Network node and method for scheduling

Abstract

This network node may comprise: a memory storing instructions and including one or more storage media; and at least one processor including a processing circuit. The instructions, when executed individually or collectively by the at least one processor, may cause the network node to: generate throughput information for each of terminals; calculate a scheduling metric for each of the terminals by applying a weight to the throughput information about each of the terminals; identify, on the basis of the scheduling metric for each of the terminals, a terminal having a maximum scheduling metric among the terminals; and allocate a resource to the terminal.

Description

Network nodes and methods for scheduling

[0001] The descriptions below relate to network nodes and methods for scheduling.

[0002] In a wireless communication system, a base station can allocate resources to terminals for wireless communication. To increase cell throughput and / or terminal throughput, the base station can identify terminals connected to the base station to which resources will be allocated.

[0003] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above-described matters constitute prior art related to the present disclosure.

[0004] A network node is provided. The network node may include a memory storing instructions and including one or more storage media. The network node may include at least one processor including a processing circuit. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to generate throughput information for each of the terminals based on the amount of traffic of the terminal and the occupancy period for which the traffic remains in a buffer for the terminal. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to calculate a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the throughput information for each of the terminals relative to the sum of the occupancy periods of the terminals. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify a terminal among the terminals having a maximum scheduling metric based on the scheduling metric for each of the terminals. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform resource allocation to the terminal.

[0005] A method is provided. The method can be executed within a network node. The method can include generating throughput information for each terminal based on the amount of traffic of the terminal and the occupancy period during which the traffic remains in a buffer for the terminal. The method can include calculating a scheduling metric for each terminal by applying a weight corresponding to the occupancy period of the terminal to the sum of the occupancy periods of the terminals to the throughput information for each terminal. The method can include identifying a terminal having a maximum scheduling metric among the terminals based on the scheduling metric for each terminal. The method can include performing resource allocation to the terminal.

[0006] A non-transitory computer-readable storage medium is provided. The non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by a network node, cause the network node to generate throughput information for each of the terminals based on the amount of traffic of the terminal and the occupancy period that the traffic remains in the buffer for the terminal. The one or more programs may include instructions that, when executed by the network node, cause the network node to calculate a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the sum of the occupancy periods of the terminals to the throughput information for each of the terminals. The one or more programs may include instructions that, when executed by the network node, cause the network node to identify, based on the scheduling metric for each of the terminals, a terminal having a maximum scheduling metric among the terminals. The one or more programs may include instructions that, when executed by the network node, cause the network node to perform resource allocation to the terminal.

[0007] Figure 1 illustrates an example of a wireless communication system.

[0008] Figure 2 illustrates an example of an interface between an upper network node and a lower network node.

[0009] Figure 3 illustrates an example of the functional configuration of a network node.

[0010] Figure 4 illustrates an example of a resource structure in the time domain and frequency domain.

[0011] Figures 5a and 5b illustrate examples of scheduling methods.

[0012] Figure 6 illustrates an example of traffic within a buffer in a partial buffer environment.

[0013] Figure 7 illustrates an example of operations in which a network node performs resource allocation to a terminal.

[0014] Figure 8 illustrates examples of operations in which a network node performs resource allocation to a combination of terminals.

[0015] FIGS. 9A to 9D illustrate examples of the performance of scheduling according to embodiments of the present disclosure in a non-CA (non-carrier aggregation) environment.

[0016] FIGS. 10A to 10D illustrate examples of the performance of scheduling according to embodiments of the present disclosure in a carrier aggregation (CA) environment.

[0017] The terms used in this disclosure are used only to describe specific embodiments and may not be intended to limit the scope of other embodiments. The singular expression may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by those of ordinary skill in the art described in this disclosure. Terms defined in general dictionaries among the terms used in this disclosure may be interpreted as having the same or similar meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined in this disclosure. In some cases, even if a term is defined in this disclosure, it cannot be interpreted to exclude embodiments of the present disclosure.

[0018] The various embodiments of the present disclosure described below illustrate a hardware-based approach as an example. However, since the various embodiments of the present disclosure include techniques utilizing both hardware and software, the various embodiments of the present disclosure do not exclude a software-based approach.

[0019] In the following description, terms referring to signals (e.g., packet, message, signal, information, signaling), terms referring to resources (e.g., section, symbol, slot, subframe, radio frame, subcarrier, RE (resource element), RB (resource block), BWP (bandwidth part), band, spectrum), terms for operational states (e.g., step, operation, procedure), terms referring to data (e.g., packet, message, user stream, information, bit, symbol, codeword), terms referring to channels, terms referring to network entities (distributed unit (DU), radio unit (RU), central unit (CU), control plane (CU-CP), user plane (CU-UP), open radio access network (O-RAN) DU (O-DU), O-RAN RU (O-RU), Terms such as O-CU (O-RAN CU), O-CU-UP (O-RAN CU-CP), O-CU-CP (O-RAN CU-CP)), referring to components of the device, are examples for convenience of explanation. Therefore, the present disclosure is not limited to the terms described below, and other terms having equivalent technical meanings may be used. In addition, terms such as '... part', '... device', '... object', '... body', etc. used below may mean at least one shape structure or a unit that processes a function.

[0020] In addition, in the present disclosure, expressions such as "more than" or "less than" may be used to determine whether a specific condition is satisfied or fulfilled, but this is merely a description for expressing an example and does not exclude descriptions such as "more than" or "less than." A condition described as "more than" may be replaced with "more than," a condition described as "less than" may be replaced with "less than," and a condition described as "more than and less than" may be replaced with "more than and less than." In addition, hereinafter, "A" to "B" mean at least one of elements from A (including A) to B (including B). hereinafter, "C" and / or "D" mean at least one of "C" or "D," that is, including {"C", "D", "C" and "D"}.

[0021] Although this disclosure describes embodiments using terminology used in certain communication standards (e.g., 3rd Generation Partnership Project (3GPP)), this is merely an example for illustrative purposes. Embodiments of this disclosure can also be applied to other communication and broadcasting systems.

[0022] Figure 1 illustrates an example of a wireless communication system.

[0023] Referring to FIG. 1, FIG. 1 illustrates a base station (110) and a terminal (120) as some of the nodes utilizing a wireless channel in a wireless communication system. Although FIG. 1 illustrates only one base station, the wireless communication system may further include other base stations identical or similar to the base station (110).

[0024] The base station (110) is a network infrastructure that provides wireless access to the terminal (120). The base station (110) has coverage defined based on the distance at which a signal can be transmitted. In addition to the base station, the base station (110) may be referred to as an 'access point (AP)', 'eNodeB (eNB)', '5th generation node', 'next generation nodeB (gNB)', 'wireless point', 'transmission / reception point (TRP)', or other terms having equivalent technical meanings.

[0025] The terminal (120) is a device used by a user and communicates with the base station (110) via a wireless channel. The link from the base station (110) to the terminal (120) is referred to as a downlink (DL), and the link from the terminal (120) to the base station (110) is referred to as an uplink (UL). In addition, although not shown in FIG. 1, the terminal (120) and another terminal may communicate with each other via a wireless channel. In this case, the link between the terminal (120) and another terminal (device-to-device link, D2D) is referred to as a sidelink, and the sidelink may be used interchangeably with the PC5 interface. In some other embodiments, the terminal (120) may be operated without the involvement of a user. In one embodiment, the terminal (120) is a device that performs machine type communication (MTC) and may not be carried by the user. Additionally, according to one embodiment, the terminal (120) may be an NB (narrowband)-IoT (internet of things) device.

