Device and method for estimating near-field channel in wireless communication system

Abstract

The present invention is for estimating a near-field channel in a wireless communication system. This method for operating a terminal may comprise the steps of: receiving first configuration information related to sounding from a base station; transmitting a sounding signal on the basis of the first configuration information; receiving second configuration information related to channel estimation from the base station; receiving a downlink reference signal from the base station on the basis of the second configuration information; and performing the channel estimation on the basis of the downlink reference signal.

Description

Device and method for estimating a near-field channel in a wireless communication system

[0001] The following description relates to a wireless communication system, and to a device and method for estimating a near-field channel in a wireless communication system.

[0002] Wireless access systems are widely deployed to provide various types of communication services, such as voice and data. Typically, wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single-carrier frequency division multiple access (SC-FDMA).

[0003] In particular, as numerous communication devices demand greater communication capacity, enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT). Furthermore, massive machine type communications (mMTC), which connects multiple devices and objects to provide diverse services anytime and anywhere, as well as communication systems that consider reliability and latency-sensitive services / user equipment (UE), are being proposed. Various technological configurations are being proposed for these purposes.

[0004] The present disclosure can provide a device and method for effectively estimating a channel in a wireless communication system.

[0005] The present disclosure can provide a device and method for effectively estimating a channel in a near-field environment in a wireless communication system.

[0006] The present disclosure may provide a device and method for providing auxiliary information for channel estimation using a sounding signal in a wireless communication system.

[0007] The present disclosure may provide a device and method for estimating the position of an antenna used to transmit a sounding signal in a wireless communication system.

[0008] The present disclosure can provide a device and method for estimating the position of an antenna of each terminal by using signals received in an overlapping manner from a plurality of terminals in a wireless communication system.

[0009] The present disclosure may provide a device and method for estimating the position of an antenna using a neural network model in a wireless communication system.

[0010] The present disclosure may provide a device and method for generating information to assist channel estimation based on an estimated antenna position in a wireless communication system.

[0011] The present disclosure may provide a device and method for determining a dictionary and / or basis search range based on an estimated antenna position in a wireless communication system.

[0012] The present disclosure may provide a device and method for determining a region-focusing dictionary focused on an estimated antenna location in a wireless communication system.

[0013] The present disclosure can provide a device and method for estimating a channel by selecting columns of a dictionary in a range corresponding to an estimated position of an antenna in a wireless communication system.

[0014] The technical objectives to be achieved in the present disclosure are not limited to those mentioned above, and other technical tasks not mentioned can be considered by a person having ordinary skill in the technical field to which the technical configuration of the present disclosure is applied from the embodiments of the present disclosure described below.

[0015] As an example of the present disclosure, a method of operating a terminal in a wireless communication system may include the steps of receiving first configuration information related to sounding from a base station, transmitting a sounding signal based on the first configuration information, receiving second configuration information related to channel estimation from the base station, receiving a downlink reference signal from the base station based on the second configuration information, and performing the channel estimation based on the downlink reference signal. The second configuration information may be based on an antenna position of the terminal estimated based on the sounding signal, and may include information for determining a range of at least one basis vector included in a dictionary.

[0016] As an example of the present disclosure, a method of operating a base station in a wireless communication system may include the steps of transmitting first configuration information related to sounding to a terminal, receiving a sounding signal based on the first configuration information, transmitting second configuration information related to channel estimation to the terminal, and transmitting a downlink reference signal to the terminal based on the second configuration information. The second configuration information may be based on an antenna position of the terminal estimated based on the sounding signal, and may include information for determining a range of at least one basis vector included in a dictionary.

[0017] As an example of the present disclosure, in a wireless communication system, a terminal includes a transceiver and a processor connected to the transceiver, wherein the processor receives first configuration information related to sounding from a base station, transmits a sounding signal based on the first configuration information, receives second configuration information related to channel estimation from the base station, receives a downlink reference signal from the base station based on the second configuration information, and performs the channel estimation based on the downlink reference signal, wherein the second configuration information is based on an antenna position of the terminal estimated based on the sounding signal, and may include information for determining a range of at least one basis vector included in a dictionary.

[0018] As an example of the present disclosure, in a wireless communication system, a base station includes a transceiver and a processor connected to the transceiver, wherein the processor transmits first configuration information related to sounding to a terminal, receives a sounding signal based on the first configuration information, transmits second configuration information related to channel estimation to the terminal, and controls transmission of a downlink reference signal to the terminal based on the second configuration information, wherein the second configuration information is based on an antenna position of the terminal estimated based on the sounding signal, and may include information for determining a range of at least one basis vector included in a dictionary.

[0019] As an example of the present disclosure, a communication device includes at least one processor, and at least one computer memory connected to the at least one processor and storing instructions that, when executed by the at least one processor, direct operations, wherein the operations may include: receiving first configuration information related to sounding from a base station; transmitting a sounding signal based on the first configuration information; receiving second configuration information related to channel estimation from the base station; receiving a downlink reference signal from the base station based on the second configuration information; and performing the channel estimation based on the downlink reference signal. The second configuration information may include information for determining a range of at least one basis vector included in a dictionary based on an antenna position of the terminal estimated based on the sounding signal.

[0020] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction includes at least one instruction executable by a processor, wherein the at least one instruction controls a device to receive first configuration information related to sounding from a base station, transmit a sounding signal based on the first configuration information, receive second configuration information related to channel estimation from the base station, receive a downlink reference signal from the base station based on the second configuration information, and perform the channel estimation based on the downlink reference signal, wherein the second configuration information is based on an antenna position of the terminal estimated based on the sounding signal and may include information for determining a range of at least one basis vector included in a dictionary.

[0021] The above-described aspects of the present disclosure are only some of the preferred embodiments of the present disclosure, and various embodiments reflecting the technical features of the present disclosure can be derived and understood by a person having ordinary skill in the art based on the detailed description of the present disclosure to be described below.

[0022] The following effects may be achieved by embodiments based on the present disclosure.

[0023] According to the present disclosure, a channel in a near-field environment can be effectively estimated.

[0024] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art to which the technical configuration of the present disclosure is applied, from the description of the embodiments of the present disclosure below. In other words, unintended effects resulting from implementing the configuration described in the present disclosure can also be derived from the embodiments of the present disclosure by those skilled in the art.

[0025] The accompanying drawings are intended to aid understanding of the present disclosure and may provide embodiments of the present disclosure along with detailed descriptions. However, the technical features of the present disclosure are not limited to specific drawings, and the features disclosed in each drawing may be combined with each other to form new embodiments. Reference numerals in each drawing may indicate structural elements.

[0026] Figure 1 illustrates an example of a communication system applicable to the present disclosure.

[0027] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0028] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0029] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure.

[0030] FIG. 5 illustrates an example of a communication structure that can be provided in a 6G (6th generation) system applicable to the present disclosure.

[0031] Figure 6 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0032] Figure 7 illustrates a THz communication method applicable to the present disclosure.

[0033] FIG. 8 illustrates a THz wireless communication transceiver applicable to the present disclosure.

[0034] FIG. 9 illustrates a THz signal generation method applicable to the present disclosure.

[0035] FIG. 10 illustrates a wireless communication transceiver applicable to the present disclosure.

[0036] Figure 11 illustrates a transmitter structure applicable to the present disclosure.

[0037] Figure 12 illustrates a modulator structure applicable to the present disclosure.

[0038] FIG. 13 illustrates the concept of a sounding-assisted channel estimation technique according to one embodiment of the present disclosure.

[0039] FIG. 14 illustrates an example of a procedure for performing sounding-aided channel estimation according to one embodiment of the present disclosure.

[0040] FIG. 15 illustrates an example of the structure of a neural network for determining an antenna position according to one embodiment of the present disclosure.

[0041] FIG. 16A and FIG. 16B illustrate examples of radiation pattern and antenna position detection results according to one embodiment of the present disclosure.

[0042] FIG. 17 illustrates an example of a procedure for performing channel estimation according to one embodiment of the present disclosure.

[0043] FIG. 18 illustrates an example of a procedure for assisting channel estimation according to one embodiment of the present disclosure.

[0044] FIG. 19 illustrates an example of a procedure for estimating a channel based on an antenna position according to one embodiment of the present disclosure.

[0045] FIG. 20 illustrates an example of a procedure for providing auxiliary information based on antenna location according to one embodiment of the present disclosure.

[0046] FIG. 21 illustrates the performance of a channel estimation technique according to embodiments of the present disclosure.

[0047] The following embodiments combine components and features of the present disclosure in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, some components and / or features may be combined to form embodiments of the present disclosure. The order of operations described in the embodiments of the present disclosure 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.

