Method performed by node in wireless communication system, electronic apparatus, and storage medium

Abstract

The embodiments of the present disclosure provide a method performed by a node in a wireless communication system, an electronic apparatus, and a storage medium. The method includes: demodulating first signals corresponding to received respective resource elements to obtain second signals corresponding to the respective resource elements and confidence of the second signals corresponding to the respective resource elements; selecting second signals corresponding to a first set of resource elements from among the second signals corresponding to the respective resource elements, according to the confidence of the second signals corresponding to the respective resource elements; determining channel state information corresponding to the first set of resource elements, according to the second signals corresponding to the first set of resource elements; determining channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements.

Description

METHOD PERFORMED BY NODE IN WIRELESS COMMUNICATION SYSTEM, ELECTRONIC APPARATUS, AND STORAGE MEDIUM

[0001] The present disclosure relates to a field of wireless communication technology, specifically to a method performed by a node in a wireless communication system, an electronic apparatus, and a storage medium.

[0002] 5G mobile communication technologies define broad frequency bands such that high transmission rates and new services are possible, and can be implemented not only in "Sub 6GHz" bands such as 3.5GHz, but also in "Above 6GHz" bands referred to as mmWave including 28GHz and 39GHz. In addition, it has been considered to implement 6G mobile communication technologies (referred to as Beyond 5G systems) in terahertz bands (for example, 95GHz to 3THz bands) in order to accomplish transmission rates fifty times faster than 5G mobile communication technologies and ultra-low latencies one-tenth of 5G mobile communication technologies.

[0003] At the beginning of the development of 5G mobile communication technologies, in order to support services and to satisfy performance requirements in connection with enhanced Mobile BroadBand (eMBB), Ultra Reliable Low Latency Communications (URLLC), and massive Machine-Type Communications (mMTC), there has been ongoing standardization regarding beamforming and massive MIMO for mitigating radio-wave path loss and increasing radio-wave transmission distances in mmWave, supporting numerologies (for example, operating multiple subcarrier spacings) for efficiently utilizing mmWave resources and dynamic operation of slot formats, initial access technologies for supporting multi-beam transmission and broadbands, definition and operation of BWP (BandWidth Part), new channel coding methods such as a LDPC (Low Density Parity Check) code for large amount of data transmission and a polar code for highly reliable transmission of control information, L2 pre-processing, and network slicing for providing a dedicated network specialized to a specific service.

[0004] Currently, there are ongoing discussions regarding improvement and performance enhancement of initial 5G mobile communication technologies in view of services to be supported by 5G mobile communication technologies, and there has been physical layer standardization regarding technologies such as V2X (Vehicle-to-everything) for aiding driving determination by autonomous vehicles based on information regarding positions and states of vehicles transmitted by the vehicles and for enhancing user convenience, NR-U (New Radio Unlicensed) aimed at system operations conforming to various regulation-related requirements in unlicensed bands, NR UE Power Saving, Non-Terrestrial Network (NTN) which is UE-satellite direct communication for providing coverage in an area in which communication with terrestrial networks is unavailable, and positioning.

[0005] Moreover, there has been ongoing standardization in air interface architecture / protocol regarding technologies such as Industrial Internet of Things (IIoT) for supporting new services through interworking and convergence with other industries, IAB (Integrated Access and Backhaul) for providing a node for network service area expansion by supporting a wireless backhaul link and an access link in an integrated manner, mobility enhancement including conditional handover and DAPS (Dual Active Protocol Stack) handover, and two-step random access for simplifying random access procedures (2-step RACH for NR). There also has been ongoing standardization in system architecture / service regarding a 5G baseline architecture (for example, service based architecture or service based interface) for combining Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) technologies, and Mobile Edge Computing (MEC) for receiving services based on UE positions.

[0006] As 5G mobile communication systems are commercialized, connected devices that have been exponentially increasing will be connected to communication networks, and it is accordingly expected that enhanced functions and performances of 5G mobile communication systems and integrated operations of connected devices will be necessary. To this end, new research is scheduled in connection with eXtended Reality (XR) for efficiently supporting AR (Augmented Reality), VR (Virtual Reality), MR (Mixed Reality) and the like, 5G performance improvement and complexity reduction by utilizing Artificial Intelligence (AI) and Machine Learning (ML), AI service support, metaverse service support, and drone communication.

[0007] Furthermore, such development of 5G mobile communication systems will serve as a basis for developing not only new waveforms for providing coverage in terahertz bands of 6G mobile communication technologies, multi-antenna transmission technologies such as Full Dimensional MIMO (FD-MIMO), array antennas and large-scale antennas, metamaterial-based lenses and antennas for improving coverage of terahertz band signals, high-dimensional space multiplexing technology using OAM (Orbital Angular Momentum), and RIS (Reconfigurable Intelligent Surface), but also full-duplex technology for increasing frequency efficiency of 6G mobile communication technologies and improving system networks, AI-based communication technology for implementing system optimization by utilizing satellites and AI (Artificial Intelligence) from the design stage and internalizing end-to-end AI support functions, and next-generation distributed computing technology for implementing services at levels of complexity exceeding the limit of UE operation capability by utilizing ultra-high-performance communication and computing resources.

[0008] In order to at least solve the above-mentioned problems existing in the related art, the present disclosure provides a method performed by a node in a wireless communication system, an electronic apparatus, and a storage medium.

[0009] According to a first aspect of an embodiment of the present disclosure, a method performed by a first node in a wireless communication system is provided, the method includes: demodulating first signals corresponding to received respective resource elements, to obtain second signals corresponding to the respective resource elements and confidence of the second signals corresponding to the respective resource elements; selecting second signals corresponding to a first set of resource elements from among the second signals corresponding to the respective resource elements, according to the confidence of the second signals corresponding to the respective resource elements; determining channel state information corresponding to the first set of resource elements, according to the second signals corresponding to the first set of resource elements; determining channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements.

