Method and apparatus for performing scheduling in wireless communication system

Abstract

The present disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate than a 4G communication system such as LTE. A method performed by a terminal in a wireless communication system, according to the present disclosure, may comprise the steps of: receiving, from a base station, RRC signaling comprising candidate port subset search configuration information and report condition configuration information; transmitting, to the base station, information about at least one first port subset selected on the basis of the candidate port subset search configuration information and the report condition configuration information; receiving, from the base station, information about a port subset determined for reception of a PDSCH; and receiving, from the base station, the PDSCH by using the determined port subset.

Description

Method and apparatus for performing scheduling in a wireless communication system

[0001] The present disclosure relates to a terminal and a base station in a wireless communication system. Specifically, the present disclosure relates to a method and apparatus for performing scheduling in a wireless communication system.

[0002] Looking back at the evolution of wireless communication through successive generations, technologies have been developed primarily for human-oriented services, such as voice, multimedia, and data. Following the commercialization of 5G (5th Generation) communication systems, connected devices, which have been increasing explosively, are expected to be connected to communication networks. Examples of networked objects include vehicles, robots, drones, home appliances, displays, smart sensors installed in various infrastructures, construction machinery, and factory equipment. Mobile devices are expected to evolve into various form factors, such as augmented reality glasses, virtual reality headsets, and holographic devices. In the 6G (6th Generation) era, efforts are underway to develop improved 6G communication systems to connect hundreds of billions of devices and objects to provide diverse services. For this reason, 6G communication systems are being referred to as "beyond 5G" systems.

[0003] In the 6G communication system predicted to be realized around 2030, the maximum transmission speed is tera (i.e., 1,000 gigabit) bps (bit per second), and the wireless latency is 100 microseconds (μsec). In other words, compared to the 5G communication system, the transmission speed in the 6G communication system is 50 times faster, and the wireless latency is reduced to one-tenth.

[0004] To achieve such high data transmission speeds and ultra-low latency, 6G communication systems are being considered for implementation in the terahertz (THz) band (e.g., the 95 gigahertz (GHz) to 3 terahertz (3THz) band). Due to more severe path loss and atmospheric absorption phenomena compared to the millimeter wave (mmWave) band introduced in 5G, the importance of technologies capable of guaranteeing signal reach, or coverage, is expected to increase in the terahertz band. As key technologies to ensure coverage, new waveforms, beamforming, and multi-antenna transmission technologies such as massive Multiple-Input and Multiple-Output (MIMO), Full Dimensional MIMO (FD-MIMO), array antennas, and large-scale antennas, which are superior in terms of coverage compared to RF (Radio Frequency) devices, antennas, and OFDM (Orthogonal Frequency Division Multiplexing), must be developed. In addition, new technologies such as metamaterial-based lenses and antennas, high-dimensional spatial multiplexing technology using Orbital Angular Momentum (OAM), and Reconfigurable Intelligent Surface (RIS) are being discussed to improve the coverage of terahertz band signals.

[0005] In addition, to improve frequency efficiency and system network, development is underway in 6G communication systems for full duplex technology, in which uplink and downlink simultaneously utilize the same frequency resources at the same time; network technology that integrates satellites and HAPS (High-Altitude Platform Stations); network structure innovation technology that supports mobile base stations and enables network operation optimization and automation; dynamic spectrum sharing technology through collision avoidance based on spectrum usage prediction; AI-based communication technology that utilizes AI (Artificial Intelligence) from the design stage and internalizes end-to-end AI support functions to realize system optimization; and next-generation distributed computing technology that realizes services of complexity exceeding the limits of terminal computing capabilities by utilizing ultra-high performance communication and computing resources (Mobile Edge Computing (MEC), cloud, etc.). In addition, attempts are continuing to further strengthen connectivity between devices, further optimize networks, promote the softwareization of network entities, and increase the openness of wireless communication through the design of new protocols to be used in 6G communication systems, the implementation of hardware-based security environments, the development of mechanisms for the safe utilization of data, and the development of technologies regarding privacy maintenance methods.

[0006] Due to the research and development of such 6G communication systems, it is expected that a new dimension of hyper-connected experience will become possible through the hyper-connectivity of 6G communication systems, which encompasses not only connections between objects but also connections between people and objects. Specifically, it is projected that 6G communication systems will enable the provision of services such as truly immersive extended reality (XR), high-fidelity mobile holograms, and digital replicas. Furthermore, services such as remote surgery, industrial automation, and emergency response, which are provided through 6G communication systems with enhanced security and reliability, will be applied in various fields including industry, healthcare, automotive, and home appliances.

[0007] Based on the discussion above, the present disclosure aims to provide a method and apparatus for selecting a transmitting port subset based on channel state information reporting in a wireless communication system.

[0008] The technical problems to be solved in this document are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which this invention belongs from the description below.

[0009] A method performed by a base station in a wireless communication system according to one embodiment of the present disclosure may include: transmitting setting information to a terminal (user equipment) for acquiring channel feature information and channel state feature information; acquiring the channel feature information based on the channel state information of the terminal acquired based on the setting information; acquiring the channel state feature information based on the acquired channel feature information and the channel state information of the terminal at a predetermined time point; and performing scheduling based on the channel feature information, the channel state feature information, and the channel state information.

[0010] A method performed by a terminal (user equipment, UE) in a line communication system according to one embodiment of the present disclosure may include: receiving configuration information for obtaining channel feature information and channel state feature information from a base station; transmitting to the base station the channel feature information associated with a downlink channel environment based on the channel state information of the terminal obtained based on the configuration information and a downlink reference signal received from the base station; transmitting to the base station the channel state feature information based on the obtained channel feature information and the channel state information of the terminal at a predetermined point in time; and receiving from the base station information regarding scheduling performed based on the channel feature variable, the channel state feature variable, and the channel state information.

[0011] In a wireless communication system according to one embodiment of the present disclosure, a base station may include a transceiver and at least one processor connected to the transceiver. The at least one processor may be configured such that the base station transmits configuration information to a user equipment to obtain channel feature information and channel state feature information, obtains the channel feature information based on the channel state information of the user equipment obtained based on the configuration information, obtains the channel state feature information based on the obtained channel feature information and the channel state information of the user equipment at a predetermined point in time, and performs scheduling based on the channel feature variable, the channel state feature variable, and the channel state information.

[0012] In a wireless communication system according to one embodiment of the present disclosure, a terminal (user equipment) may include a transceiver and at least one processor connected to the transceiver. The at least one processor may be configured such that the terminal receives configuration information from a base station for acquiring channel feature information and channel state feature information, transmits to the base station the channel state information of the terminal acquired based on the configuration information and the channel feature information associated with the downlink channel environment based on a downlink reference signal received from the base station, transmits to the base station the channel state feature information based on the acquired channel feature information and the channel state information of the terminal at a predetermined point in time, and receives from the base station information regarding scheduling performed based on the channel feature variable, the channel state feature variable, and the channel state information.

[0013] The present disclosure provides an apparatus and method capable of effectively providing services in a wireless communication system.

[0014] The effects obtainable in the present disclosure are not limited to those mentioned in the various embodiments, and other unmentioned effects will be clearly understood by those skilled in the art to which the present disclosure pertains from the description below.

[0015] FIG. 1 illustrates a wireless environment network in a wireless communication system according to one embodiment of the present disclosure.

[0016] FIG. 2 illustrates the functional configuration of a base station in a wireless communication system according to one embodiment of the present disclosure.

[0017] FIG. 3 illustrates the functional configuration of a terminal in a wireless communication system according to one embodiment of the present disclosure.

[0018] FIG. 4 illustrates an example of a wireless resource area in a wireless communication system according to one embodiment of the present disclosure.

[0019] FIG. 5 illustrates a schematic diagram of an operation for performing scheduling based on channel measurement according to one embodiment of the present disclosure.

[0020] FIG. 6 illustrates a flowchart of an operation for providing cell synchronization and cell system information according to one embodiment of the present disclosure.

[0021] FIG. 7 illustrates a flowchart of an operation for performing channel measurement according to one embodiment of the present disclosure.

[0022] FIG. 8 illustrates a flowchart of an operation for performing scheduling according to one embodiment of the present disclosure.

[0023] FIG. 9 illustrates a schematic diagram of an operation for performing scheduling based on channel feature information and channel state feature information according to one embodiment of the present disclosure.

[0024] FIG. 10 illustrates a schematic diagram of performing scheduling in a wireless communication system according to one embodiment of the present disclosure.

[0025] FIG. 11 illustrates a schematic diagram of a base station transmitting setting information to a terminal according to one embodiment of the present disclosure.

[0026] FIG. 12 illustrates a flowchart of an operation in which a base station transmits setting information to a terminal according to one embodiment of the present disclosure.

[0027] FIG. 13 illustrates a schematic diagram for obtaining channel feature information according to one embodiment of the present disclosure.

[0028] FIG. 14 illustrates a flowchart of an operation for acquiring channel feature information according to one embodiment of the present disclosure.

[0029] FIG. 15 illustrates a schematic diagram for obtaining channel state feature information according to one embodiment of the present disclosure.

[0030] FIG. 16 illustrates a flowchart of an operation for acquiring channel state feature information according to one embodiment of the present disclosure.

[0031] FIG. 17 illustrates a schematic diagram of performing scheduling according to one embodiment of the present disclosure.

[0032] FIG. 18 illustrates a flowchart of an operation for performing scheduling according to one embodiment of the present disclosure.

[0033] FIG. 19 illustrates a schematic diagram of the learning process of a neural network model for performing scheduling according to one embodiment of the present disclosure.

[0034] FIG. 20 illustrates an example of a neural network model for performing scheduling according to one embodiment of the present disclosure.

[0035] FIG. 21 illustrates a flowchart of operations performed by a base station in a wireless communication system according to one embodiment of the present disclosure.

[0036] FIG. 22 illustrates a flowchart of operations performed by a terminal in a wireless communication system according to one embodiment of the present disclosure.

[0037] Hereinafter, embodiments are described in detail with reference to the attached drawings so that those skilled in the art can easily implement the contents of the present disclosure. However, the disclosed embodiments may be implemented in various different forms and are not limited to the embodiments described herein. Furthermore, in order to clearly explain the present disclosure in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification have been given similar reference numerals.

[0038] The terms used in this disclosure are described in their current, general form considering the functions mentioned herein; however, they may refer to various other terms depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Accordingly, the terms used in this disclosure should not be interpreted solely by their names, but should be interpreted based on the meaning of the terms and the overall content of this disclosure.

[0039] Additionally, terms such as 'first', 'second', etc., may be used to describe various components, but the components are not limited by these terms. These terms are used for the purpose of distinguishing one component from another.

[0040] In the present disclosure, when a part is described as being "connected" to another part, this includes not only cases where they are "directly connected," but also cases where they are "electrically connected" or "operationally connected" with other elements interposed between them. Furthermore, when a part is described as "comprising" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0041] The terms used in this disclosure are used merely to describe specific embodiments and are not intended to limit the scope of other embodiments. A singular expression may include a plural expression unless the context clearly indicates otherwise. Terms used, including technical or scientific terms, may have the same meaning as generally understood by those skilled in the art described in this disclosure. Terms used in this disclosure that are defined in a general dictionary may be interpreted as having the same or similar meaning as they have in the context of the relevant technology, and are not to be interpreted in an ideal or overly formal sense unless explicitly defined in this disclosure. In some cases, even terms defined in this disclosure are not to be interpreted to exclude the embodiments of this disclosure.

[0042] In the various embodiments of the present disclosure described below, a hardware-based approach is described as an example. However, since the various embodiments of the present disclosure include techniques using both hardware and software, the various embodiments of the present disclosure do not exclude a software-based approach. Furthermore, terms referring to network entities, terms referring to device components, etc., are illustrative for the convenience of explanation. Accordingly, the present disclosure is not limited to the terms described below, and other terms having equivalent technical meanings may be used.

[0043] Additionally, the present disclosure describes various embodiments using terms defined in some communication standards (e.g., 3GPP (3rd generation partnership project), ETSI (European Telecommunication Standards Institute)), but this is merely illustrative. Various embodiments of the present disclosure can be easily modified and applied to other communication systems.

[0044] Additionally, in this disclosure, expressions such as "greater than" or "less than" may be used to determine whether a specific condition is satisfied or fulfilled; however, this is merely for the purpose of expressing an example and does not exclude descriptions such as "greater than" or "less than." Conditions described as "greater than" may be replaced with "greater than," conditions described as "less than" may be replaced with "less than," and conditions described as "greater than and less than" may be replaced with "greater than and less than."