[0048] In the description of the drawings, procedures or steps that may obscure the gist of the present disclosure are not described, and procedures or steps that can be understood by a person skilled in the art are also not described.

[0049] Throughout the specification, when a part is said to "comprising" or "including" a component, this does not mean that other components may be included, but rather that other components may be excluded, unless otherwise specifically stated. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the context of describing the present disclosure (especially in the context of the claims below) to include both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context.

[0050] Embodiments of the present disclosure described herein focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station is understood as a terminal node of a network that directly communicates with the mobile station. Certain operations described herein as being performed by the base station may, in some cases, be performed by an upper node of the base station.

[0051] 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, the term '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.

[0052] Additionally, in the embodiments of the present disclosure, 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).

[0053] Additionally, a transmitter refers to a fixed and / or mobile node that provides data or voice services, and a receiver refers to a fixed and / or mobile node that receives data or voice services. Therefore, for uplink, a mobile station can be the transmitter, and a base station can be the receiver. Similarly, for downlink, a mobile station can be the receiver, and a base station can be the transmitter.

[0054] Embodiments of the present disclosure may be supported by standard documents disclosed in at least one of wireless access systems, such as IEEE 802.xx system, 3rd Generation Partnership Project (3GPP) system, 3GPP Long Term Evolution (LTE) system, 3GPP 5th generation (5G) NR (New Radio) system and 3GPP2 system, and in particular, embodiments of the present disclosure 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.

[0055] Furthermore, the embodiments of the present disclosure can be applied to other wireless access systems and are not limited to the systems described above. For example, they can be applied to systems implemented after the 3GPP 5G NR system and are not limited to a specific system.

[0056] That is, obvious steps or parts not described in the embodiments of the present disclosure can be explained by referring to the above documents. In addition, all terms disclosed in this document can be explained by the above standard documents.

[0057] Hereinafter, preferred embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the technical configurations of the present disclosure may be implemented.

[0058] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding the present disclosure, and the use of such specific terms may be changed to other forms without departing from the technical spirit of the present disclosure.

[0059] 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).

[0060] For clarity, the following description is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical spirit of the present disclosure is not limited thereto. LTE may refer to technology after 3GPP TS 36.xxx Release 8. Specifically, LTE technology after 3GPP TS 36.xxx Release 10 may be referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 may be referred to as LTE-A pro. 3GPP NR may refer to technology after TS 38.xxx Release 15. 3GPP 6G may refer to technology after TS Release 17 and / or Release 18. "xxx" refers to a standard document detail number. LTE / NR / 6G may be collectively referred to as a 3GPP system.

[0061] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to this disclosure. For example, reference may be made to standard documents 36.xxx and 38.xxx.

[0062] Communication system applicable to the present disclosure

[0063] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present disclosure disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0064] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0065] Figure 1 illustrates an example of a communication system applied to the present disclosure.

[0066] Referring to FIG. 1, a communication system (100) applied to the present disclosure includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the 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 Things) device (100f), and an AI (artificial intelligence) device / server (100g). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicles (100b-1, 100b-2) may include unmanned aerial vehicles (UAVs) (e.g., drones). The XR devices (100c) include augmented reality (AR) / virtual reality (VR) / mixed reality (MR) devices, and may be implemented in the form of head-mounted devices (HMDs), head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. The portable devices (100d) may include smartphones, smart pads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.), etc. The home appliances (100e) may include TVs, refrigerators, washing machines, etc. The IoT devices (100f) may include sensors, smart meters, etc.For example, the base station (120) and the network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node to other wireless devices.

[0067] Wireless devices (100a to 100f) can be connected to a network (130) via a base station (120). AI technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) via a network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR), or a 6G network. The wireless devices (100a to 100f) can communicate with each other via the base station (120) / network (130), but can 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). Additionally, an IoT device (100f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or another wireless device (100a to 100f).

[0068] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base stations (120), and base stations (120) / base stations (120). Here, the wireless communication / connection can be established through various wireless access technologies such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and base station-to-base station communication (150c) (e.g., relay, IAB (integrated access backhaul)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and base station / wireless device, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, the wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on various proposals of the present disclosure, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), resource allocation processes, etc. may be performed.

[0069] Devices applicable to the present disclosure

[0070] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0071] Referring to FIG. 2, the wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G). The wireless device (200) includes at least one processor (202) and at least one memory (204), and may additionally include at least one transceiver (206) and / or at least one antenna (208).

[0072] The processor (202) controls the memory (204) and / or the transceiver (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (206). In addition, the processor (202) may receive a wireless signal including second information / signal via the transceiver (206), and then store information obtained from signal processing of the second information / signal in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may store software code including instructions for performing some or all of the processes controlled by the processor (202), or for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology. The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via at least one antenna (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF (radio frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0073] Hereinafter, the hardware elements of the wireless device (200) will be described in more detail. Although not limited thereto, at least one protocol layer may be implemented by at least one processor (202). For example, at least one processor (202) may implement at least one layer (e.g., a functional layer such as physical (PHY), media access control (MAC), radio link control (RLC), packet data convergence protocol (PDCP), radio resource control (RRC), and service data adaptation protocol (SDAP)). At least one processor (202) may generate at least one Protocol Data Unit (PDU) and / or at least one Service Data Unit (SDU) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) may generate a message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) can generate a signal (e.g., a baseband signal) including a PDU, an SDU, a message, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this document, and provide the signal to at least one transceiver (206). At least one processor (202) can receive a signal (e.g., a baseband signal) from at least one transceiver (206) and obtain the PDU, SDU, message, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document.

[0074] At least one processor (202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. The at least one processor (202) may be implemented by hardware, firmware, software, or a combination thereof. For example, at least one application specific integrated circuit (ASIC), at least one digital signal processor (DSP), at least one digital signal processing device (DSPD), at least one programmable logic device (PLD), or at least one field programmable gate array (FPGA) may be included in the at least one processor (202). The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be included in the at least one processor (202), or may be stored in at least one memory (204) and executed by the at least one processor (202). The descriptions, functions, procedures, suggestions, methods and / or flowcharts disclosed in this document may be implemented using firmware or software in the form of code, instructions and / or sets of instructions.

[0075] At least one memory (204) can be connected to at least one processor (202) and can store various forms of data, signals, messages, information, programs, codes, instructions and / or commands. The at least one memory (204) can be configured as a read only memory (ROM), a random access memory (RAM), an erasable programmable read only memory (EPROM), a flash memory, a hard drive, a register, a cache memory, a computer readable storage medium and / or a combination thereof. The at least one memory (204) can be located internally and / or externally to the at least one processor (202). In addition, the at least one memory (204) can be connected to the at least one processor (202) via various technologies such as a wired or wireless connection.

[0076] At least one transceiver (206) can transmit user data, control information, wireless signals / channels, etc., mentioned in the methods and / or flowcharts of this document to at least one other device. At least one transceiver (206) can receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts disclosed in this document from at least one other device. For example, at least one transceiver (206) can be connected to at least one processor (202) and can transmit and receive wireless signals. For example, at least one processor (202) can control at least one transceiver (206) to transmit user data, control information, or wireless signals to at least one other device. Furthermore, at least one processor (202) can control at least one transceiver (206) to receive user data, control information, or wireless signals from at least one other device. In addition, at least one transceiver (206) may be connected to at least one antenna (208), and at least one transceiver (206) may be configured to transmit and receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts disclosed in this document through at least one antenna (208). In this document, at least one antenna may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports). At least one transceiver (206) may convert the received wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using at least one processor (202). At least one transceiver (206) may convert the processed user data, control information, wireless signals / channels, etc. from baseband signals to RF band signals using at least one processor (202).For this purpose, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0077] The components of the wireless device described with reference to FIG. 2 may be referred to by different terms in terms of functionality. For example, the processor (202) may be referred to as a control unit, the transceiver (206) as a communication unit, and the memory (204) as a storage unit. In some cases, the communication unit may be used to mean at least a portion of the processor (202) and the transceiver (206).

[0078] The structure of the wireless device described with reference to FIG. 2 can be understood as the structure of at least a portion of various devices. For example, the structure of the wireless device illustrated in FIG. 2 can be at least a portion of various devices described with reference to FIG. 1 (e.g., a robot (100a), a vehicle (100b-1, 100b-2), an XR device (100c), a portable device (100d), a home appliance (100e), an IoT device (100f), an AI device / server (100g)). Furthermore, according to various embodiments, in addition to the components illustrated in FIG. 2, the device may further include other components.