[0010] Alternatively, the demodulating first signals corresponding to received respective resource elements to obtain the second signals corresponding to the respective resource elements and the confidence of the second signals corresponding to the respective resource elements includes: obtaining probability information corresponding to respective constellation points in a constellation diagram by demodulating the first signals corresponding to the respective resource elements, and determining a second signal corresponding to the resource element and confidence of the second signal corresponding to the resource element based on the probability information; and / or, obtaining probability information of respective bits corresponding to the first signal by demodulating the first signals corresponding to the respective resource elements, determining a constellation point corresponding to the first signal in the constellation diagram based on the probability information, obtaining a second signal corresponding to the resource element based on the constellation point corresponding to the first signal, and determining the confidence of the second signal corresponding to the resource element based on the probability information.

[0011] Alternatively, the determining the confidence of the second signal corresponding to the resource element based on the probability information includes: using a negative number or an inverse function of entropy of the probability information as the confidence of the second signal corresponding to the resource element.

[0012] Alternatively, the determining the channel state information corresponding to the first set of resource elements according to the second signals corresponding to the first set of resource elements includes: for each resource element in the first set of resource elements, determining a second resource element associated with the resource element, and determining the channel state information corresponding to the resource element based on a second signal corresponding to the second resource element and the first signal corresponding to the second resource element.

[0013] Alternatively, the second resource element associated with the resource element is at least one resource element adjacent to the resource element in the time domain and / or the frequency domain.

[0014] Alternatively, the determining the second resource element associated with the resource element includes: determining candidate second resource elements associated with the resource element; obtaining an eigenvalue of each of a plurality of matrices composed of second signals corresponding to the candidate second resource elements, based on the matrices; determining a target eigenvalue based on the eigenvalues of each matrix, and determining the second resource element from among the candidate second resource elements based on the target eigenvalue.

[0015] Alternatively, the determining the candidate second resource elements associated with the resource element includes: determining the candidate second resource elements associated with the resource element based on at least one of an Euclidean distance from the resource element, and the confidence of the corresponding second signal.

[0016] Alternatively, the determining the target eigenvalue based on the eigenvalues of each matrix and determining the second resource element from among the candidate second resource elements based on the target eigenvalue includes: determining a minimum eigenvalue among the eigenvalues of each matrix; selecting a maximum eigenvalue from the minimum eigenvalues corresponding to the matrices, and using a resource element corresponding to the maximum eigenvalue as the second resource element.

[0017] Alternatively, the determining channel state information corresponding to the respective resource elements based on the channel state information corresponding to the first set of resource elements includes: eliminating abnormal channel state information among the channel state information corresponding to the first set of resource elements, wherein the abnormal channel state information is channel state information with an amplitude exceeding a threshold; determining the channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements of which the abnormal channel state information is eliminated.

[0018] Alternatively, the method further includes determining the threshold, wherein the determining the threshold includes: selecting an amplitude at a predetermined proportional location from a ranking result of amplitudes of the channel state information corresponding to resource elements in the first set of resource elements, as the threshold.

[0019] According to a second aspect of an embodiment of the present disclosure, an electronic apparatus is provided, which includes: a transceiver for transmitting and receiving signals; and a processor coupled with the transceiver, and configured to perform the method performed by the first node in the wireless communication system as described above.

[0020] According to a third aspect of an embodiment of the present disclosure, a computer-readable storage medium storing instructions, characterized in that, the instructions, when performed by at least one processor, cause the at least one processor to perform the method performed by the first node in the wireless communication system as described above.

[0021] The beneficial effects brought by the technical solutions provided by the embodiments of the present disclosure will be described in the later section in combination with specific optional embodiments, or may be learned from descriptions of the embodiments, or may be learned from implementation of the embodiments.

[0022] In order to more clearly and easily explain and understand technical solutions in embodiments of the present disclosure, a brief introduction will be given to the accompanying drawings required in the description of the embodiments of the present disclosure below.

[0023] FIG. 1 is a diagram illustrating an example wireless network according to an embodiment of the present disclosure;

[0024] FIG. 2 is a block diagram illustrating an example base station according to an embodiment of the present disclosure;

[0025] FIG. 3 is a block diagram illustrating an example user equipment according to an embodiment of the present disclosure;

[0026] FIG. 4 is a schematic diagram illustrating an example of placement pattern of a pilot signal (DMRS) in an NR system;

[0027] FIG. 5 is a flowchart illustrating a method performed by a first node in a wireless communication system according to an exemplary embodiment of the present disclosure;

[0028] FIG. 6 is a schematic diagram illustrating a method of pilot free channel estimation and subsequent equalization and demodulation according to an exemplary embodiment of the present disclosure;

[0029] FIG. 7 is a flowchart illustrating a method of demodulating first signals corresponding to received respective resource elements to obtain second signals corresponding to the respective resource elements;

[0030] FIG. 8 is a flowchart illustrating a method of obtaining confidence of second signals corresponding to respective resource elements;

[0031] FIG. 9 is a flowchart illustrating a method of obtaining confidence of second signals corresponding to respective resource elements according to another exemplary embodiment of the present disclosure;

[0032] FIG. 10 is a flowchart illustrating a method of determining channel state information corresponding to a first set of resource elements based on second signals corresponding to the first set of resource elements according to an exemplary embodiment of the present disclosure;

[0033] FIG. 11 is a flowchart illustrating method of obtaining a combination of associated resources of a target time-frequency resource unit according to an exemplary embodiment of the present disclosure;

[0034] FIG. 12 is a schematic diagram illustrating a method of matching a plurality of candidate associated resource combinations according to an exemplary embodiment of the present disclosure;

[0035] FIG. 13 is a flowchart illustrating a method of determining channel state information corresponding to respective resource elements based on channel state information corresponding to a first set of resource elements according to an exemplary embodiment of the present disclosure;

[0036] FIG. 14 is a block diagram illustrating an electronic apparatus according to an exemplary embodiment of the present disclosure.