[0045] Terms referring to signals, channels, control information, network entities, and device components used in the following description are examples provided for the convenience of explanation. Accordingly, the present disclosure is not limited to the terms described below, and other terms having equivalent technical meanings may be used.

[0046] Phrases such as "in one embodiment" appearing in various places in this disclosure do not necessarily refer to the same embodiment.

[0047] FIG. 1 illustrates a wireless environment network in a wireless communication system according to one embodiment of the present disclosure. FIG. 1 illustrates a base station (110), a first terminal (120), and a second terminal (130) as some of the nodes using a wireless channel in the wireless communication system. FIG. 1 illustrates only one base station, but other base stations identical or similar to the base station (110) may be additionally included.

[0048] A base station (110) is a network infrastructure that provides wireless access to terminals (120, 130). The base station (110) has coverage defined as a certain geographical area based on the distance at which it can transmit signals. In addition to being a base station, the base station (110) may be referred to as an 'access point (AP)', 'eNodeB (eNB)', '5G node (5th generation node)', 'next generation nodeB (gNB)', 'wireless point', 'transmission / reception point (TRP)', or other terms having an equivalent technical meaning.

[0049] Each of the first terminal (120) and the second terminal (130) is a device used by a user and performs communication with the base station (110) via a wireless channel. In some cases, at least one of the first terminal (120) and the second terminal (130) may be operated without user involvement. That is, at least one of the first terminal (120) and the second terminal (130) is a device that performs machine type communication (MTC) and may not be carried by the user. Each of the first terminal (120) and the second terminal (130) may be referred to as 'user equipment (UE)', 'mobile station', 'subscriber station', 'remote terminal', 'wireless terminal', or 'user device', or other terms having an equivalent technical meaning, in addition to 'terminal'.

[0050] The base station (110), the first terminal (120), and the second terminal (130) can transmit and receive wireless signals in the millimeter wave (mmWave) band (e.g., 28 GHz, 30 GHz, 38 GHz, 60 GHz). At this time, to improve channel gain, the base station (110), the first terminal (120), and the second terminal (130) can perform beamforming.

[0051] Beamforming may include transmitting beamforming and receiving beamforming. That is, the base station (110), the first terminal (120), and the second terminal (130) may provide directivity to the transmitted signal or the received signal. To this end, the base station (110) and the terminals (120, 130) may select serving beams through a beam search or beam management procedure. After the serving beams are selected, subsequent communication may be performed through a resource that is in a quasi-co-located (QCL) relationship with the resource that transmitted the serving beams.

[0052] If large-scale characteristics of the channel transmitting the symbol on the first antenna port can be inferred from the channel transmitting the symbol on the second antenna port, the first antenna port and the second antenna port may be evaluated to have a QCL relationship. For example, the large-scale characteristics may include at least one of a delay spread, a Doppler spread, a Doppler shift, an average gain, an average delay, and a spatial receiver parameter.

[0053] FIG. 2 illustrates the functional configuration of a base station in a wireless communication system according to one embodiment of the present disclosure. The configuration exemplified in FIG. 2 can be understood as the functional configuration of a base station (110). Terms such as '... unit', '... unit' used below refer to a unit that processes at least one function or operation, and this may be implemented in hardware or software, or a combination of hardware and software.

[0054] Referring to FIG. 2, a base station according to one embodiment of the present disclosure may include a wireless communication unit (210), a backhaul communication unit (220), a storage unit (230), and a control unit (240).

[0055] The wireless communication unit (210) can perform functions for transmitting and receiving signals through a wireless channel. For example, the wireless communication unit (210) can perform conversion functions between baseband signals and bit sequences according to the physical layer specifications of the system. For example, when transmitting data, the wireless communication unit (210) can generate complex symbols by encoding and modulating the transmitted bit sequence. Also, when receiving data, the wireless communication unit (210) can restore the received bit sequence by demodulating and decoding the baseband signal.

[0056] Additionally, the wireless communication unit (210) can up-convert a baseband signal into an RF (radio frequency) band signal and transmit it through an antenna, and down-convert an RF band signal received through an antenna into a baseband signal. To this end, the wireless communication unit (210) may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a DAC (digital to analog converter), an ADC (analog to digital converter), etc. Additionally, the wireless communication unit (210) may include a plurality of transmission and reception paths. Furthermore, the wireless communication unit (210) may include at least one antenna array composed of a plurality of antenna elements.

[0057] In terms of hardware, the wireless communication unit (210) may be composed of a digital unit and an analog unit, and the analog unit may be composed of a plurality of sub-units depending on operating power, operating frequency, etc. The digital unit may be implemented as at least one processor (e.g., a digital signal processor (DSP)).

[0058] The wireless communication unit (210) transmits and receives signals as described above. Accordingly, all or part of the wireless communication unit (210) may be referred to as a 'transmitter', a 'receiver', or a 'transceiver'. Furthermore, in the following description, transmission and reception performed through a wireless channel may be used to include the processing performed by the wireless communication unit (210) as described above.

[0059] The backhaul communication unit (220) can provide an interface for communicating with other nodes within the network. That is, the backhaul communication unit (220) can convert a bit sequence transmitted from a base station to another node, e.g., another connection node, another base station, an upper node, a core network, etc., into a physical signal, and can convert a physical signal received from another node into a bit sequence.

[0060] The storage unit (230) can store data such as basic programs, application programs, and configuration information for the operation of the base station. The storage unit (230) may be composed of volatile memory, non-volatile memory, or a combination of volatile memory and non-volatile memory. Additionally, the storage unit (230) can provide the stored data upon request from the control unit (240).

[0061] A control unit (240) (e.g., a controller) can control the overall operations of the base station. For example, the control unit (240) can transmit and receive signals through the wireless communication unit (210) or through the backhaul communication unit (220). Additionally, the control unit (240) can write and read data to and from the storage unit (230). Furthermore, the control unit (240) can perform the functions of a protocol stack required by the communication standard. According to other implementation examples, the protocol stack may be included in the wireless communication unit (210). To this end, the control unit (240) may include at least one processor.

[0062] According to various embodiments, the control unit (240) can control the base station to perform operations according to various embodiments of the present disclosure.

[0063] FIG. 3 illustrates the functional configuration of a terminal in a wireless communication system according to one embodiment of the present disclosure. The configuration exemplified in FIG. 3 can be understood as the functional configuration of a terminal (120, 130). Terms such as '...part', '...unit' used below refer to a unit that processes at least one function or operation, and this may be implemented in hardware or software, or a combination of hardware and software.

[0064] Referring to FIG. 3, the terminal includes a communication unit (310), a storage unit (320), and a control unit (330).

[0065] The communication unit (310) can perform functions for transmitting and receiving signals through a wireless channel. For example, the communication unit (310) can perform conversion functions between a baseband signal and a bit sequence according to the physical layer specifications of the system. For example, when transmitting data, the communication unit (310) can generate complex symbols by encoding and modulating the transmitted bit sequence. Also, when receiving data, the communication unit (310) can restore the received bit sequence by demodulating and decoding the baseband signal. Additionally, the communication unit (310) can up-convert the baseband signal into an RF band signal and transmit it through an antenna, and down-convert the RF band signal received through the antenna into a baseband signal. For example, the communication unit (310) may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a DAC, an ADC, etc.

[0066] Additionally, the communication unit (310) may include a plurality of transmission and reception paths. Furthermore, the communication unit (310) may include at least one antenna array composed of a plurality of antenna elements. In terms of hardware, the communication unit (310) may be composed of a digital circuit and an analog circuit (e.g., a radio frequency integrated circuit (RFIC)). Here, the digital circuit and the analog circuit may be implemented as a single package. Additionally, the communication unit (310) may include a plurality of RF chains. Furthermore, the communication unit (310) may perform beamforming.

[0067] The communication unit (310) transmits and receives signals as described above. Accordingly, all or part of the communication unit (310) may be referred to as a 'transmitter', a 'receiver', or a 'transmitter / receiver'. Additionally, in the following description, transmission and reception performed via a wireless channel may be used to include the meaning that processing as described above is performed by the communication unit (310).

[0068] The storage unit (320) can store data such as basic programs, application programs, and setting information for the operation of the terminal. The storage unit (320) may be composed of volatile memory, non-volatile memory, or a combination of volatile memory and non-volatile memory. Additionally, the storage unit (320) can provide the stored data upon request from the control unit (330).

[0069] A control unit (330) (e.g., a controller) can control the overall operations of the terminal. For example, the control unit (330) can transmit and receive signals through the communication unit (310). Additionally, the control unit (330) can write and read data from the storage unit (320). Furthermore, the control unit (330) can perform the functions of a protocol stack required by the communication standard. To this end, the control unit (330) may include at least one processor or microprocessor, or be part of a processor. Additionally, part of the communication unit (310) and the control unit (330) may be referred to as a communication processor (CP).

[0070] According to various embodiments, the control unit (330) can control the terminal to perform operations according to various embodiments described below.

[0071] FIG. 4 illustrates an example of a radio resource domain in a wireless communication system according to one embodiment of the present disclosure. In various embodiments of the present disclosure, the radio resource domain may include a structure in a time-frequency domain. According to one embodiment, the wireless communication system may include an NR communication system.

[0072] Referring to FIG. 4, in the wireless resource domain, the horizontal axis represents the time domain and the vertical axis represents the frequency domain. The length of the wireless frame (404) is 10 ms. The wireless frame (404) may be a time domain segment consisting of 10 subframes. The length of the subframe (403) is 1 ms. The unit of composition in the time domain may be an OFDM (orthogonal frequency division multiplexing) and / or DFT-s-OFDM (DFT (discrete Fourier transform)-spread-OFDM) symbol, and N-symb OFDM and / or DFT-s-OFDM symbols (401) may be combined to form a single slot (402). In various embodiments, the OFDM symbol may include a symbol for transmitting and receiving a signal using the OFDM multiplexing method, and the DFT-s-OFDM symbol may include a symbol for transmitting and receiving a signal using the DFT-s-OFDM or SC-FDMA (single carrier frequency division multiple access) multiplexing method. The minimum transmission unit in the frequency domain is a subcarrier, and the carrier bandwidth constituting the resource grid can be composed of a total of NscBW subcarriers (405). Additionally, for convenience of explanation, an embodiment regarding downlink signal transmission and reception is described in this disclosure, but this may also be applied to an embodiment regarding uplink signal transmission and reception.

[0073] In some embodiments, the number of slots (402) constituting one subframe (403) and the length of the slots (402) may vary depending on the subcarrier spacing. This subcarrier spacing is a numerology ( It can be referred to as ). That is, the subcarrier spacing, the number of slots included in the subframe, the length of the slot, and the length of the subframe can be configured variably. For example, in an NR communication system, when the subcarrier spacing (SCS) is 15 kHz, one slot (402) constitutes one subframe (403), and the lengths of the slot (402) and the subframe (403) may each be 1 ms. Also, for example, when the subcarrier spacing is 30 kHz, two slots may constitute one subframe (403). In this case, the length of the slot may be 0.5 ms and the length of the subframe may be 1 ms.

[0074] In some embodiments, the subcarrier spacing, the number of slots included in a subframe, the slot length, and the subframe length may be applied variably depending on the communication system. For example, in the case of an LTE (long-term evolution) system, the subcarrier spacing is 15 kHz, and two slots constitute one subframe, wherein the slot length may be 0.5 ms and the subframe length may be 1 ms. As another example, in the case of an NR system, the subcarrier spacing ( ) can be one of 15kHz, 30kHz, 60kHz, 120kHz, or 240kHz, and the subcarrier interval ( Depending on ), the number of slots included in one subframe can be 1, 2, 4, 8, or 16.

[0075] In the time-frequency domain, the basic unit of a resource may be a resource element (RE) (406), and the resource element (406) may be represented by an OFDM symbol index and a subcarrier index. A resource block may contain multiple resource elements. In an NR system, a resource block (RB) (or physical resource block (PRB)) (407) may be defined as N_SCRB consecutive subcarriers in the frequency domain. The number of subcarriers N_SCRB may be 12. The frequency domain may contain common resource blocks (CRBs). A physical resource block (PRB) may be defined in the bandwidth part (BWP) in the frequency domain. The CRB and PRB numbers may be determined differently depending on the subcarrier interval. In an LTE system, an RB may be defined as Nsymb consecutive OFDM symbols in the time domain and N_SCRB consecutive subcarriers in the frequency domain.