[0079] For example, the device may be a portable device such as a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an interface unit that includes at least one port for connection with another device (e.g., an audio input / output port, a video input / output port), and an input / output unit for inputting and outputting image information / signals, audio information / signals, data, and / or information input from a user.

[0080] For example, the device may be a mobile device such as a mobile robot, a vehicle, a train, an aerial vehicle (AV), a ship, etc. In this case, the device may further include at least one of a driving unit including at least one of an engine, a motor, a power train, wheels, brakes, and a steering unit of the device, a power supply unit including a wired / wireless charging circuit, a battery, etc. that supplies power, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, an autonomous driving unit that performs functions such as path maintenance, speed control, and destination setting, and a position measurement unit that obtains location information of the mobile device through a global positioning system (GPS) and various sensors.

[0081] For example, the device may be an XR device such as an HMD, a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an input / output unit that obtains control information, data, etc. from the outside and outputs the generated XR object, and a sensor unit that senses status information, environmental information, and user information of the device or the surroundings of the device.

[0082] For example, the device may be a robot that can be classified into industrial, medical, household, military, etc. types depending on the purpose or field of use. In this case, the device may further include at least one of a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a driving unit that performs various physical actions, such as moving the robot joints.

[0083] For example, the device may be an AI device such as a TV, a projector, a smartphone, a PC, a laptop, a digital broadcasting terminal, a tablet PC, a wearable device, a set-top box (STB), a radio, a washing machine, a refrigerator, digital signage, a robot, a vehicle, etc. In this case, the device may further include at least one of an input unit that acquires various types of data from the outside, an output unit that generates output related to sight, hearing, or touch, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a training unit that trains a model composed of an artificial neural network using learning data.

[0084] The structure of the wireless device illustrated in FIG. 2 may be understood as a part of a RAN node (e.g., base station, DU, RU, RRㅗ, etc.). That is, the device illustrated in FIG. 2 may be a RAN node. In this case, the device may further include a wired transceiver for front haul and / or back haul communication. However, if the front haul and / or back haul communication is based on wireless communication, at least one transceiver (206) illustrated in FIG. 2 may be used for front haul and / or back haul communication, and a wired transceiver may not be included.

[0085] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, 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). At this time, as an example, the operations / functions of FIG. 3 may be performed in the processor (202) and / or the transceiver (206) of FIG. 2. Furthermore, as an example, the hardware elements of FIG. 3 may be implemented in the processor (202) and / or the transceiver (206) of FIG. 2. As an example, blocks 310 to 360 may be implemented in the processor (202) of FIG. 2. Additionally, blocks 310 to 350 may be implemented in the processor (202) of FIG. 2, and block 360 may be implemented in the transceiver (206) of FIG. 2, and are not limited to the above-described embodiment.

[0086] The 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 transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH). Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (310). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (320). The modulation scheme may include pi / 2-binary phase shift keying (pi / 2-BPSK), m-phase shift keying (m-PSK), m-quadrature amplitude modulation (m-QAM), etc.

[0087] A complex modulation symbol sequence can be mapped to at least one transmission layer by a layer mapper (330). The modulation symbols of each transmission layer can be mapped to corresponding antenna port(s) by a precoder (340). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by a precoding matrix W of NХM, 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., discrete Fourier transform (DFT) transform) on the complex modulation symbols. Additionally, the precoder (340) can perform precoding without performing transform precoding.

[0088] The resource mapper (350) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (360) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (360) can include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, and the like.

[0089] The signal processing process for a received signal in a wireless device may be configured in reverse order of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200 of FIG. 2) may receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal may be converted into a baseband signal through a signal restorer. For this purpose, 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. Thereafter, the baseband signal may be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codeword may be restored to the original information block through decoding. Therefore, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.

[0090] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure. Figure 4 illustrates operations of a terminal (410) and a base station (420) transmitting and / or receiving data and operations performed prior thereto.

[0091] Referring to FIG. 4, in step 401, the terminal (410) and the base station (420) perform synchronization. For example, the terminal (410) performs an initial cell search operation. Specifically, the terminal (410) can detect at least one synchronization signal transmitted from the base station (420) according to a predefined rule. Here, the synchronization signal can include multiple synchronization signals classified according to structure or purpose (e.g., primary synchronization signal, secondary synchronization signal). Through this, the terminal (410) can check the boundary of the frame, subframe, slot, and / or symbol of the base station (420) and obtain information about the base station (420) (e.g., cell identifier).

[0092] In step 403, the terminal (410) obtains system information transmitted from the base station (420). The system information is information related to the properties, characteristics, and / or capabilities of the base station (420) required to access the base station (420) and use the service, and may be classified according to the content (e.g., whether it is essential for access), transmission structure (e.g., channel used, whether provided on-demand), etc., and may be classified into, for example, a master information block (MIB) and a system information block (SIB). If necessary, the terminal (410) may transmit a signal requesting system information before receiving the system information. However, the request and provision of the system information may be performed after the random access procedure described below.

[0093] In step 405, the terminal (410) and the base station (420) perform a random access procedure. The terminal (410) may transmit and / or receive at least one message (e.g., a random access preamble, a random access response (RAR) message, etc.) for the random access procedure based on information related to the random access channel of the base station (420) obtained through system information (e.g., channel position, channel structure, supported preamble structure, etc.). For example, the terminal (410) may transmit a preamble (e.g., MSG1) through the random access channel, receive an RAR message (e.g., MSG2), transmit a message (e.g., MSG3) including information related to the terminal (410) (e.g., identification information) to the base station (420) using scheduling information included in the RAR message, and receive a message (e.g., MSG4) for contention resolution and / or connection establishment. As another example, MSG1 and MSG3 may be sent and received as one message, or MSG2 and MSG4 may be sent and received as one message.

[0094] In step 407, the terminal (410) and the base station (420) perform signaling of control information. Here, the control information may be defined in various layers, such as a layer that controls a connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transport channels (e.g., a media access control (MAC) layer), and a layer that handles physical channels (e.g., a physical (PHY) layer). For example, the terminal (410) and the base station (420) may perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and signaling for indicating allocated resources.

[0095] In step 409, the terminal (410) and the base station (420) transmit and / or receive data. In other words, the terminal (410) and the base station (420) can process, transmit, and / or receive data based on the signaling of the control information. For example, when transmitting data, the terminal (410) or the base station (420) can perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on the information bits. Conversely, when receiving data, the terminal (410) or the base station (420) can perform at least one of signal extraction from resources, waveform demodulation for each antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and channel decoding.

[0096] 6G communication systems and core implementation technologies of 6G systems

[0097] The 5G system defines various operating bands within FR1 (frequency range 1), which covers 410 MHz to 7125 MHz, and FR2 (frequency range 2), which covers 24,250 MHz to 71,000 MHz. Various frequencies are being discussed as operating bands for the subsequent 6G system, and the use of higher frequencies than 5G systems is also being considered for wider bandwidth and higher transmission speeds. One such band is the THz (terahertz) frequency band, which covers approximately 100 GHz to 10 THz. The THz frequency band is a band that has both the transparency of radio waves and the straightness of light waves, and communications using the THz frequency band are expected to play a transitional role from existing radio-centered communications to lightwave-based communications.

[0098] 6G systems utilizing the THz frequency band have the following goals: i) very high data rates per device, ii) a very large number of connected devices, iii) global connectivity, iv) very low latency, v) reduced energy consumption of battery-free IoT devices, vi) ultra-reliable connectivity, and vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: “intelligent connectivity,” “deep connectivity,” “holographic connectivity,” and “ubiquitous connectivity,” and the 6G system can be designed to satisfy the requirements as shown in [Table 1] below.

[0099] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0100] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0101] Figure 5 illustrates an example of a communication structure that can be provided in a 6G system applicable to the present disclosure. Referring to Figure 5, the 6G system is expected to have 50 times higher simultaneous wireless communication connectivity than the 5G wireless communication system. URLLC, a key feature of 5G, is expected to become an even more important technology in 6G communication by providing an end-to-end delay of less than 1 ms. In this case, the 6G system will have much better volumetric spectral efficiency than the frequently used area spectral efficiency. The 6G system can provide very long battery life and advanced battery technology for energy harvesting, so that mobile devices in the 6G system may not need to be separately charged.

[0102] As core implementation technologies of the 6G system, technologies such as artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, FSO backhaul network, massive MIMO technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS) can be adopted.

[0103] THz communication utilizes a spectrum in the frequency band between 0.1 THz and 10 THz with corresponding wavelengths ranging from 0.03 mm to 3 mm, as shown in Fig. 6. THz communication can be implemented as follows.

