Method for increasing downlink RSMA channel capacity by using RIS channel similarity enhancement

Abstract

A method according to one embodiment of the present specification comprises the steps of: determining a reflection coefficient of a reconfigurable intelligent surface (RIS) on the basis of channel state information (CSI); determining channel similarity on the basis of the reflection coefficient; determining, on the basis of the channel similarity, clusters for common streams related to rate splitting multiple access (RSMA); and allocating the common streams and private streams to second wireless devices on the basis of the clusters.

Description

DOWNLINK RSMA Channel Capacity Augmentation Technique Using RIS Channel Similarity Enhancement

[0001] This specification relates to a Downlink RSMA channel capacity increase technique using RIS channel similarity enhancement.

[0002] Mobile communication systems were developed to provide voice services while ensuring user mobility. However, mobile communication systems have expanded their scope to include data services as well as voice. Currently, due to the explosive increase in traffic leading to resource shortages and users demanding higher-speed services, more advanced mobile communication systems are required.

[0003] The requirements for next-generation mobile communication systems largely include the ability to accommodate explosive data traffic, a dramatic increase in transmission rates per user, a significantly increased number of connected devices, very low end-to-end latency, and high energy efficiency. To achieve this, various technologies are being researched, such as dual connectivity, massive multiple input multiple output (MMIMO), in-band full duplex, non-orthogonal multiple access (NOMA), super wideband support, and device networking.

[0004] Meanwhile, there has been a continuous demand for technologies to satisfy the Quality of Experience (QoE) of user terminals. To this end, technologies capable of securing increased channel capacity through techniques such as Space-Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA) have been proposed. However, these technologies had several drawbacks, including limitations in spatial resources, complexity in power control, and limitations of Successive Interference Cancellation (SIC). To address these issues, the Rate-Splitting Multiple Access (RSMA) technique was proposed.

[0005] When the RSMA technique is utilized in a multi-cell environment, the complexity of Successive Interference Cancellation (SIC) increases. Considering this SIC complexity, a method is being considered in which the Central Processor (CP) splits the signal into a common stream and a private stream and allocates them to BSs. Under this method, as the number of terminals increases, the number of common streams increases exponentially, which may result in exceeding the channel capacity.

[0006] The purpose of this specification is to propose a method for solving the aforementioned problems.

[0007] The technical problems to be solved in this specification 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 specification belongs from the description below.

[0008] A method according to one embodiment of the present specification includes the steps of determining a reflection coefficient of a Reconfigurable Intelligent Surface (RIS) based on Channel State Information (CSI), determining a channel similarity based on the reflection coefficient, determining clusters for common streams related to Rate Splitting Multiple Access (RSMA) based on the channel similarity, and assigning the common streams and private streams to second wireless devices based on the clusters.

[0009] The above channel state information may include first information, second information, and third information. The first information may include information related to the channel state between i) one of the third wireless devices and ii) one of the second wireless devices. The second information may include information related to the channel state between i) one of the third wireless devices and ii) the RIS. The third information may include information related to the channel state between i) one of the second wireless devices and ii) the RIS.

[0010] First channel similarities can be calculated for all cases in which a pair is formed based on two of the above third wireless devices.

[0011] Among the reflection coefficients associated with the above RIS, the reflection coefficient that maximizes the sum of the first channel similarities can be determined. The channel similarity can be based on the second channel similarities calculated for all cases based on the reflection coefficient.

[0012] The first channel similarities and the second channel similarities may be based on cosine similarity.

[0013] Hierarchical clustering can be performed based on the second channel similarities mentioned above. The clusters can be determined based on the hierarchical clustering.

[0014] Based on the above hierarchical clustering, clusters for each of the plurality of layers can be determined. The clusters may be clusters for one of the plurality of layers based on a channel similarity threshold.

[0015] Each cluster may include at least one of the third wireless devices.

[0016] The above individual streams and the above common streams can be allocated based on the maximum number of streams that can be accommodated per second wireless device.

[0017] Each of the above individual streams can be assigned to a second wireless device having the highest channel quality for that individual stream.

[0018] Each of the above common streams can be assigned to a second wireless device with the highest channel quality for the cluster associated with the common stream.

[0019] Values ​​related to the mobility of the third wireless devices can be calculated based on the channel state information. Based on these values, an estimated channel similarity value can be determined by a learned model. Based on the fact that the estimated channel similarity value is smaller than the channel similarity threshold, the clusters can be reset.

[0020] A first wireless device according to another embodiment of the present specification includes one or more transceivers, one or more processors for controlling the one or more transceivers, and one or more memories connected to the one or more processors for storing instructions.

[0021] The above instructions are characterized by causing the first wireless device to perform all steps of any one of the above methods based on execution by the one or more processors.

[0022] An apparatus according to another embodiment of the present specification includes one or more memories and one or more processors functionally connected to the one or more memories.

[0023] The one or more memories are characterized by storing instructions that cause the device to perform all steps of any one of the methods based on execution by the one or more processors.

[0024] One or more non-transitory computer-readable media according to another embodiment of the present specification store instructions. The instructions, executable by one or more processors, are characterized by causing the one or more processors to perform all steps of any one of the methods.

[0025] A method according to another embodiment of the present specification includes the steps of transmitting Channel State Information (CSI) to a second wireless device and receiving a private stream and a common stream associated with Rate Splitting Multiple Access (RSMA) from the second wireless device.

[0026] Based on the above CSI, the reflection coefficient of the RIS (Reconfigurable Intelligent Surface) is determined. Based on the above reflection coefficient, channel similarity is determined. Based on the above channel similarity, clusters for common streams are determined. The common stream may be based on the cluster assigned to the second wireless device among the clusters.

[0027] A third wireless device according to another embodiment of the present specification comprises one or more transceivers, one or more processors for controlling the one or more transceivers, and one or more memories connected to the one or more processors for storing instructions.

[0028] The above instructions are characterized by causing the third wireless device to perform all steps of the method based on execution by the one or more processors.

[0029] According to the embodiments of this specification, common streams are allocated according to clusters based on channel similarity. Resource utilization can be improved compared to allocating common streams without clustering. In addition, throughput can be improved through resource allocation optimization.

[0030] The effects obtainable in this specification are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below.

[0031] FIG. 1 is a drawing illustrating an example of a communication system applicable to the present specification.

[0032] FIG. 2 is a drawing illustrating an example of a wireless device that can be applied to the present specification.

[0033] FIG. 3 is a diagram illustrating a method for processing a transmission signal applicable to the present specification.

[0034] FIG. 4 is a drawing illustrating another example of a wireless device to which the present specification applies.

[0035] FIG. 5 is a drawing illustrating an example of a portable device to which the present specification applies.

[0036] FIG. 6 is a diagram illustrating physical channels applicable to the present specification and a signal transmission method using them.

[0037] Figure 7 is a figure showing an example of a communication structure that can be provided in a 6G system.

[0038] Figure 8 illustrates the classification of CoMP technologies.

[0039] Figure 9 illustrates a Generalized CoMP structure.

[0040] FIG. 10 illustrates the structure of a transceiver to which an embodiment of the present specification can be applied.

[0041] FIG. 11 illustrates a model related to a CoMP to which an embodiment of the present specification can be applied.

[0042] Figure 12 illustrates a communication environment in an RSMA system.

[0043] Figure 13 illustrates the baseband transceiver structure in an RSMA system.

[0044] Figure 14 illustrates a conventional wireless environment.

[0045] Figure 15 illustrates an intelligent wireless environment.

[0046] Figure 16 illustrates a communication theory model for a conventional wireless environment.

[0047] Figure 17 illustrates a communication theory model for an intelligent wireless environment.

[0048] FIG. 18 illustrates the structure of a Downlink RSMA system according to an embodiment of the present specification.

[0049] FIG. 19 illustrates a procedure for RIS control according to an embodiment of the present specification.

[0050] FIG. 20 illustrates a procedure for enhancing channel similarity using RIS according to an embodiment of the present specification.

[0051] FIG. 21 illustrates layer-by-layer clustering according to an embodiment of the present specification.

[0052] FIG. 22 illustrates a channel similarity-based clustering and stream allocation procedure according to an embodiment of the present specification.

[0053] FIG. 23 illustrates a mobility evaluation value learning procedure for channel similarity compensation according to an embodiment of the present specification.

[0054] FIG. 24 is a flowchart illustrating a method according to one embodiment of the present specification.

[0055] FIG. 25 is a flowchart illustrating a method according to another embodiment of the present specification.

[0056] The following embodiments are combinations of the components and features of this specification in a predetermined form. Each component or feature may be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form not combined with other components or features. Additionally, some components and / or features may be combined to constitute the embodiments of this specification. The order of operations described in the embodiments of this specification may be changed. Some components or features of any embodiment may be included in another embodiment, or may be replaced with corresponding components or features of another embodiment.

[0057] In the description of the drawings, procedures or steps that could obscure the gist of the specification have not been described, nor have procedures or steps that are understandable to those skilled in the art been described.

[0058] Throughout the specification, when a part is described as "comprising" or "including" a component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. Furthermore, terms such as "...part," "...unit," and "module" as used in the specification refer to a unit that performs at least one function or operation, and this may be implemented in hardware, software, or a combination of hardware and software. Additionally, "one (a or an)," "one," "the," and similar related terms may be used in the context describing this specification (particularly in the context of the following claims) to include both singular and plural forms, unless otherwise indicated in this specification or clearly contradicted by the context.

[0059] The embodiments of this specification have been described with a focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station refers to a terminal node of a network that communicates directly with a mobile station. Specific operations described herein as being performed by a base station may, in some cases, be performed by an upper node of the base station.

[0060] That is, in a network consisting of multiple network nodes including a base station, various operations performed for communication with a mobile station may be performed by the base station or other network nodes other than the base station. In this case, 'base station' may be replaced by terms such as fixed station, Node B, eNB (eNode B), gNB (gNode B), ng-eNB, advanced base station (ABS), or access point.

[0061] Additionally, in the embodiments of this specification, the term terminal may be replaced with terms such as user equipment (UE), mobile station (MS), subscriber station (SS), mobile subscriber station (MSS), mobile terminal, or advanced mobile station (AMS).

[0062] Furthermore, the transmitting end refers to a fixed and / or mobile node that provides data or voice services, and the receiving end refers to a fixed and / or mobile node that receives data or voice services. Therefore, in the case of the uplink, a mobile station can be the transmitting end and a base station can be the receiving end. Similarly, in the case of the downlink, a mobile station can be the receiving end and a base station can be the transmitting end.

[0063] Embodiments of the present specification may be supported by standard documents disclosed in at least one of the wireless access systems, such as IEEE 802.xx systems, 3GPP (3rd Generation Partnership Project) systems, 3GPP LTE (Long Term Evolution) systems, 3GPP 5G (5th generation) NR (New Radio) systems and 3GPP2 systems, and in particular, embodiments of the present specification may be supported by 3GPP TS (technical specification) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents.

[0064] In addition, the embodiments of this specification may be applied to other wireless access systems and are not limited to the systems described above. For example, they may be applicable to systems applied after the 3GPP 5G NR system and are not limited to specific systems.

[0065] That is, obvious steps or parts not described in the embodiments of this specification may be described by referring to the aforementioned documents. Additionally, all terms disclosed in this specification may be explained by the aforementioned standard documents.

[0066] Hereinafter, preferred embodiments according to the present specification will be described in detail with reference to the accompanying drawings. The detailed description disclosed below, together with the accompanying drawings, is intended to describe exemplary embodiments of the present specification and is not intended to represent the only embodiment in which the technical configuration of the present specification can be implemented.