[0037] Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document. The term "couple" and its derivatives refer to any direct or indirect communication between two or more elements, whether those elements are in physical contact with one another. The terms "transmit," "receive," and "communicate," as well as derivatives thereof, encompass both direct and indirect communication. The terms "include" and "comprise," as well as derivatives thereof, mean inclusion without limitation. The term "or" is inclusive, meaning and / or. The phrase "associated with," as well as derivatives thereof, means to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The term "controller" means any device, system or part thereof that controls at least one operation. Such a controller may be implemented in hardware or a combination of hardware and software and / or firmware. The functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. The phrase "at least one of," when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, "at least one of: A, B, and C" includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C. Likewise, the term "set" means one or more. Accordingly, a set of items can be a single item or a collection of two or more items.

[0038] Moreover, various functions described below can be implemented or supported by one or more computer programs, each of which is formed from computer readable program code and embodied in a computer readable medium. The terms "application" and "program" refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable computer readable program code. The phrase "computer readable program code" includes any type of computer code, including source code, object code, and executable code. The phrase "computer readable medium" includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A "non-transitory" computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device.

[0039] Definitions for other certain words and phrases are provided throughout this patent document. Those of ordinary skill in the art should understand that in many if not most instances, such definitions apply to prior as well as future uses of such defined words and phrases.

[0040] The figures included herein, and the various embodiments used to describe the principles of the present disclosure are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Further, those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged wireless communication system.

[0041] Hereinafter, embodiments of the disclosure will be described in detail with reference to the accompanying drawings.

[0042] In describing the embodiments, descriptions related to technical contents well-known in the art and not associated directly with the disclosure will be omitted. Such an omission of unnecessary descriptions is intended to prevent obscuring of the main idea of the disclosure and more clearly transfer the main idea.

[0043] For the same reason, in the accompanying drawings, some elements may be exaggerated, omitted, or schematically illustrated. Further, the size of each element does not completely reflect the actual size. In the drawings, identical or corresponding elements are provided with identical reference numerals or different reference numerals.

[0044] The advantages and features of the disclosure and ways to achieve them will be apparent by making reference to embodiments as described below in detail in conjunction with the accompanying drawings. However, the disclosure is not limited to the embodiments set forth below, but may be implemented in various different forms. The following embodiments are provided only to completely disclose the disclosure and inform those skilled in the art of the scope of the disclosure, and the disclosure is defined only by the scope of the appended claims. Throughout the specification, the same or like reference numerals designate the same or like elements. Furthermore, in describing the disclosure, a detailed description of known functions or constitution incorporated herein will be omitted in the case that it is determined that the description may make the subject matter of the disclosure unnecessarily unclear. The terms which will be described below are terms defined in consideration of the functions in the disclosure, and may be different according to users, intentions of the operators, or customs. Therefore, the definitions of the terms should be made based on the contents throughout the specification.

[0045] Herein, it will be understood that each block of the flowchart illustrations, and combinations of blocks in the flowchart illustrations, may be performed based on computer program instructions. These computer program instructions may be loaded collectively onto at least one processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which perform through any one of, or in any combination of, the at least one processor of the computer or other programmable data processing apparatus, create means for performing the functions specified in the flowchart block(s). These computer program instructions may also be stored in a non-transitory computer usable or computer-readable memory that may direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer usable or computer-readable memory produce an article of manufacture including instruction means that perform the function specified in the flowchart block(s). The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable data processing apparatus to produce a computer executed process such that the instructions that perform on the computer or other programmable data processing apparatus provide steps for executing the functions specified in the flowchart block(s).

[0046] Further, each block may represent a module, segment, or portion of code, which includes one or more executable instructions for executing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks may occur out of the order. For example, two blocks(or functions) shown in succession may in fact be performed substantially concurrently or the blocks may sometimes be performed in the reverse order, depending upon the functionality involved.

[0047] As used in embodiments of the disclosure, a "~unit" may refer to a software element or a hardware element, such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC), which performs a predetermined function. However, the term including the word "~unit" does not always have a meaning limited to software or hardware. The "~unit" may be constructed either to be stored in an addressable storage medium or to execute one or more processors. Therefore, the "~unit" includes, for example, software elements, object-oriented software elements, components such as class elements and task elements, processes, functions, properties, procedures, sub-routines, segments of a program code, drivers, firmware, micro-codes, circuits, data, database, data structures, tables, arrays, and parameters. The components and functions provided by the "~unit" may be either combined into a smaller number of components and a "~unit," or divided into additional components and a "~unit." Moreover, the components and "~units" may be implemented to reproduce one or more central processing units (CPUs) within a device or a security multimedia card. Further, in the embodiments, the "쪟unit" may include one or more processors.

[0048] It should be appreciated that the blocks in each flowchart and combinations of the flowcharts may be performed by one or more computer programs which include instructions. The entirety of the one or more computer programs may be stored in a single memory device or the one or more computer programs may be divided with different portions stored in different multiple memory devices.

[0049] Any of the functions or operations described herein can be processed by one processor or a combination of processors. The one processor or the combination of processors is circuitry performing processing and includes circuitry like an application processor (AP, e.g. a CPU), a communication processor (CP, e.g., a modem), a graphics processing unit (GPU), a neural processing unit (NPU) (e.g., an artificial intelligence (AI) chip), a Wi-Fi chip, a Bluetooth® chip, a global positioning system (GPS) chip, a near field communication (NFC) chip, connectivity chips, a sensor controller, a touch controller, a finger-print sensor controller, a display driver integrated circuit (IC), an audio CODEC chip, a universal serial bus (USB) controller, a camera controller, an image processing IC, a microprocessor unit (MPU), a system on chip (SoC), an IC, or the like.

