Wireless signal transmission and reception method and apparatus in a wireless communication system

Abstract

A method and apparatus for transmitting and receiving a radio signal in a wireless communication system are disclosed. The method according to an embodiment of the present disclosure may include receiving configuration information for a plurality of TCI states from a base station, receiving control information from the base station, the control information including one or more TCI states to be applied to one or more UEs among the plurality of TCI states and individual time offsets for each of the one or more TCI states, and transmitting an uplink transmission or receiving a downlink transmission based on the one or more TCI states from a time according to the time offsets.

Description

Technical Field

[0001] The present disclosure relates to a wireless communication system, and more particularly, to a method and apparatus for transmitting and receiving uplink transmission or downlink transmission in a wireless communication system.

Background Art

[0002] Mobile communication systems were developed to provide voice services while ensuring user mobility. However, mobile communication systems have expanded their scope to include data services as well as voice, and currently, due to the explosive increase in traffic, there is a shortage of resources, and users are also demanding faster services. Therefore, a more advanced mobile communication system is desired.

[0003] The requirements for next-generation mobile communication systems are, broadly speaking, the acceptance of explosive data traffic, a revolutionary increase in the transmission rate per user, the acceptance of a significantly increased number of connected devices, a very low end-to-end latency, and support for high energy efficiency. For this purpose, various technologies such as dual connectivity, massive multiple input multiple output (Massive MIMO), in-band full duplex, non-orthogonal multiple access (NOMA), super wideband support, and device networking are being studied.

Summary of the Invention

Problems to be Solved by the Invention

[0004] The technical problem addressed by this disclosure is to provide a method and apparatus for transmitting and receiving uplink transmissions (e.g., PUSCH (physical uplink shared channel), PUCCH (physical uplink control channel), etc.) or downlink transmissions (e.g., PDSCH (physical downlink shred channel), PDCCH (physical downlink control channel)).

[0005] Furthermore, a further technical challenge of this disclosure is to provide a method and apparatus for configuring uplink / downlink transmission beams (or transmission configuration indication (TCI) states) for one or more user equipment (UEs).

[0006] The technical challenges addressed in this disclosure are not limited to those mentioned above, and other technical challenges not mentioned will be clearly understood by those with ordinary skill in the art to which this disclosure pertains from the following description. [Means for solving the problem]

[0007] A method performed by user equipment in a wireless communication system according to one aspect of the present disclosure may include: receiving setting information for a plurality of transmission configuration indication (TCI) states from a base station; receiving control information from the base station, wherein the control information includes one or more TCI states from the plurality of TCI states that are applied to one or more UEs, and a separate time offset for each of the one or more TCI states; and transmitting an uplink transmission or receiving a downlink transmission based on the one or more TCI states from the time of the time offset.

[0008] A method performed by a base station in a wireless communication system according to a further aspect of the present disclosure may include: transmitting configuration information for a plurality of transmission configuration indication (TCI) states to user equipment (UE); transmitting control information from the base station to the UE, wherein the control information includes one or more TCI states from the plurality of TCI states that are applied to one or more UEs, and a separate time offset for each of the one or more TCI states; and receiving an uplink transmission or transmitting a downlink transmission based on the one or more TCI states from the time of the time offset. [Effects of the Invention]

[0009] According to embodiments of this disclosure, signaling overhead can be reduced by directing one or more beams (or TCI states) to one or more UEs with a single signaling.

[0010] Furthermore, according to the embodiments of this disclosure, by predicting and indicating a future point in time when one or more beams (or TCI states) will be applied, it is possible to respond more quickly to rapidly changing channel conditions.

[0011] Furthermore, according to the embodiments of this disclosure, more suitable link adaptation can be achieved by acquiring / reporting optimal channel state information for single and / or multiple TRP transmissions, thereby improving the performance of the wireless communication system. [Brief explanation of the drawing]

[0012] The accompanying drawings, included as part of the detailed description to aid in understanding this disclosure, provide examples relating to this disclosure and illustrate the technical features of this disclosure together with the detailed description.

[0013] [Figure 1]This disclosure provides an example of the structure of a wireless communication system to which it applies.

[0014] [Figure 2] This disclosure illustrates a frame structure in a wireless communication system to which it applies.

[0015] [Figure 3] This disclosure provides an example of a resource grid in a wireless communication system to which it applies.

[0016] [Figure 4] Examples of physical resource blocks in wireless communication systems to which this disclosure applies are given.

[0017] [Figure 5] This disclosure illustrates a slot structure in a wireless communication system to which it may apply.

[0018] [Figure 6] This disclosure provides examples of physical channels used in wireless communication systems to which this disclosure applies, and general signal transmission and reception methods using them.

[0019] [Figure 7] This provides an example of how artificial intelligence can be classified.

[0020] [Figure 8] Let's take a feed-forward neural network as an example.

[0021] [Figure 9] The recurrent neural network is an example.

[0022] [Figure 10] A convolutional neural network is given as an example.

[0023] [Figure 11] An autoencoder is given as an example.

[0024] [Figure 12] This provides an example of a functional framework for AI operation.

[0025] [Figure 13] This illustrates segmented AI inference.

[0026] [Figure 14] This example illustrates the application of a functional framework in wireless communication systems.

[0027] [Figure 15] This example illustrates the application of a functional framework in wireless communication systems.

[0028] [Figure 16] This example illustrates the application of a functional framework in wireless communication systems.

[0029] [Figure 17] This diagram illustrates a high-speed train scenario.

[0030] [Figure 18] This figure illustrates a beam instruction according to one embodiment of the present disclosure.

[0031] [Figure 19] This figure illustrates a beam instruction according to one embodiment of the present disclosure.

[0032] [Figure 20] This figure illustrates a beam instruction according to one embodiment of the present disclosure.

[0033] [Figure 21] An example of a signaling procedure between a network and a UE for a wireless signal transmission and reception method according to one embodiment of this disclosure is provided.

[0034] [Figure 22] This figure illustrates the operation of a UE (User Interface) for a wireless signal transmission and reception method according to one embodiment of the present disclosure.

[0035] [Figure 23] This figure illustrates the operation of a base station for a wireless signal transmission and reception method according to one embodiment of the present disclosure.

[0036] [Figure 24] This is a block diagram illustrating an example of a wireless communication device according to one embodiment of the present disclosure. [Modes for carrying out the invention]

[0037] Preferred embodiments relating to this disclosure will be described in detail below with reference to the accompanying drawings. The detailed description disclosed below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of this disclosure and is not intended to represent the only possible embodiments of this disclosure. The detailed description below includes specific details to provide a complete understanding of this disclosure. However, those skilled in the art will understand that this disclosure is implementable without such specific details.

[0038] In some cases, to avoid ambiguity of the concepts in this disclosure, known structures and devices may be omitted, or they may be shown in the form of block diagrams focusing on the core function of each structure and device.

[0039] In this disclosure, when one component is “connected,” “joined,” or “linked” to another component, this can include not only a direct connection but also an indirect connection in which other components exist between them. Furthermore, in this disclosure, the terms “includes” or “have” identify the presence of the referred features, stages, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, stages, operations, elements, components and / or groups thereof.

[0040] In this disclosure, terms such as “first,” “second,” etc., are used solely to distinguish one component from another, and are not used to limit the components, nor do they limit the order or importance of the components unless otherwise specified. Therefore, within the scope of this disclosure, a first component in one embodiment may be referred to as a second component in another embodiment, and similarly, a second component in one embodiment may be referred to as a first component in another embodiment.

[0041] The terms used in this disclosure are for illustrative purposes relating to specific embodiments and are not intended to limit the scope of the claims. As used in the description of the embodiments and in the attached claims, singular forms are intended to include plural forms unless otherwise specified in the context. The terms “and / or” used in this disclosure may refer to one of the related enumerated items, or to any and all possible combinations of two or more of them. In this disclosure, “ / ” between words has the same meaning as “and / or” unless otherwise specified.

[0042] This disclosure describes a wireless communication network or wireless communication system, where operations performed in the wireless communication network may occur in the process of a device (e.g., a base station) controlling the network and transmitting or receiving signals, or in the process of a terminal connected to the wireless network transmitting or receiving signals to or from the network.

[0043] In this disclosure, transmitting or receiving a channel includes transmitting or receiving information or signals on that channel. For example, transmitting a control channel means transmitting control information or signals on the control channel. Similarly, transmitting a data channel means transmitting data information or signals on the data channel.

[0044] In the following, downlink (DL) refers to communication from the base station to the terminal, and uplink (UL) refers to communication from the terminal to the base station. In the downlink, the transmitter may be part of the base station, and the receiver may be part of the terminal. In the uplink, the transmitter may be part of the terminal, and the receiver may be part of the base station. The base station may be referred to as the first communication device, and the terminal as the second communication device. The term Base Station (BS) may be replaced with terms such as fixed station, Node B, eNB (evolved-Node B), gNB (Next Generation Node B), BTS (base transceiver system), Access Point (AP), network (5G network), AI (Artificial Intelligence) system / module, RSU (roadside unit), robot, drone (UAV: Unmanned Aerial Vehicle), AR (Augmented Reality) device, VR (Virtual Reality) device, etc. Furthermore, the term "Terminal" may be fixed or mobile, and may be replaced by terms such as UE (User Equipment), MS (Mobile Station), UT (user terminal), MSS (Mobile Subscriber Station), SS (Subscriber Station), AMS (Advanced Mobile Station), WT (Wireless terminal), MTC (Machine-Type Communication) device, M2M (Machine-to-Machine) device, D2D (Device-to-Device) device, vehicle, RSU (roadside unit), robot, AI (Artificial Intelligence) module, drone (UAV: Unmanned Aerial Vehicle), AR (Augmented Reality) device, and VR (Virtual Reality) device.

[0045] The following technologies may be used in various wireless connectivity systems such as CDMA, FDMA, TDMA, OFDMA, and SC-FDMA. CDMA may be implemented by wireless technologies such as UTRA (Universal Terrestrial Radio Access) and CDMA2000. TDMA may be implemented by wireless technologies such as GSM (Global System for Mobile communications) / GPRS (General Packet Radio Service) / EDGE (Enhanced Data Rates for GSM Evolution). OFDMA may be implemented by wireless technologies such as IEEE 802.11 (Wi-Fi®), IEEE 802.16 (WiMAX®), IEEE 802-20, and E-UTRA (Evolved UTRA). UTRA is part of UMTS (Universal Mobile Telecommunications System). 3GPP® (3rd Generation Partnership Project) LTE (Long Term Evolution) is part of E-UMTS (Evolved UMTS) which uses E-UTRA, and LTE-A (Advanced) / LTE-A pro are advanced versions of 3GPP LTE. 3GPP NR (New Radio or New Radio Access Technology) is an advanced version of 3GPP LTE / LTE-A / LTE-A pro.

[0046] For clarity, the explanation will be based on 3GPP communication systems (e.g., LTE-A, NR), but the technical concepts of this disclosure are not limited thereto. LTE refers to 3GPP TS (Technical Specification) 36.xxx Release 8 and later technologies. More specifically, LTE technologies from 3GPP TS 36.xxx Release 10 onwards are called LTE-A, and LTE technologies from 3GPP TS 36.xxx Release 13 onwards are called LTE-A pro. 3GPP NR refers to TS 38.xxx Release 15 and later technologies. LTE / NR may be referred to as a 3GPP system. "xxx" means the standard document detail number. LTE / NR may be referred to as a 3GPP system. For background information, terminology, abbreviations, etc., used in this disclosure, refer to the standard documents published prior to this disclosure. For example, refer to the following documents.

[0047] For 3GPP LTE, you can refer to TS 36.211 (Physical Channels and Modulation), TS 36.212 (Multiplexing and Channel Coding), TS 36.213 (Physical Layer Procedures), TS 36.300 (General Description), and TS 36.331 (Radio Resource Control).

[0048] For 3GPP NR, you can refer to TS 38.211 (Physical Channels and Modulation), TS 38.212 (Multiplexing and Channel Coding), TS 38.213 (Physical Layer Procedures for Control), TS 38.214 (Physical Layer Procedures for Data), TS 38.300 (General Description of NR and NG-RAN (New Generation-Radio Access Network)), and TS 38.331 (Radio Resource Control Protocol Standard).