[0067] Additionally, specific terms used in the embodiments of this specification are provided to aid in understanding this specification, and the use of such specific terms may be modified in other forms without departing from the technical spirit of this specification.

[0068] The following technology can be applied to various wireless access systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access).

[0069] For the sake of clarity in the following description, the explanation is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical concept of the present invention is not limited thereto. LTE may refer to technology from 3GPP TS 36.xxx Release 8 onwards. Specifically, LTE technology from 3GPP TS 36.xxx Release 10 onwards is referred to as LTE-A, and LTE technology from 3GPP TS 36.xxx Release 13 onwards may be referred to as LTE-A pro. 3GPP NR may refer to technology from TS 38.xxx Release 15 onwards. 3GPP 6G may refer to technology from TS Release 17 and / or Release 18 onwards. "xxx" indicates a standard document detail number. LTE / NR / 6G may be collectively referred to as 3GPP systems.

[0070] Regarding the background technology, terms, abbreviations, etc. used in this specification, reference may be made to matters described in standard documents published prior to the present invention. For example, reference may be made to standard documents 36.xxx and 38.xxx.

[0071] Communication systems applicable to the present specification

[0072] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this specification may be applied to various fields requiring wireless communication / connection (e.g., 5G) between devices.

[0073] Examples are provided in more detail below with reference to the drawings. In the following drawings and descriptions, the same reference numerals may represent the same or corresponding hardware blocks, software blocks, or function blocks unless otherwise described.

[0074] FIG. 1 is a drawing illustrating an example of a communication system to which the present specification applies. Referring to FIG. 1, the communication system (100) to which the present specification applies includes a wireless device, a base station, and a network. Here, a wireless device refers to a device that performs communication using wireless access technology (e.g., 5G NR, LTE) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, a wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (extended reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Thing) device (100f), and an AI (artificial intelligence) device / server (100g). For example, a vehicle may include a vehicle equipped with wireless communication capabilities, an autonomous vehicle, a vehicle capable of performing inter-vehicle communication, etc. Here, the vehicle (100b-1, 100b-2) may include an unmanned aerial vehicle (UAV) (e.g., a drone). The XR device (100c) includes an augmented reality (AR) / virtual reality (VR) / mixed reality (MR) device and may be implemented in the form of a head-mounted device (HMD), a head-up display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc. The portable device (100d) may include a smartphone, a smart pad, a wearable device (e.g., a smartwatch, smart glasses), a computer (e.g., a laptop, etc.). The home appliance (100e) may include a TV, a refrigerator, a washing machine, etc. The IoT device (100f) may include a sensor, a smart meter, etc.For example, the base station (120) and network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node for other wireless devices.

[0075] Wireless devices (100a to 100f) can be connected to a network (130) through a base station (120). AI technology may be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) through the network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, or a 5G (e.g., NR) network. The wireless devices (100a to 100f) may communicate with each other through the base station (120) / network (130), but they may also communicate directly (e.g., sidelink communication) without going through the base station (120) / network (130). For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). Also, IoT devices (100f) (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0076] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a~100f) / base station (120) and between base station (120) / base station (120). Here, wireless communication / connection can be established through various wireless access technologies (e.g., 5G NR), such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and communication between base stations (150c) (e.g., relay, IAB (integrated access backhaul)). Through wireless communication / connection (150a, 150b, 150c), wireless devices and base stations / wireless devices, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on the various proposals of this specification, at least some of the following may be performed: a process for setting various configuration information for transmitting / receiving wireless signals, a process for various signal processing (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), a resource allocation process, etc.

[0077] Communication systems applicable to the present specification

[0078] FIG. 2 is a drawing illustrating an example of a wireless device that can be applied to the present specification.

[0079] Referring to FIG. 2, the first wireless device (200a) and the second wireless device (200b) can transmit and receive wireless signals through various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (200a), the second wireless device (200b)} may correspond to {the wireless device (100x), the base station (120)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 1.

[0080] The first wireless device (200a) includes one or more processors (202a) and one or more memories (204a), and may additionally include one or more transceivers (206a) and / or one or more antennas (208a). The processor (202a) controls the memory (204a) and / or transceivers (206a) and may be configured to implement the descriptions, functions, procedures, proposals, methods and / or sequences of operation disclosed herein. For example, the processor (202a) may process information within the memory (204a) to generate a first information / signal and then transmit a wireless signal containing the first information / signal through the transceiver (206a). Additionally, the processor (202a) may receive a wireless signal containing a second information / signal through the transceiver (206a) and then store information obtained from the signal processing of the second information / signal in the memory (204a). Memory (204a) may be connected to the processor (202a) and may store various information related to the operation of the processor (202a). For example, memory (204a) may store software code including instructions for performing some or all of the processes controlled by the processor (202a) or for performing the descriptions, functions, procedures, proposals, methods, and / or sequences of operation disclosed in this specification. Here, the processor (202a) and memory (204a) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). A transceiver (206a) may be connected to the processor (202a) and may transmit and / or receive wireless signals through one or more antennas (208a). The transceiver (206a) may include a transmitter and / or receiver. The transceiver (206a) may be combined with an RF (radio frequency) unit. In this specification, a wireless device may refer to a communication modem / circuit / chip.

[0081] The second wireless device (200b) includes one or more processors (202b) and one or more memories (204b), and may additionally include one or more transceivers (206b) and / or one or more antennas (208b). The processor (202b) controls the memory (204b) and / or transceivers (206b) and may be configured to implement the descriptions, functions, procedures, proposals, methods and / or sequences of operation disclosed herein. For example, the processor (202b) may process information within the memory (204b) to generate a third information / signal and then transmit a wireless signal containing the third information / signal through the transceiver (206b). Additionally, the processor (202b) may receive a wireless signal containing a fourth information / signal through the transceiver (206b) and then store information obtained from the signal processing of the fourth information / signal in the memory (204b). The memory (204b) may be connected to the processor (202b) and may store various information related to the operation of the processor (202b). For example, the memory (204b) may store software code including instructions for performing some or all of the processes controlled by the processor (202b) or for performing the descriptions, functions, procedures, proposals, methods, and / or sequence diagrams of operation disclosed in this specification. Here, the processor (202b) and the memory (204b) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206b) may be connected to the processor (202b) and may transmit and / or receive wireless signals through one or more antennas (208b). The transceiver (206b) may include a transmitter and / or receiver. The transceiver (206b) may be used in combination with an RF unit. In this specification, a wireless device may refer to a communication modem / circuit / chip.

[0082] Hereinafter, hardware elements of the wireless device (200a, 200b) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (202a, 202b). For example, one or more processors (202a, 202b) may implement one or more layers (e.g., functional layers such as PHY (physical), MAC (media access control), RLC (radio link control), PDCP (packet data convergence protocol), RRC (radio resource control), and SDAP (service data adaptation protocol). One or more processors (202a, 202b) may generate one or more PDUs (Protocol Data Units) and / or one or more SDUs (service data units) according to the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed herein. One or more processors (202a, 202b) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this specification. One or more processors (202a, 202b) may generate a signal (e.g., baseband signal) including a PDU, SDU, message, control information, data, or information according to the functions, procedures, proposals, and / or methods disclosed in this specification and provide it to one or more transceivers (206a, 206b). One or more processors (202a, 202b) may receive a signal (e.g., baseband signal) from one or more transceivers (206a, 206b) and may obtain a PDU, SDU, message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this specification.

[0083] One or more processors (202a, 202b) may be referred to as a controller, microcontroller, microprocessor, or microcomputer. One or more processors (202a, 202b) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), or one or more field programmable gate arrays (FPGAs) may be included in one or more processors (202a, 202b). Descriptions, functions, procedures, proposals, methods, and / or flowcharts disclosed herein may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. Firmware or software configured to perform the descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this specification may be included in one or more processors (202a, 202b) or stored in one or more memories (204a, 204b) and driven by one or more processors (202a, 202b). The descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this specification may be implemented using firmware or software in the form of code, instructions, and / or sets of instructions.

[0084] One or more memories (204a, 204b) may be connected to one or more processors (202a, 202b) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. One or more memories (204a, 204b) may be composed of ROM (read-only memory), RAM (random access memory), EPROM (erasable programmable read-only memory), flash memory, hard drives, registers, cache memory, computer-readable storage media, and / or combinations thereof. One or more memories (204a, 204b) may be located inside and / or outside of one or more processors (202a, 202b). Additionally, one or more memories (204a, 204b) may be connected to one or more processors (202a, 202b) through various technologies such as wired or wireless connections.

[0085] One or more transceivers (206a, 206b) may transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or operation flowcharts, etc., of this specification to one or more other devices. One or more transceivers (206a, 206b) may receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts, etc., disclosed in this specification from one or more other devices. For example, one or more transceivers (206a, 206b) may be connected to one or more processors (202a, 202b) and may transmit and receive wireless signals. For example, one or more processors (202a, 202b) may control one or more transceivers (206a, 206b) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (202a, 202b) may control one or more transceivers (206a, 206b) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (206a, 206b) may be connected to one or more antennas (208a, 208b), and one or more transceivers (206a, 206b) may be configured to transmit and receive user data, control information, wireless signals / channels, etc., as described in the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed herein through one or more antennas (208a, 208b). In this specification, one or more antennas may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports). One or more transceivers (206a, 206b) can convert the received wireless signal / channel, etc. from an RF band signal to a baseband signal in order to process the received user data, control information, wireless signal / channel, etc. using one or more processors (202a, 202b).One or more transceivers (206a, 206b) can convert user data, control information, wireless signals / channels, etc. processed using one or more processors (202a, 202b) from baseband signals to RF band signals. To this end, one or more transceivers (206a, 206b) may include (analog) oscillators and / or filters.

[0086] FIG. 3 is a diagram illustrating a method for processing a transmission signal applicable to the present specification. For example, the transmission signal may be processed by a signal processing circuit. In this case, the signal processing circuit (300) may include a scrambler (310), a modulator (320), a layer mapper (330), a precoder (340), a resource mapper (350), and a signal generator (360). In this case, for example, the operation / function of FIG. 3 may be performed in the processor (202a, 202b) and / or transceiver (206a, 206b) of FIG. 2. Also, for example, the hardware element of FIG. 3 may be implemented in the processor (202a, 202b) and / or transceiver (206a, 206b) of FIG. 2. For example, blocks 310 to 350 may be implemented in the processor (202a, 202b) of FIG. 2, and block 360 may be implemented in the transceiver (206a, 206b) of FIG. 2, but are not limited to the above-described embodiment.

[0087] A codeword can be converted into a wireless signal through the signal processing circuit (300) of FIG. 3. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transmission block (e.g., UL-SCH transmission block, DL-SCH transmission block). The wireless signal may be transmitted through various physical channels (e.g., PUSCH, PDSCH) of FIG. 6. Specifically, the codeword can be converted into a scrambled bit sequence by a scrambler (310). The scrambled sequence used for scrambling is generated based on an initialization value, which may include ID information of a wireless device, etc. The scrambled bit sequence may be modulated into a modulation symbol sequence by a modulator (320). The modulation method may include pi / 2-BPSK (pi / 2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

[0088] A complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (330). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (340) (precoding). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by an N*M precoding matrix W, where N is the number of antenna ports and M is the number of transmission layers. Here, the precoder (340) can perform precoding after performing transform precoding (e.g., a discrete Fourier transform (DFT)) on the complex modulation symbols. Alternatively, the precoder (340) can perform precoding without performing transform precoding.

[0089] A resource mapper (350) can map the modulation symbols of each antenna port to a time-frequency resource. The time-frequency resource may include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. A signal generator (360) generates a radio signal from the mapped modulation symbols, and the generated radio signal can be transmitted to another device through each antenna. To this end, the signal generator (360) may include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, etc.

