parameters includes information indicating the number of the plurality of first beam sets.

[0025] According to an additional aspect, the at least one beam set includes at least one first beam set associated with the input of the AI / ML model, and the information for setting the cell parameters includes information indicating the number of beams of each of the at least one first beam set.

[0026] According to an additional aspect, information for setting the cell parameters includes System Frame Number (SFN) information indicating the start of non-transmission of at least one beam set and SFN information indicating the end of non-transmission.

[0027] According to an additional aspect, a beam report is performed based on at least one beam among the beams of the second beam set having the greatest strength of the received signal.

[0028] According to another aspect of the proposed invention, a method of operating a base station in a wireless communication system comprises the steps of: transmitting information for setting cell parameters; and transmitting at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model based on the information for setting cell parameters. The information for setting cell parameters includes bitmap information and transmission interval information for the at least one beam set.

[0029] According to an additional aspect, the at least one beam set includes at least one first beam set associated with the input of the AI / ML model and at least one second beam set associated with the output of the AI / ML model.

[0030] According to an additional aspect, the bitmap information is set for beams corresponding to at least one of the at least one first beam set and the at least one second beam set, and the transmission interval information represents at least one of i) the transmission interval of the at least one first beam set, ii) the transmission interval of the second beam set, and iii) the transmission interval between the at least one first beam set.

[0031] According to an additional aspect, the at least one first beam set comprises a plurality of first beam sets, and the union of the plurality of first beam sets is included in or equal to the second beam set.

[0032] According to an additional aspect, the information for setting the cell parameters includes information indicating the application of overhead reduction using the AI / ML model.

[0033] According to an additional aspect, the at least one beam set includes a plurality of first beam sets associated with the input of the AI / ML model, and the information for setting the cell parameters includes information indicating the number of the plurality of first beam sets.

[0034] According to an additional aspect, the at least one beam set includes at least one first beam set associated with the input of the AI / ML model, and the information for setting the cell parameters includes information indicating the number of beams of each of the at least one first beam set.

[0035] According to an additional aspect, information for setting the cell parameters includes System Frame Number (SFN) information indicating the start of non-transmission of at least one beam set and SFN information indicating the end of non-transmission.

[0036] According to an additional aspect, a beam report is received based on at least one beam among the beams of the second beam set having the greatest strength of the received signal.

[0037] According to another aspect of the proposed invention, a terminal in a wireless communication system comprises a transceiver for transmitting and receiving wireless signals, a memory for storing instructions, and a processor operatively connected to the transceiver and the memory. An operation performed based on the execution of the instructions by the processor comprises: receiving information for setting cell parameters, and acquiring at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model based on the information for setting the cell parameters. The information for setting the cell parameters includes bitmap information and transmission interval information for the at least one beam set.

[0038] According to another aspect of the proposed invention, a base station in a wireless communication system comprises a transceiver for transmitting and receiving wireless signals, a memory for storing instructions, and a processor operatively connected to the transceiver and the memory. An operation performed based on the execution of the instructions by the processor comprises: a step of transmitting information for setting cell parameters, and a step of transmitting at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model based on the information for setting the cell parameters. The information for setting the cell parameters includes bitmap information and transmission interval information for the at least one beam set.

[0039] According to another aspect of the proposed invention, a method of operation of a terminal in a wireless communication system comprises the steps of receiving system information and receiving at least one beam set based on the received system information. If the at least one beam set is received during a first time interval and is not received during a second time interval after the first time interval, at least one of i) setting information in which a timer associated with a wireless link failure is longer than the second time interval and ii) setting information indicating the start time and end time of the second time interval is obtained.

[0040] According to an additional aspect, setting information indicating the start and end times of the second time interval is obtained through the received system information using the System Frame Number (SFN).

[0041] According to the present invention, by applying AI / ML-based beam prediction technology, the performance degradation of the existing User Equipment (UE) can be minimized even when reducing the overhead of the Synchronization Signal Block (SSB) for beam sweeping.

[0042] In particular, since the replacement cycle of UEs is long and they handle safety-related information, the degradation of existing UE performance must be minimized, so the present invention is an essential technology for this purpose.

[0043] Figure 1 is a conceptual diagram illustrating a beam management method using AI / ML according to the prior art.

[0044] Figure 2 is a conceptual diagram illustrating the configuration of a beam set according to the prior art.

[0045] FIG. 3 is a flowchart schematically illustrating a method for ensuring communication quality of an existing UE when applying AI / ML-based beam prediction according to one embodiment.

[0046] FIG. 4 is a conceptual diagram illustrating the beam set transmission method of BM-Case 1 in the existing UE communication quality assurance method when applying AI / ML-based beam prediction according to one embodiment.

[0047] FIG. 5 is a conceptual diagram illustrating the beam set transmission method of BM Case 2-Case A in the existing UE communication quality assurance method when applying AI / ML-based beam prediction according to one embodiment.

[0048] The foregoing and additional aspects are embodied through embodiments described with reference to the attached drawings. It is understood that the components of each embodiment may be combined in various ways within the embodiment or with components of other embodiments, unless otherwise stated or contradicted. Based on the principle that the inventor can appropriately define the concepts of terms to best describe his invention, the terms used in this specification and claims shall be interpreted in a meaning and concept consistent with the description or proposed technical idea.