[0104] Fig. 7 illustrates a THz communication method applicable to the present disclosure. Referring to Fig. 7, THz wireless communication refers to wireless communication using THz waves having a frequency of approximately 0.1 to 10 THz (1 THz = 1012 Hz), and may refer to terahertz (THz) band wireless communication using a very high carrier frequency of 100 GHz or higher. THz waves are located between the RF (Radio Frequency) / millimeter (mm) and infrared bands, and (i) compared to visible light / infrared rays, they penetrate non-metallic / non-polarizable materials well, and compared to RF / millimeter waves, they have a shorter wavelength, thus having high linearity and enabling beam focusing.

[0105] In addition, since the photon energy of THz waves is only a few meV, it has the characteristic of being harmless to the human body. The frequency band expected to be used for THz wireless communication may be the D-band (110 GHz to 170 GHz) or H-band (220 GHz to 325 GHz) bands where propagation loss due to absorption of molecules in the air is small. In addition to 3GPP, standardization discussions for THz wireless communication are being centered around the IEEE 802.15 THz WG (working group), and standard documents issued by the IEEE 802.15 TG (task group) (e.g., TG3dimensional, TG3e) can specify or supplement the contents described in this specification. THz wireless communication can be applied to wireless cognition, sensing, imaging, wireless communication, THz navigation, etc.

[0106] Specifically, referring to Fig. 7, THz wireless communication scenarios can be categorized into macro networks, micro networks, and nanoscale networks. In macro networks, THz wireless communication can be applied to vehicle-to-vehicle (V2V) connections and backhaul / fronthaul connections. In micro networks, THz wireless communication can be applied to fixed point-to-point or multi-point connections such as indoor small cells, wireless connections in data centers, and near-field communication such as kiosk downloading. Table 2 below shows examples of technologies that can be utilized in THz waves.

[0107] Transceivers DeviceAvailable immature: UTC-PD, RTD and SBDModulation and codingLow order modulation techniques (OOK, QPSK), LDPC, Reed Soloman, Hamming, Polar, TurboAntennaOmni and Directional, phased array with low number of antenna elementsBandwidth69 GHz (or 23 GHz) at 300 GHzChannel modelsPartiallyData rate100 GbpsOutdoor deploymentNoFee space lossHighCoverageLowRadio Measurements300 GHz inddorDevice sizeFew micrometers

[0108] Fig. 8 illustrates a THz wireless communication transceiver applicable to the present disclosure. Referring to Fig. 8, THz wireless communication can be classified based on the method for generating and receiving THz. The THz generation method can be classified into optical device-based or electronic device-based technology. Here, the method for generating THz using electronic devices includes a method using a semiconductor device such as a resonant tunneling diode (RTD), a method using a local oscillator and a multiplier, a method using a monolithic microwave integrated circuit (MMIC) using a compound semiconductor high electron mobility transistor (HEMT)-based integrated circuit, and a method using a Si-CMOS-based integrated circuit. In the case of Fig. 8, a doubler (tripler, multiplier) is applied to increase the frequency, and it passes through a subharmonic mixer and is radiated by an antenna. Since the THz band forms a high frequency, a doubler is essential. Here, the multiplier is a circuit that provides an output frequency that is N times that of the input, matches it to the desired harmonic frequency, and filters out all remaining frequencies. In addition, beamforming can be implemented by applying an array antenna, etc. to the antenna of Fig. 8. In Fig. 8, IF represents an intermediate frequency, a tripler and a multiplier represent a multiplier, PA represents a power amplifier, LNA represents a low noise amplifier, and PLL represents a phase-locked loop.

[0109] FIG. 9 illustrates a THz signal generation method applicable to the present disclosure. FIG. 10 also illustrates a wireless communication transceiver applicable to the present disclosure. Referring to FIGS. 9 and 10 , the optical device-based THz wireless communication technology refers to a method of generating and modulating a THz signal using an optical device. The optical device-based THz signal generation technology is a technology that generates an ultra-high-speed optical signal using a laser and an optical modulator, and converts it into a THz signal using an ultra-high-speed photodetector. Compared to a technology that uses only electronic devices, this technology makes it easy to increase the frequency, enables high-power signal generation, and can obtain a flat response characteristic over a wide frequency band. For the optical device-based THz signal generation, as illustrated in FIG. 9 , a laser diode, a wideband optical modulator, and an ultra-high-speed photodetector are required. In the case of FIG. 9 , light signals from two lasers with different wavelengths are combined to generate a THz signal corresponding to the wavelength difference between the lasers. In Fig. 9, an optical coupler refers to a semiconductor device that transmits an electrical signal using optical waves to provide electrical isolation and coupling between circuits or systems, and a uni-travelling carrier photo-detector (UTC-PD) is a type of photodetector that uses electrons as active carriers and reduces the travel time of electrons through bandgap grading. The UTC-PD is capable of photodetection at 150 GHz or higher.In Fig. 0, EDFA (erbium-doped fiber amplifier) ​​represents an erbium-doped fiber amplifier, PD (photo detector) represents a semiconductor device that can convert an optical signal into an electrical signal, OSA represents an optical module (optical sub assembly) that modularizes various optical communication functions (e.g., photoelectric conversion, electro-optical conversion, etc.) into a single component, and DSO represents a digital storage oscilloscope.

[0110] Fig. 11 illustrates a transmitter structure applicable to the present disclosure. In addition, Fig. 12 illustrates a modulator structure applicable to the present disclosure. Referring to Figs. 11 and 12, a signal phase, etc. can be changed by passing an optical source of a laser through an optical wave guide. At this time, data is loaded by changing the electrical characteristics through a microwave contact, etc. Accordingly, the optical modulator output is formed as a modulated waveform. An opto-electrical modulator (O / E converter) can generate a THz pulse by optical rectification operation by a nonlinear crystal, photoelectric conversion (O / E conversion) by a photoconductive antenna, emission from a bunch of relativistic electrons, etc. Terahertz pulses (THz pulses) generated in the above manner can have lengths ranging from femtoseconds to picoseconds. The optical / electrical converter (O / E converter) performs down conversion by utilizing the non-linearity of the device.

[0111] Considering the THz spectrum usage, it is likely that THz systems will use multiple contiguous gigahertz bands for fixed or mobile service purposes. Based on the outdoor scenario criteria, the available bandwidth can be classified based on the oxygen attenuation of 10^2 dB / km in the spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is composed of multiple band chunks can be considered. As an example of the above framework, if the THz pulse length for one carrier is set to 50 ps, ​​the bandwidth (BW) becomes approximately 20 GHz.

[0112] Effective down-conversion from the infrared band to the terahertz band (THz band) depends on how to utilize the nonlinearity of the optical / electrical converter (O / E converter). In other words, to down-convert to the desired terahertz band (THz band), it is necessary to design an O / E converter with the most ideal non-linearity for transferring to the corresponding terahertz band (THz band). If an O / E converter that is not suitable for the target frequency band is used, errors are likely to occur in the amplitude and phase of the corresponding pulse.

[0113] A terahertz transmission and reception system can be implemented using a single optical-to-electrical converter in a single-carrier system. Depending on the channel environment, an optical-to-electrical converter may be required equal to the number of carriers in a multi-carrier system. This phenomenon will be particularly noticeable in a multi-carrier system that utilizes multiple broadbands according to the aforementioned spectrum usage plan. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-converted using an optical-to-electrical converter may be transmitted in a specific resource region (e.g., a specific frame). The frequency region of the specific resource region may include a plurality of chunks. Each chunk may be composed of at least one component carrier (CC).

[0114] Specific embodiments of the present disclosure

[0115] The present disclosure relates to techniques for channel estimation in a wireless communication system. In particular, the present disclosure proposes various embodiments for channel estimation in a near-field environment.

[0116] Next-generation communication systems, such as 6G (6th generation), are envisioned to deliver extreme performance in connectivity, sensing, and artificial intelligence (AI). One of the key infrastructures to materialize this vision is extremely large-scale (XL) arrays. An XL array could be, for example, an XL planar array of thousands of antenna elements. Meanwhile, the remarkably increased array aperture could provide XL arrays with multi-access and sensing opportunities. Furthermore, a large array aperture inevitably leads to dramatically increased Rayleigh distances, placing user devices in the Fresnal region, also known as the near-field region. Many research challenges remain for near-field communications, including channel estimation and beam training. Therefore, this disclosure proposes an effective near-field channel estimation technique that improves the performance of channel estimation using channel sounding.