[0049] Abbreviations of terms used in this disclosure are defined as follows:

[0050] - BM: Beam Management

[0051] - CQI: Channel Quality Indicator

[0052] - CRI: Channel State Information - Reference Signal Resource Indicator

[0053] - CSI: Channel State Information

[0054] - CSI-IM: Channel State Information - Interference Measurement

[0055] - CSI-RS: Channel State Information - Reference Signal

[0056] - DMRS: Demodulation reference signal

[0057] - FDM: Frequency Division Multiplexing

[0058] - FFT: Fast Fourier Transform

[0059] - IFDMA: Interleaved frequency division multiple access

[0060] - IFFT: Inverse Fast Fourier Transform

[0061] - L1-RSRP: Layer 1 reference signal received power

[0062] - L1-RSRQ: Layer 1 reference signal received quality

[0063] - MAC: Medium Access Control

[0064] - NZP: Non-Zero Power

[0065] - OFDM: Orthogonal frequency division multiplexing

[0066] - PDCCH: Physical Downlink Control Channel

[0067] - PDSCH: Physical Downlink Shared Channel

[0068] - PMI: Precoding matrix indicator

[0069] - RE: Resource element

[0070] - RI: Rank indicator

[0071] - RRC: Radio Resource Control

[0072] - RSSI: received signal strength indicator

[0073] - Rx: Reception

[0074] - QCL: quasi co-location

[0075] - SINR: Signal-to-interference and noise ratio

[0076] - SSB (or SS / PBCH block): Synchronization signal block (including primary synchronization signal (PSS), secondary synchronization signal (SSS), and physical broadcast channel (PBCH))

[0077] - TDM: time division multiplexing

[0078] - TRP: Transmission and Reception Point

[0079] - TRS: Tracking Reference Signal

[0080] - Tx: transmission

[0081] - UE: User equipment

[0082] - ZP: Zero Power

[0083] General System

[0084] As more communication devices demand greater communication capacity, the need for improved mobile broadband communication compared to existing radio access technology (RAT) is emerging. Massive Machine Type Communications (MTC), which connects numerous devices and things to provide various services anytime, anywhere, is also a major consideration in next-generation communications. In addition, communication system design that takes into account reliability and latency-sensitive services / terminals is being discussed. Thus, the introduction of next-generation RATs that consider eMBB (enhanced mobile broadband communication), Mmtc (massive MTC), URLLC (Ultra-Reliable and Low Latency Communication), etc., is being discussed, and for convenience in this disclosure, this technology will be referred to as NR. NR is an expression representing an example of 5G RAT.

[0085] The new RAT system, including NR, uses an OFDM transmission scheme or a similar scheme. The new RAT system may follow OFDM parameters different from those of LTE. Alternatively, the new RAT system may follow the existing LTE / LTE-A numerology but support a larger system bandwidth (e.g., 100 MHz). Alternatively, a single cell may support multiple numerologies; that is, terminals operating with different numerologies may coexist within a single cell.

[0086] Numerology corresponds to a single subcarrier spacing in the frequency domain. Different numerologies can be defined by scaling the reference subcarrier spacing by an integer N.

[0087] Figure 1 illustrates the structure of a wireless communication system to which this disclosure applies.

[0088] Referring to Figure 1, the NG-RAN consists of gNBs that provide control plane (RRC) protocol termination for the NG-RA (NG-Radio Access) user plane (i.e., the new AS (access stratum) sublayer / PDCP (Packet Data Convergence Protocol) / RLC (Radio Link Control) / MAC / PHY) and UE. The gNBs are interconnected via the Xn interface. The gNBs are also connected to the NGC (New Generation Core) via the NG interface. More specifically, the gNBs are connected to the AMF (Access and Mobility Management Function) via the N2 interface and to the UPF (User Plane Function) via the N3 interface.

[0089] Figure 2 illustrates a frame structure in a wireless communication system to which this disclosure is applicable.

[0090] The NR system can support a number of numerologies, which may be defined by subcarrier spacing and cyclic prefix (CP) overhead. These number of subcarrier spacings may be derived by scaling the fundamental (reference) subcarrier spacing by an integer N (or μ). Furthermore, even assuming that very low subcarrier spacings are not used at very high carrier frequencies, the numerologies used may be selected independently of the frequency band. The NR system may also support various frame structures based on these number of numerologies.

[0091] The following describes the OFDM numerologies and frame structures that can be considered in the NR system. Many of the OFDM numerologies supported in the NR system may be defined as shown in Table 1 below.

[0092] [Table 1]

[0093] NR supports a number of numerologies (or subcarrier spacings (SCS)) to support various 5G services. For example, an SCS of 15kHz supports wide area on traditional cellular bands, an SCS of 30kHz / 60kHz supports dense-urban areas, lower latency, and wider carrier bandwidth, and an SCS of 60kHz or higher supports bandwidths greater than 24.25GHz to overcome phase noise.

[0094] The NR frequency band is defined as a frequency range of two types (FR1 and FR2). FR1 and FR2 may be configured as shown in Table 2 below. Furthermore, FR2 can represent millimeter waves (mmW).

[0095] [Table 2]

[0096] In relation to the frame structure in an NR system, the sizes of various fields in the time domain are T c = 1 / (Δf max ·N f It is expressed as a multiple of the time unit of ). Here, Δf max =480·10 3 It is Hz, Nf = 4096. Downlink and uplink transmissions are based on T f = 1 / (Δf max N f / 100)·T c = 10 ms. The radio frame is composed of intervals of T sf =(Δf max N f / 1000)·T c = 1 ms and consists of 10 subframes. In this case, there may be one set of frames for the uplink and one set of frames for the downlink. Also, the transmission at the uplink frame number i from the terminal must start T TA =(N TA +N TA,offset )T c before the start of the corresponding downlink frame at the terminal. For the subcarrier spacing configuration μ, the slot is numbered in increasing order of n s μ ∈{0,...,N slot subframe,μ -1} within the subframe and in increasing order of n s,f μ ∈{0,...,N slot frame,μ -1} within the radio frame. One slot is composed of N symb slot consecutive OFDM symbols, and N symb slot is determined by the CP. In the subframe, the start of slot n s μ is the OFDM symbol n s μ N symb slotThe start and timing are aligned. Not all terminals can transmit and receive simultaneously, which means that not all OFDM symbols in the downlink slot or uplink slot can be used.

[0097] Table 3 shows the number of OFDM symbols per slot in a general CP (N symb slot ), Number of slots per wireless frame (N slot frame,μ ), Number of slots per subframe (N slot subframe,μ Table 4 shows the number of OFDM symbols per slot, the number of slots per wireless frame, and the number of slots per subframe in the extended CP.

[0098] [Table 3]

[0099] [Table 4]

[0100] Figure 2 shows an example where μ=2 (SCS is 60kHz). Referring to Table 3, one subframe can contain four slots. The one subframe = {1,2,4} slots shown in Figure 2 is just an example; the number of slots that can be included in one subframe is defined as shown in Table 3 or Table 4. Also, a mini-slot can contain 2, 4, or 7 symbols, or more or fewer symbols.

[0101] In relation to physical resources in an NR system, antenna ports, resource grids, resource elements, resource blocks, and carrier parts may be considered. The following describes in detail the physical resources that can be considered in an NR system.

[0102] First, in relation to antenna ports, an antenna port is defined such that the channel on which a symbol is carried on an antenna port can be inferred from the channel on which other symbols on the same antenna port are carried. If the large-scale property of the channel on which a symbol is carried on one antenna port can be inferred from the channel on which a symbol is carried on another antenna port, then the two antenna ports can be said to be in a QC / QCL (quasi co-located or quasi co-location) relationship. Here, the large-scale property includes one or more of the following: delay spread, Doppler spread, frequency shift, average received power, and received timing.

[0103] Figure 3 illustrates a resource grid in a wireless communication system to which this disclosure applies.

[0104] Referring to Figure 3, the resource grid is N in the frequency domain. RB μ N sc RB It consists of subcarriers, with one subframe being 14.2 μ This description exemplifies the use of OFDM symbols, but is not limited to them. In an NR system, the transmitted signal is N RB μN sc RB One or more resource grids and 2 μ N symb (μ) This is explained by the OFDM symbol, where N RB μ ≤N RB max,μ The above N RB max,μ This represents the maximum transmission bandwidth, which may vary not only in terms of numerology but also between the uplink and downlink. In this case, one resource grid may be set up for each μ and antenna port p. Each element of the resource grid for μ and antenna port p is called a resource element, and is an index pair (k, It is uniquely identified by JPEG0007849501000005.jpg53), where k=0,...,N RB μ N sc RB -1 is an index in the frequency domain, JPEG0007849501000006.jpg762 represents the position of a symbol within a subframe. When indicating resource elements in a slot, an index pair (k,l) is used, where l = 0, ..., N symb μ -1. Resource elements (k, JPEG0007849501000007.jpg54) is a complex value. This corresponds to JPEG0007849501000008.jpg811. When there is no risk of confusion, or when a specific antenna port or numerology is not identified, indices p and μ may be dropped, and as a result, the complex value JPEG0007849501000009.jpg912 or It could be JPEG0007849501000010.jpg912. Also, the resource block (RB) is N in the frequency domain.sc RB This is defined as a series of 12 consecutive subcarriers.

[0105] Point A acts as the common reference point for the resource block grid and is obtained as follows:

[0106] - The offsetToPointA for the Primary Cell (PCell) downlink indicates the frequency offset between the lowest subcarrier of the lowest resource block overlapping with the SS / PBCH block used by the terminal for initial cell selection and point A. It is expressed in resource block units, assuming a 15kHz subcarrier spacing for FR1 and a 60kHz subcarrier spacing for FR2.

[0107] - absoluteFrequencyPointA indicates the frequency-position of point A as expressed in ARFCN (absolute radio-frequency channel number).

[0108] Common resource blocks are numbered upwards from 0 in the frequency domain relative to the subcarrier spacing setting μ. The center of subcarrier 0 of common resource block 0 relative to the subcarrier spacing setting μ coincides with 'point A'. In the frequency domain, common resource block number n... CRB μ The relationship between the resource element (k,l) and the subcarrier spacing μ is given by Equation 1 below.

[0109]

number

[0110] In Equation 1, k is defined relative to point A such that k=0 corresponds to a subcarrier centered at point A. The physical resource block ranges from 0 to N within the bandwidth part (BWP). BWP,i size,μ The numbers are assigned down to -1, where i is the BWP number. In BWP i, the physical resource block n PRB and common resource block n CRB The relationship between them is given by equation 2 below.

[0111]

number

[0112] N BWP,i start,μ This is a common resource block where BWP starts relative to common resource block 0.

[0113] Figure 4 illustrates a physical resource block in a wireless communication system to which this disclosure applies. Figure 5 illustrates a slot structure in a wireless communication system to which this disclosure applies.

[0114] Referring to Figures 4 and 5, a slot contains multiple symbols in the time domain. For example, in a general CP, one slot contains seven symbols, while in an extended CP, one slot contains six symbols.

[0115] A carrier wave contains multiple subcarriers in the frequency domain. An RB (Resource Block) is defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain. A BWP (Bandwidth Part) is defined as multiple consecutive (physical) resource blocks in the frequency domain and can correspond to a single numerology (e.g., SCS, CP length, etc.). A carrier wave can contain up to N (e.g., 5) BWPs. Data communication takes place over activated BWPs, and only one BWP may be activated for a single terminal. In a resource grid, each element is called a resource element (RE) and may be mapped to a single complex symbol.

[0116] An NR system may support up to 400 MHz per component carrier (CC). If a terminal operating on such a wideband CC keeps its radio frequency (RF) chip on for the entire CC at all times, terminal battery consumption may increase. Alternatively, considering various use cases operating within a single wideband CC (e.g., eMBB, URLLC, Mmtc, V2X, etc.), different numerologies (e.g., subcarrier spacing) may be supported for each frequency band within that CC. Alternatively, terminals may have different capabilities for the maximum bandwidth. Taking this into consideration, a base station may instruct terminals to operate only on a portion of the wideband CC's bandwidth rather than the entire bandwidth, and this portion of the bandwidth is conveniently defined as a bandwidth part (BWP). A BWP may consist of consecutive RBs on the frequency axis and may correspond to a single numerology (e.g., subcarrier spacing, CP length, slot / minislot interval).

[0117] On the other hand, a base station can configure multiple BWPs within a single CC configured on a terminal. For example, a PDCCH monitoring slot can be configured with a BWP occupying a relatively small frequency range, while a PDSCH instructed by the PDCCH may be scheduled on a larger BWP. Alternatively, if UEs are concentrated on a particular BWP, other BWPs may be configured on some terminals for load balancing. Or, considering frequency domain inter-cell interference cancellation between adjacent cells, a portion of the spectrum from the total bandwidth can be excluded, and both BWPs can be configured within the same slot. In other words, a base station can configure at least one DL / UL BWP on terminals associated with a broadband CC. A base station can activate at least one DL / UL BWP among those configured at a given time (by L1 signaling, MAC CE (Control Element), or RRC signaling, etc.). Furthermore, the base station can instruct switching to another configured DL / UL BWP (by L1 signaling, MAC CE, or RRC signaling, etc.). Alternatively, it may switch to a designated DL / UL BWP when a timer expires. In this case, the activated DL / UL BWP is defined as the active DL / UL BWP. However, in situations such as when a terminal is in the initial access process or before the RRC connection is set up, the configuration for the DL / UL BWP may not be received. In such situations, the DL / UL BWP assumed by the terminal is defined as the initial active DL / UL BWP.

[0118] Figure 6 illustrates physical channels used in wireless communication systems to which this disclosure applies, and general signal transmission and reception methods using them.

[0119] In wireless communication systems, a terminal receives information from a base station via the downlink and transmits information to the base station via the uplink. The information transmitted and received between the base station and the terminal includes data and various control information, and various physical channels exist depending on the type and purpose of the information being transmitted and received.