[0026] The terminal (120) may be referred to as a terminal, or other terms such as 'user equipment (UE),' 'customer premises equipment (CPE),' 'mobile station,' 'subscriber station,' 'remote terminal,' 'wireless terminal,' 'electronic device,' or 'user device,' or other terms having equivalent technical meanings.

[0027] The base station (110) and the terminal (120) can perform beamforming. The base station (110) and the terminal (120) can transmit and receive wireless signals in a relatively low frequency band (e.g., FR 1 (frequency range 1) of NR). In addition, the base station (110) and the terminal (120) can transmit and receive wireless signals in a relatively high frequency band (e.g., FR 2 (or, FR 2-1, FR 2-2, FR 2-3), FR 3 of NR), millimeter wave (mmWave) band (e.g., 28 GHz, 30 GHz, 38 GHz, 60 GHz)). To improve channel gain, the base station (110) and the terminal (120) can perform beamforming. Here, the beamforming can include transmission beamforming and reception beamforming. The base station (110) and the terminal (120) can provide directionality to the transmitted or received signal. To this end, the base station (110) and the terminal (120) can select serving beams through a beam search or beam management procedure. After the serving beams are selected, subsequent communication can be performed through resources that are in a quasi-co-located (QCL) relationship with the resource that transmitted the serving beams.

[0028] If large-scale characteristics of a channel carrying a symbol on a first antenna port can be inferred from a channel carrying a symbol on a second antenna port, the first antenna port and the second antenna port can be evaluated to have a QCL relationship. For example, the large-scale characteristics may include at least one of delay spread, Doppler spread, Doppler shift, average gain, average delay, and a spatial receiver parameter.

[0029] Although both the base station (110) and the terminal (120) are described as performing beamforming in FIG. 1, the embodiments of the present disclosure are not necessarily limited thereto. In some embodiments, the terminal may or may not perform beamforming. Furthermore, the base station may or may not perform beamforming. That is, either only one of the base station and the terminal may perform beamforming, or neither the base station nor the terminal may perform beamforming.

[0030] In the present disclosure, a beam refers to a spatial flow of a signal in a wireless channel, and is formed by one or more antennas (or antenna elements), and this forming process may be referred to as beamforming. Beamforming may include at least one of analog beamforming and digital beamforming (e.g., precoding). Reference signals transmitted based on beamforming may include, for example, a demodulation-reference signal (DM-RS), a channel state information-reference signal (CSI-RS), a synchronization signal / physical broadcast channel (SS / PBCH), and a sounding reference signal (SRS). In addition, as a configuration for each reference signal, an IE such as a CSI-RS resource or an SRS-resource may be used, and this configuration may include information associated with the beam. Information associated with a beam may mean whether the configuration (e.g., a CSI-RS resource) uses the same spatial domain filter as another configuration (e.g., another CSI-RS resource within the same CSI-RS resource set) or a different spatial domain filter, or whether it is QCLed with a reference signal, and if so, what type it is (e.g., QCL type A, B, C, D).

[0031] In the past, in communication systems with relatively large cell radius of base stations, each base station was installed to include the functions of a digital processing unit (or distributed unit (DU)) and a radio frequency (RF) processing unit (or radio unit (RU)). However, as higher frequency bands are used in 4G (4th generation) and / or subsequent communication systems (e.g., 5G) and the cell coverage of base stations becomes smaller, the number of base stations to cover a specific area has increased. The installation costs for operators to install base stations have also increased. In order to minimize the installation costs of base stations, a structure has been proposed in which the DU and RU of a base station are separated, one or more RUs are connected to one DU via a wired network, and one or more RUs are geographically distributed to cover a specific area. Hereinafter, the deployment structure and expansion examples of base stations according to various embodiments of the present disclosure are described through FIG. 2.

[0032] Figure 2 illustrates an example of an interface between an upper network node and a lower network node.

[0033] FIG. 2 illustrates an interface between an upper network node and a lower network node. The interface between the upper network node and the lower network node may include a fronthaul interface. Fronthaul refers to entities between a wireless LAN and a base station, unlike backhaul between a base station and a core network. FIG. 2 illustrates an example of a fronthaul structure between an upper network node (210) and one lower network node (220), but this is merely for convenience of explanation and the present disclosure is not limited thereto. In other words, embodiments of the present disclosure may also be applied to a fronthaul structure between one upper network node and multiple lower network nodes. For example, embodiments of the present disclosure may be applied to a fronthaul structure between one upper network node and two lower network nodes. Furthermore, embodiments of the present disclosure may also be applied to a fronthaul structure between one upper network node and three lower network nodes.

[0034] For example, an upper network node may include a digital unit / distributed unit (DU). The upper network node may be referred to as a DU. A lower network node may include a radio unit (RU) or a massive MIMO unit (MMU). The lower network node may be referred to as a RU or an MMU.

[0035] Referring to FIG. 2, a base station (110) may include an upper network node (210) and a lower network node (220). A fronthaul (215) between the upper network node (210) and the lower network node (220) may be operated via an Fx interface. For operation of the fronthaul (215), an interface such as an enhanced common public radio interface (eCPRI) or radio over ethernet (ROE) may be used, for example.

[0036] As communication technology develops, mobile data traffic increases, and accordingly, the bandwidth demand required in the fronthaul between the digital unit and the wireless unit has increased significantly. In a deployment such as a centralized / cloud radio access network (C-RAN), an upper network node (210) performs functions for packet data convergence protocol (PDCP), radio link control (RLC), media access control (MAC), and physical (PHY), and a lower network node (220) may be implemented to perform functions for the PHY layer in addition to the RF (radio frequency) function.

[0037] The upper network node (210) may be responsible for upper layer functions of a wireless network. For example, the upper network node (210) may perform functions of the MAC layer and a part of the PHY layer. Here, a part of the PHY layer refers to functions performed at a higher level among the functions of the PHY layer, and may include, for example, channel encoding (or channel decoding), scrambling (or descrambling), modulation (or demodulation), and layer mapping (or layer demapping). According to an embodiment, when the upper network node (210) complies with the O-RAN standard, it may be referred to as an O-DU (O-RAN DU) (or DU). The upper network node (210) may be replaced with a first network entity or DU for a base station (e.g., gNB) in embodiments of the present disclosure, as needed.

[0038] The lower network node (220) may be responsible for lower layer functions of the wireless network. For example, the lower network node (220) may perform a part of the PHY layer, an RF function. Here, a part of the PHY layer refers to functions of the PHY layer that are performed at a relatively lower level than the upper network node (210), and may include, for example, iFFT transformation (or FFT transformation), CP (cyclic prefix) insertion (CP removal), and digital beamforming. The lower network node (220) may be referred to as an 'access unit (AU)', 'access point (AP)', 'transmission / reception point (TRP)', 'remote radio head (RRH)', 'radio unit (RU)', or other terms having an equivalent technical meaning thereto. In one embodiment, if a lower network node (220) complies with the O-RAN standard, it may be referred to as an O-RU (O-RAN RU) (or RU). The lower network node (220) may be replaced with a second network entity or RU for a base station (e.g., gNB) in embodiments of the present disclosure, as needed.