[0076] In NR and / or LTE systems, scheduling information for downlink data or uplink data may be transmitted from a base station (110) to a terminal (120) via downlink control information (DCI). In various embodiments, DCI may be defined according to various formats, each format may indicate whether the DCI includes scheduling information for uplink data (e.g., UL grant), scheduling information for downlink data (DL resource allocation), whether it is a compact DCI with a small size of control information, whether it is a fall-back DCI, whether spatial multiplexing using multiple antennas is applied, and / or whether it is a DCI for power control. For example, NR DCI format 1_0 or NR DCI format 1_1 may include scheduling for downlink data. Additionally, for example, NR DCI format 0_0 or NR DCI format 0_1 ​​may include scheduling for uplink data.

[0077] As described above, FIG. 4 illustrates an example of a downlink and uplink slot structure in a wireless communication system. In particular, FIG. 4 illustrates the structure of a resource grid in a 3GPP NR system. Referring to FIG. 4, a slot may include multiple orthogonal frequency division multiplexing (OFDM) symbols in the time domain and multiple resource blocks (RBs) in the frequency domain. A signal may consist of part or all of the resource grid. Additionally, the number of OFDM symbols generally included in a single slot may vary depending on the length of the cyclic prefix (CP). In FIG. 4, for convenience of explanation, a case in which a single slot consists of 14 OFDM symbols is illustrated, but the configuration of symbols is not specified for the signal referred to in this disclosure. In addition, the modulation method of the generated signal is not limited to a specific value of QAM (Quadrature Amplitude Modulation) and can follow modulation methods of various communication standards such as BPSK (Binary phase-shift keying) and QPSK (Quadrature Phase Shift Keying).

[0078] Various embodiments of the present disclosure may be applied in various wireless communication systems for transmitting downlink or uplink control information. Furthermore, it is understood that the contents of the present disclosure may be applied in unlicensed bands in addition to licensed bands as needed.

[0079] In the present disclosure, the higher layer signaling or higher signal may be a signal transmission method transmitted from a base station (110) to a terminal (120) using a physical layer downlink data channel, or from a terminal (120) to a base station (110) using a physical layer uplink data channel. According to one embodiment, the higher layer signaling may include at least one of radio resource control (RRC) signaling, signaling according to an F1 interface between a centralized unit (CU) and a distributed unit (DU), or a signal transmission method transmitted through a media access control (MAC) control element (MAC CE). Additionally, according to one embodiment, the higher layer signaling or higher signal may include system information, such as a system information block (SIB), that is commonly transmitted to a plurality of terminals (120).

[0080] In a 5G wireless communication system, a synchronization signal block (SSB) (also referred to as an SS block, SS / PBCH block, etc.) may be transmitted for initial access, and the synchronization signal block may consist of a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH). In the initial access phase, when a terminal first connects to the system, the terminal can obtain downlink time and frequency domain synchronization from the synchronization signal and obtain a cell identity (cell ID) through a cell search procedure. The synchronization signal may include the PSS and the SSS. The terminal can receive a PBCH containing a master information block (MIB) from the base station to obtain system information related to transmission and reception, such as system bandwidth or related control information, as well as basic parameter values. Based on the received PBCH, the terminal can obtain a system information block (SIB) by performing decoding on the PDCCH (physical downlink control channel) and PDSCH (physical downlink shared channel). Subsequently, the terminal can exchange identity with the base station through a random access step and initially connect to the network after going through steps such as registration and authentication.

[0081] As described above, one slot may contain 14 symbols, and in a 5G communication system, the uplink-downlink configuration of symbols and / or slots may be configured in three stages.

[0082] As a first method, the uplink-downlink of symbols and / or slots can be established semi-statically at the symbol level through cell-specific configuration information derived from system information. More specifically, the cell-specific uplink-downlink configuration information derived from system information may include uplink-downlink pattern information and reference subcarrier information. The uplink-downlink pattern information may indicate the pattern periodicity, the number of consecutive downlink slots and the number of symbols in the next slot from the start of each pattern, the number of consecutive uplink slots and the number of symbols in the next slot from the end of the pattern. Slots and symbols not designated as uplink or downlink may be determined as flexible slots / symbols.

[0083] In a second method, through user-specific configuration information via dedicated upper-level signaling, a flexible slot or a slot containing a flexible symbol can be indicated by the number of consecutive downlink symbols from the start symbol of the slot and the number of consecutive uplink symbols from the end of the slot, respectively, or can be indicated by the entire slot downlink or the entire slot uplink.

[0084] As a third method, to dynamically change the downlink and uplink signal transmission intervals, symbols designated as flexible symbols in each slot (e.g., symbols not designated as downlink and uplink) can be indicated as downlink symbols, uplink symbols, or flexible symbols through a Slot Format Indicator (SFI) included in the downlink control channel. The Slot Format Indicator can select an index from a pre-configured table (e.g., 3GPP TS 38.213 Table 11.1.1-1) for the uplink-downlink configuration of 14 symbols within a single slot.

[0085] FIG. 5 illustrates a schematic diagram of an operation for performing scheduling based on channel measurement according to one embodiment of the present disclosure.

[0086] Referring to FIG. 5, the base station may perform scheduling based on channel measurement results. In the present disclosure, 'scheduling' may include the operation of the base station allocating time resources and / or frequency resources for transmission and reception to a terminal.

[0087] In step 510, operations for cell synchronization and providing cell system information may be performed. Cell synchronization may include an operation for determining the timing of a transmission link for a discovered cell based on a signal broadcast from a base station. Additionally, cell synchronization may include a cell search procedure for searching for cells around the terminal and obtaining the physical cell ID (PCI) of the cell, and a cell selection procedure for determining whether to connect to the discovered cell. Cell system information may include a system information block (SIB), a master information block (MIB), etc., containing information about the cell. Step 510 may further include a step in which the terminal attempts initial access to a base station and a step in which the terminal camps on to the base station.

[0088] In step 520, channel measurement between the terminal and the base station may be performed. Channel measurement may include an operation to obtain channel state information based on a reference signal (RS). For example, channel measurement may include an operation to obtain channel state information (CSI) regarding the downlink channel state based on a downlink reference signal, CSI-RS. For example, channel measurement may include an operation to obtain information regarding the uplink channel state based on a sounding reference signal (SRS). Of course, the types of reference signals or channel state information used for channel measurement are not limited to the examples described above.

[0089] In step 530, the base station may perform scheduling based on the channel measurement results performed in step 520. Specifically, the base station may allocate frequency resources and / or time resources to at least one terminal based on information regarding the status of the uplink channel and the downlink channel.

[0090] FIG. 6 illustrates a flowchart of an operation for providing cell synchronization and cell system information according to one embodiment of the present disclosure. Steps 610 to 640 of FIG. 6 may correspond to step 510 of FIG. 5.

[0091] According to one embodiment, in step 610, the base station may broadcast a cell search assistance signal. The terminal may receive the cell search assistance signal broadcast from the base station. The cell search assistance signal may include a synchronization signal block (SSB). The SSB may include a synchronization signal (SS) and a physical broadcasting channel (PBCH).

[0092] According to one embodiment, in step 620, the terminal can perform cell synchronization based on the cell search support signal received in step 610.

[0093] According to one embodiment, in step 630, the base station may transmit cell system information to the terminal. The terminal may receive cell system information from the base station. The cell system information may include a master information block (MIB) and a system information block (SIB). For example, the terminal may receive the MIB from the base station. For example, the terminal may receive the SIB from the base station based on the information contained in the MIB received from the base station.

[0094] According to one embodiment, at step 640, the terminal may store cell system information received from the base station. For example, the terminal may store the cell system information in memory. The terminal may perform a random access (RA) procedure to the base station based on the stored cell system information. After performing the RA procedure, the terminal may perform radio resource control (RRC) connection setup and a protocol data unit (PDU) session to ensure quality of service (QoS).

[0095] FIG. 7 illustrates a flowchart of an operation for performing channel measurement according to an embodiment of the present disclosure. Steps 710 to 780 of FIG. 7 may correspond to step 520 of FIG. 5. The order of steps 710 to 780 is not limited as illustrated in the example. For example, FIG. 7 illustrates that steps 710 to 730, which obtain terminal-side channel measurement information based on a downlink reference signal, are performed prior to steps 740 to 760, which obtain base station-side channel measurement information based on an uplink reference signal; however, steps 710 to 730 may be performed after steps 740 to 760 or in parallel with steps 740 to 760.

[0096] According to one embodiment, in steps 710 to 780, the terminal and the base station may obtain channel measurement information based on a reference signal. In the present disclosure, channel measurement information may be referred to as a term meaning information related to the channel state. For example, channel measurement information may include CSI, which is information about the state of the downlink channel estimated based on CSI-RS, namely CQI (channel quality indicator), RI (rank indicator), PMI (precoding matrix indicator), etc. For example, channel measurement information may include information about the state of the uplink channel estimated based on SRS.

[0097] According to one embodiment, in step 710, the base station may transmit a downlink reference signal to the terminal. The terminal may receive the downlink reference signal from the base station. The downlink reference signal may include CSI-RS as described above with reference to FIG. 5.

[0098] According to one embodiment, in step 720, the base station may transmit a downlink reference signal to the terminal. The terminal may receive the downlink reference signal from the base station. Step 720 can be understood as repeatedly performing the operation of step 710. Although FIG. 7 illustrates that the base station transmits two downlink reference signals to the terminal through steps 710 and 720, the number of times and the interval at which the base station transmits downlink reference signals to the terminal are not limited as illustrated in the example. For example, the base station may transmit three or more downlink reference signals to the terminal.

[0099] According to one embodiment, in step 730, the terminal may perform terminal-side channel measurement based on the downlink reference signal received from the base station in steps 710 to 720. In the present disclosure, "terminal-side channel measurement" may mean an operation in which the terminal estimates the state of a downlink channel based on the downlink reference signal received from the base station via the downlink. For example, terminal-side channel measurement may include an operation in which the terminal obtains CSI, which is information about the state of the downlink channel, based on the CSI-RS received from the base station.

[0100] According to one embodiment, in step 740, the terminal may transmit an uplink reference signal to the base station. The base station may receive the uplink reference signal from the terminal. The uplink reference signal may include an SRS as described above with reference to FIG. 5.

[0101] According to one embodiment, in step 750, the terminal may transmit an uplink reference signal to the base station. The base station may receive the uplink reference signal from the terminal. Step 750 can be understood as repeatedly performing the operation of step 740. Although FIG. 7 illustrates that the terminal transmits two uplink reference signals to the base station through steps 740 and 750, the number of times and the interval at which the terminal transmits uplink reference signals to the base station are not limited as illustrated in the example. For example, the terminal may transmit three or more uplink reference signals to the base station.

[0102] According to one embodiment, in step 760, the base station may perform base station-side channel measurement based on the uplink reference signal received from the terminal in steps 740 to 750. In the present disclosure, "base station-side channel measurement" may refer to an operation in which the base station estimates the state of the uplink channel based on the uplink reference signal received from the terminal via the uplink. For example, base station-side channel measurement may include an operation in which the base station obtains information about the state of the uplink channel based on the SRS received from the terminal.

[0103] According to one embodiment, in step 770, the terminal may provide the terminal’s channel measurement information to the base station. The ‘terminal’s channel measurement information’ may correspond to information regarding the state of the downlink channel obtained by the terminal through terminal-side channel measurement in step 730. For example, the terminal’s channel measurement information may include CQI (channel quality indicator), PMI (precoding matrix indicator), and RI (rank indicator). Of course, the terminal’s channel measurement information is not limited thereto. For example, the terminal’s channel measurement information may include RSRP (reference signal received power), RSSI (received signal strength indicator), and RSRQ (reference signal received quality).

[0104] According to one embodiment, at step 780, the base station may store channel measurement information of the terminal. For example, the base station may store terminal channel measurement information received from the terminal at step 770 in memory. For example, the base station may store information regarding the state of the uplink channel obtained by the base station through base station-side channel measurement at step 760 in memory.

[0105] FIG. 8 illustrates a flowchart of an operation for performing scheduling according to one embodiment of the present disclosure. Steps 810 to 850 of FIG. 8 may correspond to step 530 of FIG. 5.