[0120] When a terminal is powered on or enters a new cell, it performs initial cell search operations, such as synchronizing with the base station (S601). To do this, the terminal receives a primary synchronization signal (PSS) and a secondary synchronization signal (SSS) from the base station to synchronize with the base station and obtain information such as the cell identifier (ID). Subsequently, the terminal receives the physical broadcast channel (PBCH) from the base station to obtain intra-cell broadcast information. Meanwhile, during the initial cell search phase, the terminal can receive a downlink reference signal (DL RS) to check the downlink channel status.

[0121] Once the terminal has completed its initial cell search, it can receive the Physical Downlink Control Channel (PDCCH) and the Physical Downlink Shared Channel (PDSCH) via the information carried on the PDCCH, thereby obtaining more specific system information (S602).

[0122] On the other hand, if the terminal is initially connected to a base station or does not have radio resources for signal transmission, it can perform a Random Access Procedure (RACH) to the base station (stages S603 to S606). To do this, the terminal transmits a specific sequence as a preamble over a Physical Random Access Channel (PRACH) (S603 and S605), and can receive a response message to the preamble on the PDCCH and the corresponding PDSCH (S604 and S606). In the case of a conflict-based RACH, a Contention Resolution Procedure can also be performed.

[0123] A terminal that has performed the procedures described above can then perform general uplink / downlink signal transmission procedures, such as receiving PDCCH / PDSCH (S607) and transmitting Physical Uplink Shared Channel (PUSCH) / Physical Uplink Control Channel (PUCCH) (S608). In particular, the terminal receives Downlink Control Information (DCI) via PDCCH. Here, DCI includes control information such as resource allocation information for the terminal, and its format differs depending on its purpose of use.

[0124] On the other hand, control information that a terminal transmits to or receives from a base station on the uplink includes downlink / uplink ACK / NACK (Acknowledgement / Non-Acknowledgement) signals, CQI (Channel Quality Indicator), PMI (Precoding Matrix Indicator), RI (Rank Indicator), etc. In the 3GPP LTE system, the terminal can transmit the above-mentioned control information such as CQI / PMI / RI via PUSCH and / or PUCCH.

[0125] Table 5 shows an example of the DCI format in the NR system.

[0126] [Table 5]

[0127] Referring to Table 5, DCI formats 0_0, 0_1, and 0_2 can include resource information related to PUSCH scheduling (e.g., UL / SUL (Supplementary UL), frequency resource allocation, time resource allocation, frequency hopping, etc.), Transmit Block (TB) related information (e.g., MCS (Modulation Coding and Scheme), NDI (New Data Indicator), RV (Redundancy Version), etc.), HARQ (Hybrid - Automatic Repeat and Request) related information (e.g., process number, DAI (Downlink Assignment Index), PDSCH-HARQ feedback timing, etc.), multiplex antenna related information (e.g., DMRS sequence initialization information, antenna ports, CSI requests, etc.), and power control information (e.g., PUSCH power control, etc.). The control information included in each DCI format may be predefined.

[0128] DCI format 0_0 is used for scheduling PUSCH within a single cell. The information contained in DCI format 0_0 is scrambled using CRC (cyclic redundancy check) by C-RNTI (Cell RNTI: Cell Radio Network Temporary Identifier), CS-RNTI (Configured Scheduling RNTI), or MCS-C-RNTI (Modulation Coding Scheme Cell RNTI) before transmission.

[0129] DCI format 0_1 ​​is used to instruct terminals to schedule one or more pushes in a single cell, or to provide configured grant (CG) downlink feedback information. The information contained in DCI format 0_1 ​​is transmitted after being CRC scrambled by C-RNTI, CS-RNTI, SP-CSI-RNTI (Semi-Persistent CSI RNTI), or MCS-C-RNTI.

[0130] DCI format 0_2 is used for scheduling pushes within a single cell. The information contained in DCI format 0_2 is CRC scrambled by C-RNTI, CS-RNTI, SP-CSI-RNTI, or MCS-C-RNTI before transmission.

[0131] Next, DCI formats 1_0, 1_1, and 1_2 may include resource information related to PDSCH scheduling (e.g., frequency resource allocation, time resource allocation, VRB (virtual resource block)-PRB (physical resource block) mapping, etc.), transmit block (TB) related information (e.g., MCS, NDI, RV, etc.), HARQ related information (e.g., process number, DAI, PDSCH-HARQ feedback timing, etc.), multiplex antenna related information (e.g., antenna port, TCI (transmission configuration indicator), SRS (sounding reference signal) request, etc.), and PUCCH related information (e.g., PUCCH power control, PUCCH resource indicator, etc.), and the control information included in each DCI format may be predefined.

[0132] DCI format 1_0 is used for PDSCH scheduling within a single DL cell. The information contained in DCI format 1_0 is CRC scrambled by C-RNTI, CS-RNTI, or MCS-C-RNTI before transmission.

[0133] DCI format 1_1 is used for PDSCH scheduling within a single cell. The information contained in DCI format 1_1 is transmitted after being CRC scrambled by C-RNTI, CS-RNTI, or MCS-C-RNTI.

[0134] DCI format 1_2 is used for PDSCH scheduling within a single cell. The information contained in DCI format 1_2 is transmitted after being CRC scrambled by C-RNTI, CS-RNTI, or MCS-C-RNTI.

[0135] Artificial Intelligence (AI) operation

[0136] The advancement of artificial intelligence / machine learning (AI / ML) technology is leading to the increased intelligence and sophistication of nodes and terminals that constitute wireless communication networks. In particular, with the increasing intelligence of networks and base stations, it is expected that various network / base station determination parameter values ​​(e.g., transmit / receive power of each base station, transmit power of each terminal, base station / terminal precoder / beam, time / frequency resource allocation for each terminal, duplex scheme of each base station, etc.) will be rapidly optimized, derived, and applied based on various environmental parameters (e.g., distribution / location of base stations, distribution / location / material of buildings / furniture, terminal location / movement direction / speed, climate information, etc.). In line with this trend, many standardization bodies (e.g., 3GPP, O-RAN) are considering its introduction, and studies on this topic are actively underway.

[0137] The AI-related descriptions and operations described below may be applied in conjunction with the methods proposed in this disclosure, as described below, or may be supplemented to clarify the technical features of the methods proposed in this disclosure.

[0138] Figure 7 illustrates an example of artificial intelligence classification.

[0139] Referring to Figure 7, Artificial Intelligence (AI) encompasses all automation that machines can perform to do what humans would otherwise have to do.

[0140] Machine learning (ML) refers to a technology in which machines learn decision-making patterns from data without explicitly programming rules.

[0141] Deep learning is an artificial neural network-based model that allows machines to perform feature extraction and decision-making from unstructured data in a single step. The algorithm relies on a multi-layer network composed of interconnected nodes for feature extraction and transformation, focusing on the biological nervous system, i.e., the neural network. Common deep learning network architectures include deep neural networks (DNNs), recurrent neural networks (RNNs), and convolutional neural networks (CNNs).

[0142] In a narrow sense, AI (or AI / ML) can refer to deep learning-based artificial intelligence, but this disclosure is not limited to this. In other words, in this disclosure, AI (or AI / ML) can be a general term for automation technologies applied to intelligent machines that can perform tasks like humans (e.g., UE, RAN, network nodes, etc.).

[0143] AI (or AI / ML) can be classified as follows based on various criteria:

[0144] 1. Offline / Online Learning

[0145] a) Offline Learning

[0146] Offline learning follows a sequential procedure of database collection, training, and prediction. That is, collection and training are performed offline, and the completed program can be installed on-site and used for prediction work. Offline learning does not involve incremental learning; training is performed using all available collected data, and the system is applied without further training. If training on new data becomes necessary, training can be restarted using the new complete dataset.

[0147] b) Online Learning

[0148] In recent years, this method has leveraged the fact that data usable for learning is continuously generated via the internet, allowing for incremental learning using real-time data to gradually improve performance. Learning is performed in real time on specific data (sets) collected online, enabling the system to quickly adapt to changing data.

[0149] For building an AI system, online learning may be used exclusively, and training may be performed using only real-time data. Alternatively, offline learning may be performed using a predetermined dataset, followed by additional training using real-time data as it becomes available (online + offline learning).

[0150] 2. Classification based on AI / ML framework concepts

[0151] a) Centralized Learning

[0152] In centralized learning, training data collected from multiple different nodes is reported to a centralized node, and all data resources, storage, and learning (e.g., supervised learning, unsupervised learning, reinforcement learning, etc.) are performed at a single central node.

[0153] b) Federated Learning

[0154] Federative learning involves constructing a collective model based on data that exists across distributed data owners. Instead of collecting data into the model, the AI / ML model is fed into the data source, allowing local nodes / individual devices to collect the data and train their own model copies, eliminating the need to report source data to a central node. In federative learning, the parameters / weights of the AI / ML model can be sent back to the central node to support general model training. Federative learning offers advantages in terms of increased computational speed and information security. Specifically, it eliminates the need to upload personal data to a central server, preventing the leakage and misuse of personal information.

[0155] c) Distributed Learning

[0156] Distributed learning refers to the concept of machine learning processes being extended and distributed across a node cluster. The training model is divided and shared among multiple nodes operating simultaneously to increase the speed of model training.

[0157] 3. Classification by learning method

[0158] a) Supervised Learning

[0159] Supervised learning is a machine learning process that aims to learn a mapping function from input to output, given a dataset with specified labels. The input data, called training data, has known labels or results. An example of supervised learning is as follows:

[0160] - Regression: Linear Regression, Logistic Regression

[0161] - Instance-based algorithms: k-Nearest Neighbor (KNN)

[0162] - Decision Tree Algorithms: Classification and Regression Tree (CART)

[0163] - Support Vector Machines (SVM)

[0164] - Bayesian algorithms: Naive Bayes

[0165] - Ensemble Algorithms: Extreme Gradient Boosting, Bagging: Random Forest

[0166] Supervised learning can be further grouped into regression and classification problems, where classification is predicting labels and regression is predicting quantities.

[0167] b) Unsupervised Learning

[0168] Unsupervised learning is a machine learning task that aims to learn the ability to explain hidden structures from unlabeled data. The input data is unlabeled and there are no known results. Some examples of unsupervised learning include K-means clustering, principal component analysis (PCA), nonlinear independent component analysis (ICA), and long-short-term memory (LSTM).

[0169] c) Reinforcement Learning (RL)

[0170] In reinforcement learning (RL), the agent aims to optimize long-term goals by interacting with the environment through a trial-and-error process; it is a goal-oriented learning method based on interaction with the environment. An example of an RL algorithm is as follows:

[0171] - Q-learning

[0172] - Multi-armed bandit learning

[0173] - Deep Q Network

[0174] - State-Action-Reward-State-Action (SARSA)

[0175] - Temporal Difference Learning

[0176] - Actor-critic reinforcement learning

[0177] - Deep deterministic policy gradient (DDPG)

[0178] - Monte-Carlo tree search

[0179] Furthermore, reinforcement learning can be grouped into model-based reinforcement learning and model-free reinforcement learning, as follows:

[0180] - Model-based reinforcement learning: This refers to RL algorithms that use predictive models. It obtains state transition probabilities using various dynamic states of the environment and models in which such states lead to compensation.

[0181] - Model-free reinforcement learning: This refers to RL algorithms based on values ​​or policies that achieve the greatest future compensation. In multi-agent environments / states, it is computationally relatively simple and does not require an accurate representation of the environment.

[0182] Furthermore, RL algorithms can be classified into categories such as value-based RL versus policy-based RL, and policy-based RL versus non-policy RL.

[0183] The following are examples of representative deep learning models.

[0184] Figure 8 illustrates a feed-forward neural network.

[0185] A feed-forward neural network (FFNN) consists of an input layer, a hidden layer, and an output layer.

[0186] In an FFNN, information is transmitted only from the input layer to the output layer, and if there is a hidden layer, it is transmitted through it.

[0187] Figure 9 illustrates a recurrent neural network.

[0188] A circulating neural network (RNN) is a type of artificial neural network in which hidden nodes are connected to directional edges to form a cyclic structure (directed cycle). It is a suitable model for processing sequentially appearing data such as speech and text.

[0189] In Figure 9, A is a neural network, x t is the input value, h t represents the output value. Here, h t This can mean a state value that indicates the present based on time, and h t-1 This can indicate a previous state value.

[0190] One type of RNN is LSTM (Long Short-Term Memory), which is a structure that adds cell states to the hidden states of an RNN. In an LSTM, input gates, forget gates, and output gates are added to the RNN cells (memory cells in the hidden layer), allowing unnecessary memories to be erased. Compared to an RNN, an LSTM has added cell states.

[0191] Figure 10 illustrates a convolutional neural network.

[0192] Convolutional neural networks (CNNs) are used for two purposes: to reduce model complexity and to extract good features, by applying convolutional operations, which are commonly used in the fields of video or image processing.

[0193] - Kernel or filter: Refers to a unit / structure that applies weighted values ​​to a specific range / unit of input. The kernel (or filter) may be modified through learning.