[0090] The signal processing process for a received signal in a wireless device can be configured as the inverse of the signal processing process (310–360) of FIG. 3. For example, a wireless device (e.g., 200a, 200b of FIG. 2) can receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal can be converted into a baseband signal through a signal restorer. To this end, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Subsequently, the baseband signal can be restored into a codeword through a resource de-mapper process, a postcoding process, a demodulation process, and a de-scrambling process. The codeword can be restored into the original information block through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0091] Wireless device structure applicable to the present specification

[0092] FIG. 4 is a drawing illustrating another example of a wireless device to which the present specification applies.

[0093] Referring to FIG. 4, the wireless device (400) corresponds to the wireless device (200a, 200b) of FIG. 2 and may be composed of various elements, components, units / parts, and / or modules. For example, the wireless device (400) may include a communication unit (410), a control unit (420), a memory unit (430), and additional elements (440). The communication unit may include a communication circuit (412) and transceiver(s) (414). For example, the communication circuit (412) may include one or more processors (202a, 202b) and / or one or more memories (204a, 204b) of FIG. 2. For example, the transceiver(s) (414) may include one or more transceivers (206a, 206b) and / or one or more antennas (208a, 208b) of FIG. 2. The control unit (420) is electrically connected to the communication unit (410), the memory unit (430), and additional elements (440) and controls the general operation of the wireless device. For example, the control unit (420) may control the electrical / mechanical operation of the wireless device based on a program / code / command / information stored in the memory unit (430). Additionally, the control unit (420) may transmit information stored in the memory unit (430) to an external (e.g., another communication device) via a wireless / wired interface through the communication unit (410), or store information received from an external (e.g., another communication device) via a wireless / wired interface through the communication unit (410) in the memory unit (430).

[0094] The additional element (440) can be configured in various ways depending on the type of wireless device. For example, the additional element (440) may include at least one of a power unit / battery, an input / output unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device (400) may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or financial device), a security device, a climate / environment device, an AI server / device (Fig. 1, 140), a base station (Fig. 1, 120), a network node, etc. Wireless devices can be used in a movable or fixed location depending on the use—e.g., service.

[0095] In FIG. 4, various elements, components, units / parts, and / or modules within the wireless device (400) may be entirely interconnected via a wired interface, or at least partially connected via a communication unit (410). For example, within the wireless device (400), the control unit (420) and the communication unit (410) may be connected via a wire, and the control unit (420) and the first unit (e.g., 430, 440) may be connected wirelessly via the communication unit (410). Additionally, each element, component, unit / part, and / or module within the wireless device (400) may include one or more additional elements. For example, the control unit (420) may be composed of one or more sets of processors. For example, the control unit (420) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (430) may be composed of RAM, DRAM (dynamic RAM), ROM, flash memory, volatile memory, non-volatile memory and / or a combination thereof.

[0096] Mobile devices to which this specification applies

[0097] FIG. 5 is a drawing illustrating an example of a portable device to which the present specification applies.

[0098] FIG. 5 illustrates a portable device to which the present specification applies. The portable device may include a smartphone, a smartpad, a wearable device (e.g., a smart watch, smart glasses), a portable computer (e.g., a laptop, etc.). The portable device may be referred to as an MS (mobile station), UT (user terminal), MSS (mobile subscriber station), SS (subscriber station), AMS (advanced mobile station), or WT (wireless terminal).

[0099] Referring to FIG. 5, the portable device (500) may include an antenna unit (508), a communication unit (510), a control unit (520), a memory unit (530), a power supply unit (540a), an interface unit (540b), and an input / output unit (540c). The antenna unit (508) may be configured as part of the communication unit (510). Blocks 510 to 530 / 540a to 540c correspond to blocks 410 to 430 / 440 of FIG. 4, respectively.

[0100] The communication unit (510) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (520) can control the components of the portable device (500) to perform various operations. The control unit (520) may include an application processor (AP). The memory unit (530) can store data / parameters / programs / code / commands required for the operation of the portable device (500). Additionally, the memory unit (530) can store input / output data / information, etc. The power supply unit (540a) supplies power to the portable device (500) and may include wired / wireless charging circuits, batteries, etc. The interface unit (540b) can support the connection between the portable device (500) and other external devices. The interface unit (540b) may include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (540c) can receive or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (540c) may include a camera, a microphone, a user input unit, a display unit (540d), a speaker and / or a haptic module, etc.

[0101] For example, in the case of data communication, the input / output unit (540c) acquires information / signals (e.g., touch, text, voice, image, video) input by the user, and the acquired information / signals can be stored in the memory unit (530). The communication unit (510) converts the information / signals stored in the memory into wireless signals and can directly transmit the converted wireless signals to another wireless device or to a base station. Additionally, the communication unit (510) can receive wireless signals from another wireless device or base station and then restore the received wireless signals to their original information / signals. The restored information / signals are stored in the memory unit (530) and then can be output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (540c).

[0102] Physical channels and general signal transmission

[0103] In a wireless access system, a terminal can receive information from a base station via a downlink (DL) and transmit information to a base station via an uplink (UL). The information transmitted and received by the base station and the terminal includes general data information and various control information, and various physical channels exist depending on the type and purpose of the information they transmit and receive.

[0104] FIG. 6 is a diagram illustrating physical channels applicable to the present specification and a signal transmission method using them.

[0105] When a terminal is turned on again after being turned off, or when it newly enters a cell, it performs initial cell search operations, such as synchronizing with the base station, in step S611. To do this, the terminal receives the primary synchronization channel (P-SCH) and secondary synchronization channel (S-SCH) from the base station to synchronize with the base station and obtain information such as the cell ID.

[0106] Subsequently, the terminal can obtain in-cell broadcast information by receiving a physical broadcast channel (PBCH) signal from the base station. Meanwhile, during the initial cell search phase, the terminal can check the downlink channel status by receiving a Downlink Reference Signal (DL RS). After completing the initial cell search, the terminal can obtain more specific system information by receiving the physical downlink control channel (PDCCH) and the physical downlink shared channel (PDSCH) based on the physical downlink control channel information in step S612.

[0107] Subsequently, the terminal may perform a random access procedure, such as steps S613 through S616, to complete the connection to the base station. To this end, the terminal transmits a preamble through a physical random access channel (PRACH) (S613) and receives a random access response (RAR) for the preamble through a physical downlink control channel and a corresponding physical downlink shared channel (S614). The terminal transmits a physical uplink shared channel (PUSCH) using scheduling information within the RAR (S615) and performs a contention resolution procedure, such as receiving a physical downlink control channel signal and a corresponding physical downlink shared channel signal (S616).

[0108] A terminal that has performed the procedure described above may subsequently perform the reception of a physical downlink control channel signal and / or a physical downlink shared channel signal (S617) and the transmission of a physical uplink shared channel (PUSCH) signal and / or a physical uplink control channel (PUCCH) signal (S618) as a general uplink / downlink signal transmission procedure.

[0109] Control information transmitted by a terminal to a base station is collectively referred to as uplink control information (UCI). UCI includes HARQ-ACK / NACK (hybrid automatic repeat and request acknowledgment / negative-ACK), SR (scheduling request), CQI (channel quality indication), PMI (precoding matrix indication), RI (rank indication), BI (beam indication) information, etc. In this case, UCI is generally transmitted periodically via PUCCH, but depending on the embodiment (e.g., when control information and traffic data need to be transmitted simultaneously), it may be transmitted via PUSCH. Additionally, the terminal may transmit UCI non-periodically via PUSCH in response to a request or instruction from the network.

[0110] Figure 7 is a figure showing an example of a communication structure that can be provided in a 6G system.

[0111] 6G systems are expected to have 50 times higher simultaneous wireless connectivity than 5G wireless communication systems. URLLC, a key feature of 5G, will become an even more dominant technology in 6G communication by providing end-to-end latency of less than 1ms. Unlike the frequently used area spectrum efficiency, 6G systems will exhibit significantly superior volume spectrum efficiency. 6G systems can provide very long battery life and advanced battery technologies for energy harvesting, meaning mobile devices in 6G systems will not require separate charging. New network characteristics in 6G may include the following.

[0112] - Satellite Integrated Network: 6G is expected to be integrated with satellites to provide a global mobile population. Integrating terrestrial, satellite, and airborne networks into a single wireless communication system is crucial for 6G.

[0113] - Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is innovative and will update wireless evolution from "connected things" to "connected intelligence." AI can be applied at each stage of the communication process (or at each step of the signal processing described below).

[0114] - Seamless integration of wireless information and energy transfer: 6G wireless networks will transfer power to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated.

[0115] - Ubiquitous Super 3D Connectivity: Connectivity to the network and core network functions of drones and very low Earth orbit satellites will create Super 3D connectivity in 6G ubiquitous.

[0116] Some general requirements regarding the new network characteristics of 6G mentioned above may be as follows.

[0117] - Small cell networks: The idea of ​​small cell networks was introduced to improve the quality of received signals in cellular systems as a result of increased throughput, energy efficiency, and spectrum efficiency. Consequently, small cell networks are an essential feature of communication systems for 5G and beyond 5G (5GB). Therefore, 6G communication systems also adopt the characteristics of small cell networks.

[0118] - Ultra-dense heterogeneous network: Ultra-dense heterogeneous networks will be another important characteristic of 6G communication systems. Multi-tier networks composed of heterogeneous networks improve overall QoS and reduce costs.

[0119] - High-capacity backhaul: Backhaul connections are characterized as high-capacity backhaul networks to support high-volume traffic. High-speed fiber optics and free-space optics (FSO) systems can be possible solutions to this problem.

[0120] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communication is one of the functions of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0121] - Softwarization and virtualization: Softwarization and virtualization are two important features that form the basis of the design process in 5GB networks to ensure flexibility, reconfigurability, and programmability. Additionally, billions of devices can be shared across a shared physical infrastructure.

[0122] < Reconfigurable intelligent surface (RIS) >

[0123] RIS is a plate-shaped device made of electromagnetic (EM) material. Because RIS can be controlled electronically, it is expected to have high utility in the field of wireless communication. Generally, wireless communication environments are difficult to control artificially, but RIS opens up the possibility of controlling wireless environments. Through the utilization of RIS, it may ultimately become possible to control wireless communication environments.

[0124] The biggest advantage of RIS is that it can change the radio environment as desired to improve the quality of the received signal.

[0125] The main characteristics of RIS are as follows.

[0126] Since RIS is a passive element, it does not require an energy source such as a power supply.

[0127] RIS is a continuous plate-shaped element that can shape all waveforms entering the RIS into a desired form and reflect them.

[0128] Since RIS does not require an ADC (Analog to Digital Converter) or DAC (Analog to Digital Converter), it is not affected by receiver noise.

[0129] Since RIS does not have a specific operating frequency, it can be used across the entire available band.

[0130] RIS can be easily deployed. For example, RIS can be operated by simply attaching it to the exterior walls of a building, the ceiling of an interior, the walls or ceiling of a factory, human clothing, etc.

[0131] Rate-splitting is an advanced strategy used in multiple access communication systems that enables efficient data transmission when multiple users simultaneously share a single frequency band. The basic idea is to maximize transmission efficiency by dividing the entire data bit into multiple parts and allocating each part to different users for transmission. This splitting is performed by considering various channel conditions or requirements among the diverse users, and the divided data is transmitted simultaneously. Each user receives the data part allocated to them, restores it, and reconstructs the original data. Currently, the rate-splitting technique is being researched as RSMA (Rate-Splitting Multiple Access), a type of multiple access method, and is being proposed as a technology focused on the efficient utilization of frequency resources.