[0050] It will be appreciated that various embodiments of the disclosure according to the claims and description in the specification can be realized in the form of hardware, software or a combination of hardware and software.

[0051] Any such software may be stored in non-transitory computer readable storage media. The non-transitory computer readable storage media store one or more computer programs (software modules), the one or more computer programs include computer-executable instructions that, when executed by one or more processors of an electronic device individually or collectively, cause the electronic device to perform a method of the disclosure.

[0052] Any such software may be stored in the form of volatile or non-volatile storage such as, for example, a storage device like read only memory (ROM), whether erasable or rewritable or not, or in the form of memory such as, for example, random access memory (RAM), memory chips, device or integrated circuits or on an optically or magnetically readable medium such as, for example, a compact disk (CD), digital versatile disc (DVD), magnetic disk or magnetic tape or the like. It will be appreciated that the storage devices and storage media are various embodiments of non-transitory machine-readable storage that are suitable for storing a computer program or computer programs comprising instructions that, when executed, implement various embodiments of the disclosure. Accordingly, various embodiments of the present disclosure may provide a program comprising code for implementing apparatus or a method as claimed in any one of the claims of this specification and a non-transitory machine-readable storage storing such a program.

[0053] Hereinafter, the determination of priority between A and B in the present disclosure may refer to various actions such as selecting the one having a higher priority based on a predefined priority rule and performing an operation corresponding thereto, or omitting or dropping an operation corresponding to the one having a lower priority.

[0054] Hereinafter, "A or B" as described in the present disclosure may be understood as "A and / or B," which may include A, or B, or both A and B.

[0055] In addition, "at least one of A, B, and C" as described in the present disclosure may be understood to include A, or B, or C, or any combination of A, B, and C.

[0056] In addition, "at least one of A, B, or C" as described in the present disclosure may be understood to include A, or B, or C, or any combination of A, B, and C.

[0057] Furthermore, "A / B" as described in the present disclosure may be understood as "A and / or B," which may include A, or B, or both A and B.

[0058] Furthermore, "A, B" as described in the present disclosure may be understood as "A and / or B," which may include A, or B, or both A and B.

[0059] Furthermore, "A and B" as described in the present disclosure may be understood as "A and / or B," which may include A, or B, or both A and B.

[0060] Furthermore, "if condition A and condition B are satisfied," as described in the present disclosure, may not be limited to a case where both condition A and condition B are satisfied, but may be understood to include a case where either condition A or condition B is individually satisfied, both condition A and condition B are satisfied, or one or more additional conditions are satisfied in combination.

[0061] Furthermore, throughout this disclosure, ordinal terms such as "first," "second," "third," etc., (and similar qualifiers) are used merely to distinguish between different instances, occurrences, configurations, messages, stages, or aspects of elements, operations, or information as described herein. Unless the context clearly dictates otherwise, the use of such ordinal terms does not itself require that the elements, operations, or information distinguished by these terms be structurally different, numerically distinct, or substantively dissimilar. For example, a "first signal" and a "second signal" may refer to instances of the same signal transmitted at different times or containing the same core information despite minor variations, or they may refer to signals with different content or characteristics, depending on the specific context. Similarly, a "first value" and a "second value" may represent the same magnitude but measured or applied in different circumstances, or they may represent different magnitudes. The interpretation should be guided by the specific technical context, function, and relationship described in the relevant portion of the specification and claims.

[0062] Furthermore, the terms "first ~", "second ~", etc., as described in the present disclosure with respect to various elements (e.g., information, objects, operation, sequences, or the like), should not limit those elements. These terms may only be intended to distinguish one element from another, and may not be intended to indicate a specific order. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element.

[0063] Furthermore, even if "first ~" and "second ~" are described in the present disclosure, it may be understood that element(s) referred to by "first ~" and "second ~" may be the same or different. For example, in case of element(s) being information, first information and second information may both be same information and, in some cases, are separate and different information.

[0064] In addition, the terms "if ~" and "in case that ~" as used in the disclosure or claims may be interpreted to include the meanings of "when (or upon) ~," "in response to ~," "based on ~," or "according to ~," and may be used interchangeably with these expressions. In addition, expressions other than those exemplified herein may also be used, as long as they have substantially the same meaning and do not impair the technical features of the present disclosure.

[0065] For example, the physical layer signaling may be referred to as Layer 1 (L1) signaling and may include downlink control information (DCI). In addition, the higher layer signaling may include a medium access control (MAC) control message, a radio resource control (RRC) signaling message, a non-access stratum (NAS) signaling message, or an application layer message. The RRC signaling message may be referred to as L3 (layer 3) signaling. It should be noted, however, that the higher layer signaling is not limited to the aforementioned examples.

[0066] In addition, the term "not perform" as used in the present disclosure or claims may, in context, be understood to mean that the corresponding step is omitted or skipped. Such a term may be replaced with other terms having the same or substantially equivalent meaning.

[0067] In addition, "transmitting a message including A and B" as described in the present disclosure, may be understood as encompassing both (i) transmitting A and B in a single message, and (ii) transmitting A and B separately via multiple messages (e.g., transmitting a first message including A and a second message including B). This interpretation may also apply to messages that include two or more items (e.g., A, B, C), transmitted either together or separately.

[0068] In addition, "transmitting a message including A and transmitting a message including B" may also be interpreted as transmitting a message including A and B in a single message.

[0069] In the specific embodiments of the present disclosure described below, terms or components included in the disclosure may be expressed in singular or plural form depending on the specific embodiments presented. However, such singular or plural expressions are selected appropriately for convenience of description, and the present disclosure is not limited to a singular or plural number of components. A component expressed in the plural form may be implemented as a single component, and a component expressed in the singular form may be implemented as multiple components.