[0194] - Stride: Refers to the range of movement the kernel can make within the input.

[0195] - Feature map: This represents the result of applying a kernel to the input. Multiple feature maps may be extracted to guide the model towards being more robust to distortion, modification, etc.

[0196] - Padding: This refers to the value added to adjust the size of a property map.

[0197] - Pooling: This refers to operations that reduce the size of a characteristic map by downsampling it (e.g., max pooling, average pooling).

[0198] Figure 11 illustrates an autoencoder.

[0199] An autoencoder is a neural network that takes a feature vector x(x1,x2,x3,...) as input and outputs the same or similar vector x'(x'1,x'2,x'3,...)'.

[0200] An autoencoder is characterized by having identical input and output nodes. Because it reconstructs the input, it can be called an output reconstruction. Furthermore, an autoencoder is a type of unsupervised learning.

[0201] The loss function of the autoencoder illustrated in Figure 11 is calculated based on the difference between the input and the output. Based on this, the degree of input loss is determined, and the autoencoder undergoes an optimization process to minimize the loss.

[0202] To provide a more detailed explanation of AI (or AI / ML), the following terms can be defined:

[0203] - Data collection: Data collected from network nodes, management entities, or UEs (Unified Environments) as a base for AI model training, data analysis, and inference.

[0204] - AI Model: A data-driven algorithm that applies AI technology to generate a set of outputs, including predictive information and / or decision parameters, based on a set of inputs.

[0205] - AI / ML Training: An online or offline process of training an AI / ML model by learning the functions and patterns that best display data and enable the AI / ML model to be trained for inference.

[0206] - AI / ML Inference: The process of making predictions or inducing decisions based on collected data and the AI ​​model, using a trained AI model.

[0207] Figure 12 illustrates a functional framework for AI operation.

[0208] Referring to Figure 12, the Data Collection function 10 is a function that collects input data and provides the processed input data to the Model Training function 20 and the Model Inference function 30.

[0209] Examples of input data may include measurements from UEs or other network entities, actor feedback, and AI model output.

[0210] The data collection function 10 performs data preparation based on the input data and provides the input data processed by the data preparation. Here, the data collection function 10 does not perform specific data preparation for each AI algorithm (for example, data pre-processing and cleaning, formatting and transformation), but can perform data preparation common to all AI algorithms.

[0211] After the data preparation process is completed, the model acquisition function 10 provides training data 11 to the model training function 20 and inference data 12 to the model inference function 30. Here, the training data 11 is the data required as input for the AI ​​model training function 20. The inference data 12 is the data required as input for the AI ​​model inference function 30.

[0212] The data collection function 10 may be performed by a single entity (e.g., a UE, RAN node, network node, etc.), or by multiple entities. In this case, training data 11 and inference data 12 may be provided from multiple entities to the model training function 20 and the model inference function 30, respectively.

[0213] The model training function 20 is part of the AI ​​model testing procedure and performs AI model training, validation, and testing, which can generate model performance metrics. The model training function 20 is also responsible for data preparation (e.g., data preprocessing and organization, formatting, and transformation) based on the training data 11 provided by the data collection function 10, if necessary.

[0214] Here, Model Deployment / Update 13 is used to initially distribute the trained, validated, and tested AI model to the Model Inference Function 30, or to provide the updated model to the Model Inference Function 30.

[0215] The model inference function 30 is a function that provides AI model inference output 16 (e.g., prediction or decision). The model inference function 30 can provide model performance feedback 14 to the model training function 20, if applicable. The model inference function 30 is also responsible for data preparation (e.g., data preprocessing and organization, formatting and transformation) based on the inference data 12 provided by the data collection function 10, if necessary.

[0216] Here, Output 16 refers to the inference output of the AI ​​model generated by the model inference function 30, and the detailed information of the inference output may vary depending on the use case.

[0217] Model performance feedback 14 can be used to monitor the performance of the AI ​​model if available, and this feedback may be omitted.

[0218] The Actor function 40 receives output 16 from the Model Inference function 30 and triggers or executes the corresponding task / action. The Actor function 40 can trigger tasks / actions on other entities (e.g., one or more UEs, one or more RAN nodes, one or more network nodes, etc.) or on itself.

[0219] The feedback 15 may be used to derive training data 11 and inference data 12, or to monitor the performance of the AI ​​model, its impact on the network, etc.

[0220] On the other hand, the definitions of training, validation, and test in datasets used in AI / ML can be categorized as follows:

[0221] - Training data: This refers to the dataset used to train a model.

[0222] - Validation data: This refers to a dataset used to validate a model that has already been trained. In other words, it is a dataset used to prevent overfitting of the training dataset.

[0223] Furthermore, it refers to a dataset used to select the best model from among the various models learned during the learning process. Therefore, it can be considered a type of learning.

[0224] - Test data: This refers to the dataset used for final evaluation. This data is not related to the training process.

[0225] In the case of the aforementioned dataset, when dividing the training set, the training data and validation data within the overall training set can generally be divided into a ratio of 8:2 or 7:3, and if the test is included, it can be divided into a ratio of 6:2:2 (training:validation:test).

[0226] The level of cooperation can be defined as follows based on the capability (capable) of AI / ML functions between the base station and the terminal, and it is also possible to combine multiple levels or decouple any one of them.

[0227] Cat 0a) No collaboration framework: AI / ML algorithms are purely implementation-based and do not require changes to the wireless interface.

[0228] Cat 0b) This level corresponds to a framework that includes a wireless interface modified to suit efficient, real-world AI / ML algorithms, but without collaboration.

[0229] Cat 1) Inter-node support is provided to improve the AI / ML algorithms of each node. This applies when the UE receives support from gNB (for training, adaptation, etc.) and vice versa. At this level, model exchange between network nodes is not required.

[0230] Cat 2) Collaborative ML work between UE and gNB is permitted. This level requires the exchange of AI / ML model instructions or network nodes.

[0231] The functions illustrated in Figure 12 may be implemented in RAN nodes (e.g., base stations, TRPs, base station central units (CUs)), network nodes, network operators' OAMs (operation administration maintenance), or UEs.

[0232] Alternatively, two or more entities from among the RAN, network nodes, network operator's OAM, or UE may cooperate to embody the functions exemplified in Figure 12. For example, one entity may perform part of the functions in Figure 12, while the others perform the remaining functions. In this way, by having some of the functions exemplified in Figure 12 performed by a single entity (e.g., UE, RAN node, network node, etc.), the transmission / provision of data / information between each function may be omitted. For example, if the model training function 20 and the model inference function 30 are performed by the same entity, the transmission / provision of model distribution / update 13 and model performance feedback 14 may be omitted.

[0233] Alternatively, one of the functions exemplified in Figure 12 can be performed by two or more entities from among the RAN, network nodes, network operator's OAM, or UE in collaboration. This can be called split AI operation.

[0234] Figure 13 illustrates segmented AI inference.

[0235] Figure 13 illustrates a case in which the model inference function of segmented AI operation is performed collaboratively by an end device such as a UE and a network AI / ML endpoint.

[0236] In addition to the model inference function, the model training function, actor function, and data collection function may also be split into multiple parts depending on the current work and environment, and performed by multiple individuals working together.

[0237] For example, computation-intensive and energy-intensive parts are performed at the network terminal, while parts sensitive to personal information and parts sensitive to latency may be performed at the terminal device. In this case, the terminal device can transmit intermediate data to the network terminal after executing the operation / model from the input data to a specific part / hierarchy. The network terminal executes the remaining parts / hierarchies and provides the inference output results to one or more devices that perform the operation / work.

[0238] FIG. 14 illustrates the application of a functional framework in a wireless communication system.

[0239] FIG. 14 exemplifies the case where the AI model training function is performed by a network node (e.g., a core network node, OAM of a network operator, etc.) and the AI model inference function is performed by a RAN node (e.g., a base station, a TRP, a CU of a base station, etc.).

[0240] Step 1: RAN Node 1 and RAN Node 2 transmit input data (i.e., training data) for AI model training to the network node. Here, RAN Node 1 and RAN Node 2 can jointly transmit data collected from the UE (e.g., UE measurements related to RSRP, RSRQ, SINR of the serving cell and adjacent cells, UE position, speed, etc.) to the network node.

[0241] Step 2: The network node trains the AI model using the received training data.

[0242] Step 3: The network node distributes / updates the AI model to RAN Node 1 and / or RAN Node 2. RAN Node 1 (and / or RAN Node 2) can also continue to perform model training based on the received AI model.

[0243] For the sake of explanation, let's assume that the AI ​​model was distributed / updated only to RAN node 1.

[0244] Stage 4: RAN node 1 receives input data (i.e., inference data) for AI model inference from UE and RAN node 2.

[0245] Stage 5: RAN node 1 performs AI model inference using the received inference data and generates output data (e.g., prediction or decision).

[0246] Stage 6: If applicable, RAN node 1 can send model performance feedback to the network nodes.

[0247] Stage 7: RAN Node 1, RAN Node 2, and UE (or "RAN Node 1 and UE", or "RAN Node 1 and RAN Node 2") perform actions based on the output data. For example, in the case of a load balancing action, the UE can move from RAN Node 1 to RAN Node 2.

[0248] Stage 8: RAN Node 1 and RAN Node 2 send feedback information to the network node.

[0249] Figure 15 illustrates the application of a functional framework in a wireless communication system.

[0250] Figure 15 illustrates a case where both AI model training and AI model inference are performed by RAN nodes (e.g., base stations, TRPs, base station CUs, etc.).

[0251] Stage 1: UE and RAN node 2 send input data (i.e., training data) for AI model training to RAN node 1.

[0252] Stage 2: RAN node 1 trains the AI ​​model using the received training data.

[0253] Stage 3: RAN node 1 receives input data (i.e., inference data) for AI model inference from UE and RAN node 2.

[0254] Stage 4: RAN node 1 performs AI model inference using the received inference data and generates output data (e.g., prediction or decision).

[0255] Stage 5: RAN Node 1, RAN Node 2, and UE (or "RAN Node 1 and UE", or "RAN Node 1 and RAN Node 2") perform actions based on the output data. For example, in the case of load balancing, the UE can move from RAN Node 1 to RAN Node 2.

[0256] Stage 6: RAN node 2 sends feedback information to RAN node 1.

[0257] Figure 16 illustrates the application of a functional framework in a wireless communication system.

[0258] Figure 16 illustrates a case where the AI ​​model training function is performed by RAN nodes (e.g., base stations, TRPs, base station CUs, etc.) and the AI ​​model inference function is performed by UEs.

[0259] Stage 1: The UE sends input data (i.e., training data) for training the AI ​​model to the RAN node. Here, the RAN node can collect data from various UEs and / or other RAN nodes (e.g., UE measurements related to RSRP, RSRQ, SINR of the serving cell and adjacent cells, UE location, velocity, etc.).

[0260] Stage 2: The RAN node trains the AI ​​model using the received training data.

[0261] Step 3: The RAN node distributes / updates the AI model to the UE. The UE can also continue to perform model training based on the received AI model.

[0262] Step 4: Receive input data (i.e., inference data) for AI model inference from the UE and the RAN node (and / or from other UEs).

[0263] Step 5: The UE performs AI model inference using the received inference data and generates output data (e.g., predictions or decisions).

[0264] Step 6: If applicable, the UE can send model performance feedback to the RAN node.

[0265] Step 7: The UE and the RAN node perform actions based on the output data.

[0266] Step 8: The UE sends feedback information to the RAN node.

[0267] Quasi-Co Location (QCL)

[0268] An antenna port is defined such that the channel on which the symbols on the antenna port are carried can be inferred from the channels on which other symbols on the same antenna port are carried. If the characteristics of the channel on which the symbols on one antenna port are carried can be inferred from the channels on which the symbols on other antenna ports are carried, it can be said that the two antenna ports are in a QC / QCL (quasi co-located) relationship.

[0269] Here, the channel characteristics include one or more of the following: delay spread, Doppler spread, frequency / Doppler shift, average received power, received timing / average delay, and spatial Rx parameter. Here, the spatial reception parameter refers to a spatial (received) channel characteristic parameter such as the angle of arrival.

[0270] The terminal may have a list of up to M TCI state settings in the upper-layer parameter PDSCH-Config in order to decode the PDSCH with the detected PDCCH which has the intended DCI for the terminal and the given serving cell. The M depends on the UE capability.

[0271] Each TCI-State includes parameters for establishing a quasi-identical positional relationship between one or two DL reference signals and the DM-RS ports of the PDSCH.

[0272] The quasi-identical positional relationship is established by the upper-level parameter qcl-Type1 for the first DL RS and qcl-Type2 (if set) for the second DL RS. For two DL RSs, the QCL type is not the same regardless of whether the reference is the same DL RS or a different DL RS.