[0132] Methods utilizing the characteristics of Rate-Splitting technology are currently being continuously researched. There has been a persistent demand for technologies to satisfy the Quality of Experience (QoE) of user terminals, and to this end, attempts to increase user terminal throughput by improving spectral efficiency or interference mitigation have been ongoing. To this end, technologies capable of securing increased channel capacity through techniques such as Space-Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA) have been introduced. However, these technologies had various problems, including limitations in spatial resources, power control complexity, and SIC limitations. To address these issues, Rate-Splitting Multiple Access (RSMA) was proposed as a technique that maintains high performance by efficiently utilizing frequency resources through the introduction of optimizations such as message splitting, precoding, beamforming, and the WMMSE approach. However, in actual multi-cell environments, the proposed RSMA technique faces the problem of increasing the SIC complexity originally proposed. Therefore, methods to perform complex precoding and beamforming optimization in C-RAN-based Centralized Units (CUs) are currently being proposed. In addition, as the efficiency of the common stream decreases due to message splitting as the number of users increases, clustering techniques are also being proposed to solve this problem.

[0133] The descriptions of terms and abbreviations used in this specification are as follows.

[0134] - RSMA (Rate Splitting Multiple Access): Rate Division Multiple Access

[0135] - OMA (Orthogonal Multiple Access): Orthogonal Multiple Access

[0136] - SC (Superposition Coding): Nested coding

[0137] - SIC (Successive Interference Cancellation): Sequential interference cancellation

[0138] - RIS (Reconfigurable Intelligent Surface): Intelligent reflector

[0139] - SRE (Smart Radio Environment): Intelligent wireless environment

[0140] In this specification, User may be interpreted / replaced with Terminal (UE).

[0141] This specification proposes a method to configure each user's data stream through message partitioning based on a Downlink RSMA system in a multi-cell network, and to increase channel capacity through stream-based clustering and beamforming optimization. Specifically, the objective of this specification is to minimize interference in stream-based clustering by using RIS to enhance channel similarity for each user.

[0142] A multi-cell network consists of a Serving Base Station (BS) that services user terminals and Coordinated Base Stations that cooperate with it. User terminals connected to the Serving BS experience performance degradation due to SINR (Signal to Interference plus Noise Ratio) at the cell edges. To overcome this, standardization of Coordinated Multi-Point (CoMP) technology, a multi-cell cooperation technique, began with 3GPP Release 11. CoMP enables communication with the same terminal by utilizing not only the Serving cell but also neighboring cells, thereby forming a form of virtual MIMO. This technology can improve the throughput of users experiencing performance degradation at the cell edges. However, using CoMP increases complexity because it requires cooperation between base stations to support users. Coordination regarding data exchange, resources, and scheduling between each base station is necessary, making management complex. Furthermore, delays occur during the preceding data exchange and coordination, which can cause interference to other users of the cooperating base station and degrade performance. Research on CoMPs has continued to overcome these disadvantages. CoMPs can be classified as shown in Figure 8.

[0143] Figure 8 illustrates the classification of CoMP technology. Specifically, CoMP can be classified into Coordinated Scheduling (CS), Coordinated Beamforming (CB), and Joint Processing (JP). Here, JP can be classified into Joint Transmission (JT) and Dynamic Point Selection (DPS).

[0144] CS is a method that shares channel information (CQI, PMI, RI, SINR, etc.) between the Serving cell and the Coordinated cell and appropriately allocates each frequency resource through scheduling. Through CS, resources can be dynamically allocated based on channel conditions. CB performs cooperative communication by allocating different beam patterns and assigns beam patterns to avoid interference. CS and CB are typically used together; they dynamically allocate different frequency resources and simultaneously cooperate to assign beamforming patterns. Interference can be avoided through CS, while reception performance throughput can be improved through CB.

[0145] JT is a method in which the Serving cell and the Coordinated cell use the same frequency / time resources to transmit the same data simultaneously. While receiving the same data redundantly can increase throughput, synchronous scheduling for simultaneous transmission is essential. Low-latency signaling is required for simultaneous transmission, and X2 / Xn is required depending on the deployment of JT cells and Serving cells. DPS is also a JP family method in which multiple cells share the same data. Although the cell backhaul prepares to transmit the same data to each cell, the DPS method actually operates through a single cell with the best channel condition based on the terminal's channel status, performing dynamic switching at the subframe level. When the cell with the best condition starts transmission, the remaining DPS cells mute that subframe.

[0146] CoMP considering 5G and beyond is also being researched, and a framework rather than a specific technique is being proposed. This framework, referred to as Generalized CoMP, is divided into three stages: Inputs, Decision Making, and Outputs. This will be explained below with reference to Fig. 9.

[0147] Figure 9 illustrates a Generalized CoMP structure.

[0148] Referring to Figure 9, examining each step reveals that the Inputs consist of User Requirement, CoMP Architecture, and CoMP Scenario. The first input component, User Requirement, can include elements such as Throughput, Capacity, Latency, Mobility, and Connectivity. Security is also considered as an input component. For example, if Multi-Transmission is used, Capacity can be increased. The second input component, CoMP Architecture, can include Centralized or Distributed coordination structures. An example of a Centralized structure is C-RAN (Cloud RAN). While C-RAN can reduce network management and OPEX (Operational Expenditure) in CoMP, it increases the load on Backhaul and requires meeting latency requirements. In such cases, it is difficult to apply to latency-sensitive services like V2X. Recently, concepts such as Fog / Edge Computing have been proposed, and research is being conducted in a direction that can reduce latency in Centralized structures. The third input component, Scenario, consists of three CoMP scenarios proposed by 3GPP: Homogeneous intra-site CoMP, Inter-site CoMP, and HetNets. In the intra-site scenario, there is no additional backhaul load because CoMP cells and nodes exist at the same site. However, the other two scenarios require high-speed backhaul links and additional connections between Transmission Points (TPs).Furthermore, since HetNets include NTNs (Non-Terrestrial Networks), this is a scenario that requires techniques different from existing communication methods.

[0149] The second step in GCoMP configuration is Decision Making. This is the stage where the most optimal CoMP technique is determined using the previously provided inputs. In this stage, inputs can be handled using three approaches: user-centric, network-centric, and hybrid. User-centric approaches aim to meet the specific requirements of a particular user. Network-centric approaches aim to simplify the implementation of the entire network while maximizing performance for all users to meet their requirements. Hybrid approaches appropriately combine the two methods above to tailor the network to the specific user's requirements according to the situation. Additionally, two methods—Triggered Update and Periodic Update—are proposed for how to apply these approaches.

[0150] The final stage involves determining the outputs through the two steps of Inputs and Decision Making. To date, the optimal CoMP has been found through the preceding two stages, and the results consist of proven CoMP techniques such as CS / CB, JT, and DPS. GCoMP is a framework proposed to flexibly respond to 5G and the numerous services that will be added thereafter. Rather than using a fixed CoMP technique, its purpose is to configure Coordination Areas (CAs) according to various requirements and dynamically adapt to those requirements depending on the situation.

[0151] Research on such CoMP techniques was also considered in Rate-Splitting Multiple Access (RSMA). Among the RSMA strategies considered in the transceiver architecture design of Downlink RSMA, Rate-Splitting and Common Message Decoding (RS-CMD) and Generalized RS were proposed. This will be explained below with reference to Figures 10 and 11.

[0152] FIG. 10 illustrates the structure of a transceiver to which an embodiment of the present specification can be applied. Specifically, FIG. 10 shows a k-user RS-CMD transceiver in a MISO BC.

[0153] RS-CMD was initially proposed for application in C-RAN. A method can be used in which streams are transmitted to base stations via rate-splitting in the backhaul, distributed at the base station level, and combined at the user. Referring to Fig. 10, the difference in the RS-CMD technique is that there is no Message Combiner at the transmitter. user-k's message at the transmitter Is , It is divided into two sub-messages. As a result When exists The sub-message of must be encoded. Therefore The transmit signal of can be expressed as in the following mathematical equation 1.

[0154]

[0155] also Is It must have a layer SIC structure. Decoding the common stream and then the private stream Decodes. The decoding order When defined as, common stream and private stream The rate is defined as shown in mathematical formulas 2 and 3 below.

[0156]

[0157]

[0158] Therefore, the whole The achievable rate of can be expressed as shown in the following mathematical equation 4.

[0159]

[0160] FIG. 11 illustrates a model related to CoMP to which embodiments of the present specification can be applied. Specifically, FIG. 11 shows a Generalized RS framework proposed for the purpose of increasing the achievable rate by considering QoS.

[0161] Referring to Fig. 11, the entity performing rate-splitting to apply CoMP is named the Central Controller. The proposed CoMP technique using Generalized RS involves the Central Controller performing rate-splitting. It performs message optimization and distributes it to the relevant base stations. In the proposed method, since the Central Controller acts as a kind of backhaul, it is assumed that there is no delay in the channel between the receiving base station and the controller. Referring to Fig. 11, the message of each user among the three users 4 sub-messages each , , It is divided through Rate-Splitting. Sub-message It is encoded into a 3-order stream This becomes a 2-order stream Each , , It consists of. Therefore, the transmitted signal can be expressed as shown in the following mathematical equation 5.

[0162]

[0163] The beamformer for transmit signal x is It is configured as follows. Transmit signal x must be delivered to the relevant base station. When Transmit signal x is delivered from the base station to the user, the corresponding sub-messages are classified via SIC. For example, in the case of user-1, stream Decoding is performed based on SIC. As described above, Generalized RS divides user messages into sub-messages and performs optimization for each order. The above method utilizing RSMA guarantees QoS through sub-messages. Furthermore, according to the above method, when the transmission ratio of Serving BS and Coordinated BS is adjusted according to channel conditions, it can demonstrate dynamic interference management compared to NOMA (Non-Orthogonal Multiple Access) or SDMA (Spatial Division Multiple Access), thereby showing relatively high performance. However, the RSMA technique inevitably requires high transceiver complexity as the number of users increases. It is a solution that can only be used to a limited extent in realistic macro cells. Considering the performance degradation caused by transceiver complexity as the number of users increases, 1-layer RS ​​demonstrates the least dependence on the number of users.

[0164] Since CoMP technologies aim to improve terminal performance at the cell edge, they inevitably result in sacrifices for other users in the serving cell and the coordinated cell. Furthermore, the coordinated cell must separately allocate beamforming and frequency resources for neighboring terminals. The proposed method utilizes 1-layer Rate-Splitting to mitigate interference from other users in the serving cell, and employs RIS for beamforming in the coordinated cell to minimize the impact on existing users within the coordinated cell. In situations where throughput drops due to SINR degradation in the serving cell, Common messages are allocated to the serving cell via Rate-Splitting and Private messages are allocated to the cooperating coordinated cell to improve the SINR of the users in that serving cell. To achieve this, the serving cell and the coordinated cell perform signaling for scheduling, and a Central Processor acting as a Backhaul optimizes the Rate-Splitting to be delivered to each cell. Optimized Common messages are delivered to the Serving cell to convey the user's Common messages, while Private messages are delivered from the Coordinated cell, thereby achieving an overall SINR improvement. The Coordinated cell also performs RIS beamforming optimization with the user in the Serving cell to minimize the impact on other users in the existing Coordinated cell.The proposed method guarantees throughput to users of the serving cell while minimizing the impact of the cooperating coordinated cell, and simultaneously achieves SINR mitigation for other users.