[0070] The drawings or flowcharts described below illustrate exemplary methods that may be implemented according to the principles of the present disclosure, and various modifications may be made to the methods illustrated in the flowcharts of the present disclosure. For example, although illustrated as a series of steps, various steps in each drawing or flowchart may overlap, occur in parallel, occur in a different order, or be repeated. In other examples, any step may be omitted or replaced with another step.

[0071] The methods and apparatuses proposed in the embodiments of the present disclosure are not limited to each embodiment individually, but may also be applied in combination of all or some of the embodiments proposed in the disclosure. Therefore, the embodiments of the present disclosure may be modified and applied without significantly departing from the scope of the present disclosure, as would be understood by those skilled in the art.

[0072] In this case, even if certain wordings are described differently across embodiments, they may be used interchangeably or in substitution or in combination if their underlying concepts are equivalent. For example, for the same or equivalent concept, even if one embodiment uses the expression "A" and another embodiment uses the expression "B", such expressions may be understood interchangeably, in substitution, or in combination.

[0073] The terms used in the following description to refer to access nodes, network entities, messages, interfaces between network entities, various types of identification information, and the like, are provided merely for the convenience of explanation by way of example. Therefore, the present disclosure is not limited to the terms described below, and other terms having equivalent technical meanings may also be used. Such terms may also be interchangeable with terms defined in any 3rd generation partnership project　(3GPP) technical specifications (TS) where appropriate.

[0074] Hereinafter, a base station is an entity that allocates resources to terminals, and may be at least one of a gNode B, an eNode B, a Node B, a base station (BS), a wireless access unit, a BS controller, or a node on a network.

[0075] Furthermore, the base station of the present disclosure may include a split architecture comprising a central unit (CU) and a distributed unit (DU). In this structure, the CU is configured to process the higher layers of the control and user planes, while the DU is configured to process lower-layer radio resource functions. The embodiments of the present disclosure may be equally applicable to 5G base station architectures in which such CU and DU functional splits are implemented.

[0076] A terminal may include a UE, a mobile station (MS), a cellular phone, a smartphone, a computer, or a multimedia system capable of performing communication functions.

[0077] In the disclosure, a downlink (DL) refers to a radio link through which a BS transmits a signal to a UE, and an uplink (UL) refers to a radio link through which a UE transmits a signal to a BS.

[0078] Furthermore, hereinafter, 5th generation (5G) mobile communication technologies (e.g., 5G new radio (NR)), 6th generation (6G) mobile communication technologies may be described by way of example, but the embodiments of the present disclosure may also be applied to other communication systems having similar technical backgrounds or channel types. For example, newly evolved mobile communication systems developed after 5G and 6G may be included. Furthermore, based on determinations by those skilled in the art, the embodiments of the present disclosure may also be applied to other communication systems (e.g., Wi-Fi systems) through some modifications without significantly departing from the scope of the present disclosure

[0079] In the following description, the terms physical channel and signal may be used interchangeably with data or control signal. For example, the term physical downlink shared channel (PDSCH) refers to a physical channel through which data is transmitted, but the term PDSCH may also be used to refer to the data itself. That is, in the present disclosure, the expression "transmit a physical channel" may be interpreted as being equivalent to the expression "transmit data or a signal via a physical channel."

[0080] Hereinafter, in the context of the present disclosure, higher layer signaling may refer to signaling corresponding to at least one or any combination of the following: master information block (MIB), system information block (SIB) or SIB M (M = 1, 2, ...), radio resource control (RRC), or medium access control (MAC) control element (CE), or a non-access stratum (NAS) signaling message, or an application layer message. The RRC signaling message may be referred to as L3 (layer 3) signaling.

[0081] In addition, L1 signaling may refer to signaling corresponding to at least one or any combination of signaling techniques using the at least one or any combination of the following physical layer channels or signaling: physical downlink control channel (PDCCH), downlink control information (DCI), user equipment (UE)-specific DCI, group-common DCI, common DCI, scheduling DCI (e.g., DCI used for scheduling downlink or uplink data), non-scheduling DCI (e.g., DCI not used for scheduling downlink or uplink data) physical uplink control channel (PUCCH), or uplink control information (UCI). The L1 signaling message may be referred to as a physical layer signaling.

[0082] Hereinafter, the expression that information is configured by the BS, as used in the present disclosure or claims, may, in context, be understood to mean that the terminal receives the corresponding information from the BS via a physical layer signaling or a higher layer signaling. Such an expression may be replaced with other terms having the same or substantially equivalent meaning.

[0083] Hereinafter, the operational principle of the present disclosure will be described in detail with reference to the accompanying drawings.

[0084] Considering the development of wireless communication from generation to generation, the technologies have been developed mainly for services targeting humans, such as voice calls, multimedia services, and data services. Following the commercialization of 5th-generation (5G) communication systems, it is expected that the number of connected devices will exponentially grow. Increasingly, these will be connected to communication networks. Examples of connected things may include vehicles, robots, drones, home appliances, displays, smart sensors connected to various infrastructures, construction machines, and factory equipment. Mobile devices are expected to evolve in various form-factors, such as augmented reality glasses, virtual reality headsets, and hologram devices. In order to provide various services by connecting hundreds of billions of devices and things in the 6th-generation (6G) era, there have been ongoing efforts to develop improved 6G communication systems. For these reasons, 6G communication systems are referred to as beyond-5G systems.

[0085] 6G communication systems, which are expected to be commercialized around 2030, will have a peak data rate of tera (1,000 giga)-level bps and a radio latency less than 100μsec, and thus will be 50 times as fast as 5G communication systems and have the 1 / 10 radio latency thereof.