[0273] The QCL type corresponding to each DL RS is given by the higher-level parameter qcl-Type in QCL-Info, and can take one of the following values:

[0274] - "QCL-TypeA": {Doppler shift, Doppler diffusion, mean delay, delay diffusion}

[0275] - "QCL-TypeB": {Doppler shift, Doppler diffusion}

[0276] - "QCL-TypeC": {Doppler shift, mean delay}

[0277] - "QCL-TypeD": {Spatial reception parameters}

[0278] For example, if the target antenna port is a specific NZP CSI-RS, that NZP CSI-RS antenna port may be instructed / configured as a specific TRS from a QCL-Type A perspective and as a specific SSB from a QCL-Type D perspective. A terminal that receives such instructions / configurations can receive the NZP CSI-RS using the Doppler and delay values ​​measured from the QCL-Type A TRS, and apply the received beam used for QCL-Type D SSB reception to the NZP CSI-RS reception.

[0279] The UE can receive activation commands via MAC CE signaling, which are used to map up to eight TCI states to codepoints in the DCI field 'Transmission Configuration Indication'.

[0280] Beam direction method

[0281] In this disclosure, the QCL type-D reference signal (RS) or TCI state (or abbreviated as TCI) may refer to a spatial parameter, i.e., the QCL reference RS for a DL beam, or may be extended to refer to the reference RS or source RS for that spatial parameter or other beam / space-related parameters. Furthermore, in the proposed method of this disclosure, the designation of the QCL type-D RS may be omitted in environments where analog beamforming is not used, such as in the low-frequency band. In this case, the QCL type-D RS in this disclosure may be analyzed as the QCL reference RS (i.e., if only one reference RS exists in the TCI state, it may refer to that RS). Also, from an UL perspective, the TCI state (or abbreviated as TCI) may refer to the reference / source RS for the UL beam, or it may refer to the spatial relation RS (and path loss RS) in existing Rel-15 / 16. Here, the path loss RS may be the same as the spatial relation RS, or it may be set in relation to the UL TCI state or set separately.

[0282] In Rel-15, beam designation was performed for each DL / UL channel / signal, but in Rel-16, integrated beam designation methods for multiple component carriers and for multiple PUCCH resources were introduced. Furthermore, Rel-17 introduced an integrated beam designation method for multiple DL / UL channels / signals. According to the Rel-17 method, the TCI state can be applied to UL as well as DL. Moreover, this TCI state may be applied to PDCCH, PDSCH, PUCCH, PUSCH, SRS, and CSI-RS, and by changing / designating this TCI state, the beam for the DL / UL channel / signal can be changed at once.

[0283] The UE may have a list of up to M TCI-state settings (i.e., DL TCIs) in the upper-layer parameter PDSCH-Config in order to decode the PDSCH with the detected PDCCH, which includes the DCI for the UE and a given serving cell. Here, each TCI-state includes one or two DL reference signals (RS) and parameters for setting up QCL relationships between the DM-RS ports of the PDSCH, the DM-RS ports of the PDCCH, or the CSI-RS ports of the CSI.

[0284] Furthermore, the UE may be configured with a list of up to 128 TCI-state settings in the upper-level parameter dl-OrJointTCI-StateToAddModList (i.e., Joint TCI) within PDSCH-Config, for i) providing DMRS for PDSCH and PDDCCH within BWP / component carrier (CC), DMRS for PDDCCH, RS for QCL for CSI-RS, and ii) providing a reference for determining UL Tx spatial filters for dynamic grant and configured-grant based PUSCH and PUCCH resources within BWP / CC.

[0285] Furthermore, the UE may be configured with a list of up to 64 TCI-UL-State settings (i.e., UL TCI) within the upper-level parameter BWP-UplinkDedicated. Each TCI-UL-State setting includes parameters for configuring dynamic-grant and configured-grant based PUSCH and PUCCH resources within the CC, and for setting the RS to determine the UL TX spatial filter for the SRS.

[0286] These beam direction methods can be broadly classified into the following two types:

[0287] Scheme 1) MAC-CE based scheme

[0288] As described above, when N TCI states are set by RRC signaling and only one of the N TCI states is activated by the MAC-control element (CE), the UE applies that TCI state to the channel / signal (i.e., applies the beam activated by the MAC-CE).

[0289] For example, MAC CEs for TCI state indication of DL RS / channels may include semi-persistent (SP) CSI-RS / CSI-IM resource set activation / deactivation MAC CEs, TCI states activation / deactivation for UE-specific PDSCH MAC CEs, and TCI state indication for UE-specific PDCCH MAC CEs. Furthermore, MAC CEs for spatial relation or TCI state indication of UL RS / channels may include SP SRS Activation / Deactivation MAC CE, Enhanced SP / AP SRS Spatial Relation Indication MAC CE, SP / AP SRS TCI State Indication MAC CE, PUCCH Spatial Relation Activation / Deactivation MAC CE, Enhanced PUCCH Spatial Relation Activation / Deactivation MAC CE, etc. Also, integrated TCI state indications for DL ​​RS / channels and UL RS / channels may include Unified TCI States Activation / Deactivation MAC CE, etc.

[0290] Scheme 2) DCI-based method

[0291] As described above, RRC signaling sets up N TCI states, and MAC-CE (see MAC-CE exemplified in the MAC-CE-based scheme) activates M (M>1) of these TCI states. Then, DCI designates one of the M activated TCI states (using the TCI field in the already defined DCI). The UE applies this TCI state to the channel / signal (i.e., applies the beam finalized by DCI).

[0292] The UE can assume that when a TCI-state is set in dl-OrJoint-TCIStateList or PDSCH-Config, the DMRS of PDSCH, the DMRS of PDCCH, and the CSI-RS are QCL'd with the RS set to the qcl-Type set to "typeD" of the indicated TCI-state.

[0293] When a UE is set to dl-OrJoint-TCIStateList or TCI-UL-State, the UE can make a PUSCH transmission corresponding to a Type 1 set grant, a Type 2 set grant, or a dynamic grant by a spatial relation that references an RS for determining the UL TX spatial filter. The RS may be determined based on i) an RS set to qcl-Type set to "typeD" of the indicated TCI-state, or ii) an RS within the indicated TCI-UL-State.

[0294] In the future, if a network can predict the optimal transmission beam (Tx beam) at a future point in time through the introduction of AI / ML, the UL / DL transmission beam can be determined more effectively.

[0295] Based on (i.e., extended / modified) the beam pointing operation / method described above, this disclosure proposes a multicast (optimal future time point) beam pointing method for a group of multiple UEs.

[0296] In this disclosure, "beam" may be interpreted as equivalent to a TCI state (or simply TCI).

[0297] Furthermore, in the following descriptions of this disclosure, unless otherwise specified, it is assumed that a UE group consists of one or more UEs, and if it consists of only one UE, a UE group may be interpreted as a single UE.

[0298] In the case of high-speed trains (HSTs), the UE moves at a high speed, but it moves at a constant speed along the railway tracks, making it relatively easy to predict the transmission and reception beams.

[0299] Figure 17 illustrates a high-speed train scenario.

[0300] Referring to Figure 17, we illustrate a case where the UEs included in UE group 4 are currently receiving the DL channel on beam 2, and the UEs included in UE group 1 are currently receiving the DL channel on beam 1. With respect to the direction of travel of the train, UE groups 1, 2, 3, and 4 are from front to back. It is preferable that UE group 2 receives the DL channel on beam 1 after a certain time t, UE group 3 receives the DL channel on beam 1 after a certain time 2t, and UE group 4 receives the DL channel on beam 1 after a certain time 3t. Therefore, although beam 1 is currently applied only to UE group 1, it needs to be applied to all other UE groups as time progresses.

[0301] This allows for a reduction in signaling overhead compared to the existing UE-specific beam indication method, by using a multicast beam indication method where multiple UEs receive beam indication.

[0302] In other words, this disclosure proposes a method for directing one or more beams to one or more UE groups with a single signaling, where each UE group consists of one or more UEs. For the sake of clarity in this disclosure, we assume that each UE knows which UE group it belongs to, and as an example, a base station can pre-instruct each UE which UE group it belongs to.

[0303] Figure 18 is a diagram illustrating a beam instruction according to one embodiment of the present disclosure.

[0304] Referring to Figure 18, a multicast beam instruction may include information about a beam applied to one or more UE groups (e.g., TCI status or QCL type-D RS) and a time offset for applying that beam to each UE group. It may also include identification information / index for each UE group. As mentioned above, a single UE group may consist of one or more UEs. For example, if it consists of one UE, then in Figure 18, UE groups 1, 2, 3, and 4 may be interpreted as UE1, 2, 3, and 4, respectively.

[0305] In other words, a base station can use multicast beam instruction to specify which beams to apply to multiple UE groups, and can also specify a time offset for when to apply those beams to each UE group. Here, the time offset may be specified in units of OFDM symbols, slots, or absolute time units (e.g., ms).

[0306] Here, the reference time to which the time offset is applied may be the time when the multicast signal (i.e., the signal including the multicast beam instruction) is fully received by the UE, or the reference time itself may be indicated by being appended to the multicast signal (i.e., the signal including the multicast beam instruction). Here, the unit of the reference time to which the time offset is applied may be the same as the unit of the time offset. For example, if the multicast beam instruction is transmitted in DCI, the reference time may be determined based on the last OFDM symbol (symbol) in which the DCI is received.

[0307] Each UE can apply the designated beam at a time calculated by adding a time offset value in its UE group to the reference time (or from that time until the next new beam is designated). Each UE can also apply the designated beam for a specific duration starting from a time calculated by adding a time offset value in its UE group to the reference time. Here, the duration may be provided to the UE by the multicast beam designation or other signaling, and may be predefined in a standard or similar.

[0308] For example, if the instruction method in Figure 18 is applied to the case in Figure 17, the beam indication will be set to beam 1, and the time offset values ​​1, 2, 3, and 4 may be indicated for UE groups 1, 2, 3, and 4, respectively. As mentioned above, the time offset may be indicated in OFDM symbol units, slot units, absolute time units (e.g., ms), and we will assume that it is indicated in slot units. In this case, for a reference slot n determined by the reference time, UE groups 1, 2, 3, and 4 will apply beam 1 to slots n+1, n+2, n+3, and n+4, respectively, and can apply the beam until the next beam indication is given or for a specific duration (where duration information may be further specified).

[0309] Figure 19 is a diagram illustrating a beam instruction according to one embodiment of the present disclosure.

[0310] Referring to Figure 19, a beam indication may include information for one or more beams (e.g., TCI status or QCL type-D RS) and a time offset for each beam to which that beam is applied. It may also include identification information / index for the target UE group (or UE). Here, the time offset may be indicated in OFDM symbol units, slot units, absolute time units (e.g., ms), etc.

[0311] In other words, a base station can multicast beam instructions to UE groups that pass through similar / identical channel environments. Here, in environments where future beams can be predicted, such as HST, the base station can give instructions for multiple beams to be applied to more distant futures, not just one beam, at once. For example, if the base station (e.g., base station AI) determines that it is best to apply beam 1 to UE group 1 at time t, and beams 2, 3, and 4 at times t+1, t+2, and t+3 respectively, the base station can signal a multicast beam instruction to the UE group as shown in Figure 19.

[0312] Alternatively, as described above, a UE group may consist of one or more UEs. For example, if it consists of one UE, the beam indication (i.e., unicast beam indication) shown in Figure 19 may be signaled to one UE.

[0313] In other words, a single beam instruction may specify one or more beams, and the time offset value to which each beam should be applied may be specified. Referring to Figure 19, an example is shown where beams 1, 2, 3, and 4 are specified at once, and the time offset value to which each beam should be applied is specified. A UE group (or UE) receiving this can apply beam 1 after offset 1 from the reference time, beam 2 after offset 2, beam 3 after offset 3, and beam 4 after offset 4. As described above, the time offset may be specified in OFDM symbol units, slot units, absolute time units (e.g., ms), etc. The reference time to which the time offset is applied may be the time when the multicast signal (i.e., the signal containing the multicast beam instruction) has been fully received by the UE, or the reference time itself may be specified in addition to the multicast signal (i.e., the signal containing the multicast beam instruction). Here, the unit of the reference time to which the time offset is applied may be the same as the unit of the time offset.

[0314] Figure 20 is a diagram illustrating a beam instruction according to one embodiment of the present disclosure.

[0315] Figure 20 illustrates a case where the examples in Figures 18 and 19 described above are combined. Specifically, referring to Figure 20, a multicast beam instruction may include information for one or more beams applied to one or more UE groups (e.g., TCI status or QCL type-D RS) and a time offset (time offset) to which each beam is applied for each UE group. It may also include identification information / index for each UE group. Here, the time offset may be indicated in OFDM symbol units, slot units, absolute time units (e.g., ms), etc. As described above, one UE group may consist of one or more UEs. For example, if it consists of one UE, in Figure 20, UE groups 1, 2, 3, and 4 may be interpreted as UE1, 2, 3, and 4, respectively.

[0316] Referring to Figure 20, UE groups 1, 2, 3, and 4 may all be treated identically with beams 1, 2, 3, and 4, but the time offsets to which each beam is applied may be set independently for each UE group.