[0165] As mentioned above, CoMP technologies are used in multi-cell network environments to improve the performance of the entire network; a similar technology is Stochastic Coordinated Beamforming (SCB). Like CoMP-JT, this technology optimizes beamforming through cooperation between base stations. While the objective of reducing interference between base stations is similar, it focuses on optimizing beamforming vectors by utilizing Stochastic Channel State Information (CSI). The difference is that while CoMP-JT aims for multiple base stations to transmit data to the same user simultaneously, SCB aims for multiple base stations to cooperate to optimize the overall beamforming vector, thus placing greater emphasis on beamforming vector optimization than on data transmission.

[0166] < RSMA(Rate Splitting Multiple Access) >

[0167] RSMA technology is a multiple access technique in wireless communication systems that provides a method for efficiently managing interference and resources among multiple users. Its key feature is the division of messages into common messages and private messages. Furthermore, since common messages can be eliminated through sequential interference cancellation techniques, interference caused by common messages can be removed when decoding private messages. In other words, when decoding private messages, only interference from other users' private messages exists. This means that the rate at which interference signals can be decoded can be controlled.

[0168] RSMA technology is still in the research stage where standards have not yet been established, and therefore there are no precise guidelines on how to use frequency and time resources. However, research exists that proceeds in the same direction as the frequency usage methods used in NOMA (Non-orthogonal Multiple Access) technology. That is, all users share frequency and time resources. This will be explained below with reference to Figures 12 and 13.

[0169] FIG. 12 illustrates a communication environment in an RSMA system. Specifically, FIG. 12 illustrates k terminals using an RSMA-based communication environment.

[0170] Figure 13 illustrates the baseband transceiver structure in an RSMA system.

[0171] Specifically, FIG. 13 shows the structure of a 1-layer RS ​​(Rate Split) transmitter and receiver for k terminals. Depending on the antenna structure of the transmitter and receiver class The number of can change.

[0172] The transmitter on the left is a baseband structure for transmitting messages to k terminals. The 1-layer RS ​​structure combines the common message of all terminals into one and transmits the remaining private messages to each terminal. The message from each terminal is Represented as, and shared message by Message Splitter private message It is divided into. Each user's shared messages are combined by the Common Message Combiner. It forms, and individual messages are separated, enter an encoder, and are encoded. It forms. Subsequently, precoding is performed by the precoder, and transmission occurs after RF processing. Therefore, at the transmitter, k+1 messages are transmitted as signals. It forms, and here It depends on the transmitting and receiving antennas. Transmitted signal It is equal to the following mathematical formula 6.

[0173]

[0174] The signal received by the k-th terminal It is equal to mathematical formula 7 below.

[0175]

[0176] is a channel for terminal k, and is a precoding matrix, and is Gaussian Channel Noise.

[0177] The transmission rates of each user's shared messages and private messages are given by the following mathematical formulas 8 and 9.

[0178]

[0179]

[0180] In addition, for all terminals to decrypt the shared message, they must satisfy the conditions according to Equation 10 below.

[0181]

[0182] Referring to FIG. 13, in the receiver of terminal k When receiving, first share the message Decodes it. And the original message Decrypted shared message Remove using the Sequential Interference Cancellation (SIC) technique, and decode the remaining private messages. Decoded shared message private message Each is combined through Combine to form the message of terminal k.

[0183] A wireless environment and an intelligent wireless environment will be described below with reference to FIGS. 14 and 15.

[0184] Smart Radio Environment

[0185] According to current wireless technology, H, the channel in the wireless environment, is defined as naturally fixed and uncontrollable random. Therefore, an optimal transmission and reception method adapted to that channel is sought.

[0186] FIG. 14 illustrates a conventional wireless environment. Specifically, FIG. 14 illustrates a conventional wireless communication technology that adapts to a wireless environment. According to conventional wireless communication technology, the transceiver is controlled to optimize communication. Conventional wireless technology optimizes by recognizing and compensating for the current channel, but limitations arise in poor NLOS environments, such as dead zones.

[0187]

[0188] According to Shannon's capacity limit, no matter how much the transmitted signal P is precoded and processed, the channel If the size is small, it is impossible to increase channel capacity. Therefore, intelligent wireless environment technology has emerged that uses a configurable intelligent surface (RIS) to use the wireless channel environment as a factor to control the transceiver.

[0189] Figure 15 illustrates an intelligent wireless environment.

[0190] Specifically, FIG. 15 illustrates an intelligent wireless environment technology (SRE) called Wireless 2.0. According to the intelligent wireless environment technology, the channel H of the wireless environment is considered a controllable factor, and Joint Optimization is performed by adding the environment (channel) H to End-Points Optimization.

[0191] A theoretical communication model for a wireless environment will be explained below with reference to FIGS. 16 and FIGS. 17.

[0192] Figure 16 illustrates a communication theory model for a conventional wireless environment. Figure 17 illustrates a communication theory model for an intelligent wireless environment. Referring to Figures 16 and 17, the current wireless communication environment is denoted as P1, and the intelligent wireless environment is denoted as P2. P1 and P2 represent the probability of receiving a signal y when a signal x is sent, respectively.

[0193] Referring to Fig. 16, in the current wireless environment, P1 is fixed, and the receiver (Decoder) measures the transmitted signal and sends feedback to the transmitter. Based on the feedback, the transmitter controls the transceiver to adapt to the communication environment. As a specific example, the receiver (e.g., terminal) measures the Channel Quality Indicator (CQI) for the transmitted signal and feeds it back to the transmitter (e.g., base station). Based on this, the transmitter adjusts the MCS and informs the receiver.

[0194] Referring to Fig. 17, in an intelligent wireless environment, wireless environment P2 is recognized and the wireless environment can be changed through RIS control. At the same time, feedback is received from the receiver, and the transceiver can also be optimized.

[0195] Below, the structure and operating principle for the embodiments of the present specification will be examined in detail with reference to FIG. 18.

[0196] First, we examine the scenario environment configuration related to the embodiments of this specification.

[0197] The structure and method proposed in this specification is a method for increasing channel capacity by configuring message stream-based clustering divided through rate-splitting in a mobile communication environment where k terminals exist based on a downlink RSMA system, and performing optimization based thereon. In addition, a method is also proposed to improve signal quality by minimizing interference between clusters using RIS optimization to enhance user channel similarity.

[0198] In a multi-cell network environment, network architectures based on centralized processing, such as C-RAN (Centralized, Cloud, Coordinated, Clean-RAN), can be applied to optimize the entire network within a Centralized Unit (CU). By configuring a Central Baseband Unit (BBU) within the CU, C-RAN can expect improvements in overall network resource utilization, resource sharing, and data processing capabilities. However, due to capacity limitations of the Fronthaul Interface between the CU and the BS (or RRH, Remote Radio Head), high Fronthaul performance is required to overcome these limitations. Furthermore, additional constraints regarding Fronthaul capacity must be calculated in addition to the constraints required for optimization calculations.

[0199] FIG. 18 illustrates the structure of a Downlink RSMA system according to an embodiment of the present specification. Specifically, FIG. 18 shows a C-RAN architecture.

[0200] Each BS (e.g., Radio Remote Head (RRH) or Transmission and Reception Point (TRP)) is connected to a CU and is controlled to use allocated resources through the CU's centralized processing. The CU allocates resources to be used by each BS and delivers them to each BS. The RIS can be controlled via the CU or by being connected to the BS. The CU calculates resource allocation based on Downlink RSMA. The CU separates the messages delivered to each BS into a Common stream and a Private stream. The most suitable scheme for C-RAN-based Downlink RSMA is Rate-Splitting Common Message Decoding (RS-CMD). According to RS-CMD, the CU separates all signal components into a Common stream and a Private stream and delivers them to each BS.

[0201] This specification proposes a method in which Common / Private streams divided by the CU are optimized and then allocated to each BS. Additionally, according to an embodiment of this specification, a structure is used in which the optimization of the RIS is performed by the CU. The CU forms clusters based on RIS channel similarity enhancement and delivers them to each BS. The BS applies beamforming optimization to the allocated streams and delivers signals to each user.

[0202] The CU receives parameters for optimization through a connection with each BS. Specifically, the CU receives the beamforming vector and maximum power for power constraints of each base station in advance and uses them in optimization calculations. In addition, the CU receives reflection coefficient information for adjusting the phase pattern of the RIS. The path through which information is transmitted may differ depending on whether the RIS is directly connected to the CU or connected to a BS. In the system according to the embodiment of this specification, since the CU performs optimization for beamforming and the RIS phase pattern, the information described above is transmitted to the CU, and the information transmitted by the CU is used and managed. The procedure for RIS control will be described in detail below with reference to FIG. 19.

[0203] FIG. 19 illustrates a procedure for RIS control according to an embodiment of the present specification. Specifically, FIG. 19 shows an initial setup and an RIS control method procedure.

[0204] In S1910, the phase information of the RIS is shared with the CU. If the RIS ownership is in the CU, the CU receives the phase information from the RIS (S1911). If the RIS ownership is in the BS, the BS (e.g., BS1) receives the phase information from the RIS and transmits the phase information to the CU (S1912).

[0205] In S1920, each BS transmits parameters for optimization to the CU. Specifically, the parameters may be related to at least one of power constraints, precoding vectors, and / or CSI.

[0206] In S1930, the CU generates a codebook composed of pre-calculated codewords based on the phase information of the RIS. This codebook contains multiple codewords. Each codeword provides a specific beam direction or reflection pattern. According to the present embodiment, the codebook specifies a codeword for the beam pattern of the RIS.

[0207] In S1940, the CU transmits information about the codebook (i.e., RIS codebook information) to the users (UEs). Specifically, the information about the codebook can be transmitted to the users through BS (BS1, BS2).

[0208] In S1950, the phase of the RIS based on the codebook is changed, and channel status information is reported based on this.

[0209] To perform codebook-based initial RIS beam training, a RIS reflection pattern is formed by sequentially applying each codeword defined in the codebook using a Synchronization Signal Block (SSB) or CSI-RS. The CU changes the phase of the RIS based on the codebook. For example, the CU transmits information indicating the phase change to the RIS (S1951).

[0210] In S1952, each BS requests channel state information from each UE. For example, each BS may send information (e.g., DCI) to each UE that triggers the reporting of channel state information. Each BS may send SSB and / or CSI-RS to the UE.

[0211] In S1953, each UE measures the signal strength for each codeword and feeds it back to the BS as channel state information. For RIS channel measurements, the UE reports the channel state for all codebooks to the BS, even if it is a codebook-based channel measurement. Each UE reports the channel state information to the BS (e.g., the BS connected to the UE), and the BS transmits the channel state information to the CU.

[0212] In S1971, the CU optimizes beamforming and resources for the user based on channel state information received from each BS. The CU transmits the optimized parameters to the BS and RIS, respectively. The parameters may be related to at least one of a beamforming vector, power allocation, and RIS element coefficient.

[0213] < RIS Channel Similarity-Based Clustering and Stream Allocation Method >

[0214] Performance in a wireless communication system can be improved through channel similarity enhancement using RIS. According to an embodiment of this specification, clustering is performed to improve channel capacity by minimizing user interference through the formation of clusters based on RIS channel similarity enhancement between users. Channel similarity is based on cosine similarity. The cosine similarity is two vectors ( and It relates to the directional similarity between. Since the method utilizing the above cosine similarity focuses on direction rather than the magnitude (length) of the vectors, it is useful for indicating how similar the directions of two vectors are. Cosine similarity is mainly used in the fields of text mining, information retrieval, and clustering. Cosine similarity can be defined as shown in the following mathematical equation 12.

[0215]

[0216] is the inner product of two vectors, and and are each vector and It is the norm (i.e., the magnitude of the vector). As a result of the above equation, the cosine similarity has a value between -1 and 1.