[0039] Although the above example describes that the upper network node (210) includes a DU and the lower network node (220) includes an RU, the embodiments of the present disclosure are not limited thereto. A base station according to the embodiments may be implemented in a distributed deployment according to a centralized unit (CU) configured to perform functions of upper layers of an access network (e.g., packet data convergence protocol (PDCP), radio resource control (RRC)) and a distributed unit (DU) configured to perform functions of lower layers. At this time, the distributed unit (DU) may include a digital unit (DU) and a radio unit (RU). Between a core (e.g., 5GC (5G core) or NGC (next generation core)) network and a radio network (RAN), the base station may be implemented in a structure in which CU, DU, and RU are arranged in that order. The interface between the CU and the distributed unit (DU) may be referred to as an F1 interface.

[0040] For example, a centralized unit (CU) may be connected to one or more DUs and may be responsible for functions at a higher layer than the DU. For example, the CU may be responsible for functions at the RRC (radio resource control) and PDCP (packet data convergence protocol) layers, while the DU and RU may be responsible for functions at lower layers. The DU may perform some functions (high PHY) of the RLC (radio link control), MAC (media access control), and PHY (physical) layers, and the RU may be responsible for the remaining functions (low PHY) of the PHY layer. In addition, for example, a digital unit (DU) may be included in a distributed unit (DU) depending on the implementation of a distributed deployment of a base station. Hereinafter, unless otherwise defined, the operations of DU and RU are described, but various embodiments of the present disclosure can be applied to both a base station deployment including a CU and a deployment in which the DU is directly connected to the core network (i.e., a base station in which the CU and DU are integrated into a single entity (e.g., an NG-RAN node)).

[0041] Figure 3 illustrates an example of the functional configuration of a network node.

[0042] The configuration of the network node (300) illustrated in Fig. 3 can be understood as a configuration of a base station (110), a terminal (120), an upper network node (210), a lower network node (220), or a server. Terms such as "...unit" and "...unit" used hereinafter mean a unit that processes at least one function or operation, and this can be implemented by hardware, software, or a combination of hardware and software.

[0043] Referring to FIG. 3, the network node (300) may include a transceiver (310), a memory (320), and a processor (330). However, the present disclosure is not limited thereto. For example, the network node (300) may not include at least some of the components illustrated in FIG. 3, or may include further components not illustrated in FIG. 3.

[0044] The transceiver (310) may perform functions for transmitting and receiving signals in a wired communication environment. The transceiver (310) may include a wired interface for controlling direct connection between devices via a transmission medium (e.g., copper wire, optical fiber). For example, the transceiver (310) may transmit an electrical signal to another device via copper wire or perform conversion between an electrical signal and an optical signal. According to one embodiment, the network node (300) may communicate with a radio unit (RU) via the transceiver (310). In this respect, the transceiver (310) may be referred to as a fronthaul transceiver. As a non-limiting example, the network node (300) may be connected to a core network or a CU in a distributed arrangement via the transceiver (310).

[0045] The transceiver (310) may perform functions for transmitting and receiving signals in a wireless communication environment. For example, the transceiver (310) may perform a conversion function between a baseband signal and a bit stream according to the physical layer specifications of the system. For example, when transmitting data, the transceiver (310) generates complex symbols by encoding and modulating the transmitted bit stream. In addition, when receiving data, the transceiver (310) restores the received bit stream by demodulating and decoding the baseband signal. In addition, the transceiver (310) may include multiple transmission and reception paths. In addition, according to one embodiment, the transceiver (310) may be connected to the core network or other nodes (e.g., an integrated access backhaul (IAB).

[0046] The transceiver (310) can transmit and receive signals. The transceiver (310) can function as a fronthaul transceiver. For example, the network node (300) can transmit or receive a management plane (M-plane) message through the transceiver (310). For example, the network node (300) can transmit or receive a management plane (S-plane) message through the transceiver (310). For example, the network node (300) can transmit or receive a control plane (C-plane) message through the transceiver (310). For example, the network node (300) can transmit or receive a user plane (U-plane) message through the transceiver (310). Although only the transceiver (310) is illustrated in FIG. 3, according to another implementation example, the network node (300) may include two or more transceivers.

[0047] The transceiver (310) transmits and receives signals as described above. Accordingly, all or part of the transceiver (310) may be referred to as a "communication unit," a "transmitter," a "receiver," or a "transmitter-receiver unit." Furthermore, in the following description, transmission and reception performed via a wireless channel are used to mean that the transceiver (310) performs the processing described above.

[0048] Although not illustrated in FIG. 3, the transceiver (310) may further include a backhaul transceiver for connection to the core network or other base stations. The backhaul transceiver provides an interface for communicating with other nodes within the network. That is, the backhaul transceiver converts a bit stream transmitted from the base station to other nodes, such as other access nodes, other base stations, upper nodes, the core network, etc., into a physical signal, and converts a physical signal received from other nodes into a bit stream.

[0049] The memory (320) stores data such as basic programs, application programs, and setting information for the operation of the network node (300). The memory (320) may be referred to as a storage unit. The memory (320) may store instructions for the operations of the upper network node (210). The memory (320) may be composed of volatile memory, nonvolatile memory, or a combination of volatile memory and nonvolatile memory. In addition, the memory (320) provides the stored data according to the request of the processor (330).

[0050] The processor (330) controls the overall operations of the network node (300). The processor (330) may be referred to as a control unit. The processor (330) may include control circuits and / or processing circuits. For example, the processor (330) transmits and receives signals via the transceiver (310) (or via the backhaul communication unit). In addition, the processor (330) writes and reads data to and from the memory (320). In addition, the processor (330) may perform the functions of the protocol stack required by the communication standard. Although only the processor (330) is illustrated in FIG. 3, the network node (300) may include two or more processors according to other implementation examples.

[0051] For example, the processor (330) may include various processing circuits and / or multiple processors. For example, the term "processor" as used herein, including in the claims, may include various processing circuits including at least one processor, one or more of which may be configured to individually and / or collectively perform the various functions described below in a distributed manner. As used herein, when "processor," "at least one processor," and "one or more processors" are described as being configured to perform various functions, these terms encompass situations where one processor performs some of the recited functions and other processor(s) perform other parts of the recited functions, and / or situations where one processor can perform all of the recited functions. Additionally, the at least one processor may include a combination of processors that perform the various functions enumerated / disclosed, for example, in a distributed manner. At least one processor may execute program instructions to achieve or perform the various functions.

[0052] The configuration of the network node (300) illustrated in FIG. 3 is merely an example, and examples of network nodes (300) that perform embodiments of the present disclosure are not limited to the configuration illustrated in FIG. 3. In some embodiments, some configurations may be added, deleted, or changed.

[0053] Figure 4 illustrates an example of a resource structure in the time domain and frequency domain. Figure 4 illustrates the basic structure of the time-frequency domain, which is a radio resource region where data or control channels are transmitted in the downlink or uplink.

[0054] Referring to Fig. 4, the horizontal axis represents the time domain, and the vertical axis represents the frequency domain. The minimum transmission unit in the time domain is an orthogonal frequency division multiplexing (OFDM) symbol, and Nsymb OFDM symbols (402) are grouped to form one subframe (406). The length of the subframe is defined as 1.0 ms, and the length of the radio frame (414) is defined as 10 ms. The minimum transmission unit in the frequency domain is a subcarrier, and the carrier bandwidth constituting the resource grid is composed of NDLRB (downlink) or NULRB (uplink) subcarriers (404).