[0117] Common estimation techniques for far-field channels are based on planar wavefront models in the far field. However, planar wavefront models may not be valid in the near field. Accurate estimation of the near-field channel requires a spherical wave model. In the near field, the channel response depends on the angle and distance between the array of user device antennas and the access point (AP) (e.g., base station). In other words, the channel phase can be described using the exact distances between the transmit and receive antennas. These characteristics of the near-field channel invalidate the assumption of angular-domain sparsity in the far field. Consequently, applying far-field channel estimation algorithms in the near field is difficult.

[0118] Therefore, the far-field orthogonal matching pursuit (OMP) algorithm can be modified into subarray-wise and scatter-wise variants for application to near-field spherical wavefronts. For more accurate and efficient estimation, the polar-domain sparsity of near-field channels has been studied. The results of this sparsity study can be used to design sampling techniques for angles and distances, and further, to develop an OMP algorithm in the polar domain. The OMP algorithm in the polar domain requires a set of orthogonal pilot signals (e.g., reference signals) between different user devices. The pilots transmitted from the devices are received by the AP (e.g., base station) and can be used as input to the OMP algorithm. The pilot length can be set as a function of the number of AP antennas, for example, half.

[0119] A promising approach to improving the near-field OMP algorithm is to accelerate iterative estimation algorithms based on neural networks (NNs). Following the deep unfolding paradigm, the near-field channel estimation problem in the compressive sensing format can be solved by training the learning iterative shrinkage and thresholding algorithm (LISTA). The LISTA algorithm can be embedded in a neural network, where each layer performs one iteration of a conventional iterative algorithm. However, the consumption of time resources will increase with the number of devices, as a proportion of the required pilot length. Given the large number of devices in 6G, such techniques will incur long delays and pose challenges for massive connectivity. Therefore, this disclosure proposes an effective channel estimation technique using an enhanced OMP technique utilizing channel sounding. The proposed technology may be referred to as sounding-assisted OMP (SAOMP), sounding-assisted channel estimation, or other terms with equivalent technical meaning. However, the names do not limit the scope of the rights.

[0120] Channel sounding is a classic and practical technique for profiling the propagation environment. Channel sounding, derived from underwater acoustic sounding, refers to detecting impulse responses in a wireless channel. Because near-field channels depend on both the traversing distance and angle of the wave, the channel sounding problem for near-field channels can be considered as profiling the device's position and channel gain. To achieve this goal, this disclosure proposes neural channel sounding for near-field channel estimation. The proposed technique allows devices to transmit a common multi-tone signal without inter-user orthogonality. This shared pilot limits the overhead of SAOMP. While non-orthogonal waveforms reduce bandwidth and time resource overhead, they result in superposition of received signals at the AP array.

[0121] Accordingly, the channel estimation technique according to various embodiments utilizes the sensing functionality of the XL array of the AP to detect the positions and channel gain of user devices from overlapping signals. Sampling spatially distributed signals from the multi-antenna array provides the array with sensing capabilities, i.e., the ability to detect scatter and determine locations. In near-field channel estimation according to various embodiments, the sensing capabilities can be applied to distinguish between different transmitting devices. Furthermore, the estimated antenna positions of the devices can be encoded into an OMP dictionary that focuses on those positions.

[0122] The framework of the SAOMP technique according to various embodiments is as follows.

[0123] SAOMP Protocol: Channel estimation according to various embodiments follows a two-phase protocol for near-field channel estimation. The first phase, channel sounding, utilizes a multi-tone waveform shared by devices without orthogonality between devices. This enables resource-efficient sensing for many devices. The transmitted results of the multi-tone waveform are encoded in a region-focusing dictionary. In the second phase, orthogonal pilots are used for each device, and SAOMP using the region-focusing dictionary is performed to compute an estimated channel.

[0124] Reconstruction of radiation patterns and antenna selection for channel sounding: An algorithm is used to reconstruct radiation patterns. A series of operations including Fourier transform, filtering, interpolation, and inverse Fourier transform can be performed to obtain radiation patterns from received signals. Here, filtering can be performed to focus the imaging plane onto the plane at which the targets are located. The magnitude of each pixel in the radiation pattern represents the estimated channel gain for a point in three-dimensional space. In addition, a deep learning-based antenna detection algorithm can be used. The antenna detection algorithm can be built upon a semantic-segmentation neural network, thereby enabling rapid antenna detection based on the reconstructed radiation patterns.

[0125] SAOMP: Based on the estimated antenna locations of the devices, a dictionary to be used in SAOMP can be determined. Angular samples from the antenna locations of the devices are used to form a dictionary, which is different from an omnidirectional dictionary, according to various embodiments. This concentrated dictionary allows SAOMP to achieve a level of channel estimation accuracy comparable to that of OMP, even with fewer pilots.

[0126] FIG. 13 illustrates the concept of a sounding-assisted channel estimation technique according to one embodiment of the present disclosure. FIG. 13 shows a near-field line of sight (LoS) channel model.

[0127] Referring to FIG. 13, terminals (1310-1 to 1310-3) transmit sounding signals to a base station (1320). The sounding signals transmitted from terminals (1310-1 to 1310-3) are transmitted non-orthogonally, and thus the base station (1320) receives superimposed sounding signals. The base station (1320) A planar antenna array including multiple receiving antennas is provided. In addition, M terminals exist within a near-field region. Each of the terminals (1310-1 to 1310-3) may have a single antenna or multiple antennas. However, for convenience of explanation, it is assumed below that each of the terminals (1310-1 to 1310-3) has a single antenna. In this case, the channel between the base station (1320) and the terminals (1310-1 to 1310-3) can be expressed as in [Mathematical Formula 1] below.

[0128]

[0129] In [Equation 1], is the near-field channel between the base station antenna n and the terminal antenna m at frequency f, is the attenuation factor, is the signal frequency, means the distance between the base station antenna n and the terminal antenna m.

[0130] Here, the distance between the base station antenna n and the terminal antenna m can be defined as in [Mathematical Formula 2] below.

[0131]

[0132] In [Equation 2], is the distance between the base station antenna n and the terminal antenna m, is the x-axis coordinate of the terminal antenna m, is the y-axis coordinate of the terminal antenna m, is the z-axis coordinate of the terminal antenna m, is the x-axis coordinate of the base station antenna n, is the y-axis coordinate of the terminal antenna m, is the location information of the terminal antenna m, means the location information of base station antenna n.

[0133] In the near-field region, the channel gain from the terminal to the base station antennas can be considered uniform. In other words, the channel attenuation from the terminal to the base station antennas can be considered to not vary depending on the base station antenna. Therefore, as in [Mathematical Equation 1], the phase of the channel between the terminal and the base station antennas depends only on the position and / or distance. Here, since the positions of the base station antennas are fixed and known, an estimation of the position of the terminal antenna is required.

[0134] Additionally, the normalized mean squared error (NMSE) can be used as an indicator for evaluating channel sounding performance. For example, NMSE can be defined as in [Mathematical Equation 3] below.

[0135]

[0136] In [Equation 3], is the near-field channel between the base station antenna n and the terminal antenna m at frequency f, Is It means the estimation of .

[0137] A sounding-aided channel estimation technique according to various embodiments may be comprised of two phases, for example, a channel sounding phase and a channel estimation phase. In the channel sounding phase, devices are synchronized to transmit the same multi-tone signal. Here, synchronization may be performed through a timing sequence. Upon successful synchronization with negligible error, the base station can receive the superposed multi-tone signal and estimate the positions of terminals based on the received signal. In the subsequent channel estimation phase, the estimated positions may be encoded as SAOMP parameters so that the terminals can estimate the channel based on orthogonal pilots transmitted by the base station.

[0138] Figure 14 illustrates an example of a procedure for performing sounding-aided channel estimation according to one embodiment of the present disclosure. Figure 14 illustrates signal exchange between a terminal (1410) and a base station (1420). While Figure 14 illustrates a procedure related to a single terminal (1410), multiple terminals may participate in this procedure simultaneously with the terminal (1410).

[0139] Referring to FIG. 14, in step S1401, the terminal (1410) and the base station (1420) perform an initialization operation. According to one embodiment, the terminal (1410) and the base station (1420) may exchange capability information for channel estimation and allocate resources for subsequent signal transmission. Furthermore, according to one embodiment, during the initialization operation, the terminal (1410) may perform synchronization with at least one other terminal for subsequent signal transmission.

[0140] In step S1403, the terminal (1410) transmits a sensing signal. The sensing signal is transmitted to sense the antenna position of the terminal (1410) and may be referred to as a sensing waveform signal. In addition, the sensing signal may be referred to as a sounding signal or a sounding reference signal. A plurality of terminals including the terminal (1410) may transmit signals simultaneously using the same unit transmission power. The signal may be referred to as a multi-tone waveform and may be defined as in [Mathematical Formula 4] below.