[0049] In this specification, a module or part may be composed of a processor and memory and a set of program instructions stored in memory so as to be executed on the processor. Additionally, a module or part may be composed using a set of electronic components or circuits, such as an ASIC or FPGA, designed to execute these instructions. Furthermore, the operation of each module or part may be performed by one or more processors or devices.

[0050] Components marked with identical or similar symbols perform identical or similar functions, so their descriptions may be omitted. For components with omitted drawing symbols, reference may be made to the descriptions provided for components with identical or similar symbols.

[0051] Preferred embodiments of the present invention will be described in detail below with reference to the attached drawings.

[0052] FIG. 3 is a flowchart schematically illustrating a method for ensuring communication quality of an existing UE when applying AI / ML-based beam prediction according to one embodiment.

[0053] According to one embodiment, a base station (170) of a wireless communication system transmits information for setting cell parameters to a terminal (130) (S130). The terminal (130) receives the information for setting cell parameters transmitted from the base station. The information for setting cell parameters includes bitmap information for at least one beam set and transmission interval information.

[0054] The base station (170) transmits at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model based on information for setting cell parameters to the terminal (S150). The terminal (130) obtains at least one beam set associated with the AI / ML model transmitted by the base station based on information for setting cell parameters. The beam set may include a first beam set associated with an input and a second beam set associated with an output.

[0055] The terminal (130) performs a beam report to the base station (S170). The base station (170) receives the beam report from the terminal. The beam reception report can be performed based on the beam with the highest signal strength among the beams of the second beam set associated with the output.

[0056] A more detailed configuration of the embodiment is described below.

[0057] In the present invention, beam prediction-related information transmitted by a base station via RRC (Radio Resource Control) and the operation of the UE are initiated to maintain the performance of the existing user terminal (UE).

[0058] SIB 1 (SystemInformationBlockType1) of NR (New Radio), which transmits information updated at a 160ms interval, includes ServingCellConfigCommonSIB as an option, and ServingCellConfigCommonSIB includes ssb-PositionsInBurst and ssb-PeriodicityServingCell. ssb-PositionsInBurst is a variable used to represent the types of beams transmitted in an SSB burst as a bitmap, and consists of 8 bits for FR1 (below 6GHz) and 8 bits for additional use in FR2 (above 6GHz). ssb-PeriodicityServingCell is a variable representing the transmission period of the SSB, and is currently selectable from {ms5, ms10, ms20, ms40, ms80, ms160}.

[0059] When an AI / ML model is applied, the base station periodically transmits an SSB configured with Set B. Additionally, the base station needs to transmit an SSB configured with Set A for the model training and monitoring of AI / ML-supported UEs, as well as for existing UEs. In this invention, an SSB burst configured with Set A is referred to as SSBs_A, and an SSB burst configured with Set B is referred to as SSBs_B.

[0060] Three types of UEs can exist simultaneously in a network: existing UEs that do not support AI / ML, new UEs that do not support AI / ML, and UEs that do support AI / ML. When UEs that do not support AI / ML are present, it is necessary to minimize the performance degradation of these UEs caused by the application of AI / ML. In particular, if the UE that does not support AI / ML is a safe UE, it is desirable that there be no performance degradation for that UE; however, even if there is performance degradation, it must be possible to provide the 5QI (5G QoS Indicator) required by the safe UE.

[0061] Table 1 is a table classifying UEs based on whether they support AI / ML.

[0062] Category | Provided Features UE_a | AI / ML Support | New | Supports UEServingCellConfigCommonSIB, supports new RRC signals related to AI / ML-based beam prediction UE_b | AI / ML Non-support | New | Supports UEServingCellConfigCommonSIB, supports new RRC signals related to AI / ML-based beam prediction UE_c | ServingCellConfigCommonSIB Non-support, supports new RRC signals related to AI / ML-based beam prediction UE_d | Existing | Supports UEServingCellConfigCommonSIB UE_e | ServingCellConfigCommonSIB Non-support

[0063] 1. Terminal Operation and Related Signaling in BM-Case 1

[0064] In the case where BM-Case 1 applies, non-AI / ML-supported UEs can be further divided into UE_b / UE_d, which support the ServingCellConfigCommonSIB option, and UE_c / UE_e, which do not.

[0065] Since UE_c and UE_e cannot read ServingCellConfigCommonSIB information, they proceed with beam selection using all SSBs transmitted by the base station. If the corresponding UE_c / UE_e is connected, the base station can instruct the UE to select the best beam through beam scanning at the time the base station transmits an SSB using Set A. To do this, it is necessary for the base station to periodically transmit SSBs_A.

[0066] However, when a UE performs beam scanning in an idle state, there is a high probability that the UE will select a beam from Set B. This increases the likelihood of performance degradation caused by the UE selecting an inappropriate beam, and in severe cases, the UE may not be able to attempt connection establishment until the base station transmits an SSB configured with Set A. Therefore, to reduce the time required for UE_c / UE_e to select an appropriate beam during the beam scanning process, a method can be applied in which multiple Set Bs are created and the union of the Set Bs includes Set A. For example, this is a method in which the base station alternately transmits Set B1 and Set B2, such that Set B1 ∪ Set B2 ⊇ Set A. Although the present invention focuses on the case where Set B1 and Set B2 exist, this method can be easily extended to cases where Set B1, Set B2, ..., Set Bn exist.