[0055] The basic unit of resources in the time-frequency domain is a resource element (RE) (412), which can be represented by an OFDM symbol index and a subcarrier index. A resource block may include multiple resource elements. In an LTE system, a resource block (RB) (or physical resource block (PRB)) is defined by Nsymb consecutive OFDM symbols in the time domain and NSCRB consecutive subcarriers in the frequency domain. In an NR system, a resource block (RB) (408) may be defined by NSCRB consecutive subcarriers (410) in the frequency domain. One RB (408) includes NSCRB REs (412) in the frequency domain. Generally, the minimum transmission unit of data is an RB, and the number of subcarriers is NSCRB=12. The frequency domain may include common resource blocks (CRBs). Physical resource blocks (PRBs) can be defined in the bandwidth part (BWP) of the frequency domain. The CRB and PRB numbers can be determined based on subcarrier spacing. The data rate can increase proportionally to the number of RBs scheduled to the terminal.

[0056] In the NR system, in the case of a frequency division duplex (FDD) system that operates the downlink and uplink by frequency division, the downlink transmission bandwidth and the uplink transmission bandwidth may be different. The channel bandwidth represents the radio frequency (RF) bandwidth corresponding to the system transmission bandwidth. [Table 1] shows part of the correspondence between the system transmission bandwidth, subcarrier spacing (SCS), and channel bandwidth defined in the NR system in a frequency band lower than x GHz (e.g., frequency range (FR) 1 (410 MHz to 7125 MHz)). And [Table 2] shows part of the correspondence between the transmission bandwidth, subcarrier spacing, and channel bandwidth defined in the NR system in a frequency band higher than y GHz (e.g., FR2 (24250 MHz - 52600 MHz) or FR2-2 (52600 MHz to 71000 MHz)). For example, an NR system with a 100 MHz channel bandwidth and a 30 kHz subcarrier spacing has a transmission bandwidth of 273 RBs. In [Table 1] and [Table 2], N / A may indicate a bandwidth-subcarrier combination not supported by the NR system.

[0057]

[0058]

[0059] For example, resources may be allocated to the terminal (120) from the network node (300). For example, the resources may include resources for uplink or downlink. However, the present disclosure is not limited thereto. For example, the resources may include resources for a sidelink between the terminal (120) and another terminal. For example, the network node (300) may perform resource allocation using a report message obtained from the terminal (120). For example, the report message may include at least one of terminal information, which is information about the terminal, configuration information set for the terminal, or measurement information measured by the terminal. For example, the report message may be included in channel state information (CSI). For example, the report message may include parameters related to DC or CA to utilize simultaneous access technology (e.g., dual connectivity (DC)) or CA, or to secure a priority for requesting as many resources to be allocated from DC or CA as possible. As mentioned above, the report message may include parameters that may influence resource allocation (or PF scheduling, PF priority). For example, each piece of information included in the report message may be referenced as a parameter.

[0060] For example, the network node (300) can perform scheduling. For example, the scheduler of the MAC (media access control) layer of the network node (300) can perform resource allocation to multiple terminals through proportional fair (PF) scheduling. For example, the scheduler can be included in the network node (300), the upper network node (210) (or DU), or the base station (110). In the examples below, the resource is described as an example of a frequency resource, but the present disclosure is not limited thereto.

[0061] For example, PF scheduling is described and illustrated in more detail with reference to FIGS. 5a and 5b.

[0062] Figures 5a and 5b illustrate examples of scheduling methods. Scheduling may refer to the process of allocating resources (e.g., time-frequency resources) for wireless communication. For example, a network node (300) (e.g., a base station (110), an upper network node (210), a lower network node (220)) may allocate resources to a terminal (e.g., a terminal (120)). The network node (300) may transmit resource allocation information indicating the resources allocated to the terminal to the terminal. More specifically, scheduling (or a scheduling algorithm) may be described as a method of allocating available resources within a wireless communication system to multiple terminals in order to efficiently utilize limited resources in the wireless communication system. The network node (300) may allocate resources to one or more terminals per TTI (transmission time interval) through scheduling. For example, scheduling may be performed by the network node (300). For example, scheduling can be controlled by the processor (330) of the network node (300). For example, the network node (300) can identify terminals for which resource allocation is to be performed by performing scheduling.

[0063] In general, a network node (300) can perform fair resource allocation for terminals receiving services from the network node (300). For example, the PF scheduling (or PF scheduling algorithm) can be utilized for the fair resource allocation. For example, the network node (300) can perform resource allocation according to the channel status of each terminal while maintaining the maximum performance of the network (or system).

[0064] For example, PF scheduling may be an example of a scheduling method. For example, a network node (300) may allocate resources to multiple terminals based on the channel conditions of each of the multiple terminals according to PF scheduling. For example, the network node (300) may allocate resources to a terminal (or combination of terminals) among the multiple terminals that has the highest channel condition quality according to PF scheduling.

[0065] For example, the scheduler (520) may indicate a terminal (or combination of terminals) for which resource allocation is to be performed among the terminals (511) within the cell of the network node (300). For example, the terminal for which resource allocation is to be performed may be identified by the network node (300) performing scheduling.

[0066] For example, the network node (300) may perform resource allocation to terminal (511-1) in TTI (521). For example, in TTI (521), the channel state (or wireless link state) of terminal (511-1) may indicate that it is better than the channel state of terminal (511-2) or the channel state of terminal (511-3). For example, a good channel state may include high channel quality.

[0067] For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-1) and terminal (511-3) in TTI (522). For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-2) and terminal (511-3) in TTI (523).

[0068] For example, the network node (300) can identify a terminal (or combination of terminals) for which resource allocation will be performed among the terminals (511) using PF scheduling in the TTI (524). For example, the method for the network node (300) to select a terminal for which resource allocation will be performed using PF scheduling can be referred to the following mathematical formula.

[0069]

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076] For example, when a network node (300) schedules one terminal in each TTI, PF scheduling in TTI n can be expressed by the following mathematical formula.

[0077]

[0078]

[0079] For example, the mathematical formulas described above can be derived by applying an environment different from the actual buffer environment. For example, the mathematical formulas described above can be derived by applying an environment in which the terminal buffer is always occupied by traffic. For example, an environment in which the terminal buffer is always occupied by traffic can be defined as a full buffer environment. For example, the full buffer environment may not reflect the different buffer occupancy (BO) of each terminal or the head-of-line (HOL) delay time of packets.

[0080] For example, the actual buffer environment may resemble a partial buffer environment rather than the full buffer environment described above. For example, the partial buffer environment may be defined as an environment in which each terminal has a different buffer occupancy rate. For example, the scheduling policy calculated using the full buffer environment may have lower quality than the scheduling policy calculated using the partial buffer environment described below.

[0081] For example, to improve the efficiency of resource allocation of a network node (300), a scheduling policy that applies an environment more similar to the actual environment than the full buffer environment may be required. For example, a scheduling policy applying the partial buffer environment will be described and exemplified in more detail with reference to FIG. 6.

[0082] Referring to FIG. 5b, the network node (300) can provide wireless communication services using multiple frequencies. For example, the network node (300) can transmit traffic to and receive traffic from terminals (511) within a cell using multiple channels.

[0083] For example, a network node (300) can increase the capacity and transmission speed of traffic within a cell by utilizing multiple channels. For example, a network node (300) can expand the bandwidth of a wireless communication system by utilizing multiple frequencies.

[0084] For example, the network node (300) can identify a terminal (or combination of terminals) for which resource allocation will be performed among the terminals (511) within the cell for each channel. For example, the network node (300) can identify a terminal for which resource allocation will be performed among the terminals (511) within the cell for each channel by performing scheduling. For example, the scheduling may include PF scheduling.