[0106] According to one embodiment, at step 810, the terminal may transmit a scheduling request and terminal information to the base station. At step 810, the base station may receive the scheduling request and terminal information from the terminal. The terminal information may include information related to the terminal that the base station considers during scheduling. For example, the terminal information transmitted by the terminal to the base station at step 810 may include the quality of service (QoS) of the required service, a buffer status report of the terminal, and a power headroom report of the terminal.

[0107] According to one embodiment, in step 820, the base station may generate scheduling group candidates. A scheduling group may be referred to as a group for scheduling in which a plurality of terminals are classified into at least two sets based on terminal information received from a terminal. Here, for terminals belonging to the same scheduling group, the base station may perform scheduling such that at least one common method is applied. For example, the base station may perform scheduling such that terminals belonging to the same scheduling group use the same uplink transmission power. The base station may determine a plurality of scheduling group candidates. A scheduling group candidate may refer to a plurality of types of scheduling groups classified based on various criteria, and the base station may determine a scheduling group by selecting one of the scheduling group candidates.

[0108] According to one embodiment, in step 830, the base station can predict scheduling group performance. Scheduling group performance may be related to the channel state between the base station and the terminals included in the scheduling group candidates determined in step 820. In step 830, the base station can predict scheduling group performance for each scheduling group candidate by estimating the channel state for the terminals included in the scheduling group candidates.

[0109] According to one embodiment, in step 840, the base station may perform scheduling optimization. Scheduling optimization may include determining a transmission power or resource allocation method that satisfies certain requirements, such as a delay and transmission amount, to have an optimal signal-to-interference and noise ratio (SINR) for a selected scheduling group based on the scheduling group performance predicted in step 830.

[0110] According to one embodiment, in step 850, the base station may provide (transmit) scheduling information to the terminal based on an optimized scheduling method. The terminal may receive scheduling information from the base station. The scheduling information may include configuration information for a resource to which the terminal can transmit uplink data to the base station. Alternatively, the scheduling information may include configuration information for a resource to which the base station transmits downlink data to the terminal.

[0111] According to various embodiments of the present disclosure, an upper mid-band band of 7-24 GHz can be used as a communication frequency band, having a shorter wavelength than the existing sub-6 GHz frequency band, using more antennas, and having wider coverage than the millimeter wave frequency band.

[0112] In addition, to maximize the advantages of the upper mid-band frequency band, an extreme MIMO (X-MIMO) system using a larger number of antennas—including 256 to 512 transceivers compared to the 64 transceivers of the massive MIMO (multi-input multi-output) in existing 5G NR (new radio)—can be utilized. When using the upper mid-band band in a wireless communication system, there can be a much wider variety of channel characteristics compared to when using the 3.5 GHz band. For example, when using the 3.5 GHz band, the channel model may primarily correspond to the uncorrelated Rayleigh model. On the other hand, when a new band (e.g., the upper mid-band band) is used, various channel characteristics such as the correlated Rician fading channel model, Rician-mixture fading, and nWDP (n-wave with diffuse power) fading may be present.

[0113] Consequently, accurate channel distribution information (CDI) may be required to guarantee performance and optimize resource efficiency in scheduling designed to support high-reliability, low-latency, high-capacity, and non-periodic / random traffic patterns in the uplink, based on channel environments corresponding to various channel characteristics. However, uplink reference signal (e.g., SRS) resources for uplink channel estimation are limited in terms of frequency, time, code, etc., which may prevent the complete estimation of channel distribution in spatial dimensions in large-scale MIMO systems. For example, the size of the line-of-sight (LoS) channel estimation corresponds to the product of the antenna size of the transmitter and the antenna size of the receiver, while the size of the non-LoS (NLoS) channel correlation matrix may correspond to the square of the product of the antenna sizes of the transmitter and the receiver. As a result, while the size of channel distribution information required for channel estimation in large-scale MIMO systems increases significantly, the communication resources necessary for channel estimation are limited, which may constrain accurate channel estimation. If an inaccurate CDI is obtained due to constraints in channel estimation, resource efficiency is significantly reduced, so the provision of communication services for the target traffic to the terminal may not be achieved.

[0114] The present disclosure can provide a scheduling method that takes into account the diversity of the channel environment and the guarantee of scheduling performance.

[0115] In addition, the present disclosure can provide a method to solve the problem of increasing channel distributions and distribution estimation sizes in relation to the measurement of channel information between a terminal and a base station.

[0116] Furthermore, the present disclosure may provide a scheduling method that considers various channel environments as well as channel path loss in relation to the guarantee of scheduling performance. Additionally, the present disclosure may provide a scheduling method that considers minimum performance for guaranteeing scheduling performance as well as average scheduling performance.

[0117] In addition, the present disclosure may provide a scheduling method for guaranteeing uplink performance and a method for estimating the conditional distribution of an actual channel for scheduling when errors and outdatedness exist in the channel state information in a multiple-input / output system in which the antenna size of the transmitting end or the antenna size of the receiving end is relatively large.

[0118] In addition, the present disclosure can provide a method for accurately predicting scheduling performance for any scheduling group based on estimating the conditional distribution of the actual channel.

[0119] In addition, the present disclosure can provide a method for optimizing scheduling based on accurate scheduling performance prediction.

[0120] In the various embodiments of the present disclosure described above, the present disclosure aims to provide a method for estimating the conditional distribution of an actual channel based on information regarding errors and aging of the channel state information along with channel state information for a terminal requesting scheduling, predicting the performance of scheduling based on the estimated conditional distribution of the actual channel, and optimizing scheduling based on the predicted scheduling performance. To this end, the present disclosure may provide a method utilizing three types of channel-related information referred to as channel state information (CSI), channel feature information, and channel state feature information.

[0121] In the present disclosure, 'channel state information' may be referred to as a term meaning information regarding a channel state obtained through immediate channel state estimation based on a reference signal. In one embodiment, the channel state information may include channel state estimation information and the time of acquisition of the channel state information.

[0122] In the present disclosure, 'channel feature information' may be referred to as a term meaning information including the type of environmental channel distribution function of a base station or cell and the distribution parameters thereof. In one embodiment, the channel feature information may include information regarding a channel state determined according to the channel environment. For example, the channel feature information may include information regarding a channel state determined based on base station antenna correlation and the location of the user terminal. Additionally, in the present disclosure, the channel feature information may be referred to as a 'channel feature variable' determined according to the channel environment.

[0123] In the present disclosure, 'channel state feature information' may be referred to as a term meaning information including the type of a conditional channel state distribution function and the parameters of a conditional channel state distribution function, based on errors in channel state information and the aging of channel state information. In one embodiment, the channel state feature information may include, but is not limited to, a conditional probability distribution function regarding user mobility, Doppler frequency, user location, and average received signal magnitude. Additionally, in the present disclosure, the channel state feature information may be referred to as a 'channel state feature variable'. The channel state feature information may be acquired periodically, and as described below with reference to FIG. 16, the base station may update the channel state feature information by acquiring and storing the changed channel state feature information from the terminal. The period during which the base station acquires the channel state feature information may be greater than the period during which the base station acquires the channel feature information, but is not limited thereto.

[0124] FIG. 9 illustrates a schematic diagram of an operation for performing scheduling based on channel feature information and channel state feature information according to one embodiment of the present disclosure.

[0125] According to one embodiment, in step 910, the base station may provide the terminal with configuration information for obtaining channel feature information and channel state feature information. That is, the base station may transmit the configuration information for obtaining channel feature information and channel state feature information to the terminal. The terminal may receive the configuration information for obtaining channel feature information and channel state feature information from the base station.

[0126] According to one embodiment, in step 920, the base station may acquire channel feature information. The channel feature information may include information regarding channel estimation results estimated by the terminal and the base station, respectively, based on the configuration information and reference signal of step 910. The terminal may transmit to the base station terminal-side channel feature information including information regarding the channel estimation results estimated at the terminal side. The base station may receive terminal-side channel feature information from the terminal.

[0127] According to one embodiment, in step 930, the base station may acquire channel state feature information. The channel state feature information may include information regarding the channel estimation result of a downlink channel estimated based on the configuration information of step 910. The terminal may collect the downlink channel estimation information based on the configuration information of step 910. The terminal may acquire channel state feature information based on the collected channel estimation information. If the terminal acquires a channel state feature variable different from the previously acquired channel state feature information, it may report the changed channel state feature information to the base station. The base station may receive the channel state feature information from the terminal.

[0128] According to one embodiment, at step 940, a scheduling procedure may be performed. The scheduling procedure of step 940 may include the step of a base station generating a scheduling model by considering channel feature information and channel state feature information, the step of a base station performing scheduling for a terminal based on the scheduling model, and the step of a base station providing scheduling information to the terminal.

[0129] The specific operations included in steps 910 to 940 of FIG. 9 will be explained in detail with reference to FIG. 10 and subsequent drawings to be described later.

[0130] FIG. 10 illustrates a schematic diagram of performing scheduling in a wireless communication system according to one embodiment of the present disclosure.

[0131] FIG. 10 can be understood as an example of a scheduling model in a wireless communication system including a base station and a terminal that perform the operation of FIG. 9. That is, in describing a scheduling method with reference to the drawings below, the scheduling model illustrated in FIG. 10 may be referred to as an example. The base station (110) of FIG. 10 may correspond to the base station (110) of FIG. 1 and FIG. 2. The terminals of FIG. 10 may correspond to the terminals (120, 130) of FIG. 1 and FIG. 2.

[0132] According to one embodiment, the base station (110) may include a plurality of antennas. Each of the plurality of terminals may correspond to a terminal including a single antenna. Hereinafter, in the present disclosure, the number of the plurality of antennas included in the base station is It can be expressed as such. In addition, the number of terminals including a single antenna that are subject to scheduling by the base station (110) is It can be expressed as.

[0133] In various embodiments of the present disclosure, quality of service parameters (QoSP) may be defined. In the present disclosure, QoSP may include parameters related to reliability, latency, burst size, and arrival rate. Hereinafter, in the present disclosure, QoSP It can be expressed as follows. is a parameter related to reliability, and reliability is It can be defined as. is a parameter related to delay, and can be expressed in milliseconds. can include a parameter for expressing the number of bits per packet as a parameter associated with the burst size. can include a parameter for expressing the number of packets per unit time as a parameter related to the arrival rate.

[0134] According to one embodiment, a consistent subchannel can be defined for terminals included in a cell area. The subchannel is a subband subband Subframe period and symbols for communication It can be defined as. User Regarding this, the energy constraint per side channel is and large-scale path loss is It can be defined as. User energy information (UEI) is It can be defined as. User The single user channel vector for is, It can be defined as. User group Regarding this, the multi-user channel vector is It can be defined as. In this case, the probability density function (PDF) for a multi-user channel vector is It can be displayed as.

[0135] According to one embodiment, the scheduling model (1000) comprises a grouped user group or a scheduling group , unit allocation , pilot allocation , power control It may be composed of. In the present disclosure, the scheduling model (1000) is, It can be expressed in a form like this.

[0136] According to one embodiment, in a scheduling model, the scheduling group is It can be defined as follows. That is, a scheduling group may mean a subset of terminals determined to perform space division multiple access (SDMA) on a consistent subchannel. For example, referring to FIG. 10, scheduling groups (1010, 1020, 1030) may correspond to a subset including at least one terminal.

[0137] In the present disclosure, scheduling groups in a scheduling model according to various embodiments are Conditions such as can be satisfied. For example, scheduling groups include at least one terminal ( Each scheduling group does not include the same terminal ( ), union of all scheduling groups( ) can correspond to all terminals that are subject to scheduling.

[0138] According to one embodiment, in a scheduling model, subband allocation is, It can be defined as follows. Here, is, scheduling group It can mean the number of sub-bands allocated to.

[0139] According to one embodiment, a pilot assignment is, It can be defined as follows. Here, is, user or terminal It can mean a unit vector uniquely assigned to. That is, pilot assignment silver, It can be defined as a set of unit vectors such as . group Two different terminals at The pilot cross-correlation for is, It can be defined as.

[0140] According to one embodiment, in a scheduling model, power control means a set of target received power vectors. It can be defined as. That is, the target received power vector is It can be defined as follows. Here, can refer to the pilot's target received power (Target Rx Pilot Power). Also, can mean the target reception power of the data (Target Rx Data Power).