[0067] Based on the above method, the method by which a base station transmits Set A and Set B can be divided into the following three cases.

[0068] (Case 1) The base station alternately transmits SSB_B1, which consists of Set B1, and SSB_B2, which consists of Set B2. The SSB Burst transmission cycle of Case 1 is illustrated in FIG. 4 (a).

[0069] (Case 2) The base station transmits Set A at long intervals while transmitting Set B. When the transmission times of Set B and Set A overlap, Set A is transmitted. The transmission method of Set A and Set B in Case 2 is illustrated in FIG. 4 (b).

[0070] (Case 3) The base station transmits Set A at long intervals while alternately transmitting Set B1 and Set B2. If the transmission times of Set B1 / B2 and Set A overlap, Set A is transmitted. If the transmission time of Set B2 overlaps with the transmission time of Set A, then Set B2 is transmitted instead of Set B1 during the next Set B transmission turn. The transmission method of Set A, Set B1, and Set B2 in Case 3 is illustrated in FIG. 4 (c).

[0071] FIG. 4 is a conceptual diagram illustrating the beam set transmission method of BM-Case 1 in the existing UE communication quality assurance method when applying AI / ML-based beam prediction according to one embodiment.

[0072] Figure 4(a) shows the SSB Burst transmission period of Case 1, Figure 4(b) shows the transmission method of Set A and Set B of Case 2, and Figure 4(c) shows the transmission method of Set A, Set B1, and Set B2 of Case 3.

[0073] When Case 1 is applied, the existing UE can receive both the beams of Set B1 and Set B2 and then select the optimal beam, so the strength of the received signal (e.g., RSRP) becomes greater than that of the existing technology that transmits only Set B.

[0074] When Case 2 is applied, the existing UE scans the beam using Set A, which is included in the entire beam, so it can find the optimal beam at the same level as the existing one. However, it has the disadvantage that more RB (Resource Block) is allocated to beam scanning than in Case 1.

[0075] Case 3 is a technique that maintains the beam optimization performance of the existing UE while using an RB that is intermediate between Case 1 and Case 2.

[0076] 1.1. BA Case 1 - Terminal Operation and Related Signaling in Case 1

[0077] In Case 1, the operation of UE_a to UE_e is as follows. UE_c and UE_e perform beam scanning whenever an SSB is transmitted, as before. This is because, since both Set B1 and Set B2 are transmitted, the optimal beam among all beams can be found over time.

[0078] UE_d can identify some information about Set B1 and Set B2 using ssb-PositionsInBurst and ssb-PeriodicityServingCell of the ServingCellConfigCommonSIB transmitted by the base station, and then act accordingly. To do this, the base station must set ssb-PositionsInBurst and ssb-PeriodicityServingCell to appropriate values. For example, existing variables can be defined as shown in Table 2 below.

[0079] (1) ssb-PeriodicityServingCell: Transmission interval between SSBs_B1 (Set B1) and SSBs_B2 (Set B2) (2) ssb-PositionsInBurst: Displays the beam between Set B1 and Set B2

[0080] If Set B1 ∪ Set B2 = Set A, then ssb-PositionsInBurst represents the beam of Set A, and if Set B1 ∪ Set B2 ⊂ Set A, then it represents a beam smaller than Set A. However, in the case where Set B1 ∪ Set B2 ⊂ Set A, the base station does not transmit an SSB burst composed of an actual Set A, so UE_d does not need to know Set A.

[0081] UE_d, having received the above information, can determine that not all beams of ssb-PositionsInBurst have been transmitted if only the beam of SSBs_B1 has been received. Based on this, it can receive additional beam scanning in the next cycle and then transmit PRACH or report measurement results to the base station.

[0082] UE_a and UE_b can identify the existence and transmission period of Set B1 and Set B2 through the newly defined RRC signal. For example, new variables can be defined in the RRC signaling as shown in Table 3 below.

[0083] (1) ssb-BeamReduction: Indicates whether AI / ML-based beam prediction is applied (2) ssb-ReducedBeamSet: Indicates the number of beams in Set B (3) ssb-PositionInBurstA: Indicates the beams in Set A

[0084] Utilizing the above information, UE_a can derive Set A by combining the measurement results of Set B1 and Set B2, and use it for training and monitoring AI / ML-based beam prediction. UE_b can wait until all beams from Set B1 and Set B2 are received, and then report the measured results to the base station or utilize them in a random access procedure.

[0085] The information on RRC signals and UE operations defined for UE_a and UE_b can be configured as described in item “3. BA Case 1 - Terminal Operation and Related Signaling of Case 1” of the embodiments to be described later, taking into account the preceding ssb-PositionsInBurst and ssb-PeriodicityServingCell.

[0086] 1.2. Terminal Operation and Related Signaling in BA Case 1-Case 2

[0087] In Case 2, the operation of UE_a to UE_e is as follows. UE_c and UE_e perform beam scanning whenever an SSB is transmitted. Accordingly, they cannot scan for the optimal beam when Set B is transmitted, but they can find the optimal beam among all beams when Set A is transmitted. If UE_c and UE_e terminals are newly connected to any gNB, the gNB may instruct the terminals to perform beam scanning at the time of sending Set A.