[0317] Furthermore, while Figure 20 illustrates a case where beams 1, 2, 3, and 4 are identically configured for all UE groups 1, 2, 3, and 4, different beams may be configured for each UE group. For example, beams 1, 2, 3, and 4 may be configured for UE groups 1 and 2, beams 2, 3, and 4 for UE group 3, and beams 3 and 4 for UE group 4. In this case, only time offset information for the beams configured for each UE group may be included.

[0318] The multicast beam instruction information described above may be communicated to the UE using various signaling methods such as DCI / MAC control elements (CE) / RRC.

[0319] For example, when DCI is used, a DCI format 2-x for multicast use may be further defined and used to transmit multicast beam indication information. That is, another DCI format for transmitting multicast beam indication information may be defined. Furthermore, another RNTI may be defined for use in scrambling sequence generation and CRC (cyclic redundancy check) of the DCI. That is, another RNTI for transmitting multicast beam indication information may be defined, in which case the UE can decode the DCI containing the multicast beam indication information using the newly defined RNTI.

[0320] As another example, when MAC-CE is used (or when RRC signaling is used), the multicast beam indication information may be transmitted via a PDSCH. In this case, the DCI scheduling the PDSCH may be transmitted via a common search space so that it can be propagated to multiple UEs. Furthermore, another RNTI may be defined for scrambling sequence generation and CRC of the DCI scheduling the PDSCH, in which case the UE can decode the DCI containing the multicast beam indication information using the newly defined RNTI.

[0321] Furthermore, in the proposed method described above, in order for the network / base station to derive the output (i.e., multicast beam instruction information) (for example, this may correspond to output 16 in Figure 12, and the output may be derived by a procedure as shown in Figure 14 or Figure 15), the UE or UE group can provide the network / base station with input parameters (for example, this may correspond to inference data 12 in Figure 12), such as UE location and / or velocity-related information, DL channel / signal measurements, beam-specific SINR (signal to interference and noise ratio), beam-specific RSRP (reference signal received power), and beam preference.

[0322] Furthermore, although the proposed method in the above-described embodiment assumes an HST environment for the sake of explanation, this disclosure is not limited to this and can be extended and applied to other scenarios / environments.

[0323] Furthermore, the proposed methods described in the above-mentioned embodiments may be applied individually, or two or more proposed methods may be applied in combination / joinery.

[0324] Furthermore, the base station can instruct the UE whether or not to apply the proposed operation described in the above-mentioned embodiment through signaling such as RRC / MAC CE (control element) / DCI.

[0325] Furthermore, the proposed operation according to the above-described embodiment may be applied to various channels or reference signals such as PDSCH / PUSCH / PDCCH / PUCCH.

[0326] Figure 21 illustrates a signaling procedure between a network and a UE for a wireless signal transmission and reception method according to one embodiment of the present disclosure.

[0327] Figure 21 illustrates signaling between a network (e.g., TRP1, TRP2) and a UE for a method proposed in the present invention (e.g., one of the proposed methods or a combination of the proposed methods). Here, the UE / network is merely an example and may be substituted with various devices. Figure 21 is for illustrative purposes only and does not limit the scope of this disclosure. Furthermore, some steps illustrated in Figure 21 may be omitted depending on the circumstances and / or settings.

[0328] The signaling scheme described in Figure 21 may be extended and applied to signaling between multiple TRPs and multiple UEs. In the following description, the network may be a single base station containing multiple TRPs, or a single cell containing multiple TRPs. As an example, an ideal / non-ideal backhaul may be set up between TRP1 and TRP2 that constitute the network. Furthermore, although the following description is based on multiple TRPs, it may be similarly extended and applied to transmission using multiple panels. In addition, in this disclosure, the operation of a UE receiving a signal from TRP1 / TRP2 may be interpreted / described (or may be an operation) of a UE receiving a signal from the network (via / using TRP1 / 2), and the operation of a terminal transmitting a signal to TRP1 / TRP2 may be interpreted / described (or may be an operation) of a UE transmitting a signal to the network (via / using TRP1 / TRP2), and vice versa.

[0329] The term "base station" may refer collectively to the objects that transmit and receive data with the UE. For example, the base station may be a concept that includes one or more TPs (Transmission Points) and one or more TRPs (Transmission and Reception Points). Furthermore, the TPs and / or TRPs may include the base station's panel, transmission and reception unit, etc. Also, "TRP" may be replaced with expressions such as panel, antenna array, cell (e.g., macro cell / small cell / pico cell), TP (transmission point), base station (base station, gNB, etc.). As mentioned above, TRPs may be distinguished by information (e.g., index, ID) for the CORESET group (or CORESET pool). For example, if one UE is configured to transmit and receive with multiple TRPs (or cells), this means that multiple CORESET groups (or CORESET pools) are configured for one UE. Such configurations for CORESET groups (or CORESET pools) may be performed using higher-level signaling (e.g., RRC signaling).

[0330] The UE receives configuration information from the network (S2101).

[0331] The configuration information may include information related to the network configuration (e.g., TRP configuration) and information related to M-TRP-based transmission and reception (e.g., resource allocation). In this case, the configuration information may be transmitted by higher-layer signaling (e.g., RRC signaling, MAC-CE, etc.).

[0332] The aforementioned configuration information may include configuration information related to the setting of the TCI state (i.e., beam) as described in the proposed methods described above (for example, one of the proposed methods or a combination of the proposed methods).

[0333] More specifically, the configuration information may include information for the configuration of joint TCIs and / or separate DL / UL TCIs. For example, the configuration information may include a list of TCI states that provides a reference signal for QCL for DMRS / downlink signals (e.g., CSI-RS) on downlink channels (e.g., PDSCH, PDCCH) and / or a reference for determining the uplink transmit spatial filter for DMRS / uplink signals (e.g., SRS) on uplink channels (e.g., PUSCH, PUCCH). For example, the UE may be configured with a list of up to M TCI-state settings (i.e., DL TCIs) in the upper-layer parameter PDSCH-Config to decode the PDSCH. As another example, the UE may be configured with a list of up to 128 TCI-state settings in PDSCH-Config to provide i) DMRS for PDSCH and DMRS for PDDCCH, RS for QCL for CSI-RS, and ii) a reference for determining UL Tx spatial filters for dynamic grant and configured-grant based PUSCH and PUCCH resources. As yet another example, the UE may be configured with a list of up to 64 TCI-UL-State settings (i.e., UL TCI) in the upper-layer parameter BWP-UplinkDedicated.

[0334] Furthermore, multiple UEs may be composed of multiple UE groups, and each UE group may consist of one or more UEs. In this case, the configuration information may include information about the UE group (or information about the UE group to which it belongs).

[0335] The UE receives control information from the network (S2102).

[0336] Here, the control information may correspond to the beam instruction (or TCI status instruction) described above, or it may be control information that includes the beam instruction (or TCI status instruction) described above. For the sake of explanation, it will be collectively referred to as control information below.

[0337] The control information can specify one or more TCI states (i.e., beams) to be applied to one or more UEs (or one or more groups of UEs) within the TCI state list set by the configuration information described above (from among multiple TCI states). The control information can also specify the downlink transmissions (e.g., PDSCH, PDCCH, etc.) and / or uplink transmissions (e.g., PUSCH, PUCCH, etc.) to which the beam (i.e., TCI state) instruction applies.

[0338] Furthermore, the control information may include individual time offsets for each of the one or more TCI states. Here, the time offset may be indicated in units of symbols, slots, or absolute time.

[0339] For example, as illustrated in Figure 18, the control information may include information about one TCI state applied to one or more UE groups (or one or more UEs) and a time offset for the one TCI state applied to each of the one or more UE groups (or one or more UEs). As another example, as illustrated in Figure 19, the control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states. As yet another example, as illustrated in Figure 20, the multicast control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states applied to each of the one or more UE groups (or one or more UEs).

[0340] Here, the time offset may be calculated from the time when the multicast control information has been received in the time domain. Alternatively, the multicast control information may further include information regarding a reference time for the time offset, in which case the time offset may be calculated from the reference time in the time domain.

[0341] Furthermore, the multicast control information may include information about the time interval to which the one or more TCI states are applied, in which case the one or more TCI states may be applied in the time interval from the time offset. The time interval may also be indicated in units of symbols, slots, or absolute time, as with the time offset. Furthermore, as with the time offset in Figure 18 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one TCI state. Furthermore, as with the time offset in Figure 19 above, the time interval may also be indicated for each of the one or more TCI states. Furthermore, as with the time offset in Figure 20 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one or more TCI states.

[0342] The one or more TCI states described above may correspond to outputs derived by the network / base station from an artificial intelligence / machine learning (AI / ML) model. For example, the one or more TCI states may correspond to output 16 in Figure 12, and the output may be derived by a procedure as shown in Figure 14 or Figure 15. Here, the one or more TCI states may be derived from an artificial intelligence / machine learning (AI / ML) model using at least one of the following for the one or more UEs: {position, velocity, downlink channel measurement, SINR (signal to interference and noise ratio) per downlink reference signal, RSRP (reference signal received power) per downlink reference signal, and preference for the downlink reference signal}.

[0343] Furthermore, the multicast control information may be transmitted using various signaling schemes such as DCI / MAC CE / RRC.

[0344] For example, if DCI is used, the DCI may be transmitted via PDCCH. Alternatively, a DCI format defined for multicast control information may be used, and / or an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0345] As another example, if a MAC CE is used, the MAC CE may be transmitted via a PDSCH. The DCI scheduling the PDSCH may be monitored / received in a common search space, and an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0346] The UE can send an uplink transmission to the network (e.g., PUSCH, PUCCH, etc.) or receive a downlink transmission from the network (e.g., PDSCH, PDCCH, etc.) based on one or more TCI states (S2103).

[0347] Here, transmitting an uplink transmission or receiving a downlink transmission based on one or more TCI states may have the following meanings. For example, in the case of an uplink transmission, the UE can determine the uplink transmission spatial filter (UL TX spatial filter) based on one or more TCI states (for example, based on the RS set to qcl-Type set to "typeD" in TCI-state or the RS in TCI-UL-State) and transmit the uplink transmission. Also, in the case of a downlink transmission, for receiving a downlink transmission, the UE can assume that the DMRS of the downlink transmission is QCL'd with the RS set to qcl-Type set to "typeD" in one or more TCI states.

[0348] If the multicast control information includes a separate time offset for each of the one or more TCI states, the UE can send an uplink transmission or receive a downlink transmission based on the time of the one or more TCI states determined by the time offset.

[0349] If the multicast control information includes information about a time interval to which the one or more TCI states apply, the UE may transmit an uplink transmission or receive a downlink transmission based on the one or more TCI states in the time interval from the time offset. Alternatively, if the multicast control information does not include information about a time interval to which the one or more TCI states apply, the UE may transmit an uplink transmission or receive a downlink transmission based on the one or more TCI states until other multicast control information indicates other TCI states.

[0350] Figure 22 illustrates the operation of a UE (User Interface) for a wireless signal transmission and reception method according to one embodiment of the present disclosure.

[0351] Referring to Figure 22, which illustrates the operation of a UE based on the proposed methods (e.g., one of the proposed methods or a combination of the proposed methods). The illustration in Figure 22 is for illustrative purposes only and does not limit the scope of this disclosure. Some steps illustrated in Figure 22 may be omitted depending on the circumstances and / or settings. Also, in Figure 22, the UE is only one example and may be embodied by the device illustrated in Figure 24. For example, the processor 102 / 202 in Figure 24 can be controlled to send and receive channels / signals / data / information etc. using transceivers 106 / 206, and can be controlled to store the transmitted or received channels / signals / data / information etc. in memory 104 / 204.

[0352] Furthermore, the operation in Figure 22 may be processed by one or more processors 102,202 in Figure 24, and the operation in Figure 22 may be stored in memory (e.g., one or more memories 104,204 in Figure 24) in the form of instruction words / programs (e.g., instruction, executable code) to drive at least one processor (e.g., 102,202) in Figure 24.

[0353] The UE receives configuration information for multiple TCI states from the base station (S2201).

[0354] The aforementioned configuration information may include configuration information related to the setting of the TCI state (i.e., beam) as described in the proposed methods described above (for example, one of the proposed methods or a combination of the proposed methods).

[0355] More specifically, the configuration information for the multiple TCI states may include information for joint TCI and / or separate DL / UL TCI configurations. For example, the configuration information may include a list of TCI states that provide a reference signal for QCL for DMRS / downlink signals (e.g., CSI-RS) on downlink channels (e.g., PDSCH, PDCCH) and / or a reference for determining the uplink transmit spatial filter for DMRS / uplink signals (e.g., SRS) on uplink channels (e.g., PUSCH, PUCCH). For example, a UE may be configured with a list of up to M TCI-state configurations (i.e., DL TCIs) in the upper-layer parameter PDSCH-Config to decode a PDSCH. As another example, the UE may be configured with a list of up to 128 TCI-state settings in PDSCH-Config to provide i) DMRS for PDSCH and DMRS for PDDCCH, RS for QCL for CSI-RS, and ii) a reference for determining UL Tx spatial filters for dynamic grant and configured-grant based PUSCH and PUCCH resources. As yet another example, the UE may be configured with a list of up to 64 TCI-UL-State settings (i.e., UL TCI) in the upper-layer parameter BWP-UplinkDedicated.