[0085] For example, the scheduler (530) may indicate, in a first channel, a terminal (or a combination of terminals) for which resource allocation is to be performed among the terminals (511) within the cell of the network node (300). For example, the scheduler (540) may indicate, in a second channel, a terminal (or a combination of terminals) for which resource allocation is to be performed among the terminals (511) within the cell of the network node (300). For example, the first channel and the second channel may use different frequencies.

[0086] For example, referring to the scheduler (530), the network node (300) may perform resource allocation to the terminal (511-1) in the TTI (531) of the first channel. For example, in the TTI (531) of the first channel, the channel state (or wireless link state) of the terminal (511-1) may be indicated to be better than the channel state of the terminal (511-2) or the channel state of the terminal (511-3).

[0087] For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-1) and terminal (511-3) in the TTI (532) of the first channel. For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-2) and terminal (511-3) in the TTI (533) of the first channel.

[0088] For example, referring to the scheduler (540), the network node (300) may perform resource allocation to a combination of terminals including terminal (511-1) and terminal (511-2) in a TTI (531) of a second channel. For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-2) and terminal (511-3) in a TTI (532) of a second channel. For example, the network node (300) may perform resource allocation to a combination of terminals including terminal (511-2) and terminal (511-3) in a TTI (533) of a second channel.

[0089] For example, the network node (300) can identify a terminal (or combination of terminals) for which resource allocation will be performed among the terminals (511) for each channel by scheduling in the TTI (534). For example, the network node (300) may require a scheduling policy that applies an environment more similar to an actual environment than the full buffer environment for each of the plurality of channels. For example, a scheduling policy that applies the partial buffer environment will be described and exemplified in more detail with reference to FIG. 6.

[0090] Although resource allocation is illustrated for two channels in Fig. 5b, this is merely exemplary. For example, a network node (300) may utilize two or more channels.

[0091] Figure 6 illustrates an example of traffic within a buffer in a partial buffer environment. For example, in a partial buffer environment, the size of the traffic occupying each terminal's buffer may vary. For example, in a partial buffer environment, since the size of the traffic occupying each terminal's buffer varies, the network node (300) can perform scheduling by considering the traffic occupying each terminal's buffer.

[0092] Referring to FIG. 6, the network node (300) may consider the occupancy period (640) during which traffic remains within the buffer for each terminal for scheduling purposes applying a partial buffer environment. For example, the occupancy period (640) may be represented as the period between time points (610) and (630). For example, the occupancy period (640) may be represented as the sum of a first period (650) and a second period (660).

[0093] For example, the first period (650) can be represented as the period between time points (610) and (620). For example, time point (610) can be described as the time point at which traffic (or packets) arrives at an empty buffer. For example, time point (620) can be described as the time point at which transmission of the arrived traffic begins. For example, the first period (650) can be defined as IP-latency (internet protocol latency).

[0094] For example, the second period (660) may be represented as the period between time points (620) and (630). For example, time point (630) may be described as the time point at which all arriving traffic has been transmitted. For example, time point (630) may be represented as the time point after time point (610) at which the buffer becomes empty. For example, the second period (660) may be defined as IP-time (Internet Protocol Time).

[0095] For example, a scheduling method may be proposed in which a network node (300) selects a terminal to which resource allocation will be performed, taking into account the occupancy period (640). For example, a scheduling method in which a network node (300) selects a terminal to which resource allocation will be performed, taking into account the occupancy period (640), may be defined as perceived throughput-aware proportional fair (PTPF) scheduling. For example, a scheduling method in which a network node (300) selects a terminal to which resource allocation will be performed, taking into account the occupancy period (640), may refer to the following mathematical equation.

[0096]

[0097]

[0098] For example, terminal perceived throughput at TTI n can be defined by the following mathematical equation. For example, the terminal perceived throughput can be expressed as user perceived throughput (UPT) or throughput information for each terminal.

[0099]

[0100]

[0101]

[0102]

[0103]

[0104] For example, the scheduling policy of scheduling (e.g., PTPF scheduling) according to embodiments of the present disclosure may be referred to by the following mathematical formula.

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130] For example, the mathematical expression derived by applying the above mathematical expression 15 to the above mathematical expression 10 can be expressed as the following mathematical expression.

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137] For example, a method for performing resource allocation using scheduling (e.g., PTPF scheduling) as illustrated in FIG. 6 may be executed in a network node (300). For example, such a method is described and illustrated in more detail in FIG. 7.

[0138] Figure 7 illustrates an example of operations in which a network node performs resource allocation to a terminal.

[0139] Referring to FIG. 7, in operation 711, the network node (300) may generate throughput information for each terminal. For example, the throughput information for each terminal may be generated based on the amount of traffic for the corresponding terminal and the occupancy period (640) for which traffic remains within the buffer for the corresponding terminal. For example, the throughput information for each terminal may include the terminal-recognized throughput of Equation 6.

[0140]

[0141]

[0142]

[0143]

[0144]

[0145] For example, in operation 714, the network node (300) may perform resource allocation to the identified terminal. For example, the network node (300) may correspond to an upper network node (210) or a DU (distributed unit). For example, the network node (300) may transmit information regarding the resource allocation to the identified terminal through a lower network node (220) or a RU (radio unit). For example, the RU may be connected to the DU. For example, the upper network node (210) may be connected to a lower network node (220).

[0146] FIG. 7 illustrates that a network node (300) performs resource allocation to one terminal with the maximum scheduling metric, but this is merely exemplary.

[0147] For example, the network node (300) can determine the number of candidate terminals for which resource allocation will be performed by the network node (300). For example, the network node (300) can identify the number of terminals in order of the magnitude of the scheduling metric based on the scheduling metric for each terminal. For example, the identified number of terminals can include the terminal with the maximum scheduling metric. For example, the network node (300) can perform resource allocation to the identified number of terminals.

[0148] For example, the number of candidate terminals for which resource allocation is to be performed by the network node (300) may be two. For example, the network node (300) may identify, based on the scheduling metrics for each of the terminals, a first terminal having the largest scheduling metric among the terminals and a second terminal having a scheduling metric that is next to the scheduling metric of the first terminal among the terminals. For example, the network node (300) may perform resource allocation to the first terminal and the second terminal.

[0149] For example, the network node (300) may perform resource allocation to the first terminal in the first frequency domain. For example, the network node (300) may perform resource allocation to the second terminal in the second frequency domain. For example, the first frequency domain and the second frequency domain may have different component carriers (CCs).

[0150] According to one embodiment, the network node (300) can identify a combination of terminals for which the sum of the scheduling metrics of each terminal is maximized, based on the scheduling metrics for each terminal. For example, identifying a combination of terminals is described and illustrated in more detail in FIG. 8 .

[0151] Figure 8 illustrates examples of operations in which a network node performs resource allocation to a combination of terminals.

[0152] Referring to FIG. 8, operation 811 may be performed by the network node (300) in parallel with operation 711 or operation 712 of FIG. 7. For example, operation 811 may be performed by the network node (300) before operation 711, before operation 712, or after operation 712.

[0153] For example, in operation 811, the network node (300) may determine the number of candidate terminals for which resource allocation will be performed by the network node (300). For example, the network node (300) may determine the number based on the amount of resources available to the network node (300).

[0154] For example, in operation 812, terminals served by the cell of the network node (300) may include scheduling combinations according to the above number. For example, the network node (300) may identify, among the scheduling combinations, a scheduling combination having the largest sum of scheduling metrics of terminals included in the corresponding scheduling combination. For example, the network node (300) may identify, among the scheduling combinations, candidate terminals included in a scheduling combination having the largest sum of scheduling metrics of terminals included in the corresponding scheduling combination.