[0088] UE_d can identify some information about Set B and Set A using ssb-PositionsInBurst and ssb-PeriodicityServingCell of the ServingCellConfigCommonSIB transmitted by the base station, and then act accordingly. To do this, RRC signals can be defined as shown in Table 4 below.

[0089] (1) ssb-PeriodicityServingCell: Transmission interval of SSBs_B (2) ssb-PositionsInBurst: Mark the beams of Set A in bitmap format

[0090] When RRC signaling is configured as described above, UE_d can use the information in ssb-PositionsInBurst to determine that not all beams in ssb-PositionsInBurst have been transmitted if only the beam of set B has been received. Therefore, the UE can perform additional beam scanning until Set A is detected, and then transmit PRACH to the gNB or report the measurement results. This is because the base station transmits Set A when the transmission cycle of Set B and the transmission cycle of Set A overlap, so the UE can perform beam scanning when SSBs_A is transmitted while performing beam scanning with the cycle of SSBs_B.

[0091] UE_a and UE_b can determine the transmission period of Set A and the beam configuration of Set B through the newly defined RRC signal. For example, new variables can be defined as shown in Table 5 below.

[0092] (1) ssb-BeamReduction: Indicates whether AI / ML-based beam prediction is applied (2) ssb-PositionInBurstB: Represents the beam of Set B (3) ssb-PeriodicityServingCellA: Indicates the transmission period of SSBs_A (Set A)

[0093] UE_a and UE_b can identify information of Set A and Set B by combining the new RRC signal and the existing RRC signal. The newly defined RRC signal and terminal operation can be configured as described in item “4. Terminal operation and related signaling of BA Case 1-Case 2” of the embodiment to be described later.

[0094] 1.3. Terminal Operation and Related Signaling in BA Case 1-Case 3

[0095] In Case 3, the operation of UE_a ~ UE_e is as follows. UE_c and UE_e perform beam scanning whenever an SSB is transmitted. Since both Set B1 and Set B2 are transmitted, the optimal beam among all beams is found over time, or the optimal beam can be found with a single beam scan when Set A is transmitted.

[0096] UE_d can identify some information about Set B1, Set B2, and Set A using ssb-PositionsInBurst and ssb-PeriodicityServingCell of the ServingCellConfigCommonSIB transmitted by the base station, and then act accordingly. To do this, the base station can configure the method of setting ssb-PositionsInBurst and ssb-PeriodicityServingCell as shown in Table 6 below.

[0097] (1) ssb-PeriodicityServingCell: between transmissions between SSBs_B1 and SSBs_B2 (2) ssb-PositionsInBurst: represents Set B1 ∪ Set B2 ∪ Set A

[0098] If Set B1 ∪ Set B2 ⊆ Set A, then ssb-PositionsInBurst will display the beam of Set A, and if Set B1 ∪ Set B2 ⊃ Set A, then ssb-PositionsInBurst will display the beam of Set B1 ∪ Set B2.

[0099] UE_d, having received the above information, can determine that not all beams of ssb-PositionsInBurst have been transmitted if only the beam of Set_B1 has been received. Based on this, it can receive additional beam scanning in the next cycle and then transmit PRACH to gNB or report measurement results.

[0100] UE_a and UE_b can identify the existence and transmission cycles of Set B1 and Set B2 through newly defined RRC signals. Based on this, UE_a can derive Set A by combining the measurement results of Set B1 and Set B2, which can then be used for training and monitoring AI / ML-based beam prediction. UE_b can wait until all beams from Set B1 and Set B2 are received, and then report the measured results to the base station or utilize them in a random access procedure.

[0101] The information on RRC signals defined for UE_a and UE_b and the UE operation can be configured as described in the “5 BA Case 1-Case 3 Terminal Operation and Related Signaling” item of the embodiment to be described later, taking into account the preceding ssb-PositionsInBurst and ssb-PeriodicityServingCell.

[0102] 2. Terminal Operation and Related Signaling in BM Case 2

[0103] When BM-Case 2 is applied, the non-AI / ML-supported UEs can be further divided into UE_b / UE_d, which support the ServingCellConfigCommonSIB option, and UE_c / UE_e, which do not. Therefore, it is possible to apply Cases 1 / 2 / 3 of BM-Case 1 to BM Case 2. However, since BM Case 2 includes a T2 period where the SSB is not transmitted and a period where the transmission cycle increases to Y ms, additional signals and terminal operations are configured for this.

[0104] 2.1. Terminal Operation and Signaling in BM Case 2-Case A

[0105] In Case A, since the base station does not transmit SSB during the T2 interval, BM-Case1-Case1~3 can be applied as follows.

[0106] (Case 1) The base station alternately transmits SSB_B1, which consists of Set B1, and SSB_B2, which consists of Set B2. Afterwards, the base station does not transmit SSB for time T2. The SSB Burst transmission cycle of Case 1 is illustrated in FIG. 5 (a).

[0107] (Case 2) The base station transmits Set A at long intervals while transmitting Set B. When the transmission times of Set B and Set A overlap, Set A is transmitted. Afterwards, the base station does not transmit SSB for T2 hours. The transmission method of Set A and Set B in Case 2 is illustrated in FIG. 5(b).