[0356] Furthermore, multiple UEs may be composed of multiple UE groups, and each UE group may consist of one or more UEs. In this case, although not shown in Figure 22, a UE can receive configuration information from the base station that includes information about the UE group (or information about the UE group to which it belongs).

[0357] The UE receives control information from the base station (S2202).

[0358] Here, the control information may correspond to the beam instruction (or TCI status instruction) described above, or it may be control information that includes the beam instruction (or TCI status instruction) described above. For the sake of explanation, it will be collectively referred to as control information below.

[0359] The control information can specify one or more TCI states (i.e., beams) to be applied to one or more UEs (or one or more groups of UEs) within the TCI state list set by the configuration information described above (from among multiple TCI states). The control information can also specify the downlink transmissions (e.g., PDSCH, PDCCH, etc.) and / or uplink transmissions (e.g., PUSCH, PUCCH, etc.) to which the beam (i.e., TCI state) instruction applies.

[0360] Furthermore, the control information may include individual time offsets for each of the one or more TCI states. Here, the time offset may be indicated in units of symbols, slots, or absolute time.

[0361] For example, as illustrated in Figure 18, the control information may include information about one TCI state applied to one or more UE groups (or one or more UEs) and a time offset for the one TCI state applied to each of the one or more UE groups (or one or more UEs). As another example, as illustrated in Figure 19, the control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states. As yet another example, as illustrated in Figure 20, the multicast control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states applied to each of the one or more UE groups (or one or more UEs).

[0362] Here, the time offset may be calculated from the time when the multicast control information has been received in the time domain. Alternatively, the multicast control information may further include information regarding a reference time for the time offset, in which case the time offset may be calculated from the reference time in the time domain.

[0363] Furthermore, the multicast control information may include information about the time interval to which the one or more TCI states are applied, in which case the one or more TCI states may be applied in the time interval from the time offset. The time interval may also be indicated in units of symbols, slots, or absolute time, as with the time offset. Furthermore, as with the time offset in Figure 18 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one TCI state. Furthermore, as with the time offset in Figure 19 above, the time interval may also be indicated for each of the one or more TCI states. Furthermore, as with the time offset in Figure 20 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one or more TCI states.

[0364] The one or more TCI states described above may correspond to outputs derived by the network / base station from an artificial intelligence / machine learning (AI / ML) model. For example, the one or more TCI states described above may correspond to output 16 in Figure 12, and the output may be derived by a procedure as shown in Figure 14 or Figure 15. Here, the one or more TCI states described above may be derived from an artificial intelligence / machine learning (AI / ML) model using at least one of the following for the one or more UEs: {position, velocity, downlink channel measurement, SINR (signal to interference and noise ratio) per downlink reference signal, RSRP (reference signal received power) per downlink reference signal, and preference for the downlink reference signal}.

[0365] Furthermore, the multicast control information may be transmitted using various signaling schemes such as DCI / MAC CE / RRC.

[0366] For example, if DCI is used, the DCI may be transmitted via PDCCH. Alternatively, a DCI format defined for multicast control information may be used, and / or an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0367] As another example, if a MAC CE is used, the MAC CE may be transmitted via a PDSCH. The DCI scheduling the PDSCH may be monitored / received in a common search space, and an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0368] The UE can send uplink transmissions to the base station (e.g., PUSCH, PUCCH, etc.) or receive downlink transmissions from the base station (e.g., PDSCH, PDCCH, etc.) based on one or more TCI states (S2203).

[0369] Here, transmitting an uplink transmission or receiving a downlink transmission based on one or more TCI states may have the following meanings. For example, in the case of an uplink transmission, the UE can determine an uplink transmission spatial filter (UL TX spatial filter) based on one or more TCI states (for example, based on the RS set to qcl-Type set to "typeD" in TCI-state or the RS in TCI-UL-State) and transmit the uplink transmission. Also, in the case of a downlink transmission, for receiving a downlink transmission, the UE can assume that the DMRS of the downlink transmission is QCL'd with the RS set to qcl-Type set to "typeD" in one or more TCI states.

[0370] If the multicast control information includes a separate time offset for each of the one or more TCI states, the UE can send an uplink transmission or receive a downlink transmission based on the time of the one or more TCI states determined by the time offset.

[0371] If the multicast control information includes information about a time interval to which the one or more TCI states apply, the UE may transmit an uplink transmission or receive a downlink transmission based on the one or more TCI states in the time interval from the time offset. Alternatively, if the multicast control information does not include information about a time interval to which the one or more TCI states apply, the UE may transmit an uplink transmission or receive a downlink transmission based on the one or more TCI states until other multicast control information indicates other TCI states.

[0372] Figure 23 illustrates the operation of a base station for a wireless signal transmission and reception method according to one embodiment of the present disclosure.

[0373] Referring to Figure 23, which illustrates the operation of a base station based on the previously proposed methods (e.g., one of the proposed methods or a combination of the proposed methods). The illustration in Figure 23 is for illustrative purposes only and does not limit the scope of this disclosure. Some steps illustrated in Figure 23 may be omitted depending on the circumstances and / or settings. Also, the base station in Figure 23 is only one example and may be embodied by the device illustrated in Figure 24. For example, the processor 102 / 202 in Figure 22 can be controlled to send and receive channels / signals / data / information etc. using transceivers 106 / 206, and can be controlled to store the transmitted or received channels / signals / data / information etc. in memory 104 / 204.

[0374] Furthermore, the operation in Figure 23 may be processed by one or more processors 102,202 in Figure 24, and the operation in Figure 23 may be stored in memory (e.g., one or more memories 104,204 in Figure 24) in the form of instruction words / programs (e.g., instruction, executable code) to drive at least one processor (e.g., 102,202) in Figure 24.

[0375] The base station transmits configuration information for multiple TCI states to the UE (S2301).

[0376] The aforementioned configuration information may include configuration information related to the setting of the TCI state (i.e., beam) as described in the proposed methods described above (for example, one of the proposed methods or a combination of the proposed methods).

[0377] More specifically, the configuration information for the multiple TCI states may include information for joint TCI and / or separate DL / UL TCI configurations. For example, the configuration information may include a list of TCI states that provide a reference signal for QCL for DMRS / downlink signals (e.g., CSI-RS) on downlink channels (e.g., PDSCH, PDCCH) and / or a reference for determining the uplink transmit spatial filter for DMRS / uplink signals (e.g., SRS) on uplink channels (e.g., PUSCH, PUCCH). For example, a UE may be configured with a list of up to M TCI-state configurations (i.e., DL TCIs) in the upper-layer parameter PDSCH-Config to decode a PDSCH. As another example, the UE may be configured with a list of up to 128 TCI-state settings in PDSCH-Config to provide i) DMRS for PDSCH and DMRS for PDDCCH, RS for QCL for CSI-RS, and ii) a reference for determining UL Tx spatial filters for dynamic grant and configured-grant based PUSCH and PUCCH resources. As yet another example, the UE may be configured with a list of up to 64 TCI-UL-State settings (i.e., UL TCI) in the upper-layer parameter BWP-UplinkDedicated.

[0378] Furthermore, multiple UEs may be composed of multiple UE groups, and each UE group may consist of one or more UEs. In this case, although not shown in Figure 23, the base station can transmit configuration information to the UEs, including information about the UE group (or information about the UE group to which it belongs).

[0379] The base station transmits control information to the UE (S2302).

[0380] Here, the base station can transmit control information to multiple UEs, but for the sake of explanation, the operation of the base station in Figure 23 will be described focusing on a single UE.

[0381] Here, the control information may correspond to the beam instruction (or TCI status instruction) described above, or it may be control information that includes the beam instruction (or TCI status instruction) described above. For the sake of explanation, it will be collectively referred to as control information below.

[0382] The control information can specify one or more TCI states (i.e., beams) to be applied to one or more UEs (or one or more groups of UEs) within the TCI state list set by the configuration information described above (from among multiple TCI states). The control information can also specify the downlink transmissions (e.g., PDSCH, PDCCH, etc.) and / or uplink transmissions (e.g., PUSCH, PUCCH, etc.) to which the beam (i.e., TCI state) specification applies.

[0383] Furthermore, the control information may include individual time offsets for each of the one or more TCI states. Here, the time offset may be indicated in units of symbols, slots, or absolute time.

[0384] For example, as illustrated in Figure 18, the control information may include information about one TCI state applied to one or more UE groups (or one or more UEs) and a time offset for the one TCI state applied to each of the one or more UE groups (or one or more UEs). Another example is as illustrated in Figure 19, the control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states. Yet another example is as illustrated in Figure 20, the multicast control information may include information about one or more TCI states applied to one or more UE groups (or one or more UEs) and a time offset for each of the one or more TCI states applied to each of the one or more UE groups (or one or more UEs).

[0385] Here, the time offset may be calculated from the time when the multicast control information has been received in the time domain. Alternatively, the multicast control information may further include information regarding a reference time for the time offset, in which case the time offset may be calculated from the reference time in the time domain.

[0386] Furthermore, the multicast control information may include information about the time interval to which the one or more TCI states are applied, in which case the one or more TCI states may be applied in the time interval from the time offset. The time interval may also be indicated in units of symbols, slots, or absolute time, as with the time offset. Furthermore, as with the time offset in Figure 18 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one TCI state. Furthermore, as with the time offset in Figure 19 above, the time interval may also be indicated for each of the one or more TCI states. Furthermore, as with the time offset in Figure 20 above, the time interval may also be indicated for each of the one or more UE groups, corresponding to one or more TCI states.

[0387] The one or more TCI states described above may correspond to outputs derived by the network / base station from an artificial intelligence / machine learning (AI / ML) model. For example, the one or more TCI states may correspond to output 16 in Figure 12, and the output may be derived by a procedure as shown in Figure 14 or Figure 15. Here, the one or more TCI states may be derived from an artificial intelligence / machine learning (AI / ML) model using at least one of the following for the one or more UEs: {position, velocity, downlink channel measurement, SINR (signal to interference and noise ratio) per downlink reference signal, RSRP (reference signal received power) per downlink reference signal, and preference for the downlink reference signal}.

[0388] Furthermore, the multicast control information may be transmitted using various signaling schemes such as DCI / MAC CE / RRC.

[0389] For example, if DCI is used, the DCI may be transmitted via PDCCH. Alternatively, a DCI format defined for multicast control information may be used, and / or an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0390] As another example, if a MAC CE is used, the MAC CE may be transmitted via a PDSCH. The DCI scheduling the PDSCH may be monitored / received in a common search space, and an RNTI defined for multicast control information may be used for CRC scrambling of the DCI.

[0391] The base station may receive uplink transmissions (e.g., PUSCH, PUCCH, etc.) from the UE or transmit downlink transmissions (e.g., PDSCH, PDCCH, etc.) to the UE based on one or more TCI states (S2303).

[0392] Here, receiving an uplink transmission or transmitting a downlink transmission based on one or more TCI states may have the following meanings. For example, in the case of an uplink transmission, the UE can determine an uplink transmission spatial filter (UL TX spatial filter) based on one or more TCI states (for example, based on the RS set to qcl-Type set to "typeD" in TCI-state or the RS in TCI-UL-State) and transmit the uplink transmission. Also, in the case of a downlink transmission, for receiving the downlink transmission, the UE can assume that the DMRS of the downlink transmission is QCL'd with the RS set to qcl-Type set to "typeD" in one or more TCI states.

[0393] If the multicast control information includes a separate time offset for each of the one or more TCI states, the base station can receive uplink transmissions or transmit downlink transmissions based on the one or more TCI states from the time of the time offset.

[0394] If the multicast control information includes information about a time interval to which the one or more TCI states apply, the base station can receive uplink transmissions or transmit downlink transmissions based on the one or more TCI states in the time interval from the time offset. Alternatively, if the multicast control information does not include information about a time interval to which the one or more TCI states apply, the base station can receive uplink transmissions or transmit downlink transmissions based on the one or more TCI states until other multicast control information indicates other TCI states.

[0395] Apparatus to which this disclosure applies in general

[0396] Figure 24 is a block diagram illustrating an example of a wireless communication device according to one embodiment of the present disclosure.

[0397] Referring to Figure 24, the first wireless device 100 and the second wireless device 200 can transmit and receive wireless signals using various wireless connection technologies (e.g., LTE, NR).

[0398] The first wireless device 100 includes one or more processors 102 and one or more memories 104, and may further include one or more transceivers 106 and / or one or more antennas 108. The processor 102 may control the memory 104 and / or the transceiver 106 and be configured to embody the descriptions, functions, procedures, suggestions, methods and / or operation sequence diagrams disclosed herein. For example, the processor 102 may process information in the memory 104 to generate first information / signals and then transmit a wireless signal containing the first information / signals from the transceiver 106. Alternatively, the processor 102 may receive a wireless signal containing second information / signals from the transceiver 106 and then store information obtained from signal processing of the second information / signals in the memory 104. The memory 104 may be linked to the processor 102 and can store various information related to the operation of the processor 102. For example, memory 104 may store software code that includes instructions for performing some or all of the processes controlled by processor 102, or for executing the descriptions, functions, procedures, suggestions, methods and / or operation sequence diagrams disclosed herein. Here, processor 102 and memory 104 may be part of a communication modem / circuit / chip designed to embody wireless communication technology (e.g., LTE, NR). Transceiver 106 may be coupled with processor 102 and can transmit and / or receive radio signals via one or more antennas 108. Transceiver 106 may include a transmitter and / or receiver. Transceiver 106 may be replaced with an RF (Radio Frequency) unit. In the present invention, wireless equipment may mean a communication modem / circuit / chip.