[0141]

[0142] In [Equation 4], is a sensing signal, is the number of tones included in the sensing signal, silver It means the second tone.

[0143] Referring to [Mathematical Formula 4], adjacent tones have a common gap It is separated using . The total bandwidth consumed by the tones of the dog is can be expressed as a signal For the time-domain implementation, frequency-modulation continuous waveform (FMCW) and / or stepped-frequency continuous waveform (SFCW) can be used.

[0144] The sensing waveform signal at the nth antenna of the base station (1420) The received signal of the nth tone is a superposition of the single-tone signals of each of the multiple terminals. The superposition at the nth antenna The reception signal of the th tone can be expressed as follows [Mathematical Formula 5].

[0145]

[0146] In [Equation 5], is received at base station antenna n. The received signal of the th tone, is the attenuation factor for the mth terminal, silver th tone, represents the distance between the base station antenna n and the terminal antenna m. Since the signal to noise ratio (SNR) for LoS channels is typically high, channel noise is omitted.

[0147] In step S1405, the base station (1420) performs sensing and determines at least one parameter to assist channel estimation. Here, sensing is an operation to estimate the antenna position of the terminal (1410), and the at least one parameter is information to assist channel estimation of the terminal (1410). That is, the base station (1420) estimates the antenna position of the terminal (1410) based on a set of received signals. Then, the base station (1420) can encode the sensing result into a vector and broadcast the encoded information as a parameter for channel estimation to a plurality of terminals including the terminal (1410).

[0148] In step S1407, the base station (1420) transmits parameters for channel estimation. In other words, the base station (1420) transmits configuration information including parameters for channel estimation. Here, the parameters include at least one parameter determined in step S1405. The parameters for channel estimation may be referred to as SAOMP parameters.

[0149] In step S1409, the base station (1420) transmits pilot signals. In other words, the base station (1420) can transmit mutually orthogonal pilot signals to multiple terminals, including the terminal (1410). The pilot signals may be referred to as reference signals, CSI-RS, etc.

[0150] In step S1411, the terminal (1410) estimates a channel. The terminal (1410) can estimate the channel based on at least one of the parameters for channel estimation and the received pilot signals.

[0151] The detailed operations for channel sounding are as follows.

[0152] According to various embodiments, channel sounding may be based on scalar diffraction, which is applicable to millimeter-wave imaging and vehicle sensing. To this end, a function that maps the coordinates of a point in space to the channel gain from the AP to that point may be defined as shown in Equation 6 below.

[0153]

[0154] In [Equation 6], is a function that maps points to channel gain, is the attenuation factor for the mth terminal, refers to a set of coordinates of antennas of terminals.

[0155] Scalar diffraction is An arbitrary exponential term within This allows for the expression of terms of integrals parameterized by .

[0156]

[0157] In [Equation 7], silver th tone, is the distance between the base station antenna n and the terminal antenna m, silver , silver , is the x-axis coordinate of the base station antenna n, means the x-axis coordinate of the terminal antenna m.

[0158] By substituting [Mathematical Equation 7] into [Mathematical Equation 5] and using integration within a three-dimensional space to replace the sum between the device antennas, the signal received by the array of the base station can be expressed as in [Mathematical Equation 8] below.

[0159]

[0160] In [Equation 8], is the x-axis position, is the y-axis position, silver th tone, is located ( , )at The reception value of the th tone, is a function that maps points to channel gain, silver , silver , is the x-axis coordinate of the base station antenna n, is the x-axis coordinate of the terminal antenna m, stands for Fourier transform. The subscripts and superscripts indicate dimensionality and direction (e.g., absent for forward, -1 for reverse).

[0161] By inverting [Equation 8], a relationship similar to [Equation 9] is obtained.

[0162]

[0163] In [Equation 9], is a function that maps points to channel gain, is the Fourier transform, is the x-axis position, is the y-axis position, silver th tone, is located ( , )at It means the reception value of the th tone.

[0164] The implementation of [Equation 9] exists in the discrete domain. However, the received signal at the location of the antenna elements on the surface of the base station array Only samples of can be obtained. For alignment in the form of the derived principle, the received signals can be rearranged into a three-dimensional data cube. Without loss of generality, the planar array is per row Horizontal antennas per column and per dog It may include vertical antennas of the dog. Any entry within the data cube can be expressed as follows [Mathematical Formula 10].

[0165]

[0166] In [Equation 10], Is th tone and horizontal axis th and vertical axes The entry corresponding to the th antenna, is the vertical axis index of the antenna, is the number of horizontal axis antennas, is the horizontal axis index of the antenna, Silver tone index, refers to the number of tones.

[0167] The data cube is used as input to the channel estimation algorithm. For convenience, a two-dimensional case is described below, but the following examples can also be extended to three-dimensional cases.

[0168] The estimation in two-dimensional space is as follows.

[0169] A single frequency can be used for channel estimation. Accordingly, can be set to 1, and the notation silver As, expression silver can be simplified as follows. The single-frequency setting is a three-dimensional inverse of [Equation 9] using a preceding range-dependent filter. It provides a result in which the items are degraded into two-dimensional inverse FT items. In this case, the function that maps the coordinates of a point in space to a channel gain can be transformed as shown in [Mathematical Formula 11] below.

[0170]

[0171] In [Equation 11], Silver coordinates , , Channel gain corresponding to the point of , is the Fourier function, is located ( , ) received value, is the spatial wave number, is defined as, and is the wave number vector The horizontal axis component and the vertical axis component, refers to the depth axis or height axis coordinate from the antenna plane of the target.

[0172] Based on the relationship as in [Mathematical Formula 11], an algorithm for two-dimensional channel estimation in the discrete domain as in [Table 3] below can be performed.

[0173]

[0174] In [Table 3], and are the spatial wave numbers in the horizontal and vertical directions.

[0175] According to various embodiments of the present disclosure, semantic segmentation techniques can be used for antenna detection. Semantic segmentation features pixel-by-pixel classification and provides a neural network trained to segment the desired target from background pixels. An example of the structure of a detector including a neural network is shown in FIG. 15 below.

[0176] Fig. 15 illustrates an example of the structure of a neural network for determining an antenna position according to an embodiment of the present disclosure. Referring to Fig. 15, the detector It is designed to take as input an image (1501) of size and output an antenna detection result (1502), and each pixel value of the image has a corresponding size in the radiation pattern (e.g. ) is given by. The detector can utilize three dilated convolutional (DiConv) layers. Additionally, a ReLU layer can be embedded in each DiConv layer. In addition, a convolutional (Conv) layer and a softmax layer can be used to calculate the probability of each pixel being an antenna.

[0177] Figures 16a and 16b illustrate examples of radiation patterns and antenna position detection results according to one embodiment of the present disclosure. Figure 16a illustrates an example of a radiation pattern, and Figure 16b illustrates an example of an antenna position detection result corresponding to the radiation pattern of Figure 16a. In Figure 16a, bright areas indicate antennas of the terminal. In Figure 16b, pixels classified as background and pixels classified as antennas are expressed to be distinct from each other.

[0178] A neural network model, such as that illustrated in Figure 15, can be trained using training data. For example, the training data may be labeled data, including a mask that separates the antenna from the background in a radiation pattern image. The mask may indicate, on a pixel-by-pixel basis, whether each pixel in the image contains an antenna. Training can be performed by updating the weights of the layers included in the neural network model through backpropagation based on the results of inference or prediction performed using the data.

[0179] The estimation in 3D space is as follows.

[0180] The difference between estimation in 3D space and 2D space is that estimation requires a 3D inverse FT operation, rather than a 2D one. This difference requires replacing the filtering step with an interpolation step to extend the 2D case algorithm. The algorithm for channel estimation in 3D space can be summarized as shown in Table 4 below.

[0181]

[0182] In [Table 4], and are the spatial wave numbers in the horizontal and vertical directions, is the spatial wavenumber in the depth direction for the discrete FT operation. In the algorithm shown in [Table 4], the design of the detector is mostly similar to the detector of Fig. 15 for two dimensions, but differs in that the input and output are multi-channel images.

[0183] The SAOMP algorithm is as follows:

[0184] The SAOMP algorithm according to various embodiments can be used for near-field channel estimation. The SAOMP algorithm described below can be applied not only to a planar array but also to an arbitrary linear sub-array of a planar array. Given angle information for a reference line on a planar array, a terminal can calculate the angle for an arbitrary line on the planar array using a priori information of the array geometry.