[0108] (Case 3) The base station transmits Set A at long intervals while alternately transmitting Set B1 and Set B2. If the transmission times of Set B1 / Set B2 and Set A overlap, Set A is transmitted. If the transmission time of Set B2 overlaps with the transmission time of Set A, Set B2 is transmitted instead of Set B1 during the next Set B transmission turn. Afterwards, the base station does not transmit SSB for T2 hours. The transmission method of Set A, Set B1, and Set B2 in Case 3 is illustrated in FIG. 5(c).

[0109] FIG. 5 is a conceptual diagram illustrating the beam set transmission method of BM Case 2-Case A in the existing UE communication quality assurance method when applying AI / ML-based beam prediction according to one embodiment.

[0110] Figure 5(a) shows the SSB Burst transmission period of Case 1, Figure 5(b) shows the transmission method of Set A and Set B of Case 2, and Figure 5(c) shows the transmission method of Set A, Set B1, and Set B2 of Case 3.

[0111] Since UE_c / UE_e cannot read ServingCellConfigCommonSIB information, if the base station (gNB) does not transmit an SSB during T2, it may recognize that there are no gNBs nearby. To prevent Radio Link Failure (RLF) caused by this, one or both of the following two methods may be applied.

[0112] (Method 1) Set the timer associated with the RLF judgment longer than T2.

[0113] (Method 2) The SIB uses the SFN (System Frame Number) to indicate the start and end times of T2.

[0114] As an example of Method 1, the T310 timer, which operates when the terminal is out of sync, is set to be longer than T2. ​​For example, if T2 is 80ms, T310 can be set to a value of 100ms or more, or if T2 is 160ms, T310 can be set to a value of 200ms or more.

[0115] If Method 1 is not applied, the terminal may declare a Radio Link Failure (RLF) while the base station is not transmitting an SSB. In this case, the terminal cannot perform communication during that time and has the disadvantage of consuming more transmission power because it retryes the connection with the base station. By using the method of one embodiment, communication can be prevented by preventing the terminal from declaring an RLF. However, if T2 is long, the RLF timer may be set excessively long, which may result in a disadvantage where recovery is delayed in the event of an actual communication failure.

[0116] As an example of Method 2, the base station may provide the System Frame Number (SFN) at which T2 starts in SIB1 and the System Frame Number (SFN) at which T2 ends.

[0117] Table 7 shows an example of the RRC signaling configuration for BM Case 2-Case A.

[0118] ServingCellConfigCommonSIB::= SEQUENCE {...ssb-VoidStartBit STRING ( SIZE(10) ) / SFN where T2 starts ssb-VoidEndBit STRING ( SIZE(10) ) / SFN where T2 ends and the SSB is transmitted...}

[0119] Method 2, like Method 1, can prevent the terminal from declaring unnecessary RLF. However, the change cycle of SFN information is very long. Accordingly, the cycle for the base station to change T2 must also be extended.

[0120] 2.2. Terminal Operation and Signaling in BM Case 2-Case B

[0121] In Case B, when the AI / ML model is not applied, the period during which the base station transmits the SSB is X ms, and when the AI / ML model is applied, the period during which the base station transmits the SSB is Y ms. By substituting Y into the minimum SSB transmission interval of BM Case 1, the contents of Cases 1 through 3 of BM Case 1 can be applied as is. For example, in BM Case 1-Case 1 through Case 3, ssb-PeriodicityServingCell corresponds to Y.

[0122] Embodiments of the present invention will be described in more detail below.

[0123] 3. BA Case 1 - Terminal Operation and Related Signaling in Case 1

[0124] Three embodiments of BA Case 1-Case 1 are presented. Each embodiment is BA Case 1-Case 1-1, BA Case 1-Case 1-2, and BA Case 1-Case 1-3.

[0125] 3.1. Case 1-1

[0126] ssb-PeriodicityServingCell transmitted by the base station indicates the transmission interval between SSBs_B1 and SSBs_B2, ssb-PositionsInBurst indicates Set B1 ∪ Set B2, ssb-PositionsInBurstB1 indicates Set B1 as a bitmap, and ssb-PositionsInBurstB1 indicates Set B2 as a bitmap.

[0127] In the example below, ssb-PositionsInBurstB is transmitted in ServingCellConfigCommonSIB, but it can also be transmitted in other RRC signaling. Additionally, the example below is a standalone (SA) scenario, but it is applicable to non-standalone (NSA) scenarios as well.

[0128] Table 8 shows an example of RRC signaling in Case 1-1 composed of Sets B1 and B2.

[0129] ServingCellConfigCommonSIB::= SEQUENCE {...ssb-PositionsInBurst / Represent the beam of Set B1 ∪ Set B2 as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCell, / Transmission interval between SSBs_B1 and SSBs_B2 ssb-BeamReductionTrue or False, / Indicate whether overhead reduction using AI / ML is applied ssb-ReducedBeamSet{n2,n3}, / (Option0) Indicate the number of Set B ssb-PositionsInBurstA / (Option1) Represent the beam of Set A as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},ssb-PositionsInBurstB1 / Represent the beam of Set B1 as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},ssb-PositionsInBurstB2 / (Option2) Represent the beam of Set B2 as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},}

[0130] If the standard limits the number of Set B to a maximum of 2, the variable ssb-ReducedBeamSet of Option 0 may not be used.