[0141] According to one embodiment, a scheduling group parameter (SGP) is, It can be defined as. Here, indicates that parameter space. That is, the scheduling group parameters are, Characteristics for scheduling groups can be expressed. For example, characteristics for scheduling groups may include properties related to the scheduling group size, maximum pilot cross-correlation, or target power. Each user group In this regard, as a parameter Terminals with... target power for the pilot and data Pilot symbol according to and data symbols can be transmitted.

[0142] According to one embodiment, a scheduling group based on channel estimation results The minimum signal-to-interference and noise ratio (min SINR) for can be obtained. The instantaneously estimated channel vector is , the channel estimation error vector is It can be defined as follows. and The covariance matrix of is, respectively and It can be defined as. Terminal Regarding this, the immediate SINR of the data symbol is the target data power and can be determined based on maximal ratio combining (MRC) receivers. For example, scheduling group The minimum SINR for can be obtained through an operation such as [Equation 1].

[0143] [Mathematical Formula 1]

[0144]

[0145] In [Equation 1], the signal, interference, and noise power terms are Since it is determined by, The probability distribution function (PDF) of is, It can have as a distribution parameter. That is, The PDF is It can be defined as follows.

[0146] According to one embodiment, the reliability criterion can be defined as shown in [Equation 2] below.

[0147] [Mathematical Formula 2]

[0148]

[0149] According to one embodiment, the condition defined by [Equation 2] is, Without requiring complete knowledge of, solely This may mean that only the marginal distribution of is required to satisfy the confidence criteria.

[0150] According to one embodiment, a scheduling group A target SINR can be defined for this. Target SINR silver, The condition can be satisfied. Accordingly, the transmission rate function corresponding to the target SINR can be defined.

[0151] According to one embodiment, sub-band allocation To ensure QoS, it can be determined to satisfy [Equation 3] below.

[0152] [Mathematical Formula 3]

[0153]

[0154] In [Mathematical Formula 3], It refers to the number of pilot symbols, ... can mean the number of data symbols. Sub-band allocation Since [Equation 3] is satisfied, burst data rate can be secured for the scheduling group.

[0155] Meanwhile, according to one embodiment, the user-specific channel vector for error and aging CSI can be defined as shown in [Equation 4] below.

[0156] [Mathematical Formula 4]

[0157]

[0158] In this case, the target SINR of the scheduling model of [Equation 1] can be calculated as shown in [Equation 5] below.

[0159] [Mathematical Formula 5]

[0160]

[0161] According to one embodiment, in CDI management, user group Multi-user channel distribution for (multi-user channel PDF) is, as in [Equation 6], the set of channel distributions It can be assumed to be one element of.

[0162] [Mathematical Formula 6]

[0163]

[0164] In [Mathematical Equation 6], is the number of CDI classes, is the CDI parameter (CDIP), is CDIP space, and may mean a classified channel distribution. Accordingly, the CDI according to various embodiments of the present disclosure is, = ( It can be defined as ).

[0165] According to various embodiments of the present disclosure, the following conditions may be satisfied.

[0166] - Number of CDI classes is finite.

[0167] - CDI Parameter (CDIP) is the size of the base station antenna or the size of the user group It has a low number of parameters that are not affected by.

[0168] - CDI ( ) is the terminal-side CDI obtained by the terminal ( ) and base station side CDI obtained by the base station ( It is obtained by ).

[0169] - Minimum SINR distribution for user groups is a parametric distribution set It is a component of, and a parametric distribution set is defined as shown in [Equation 7] below.

[0170] [Mathematical Formula 7]

[0171]

[0172] In [Equation 7], is the SINR distribution parameter (SINR-DP), is CDI class It can mean the SINR-DP space for.

[0173] According to one embodiment, the minimum SINR distribution as described above go It is a component of, and multi-user channel PDF go The set of Since it is a component of, the parametric distribution function according to SINR-DP from the multi-user channel distribution is the target SINR Regarding this, it can be obtained using the transformation method of [Mathematical Formula 8] below.

[0174] [Mathematical Formula 8]

[0175]

[0176] According to [Equation 8], a SINR-DP estimation model according to various embodiments of the present disclosure ( For ), the following [Equation 9] may hold.

[0177] [Mathematical Formula 9]

[0178]

[0179] SINR-DP estimation model of [Equation 9] ( ) may include a learned neural network model for performing scheduling according to various embodiments of the present disclosure.

[0180] In addition, according to one embodiment, a SINR-DP estimation model ( Scheduling group based on ) )'s goal SINR ( ) can be obtained. For example, scheduling group( )'s goal SINR ( ) can be obtained through the inverse cumulative distribution function (ICDF) as in [Equation 11] for the cumulative distribution function (CDF) defined as in [Equation 10] below.

[0181] [Mathematical Formula 10]

[0182]

[0183] [Mathematical Formula 11]

[0184]

[0185] According to one embodiment, a scheduling group ( )'s goal SINR ( Scheduling optimization can be performed based on ). For example, the base station, performance prediction and target SINR ( This reliability Scheduling group satisfying ( ) can be determined. Through this, the base station can determine the optimal scheduling group.

[0186] With reference to the drawings below, and assuming the above-described explanation regarding the scheduling model according to FIG. 10, the operation of the terminal and the base station will be explained in detail.

[0187] In the present disclosure, 'channel feature information' is the CDI described with reference to FIG. 10 ( It may be referred to as a term meaning a distribution function and its parameters regarding a channel distribution including ).

[0188] In the present disclosure, 'channel state feature information' may be referred to as a term meaning the type of conditional channel distribution function associated with the conditional distribution of a downlink channel and the parameters thereof. Here, “conditional” may mean that the channel state information contains errors at a given point in time, contains only a part of the channel state information, or is outdated based on a specific point in time after a given point in time when the channel state information was acquired.

[0189] FIG. 11 illustrates a schematic diagram of a base station transmitting configuration information to a terminal according to one embodiment of the present disclosure. FIG. 11 may be associated with step 910 of FIG. 9.

[0190] According to one embodiment, a base station (110) may determine configuration information (1115) for acquiring channel feature information and channel state feature information. For example, referring to FIG. 11, the base station may configure configuration information for a channel distribution information model (CDI model) and a channel state information model (CSI model) as channel feature information. Here, the CDI model can be understood as an example of a model for acquiring channel feature information, and the CSI model can be understood as an example of a model for acquiring channel state feature information.

[0191] According to one embodiment, the configuration information (1115) may be transmitted to a base station-side (BS-side) CDI / CSI manager (1125). The base station-side CDI / CSI manager (1125) may be implemented as a processor of the base station. Additionally, the configuration information (1115) may be transmitted by the base station and delivered to a user equipment-side (UE-side) CDI / CSI manager (1135). The user equipment-side CDI / CSI manager (1135) may be implemented as a processor of the terminal.

[0192] According to one embodiment, a base station (110) may transmit a cell synchronization signal and cell system information to terminals (1120, 1130, 1140, 1150) included in a cell area. For example, the cell system information may include a system information block (SIB). The base station (110) may transmit configuration information (1115) through the system information block while the terminal performs cell search and cell synchronization, but the method and timing of transmitting the configuration information (1115) are not limited thereto. For example, the configuration information (1115) may be transmitted separately from the system information block.

[0193] FIG. 12 illustrates a flowchart of an operation in which a base station transmits configuration information to a terminal according to one embodiment of the present disclosure. Steps 1210 to 1250 of FIG. 12 may correspond to step 910 of FIG. 9. Additionally, steps 1210 to 1250 of FIG. 12 may be understood as operations related to FIG. 11.

[0194] According to one embodiment, in step 1210, the base station may determine a method for acquiring channel feature information and channel state feature information. The operation of the base station determining a method for acquiring channel feature information and channel state feature information can be understood as an operation of determining setting information for acquiring channel feature information and channel state feature information, as described with reference to FIG. 11. For example, the base station may determine setting information regarding a set of channel distribution types and a channel measurement method for each channel distribution type on a cell-specific basis.

[0195] According to one embodiment, in step 1220, the base station may transmit a cell search support signal to the terminal. The terminal may receive the cell search support signal from the base station. The cell search support signal transmitted from the base station to the terminal in step 1220 of FIG. 12 may correspond to the cell synchronization signal of FIG. 11. Additionally, the cell search support signal may include the cell search support signal described above with reference to FIG. 6. For example, the cell search support signal may include a synchronization signal block (SSB).

[0196] According to one embodiment, in step 1230, the terminal can perform cell synchronization based on the cell search support signal received in step 610.

[0197] According to one embodiment, in step 1240, the base station may transmit to the terminal cell system information, a method for obtaining channel feature information determined in step 1210, and configuration information associated with a method for obtaining channel state feature information. Here, the configuration information associated with the method for obtaining channel feature information and the method for obtaining channel state feature information may include the configuration information for obtaining channel feature information and the configuration information for obtaining channel state feature information of FIG. 11. Referring to FIG. 12, the configuration information for obtaining channel feature information and the configuration information for obtaining channel state feature information may be transmitted from the base station to the terminal together with the cell system information in step 1240. Of course, the method of transmitting the configuration information is not limited to the example shown in FIG. 12. For example, the configuration information for obtaining channel feature information and the configuration information for obtaining channel state feature information may be transmitted to the terminal separately from the cell system information.

[0198] According to one embodiment, in step 1250, the terminal may store cell system information. Additionally, the terminal may store configuration information for acquiring channel feature information and channel state feature information. For example, the terminal may store configuration information regarding a method for acquiring channel feature information and channel state feature information in memory.

[0199] FIG. 13 illustrates a schematic diagram for obtaining channel feature information according to one embodiment of the present disclosure. FIG. 13 may be associated with step 920 of FIG. 9. For example, the schematic diagram of FIG. 13 may be understood as an example of an operation for obtaining channel feature information according to one embodiment of the present disclosure.

[0200] Referring to FIG. 13, a base station (110) can obtain channel feature information based on the channel estimation result estimated through a reference signal. For example, the base station (110) can receive terminal-side channel feature information determined based on the estimation result of a downlink channel estimated through a downlink reference signal from a terminal (1200). For example, the base station (110) can determine base station-side channel feature information based on the estimation result of an uplink channel estimated through an uplink reference signal. Below, the operation of determining terminal-side channel feature information and base station-side channel feature information, and the operation of the base station obtaining the determined channel feature information, will be described in detail.

[0201] According to one embodiment, a base station (110) may transmit a downlink reference signal to a terminal (1200). The terminal (1200) may receive a downlink reference signal from the base station (110). For example, referring to FIG. 13, the downlink reference signal may include CSI-RS.

[0202] According to one embodiment, the terminal (1200) can estimate the state of the downlink channel through the physical layer (PHY) (1305). For example, the terminal (1200) can obtain an estimation result for the downlink channel based on a downlink reference signal. The obtained estimation result for the downlink channel can be transmitted to the terminal-side CDI / CSI manager (1320).

[0203] According to one embodiment, a terminal (1200) can obtain an estimation result for a transmitted downlink channel through a terminal-side CDI / CSI manager (1320). For example, the terminal (1200) can perform a CDI Classification (1321) procedure through the terminal-side CDI / CSI manager (1320) to classify the estimation result for a downlink channel according to a channel distribution type. Through this, the terminal (1200) can obtain a terminal-side CDI type. In the present disclosure, the terminal-side CDI type is, It can be expressed as such. Additionally, the terminal (1200) can determine a CDI metric for configuring a channel distribution information parameter (CDIP) that determines the distribution of the channel through a terminal-side CDI / CSI manager (1320). The terminal (1200) can perform a CDIP measurement (1323) to measure the CDIP based on the determined CDI metric. In the present disclosure, the terminal-side CDIP is It can be expressed as. Also, in the present disclosure, terminal-side CDI type and terminal-side CDIP is, 'terminal-side CDI ( It can be expressed as )'.

[0204] According to one embodiment, the terminal (1200) provides the base station with a terminal-side CDI type obtained based on the estimation result for the downlink channel. and terminal-side CDIP You can report it.

[0205] According to one embodiment, a terminal-side CDI type reported from a terminal (1200) to a base station and terminal-side CDIP It can be stored in the terminal-side CDI storage (1330) within the base station (110).

[0206] According to one embodiment, a base station (110) can acquire channel feature information based on an uplink reference signal. The operation of the base station (110) acquiring base station-side channel feature information based on an uplink reference signal can be understood as corresponding to the operation of the terminal (1200) described above acquiring terminal-side channel feature information. For example, the base station can estimate the state of the uplink channel through the physical layer within the base station. Additionally, based on the estimation result of the state of the uplink channel, the base station (110) can, through the base station-side CDI manager (1340) within the base station (110), the base station-side CDI type It can obtain. In addition, the base station (110) can determine the CDI metric through the base station-side CDI / CSI manager (1340). In addition, the base station (110) can determine the base station-side CDIP based on the determined CDI metric. You can obtain.