[0155] For example, in operation 813, the network node (300) may perform resource allocation to the candidate terminals included in the scheduling combination having the largest sum of the scheduling metrics.

[0156] FIGS. 9A to 9D illustrate examples of the performance of scheduling according to embodiments of the present disclosure in a non-CA (non-carrier aggregation) environment.

[0157]

[0158] For example, in the above simulation settings, the transmission bandwidth may be set to a specified value (e.g., 20 MHZ (megahertz)). For example, in the above simulation settings, the transmit signal to noise ratio may be set to a specified value (e.g., 10 dB (decibel)). For example, the above simulation may be run repeatedly for a specified number of times (e.g., 1000 times) for a specified period of time (e.g., 1 second).

[0159] For example, referring to FIG. 9A, chart (910) may represent the correlation between the number of terminals and throughput. For example, the throughput may include the cell recognition throughput of Equation 5. For example, the number of terminals may be represented by the number of terminals served by a cell of a network node. For example, in chart (910), the packet size may be set to a constant value (e.g., 90,000 bits) during simulation settings.

[0160] For example, line (911) may correspond to scheduling (e.g., PTPF scheduling) according to embodiments of the present disclosure. For example, line (912) may correspond to PF scheduling of FIG. 5A.

[0161] For example, line (913) may correspond to optimal scheduling from the perspective of cell recognition throughput. For example, the scheduling policy corresponding to line (913) may be referred to by the following mathematical formula.

[0162]

[0163]

[0164] For example, line (914) may correspond to optimal scheduling from the perspective of fairness between the terminal recognition processing capacities of each terminal. For example, scheduling corresponding to line (914) may ensure fairness among terminals. For example, the scheduling policy corresponding to line (914) may be referenced by the following mathematical formula.

[0165]

[0166]

[0167] For example, line (915) can correspond to scheduling that randomly identifies terminals and performs resource allocation to the identified terminals.

[0168] For example, in chart (910), the throughput for the number of terminals of line (911) may be higher than the throughput for the number of terminals of line (912), the throughput for the number of terminals of line (914), or the throughput for the number of terminals of line (915). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have a higher throughput performance for the number of terminals than PF scheduling.

[0169] For example, referring to FIG. 9B, chart (920) may represent the correlation between packet size and throughput. For example, the throughput may include the cell recognition throughput of Equation 5. For example, in chart (910), the number of terminals served by a cell of a network node during simulation setup may have a specified value (e.g., 30).

[0170] For example, in chart (920), the throughput for the packet size of line (911) may be higher than the throughput for the packet size of line (912), the throughput for the packet size of line (914), or the throughput for the packet size of line (915). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have a higher throughput performance for the packet size than PF scheduling.

[0171] For example, referring to FIG. 9c, chart (930) may represent the correlation between the number of terminals and a fairness index. For example, the number of terminals may be represented as the number of terminals served by a cell of a network node. For example, in chart (930), the packet size may be set to a constant value (e.g., 90,000 bits) during simulation settings.

[0172] For example, the larger the fairness index, the higher the fairness of the terminal recognition processing amount of the above mathematical expression 6. For example, the fairness index may include Jain's fairness index. For example, Jain's fairness index may be referenced by the following mathematical expression.

[0173]

[0174]

[0175] For example, in chart (930), the fairness index for the number of terminals of line (911) may be greater than the fairness index for the number of terminals of line (912), the fairness index for the number of terminals of line (913), or the fairness index for the number of terminals of line (915). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have fairness performance in terminal awareness throughput for a higher number of terminals than PF scheduling.

[0176] For example, referring to FIG. 9d, chart (940) may represent the correlation between packet size and fairness index. For example, in chart (940), the number of terminals served by a cell of a network node during simulation setup may have a specified value (e.g., 30).

[0177] For example, in chart (940), the fairness index for the number of terminals of line (911) may be greater than the fairness index for the number of terminals of line (912), the fairness index for the number of terminals of line (913), or the fairness index for the number of terminals of line (915). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have fairness performance in terminal-aware throughput for higher packet sizes than PF scheduling.

[0178] For example, referring to FIGS. 9A to 9D, in a non-CA environment, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may result in higher cell throughput performance and terminal throughput performance than PF scheduling.

[0179] FIGS. 10A to 10D illustrate examples of the performance of scheduling according to embodiments of the present disclosure in a carrier aggregation (CA) environment.

[0180] Figures 10a to 10d may include charts representing the results of a scheduling simulation. For example, Figures 10a to 10d illustrate that a CA environment utilizing a specific number (e.g., 5) of component carriers (CCs) may be configured in a scheduling simulation setting. For example, Figures 10a to 10d illustrate that in a scheduling simulation setting, the number of CCs (e.g., 3) available to each terminal may be less than the specific number. For example, Figures 10a to 10d illustrate that in a scheduling simulation setting, the number of CCs available to each terminal may be limited.

[0181]

[0182] For example, in the above simulation settings, the transmission bandwidth may be set to a specified value (e.g., 20 MHz). For example, in the above simulation settings, the transmit signal to noise ratio may be set to a specified value (e.g., 10 dB). For example, the above simulation may be repeated a specified number of times (e.g., 1000 times) for a specified period of time (e.g., 1 second).

[0183] For example, referring to FIG. 10A, chart (1010) may represent the correlation between the number of terminals and throughput. For example, the throughput may include the cell recognition throughput of Equation 5. For example, the number of terminals may be represented by the number of terminals served by a cell of a network node. For example, in chart (1010), the packet size may be set to a constant value (e.g., 200,000 bits) during simulation settings.

[0184] For example, line (1011) may correspond to scheduling (e.g., PTPF scheduling) according to embodiments of the present disclosure. For example, line (1012) may correspond to PF scheduling of FIG. 5A.

[0185] For example, line (1013) may correspond to optimal scheduling from the perspective of cell recognition throughput. For example, the scheduling policy corresponding to line (1013) may be referred to by the following mathematical formula.

[0186]

[0187]

[0188] For example, in chart (1010), the throughput for the number of terminals of line (1011) may be smaller than the throughput for the number of terminals of line (1012) when the number of terminals is 30 or less. For example, the throughput for the number of terminals of line (1011) may be larger than the throughput for the number of terminals of line (1012) when the number of terminals is 30 or more. The throughput for the number of terminals of line (1011) may be larger than the throughput for the number of terminals of line (1015).

[0189] For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have a higher throughput performance for a higher number of terminals than PF scheduling, as the number of terminals served by a cell of a network node (300) increases.

[0190] For example, referring to FIG. 10b, chart (1020) may represent the correlation between packet size and throughput. For example, the throughput may include the cell recognition throughput of Equation 5. For example, in chart (1010), the number of terminals served by a cell of a network node during simulation setup may have a specified value (e.g., 40).

[0191] For example, in chart (1020), the throughput for the packet size of line (1011) may be greater than the throughput for the packet size of line (1012) or the throughput for the packet size of line (1015). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have a higher throughput performance for packet sizes than PF scheduling.

[0192] For example, referring to FIG. 10c, chart (1030) may represent the correlation between the number of terminals and a fairness index. For example, the number of terminals may be represented as the number of terminals served by a cell of a network node. For example, in chart (1030), the packet size may be set to a constant value (e.g., 200,000 bits) during simulation settings.

[0193] For example, the larger the fairness index, the higher the fairness of the terminal recognition processing amount of the mathematical expression 6. For example, the fairness index may include the Jain's fairness index of the mathematical expression 17.