[0185] three-element tuples , Explained using Considering the regions of the number of regions, a sounding-aided channel estimation technique, i.e., SAOMP technique, according to various embodiments of the present disclosure, which is a region-focusing variant of the omnidirectional OMP algorithm, can be performed. The transform matrix in SAOMP samples the polar domain from the angular dimension and the distance dimension. In the present disclosure, the region-focused transform matrix according to various embodiments is It is referred to as, means the number of samples in the angular domain. Angular sampling according to various embodiments -dimensional vector creates a vector. In particular, Is It contains segments of a dog, each segment being From It is an evenly spaced vector in the range up to . The length of the th segment is is a value proportional to, but rounded to an integer. In one embodiment, the angular sampling is concentrated in the area containing the terminal antennas estimated in the previous channel sounding step. Vector For any element within, the corresponding distance sample can be determined as shown in [Mathematical Formula 12] below.

[0186]

[0187] In [Equation 12], is a distance sample, Is and Integers that satisfy , are predefined hyper-parameters, means the i-th element of the angle vector. Here, refers to the minimum distance from the served sector to the base station.

[0188] Pairs of angle-distance samples is the domain-intensive transformation matrix Determines one column of the domain-intensive transformation matrix One column of can be determined as follows [Mathematical Formula 13].

[0189]

[0190] In [Equation 13], silver Index of The maximum value of, silver , is the antenna spacing of the base station, means distance sample.

[0191] Transformation matrix From the algorithm that generates the vector It is confirmed that must be broadcast to all terminals. Considering the characteristics of broadcast, vector Broadcasting of information about can be performed via a narrow-band feedback channel. Thereafter, the base station transmits pilot sequences to the terminals. Here, the pilot signals can be configured orthogonally to the terminals. For example, the pilot signals can be transmitted orthogonally via different time resources, different frequency resources, or different code resources. The pilot signal received by the terminals can be expressed as follows [Mathematical Formula 14].

[0192]

[0193] In [Equation 14], is the received pilot signal, is the pilot signal, is a channel, Silver noise, is the transformation matrix, stands for the polar-domain representation of the channel.

[0194] The terminal can parameterize the OMP algorithm using a transformation matrix and reconstruct the polar-domain representation of the channel from the received pilot signal. This procedure can be summarized as shown in [Table 5] below.

[0195]

[0196] The aforementioned SAOMP framework can be extended to near-field channel estimation based on neural network implementations of compressed sensing algorithms. Since OMP and various compressed sensing algorithms are iterative, neural network-based approaches, such as deep unfolding, can replace iterations using neural network layers. However, since learning-based techniques are also built on polar domain representations of channels, sounding-aided channel estimation techniques according to various embodiments can utilize neural network approaches. Based on different forms of transformation matrices, detected regions (e.g., regions detected in Step 4 of Tables 3 and 4) can be encoded in a form that fits the neural networks.

[0197] FIG. 17 illustrates an example of a procedure for performing channel estimation according to one embodiment of the present disclosure. FIG. 17 also illustrates an operating method of a terminal.

[0198] Referring to FIG. 17, in step S1701, the terminal receives configuration information related to sounding. In other words, the terminal receives configuration information related to a signal transmitted on the uplink. For example, the configuration information may include at least one of a resource for transmitting a signal, a sequence constituting the signal, or values. Additionally, the terminal may transmit capability information related to sounding-assisted channel estimation to the base station, or perform further synchronization operations with other terminals.

[0199] In step S1703, the terminal transmits a sounding signal. In other words, the terminal transmits a reference signal for sounding. The signal transmitted in this step may be referred to as an uplink signal, an uplink reference signal, a sounding signal, a sounding reference signal, or other terms having equivalent technical meanings. The terminal may transmit a signal for sounding based on the configuration information received in step S1701. The uplink reference signal may occupy multiple tones. According to one embodiment, the terminal may transmit the sounding signal through the same time-frequency resource as at least one other terminal. According to one embodiment, the sounding signal may have a form that allows non-coherent detection.

[0200] In step S1705, the terminal receives configuration information related to channel estimation. For example, the configuration information may include information related to a downlink signal for channel estimation, information related to a resource for reporting the result of channel estimation, and information related to a channel estimation operation. According to one embodiment, the information related to the channel estimation operation may include information generated based on the sounding signal transmitted in step S1703. Specifically, the information generated based on the sounding signal may include information for determining the range of at least one basis vector included in a dictionary. The dictionary may be referred to as a sensing matrix, a transformation matrix, or other terms having an equivalent technical meaning thereto. Here, the information elements included in the configuration information may be received via one message or multiple messages.

[0201] In step S1707, the terminal receives a downlink reference signal. For example, the downlink reference signal may be received based on the configuration information received in step S1705. At the base station, the downlink reference signal may be transmitted together with downlink reference signals for at least one other terminal, and in this case, the downlink reference signals may be transmitted orthogonally to each other. Accordingly, the terminal can receive the downlink reference signal for itself without interference.

[0202] In step S1709, the terminal performs channel estimation. The terminal can estimate the channel using the received signal of the downlink reference signal. According to various embodiments, the terminal can estimate the channel by determining a support set by selecting at least one index among the columns of the dictionary based on an iterative algorithm. Additionally, although not illustrated in FIG. 17, the terminal can transmit information related to the estimated channel to the base station. That is, the terminal can transmit a report message including information related to the channel to the base station.

[0203] FIG. 18 illustrates an example of a procedure for assisting channel estimation according to one embodiment of the present disclosure. FIG. 18 illustrates an operating method of a base station.

[0204] Referring to FIG. 18, in step S1801, the base station transmits configuration information related to sounding. In other words, the base station transmits configuration information related to a signal received on the uplink. For example, the configuration information may include at least one of a resource for transmitting a signal, a sequence constituting the signal, or values. Additionally, the base station may receive capability information related to sounding-assisted channel estimation from the terminal.

[0205] In step S1803, the base station receives a sounding signal. That is, the base station receives a reference signal for sounding. The signal received in this step may be referred to as an uplink signal, an uplink reference signal, a sounding signal, a sounding reference signal, or other terms having equivalent technical meanings. The base station may receive the sounding signal based on the configuration information transmitted in step S1801. The sounding signal may occupy multiple tones. In one embodiment, the base station may receive sounding signals from multiple terminals through the same time-frequency resource. In other words, the base station may receive overlapping sounding signals. In one embodiment, the sounding signals may have a form that allows non-coherent detection.

[0206] In step S1805, the base station transmits configuration information related to channel estimation. For example, the configuration information may include information related to a downlink signal for channel estimation, information related to a resource for reporting the result of channel estimation, and information related to a channel estimation operation. According to one embodiment, the information related to the channel estimation operation may include information generated based on the uplink reference signal received in step S1803. Specifically, the information generated based on the uplink reference signal may include information for determining the range of at least one basis vector included in the dictionary. Here, the information elements included in the configuration information may be transmitted via one message or multiple messages.

[0207] In step S1807, the base station transmits a downlink reference signal. For example, the downlink reference signal may be transmitted based on the configuration information transmitted in step S1805. At this time, downlink reference signals for multiple terminals may be transmitted together, and in this case, the downlink reference signals may be transmitted orthogonally to each other. Additionally, although not illustrated in FIG. 18, the base station may receive information related to the estimated channel from at least one terminal. That is, the base station may receive a report message including information related to the channel.

[0208] FIG. 19 illustrates an example of a procedure for estimating a channel based on an antenna position according to one embodiment of the present disclosure. FIG. 19 also illustrates an operating method of a terminal.

[0209] Referring to FIG. 19, in step S1901, the terminal receives configuration information based on an antenna position. Here, the configuration information is generated based on the antenna position of the terminal, and the antenna position may be determined based on an estimation from the base station. According to one embodiment, the configuration information based on the antenna position may include an SAOMP parameter. Specifically, the configuration information based on the antenna position may include at least one of an angle information for the antenna of the terminal in the base station antenna array, a maximum angle value, a minimum angle value, and a size of a candidate area for the antenna position (e.g., the number of pixels in a radiation pattern image).

[0210] In step S1903, the terminal determines a dictionary search range based on the configuration information. In other words, the terminal can generate a region-focused dictionary based on the omnidirectional dictionary. According to various embodiments, the terminal can generate a region-focused dictionary based on configuration information based on antenna positions and distances between antennas of the base station. Specifically, the terminal can generate a region-focused dictionary based on at least one of an angle vector including angle values ​​falling within a range of maximum and minimum angle values, distance samples corresponding to each of the angle values, and distances between antennas of the base station.