[0207] According to one embodiment, the base station (110) receives a terminal-side CDI type from the terminal (1200). and terminal-side CDIP and base station-side CDI type and base station-side CDIP SINR-DP estimation model based on ( ) can be created (1350). For example, the base station (110) can classify the CDI type ( based on classifying the correlated channel environment, such as correlated Rayleigh or non-Gaussian correlated channels) ) can determine. The base station, CDI type ( Based on ), the aforementioned SINR-DP estimation model ( ) can be generated. For example, the base station (110) is of the CDI type ( By training an artificial neural network model that estimates SINR-DP based on training data including ), the SINR-DP estimation model ( Can generate ).

[0208] FIG. 14 illustrates a flowchart of an operation for acquiring channel feature information according to one embodiment of the present disclosure. Steps 1410 to 1490 of FIG. 14 may correspond to step 920 of FIG. 9. Additionally, steps 1410 to 1490 of FIG. 14 may be understood as an operation associated with FIG. 13.

[0209] According to one embodiment, in steps 1410 to 1420, the base station may transmit a downlink reference signal to the terminal. The terminal may receive the downlink reference signal from the base station. Steps 1410 to 1420 may correspond to the operation of the base station transmitting a downlink reference signal to the terminal as described in steps 710 to 720 of FIG. 7.

[0210] According to one embodiment, in step 1430, the terminal can obtain terminal-side channel feature information based on the downlink reference signal transmitted from the base station in steps 1410 to 1420. That is, in step 1430, the terminal can perform the operation of obtaining the terminal-side channel feature information described above with reference to FIG. 13.

[0211] According to one embodiment, in step 1440, the terminal may request permission from the base station to transmit terminal-side channel feature information. In one embodiment, step 1440 may be omitted.

[0212] According to one embodiment, at step 1445, the base station may authorize the transmission of terminal-side channel feature information in response to the request of the terminal at step 1440. Alternatively, if step 1440 is omitted, the base station may request the terminal to transmit terminal-side channel feature information at step 1445.

[0213] According to one embodiment, in step 1450, the terminal may transmit terminal-side channel feature information to the base station in response to the base station's transmission permission or the base station's transmission request. The base station may receive terminal-side channel feature information from the terminal.

[0214] According to one embodiment, in step 1460, the base station may store terminal-side channel feature information received from the terminal. The base station may store the terminal-side channel feature information in memory. For example, the base station may store the terminal-side channel feature information in a terminal-side CDI storage.

[0215] FIG. 15 illustrates a schematic diagram for obtaining channel state feature information according to one embodiment of the present disclosure. FIG. 15 may be associated with step 930 of FIG. 9. For example, the schematic diagram of FIG. 15 may be understood as illustrating an example of an operation for obtaining channel state feature information in step 930 of FIG. 9 according to one embodiment of the present disclosure. The base station (110) of FIG. 15 may correspond to the base station (110) of FIG. 1 and FIG. 2. The terminal (1500) of FIG. 15 may correspond to the terminal (120, 130) of FIG. 1 and FIG. 3.

[0216] Referring to FIG. 15, a base station (110) according to one embodiment of the present disclosure may receive channel state feature information obtained based on a downlink reference signal from a terminal (1500).

[0217] According to one embodiment, a base station (110) may transmit a downlink reference signal to a terminal (1500). The terminal (1500) may receive a downlink reference signal from the base station (110). For example, referring to FIG. 15, the base station (110) may transmit a CSI-RS to the terminal (1500). For example, the terminal (1500) may receive the CSI-RS transmitted by the base station (110) through the physical layer (1505).

[0218] According to one embodiment, the terminal (1500) can perform an estimation of the downlink channel based on receiving a downlink reference signal from the base station (110). The terminal (1500) can transmit the estimation result of the downlink channel to the terminal-side CSI manager (UE-side CSI Manager) (1520).

[0219] According to one embodiment, the terminal (1500) can determine channel state feature information associated with the distribution of a downlink channel through a CSI manager (1520). For example, the CSI manager (1520) can determine the type of conditional channel state distribution function included in the channel state feature information through a CSI model setup (1521) procedure. In the present disclosure, the type of conditional channel state distribution function is It can be expressed as such. Also, referring to FIG. 15, the type of the conditional channel state distribution function may be referred to as the “type of the CSI model.” Additionally, the CSI manager (1520) may determine the distribution parameter of the conditional channel state distribution function included in the channel state feature information through a channel estimation and aging parameter (CEAP) measurement (1523) procedure. In the present disclosure, the distribution parameter of the conditional channel state distribution function is, It can be expressed as such. Also, referring to FIG. 15, the distribution parameter of the conditional channel state distribution function can be referred to as the “channel estimation and aging parameter (CEAP).”

[0220] According to one embodiment, the terminal (1500) may report determined channel state feature information to the base station. For example, the terminal (1500) may report to the base station a type of conditional channel state distribution function. and distribution parameters of the conditional channel state distribution function It can transmit.

[0221] According to one embodiment, the base station (110) may store channel state feature information reported from the terminal (1500). For example, referring to FIG. 15, the base station (110) may store channel feature information in a terminal-side CSI model storage (UE-side CSI model storage) (1530). The terminal-side CSI model storage (1530) may be included in memory within the base station (110).

[0222] According to one embodiment, the base station (110) has a SINR-DP estimation model based on stored channel state feature information ( ) can be generated (1350). SINR-DP estimation model of Fig. 15 ( The operation of generating (1350) the SINR-DP estimation model of FIG. 13 ( This can correspond to the operation of generating (1350). For example, the base station (110) can generate a SINR-DP estimation model ( by learning an artificial neural network model that estimates SINR-DP based on learning data including channel state feature information). Can generate ).

[0223] FIG. 16 illustrates a flowchart of an operation for acquiring channel state feature information according to one embodiment of the present disclosure. Steps 1610 to 1660 of FIG. 16 may correspond to step 930 of FIG. 9. Additionally, steps 1610 to 1660 of FIG. 16 may be understood as operations associated with FIG. 15.

[0224] According to one embodiment, in steps 1610 to 1620, the base station may transmit a downlink reference signal to the terminal. The terminal may receive the downlink reference signal from the base station. Steps 1610 to 1620 may correspond to the operation of the base station transmitting a downlink reference signal to the terminal as described in steps 710 to 720 of FIG. 7.

[0225] According to one embodiment, in step 1630, the terminal can obtain channel state feature information based on the downlink reference signal transmitted from the base station in steps 1610 to 1620. The operation of the terminal obtaining channel state feature information in step 1630 may correspond to the operation of obtaining channel state feature information described above with reference to FIG. 15. For example, in step 1630, the terminal can obtain the type of the conditional channel state distribution function and the distribution parameters of the conditional channel state distribution function through the channel estimation result obtained based on the downlink reference signal. Additionally, in step 1630, the terminal can track changes regarding the distribution of the channel state. Changes regarding the distribution of the channel state may include information regarding the changed channel state distribution at a time point after a predetermined time point, based on information regarding the distribution of the channel state previously obtained at a predetermined time point. For example, step 1630 can be understood as an operation to determine a conditional distribution function regarding a channel state distribution that considers factors affecting changes in the channel state, such as movement of the terminal occurring after a predetermined point in time when the previously acquired channel state information was acquired. According to one embodiment, in step 1640, the terminal may request permission from the base station to transmit terminal-side channel state feature information. In one embodiment, step 1640 may be omitted.

[0226] According to one embodiment, at step 1645, the base station may authorize the transmission of terminal-side channel state feature information in response to the request of the terminal at step 16640. Alternatively, if step 1640 is omitted, the base station may request the terminal to transmit the channel state feature information at step 1645.

[0227] According to one embodiment, in step 1650, the terminal may transmit channel state feature information to the base station in response to permission to transmit channel state feature information of the base station or a request to transmit channel state feature information of the base station. The base station may receive channel state feature information from the terminal.

[0228] According to one embodiment, in step 1660, the base station may store channel state feature information received from the terminal. The base station may store the channel state feature information in memory. For example, the base station may store the channel state feature information in a terminal-side CSI storage. Additionally, the base station may manage or update the channel state feature information by receiving and storing changed channel state feature information from the terminal.

[0229] FIG. 17 illustrates a schematic diagram of performing scheduling according to one embodiment of the present disclosure. FIG. 17 may be associated with step 940 of FIG. 9. For example, the schematic diagram of FIG. 17 may be understood as an example of an operation in which a base station performs scheduling according to one embodiment of the present disclosure. The base station (110) of FIG. 17 may correspond to the base station (110) of FIG. 1 and FIG. 2. The terminal (1700) of FIG. 17 may correspond to the terminal (120, 130) of FIG. 1 and FIG. 3.

[0230] Referring to FIG. 17, the base station (110) can perform scheduling according to a scheduling model based on channel feature information, channel state feature information, and channel state information, etc.

[0231] According to one embodiment, the base station (110) can generate a scheduling model. The scheduling model may correspond to the scheduling model described above with reference to FIG. 10.

[0232] According to one embodiment, the base station (110) has a SINR-DP estimation model ( SINR-DP estimation model generated through the ) generation procedure (1750) ), and 'terminal-side CDI ( ) Base station side CDI ( CDI type obtained based on ) You can determine the scheduling model by inputting. Terminal-side CDI ( ) may refer to a CDI stored in a CDI storage (1740) within the base station (110). Base station side CDI ( Among ), base station-side CDIP This can be obtained based on uplink reference signals transmitted by sampled UEs among all terminals subject to scheduling. For example, a base station may transmit a sounding reference signal (SRS) request to the sampled terminals. The sampled terminals may transmit an SRS to the base station (110) over the uplink in response to the SRS request received from the base station (110). For example, referring to FIG. 17, a terminal (1700) included among the sampled terminals may transmit an SRS (1703) to the base station (110). The base station (110) determines the base station-side CDIP based on the uplink channel estimated based on the SRS (1703) received from the sampled terminals. You can obtain.

[0233] According to one embodiment, the input (1761) of the scheduler for determining the scheduling model is QoSP , UEI , CDI , SINR-DP estimation model It may include. The scheduler can perform optimized scheduling by utilizing a scheduling algorithm. Based on the input to the scheduler, the base station, CS group candidates The procedure for generation (1763), performance prediction of CS group candidates (1765), and CS optimization (1767) can be performed. Through this, the base station (110) can perform a scheduling model can decide.

[0234] FIG. 18 illustrates a flowchart of an operation for performing scheduling according to one embodiment of the present disclosure. Steps 1810 to 1890 of FIG. 18 may correspond to step 940 of FIG. 9. Additionally, steps 1810 to 1890 of FIG. 18 may be understood as an operation associated with FIG. 17.

[0235] According to one embodiment, in step 1810, the base station may generate (or determine) a scheduling model based on channel feature information, channel state feature information, and channel state information. Step 1810 can be understood in correspondence with the example of generating a scheduling model of FIG. 17. The channel feature information is the terminal-side CDI ( ) and base station-side CDI ( CDI type obtained based on ) It may include. Channel state feature information is the type of conditional channel state distribution function ( ) and the distribution parameters of the conditional channel state distribution function( It may include ). The channel state information may include information regarding the channel state obtained at a predetermined time based on a reference signal.

[0236] According to one embodiment, in step 1820, the terminal may transmit an uplink reference signal to the base station. For example, the uplink reference signal may include an SRS.

[0237] According to one embodiment, in step 1830, the base station may acquire and store channel state information based on the uplink reference signal received from the terminal in step 1820. Step 1830 may correspond to an operation of acquiring information regarding the state of the uplink channel based on the uplink reference signal. For example, the base station may acquire information regarding the state of the uplink channel for the sampled terminals based on receiving SRS from the sampled terminals.

[0238] According to one embodiment, in step 1840, the terminal may request scheduling from the base station.

[0239] According to one embodiment, in step 1850, the base station may assign an uplink reference signal to the terminal. For example, the base station may transmit to the terminal configuration information regarding resources for the terminal to transmit the uplink reference signal. The terminal may receive from the base station configuration information regarding resources for the terminal to transmit the uplink reference signal. Here, the uplink reference signal may include an SRS. In one embodiment, step 1850 may be omitted. For example, the base station may omit step 1850 if the base station has acquired and stored channel state information in step 1830. That is, if the base station has stored channel state information in advance through step 1830 prior to the scheduling request, the base station may omit steps 1850 to 1870, which involve acquiring channel state information after the scheduling request, because scheduling based on channel feature information and channel state feature information can be performed even after a predetermined time has elapsed.