[0194] For example, in chart (1030), the fairness index for the number of terminals of line (1011) may be greater than the fairness index for the number of terminals of line (1012), the fairness index for the number of terminals of line (1013), or the fairness index for the number of terminals of line (1015). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have fairness performance of terminal awareness throughput for a higher number of terminals than PF scheduling.

[0195] For example, referring to FIG. 10d, chart (1040) may represent the correlation between packet size and fairness index. For example, in chart (1040), the number of terminals served by a cell of a network node during simulation setup may have a specified value (e.g., 40).

[0196] For example, in chart (1040), the fairness index for the number of terminals of line (1011) may be greater than the fairness index for the number of terminals of line (1012), the fairness index for the number of terminals of line (1013), or the fairness index for the number of terminals of line (1015). For example, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may have fairness performance in terminal-aware throughput for higher packet sizes than PF scheduling.

[0197] For example, referring to FIGS. 10A to 10D, in a CA environment, scheduling according to embodiments of the present disclosure (e.g., PTPF scheduling) may result in higher cell throughput performance and terminal throughput performance than PF scheduling.

[0198] A network node as described above may include a memory that stores instructions and includes one or more storage media. The network node may include at least one processor including a processing circuit. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to generate throughput information for each of the terminals based on the amount of traffic of the terminal and the occupancy period that the traffic remains in a buffer for the terminal. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to calculate a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the throughput information for each of the terminals relative to the sum of the occupancy periods of the terminals. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify a terminal among the terminals having a maximum scheduling metric based on the scheduling metric for each of the terminals. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform resource allocation to the terminal.

[0199] According to one embodiment, the occupancy period may be represented by the sum of a first period between the time when the traffic arrives at the buffer of the corresponding terminal and the time when the transmission of the traffic begins, and a second period between the time when the transmission of the traffic begins and the time when the transmission of the traffic is completed.

[0200] According to one embodiment, the identified terminal may be a terminal having the largest ratio of traffic transmission rate to processing amount information among the terminals.

[0201] In one embodiment, the network node may correspond to a distributed unit (DU). The instructions, when individually or collectively executed by the at least one processor, may cause the network node to transmit information about the resource allocation to the identified terminal via a radio unit (RU) connected to the DU.

[0202] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the network node to determine the number of candidate terminals for which the resource allocation is to be performed by the network node. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify, among scheduling combinations according to the number of candidate terminals for which the resource allocation is to be performed, a scheduling combination having a largest sum of scheduling metrics of terminals included in the scheduling combination. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify candidate terminals included in the scheduling combination. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform the resource allocation to the candidate terminals.

[0203] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify a second terminal having a scheduling metric that is next greater than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform the resource allocation to the second terminal.

[0204] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform the resource allocation to the identified terminal in a first frequency domain. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to identify, based on the scheduling metrics for each of the terminals, a second terminal having a scheduling metric that is greater than the scheduling metric of the identified terminal. The instructions, when individually or collectively executed by the at least one processor, may cause the network node to perform the resource allocation to the second terminal in a second frequency domain.

[0205] The method performed by the network node as described above may include an operation of generating throughput information for each terminal based on the amount of traffic of the terminal and the occupancy period during which the traffic remains in the buffer for the terminal. The method may include an operation of calculating a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the sum of the occupancy periods of the terminals to the throughput information for each of the terminals. The method may include an operation of identifying a terminal having a maximum scheduling metric among the terminals based on the scheduling metric for each of the terminals. The method may include an operation of performing resource allocation to the terminal.

[0206] According to one embodiment, the occupancy period may be represented by the sum of a first period between the time when the traffic arrives at the buffer of the corresponding terminal and the time when the transmission of the traffic begins, and a second period between the time when the transmission of the traffic begins and the time when the transmission of the traffic is completed.

[0207] According to one embodiment, the identified terminal may be a terminal having the largest ratio of traffic transmission rate to processing amount information among the terminals.

[0208] In one embodiment, the network node may correspond to a distributed unit (DU). The method may include transmitting information about the resource allocation to the identified terminal via a radio unit (RU) connected to the DU.

[0209] According to one embodiment, the method may include an operation of determining the number of candidate terminals for which the resource allocation is to be performed by the network node. The method may include an operation of identifying, among scheduling combinations according to the number of candidate terminals for which the resource allocation is to be performed, a scheduling combination having the largest sum of scheduling metrics of terminals included in the scheduling combination. The method may include an operation of identifying candidate terminals included in the scheduling combination. The method may include an operation of performing the resource allocation to the candidate terminals.

[0210] In one embodiment, the method may include an operation of identifying a second terminal having a scheduling metric that is next higher than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals. The method may include an operation of causing the second terminal to perform the resource allocation.

[0211] According to one embodiment, the method may include an operation of performing resource allocation to the identified terminal in a first frequency domain. The method may include an operation of identifying a second terminal having a scheduling metric that is next higher than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals. The method may include an operation of performing the resource allocation to the second terminal in a second frequency domain.

[0212] In a computer-readable storage medium having one or more programs stored thereon, as described above, the one or more programs may include instructions that, when executed by a network node, cause the network node to generate throughput information for each of the terminals based on the amount of traffic of the terminal and the occupancy period that the traffic remains in a buffer for the terminal. The one or more programs may include instructions that, when executed by the network node, cause the network node to calculate a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the sum of the occupancy periods of the terminals to the throughput information for each of the terminals. The one or more programs may include instructions that, when executed by the network node, cause the network node to identify, based on the scheduling metric for each of the terminals, a terminal having a maximum scheduling metric among the terminals. The one or more programs may include instructions that, when executed by the network node, cause the network node to perform resource allocation to the terminal.

[0213] According to one embodiment, the identified terminal may be a terminal having the largest ratio of traffic transmission rate to processing amount information among the terminals.

[0214] In one embodiment, the network node may correspond to a distributed unit (DU). The one or more programs, when executed by the wearable device, may include instructions that cause the wearable device to transmit information about the resource allocation to the identified terminal via a radio unit (RU) connected to the DU.

[0215] According to one embodiment, the one or more programs may include instructions that, when executed by the network node, cause the network node to determine the number of candidate terminals for which the resource allocation is to be performed by the network node. The one or more programs may include instructions that, when executed by the network node, cause the network node to identify, among scheduling combinations according to the number of candidate terminals for which the resource allocation is to be performed, a scheduling combination having a largest sum of scheduling metrics of terminals included in the scheduling combination. The one or more programs may include instructions that, when executed by the network node, cause the network node to identify candidate terminals included in the scheduling combination. The one or more programs may include instructions that, when executed by the network node, cause the network node to perform the resource allocation to the candidate terminals.

[0216] In one embodiment, the one or more programs may include instructions that, when executed by the network node, cause the network node to identify a second terminal having a scheduling metric that is next greater than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals. The one or more programs may include instructions that, when executed by the network node, cause the network node to perform the resource allocation to the second terminal.

[0217] In one embodiment, the one or more programs may include instructions that, when executed by the network node, cause the network node to perform the resource allocation in a first frequency domain to the identified terminal. The one or more programs may include instructions that, when executed by the network node, cause the network node to identify, based on the scheduling metrics for each of the terminals, a second terminal having a scheduling metric that is next greater than the scheduling metric of the identified terminal. The one or more programs may include instructions that, when executed by the network node, cause the network node to perform the resource allocation in a second frequency domain to the second terminal.