[0217] 1: When two vectors have exactly the same direction

[0218] 0 : When two vectors are orthogonal to each other, i.e., when there is no correlation

[0219] -1 : When two vectors have completely opposite directions

[0220] Clustering and clustering algorithms generally separate data based on dissimilarity or distance, so they calculate dissimilarity as shown in Equation 13 below.

[0221]

[0222] Non-apostolic is used as a measure indicating how different two vectors are. A value closer to 0 signifies higher similarity; however, since the proposed technique must achieve transmission rate maximization through RIS phase optimization, cosine similarity is used as is. The method according to the embodiments of this specification enhances similarity between UEs through RIS phase optimization for the purpose of the maximum sum-rate. Through the above method, a cluster for the optimal RIS channel can be configured. The above method can be performed as follows.

[0223] Channel information is collected for the available phase patterns of the RIS, and channel similarity for all users is calculated based on this. Through this, clusters are formed first, and optimization is performed based on the generated clusters. The edge entities (BS, RIS, etc.) of the proposed system transmit the collected channel information to the upper Main function (CU), and the Main function performs the optimization calculation as described above.

[0224] The proposed technique enhances the similarity between user UEs through RIS phase optimization and groups common user streams into clusters based on this channel similarity. A method to maximize the similarity of existing users through the addition of a single RIS beam is to form a single RIS beam based on maximum similarity. This is an approach that optimizes the RIS phase pattern to maximize the channel similarity of a specific pair or group of users. To achieve this, RIS optimization is required. A method for optimizing the RIS reflection beam based on maximum similarity is explained with reference to Fig. 20.

[0225] FIG. 20 illustrates a procedure for enhancing channel similarity using RIS according to an embodiment of the present specification. Specifically, referring to FIG. 20, the CU performs operations based on S2010 to S2060. These will be explained in order below.

[0226] Channel status information collection (S2010)

[0227] Channel vector between each user and base station Collect and the channel matrix between each user and the RIS and channel vector between base station and RIS Collects. This can be achieved by setting up codebooks based on RIS phase information and measuring user channels for all codebooks accordingly during the initial setup step for optimization shown in Fig. 19.

[0228] Channel Similarity Improvement Evaluation (S2020)

[0229] Each user pair For this, calculate the channel similarity with added RIS.

[0230] The channel similarity in the case without RIS is given by the following mathematical formula 14.

[0231]

[0232] The channel similarity when RIS is applied is given by the following mathematical formula 15.

[0233]

[0234] The objective function for the maximum similarity enhancement criterion can be set as shown in the following mathematical equation 16.

[0235]

[0236] The above objective function is intended to maximize the sum of channel similarities for all user pairs. To this end, the objective function is set / defined in the form of calculating the channel similarity for each user pair and summing them.

[0237] RIS reflection coefficient optimization using iterative optimization algorithm (S2030)

[0238] The gradient of the RIS phase with respect to channel similarity is calculated. The gradient can be based on the following mathematical formula 17.

[0239]

[0240] The RIS reflection coefficient is updated using the gradient ascent method based on Equation 18 below.

[0241]

[0242] Here, α is the learning rate. Existing iterative optimization algorithms, such as Gradient Ascent, are used to repeat the process until the magnitude of the gradient converges to below a certain threshold. That is, the update of the reflection coefficients is repeated until the magnitude of the gradient falls below a certain threshold. Through this, the optimal RIS reflection coefficients for similarity enhancement using the proposed RIS are obtained.

[0243] Optimal RIS topology based on the aforementioned RIS optimization (or reflection coefficient) and user channel similarity based thereon (Mathematical Equation 19 below) can be obtained (S2040). Here, the entire user About (Mathematical Equation 20 below) is a set of common streams, and each user Channel similarity between and other user j It is based on. Channel similarity has a value between 0 and 1; the closer it is to 0, the more different the channel states are, meaning that the two users are communicating through different signal paths. The closer the channel similarity is to 1, the more similar the channel states are, meaning that the two users are communicating through almost the same signal.

[0244]

[0245]

[0246] is the channel between the base station and the RIS, and is a channel between RIS and the user. is a direct channel between the base station and the user, and is the reflection coefficient matrix of the RIS. Also, the channel similarity threshold By defining the user cluster of A channel similarity threshold is configured (S2051). If there is no channel similarity threshold, each user is configured into a common cluster, and when there are K users, K common clusters are configured (S2052). Subsequently, when a channel similarity threshold is set, the number of common clusters decreases accordingly, and the cluster size increases.

[0247] In S2060, the private stream and common cluster allocation algorithms are performed.

[0248] The clustering technique is performed based on the validity of distance-based clustering. The objective of the proposed clustering is to achieve load balancing by allocating RS-CMD-based partitioned streams to the optimal BS. That is, the objective of the clustering is the maximum number of streams that each BS can support ( It allocates the optimal stream to the user without exceeding ). In addition, it performs efficient clustering by considering both common streams with multicast characteristics and private streams with unicast characteristics.

[0249] Operations related to clustering and cluster allocation will be described below with reference to FIGS. 21 and 22.

[0250] FIG. 21 illustrates layer-by-layer clustering according to an embodiment of the present specification. FIG. 22 illustrates channel similarity-based clustering and stream allocation procedures according to an embodiment of the present specification. Specifically, referring to FIG. 22, the CU performs operations based on S2210 to S2260. These will be described in order below.

[0251] Initialization step

[0252] CU is the maximum number of streams that each base station n can support. It sets. This is information included in the power constraints of the initial configuration information that the CU receives from each BS. The CU for each user Regarding candidate BS cluster for , Sets (S2210).

[0253] CU is each user Layering for Hierarchical Clustering is determined based on channel similarity (S2220). Channel similarity threshold In this undefined initial clustering phase, clusters of common streams are formed based on the order of similarity using channel similarity between users. Subsequently, when the initial common stream clusters are formed, a channel similarity threshold is applied based on this. Defines and then allows channel similarity clustering to be performed before stream allocation (S2230).

[0254] Stream allocation (S2240)

[0255] CU is each stream ( , Select the strongest BS (channel state information, etc.) for ) and send that stream to each individual cluster common cluster Assign to. For example, a private stream Candidate BS It is assigned to the BS with the highest channel quality.

[0256] common stream In this case, the similarity clusters generated during the initialization phase are considered. That is, assignment to base stations is based on the similarity clusters generated during the initialization phase, rather than a single stream such as a private stream. In other words, the user Similarity clusters including Collective channel quality for Highest group channel quality based on The common stream set of candidate BS n having Assign to.

[0257] However, similarity threshold In this undetermined initial phase, clusters are not formed during the stream allocation phase. Therefore, just like private streams, each common stream channel quality It is assigned to the BS with the highest channel quality based on the results.

[0258] When stream allocation is complete, in the case of the initial stream-based clustering, the common stream set The streams are individual streams that are not clustered. The common stream set of BS N Clusters the users assigned to. The users included in are clustered, and the final similarity is transmitted to the CU. The subsequent channel similarity threshold is determined using the similarity received from each BS. Perform clustering-based stream allocation by configuring it. The final similarity is determined by the similarity of the final layer when the allocated BS streams are clustered, and is passed to the CU.

[0259] Stream allocation exceeded (S2250)

[0260] If the maximum stream that the allocated BS N can accommodate If it exceeds, remove the stream with the weakest channel quality and attempt to re-allocate next.

[0261] If a common stream cluster is removed, attempt to perform stream allocation after re-clustering by setting the similarity threshold to a value higher than the current value.

[0262] Stream allocation iteration (S2260)

[0263] CU repeats the stream allocation operation until all streams are allocated or all BSs reach the maximum capacity limit.

[0264] Similarity threshold after initialization Pre-common stream clustering operation based on

[0265] The clustering operation used in the proposed technique ensures that, in the initial operation, the private stream and the common stream have the same channel quality of each stream ( : Private stream channel quality, : Determined based on common stream channel quality. In other words, the channel similarity threshold If not determined, the individual streams and common streams separated by RS-CMD's Rate-Splitting are individually assigned to the BSs. Subsequently, when the assigned streams are clustered, the similarity of the final layer is passed to the CU to determine a threshold. If a threshold exists, the common stream clusters prior to stream assignment. is determined.

[0266] Stream-based clustering techniques form clusters one by one among users with the highest similarity, based on each user's channel similarity. Below is an example of similarity-based hierarchical cluster layer formation.

[0267] Referring to Figure 21, when the similarity between users A, B, C, D, and E is calculated, clusters can be formed one by one in order of highest similarity. Layer 1 is a form in which each user is formed into a separate cluster. Layer 2 forms a single cluster {A, B} with users A and B, who have the highest similarity among the clusters. In Layer 3, clusters {D, E}, which have the next highest similarity, are formed. In Layer 4, clusters {C, D, E} are formed due to user C, who has the next highest similarity, and user D or E. In Layer 5, clusters {A, B, C, D, E} are formed because user A or B has the next highest similarity with one of users C, D, or E.

[0268] In the initialization phase, the similarity threshold Clustering is performed in order of similarity without. At this time, the channel similarity of each layer It is stored together. If the similarity threshold is If so, the common stream cluster can be composed of {A, B}, {C}, {D, E}.

[0269] Consequently, as a result of the initial stream-based clustering, a number of common clusters equal to the total number of users K is generated according to the order of channel similarity. Once the channel similarity threshold is determined after the initial stream-based clustering, the size of the common clusters increases accordingly, and the number of clusters decreases.

[0270] Stream Allocation-Based RIS and Downlink RSMA Beamforming Optimization >

[0271] According to the above-described embodiment, clustering of common streams is configured based on RIS channel similarity enhancement, and an operation is performed to allocate private streams and common streams / clusters to each BS based on channel quality, taking into account load balancing. Subsequently, optimization is performed to deliver the allocated streams to users with maximum throughput. The CU holds power constraints, precoding vectors, CSI channel information, and RIS phase coefficient information received from each BS and RIS, and performs optimization for each stream based on this. Once the beamforming vector information optimized for each stream is determined, the CU transmits the determined beamforming vector information to each BS and RIS to perform downlink communication.

[0272] An objective function was designed to achieve the maximum sum rate through the optimization of the RIS phase pattern determined for similarity enhancement in clustering and the Common / Private streams assigned to each BS. According to this embodiment, Sample Average Approximation (SAA) and Weighted Minimum Mean Square Error (WMMSE) techniques are used for optimization. This is to maximize the minimization of interference between clusters caused by similarity enhancement using RIS. The objective function for performing optimization through SAA and WMMSE is given by the following Equation 21.

[0273]

[0274] The constraints for solving the objective function are as follows.

[0275] Power Constraints:

[0276] : This is the beamforming vector of the private message transmitted by base station n to user k. The square of the magnitude of this vector represents the amount of power transmitted through the corresponding beamforming vector.

[0277] : This is the beamforming vector of the common message transmitted by base station n to user k. The square of the magnitude of this vector represents the amount of power transmitted through the corresponding beamforming vector.

[0278] : This is the total power allocated to private messages transmitted by base station n to all users.

[0279] : This is the total power allocated to the common message that base station n transmits to all users.

[0280] : This is the maximum transmission power limit of base station n.

[0281] This power constraint is the total amount of power that each base station can transmit It ensures that it does not exceed.

[0282] Fronthole Capacity Constraints:

[0283] : It is the sum of the transmission rates of private messages sent by base station n to all users.

[0284] : It is the sum of the transmission rates of common messages sent by base station n to all users.

[0285] : This is the fronthole capacity limit of base station n.

[0286] This condition indicates that the fronthaul link capacity of each base station is limited and is a constraint required for the C-RAN system architecture. The total data transmission rate that each base station can transmit must not exceed this limit.

[0287] Transmission Rate Achievement Constraint (Personal Transmission Rate):

[0288] : This is the personal transmission rate of user k.