[0131] If Set B1 ∪ Set B2 = Set A, the base station does not need to send separate Set A information, so the variable ssb-PositionsInBurstA of Option 1 may not be used.

[0132] If there are no overlapping beams between Set B1 and Set B2, Option 2 may be omitted. In this case, the UE identifies the beam of Set B2 by subtracting ssb-PositionsInBurstB from ssb-PositionsInBurst. If the set consists of Set B1, B2, and B3, ssb-PositionsInBurstB1 and ssb-PositionsInBurstB2 represent the beams of Set B1 and Set B2, and the UE identifies the beam of Set B3 by subtracting ssb-PositionsInBurstB1 and ssb-PositionsInBurstB2 from ssb-PositionsInBurst.

[0133] 3.2. Case 1-2

[0134] ssb-PeriodicityServingCell indicates the transmission interval between SSBs_B1 and SSBs_B2, ssb-PositionsInBurst indicates Set B1 ∪ Set B2, and ssb-ReducedBeamSet indicates the number of beams in Set B1, B2, ..., Bx.

[0135] In the example below, ssb-PositionsInBurstB is transmitted in ServingCellConfigCommonSIB, but it can also be transmitted in other RRC signaling. Additionally, while the example below is an SA scenario, it is applicable to NSA scenarios as well.

[0136] Table 9 shows an example of the RRC signaling configuration for Case 1-2, composed of Sets B1 and B2.

[0137] ServingCellConfigCommonSIB::= SEQUENCE {...ssb-PositionsInBurst / Represent the beams of Set B1 ∪ Set B2 as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCell, / Transmission interval between SSBs_B1 and SSBs_B2 ssb-BeamReductionTrue or False, / Indicate whether overhead reduction using AI / ML is applied ssb-ReducedBeamSet{nB1,nB2,...,nBx}, / Indicate the number of beams for Set B1, B2, ..., Bx ssb-PositionsInBurstA / (Option1) Represent the beams of Set A as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},}

[0138] In Case 1-2, if Set B1 ∪ Set B2 = Set A, there is no need to send separate Set A information, so the variable ssb-PositionsInBurstA in Option 1 may not be used.

[0139] A UE that receives ssb-ReducedBeamSet can identify the beams of Set B1 and Set B2 through the following operations.

[0140] UE considers the first nB1 indices of ssb-PositionsInBurst as Set B1, and the last nB2 indices as Set B2. If nB1+nB2 is greater than M = n ( Set B1 ∪ Set B2 ), then M_share = nB1 + nB2 - M beams are the number of beams shared between Set B1 and Set B2.

[0141] When there are three or more Sets B, the operation for the UE to distinguish the beams of each set is as follows. For example, if nB1 = nB2 = nB3 = nB4 = nB and 4nB is greater than M = n ( Set B1 ∪ Set B2 ∪ Set B3 ∪ Set B4 ), then M_share = ( 4nB - M ) / 4 becomes the number of beams shared by a single Set with its adjacent Sets. More specifically, M_share becomes the number of beams shared by Set B1 with Set B2, the number of beams shared by Set B2 with Set B3, the number of beams shared by Set B3 with Set B4, and the number of beams shared by Set B4 with Set B1. In this case, the index of each beam is as follows.

[0142] - Set B1 = { 1, 2, ... , nB}

[0143] - Set B2 = { nB - M_share + 1, ... , 2nB - M_share}

[0144] - Set B3 = { 2 (nB - M_share) + 1, ... , 3nB - 2M_share}

[0145] - Set B4 = { mod( 3 (nB - M_share) + 1, M), ... , mod( 4nB - 3M_share, M )}

[0146] If M = 16 and nB = 8, M_share = 2, and the beam indices of each Set are as follows.

[0147] - Set B1 = { 1, 2, 3, 4, 5, 6}

[0148] - Set B2 = { 5, 6, 7, 8, 9, 10}

[0149] - Set B3 = { 9, 10, 11, 12, 13, 14}

[0150] - Set B4 = { 13, 14, 15, 16, 1, 2}

[0151] If inOneGroup = 1111 1111 and groupPresence = 1100 0000, beam indices 1 to 8 correspond to groupPresence 1000 0000, and beam indices 9 to 16 correspond to groupPresence 0100 0000.

[0152] 4. Terminal Operation and Related Signaling in BA Case 1-Case 2

[0153] In the example below, ssb-PositionsInBurstB transmitted by the base station is sent in ServingCellConfigCommonSIB, but it can also be sent in other RRC signaling. Additionally, the example below is an SA scenario, but it is applicable to NSA scenarios as well.

[0154] Table 10 shows an example of the RRC signaling configuration for Case 2.

[0155] ServingCellConfigCommonSIB::= SEQUENCE {...ssb-PositionsInBurst / Represent Set A's beam as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCell, / Transmission interval of Set B ssb-BeamReductionTrue or False, / Indicate whether overhead reduction using AI / ML is applied ssb-PositionsInBurstB / Represent Set B's beam as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCellA / Transmission interval of Set A}

[0156] In Case 2, if the transmission times of ssb-PeriodicityServingCell and ssb-PeriodicityServingCell_A overlap, UE_a and UE_b determine that the beam of Set A has been transmitted and perform beam measurement and prediction operations. For example, if ssb-PeriodicityServingCell is 20 ms and ssb-PeriodicityServingCell_A is 80 ms, the 4th transmission period of the Set B beam matches the transmission period of the Set A beam. In this case, the terminal considers that the base station has transmitted an SSB burst configured with Set A.