[0240] According to one embodiment, at step 1860, the terminal may transmit an uplink reference signal to the base station. For example, the terminal may transmit an uplink reference signal to the base station based on configuration information regarding resources for the terminal to transmit an uplink reference signal received from the base station at step 1850. In one embodiment, if step 1850 is omitted, step 1860 may be omitted.

[0241] According to one embodiment, in step 1870, the base station may obtain channel state information based on the uplink reference signal received from the terminal in step 1860. For example, the base station may obtain information regarding the state of the uplink channel based on the SRS received from the terminal. In one embodiment, if steps 1850 to 1860 are omitted, step 1870 may be omitted.

[0242] According to one embodiment, in step 1880, the base station may perform scheduling based on channel feature information, channel state feature information, and channel state information. Step 1880 may include an operation of performing scheduling based on a scheduling model (model) generated through step 1810. For example, step 1880 may be understood as an operation of performing scheduling based on a scheduling model obtained as the output of the scheduler described above in FIG. 17.

[0243] According to one embodiment, at step 1890, the base station may provide scheduling information to the terminal. For example, the base station may transmit to the terminal resource allocation information for the terminal to transmit and receive signals through an uplink or downlink channel.

[0244] FIG. 19 illustrates a schematic diagram of the learning process of a neural network model (1900) for performing scheduling according to one embodiment of the present disclosure. The neural network model (1900) of FIG. 19 is the above-described SINR-DP estimation model ( It can be understood as an example of a neural network model for generating ). For example, the neural network model (1900) may mean a model trained to estimate SINR-DP.

[0245] According to one embodiment, a neural network model (1900) can be trained to estimate SINR-DP, a parameter representing a SINR distribution, based on input data including channel state information, channel feature information, and channel state feature information.

[0246] According to one embodiment, a SINR-DP estimation model ( Training of a neural network model (1900) for generating a training data set may include a training data set generation step (1910, 1930) and a neural network model training step (1920, 1940).

[0247] According to one embodiment, the step of generating a training data set (1910, 1930) comprises a type of input conditional channel state distribution function ( According to ), the operation may include generating training data for training the neural network model (1900). The training data for training the neural network model (1900) may include channel state information, channel feature information, and channel state feature information.

[0248] For example, the step of generating a training data set (1910, 1930) may include the step of generating input data expressed by [Equation 11] below.

[0249] [Mathematical Formula 11]

[0250]

[0251] In [Mathematical Equation 11], represents the CDI parameter (CDIP) included in the channel feature information described above with reference to FIG. 10, and may refer to the scheduling group parameter (SGP) (or configured SGP, CSGP) described above with reference to FIG. 10. Here, the SGP may include the size of the scheduling group and the target data symbol power. Additionally, the training dataset is at the current time ( ), CEAP CSI It may further include SINR distribution parameter coefficients (SINR-DPC). SINR-DPC may include parameters for preprocessing the SINR-DP estimation model.

[0252] According to one embodiment, in the step (1910, 1930) of generating a training data set, a minimum SINR distribution function ( based on the minimum SINR obtained through input data) Empirical data of ) can be obtained. Here, according to the conditions described with reference to Fig. 10, the minimum SINR distribution function ( ) is a parametric distribution set( One element of ) ) can be. Therefore, the minimum SINR distribution function( ) can be mapped to a distribution function determined by SINR-DP. Accordingly, in the step of generating a training data set (1910, 1930), a training data set such as [Equation 12] that fits an empirical distribution can be obtained.

[0253] [Mathematical Formula 12]

[0254]

[0255] According to one embodiment, a training step (1920, 1940) of a neural network model for estimating SINR-DP can be performed using a generated training data set as input data. In the training step (1920, 1940) of the neural network model, based on the generated training data set Supervised learning for a neural network model can be performed to satisfy [the condition]. In various embodiments of the present disclosure, learning and regression methods for the neural network may be used.

[0256] According to one embodiment, a parametric probability distribution function Based on the analysis of, SINR-DP ( For ) scheduling group parameter SGP( Regression function according to ) ) can be defined. Regression function( ) and scheduling group parameters SGP( SINR-DP according to ) The input determining ) is the SINR-DP source ( It can be defined as ). SINR-DP source ( ) can satisfy the following [Equation 13].

[0257] [Mathematical Formula 13]

[0258]

[0259] In [Equation 13], SINR-DP( ) corresponds to the output of the training step (1920, 1940) of the neural network model, and the training step (1920, 1940) of the neural network model is the optimal SINR-DP( It can be understood as the operation of training a neural network model to output ).

[0260] According to one embodiment, in the training step (1920, 1940) of a neural network model, pre-processing of input data obtained through the step (1910, 1930) of generating a training data set may be performed prior to the training step. The pre-processing operation on the input data may include an operation to reduce the size of the neural network model or an operation to normalize the input data. For example, CDIP pre-processing CDIP preprocessed according to CSGP Preprocessing The CSGP preprocessed according to It can be expressed as.

[0261] According to one embodiment, a neural network model ( For ), learning can be performed through iterative forward propagation and backward propagation.

[0262] According to one embodiment, the final SINR-DP estimation model ( ) is a regression function( ) and neural network models( It can be determined by the SINR-DP post-processing (1950) operation based on ). That is, SINR-DP estimation model ( ) can be determined as shown in [Equation 14] below.

[0263] [Mathematical Formula 14]

[0264]

[0265] FIG. 20 illustrates an example of a neural network model for performing scheduling according to one embodiment of the present disclosure. FIG. 20 is a determined SINR-DP estimation model (described with reference to FIG. 19) It can be understood as an example of an operation that performs performance prediction of a scheduling group based on ). The SINR-DP model (2001) of FIG. 20 may correspond to the learned neural network model (1900) of FIG. 19. For example, the SINR-DP estimation model (2001) of FIG. 20 is based on performing the preprocessing (2010), SINR-DPC model (2020, 2040), and SINR-DP postprocessing (2050) operations described with reference to FIG. 19, SINR-DP ( Can output ).

[0266] According to one embodiment, the determined SINR-DP estimation model described with reference to FIG. 19 ( Performance prediction of a scheduling group can be performed based on ). For example, a scheduling group performance prediction model (2000) includes a plurality of scheduling group candidates ( included in a set of scheduling groups) Performance prediction for ) can be performed. Performance prediction for scheduling groups is based on reliability parameters ( for each scheduling group It may include a step of performing a performance prediction that satisfies ).

[0267] According to one embodiment, a base station may perform an operation to maximize target performance based on performance prediction for each scheduling group and optimization of some scheduling group parameters (SGP). The operation to maximize target performance may include an operation to determine a target signal-to-interference and noise ratio (SINR) for a plurality of scheduling groups based on channel feature information, channel state feature information, and channel state information. In the present disclosure, the target SINR is, It can be expressed as.

[0268] According to one embodiment, the target SINR ( ) is the target SINR prediction model (2060) of the scheduling group performance prediction model (2000) It can be determined by the target SINR prediction model (2060)( ) is the SINR-DP output by SINR-DP post-processing (2050) ), QoS parameters according to channel environment (QoS parameter, QoSP) and group user energy information (UEI) With as input, target SINR( ) can be determined.

[0269] According to one embodiment, the base station obtains a target SINR (2000) through a scheduling group performance prediction model. The maximization process of ) can be performed. Target SINR( The maximization process of ) can be determined as shown in [Equation 15] below.

[0270] [Mathematical Formula 15]

[0271]

[0272] In [Mathematical Formula 15], represents the result value of the maximized target SINR, and is, scheduling group( It refers to fixed scheduling group parameters (CSGP) and space determined based on ), and can mean the determined scheduling group parameters (CSGP) and space to perform optimization.

[0273] According to one embodiment, the above-described performance prediction and target SINR ( The maximization process of ) can be extended and applied to various channel environments. For example, performance prediction and target SINR( The maximization process of ) can also be extended and applied to the case of the correlation Rayleigh channel.

[0274] According to one embodiment, in the case of a correlated Rayleigh channel, the channel model is, It is defined as such, where can mean the entire correlation matrix. The entire correlation matrix ( ) can be determined as shown in [Equation 16] below.

[0275] [Mathematical Formula 16]

[0276]

[0277] In the present disclosure, the total correlation matrix defined according to [Equation 16] ( )silver, Assuming that it satisfies, where can mean a correlation matrix (base station antenna correlation) observable at the terminal side. can refer to the correlation (multi-user correlation) matrix observable at the base station. Operator ' ' can mean the Kronecker product.

[0278] According to one embodiment, base station antenna correlation ( ) and multi-user correlation( The correlation characteristics of ) can be determined according to the eigenvalues ​​of each correlation matrix. Base station antenna correlation ( The eigenvalues ​​of ) are, It is expressed as, and multi-user correlation ( The eigenvalues ​​of ) are, It can be expressed as. Here, can mean a non-decreasing index.

[0279] According to one embodiment, the number of eigenvalues ​​among the eigenvalues ​​of the correlation matrices that satisfy a specified condition can be determined. For example, the specified condition is a value in which the eigenvalues ​​of the correlation matrix are set ( It may include those less than or equal to ). Base station antenna correlation ( ) eigenvalues ​​( The set value among ) The number of eigenvalues ​​less than or equal to ) is, It can be defined as such, and multi-user correlation ( )'s eigenvalue( The set value among ) The number of eigenvalues ​​less than or equal to ) is, It can be defined as follows.

[0280] According to one embodiment, a set value ( ) is, 10 -5 It can be determined as, but the set value ( The specific numerical value of ) is not limited to this. For example, the set value ( ) is, 10 -6 It can be determined as.

[0281] According to one embodiment, when a correlated Rayleigh channel model is applied, CDIP can be determined in a normalized space. For example, CDIP can be determined as shown in [Equation 17] below.

[0282] [Mathematical Formula 17]

[0283]

[0284] According to one embodiment, the base station may perform a gamma distribution approximation for the correlated Rayleigh channel. For example, the gamma distribution approximation for the correlated Rayleigh channel is, When defined as, and It can be expressed as follows. Also, the scaled ratio of independent gamma distributions It can follow the F-distribution, which is a continuous probability distribution representing the ratio of variances of samples independently drawn from a population that follows a normal distribution. Accordingly, in the case of a correlated Rayleigh channel, the target SINR ( ) can be determined as shown in [Equation 18] below.

[0285] [Mathematical Formula 18]

[0286]

[0287] In [Equation 18], represents the inverse cumulative distribution function (ICDF) of the F-distribution. Referring to [Equation 18], the SINR-DP parameter The distribution can be determined by.

[0288] According to one embodiment, SINR-DP parameters ( ) is a scheduling group parameter and It can be determined as shown in [Equation 19] below using polynomial regression associated with it.

[0289] [Mathematical Formula 19]

[0290]

[0291] In [Equation 19], Is, It can be defined as follows.

[0292] According to one embodiment, in a correlated Rayleigh channel, the preprocessed channel distribution information parameter (CDIP) and the preprocessed scheduling group parameter (SGP, or CSGP) can be defined as shown in [Equation 20] below.

[0293] [Mathematical Formula 20]

[0294]

[0295] According to one embodiment, in a correlated Rayleigh channel, the target SINR ( Optimization of ) can be performed. Target SINR in the correlated Rayleigh channel ( In order to perform optimization of ), the scheduling group parameters are, It can be defined as follows. In addition, power constraints are, It can be defined as follows. According to the definition above, the target SINR( )second To maximize it, the maximum value of [Equation 21] below can be determined.

[0296] [Mathematical Formula 21]

[0297]

[0298] According to one embodiment, the optimized target SINR can be transmitted to a scheduler. The scheduler can determine a scheduling model based on the target SINR and information regarding the channel state. For example, the scheduler can generate an optimal scheduling model based on the target SINR and information regarding the channel state, channel feature, and channel state feature.

[0299] FIG. 21 illustrates a flowchart of operations performed by a base station in a wireless communication system according to one embodiment of the present disclosure.

[0300] According to one embodiment, in step 2110, the base station may transmit to the terminal setting information for obtaining channel feature information and channel state feature information.