[0218] For one or more embodiments, at least one of the components described in one or more of the preceding drawings may be configured to perform one or more operations, techniques, processes, and / or methods as described herein. For example, a processor (e.g., a baseband processor) described herein with respect to one or more of the preceding drawings may be configured to operate according to one or more examples described herein. For another example, circuitry associated with a user equipment (UE), a base station, a network element, and the like, as described above with respect to one or more of the preceding drawings, may be configured to operate according to one or more examples described herein.

[0219] Any of the embodiments described above may be combined with any other embodiment (or combination of embodiments) unless explicitly stated otherwise. The foregoing description of one or more implementations provides examples and descriptions, but is not intended to be exhaustive or limit the scope of the embodiments to the precise forms disclosed. Modifications and variations are possible in light of the above teachings or may be learned from practicing various embodiments.

[0220] The methods according to the embodiments described in the claims or specification of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

[0221] When implemented in software, a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing one or more programs (software modules) may be provided. The one or more programs stored in the computer-readable storage medium are configured for execution by one or more processors within an electronic device. The one or more programs include instructions that cause the electronic device to execute methods according to embodiments described in the claims or specification of the present disclosure. The one or more programs may be provided as a computer program product. The computer program product may be traded between a seller and a buyer as a commodity. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created in a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0222] These programs (software modules, software) may be stored in random access memory, non-volatile memory including flash memory, read only memory (ROM), electrically erasable programmable read only memory (EEPROM), magnetic disc storage devices, compact disc-ROM (CD-ROM), digital versatile discs (DVDs) or other forms of optical storage devices, magnetic cassettes, or may be stored in memories formed by a combination of some or all of these. In addition, each configuration memory may include multiple copies.

[0223] Additionally, the program may be stored on an attachable storage device that is accessible via a communication network, such as the Internet, an intranet, a local area network (LAN), a wide area network (WAN), a storage area network (SAN), or a combination thereof. Such a storage device may be connected to a device implementing an embodiment of the present disclosure via an external port. Additionally, a separate storage device on the communication network may be connected to a device implementing an embodiment of the present disclosure.

[0224] In the specific embodiments of the present disclosure described above, components included in the disclosure are expressed singularly or plurally, depending on the specific embodiment presented. However, the singular or plural expressions are selected to suit the presented situation for convenience of explanation, and the present disclosure is not limited to singular or plural components. Components expressed in plural may be composed of singular elements, or components expressed in singular may be composed of plural elements.

[0225] According to embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., modules or programs) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0226] Meanwhile, although the detailed description of the present disclosure has described specific embodiments, it is obvious that various modifications are possible within the scope of the present disclosure.

Claims

1. In a network node, A memory storing instructions and including one or more storage media; and At least one processor comprising a processing circuit, The above instructions, when individually or collectively executed by the at least one processor, cause the network node to: Generate throughput information for each terminal based on the amount of traffic of the terminal and the occupancy period for which the traffic remains in the buffer for the terminal, By applying a weight corresponding to the occupancy period of each terminal to the sum of the occupancy periods of the terminals to the throughput information for each of the terminals, a scheduling metric for each of the terminals is calculated, Based on the scheduling metric for each of the above terminals, the terminal with the maximum scheduling metric is identified among the above terminals, and Causing the above terminal to perform resource allocation, Network node.

2. In claim 1, The above occupancy period is represented by the sum of a first period between the time when the traffic arrives at the buffer of the corresponding terminal and the time when the transmission of the traffic begins, and a second period between the time when the transmission of the traffic begins and the time when the transmission of the traffic is completed. Network node.

3. In claim 1, The above-identified terminal is a terminal having the largest ratio of traffic transmission rate to processing amount information among the terminals. Network node.

4. In claim 1, The above network node corresponds to a DU (distributed unit), The above instructions, when individually or collectively executed by the at least one processor, cause the network node to: Causing information about the above resource allocation to be transmitted to the identified terminal through the RU (radio unit) connected to the DU. Network node.

5. In claim 1, The above instructions, when individually or collectively executed by the at least one processor, cause the network node to: The number of candidate terminals for which the resource allocation is to be performed by the above network node is determined, Among the scheduling combinations according to the number of candidate terminals for which the resource allocation is to be performed, a scheduling combination having the largest sum of scheduling metrics of terminals included in the scheduling combination is identified, Identify candidate terminals included in the above scheduling combination, and Causing the above candidate terminals to perform the above resource allocation, Network node.

6. In claim 1, The above instructions, when individually or collectively executed by the at least one processor, cause the network node to: Based on the scheduling metric for each of the above terminals, a second terminal having a scheduling metric that is next larger than the scheduling metric of the identified terminal is identified, and Causing the second terminal to perform the resource allocation, Network node.

7. In claim 1, The above instructions, when individually or collectively executed by the at least one processor, cause the network node to: Perform resource allocation in the first frequency domain to the identified terminal, Based on the scheduling metric for each of the above terminals, a second terminal having a scheduling metric that is next larger than the scheduling metric of the identified terminal is identified, and Causing the second terminal to perform the resource allocation in the second frequency domain, Network node.

8. In the method of executing within a network node, An operation of generating throughput information for each terminal based on the amount of traffic of the terminal and the occupancy period for which the traffic remains in the buffer for the terminal, An operation of calculating a scheduling metric for each of the terminals by applying a weight corresponding to the occupancy period of the terminal to the sum of the occupancy periods of the terminals to the processing capacity information for each of the terminals, An operation of identifying a terminal with the maximum scheduling metric among the terminals based on the scheduling metric for each of the terminals, and Including an operation of performing resource allocation to the terminal, method.

9. In claim 8, The above occupancy period is represented by the sum of a first period between the time when the traffic arrives at the buffer of the corresponding terminal and the time when the transmission of the traffic begins, and a second period between the time when the transmission of the traffic begins and the time when the transmission of the traffic is completed. method.

10. In claim 8, The above-identified terminal is a terminal having the largest ratio of traffic transmission rate to processing amount information among the terminals. method.

11. In claim 8, The above network node corresponds to a DU (distributed unit), An operation of transmitting information about the above resource allocation to the identified terminal through a RU (radio unit) connected to the DU, method.

12. In claim 8, An operation for determining the number of candidate terminals for which resource allocation is to be performed by the network node; An operation of identifying a scheduling combination having the largest sum of scheduling metrics of terminals included in the scheduling combination among scheduling combinations according to the number of candidate terminals for which the resource allocation is to be performed, An operation for identifying candidate terminals included in the above scheduling combination, and Including an operation of performing the resource allocation to the candidate terminals, method.

13. In claim 8, An operation of identifying a second terminal having a scheduling metric that is next larger than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals, and Including an operation of performing the resource allocation to the second terminal, method.

14. In claim 8, An operation of performing resource allocation in the first frequency domain to the identified terminal; An operation of identifying a second terminal having a scheduling metric that is next larger than the scheduling metric of the identified terminal, based on the scheduling metric for each of the terminals, and Including an operation of performing resource allocation in a second frequency domain to the second terminal, method.

15. In a non-transitory computer-readable storage medium storing one or more programs, said one or more programs, when executed by a network node, Generate throughput information for each terminal based on the amount of traffic of the terminal and the occupancy period for which the traffic remains in the buffer for the terminal, By applying a weight corresponding to the occupancy period of each terminal to the sum of the occupancy periods of the terminals to the throughput information for each of the terminals, a scheduling metric for each of the terminals is calculated, Based on the scheduling metric for each of the above terminals, the terminal with the maximum scheduling metric is identified among the above terminals, and To perform resource allocation to the above terminal, Containing instructions that cause the above network node to occur, Non-transitory computer-readable storage medium.

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