[0086] In order to accomplish such a high data rate and an ultra-low latency, it has been considered to implement 6G communication systems in a terahertz band (for example, 95GHz to 3THz bands). It is expected that, due to severer path loss and atmospheric absorption in the terahertz bands than those in mmWave bands introduced in 5G, technologies capable of securing the signal transmission distance (that is, coverage) will become more crucial. It is necessary to develop, as major technologies for securing the coverage, radio frequency (RF) elements, antennas, novel waveforms having a better coverage than orthogonal frequency division multiplexing (OFDM), beamforming and massive multiple input multiple output (MIMO), full dimensional MIMO (FD-MIMO), array antennas, and multiantenna transmission technologies such as large-scale antennas. In addition, there has been ongoing discussion on new technologies for improving the coverage of terahertz-band signals, such as metamaterial-based lenses and antennas, orbital angular momentum (OAM), and reconfigurable intelligent surface (RIS).

[0087] Moreover, in order to improve the spectral efficiency and the overall network performances, the following technologies have been developed for 6G communication systems: a full-duplex technology for enabling an uplink transmission and a downlink transmission to simultaneously use the same frequency resource at the same time; a network technology for utilizing satellites, high-altitude platform stations (HAPS), and the like in an integrated manner; an improved network structure for supporting mobile base stations and the like and enabling network operation optimization and automation and the like; a dynamic spectrum sharing technology via collision avoidance based on a prediction of spectrum usage; an use of artificial intelligence (AI) in wireless communication for improvement of overall network operation by utilizing AI from a designing phase for developing 6G and internalizing end-to-end AI support functions; and a next-generation distributed computing technology for overcoming the limit of user equipment (UE) computing ability through reachable super-high-performance communication and computing resources (such as mobile edge computing (MEC), clouds, and the like) over the network. In addition, through designing new protocols to be used in 6G communication systems, developing mechanisms for implementing a hardware-based security environment and safe use of data, and developing technologies for maintaining privacy, attempts to strengthen the connectivity between devices, optimize the network, promote softwarization of network entities, and increase the openness of wireless communications are continuing.

[0088] It is expected that research and development of 6G communication systems in hyper-connectivity, including person to machine (P2M) as well as machine to machine (M2M), will allow the next hyper-connected experience. Particularly, it is expected that services such as truly immersive extended reality (XR), high-fidelity mobile hologram, and digital replica could be provided through 6G communication systems. In addition, services such as remote surgery for security and reliability enhancement, industrial automation, and emergency response will be provided through the 6G communication system such that the technologies could be applied in various fields such as industry, medical care, automobiles, and home appliances.

[0089] FIGS. 1-3 below describe various embodiments of the present disclosure implemented in wireless communications systems. The descriptions of FIGS. 1-3 are not meant to imply physical or architectural limitations to the manner in which different embodiments may be implemented. Different embodiments of the present disclosure may be implemented in any suitably-arranged communications system.

[0090] FIG. 1 illustrates an example wireless network according to embodiments of the present disclosure. The embodiment of the wireless network shown in FIG. 1 is for illustration only. Other embodiments of the wireless network 100 could be used without departing from the scope of the present disclosure.

[0091] Referring to FIG. 1, the wireless network includes a base station (next generation nodeB, gNB or gNodeB) 101, a gNB 102, and a gNB 103. The gNB 101 communicates with the gNB 102 and the gNB 103. The gNB 101 also communicates with at least one network 130, such as the Internet, a proprietary Internet Protocol (IP) network, or other data network.

[0092] The gNB 102 provides wireless broadband access to the network 130 for a first plurality of user equipments (UEs) within a coverage area 120 of the gNB 102. The first plurality of UEs includes a UE 111, which may be located in a small business; a UE 112, which may be located in an enterprise (E); a UE 113, which may be located in a WiFi hotspot (HS); a UE 114, which may be located in a first residence (R1); a UE 115, which may be located in a second residence (R2); and a UE 116, which may be a mobile device (M), such as a cell phone, a wireless laptop, a wireless personal digital assistant (PDA), or the like. The gNB 103 provides wireless broadband access to the network 130 for a second plurality of UEs within a coverage area 125 of the gNB 103. The second plurality of UEs includes the UE 115 and the UE 116, as well as subscriber stations (SS, for example, UEs) 117, 118 and 119. In some embodiments, one or more of the gNBs 101-103 may communicate with each other and with the UEs 111-116 using existing wireless communication techniques, and one or more of the UE 111-119 may communicate directly with each other (e.g., UEs 117-119) using other existing or proposed wireless communication techniques.

[0093] Depending on the network type, the term "base station" or "BS" can refer to any component (or collection of components) configured to provide wireless access to a network, such as transmit point (TP), transmit-receive point (TRP), an enhanced (or "evolved") base station (eNodeB or eNB), a 5G base station (gNB), a macrocell, a femtocell, a wireless fidelity (WiFi) access point (AP), or other wirelessly enabled devices. Base stations may provide wireless access in accordance with one or more wireless communication protocols, e.g., 3GPP 5G New Radio (NR), Long Term Evolution (LTE), LTE Advanced (LTE-A), high speed packet access (HSPA), Wi-Fi 802.11a / b / g / n / ac, etc. For the sake of convenience, the various names for a base station-type apparatus and functionality are used interchangeably in this patent document to refer to network infrastructure components that provide wireless access to remote terminals. Also, depending on the network type, the term "user equipment" (UE) can refer to any component such as a mobile station (MS), subscriber station (SS), remote terminal, wireless terminal, receive point, or user device. For the sake of convenience, the various names for a user equipment-type device and functionality are used interchangeably in this patent document to refer to remote wireless equipment that wirelessly accesses a BS, whether the UE is a mobile device (such as a mobile telephone or smartphone) or is normally considered a stationary device (such as a desktop computer or vending machine).