[0289] : It is the expectation operator for the channel state.

[0290] : It is the system's bandwidth.

[0291] : This is the signal-to-interference and noise ratio (SINR) for user k's private message.

[0292] This condition ensures that user k's individual transmission rate does not exceed the average transmission rate under specific channel conditions.

[0293] Transmission Rate Achievement Constraint (Common Transmission Rate):

[0294] : This is the common transmission rate of user k.

[0295] : This is the signal-to-interference and noise ratio (SINR) when user k decodes user i's common message.

[0296] : User k is the set of users to decode common messages.

[0297] This condition ensures that the common transmission rate of user k does not exceed the average transmission rate under specific channel conditions.

[0298] The SAA approach defines a sample size M to approximate the above objective function and defines the achievable transmission rate for each user as shown in the following Equation 22. Here and represents the individual and common signal-to-interference and noise ratio (SINR) in the m-th channel sample, respectively.

[0299]

[0300] : This is the transmission rate of user k.

[0301] : This is the sample size of SAA.

[0302] : This is the signal-to-interference and noise ratio (SINR) for user k's private message in sample m.

[0303] : This is the signal-to-interference and noise ratio (SINR) when user k at sample m decodes the common message of user i.

[0304] This equation represents a method for approximating the transmission rate using the SAA method, and the transmission rate can be estimated by calculating the average transmission rate through multiple channel samples.

[0305] Using SAA, the problem can be restructured as shown in the following mathematical equation 23.

[0306]

[0307] The constraints are as follows.

[0308] Power Constraints:

[0309] Fronthole Capacity Constraints:

[0310] Individual transmission rate achievement constraints:

[0311] Common Transmission Rate Achievement Constraints:

[0312] The problem transformed by SAA depends on the sample size M, which makes it easier to solve by converting the existing problem into a deterministic one thanks to SAA.

[0313] The WMMSE-based algorithm reconstructs the problem as shown in the following Equation 24 by utilizing the relationship between the transmission rate and MSE.

[0314]

[0315] The constraints are as follows.

[0316] Power Constraints:

[0317] Fronthole Capacity Constraints:

[0318] Individual transmission rate achievement constraints:

[0319] Common Transmission Rate Achievement Constraints:

[0320] The auxiliary variable u used when optimizing the problem through the WMMSE-based algorithm is the receiver coefficient ( It represents the optimal receiver for a specific channel realization. This is used to calculate the Minimum Mean Squared Error (MSE) of the received signal. It is also an auxiliary variable ( ) is used as a parameter for the weights for each user and each channel realization. It serves to solve the WMMSE optimization problem. That is, the receiver coefficient (u) plays the role of minimizing the Minimum Mean Squared Error (MSE) of the received signal by setting the optimal receiver for each user, and the auxiliary variable ( It is used to solve WMMSE optimization problems and helps to easily solve optimization problems by utilizing the relationship between MSE and transmission rate. Here and ε₀ is the Minimum Mean Squared Error (MMSE) of the private message and the common message, respectively. WMMSE-based algorithms utilize these auxiliary variables to optimize the transmission rate of each user and, consequently, maximize the sum transmission rate. This process is performed iteratively, updating receiver coefficients and auxiliary variables in each iteration to progressively compute the optimization problem. This technique is a method for solving the problem through the iterative optimization of general SAA and WMMSE.

[0321] < Method for compensating channel similarity due to user mobility, etc. >

[0322] If channel similarity changes due to user movement, it may affect the efficiency of the clusters configured in the previous procedure. This can be reported through user channel status reports (CSI-Reports), and the BS and CU must use this to determine whether to maintain or reconfigure the clusters based on changes in channel similarity. The channel similarity threshold used in the preceding stream-based clustering serves as the criterion for reconfiguring the clusters. This can be used. To this end, the CU transmits Time-To-Trigger (TTT) timer settings to the user terminal via the BS to perform measurements to compensate for user similarity. This timer is defined in ETSI TS 138 331 and is a function that executes a measurement report when specific event conditions are met within a set time. In the proposed method, measurements for channel similarity compensation are performed using TTT. In cooperative communication environments such as CoMP or C-RAN, channel conditions are primarily identified through Event A3 (Neighbor cell becomes offset better than serving cell), Event A5 (Serving cell becomes worse than threshold1 and neighbor cell becomes better than threshold2), and Events B1 / B2 (5G NR). If the same frequency is used, the Serving cell and Neighbor cell can be distinguished using Cell IDs, etc.

[0323] The proposed method utilizes Time-To-Trigger (TTT) to compensate for channel similarity degradation caused by beamforming of RIS and BS due to the movement of the user terminal. Since the proposed method uses a technique that guarantees SINR through the optimization of the Common stream and Private stream resulting from the Downlink RSMA technique to address channel state degradation, the proposed method compensates for maintaining channel similarity regarding user mobility. To this end, the CU transmits TTT timer settings for A3 / A4 / A5 / B1 / B2 events to the user. This is to provide an offset time, as user channel similarity may not degrade even if the signal strength of neighboring cells improves compared to the current cell. If channel similarity is maintained, a maximum sum rate can be obtained through optimization due to the effect of stream-based clustering. According to the embodiments of this specification, a procedure to identify situations where channel similarity degrades and to compensate for it can be performed as follows.

[0324] TTT settings for channel similarity:

[0325] The CU transmits TTT settings for channel similarity to the user via the BS. As with the legacy system, the trigger event can be an A3 / A4 / A5 / B1 / B2 event. Based on this event, calculations for user mobility must be performed at the user terminal. In this case, the threshold value is the threshold value for channel similarity evaluation. Delivers.

[0326] Mobility measurement evaluation

[0327] User mobility is evaluated through channel changes measured at regular time intervals for continuous channel states. In the proposed method, the mobility evaluation value transformation for comparing the mobility evaluation value with the channel similarity threshold is performed based on the following Equation 25.

[0328]

[0329] : Channel vector of user i at time t

[0330] : Channel vector of user i at time t-1

[0331] : Channel Vector The magnitude of the vector

[0332] : Vector magnitude of the change in the channel vector between time t and t-1

[0333] The purpose of the above mobility evaluation value transformation is to evaluate the user's mobility relatively by normalizing the mobility evaluation value to a value between 0 and 1. The higher the mobility, the lower the transformed value, and the lower the mobility, the higher the transformed value. Each transformation process has the following meanings.

[0334] This is used to calculate the change in the channel vector. The value indicates how much the channel vector of user i changed between time t and t-1. A larger change indicates greater user mobility.

[0335] represents the magnitude of the current channel vector. Specifically, the value represents the magnitude of the channel vector at time t.

[0336] represents the ratio of the change amount to the current channel vector magnitude. This ratio indicates the relative magnitude of the change amount to the current channel vector magnitude. The larger the change amount, the larger this ratio becomes, and the smaller the change amount, the smaller this ratio becomes.

[0337] It is obtained by subtracting the ratio of the change amount to the current channel vector magnitude from 1. The greater the mobility, the As the value decreases and mobility decreases, The value approaches 1. This is to match the change in the magnitude of the mobility evaluation value.

[0338] Mobility evaluation and channel similarity learning

[0339] Mobility and channel similarity are somewhat different concepts that cannot be directly compared. However, an approach that uses mobility ratings to predict changes in channel similarity can be valid. For example, if a user's mobility is high, channel similarity is likely to change rapidly. Through this, it is possible to predict changes in channel similarity for highly mobile users in advance and respond accordingly.

[0340] The proposed method classifies users into high-mobility and low-mobility groups based on mobility evaluation values. Channel similarity checks are performed more frequently for the high-mobility group, while a standard check cycle is maintained for the low-mobility group.

[0341] The proposed technique uses federated learning to train a model by updating the CU with mobility evaluation values ​​based on channel state information from the user, and the CU can train a global model by integrating this with channel similarity.

[0342] The CU learns mobility evaluation values ​​and changes in channel similarity using local data (channel state information) sent from each user terminal. The local loss function for learning is as follows. Here is a function that maps mobility evaluation values ​​to channel similarity. is the total length of time during the learning period, and This allows calculating the cumulative error over the entire training period, rather than the error at a single time step. The error can be measured by calculating the sum of the squares of the difference between the predicted value and the actual value using Equation 26 below.

[0343]

[0344] Channel similarity Channel similarity predicted based on mobility evaluation values The error is measured by subtracting from . A large error means that the prediction differs significantly from the actual value. The goal of model training is to minimize this error (loss). A smaller error means that the model's prediction is close to the actual value. To minimize this error, a loss function is defined, and the model's parameters are updated in the direction that minimizes it. The model update can be performed as shown in Equation 27 below.

[0345]

[0346] CU is a mobility evaluation value calculated based on the update of periodic / non-periodic channel state information for each user i. and local models based thereon Calculate and continuously update to update the global model. Here is a hyperparameter that determines the magnitude of parameter updates as the learning rate. Learning rate If ε is too large, it can oscillate near the optimal point, and if it is too small, the learning speed can become very slow. The appropriate value for the learning rate is generally found through training and experimentation. is the loss function It is the gradient with respect to . Here, the gradient indicates the direction in which the loss function heads toward the minimum point, and through this, the model parameters can be updated. The model updated through each user is used for continuous global model updates as shown in Equation 28 below.

[0347]

[0348] The user updates the global model by calculating the updates and averages of the local models. Here, N represents the total number of users. Updated global model Distribute to all users. Users are updated global models Use channel similarity threshold A decision is made on whether to reset the cluster by comparing with (see Equation 29 below).

[0349]

[0350] The above-described operations are illustrated in a flowchart as in FIG. 23. FIG. 23 illustrates a mobility evaluation value learning procedure for channel similarity compensation according to an embodiment of the present specification.

[0351] In S2310, CU is a global function for federated learning Deploys. Specifically, global function It is passed from the CU to each BS. Each BS is a global function Pass to each UE.

[0352] In S2320, each UE is a global function Updates.

[0353] In S2330, the CU has TTI settings and thresholds for channel similarity. It conveys. Specifically, TTI settings and thresholds. It is transmitted from the CU to each BS. Each BS has TTI settings and thresholds. Pass to each UE.

[0354] In S2341, the UE starts the TTT timer (triggered by channel condition degradation).

[0355] In S2342, the UE has a mobility measurement evaluation value ( Calculate )

[0356] In S2343, the UE applies the prediction channel similarity with a global function ( Calculate )

[0357] In S2344, prediction channel similarity ( ) this threshold If it is smaller, the UE requests a review of user channel similarity. The channel similarity review is transmitted to the CU via the BS (S2345).

[0358] In S2350, CU performs a user channel similarity review.

[0359] In S2360, a channel status update is performed.

[0360] In S2370, CU updates the loss function and the global function.

[0361] In S2380, after the above update, CU is a global function for federated learning Distribute.

[0362] In S2390, each UE is a global function Updates.

[0363] The effects derived from the embodiments described above will be explained in detail below.

[0364] This specification proposes a method to improve Quality of Experience (QoE) by increasing the channel capacity of all network users through the application of a Downlink RSMA system in an environment where C-RAN or multi-cell cooperative communication is performed. Furthermore, by utilizing RIS to enhance user channel similarity, the gain of common cluster formation in RSMA is maximized to improve the overall SINR, and the efficiency of clustering is improved by linking this with clustering techniques. Subsequently, a federated learning technique is introduced to maintain channel similarity, presenting a method capable of compensating for channel similarity through the learning of user mobility evaluation values.

[0365] In terms of implementation, the operations of the CU / BS / UE according to the embodiments described above can be processed by the device of FIGS. 1 to 5 described above (e.g., the processor (202a, 202b) of FIG. 2).