[0157] 5 BA Terminal Operation and Related Signaling in Case 1-Case 3

[0158] Two implementation examples, BA Case 1-Case 3-1 and BA Case 1-Case 3-2, are explained.

[0159] 5.1. Case 3-1

[0160] ssb-PeriodicityServingCell transmitted by the base station indicates the transmission interval between SSBs_B1 and SSBs_B2, ssb-PositionsInBurst indicates Set B1 ∪ Set B2 ∪ Set A, ssb-PositionsInBurstB1 indicates Set B1 as a bitmap, and ssb-PositionsInBurstB2 indicates Set B2 as a bitmap.

[0161] In the example below, ssb-PositionsInBurstB is transmitted in ServingCellConfigCommonSIB, but it can also be transmitted in other RRC signaling. Additionally, the example below is applicable to SA scenarios, but it is also applicable to NSA scenarios.

[0162] Table 11 shows an example of the RRC signaling configuration for Case 3-1.

[0163] / ssb-PeriodicityServingCell : Transmission interval between SSBs_B1 and SSBs_B2 / ssb-PositionsInBurst: Represent Set A's beam as a bitmap / ssb-PositionsInBurst_B: Represent Set B1's beam as a bitmap ServingCellConfigCommonS IB::= SEQUENCE {...ssb-PositionsInBurst / Represent Set B1 ∪ Set B2 ∪ Set A's beam as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCell, / Transmission interval between Set B1 and Set B2 ssb-BeamReductionTrue or False, / Whether to apply overhead reduction using AI / ML Display ssb-ReducedBeamSet{n2,n3}, / (Option0) Display the number of Set B ssb-PositionsInBurstA / (Option1) Represent the beams of Set A as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},ssb-PositionsInBurstB1 / Represent the beams of Set B1 as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),groupPresence BIT STRING (SIZE (8))},ssb-PositionsInBurstB2 / (Option2) Represent the beams of Set B2 as a bitmap SEQUENCE {inOneGroup BIT STRING (SIZE (8)),},}

[0164] If the standard limits the number of Set B to a maximum of 2, the variable ssb-ReducedBeamSet of Option 0 may not be used.

[0165] If Set B1 ∪ Set B2 = Set A, there is no need to send separate Set A information, so the variable ssb-PositionsInBurstA of Option 1 may not be used.

[0166] If there are no overlapping beams between Set B1 and Set B2 and Set B1 ∪ Set B2 = Set A, then Option 2 can be omitted. In this case, the UE identifies the beam of Set B2 by subtracting ssb-PositionsInBurstB from ssb-PositionsInBurst. If the set consists of Set B1, B2, and B3, then ssb-PositionsInBurstB1 and ssb-PositionsInBurstB2 represent the beams of Set B1 and Set B2, and the UE identifies the beam of Set B3 by subtracting ssb-PositionsInBurstB1 and ssb-PositionsInBurstB2 from ssb-PositionsInBurst.

[0167] 5.2. Case 3-2

[0168] It can be used when Set B1 ∪ Set B2 = Set A. The ssb-PeriodicityServingCell transmitted by the base station indicates the transmission interval between SSBs_B1 and SSBs_B2, ssb-PositionsInBurst indicates set A, and ssb-ReducedBeamSet indicates the number of Set B1, B2, ... Bx.

[0169] Table 12 shows an example of the RRC signaling configuration for Case 3-2.

[0170] ServingCellConfigCommonSIB::= SEQUENCE {...ssb-PositionsInBurst / Represent the beam of Set A as a bitmap SEQUENCE {inOneGroupBIT STRING (SIZE (8)),groupPresenceBIT STRING (SIZE (8))},ssb-PeriodicityServingCell, / Transmission interval between Set_B1 and Set_B2 ssb-BeamReductionTrue or False, / Indicate whether overhead reduction using AI / ML is applied ssb-ReducedBeamSet{nB1,nB2,...,nBx}, / Indicate the number of Sets B1, B2, ..., Bx}

[0171] A UE that receives ssb-ReducedBeamSet can identify the beams of Set B1 and Set B2 through the following operations.

[0172] The UE considers the first nB1 indices of ssb-PositionsInBurst as Set B1, and the last nB2 indices as Set B2. If nB1 + nB2 is greater than M = n ( Set B1 ∪ Set B2 ), then M_share = nB1 + nB2 - M beams represent the number of beams shared between Set B1 and Set B2. If the number of Set B is greater than 2, the UE operates identically to Case 1-2.

[0173] Although the present invention has been described above with reference to embodiments with reference to the accompanying drawings, it is not limited thereto and should be interpreted to encompass various variations that can be obviously derived from them by those skilled in the art. The claims are intended to encompass such variations.

[0174] The form for carrying out the invention is substantially the same as the best form for carrying out the invention mentioned above.

[0175] The present invention has industrial applicability as it can be utilized in a technology that guarantees the communication quality of a user terminal when applying AI / machine learning-based beam prediction.