[0094] Dotted lines show the approximate extents of the coverage areas 120 and 125, which are shown as approximately circular for the purposes of illustration and explanation only. It should be clearly understood that the coverage areas associated with gNBs, such as the coverage areas 120 and 125, may have other shapes, including irregular shapes, depending upon the configuration of the gNBs and variations in the radio environment associated with natural and man-made obstructions.

[0095] As described in more detail below, one or more of the UEs 111-119 include circuitry, programing, or a combination thereof. In certain embodiments, and one or more of the gNBs 101-103 includes circuitry, programing, or a combination thereof.

[0096] Although FIG. 1 illustrates one example of a wireless network, various changes may be made to FIG. 1. For example, the wireless network could include any number of gNBs and any number of UEs in any suitable arrangement. Also, the gNB 101 could communicate directly with any number of UEs and provide those UEs with wireless broadband access to the network 130. Similarly, each gNB 102-103 could communicate directly with the network 130 and provide UEs with direct wireless broadband access to the network 130. Further, the gNBs 101, 102, and / or 103 could provide access to other or additional external networks, such as external telephone networks or other types of data networks.

[0097] FIG. 2 illustrates an example base station according to embodiments of the present disclosure. The embodiment of the gNB 102 illustrated in FIG. 2 is for illustration only, and the gNBs 101 and 103 of FIG. 1 could have the same or similar configuration. However, gNBs come in a wide variety of configurations, and FIG. 2 does not limit the scope of the present disclosure to any particular implementation of a gNB.

[0098] Referring to FIG 2, the gNB 102 includes multiple antennas 200a-200n, multiple radio frequency (RF) transceivers 201a-201n, transmit (TX) processing circuitry 203, and receive (RX) processing circuitry 204. The gNB 102 also includes a controller / processor 205, a memory 206, and a backhaul or network interface 207.

[0099] The RF transceivers 201a-201n receive, from the antennas 200a-200n, incoming RF signals, such as signals transmitted by UEs in the network 100. The RF transceivers 201a-201n down-convert the incoming RF signals to generate intermediate frequency (IF) or baseband signals. The IF or baseband signals are sent to the RX processing circuitry 204, which generates processed baseband signals by filtering, decoding, and / or digitizing the baseband or IF signals. The RX processing circuitry 204 transmits the processed baseband signals to the controller / processor 205 for further processing.

[0100] The TX processing circuitry 203 receives analog or digital data (such as voice data, web data, electronic mail, or interactive video game data) from the controller / processor 205. The TX processing circuitry 203 encodes, multiplexes, and / or digitizes the outgoing baseband data to generate processed baseband or IF signals. The RF transceivers 201a-201n receive the outgoing processed baseband or IF signals from the TX processing circuitry 203 and up-converts the baseband or IF signals to RF signals that are transmitted via the antennas 201a-201n.

[0101] The controller / processor 205 can include one or more processors or other processing devices that control the overall operation of the gNB 102. For example, the controller / processor 205 could control the reception of forward channel signals and the transmission of reverse channel signals by the RF transceivers 201a-201n, the RX processing circuitry 204, and the TX processing circuitry 203 in accordance with well-known principles. The controller / processor 205 could support additional functions as well, such as more advanced wireless communication functions.

[0102] For instance, the controller / processor 205 could support beam forming or directional routing operations in which outgoing signals from multiple antennas 200a-200n are weighted differently to effectively steer the outgoing signals in a desired direction. Any of a wide variety of other functions could be supported in the gNB 102 by the controller / processor 205.

[0103] The controller / processor 205 is also capable of executing programs and other processes resident in the memory 206, such as an operating system (OS). The controller / processor 205 can move data into or out of the memory 206 as required by an executing process.

[0104] The controller / processor 205 is also coupled to the backhaul or network interface 207. The backhaul or network interface 207 allows the gNB 102 to communicate with other devices or systems over a backhaul connection or over a network. The interface 207 could support communications over any suitable wired or wireless connection(s). For example, when the gNB 102 is implemented as part of a cellular communication system (such as one supporting 5G, LTE, or LTE-A), the interface 207 could allow the gNB 102 to communicate with other gNBs over a wired or wireless backhaul connection. When the gNB 102 is implemented as an access point, the interface 207 could allow the gNB 102 to communicate over a wired or wireless local area network or over a wired or wireless connection to a larger network (such as the Internet). The interface 207 includes any suitable structure supporting communications over a wired or wireless connection, such as an Ethernet or RF transceiver.

[0105] The memory 206 is coupled to the controller / processor 205. Part of the memory 206 could include a random access memory (RAM), and another part of the memory 206 could include a Flash memory or other read only memory (ROM).

[0106] Although FIG. 2 illustrates one example of gNB 102, various changes may be made to FIG. 2. For example, the gNB 102 could include any number of each component shown in FIG. 2. As a particular example, an access point could include a number of interfaces 207, and the controller / processor 205 could support routing functions to route data between different network addresses. As another particular example, while shown as including a single instance of TX processing circuitry 203 and a single instance of RX processing circuitry 204, the gNB 102 could include multiple instances of each (such as one per RF transceiver). Also, various components in FIG. 2 could be combined, further subdivided, or omitted and additional components could be added according to particular needs.

[0107] FIG. 3 illustrates an example user equipment according to embodiments of the present disclosure. The embodiment of the UE 116 illustrated in FIG. 3 is for illustration only, and the UEs 111-115 and 117-119 of FIG. 1 could have the same or similar configuration. However, UEs come in a wide variety of configurations, and FIG. 3 does not limit the scope of the present disclosure to any particular implementation of a UE.

[0108] Referring to FIG. 3, the UE 116 includes an antenna 301, a radio frequency (RF) transceiver 302, TX processing circuitry 303, a microphone 304, and receive (RX) processing circuitry 305. The UE 116 also includes a speaker 306, a controller or processor 307, an input / output (I / O) interface (IF) 308, an input device 309, a touchscreen display 310, and a memory 311. The memory 311 includes an OS 312 and one or more applications 313.