[0399] The second wireless device 200 includes one or more processors 202, one or more memories 204, and may further include one or more transceivers 206 and / or one or more antennas 208. The processor 202 may control the memory 204 and / or the transceiver 206 and be configured to embody the descriptions, functions, procedures, suggestions, methods and / or operation sequence diagrams disclosed herein. For example, the processor 202 may process information in the memory 204 to generate third information / signals and then transmit a wireless signal containing the third information / signals from the transceiver 206. Alternatively, the processor 202 may receive a wireless signal containing fourth information / signals from the transceiver 206 and then store information obtained from signal processing of the fourth information / signals in the memory 204. The memory 204 may be linked to the processor 202 and can store various information related to the operation of the processor 202. For example, memory 204 may store software code that includes instructions for performing some or all of the processes controlled by processor 202, or for executing the descriptions, functions, procedures, suggestions, methods and / or operation sequence diagrams disclosed herein. Here, processor 202 and memory 204 may be part of a communication modem / circuit / chip designed to embody wireless communication technology (e.g., LTE, NR). Transceiver 206 may be coupled with processor 202 and can transmit and / or receive radio signals via one or more antennas 208. Transceiver 206 may include a transmitter and / or receiver. Transceiver 206 may be replaced with an RF unit. In the present invention, wireless equipment may mean a communication modem / circuit / chip.

[0400] The hardware elements of the wireless devices 100,200 will be described in more detail below. However, one or more protocol layers may be embodied by one or more processors 102,202. For example, one or more processors 102,202 may embodied one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors 102,202 may generate one or more PDUs (Protocol Data Units) and / or one or more SDUs (Service Data Units) by means of the descriptions, functions, procedures, proposals, methods and / or operation sequence diagrams disclosed in this disclosure. One or more processors 102,202 may generate messages, control information, data or information by means of the descriptions, functions, procedures, proposals, methods and / or operation sequence diagrams disclosed in this disclosure. One or more processors 102,202 can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data, or information by means of the functions, procedures, suggestions, and / or methods disclosed in this disclosure and provide them to one or more transceivers 106,206. One or more processors 102,202 can receive signals (e.g., baseband signals) from one or more transceivers 106,206 and can acquire PDUs, SDUs, messages, control information, data, or information by means of the descriptions, functions, procedures, suggestions, methods, and / or operation sequence diagrams disclosed in this disclosure.

[0401] One or more processors 102,202 may be referred to as controllers, microcontrollers, microprocessors, or microcomputers. One or more processors 102,202 may be embodied by hardware, firmware, software, or a combination thereof. For example, one or more ASICs (Application Specific Integrated Circuits), one or more DSPs (Digital Signal Processors), one or more DSPDs (Digital Signal Processing Devices), one or more PLDs (Programmable Logic Devices), or one or more FPGAs (Field Programmable Gate Arrays) may be included in one or more processors 102,202. The descriptions, functions, procedures, proposals, methods and / or operation sequence diagrams disclosed in this disclosure may be embodied using firmware or software, and the firmware or software may be embodied to include modules, procedures, functions, etc. Firmware or software configured to perform the descriptions, functions, procedures, suggestions, methods and / or sequence diagrams disclosed in this disclosure may be contained in one or more processors 102,202 or stored in one or more memories 104,204 and driven by one or more processors 102,202. The descriptions, functions, procedures, suggestions, methods and / or sequence diagrams disclosed in this disclosure may be embodied by firmware or software in the form of code, instructions and / or sets of instructions.

[0402] One or more memories 104,204 may be connected to one or more processors 102,202 and can store various forms of data, signals, messages, information, programs, code, instructions and / or commands. One or more memories 104,204 may consist of ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media and / or combinations thereof. One or more memories 104,204 may be located inside and / or outside of one or more processors 102,202. Furthermore, one or more memories 104,204 may be connected to one or more processors 102,202 by various technologies such as wired or wireless connections.

[0403] One or more transceivers 106,206 can transmit user data, control information, radio signals / channels, etc., as referred to in the methods and / or operation sequence diagrams of this disclosure, to one or more other devices. One or more transceivers 106,206 can receive user data, control information, radio signals / channels, etc., as referred to in the descriptions, functions, procedures, proposals, methods and / or operation sequence diagrams disclosed in this disclosure, from one or more other devices. For example, one or more transceivers 106,206 may be coupled with one or more processors 102,202 to transmit and receive radio signals. For example, one or more processors 102,202 can control one or more transceivers 106,206 to transmit user data, control information, or radio signals to one or more other devices. Also, one or more processors 102,202 can control one or more transceivers 106,206 to receive user data, control information, or radio signals from one or more other devices. Furthermore, one or more transceivers 106,206 may be connected to one or more antennas 108,208, and one or more transceivers 106,206 may be configured to transmit and receive user data, control information, radio signals / channels, etc., as referred to in the descriptions, functions, procedures, proposals, methods and / or operation sequence diagrams disclosed in this disclosure, via one or more antennas 108,208. In this disclosure, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers 106,206 may convert the received user data, control information, radio signals / channels, etc., from RF band signals to baseband signals for processing using one or more processors 102,202. One or more transceivers 106,206 may convert the user data, control information, radio signals / channels, etc., processed by one or more processors 102,202, from baseband signals to RF band signals. To this end, one or more transceivers 106,206 may include (analog) oscillators and / or filters.

[0404] The embodiments described above are combinations of the components and features of the present disclosure in a predetermined form. Each component or feature should be considered optional unless otherwise explicitly mentioned. Each component or feature may be implemented in a form that does not combine with other components or features. It is also possible to combine some components and / or features to constitute embodiments of the present disclosure. The order of operations described in embodiments of the present disclosure may be changed. Some components or features of one embodiment may be included in other embodiments, or replaced by corresponding components or features of other embodiments. It is clear that claims that do not have an explicit reference relationship in the claims may be combined to constitute embodiments, or may be included as new claims by amendment after filing.

[0405] It will be obvious to those skilled in the art that this disclosure can be embodied in other specific forms, provided that the essential features of this disclosure are not deviated from. Therefore, the above-mentioned detailed description should not be constrained in any way and should be considered illustrative. The scope of this disclosure should be determined by a reasonable interpretation of the attached claims, and any modifications within the equivalent scope of this disclosure are included within the scope of this disclosure.

[0406] The scope of this disclosure includes software or machine-executable instructions (e.g., operating systems, applications, firmware, programs, etc.) that cause an apparatus or computer to perform operations according to the methods of various embodiments, and non-transitory computer-readable medium on which such software or instructions are stored and executable on the apparatus or computer. Instructions available for programming a processing system that performs the features described in this disclosure may be stored on / in a storage medium or computer-readable storage medium, and the features described in this disclosure may be embodied using a computer program product including such storage medium. The storage medium may include, but is not limited to, high-speed random-access memory such as DRAM, SRAM, DDR RAM, or other random-access solid-state memory devices, and may include non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Memory optionally includes one or more storage devices located remotely from the processor. Memory, or alternatively, non-volatile memory devices within memory, includes non-transitory computer-readable storage medium. The features described in this disclosure may be stored on any one of the machine-readable media and integrated into software and / or firmware that can control the hardware of the processing system and cause the processing system to interact with other mechanisms that utilize the results relating to the embodiments of this disclosure. Such software or firmware may include, but is not limited to, application code, device drivers, operating systems and execution environments / containers.

[0407] Here, the wireless communication technologies embodied in the wireless devices 100 and 200 of this disclosure may include, in addition to LTE, NR, and 6G, Narrowband Internet of Things (NB-IoT) for low-power communication. In this case, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology and may be embodied by standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the names mentioned above. Additionally or alternatively, the wireless communication technologies embodied in the wireless devices 100 and 200 of this disclosure may communicate based on LTE-M technology. In this case, for example, LTE-M technology may be an example of LPWAN technology and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology may be embodied by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the names mentioned above. Additionally or alternatively, wireless communication technologies embodied in the wireless devices 100,200 of this disclosure may include at least one of ZigBee®, Bluetooth®, and Low Power Wide Area Network (LPWAN) with consideration for low-power communication, and is not limited to the names mentioned above. As an example, ZigBee technology can generate personal area networks (PANs) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and may be called by various names. [Industrial applicability]

[0408] Although the method proposed in this disclosure has been described primarily in terms of its application to 3GPP LTE / LTE-A and 5G systems, it is applicable to a variety of other wireless communication systems as well.

Claims

1. The user equipment (UE) receives setting information for multiple transmission configuration indication (TCI) states from a base station, The UE receives control information from the base station, and the control information is: Of the plurality of TCI states, one or more TCI states applied to one or more UEs, A step including a separate time offset for each of the one or more TCI states, The step includes the UE transmitting an uplink transmission or receiving a downlink transmission based on one or more TCI states from a time according to the time offset, The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is calculated from the reference time in the time domain by a method.

2. The control information is, Information regarding a single TCI status applicable to multiple UE groups, The method according to claim 1, comprising a time offset for each of the plurality of UE groups relative to one TCI state.

3. The control information is, Information regarding the TCI status applicable to a single UE group or a single UE, The method according to claim 1, comprising a time offset for each of the TCI states.

4. The method according to claim 1, wherein the time offset is calculated in the time domain from the time of completion of receiving the control information.

5. The method according to claim 1, wherein the time offset is indicated in symbol units, slot units, or absolute time units.

6. The control information includes information about the time interval to which the one or more TCI states are applied. The method according to claim 1, wherein one or more TCI states are applied between the time interval from the time according to the time offset.

7. The method according to claim 1, wherein the one or more TCI states are applied until another TCI state is indicated by other control information.

8. At least one transmitting / receiving unit for transmitting and receiving wireless signals, The system comprises at least one processor for controlling the at least one transmitting / receiving unit, The aforementioned at least one processor is The base station receives configuration information for multiple TCI (transmission configuration indication) states. The control information is received from the base station, and the control information is, Of the plurality of TCI states, one or more TCI states applied to one or more UEs, Includes a separate time offset for each of the one or more TCI states, The system is configured to transmit an uplink transmission or receive a downlink transmission based on one or more TCI states from a time according to the aforementioned time offset. The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is UE (user equipment) calculated from the reference time in the time domain.

9. At least one non-temporary computer-readable medium for storing at least one instruction, The at least one instruction that can be executed by at least one processor is: The base station receives configuration information for multiple TCI (transmission configuration indication) states. The control information is received from the base station, and the control information is, Of the plurality of TCI states, one or more TCI states applied to one or more UEs, Includes a separate time offset for each of the one or more TCI states, The user equipment (UE) is controlled to transmit an uplink transmission or receive a downlink transmission based on one or more TCI states from a time according to the aforementioned time offset. The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is a computer-readable medium calculated from the reference time in the time domain.

10. A processing device configured to control UE (user equipment) in a wireless communication system, At least one processor, Based on being operably coupled to the at least one processor and being executed by the at least one processor, Receiving configuration information for multiple TCI (transmission configuration indication) states from the base station, Receiving control information from the base station, wherein the control information is Of the plurality of TCI states, one or more TCI states applied to one or more UEs, This includes a separate time offset for each of the one or more TCI states, The computer includes at least one computer memory that stores instructions for performing an operation which includes transmitting an uplink transmission or receiving a downlink transmission based on one or more TCI states from a time according to the time offset, The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is calculated from the reference time in the time domain by a processing device.

11. The steps of a base station transmitting setting information for a plurality of TCI (transmission configuration indication) states to a UE (user equipment), In the step where the base station transmits control information to the UE, the control information is: Of the plurality of TCI states, one or more TCI states applied to one or more UEs, A step including a separate time offset for each of the one or more TCI states, The base station includes the step of receiving an uplink transmission or transmitting a downlink transmission based on one or more TCI states from a time according to the time offset, The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is calculated from the reference time in the time domain by a method.

12. At least one transmitting / receiving unit for transmitting and receiving wireless signals, The system comprises at least one processor for controlling the at least one transmitting / receiving unit, The aforementioned at least one processor is It sends configuration information for multiple TCI (transmission configuration indication) states to the UE (user equipment). Control information is transmitted to the UE, and the control information is, Of the plurality of TCI states, one or more TCI states applied to one or more UEs, Includes a separate time offset for each of the one or more TCI states, The system is configured to receive an uplink transmission or transmit a downlink transmission based on one or more TCI states from a time according to the aforementioned time offset. The control information further includes information regarding a reference time for the time offset, The aforementioned time offset is calculated from the reference time in the time domain, and is a base station.

Images