[0211] In step S1905, the terminal determines channel information within the search range. In other words, the terminal determines the channel information by estimating the channel based on a region-intensive dictionary. According to various embodiments, the terminal can estimate the channel by identifying at least one column corresponding to a non-zero element of a sparse matrix among the columns of the region-intensive dictionary. Here, the sparse matrix is ​​a matrix representing the estimated channel. Specifically, the terminal can identify at least one column corresponding to a non-zero element based on repeated operations of sequentially removing elements corresponding to columns of a specific index of the region-intensive dictionary from a matrix including reception values ​​of pilot signals. For example, the terminal can estimate the channel based on the OMP technique.

[0212] FIG. 20 illustrates an example of a procedure for providing auxiliary information based on antenna location according to one embodiment of the present disclosure. FIG. 20 illustrates a method of operating a base station. While FIG. 20 illustrates operations for a single terminal, the procedure illustrated in FIG. 20 can be performed for multiple terminals.

[0213] Referring to FIG. 20, in step S2001, the base station generates information related to the radiation pattern of a signal. Here, the information related to the radiation pattern may take the form of an image, and the signal includes a signal transmitted from a terminal for sounding. The image represents the antenna position of the terminal as observed from a reference point of the array of the base station. According to various embodiments, the base station may generate an image representing the radiation pattern by performing an FFT operation, filtering, and an IFFT operation on the received values ​​of the signal.

[0214] In step S2003, the base station estimates the antenna position based on the radiation pattern. The base station can estimate the antenna position based on an image representing the radiation pattern. To this end, according to one embodiment, the base station can utilize a neural network model. For example, the neural network model can have a structure as shown in FIG. 15. Through this, the base station can obtain at least one of information related to the antenna position, such as information on the angle formed by the terminal's antenna with respect to a reference point and reference line on the base station's antenna array, and information on the observed size.

[0215] In step S2005, the base station generates auxiliary information including information related to the antenna position. The information related to the antenna position may include at least one of angle information for the terminal's antenna, a maximum angle value, a minimum angle value, and the size of a candidate area for the antenna position (e.g., the number of pixels in a radiation pattern image). Subsequently, although not illustrated in FIG. 20 , the base station may transmit the generated auxiliary information to the terminal. For example, the auxiliary information may be transmitted as configuration information for channel estimation.

[0216] Figure 21 illustrates the performance of channel estimation techniques according to embodiments of the present disclosure. Figure 21 shows the NMSE according to the SNR variation of the proposed SAOMP technique and the omnidirectional OMP (OOMP) technique. Referring to Figure 21, compared to OOMP, the SAOMP technique achieves high channel estimation accuracy in most SNR ranges. Furthermore, the SAOMP technique has a pilot length Even though it is small, it is confirmed to provide low NMSE.

[0217] The proposed methods described above can be implemented independently, but they can also be implemented as a combination (or merge) of some of the proposed methods. Rules can be defined so that the base station notifies the terminal of the applicability of the proposed methods (or information about the rules of the proposed methods) through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0218] The present disclosure may be embodied in other specific forms without departing from the technical ideas and essential features described herein. Therefore, the above detailed description should not be construed as limiting in all respects but rather as illustrative. The scope of the present disclosure should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present disclosure are intended to be included within the scope of the present disclosure. Furthermore, claims that are not explicitly cited in the claims may be combined to form an embodiment or incorporated into a new claim through a post-filing amendment.

[0219] Embodiments of the present disclosure can be applied to various wireless access systems. Examples of various wireless access systems include the 3rd Generation Partnership Project (3GPP) or 3GPP2 systems.

[0220] The embodiments of the present disclosure can be applied not only to the various wireless access systems described above, but also to all technical fields that utilize these various wireless access systems. Furthermore, the proposed method can also be applied to mmWave and THz communication systems utilizing ultra-high frequency bands.

[0221] Additionally, embodiments of the present disclosure can be applied to various applications such as autonomous vehicles and drones.

Claims

1. In a method of operating a terminal in a wireless communication system, A step of receiving first setting information related to sounding from a base station; A step of transmitting a sounding signal based on the first setting information; A step of receiving second setting information related to channel estimation from the base station; A step of receiving a downlink reference signal from the base station based on the second setting information; and A step of performing channel estimation based on the above downlink reference signal, A method in which the second setting information is based on an antenna position of the terminal estimated based on the sounding signal, and includes information for determining a range of at least one basis vector included in a dictionary.

2. In claim 1, A method in which the above sounding signal is transmitted through time-frequency resources overlapping with at least one other terminal.

3. In claim 1, The step of performing the above channel estimation is: A step of determining a region-focusing dictionary based on the second setting information; and A method comprising the step of determining a support set by selecting an index of at least one of the columns included in the above domain-focused dictionary.

4. In claim 3, A method in which the second setting information is angle information for the antenna of the terminal in the antenna array of the base station, and includes at least one of a maximum value of the angle, a minimum value of the angle, and a size of a candidate area for the antenna position.

5. In claim 4, The step of determining the region-focusing dictionary is: A method comprising the step of determining a region-focused dictionary based on at least one of an angle vector including angle values ​​falling within the range of the maximum and minimum values, distance samples corresponding to each of the angle values, and distances between antennas of the base station.

6. In a method of operating a base station in a wireless communication system, A step of transmitting first setting information related to sounding to a terminal; A step of receiving a sounding signal based on the first setting information; A step of transmitting second setting information related to channel estimation to the terminal; A step of transmitting a downlink reference signal to the terminal based on the second setting information, A method in which the second setting information is based on an antenna position of the terminal estimated based on the sounding signal, and includes information for determining a range of at least one basis vector included in a dictionary.

7. In claim 6, A method in which the second setting information is angle information for the antenna of the terminal in the antenna array of the base station, and includes at least one of a maximum value of the angle, a minimum value of the angle, and a size of a candidate area for the antenna position.

8. In claim 6, A method further comprising a step of estimating an antenna position of the terminal based on the sounding signal.

9. In claim 8, The step of estimating the antenna position of the above terminal is: A step of generating an image representing a radiation pattern for the sounding signal; and A method comprising the step of estimating the antenna position of the terminal based on the image.

10. In claim 9, The steps for generating the above image are: A step of performing a Fourier transform on the reception values ​​of the sounding signal at points included in the space represented by the image; A step of performing filtering on the result of the Fourier transform; and A method comprising the step of performing an inverse-Fourier transform on the result of the above filtering.

11. In claim 9, A method for estimating the antenna position of the terminal using a neural network (NN) detector that takes as input an image representing the radiation pattern and provides as output the probability that each pixel of the image corresponds to the antenna.

12. In claim 11, A method wherein the neural network detector comprises at least one layer for feature extraction and a layer for calculating a probability corresponding to the antenna for at least one pixel.

13. In a wireless communication system, at a terminal, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Receive first setting information related to sounding from the base station, Transmitting a sounding signal based on the above first setting information, Receive second setting information related to channel estimation from the base station, Receive a downlink reference signal from the base station based on the second setting information, Control to perform the channel estimation based on the above downlink reference signal, A terminal wherein the second setting information is based on an antenna position of the terminal estimated based on the sounding signal, and includes information for determining a range of at least one basis vector included in a dictionary.

14. In a wireless communication system, at a base station, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Transmits first setting information related to sounding to the terminal, Receive a sounding signal based on the above first setting information, Transmit second setting information related to channel estimation to the terminal, Control to transmit a downlink reference signal to the terminal based on the above second setting information, A base station, wherein the second setting information is based on the antenna position of the terminal estimated based on the sounding signal, and includes information for determining the range of at least one basis vector included in a dictionary.

15. In communication devices, At least one processor; At least one computer memory connected to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, A step of receiving first setting information related to sounding from a base station; A step of transmitting a sounding signal based on the first setting information; A step of receiving second setting information related to channel estimation from the base station; A step of receiving a downlink reference signal from the base station based on the second setting information; and A step of performing channel estimation based on the above downlink reference signal, A communication device wherein the second setting information is based on an antenna position of the terminal estimated based on the sounding signal, and includes information for determining a range of at least one basis vector included in a dictionary.

16. In a non-transitory computer-readable medium storing at least one instruction, comprising at least one instruction executable by the processor, At least one of the above commands causes the device to: Receive first setting information related to sounding from the base station, Transmitting a sounding signal based on the above first setting information, Receive second setting information related to channel estimation from the base station, Receive a downlink reference signal from the base station based on the second setting information, Control to perform the channel estimation based on the above downlink reference signal, A non-transitory computer-readable medium comprising information for determining a range of at least one basis vector included in a dictionary, wherein the second setting information is based on an antenna position of the terminal estimated based on the sounding signal.

Images