[0366] In addition, the operations of the CU / BS / UE according to the above-described embodiment may be stored in memory (e.g., 204a, 204b of FIG. 2) in the form of instructions / programs (e.g., instructions, executable code) for driving at least one processor (e.g., processor (202a, 202b) of FIG. 2).

[0367] The embodiments described above will be explained in detail below with reference to FIGS. 24 and FIG. 25 regarding the operation of the first to third wireless devices. The methods described below are distinguished only for convenience of explanation, and it is understood that a part of one method may be substituted with a part of another method or combined with one another and applied.

[0368] FIG. 24 is a flowchart illustrating a method according to one embodiment of the present specification.

[0369] Referring to FIG. 24, a method according to one embodiment of the present specification includes the steps of determining a reflection coefficient based on CSI (S2410), determining channel similarity (S2420), determining clusters based on channel similarity (S2430), and assigning private stream and common stream based on clusters (S2440).

[0370] In S2410, the first wireless device determines the reflection coefficient of the RIS (Reconfigurable Intelligent Surface) based on Channel State Information (CSI). The first wireless device can be interpreted / replaced with the aforementioned CU or base station.

[0371] In S2420, the first wireless device determines channel similarity based on the reflection coefficient.

[0372] In S2430, the first wireless device determines clusters for common streams associated with Rate Splitting Multiple Access (RSMA) based on the channel similarity.

[0373] In S2440, the first radio device assigns the common streams and private streams to the second radio devices based on the clusters. The second radio devices can be interpreted / replaced with a plurality of base stations, a plurality of Radio Remote Heads (RRHs), or a plurality of Transmission and Reception points (TRPs).

[0374] According to one embodiment, the channel state information may include first information, second information, and third information. The first information may include information related to the channel state between i) one of the third wireless devices and ii) one of the second wireless devices. The second information may include information related to the channel state between i) one of the third wireless devices and ii) the RIS. The third information may include information related to the channel state between i) one of the second wireless devices and ii) the RIS. The third wireless devices may be interpreted / replaced with a plurality of terminals (UEs).

[0375] According to one embodiment, first channel similarities can be calculated for all cases in which a pair is formed based on two of the third wireless devices. The pair may refer to the user pair (i, j) described above. The first channel similarities may be based on Equation 15.

[0376] According to one embodiment, among the reflection coefficients associated with the RIS, the reflection coefficient that maximizes the sum of the first channel similarities may be determined. The channel similarity may be based on the second channel similarities calculated for all cases based on the reflection coefficient. The reflection coefficient is determined based on Equations 16 to 18. It can be based on. The second channel similarities can be based on Equation 19. The first channel similarities and the second channel similarities can be based on cosine similarity (Equation 12).

[0377] According to one embodiment, hierarchical clustering may be performed based on the second channel similarities. The clusters may be determined based on the hierarchical clustering. Clusters for each of the plurality of layers may be determined based on the hierarchical clustering. The clusters may be clusters for one of the plurality of layers based on a channel similarity threshold. Each cluster may include at least one of the third wireless devices.

[0378] According to one embodiment, the individual streams and the common streams may be allocated based on the maximum number of streams that can be accommodated per second wireless device. For example, the maximum number of streams is as described above. It can be based on.

[0379] According to one embodiment, each of the individual streams (e.g., ) can be assigned to the second wireless device with the highest channel quality for the respective individual stream.

[0380] According to one embodiment, each of the common streams (e.g., ) is the channel quality for the cluster associated with the common stream (e.g., ) is the second radio device with the highest value (e.g., candidate BS It can be assigned to the BS with the highest channel quality.

[0381] According to one embodiment, values ​​related to the mobility of the third wireless devices based on the channel state information (e.g., ) can be calculated. Based on the above values, a trained model (e.g., global model) Channel similarity estimate value by ) (e.g., ) can be determined. Based on the fact that the channel similarity estimate value is smaller than the channel similarity threshold value, the clusters can be reset.

[0382] Operations based on the above-described S2410 to S2440 can be implemented by the device of FIG. 2. For example, the first wireless device (200a or 200b) can control one or more transceivers (206a or 206b) and / or one or more memories (204a or 204b) to perform operations based on S2410 to S2440.

[0383] The embodiments described above will be explained in detail below with reference to FIG. 25 regarding the operation of the third wireless device. The methods described below are distinguished only for convenience of explanation, and it is understood that a part of one method may be substituted with a part of another method or combined with one another and applied.

[0384] FIG. 25 is a flowchart illustrating a method according to another embodiment of the present specification.

[0385] Referring to FIG. 25, a method according to another embodiment of the present specification includes a CSI transmission step (S2510) and a private stream and common stream reception step (S2520).

[0386] In S2510, the third wireless device transmits Channel State Information (CSI) to the second wireless device.

[0387] In S2520, a private stream and a common stream associated with Rate Splitting Multiple Access (RSMA) are received from the second wireless device.

[0388] Based on the above channel state information (CSI), the reflection coefficient of the RIS (Reconfigurable Intelligent Surface) can be determined. Based on the above reflection coefficient, channel similarity can be determined.

[0389] Clusters for common streams can be determined based on the channel similarity above. The common stream may be based on the cluster assigned to the second wireless device among the clusters.

[0390] S2510 to S2520 are based on S2410 to S2440 of FIG. 24 described above, so redundant descriptions are omitted. A specific description of the operation of the third wireless device may be replaced by the description / example of FIG. 24.

[0391] Operations based on the above-described S2510 to S2520 can be implemented by the device of FIG. 2. For example, the third wireless device (200a or 200b) can control one or more transceivers (206a or 206b) and / or one or more memories (204a or 204b) to perform operations based on S2510 to S2520.

[0392] Here, the wireless communication technology implemented in the wireless devices (200a, 200b) of this specification may include LTE, NR, and 6G, as well as Narrowband Internet of Things for low-power communication. For example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology and may be implemented according to standards such as LTE Cat NB1 and / or LTE Cat NB2, but is not limited to the names mentioned above. Additionally, or generally, the wireless communication technology implemented in the wireless devices (200a, 200b) of this specification may perform communication based on LTE-M technology. For example, LTE-M technology may be an example of LPWAN technology and may be referred to by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology may be implemented in at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the names mentioned above. Additionally or generally, wireless communication technology implemented in the wireless devices (200a, 200b) of this specification may include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) for low-power communication, and is not limited to the names mentioned above. As an example, ZigBee technology can create personal area networks (PANs) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and may be referred to by various names.

[0393] The embodiments described above are combinations of the components and features of this specification in a specific form. Each component or feature should be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form not combined with other components or features. Additionally, it is possible to construct embodiments of this specification by combining some components and / or features. The order of operations described in the embodiments of this specification may be changed. Some components or features of one embodiment may be included in another embodiment, or may be replaced with corresponding components or features of another embodiment. It is obvious that embodiments may be constructed by combining claims that do not have an explicit citation relationship in the claims, or that they may be included as new claims through amendments made after filing.

[0394] Embodiments according to the present specification may be implemented by various means, e.g., hardware, firmware, software, or a combination thereof. In the case of implementation by hardware, an embodiment of the present invention may be implemented by one or more ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

[0395] In the case of implementation by firmware or software, an embodiment of the present specification may be implemented in the form of a module, procedure, function, etc., that performs the functions or operations described above. The software code may be stored in memory and executed by a processor. The memory may be located inside or outside the processor and may exchange data with the processor by various known means.

[0396] It is obvious to those skilled in the art that this specification may be embodied in other specific forms without departing from the essential features of this specification. Accordingly, the detailed description set forth above should not be interpreted restrictively in all respects but should be considered illustrative. The scope of this specification shall be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of this specification are included within the scope of this specification.

Claims

1. Regarding the method, A step of determining the reflection coefficient of the RIS (Reconfigurable Intelligent Surface) based on Channel State Information (CSI); A step of determining channel similarity based on the above reflection coefficient; A step of determining clusters for common streams associated with Rate Splitting Multiple Access (RSMA) based on the above channel similarity; and A method comprising the step of allocating the common streams and private streams to second wireless devices based on the clusters.

2. In Paragraph 1, The above channel status information includes first information, second information and third information, and The first information above includes information related to the channel state between i) one of the third wireless devices and ii) one of the second wireless devices, and The second information includes i) information related to the channel state between one of the third wireless devices and ii) the RIS, and A method characterized in that the above third information includes i) information related to the channel state between one of the above second wireless devices and ii) the above RIS.

3. In Paragraph 2, A method characterized by calculating first channel similarities for all cases in which a pair is formed based on two of the third wireless devices.

4. In Paragraph 3, Among the reflection coefficients related to the above RIS, the reflection coefficient that maximizes the sum of the first channel similarities is determined, and A method characterized in that the above channel similarity is based on second channel similarities calculated for all above cases based on the above reflection coefficient.

5. In Paragraph 4, A method characterized in that the first channel similarities and the second channel similarities are based on cosine similarity.

6. In Paragraph 4, Hierarchical clustering is performed based on the above second channel similarities, and A method characterized in that the above clusters are determined based on the above hierarchical clustering.

7. In Paragraph 6, Based on the above hierarchical clustering, clusters for each of the multiple layers are determined, and A method characterized in that the clusters are clusters for one of the plurality of layers based on a channel similarity threshold.

8. In Paragraph 7, A method characterized in that each cluster includes at least one of the third wireless devices.

9. In Paragraph 1, A method characterized in that the individual streams and the common streams are allocated based on the maximum number of streams that can be accommodated per second wireless device.

10. In Paragraph 9, A method characterized in that each of the above individual streams is assigned to a second wireless device having the highest channel quality for the respective individual stream.

11. In Paragraph 9, A method characterized in that each of the above common streams is assigned to a second wireless device having the highest channel quality for the cluster associated with the common stream.

12. In Paragraph 7, Values ​​related to the mobility of the third wireless devices are calculated based on the channel state information above, and Based on the above values, the channel similarity estimate is determined by a model trained, and A method characterized by resetting the clusters based on the fact that the estimated channel similarity value is smaller than the channel similarity threshold value.

13. In the first wireless device, One or more transmitters / receivers; One or more processors controlling the above one or more transceivers; and It includes one or more memories connected to the above one or more processors and storing instructions, A first wireless device characterized by the above instructions, based on execution by the one or more processors, causing the first wireless device to perform all steps of the method according to any one of claims 1 to 12.

14. An apparatus comprising one or more memories and one or more processors functionally connected to the one or more memories, An apparatus characterized in that the above one or more memories store instructions that cause the apparatus to perform all steps of the method according to any one of claims 1 to 12, based on execution by the above one or more processors.

15. In one or more non-transitory computer-readable media storing instructions, One or more non-transitory computer-readable media characterized by instructions executable by one or more processors such that the one or more processors perform all steps of the method according to any one of claims 1 to 12.

16. Regarding the method, A step of transmitting Channel State Information (CSI) to a second wireless device; and The method includes the step of receiving a private stream and a common stream associated with Rate Splitting Multiple Access (RSMA) from the second wireless device; Based on the above CSI, the reflection coefficient of the RIS (Reconfigurable Intelligent Surface) is determined, and Channel similarity is determined based on the above reflection coefficient, and Clusters for common streams are determined based on the above channel similarity, and A method characterized in that the above common stream is based on the cluster assigned to the second wireless device among the above clusters.

17. In the third wireless device, One or more transmitters / receivers; One or more processors controlling the above one or more transceivers; and It includes one or more memories connected to the above one or more processors and storing instructions, A third wireless device characterized by the above instructions, based on execution by the one or more processors, causing the third wireless device to perform all steps of the method according to claim 16.

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