Claims

1. In a method of operation of a terminal in a wireless communication system, A step of receiving information for setting cell parameters; and Based on information for setting the above cell parameters, the method includes the step of acquiring at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model, and Information for setting the above cell parameters includes bitmap information and transmission interval information for the at least one beam set, a method.

2. In Paragraph 1, A method wherein the at least one beam set comprises at least one first beam set associated with the input of the AI / ML model and at least one second beam set associated with the output of the AI / ML model.

3. In Paragraph 2, The bitmap information is set for beams corresponding to at least one of the at least one first beam set and the at least one second beam set, and A method in which the transmission interval information indicates at least one of i) the transmission interval of at least one first beam set, ii) the transmission interval of the second beam set, and iii) the transmission interval between the at least one first beam set.

4. In Paragraph 2, The above method, wherein at least one first beam set comprises a plurality of first beam sets, and the union of the plurality of first beam sets is included in or is the same as the second beam set.

5. In Paragraph 1, A method comprising information for setting the above cell parameters, including information indicating the application of overhead reduction using the above AI / ML model.

6. In Paragraph 1, The above at least one beam set includes a plurality of first beam sets associated with the input of the AI / ML model, and A method for setting the cell parameters, wherein the information for setting the cell parameters includes information indicating the number of the plurality of first beam sets.

7. In Paragraph 1, The above at least one beam set includes at least one first beam set associated with the input of the AI / ML model, and A method for setting the cell parameters, wherein the information for setting the cell parameters includes information indicating the number of beams of each of the at least one first beam set.

8. In Paragraph 1, Information for setting the cell parameters includes System Frame Number (SFN) information indicating the start of non-transmission of at least one beam set and SFN information indicating the end of non-transmission.

9. In Paragraph 2, A method in which a beam report is performed based on at least one beam with the greatest strength of the received signal among the beams of the second beam set.

10. In a method of operation of a base station in a wireless communication system, A step of transmitting information for setting cell parameters; and Based on information for setting the above cell parameters, the method includes the step of transmitting at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model, and Information for setting the above cell parameters includes bitmap information and transmission interval information for the at least one beam set, a method.

11. In Paragraph 10, A method wherein the at least one beam set comprises at least one first beam set associated with the input of the AI / ML model and at least one second beam set associated with the output of the AI / ML model.

12. In Paragraph 11, The bitmap information is set for beams corresponding to at least one of the at least one first beam set and the at least one second beam set, and A method in which the transmission interval information indicates at least one of i) the transmission interval of at least one first beam set, ii) the transmission interval of the second beam set, and iii) the transmission interval between the at least one first beam set.

13. In Paragraph 11, The above method, wherein at least one first beam set comprises a plurality of first beam sets, and the union of the plurality of first beam sets is included in or is the same as the second beam set.

14. In Paragraph 10, A method comprising information for setting the above cell parameters, including information indicating the application of overhead reduction using the above AI / ML model.

15. In Paragraph 10, The above at least one beam set includes a plurality of first beam sets associated with the input of the AI / ML model, and A method for setting the cell parameters, wherein the information for setting the cell parameters includes information indicating the number of the plurality of first beam sets.

16. In Paragraph 10, The above at least one beam set includes at least one first beam set associated with the input of the AI / ML model, and A method for setting the cell parameters, wherein the information for setting the cell parameters includes information indicating the number of beams of each of the at least one first beam set.

17. In Paragraph 10, Information for setting the cell parameters includes System Frame Number (SFN) information indicating the start of non-transmission of at least one beam set and SFN information indicating the end of non-transmission.

18. In Paragraph 11, A method for receiving a beam report based on at least one beam having the greatest received signal strength among the beams of the second beam set.

19. As a terminal in a wireless communication system, Transmitter and receiver for transmitting and receiving wireless signals; Memory for storing instructions; and The operation performed based on the instruction being executed by the processor, comprising the above-mentioned transceiver and the above-mentioned memory operatively connected, is: A step of receiving information for setting cell parameters, and Based on information for setting the above cell parameters, the method includes the step of acquiring at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model, and Information for setting the above cell parameters includes bitmap information and transmission interval information for the at least one beam set, in a terminal.

20. As a base station in a wireless communication system, Transmitter and receiver for transmitting and receiving wireless signals; Memory for storing instructions; and The operation performed based on the instruction being executed by the processor, comprising the above-mentioned transceiver and the above-mentioned memory operatively connected, is: A step of transmitting information for setting cell parameters, and Based on information for setting the above cell parameters, the method includes the step of transmitting at least one beam set associated with an AI / ML (artificial intelligence / machine learning) model, and Information for setting the above cell parameters includes bitmap information for at least one beam set and transmission interval information, for a base station.

21. In a method of operation of a terminal in a wireless communication system, Step of receiving system information; and Based on the above-mentioned received system information, the method includes the step of receiving at least one beam set, and A method in which, if at least one beam set is received during a first time interval and is not received during a second time interval after the first time interval, at least one of i) setting information in which a timer associated with a wireless link failure is longer than the second time interval and ii) setting information in which the start time and end time of the second time interval are obtained.

22. In Paragraph 21, A method in which setting information indicating the start and end times of the second time interval is obtained through the received system information using the System Frame Number (SFN).

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