[0301] According to one embodiment, configuration information may be transmitted to a terminal via a cell system information block (SIB) while the terminal performs cell search and cell synchronization.

[0302] According to one embodiment, the configuration information may include information regarding a method for obtaining channel feature information based on a reference signal, and information regarding a method for obtaining channel state feature information based on a reference signal. For example, the configuration information may include information for obtaining channel feature information based on CSI (channel state information)-RS (reference signal) and SRS (sounding reference signal). Channel feature information may refer to a channel state distribution function at a specific point in time obtained based on a reference signal. Here, the channel state distribution function may include a probability distribution function associated with the channel state. The terminal-side channel feature information may be obtained based on CSI-RS, and the base station-side channel feature information may be obtained based on SRS. Additionally, for example, the configuration information may include information for obtaining channel state feature information based on CSI-RS.

[0303] According to one embodiment, in step 2120, the base station may acquire channel feature information based on the channel state information of the terminal acquired based on the configuration information. For example, the base station may store the terminal-side channel feature information transmitted from the terminal in memory. The channel feature information may include information on the channel distribution function of the downlink channel acquired based on the downlink (DL) reference signal (RS) and information on the channel distribution function of the uplink channel acquired based on the uplink (UL) reference signal.

[0304] According to one embodiment, in step 2130, the base station may acquire channel state feature information based on the acquired channel feature information and the channel state information of the terminal at a predetermined point in time. The base station may store the channel state feature information transmitted from the terminal in memory. Here, the channel state feature information may be referred to as a term meaning information including the type of a conditional channel state distribution function and the parameters of a conditional channel state distribution function based on errors in the channel state information and the degree of aging of the channel state information. The channel state feature information may refer to a conditional probability distribution function of the channel state at a specific point in time acquired based on a reference signal. That is, unlike channel feature information, which is a general channel distribution function determined according to the channel environment at a predetermined point in time of the base station or cell, the channel state feature information may refer to a conditional probability distribution function of the channel. Here, “conditional” may mean that the channel state information at a predetermined point in time contains errors, contains only a part of the channel state information, or is outdated based on a specific point in time after the predetermined point in time when the channel state information was acquired.

[0305] According to one embodiment, the channel state feature information may include, but is not limited to, a conditional probability distribution function regarding user mobility, Doppler frequency, user location, and average received signal magnitude. Additionally, the channel state feature information may include information regarding a changed channel state at a point in time after a predetermined point in time estimated based on a downlink reference signal. For example, the channel state feature information may be acquired periodically, and as described with reference to FIG. 16, the base station may update the channel state feature information by acquiring and storing the changed channel state feature information from the terminal. The period during which the base station acquires the channel state feature information may be greater than the period during which the base station acquires the channel feature information, but is not limited thereto.

[0306] According to one embodiment, in step 2140, the base station may perform scheduling based on channel feature information, channel state feature information, and channel state information. The step of performing scheduling may include determining a plurality of scheduling groups by grouping a plurality of terminals including a terminal based on channel state, and determining a target signal-to-interference and noise ratio (SINR) for the plurality of scheduling groups based on channel feature information, channel state feature information, and channel state information. The base station may perform scheduling performance prediction for the plurality of scheduling groups. The base station may perform scheduling for the plurality of scheduling groups based on the determined target SINR and the result of the scheduling performance prediction. For example, the base station may perform scheduling based on the target SINR optimized through the scheduling performance prediction. Additionally, according to one embodiment, in step 2140, the base station may transmit information regarding scheduling to the terminal.

[0307] FIG. 22 illustrates a flowchart of operations performed by a terminal in a wireless communication system according to one embodiment of the present disclosure.

[0308] According to one embodiment, in step 2210, the terminal can receive setting information for obtaining channel feature information and channel state feature information from a base station.

[0309] According to one embodiment, in step 2220, the terminal can transmit channel feature information to the base station based on the terminal's channel state information obtained based on the configuration information and the downlink reference signal.

[0310] According to one embodiment, in step 2230, the terminal can transmit channel state feature information to the base station based on channel feature information and channel state information at a predetermined time of the terminal.

[0311] According to one embodiment, in step 2240, the terminal can receive from the base station information regarding channel feature information, channel state feature information, and scheduling performed based on channel state information.

[0312] In addition, the present disclosure can provide a method and apparatus that minimizes the increase in overhead for CSI calculation complexity and CSI reporting of a terminal and satisfies the QoS requirements of a terminal by adaptively determining the number of ports used for PDSCH transmission according to the transmission environment in a wireless communication system.

[0313] When a method according to various embodiments of the present disclosure is implemented in software, a computer-readable storage medium may be provided for storing one or more programs (software modules). One or more programs stored in the computer-readable storage medium are configured for execution by one or more processors in an electronic device. One or more programs include instructions that cause the electronic device to execute methods according to the embodiments described in the claims or specification of the present disclosure.

[0314] In the present disclosure, the function or operation performed by an electronic device may be performed by one or more processors executing one or more instructions stored in memory. The function or operation of the electronic device mentioned in the present disclosure may be performed by a single processor executing one or more instructions, or by a combination of multiple processors executing one or more instructions. A processor mentioned in the present disclosure is understood to include a circuit for performing operations or controlling other components of the electronic device. For example, the one or more processors may include a central processing unit (CPU), a micro-processor unit (MPU), an application processor (AP), a communication processor (CP), a neural processing unit (NPU), a system on chip (SoC), or an integrated circuit (IC) configured to execute one or more instructions. The one or more processors may be configured to perform the operation of the electronic device described above.

[0315] In the present disclosure, a program (software module, software) may be stored in a random access memory, a non-volatile memory including flash memory, a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic disc storage device, a compact disc-ROM (CD-ROM), digital versatile discs (DVDs), or other forms of optical storage devices, or a magnetic cassette. Alternatively, it may be stored in a memory composed of some or all of these. The memory may be composed of a single storage medium or a combination of multiple storage media. The one or more instructions may be stored in a single storage medium or distributed across multiple storage media.

[0316] Additionally, the above program may be stored on an attachable storage device that can be accessed via a communication network such as the Internet, Intranet, LAN (local area network), WLAN (wide LAN), or SAN (storage area network), or a combination thereof. Such a storage device may be connected to a device performing an embodiment of the present disclosure through an external port. Additionally, a separate storage device on a communication network may be connected to a device performing an embodiment of the present disclosure.

[0317] Additionally, in the present disclosure, terms such as “part,” “module,” etc. may be a hardware component, such as a processor or circuit, and / or a software component executed by a hardware component, such as a processor.

[0318] "Parts" and "modules" may be implemented by a program that is stored on an addressable storage medium and can be executed by a processor. For example, "parts" and "modules" may be implemented by components such as software components, object-oriented software components, class components, and task components, as well as by processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables.

[0319] The specific embodiments described in this disclosure are merely examples and do not limit the scope of this disclosure in any way. For the sake of brevity, descriptions of prior electronic configurations, control systems, software, and other functional aspects of said systems may be omitted.

[0320] Meanwhile, although specific embodiments have been described in the detailed description of the present disclosure, it is understood that various modifications are possible within the scope of the present disclosure. Therefore, the scope of the present disclosure should not be limited to the described embodiments, but should be defined by the claims set forth below as well as equivalents thereof.

Claims

1. A method performed by a base station in a wireless communication system, A step of transmitting configuration information to a terminal (user equipment) for acquiring channel feature information and channel state feature information; A step of obtaining the channel feature information based on the channel state information of the terminal obtained based on the above setting information; A step of acquiring channel state feature information based on the acquired channel feature information and channel state information at a predetermined point in time of the terminal; and A method comprising the step of performing scheduling based on the channel feature information, the channel state feature information, and the channel state information.

2. In Paragraph 1, The above configuration information is transmitted to the terminal via a cell system information block (SIB) while the terminal performs cell search and cell synchronization, and The above setting information comprises information regarding a method for obtaining the channel feature information based on the reference signal, and information regarding a method for obtaining the channel state feature information based on the reference signal.

3. In Paragraph 1, A method comprising the above channel feature information including information on the channel distribution function of a downlink channel obtained based on a downlink (DL) reference signal (RS) and information on the channel distribution function of an uplink channel obtained based on an uplink (UL) reference signal.

4. In Paragraph 1, A method in which the above channel state characteristic information includes information regarding a changed channel state at a point in time after the above predetermined point in time, estimated based on a downlink reference signal.

5. In Paragraph 1, The step of acquiring the above channel feature information includes the step of storing the above channel feature information in memory, and A method comprising the step of acquiring the channel state feature information, the step of storing the channel feature information in the memory.

6. In Paragraph 1, The above channel feature information is obtained based on CSI (channel state information), RS (reference signal), and SRS (sounding reference signal), and The above channel state feature information is obtained based on the above CSI-RS.

7. In Paragraph 1, The step of performing the above scheduling is, A step of determining a plurality of scheduling groups by grouping a plurality of terminals including the terminal based on channel status; A step of determining a target signal-to-interference and noise ratio (SINR) for the plurality of scheduling groups based on the channel feature information, the channel state feature information, and the channel state information; A step of performing scheduling performance prediction for the plurality of scheduling groups; and A method comprising the step of performing scheduling for the plurality of scheduling groups based on the results of the above-determined target SINR and the above-determined scheduling performance prediction.

8. In Paragraph 7, A method in which the above target SINR is determined using a machine-learned (ML) neural network model that estimates a SINR distribution parameter (DP) using the channel feature variable, the channel state feature variable, and channel state information as input data.

9. A method performed by a terminal (user equipment) in a wireless communication system, wherein the method comprises: A step of receiving configuration information from a base station to obtain channel feature information and channel state feature information; A step of transmitting to the base station the channel characteristic information associated with the downlink channel environment based on the channel state information of the terminal obtained based on the setting information and the downlink reference signal received from the base station; A step of transmitting channel state feature information to the base station based on the acquired channel feature information and channel state information at a predetermined time of the terminal; and A method comprising the step of receiving information regarding scheduling performed based on the channel feature variable, the channel state feature variable, and the channel state information from the base station.

10. In a base station of a wireless communication system: At least one transceiver; At least one processor communicatively coupled to the above at least one transceiver; and It includes at least one memory that is communicationally coupled to the above at least one processor and stores instructions, and The above instructions are executed individually or in any combination by the above at least one processor, so that the base station: Transmit configuration information to the terminal (user equipment) for obtaining channel feature information and channel state feature information, and Based on the channel state information of the terminal obtained based on the above setting information, the channel feature information is obtained, and Based on the channel feature information obtained above and the channel state information at a predetermined point in time of the terminal, the channel state feature information is obtained, and A base station that performs scheduling based on the above channel feature variables, the above channel state feature variables, and the above channel state information.

11. In Paragraph 10, The above configuration information is transmitted to the terminal via a cell system information block (SIB) while the terminal performs cell search and cell synchronization, and A base station, wherein the above-mentioned configuration information includes information regarding a method for obtaining the channel feature information based on the reference signal, and information regarding a method for obtaining the channel state feature information based on the reference signal.

12. In Paragraph 10, The above channel feature information includes information on the channel distribution function of a downlink channel obtained based on a downlink (DL) reference signal (RS) and information on the channel distribution function of an uplink channel obtained based on an uplink (UL) reference signal, comprising a base station.

13. In Paragraph 10, The above channel feature information includes information on the channel distribution function of a downlink channel obtained based on a downlink (DL) reference signal (RS) and information on the channel distribution function of an uplink channel obtained based on an uplink (UL) reference signal, comprising a base station.

14. In Paragraph 10, The above commands are the above base station: The above channel feature information is stored in memory, and A base station that stores the channel feature information in the above memory.

15. In a wireless communication system, regarding a terminal (user equipment): At least one transceiver; At least one processor communicatively coupled to the above at least one transceiver; and It includes at least one memory that is communicationally coupled to the above at least one processor and stores instructions, and The above instructions are executed individually or in any combination by the above at least one processor, so that the terminal: Receive configuration information from a base station to obtain channel feature information and channel state feature information, and Transmitting to the base station the channel characteristic information associated with the downlink channel environment based on the channel state information of the terminal obtained based on the setting information and the downlink reference signal received from the base station, and Transmitting channel state feature information to the base station based on the acquired channel feature information and channel state information at a predetermined point in time of the terminal, and A terminal configured to receive information regarding scheduling performed based on the channel feature variable, the channel state feature variable, and the channel state information from the base station.

Images