[0109] The RF transceiver 302 receives, from the antenna 301, an incoming RF signal transmitted by a gNB of the network 100. The RF transceiver 302 down-converts the incoming RF signal to generate an IF or baseband signal. The IF or baseband signal is sent to the RX processing circuitry 305, which generates a processed baseband signal by filtering, decoding, and / or digitizing the baseband or IF signal. The RX processing circuitry 305 transmits the processed baseband signal to the speaker 306 (such as for voice data) or to the processor 307 for further processing (such as for web browsing data).

[0110] The TX processing circuitry 303 receives analog or digital voice data from the microphone 304 or other outgoing baseband data (such as web data, e-mail, or interactive video game data) from the processor 307. The TX processing circuitry 303 encodes, multiplexes, and / or digitizes the outgoing baseband data to generate a processed baseband or IF signal. The RF transceiver 302 receives the outgoing processed baseband or IF signal from the TX processing circuitry 303 and up-converts the baseband or IF signal to an RF signal that is transmitted via the antenna 301.

[0111] The processor 307 can include one or more processors or other processing devices and execute the OS 312 stored in the memory 311 in order to control the overall operation of the UE 116. For example, the processor 307 could control the reception of forward channel signals and the transmission of reverse channel signals by the RF transceiver 302, the RX processing circuitry 305, and the TX processing circuitry 303 in accordance with well-known principles. In some embodiments, the processor 307 includes at least one microprocessor or microcontroller.

[0112] The processor 307 is also capable of executing other processes and programs resident in the memory 311, such as processes for channel state information (CSI) reporting on uplink channel. The processor 307 can move data into or out of the memory 311 as required by an executing process. In some embodiments, the processor 307 is configured to execute the applications 313 based on the OS 312 or in response to signals received from gNBs or an operator. The processor 307 is also coupled to the I / O interface 308, which provides the UE 116 with the ability to connect to other devices, such as laptop computers and handheld computers. The I / O interface 308 is the communication path between these accessories and the processor 307.

[0113] The processor 307 is also coupled to the touchscreen display 310. The user of the UE 116 can use the touchscreen display 310 to enter data into the UE 116. The touchscreen display 310 may be a liquid crystal display, light emitting diode display, or other display capable of rendering text and / or at least limited graphics, such as from web sites.

[0114] The memory 311 is coupled to the processor 307. Part of the memory 311 could include RAM, and another part of the memory 311 could include a Flash memory or other ROM.

[0115] Although FIG. 3 illustrates one example of UE 116, various changes may be made to FIG. 3. For example, various components in FIG. 3 could be combined, further subdivided, or omitted and additional components could be added according to particular needs. As a particular example, the processor 307 could be divided into multiple processors, such as one or more central processing units (CPUs) and one or more graphics processing units (GPUs). Also, while FIG. 3 illustrates the UE 116 configured as a mobile telephone or smartphone, UEs could be configured to operate as other types of mobile or stationary devices.

[0116] A wireless signal in a wireless communication process may be distorted due to being subjected to channel warping, which affects accuracy of demodulation at a receiving end. To address this problem, a modern wireless communication system obtains channel state information through channel estimation, then uses an equalization method to maximize elimination of the channel warping on the wireless signal, and finally demodulates an equalized received signal, to improve the accuracy of demodulation at the receiving end. In this term, the method of obtaining the channel state information by the modern wireless communication system is to agree on a time frequency resource location for inserting a pilot and information carried by the pilot signal at both of the transmitting and receiving ends, and transmit the pilot signal at the agreed time frequency resource location by the transmitting end. The specific method of obtaining the channel state information by the receiving end is to receive the pilot signal at the agreed time-frequency resource location by the receiving end, to perform channel estimation based on the received pilot signal and the information carried by the known pilot signal, and then, to obtain channel state information on all time-frequency resources (the pilot signal is only distributed in partial time-frequency resource locations) using interpolation, extrapolation and other methods.

[0117] FIG. 4 illustrates a schematic diagram of an example of placement pattern of a pilot signal (DMRS) in a current NR system.

[0118] In the above system, in order to obtain accurate channel state information, the pilot signal needs to be orthogonal to a data signal. Specifically, when the pilot signal is placed on one time-frequency resource, no more data signals can be placed on this time-frequency resource. Therefore, this placement criterion results in a portion of time-frequency resources on one frequency band being used to place pilot signals, while another portion of the time-frequency resources being used to place data signals. In the current New radio (NR) system, a Demodulation Reference Signal (DMRS) is used as the pilot signal, accounting for 2.3% -21.4% of the entire time-frequency resources. The proportion of the pilot signals is determined by a configuration and increases with the number of antenna ports. It can be seen that a large amount of time-frequency resources are used to place the pilots and data cannot be placed, resulting in a decrease in spectral efficiency. In the future 6G system, it is expected that the antenna ports will increase several times compared to the current NR system, which will also lead to a further increase in a demand for the pilots (which is proportional to the increase in the number of antenna ports). The current channel estimation method will further increase the proportion of pilot time-frequency resources, resulting in the decrease in the spectral efficiency. This causes the gain from increasing the number of antenna ports to be offset by the frequency conduction overheads.

[0119] To address the above problem of the pilot overhead, a concept of pilot free communication is proposed. Specifically, a transmitting end places data signals on all time-frequency resources without placing any pilot signals, thereby improving spectrum utilization. Correspondingly, since no pilot signal is placed, the receiving end cannot obtain the channel state information by channel estimation. Therefore, the receiving end ignores the warping of the wireless signal caused by the channel and directly demodulates the received signal. However, the problem with this method is that the accuracy of demodulation is low and it cannot reach a demodulation threshold of the system.

[0120] Considering the above situations, the present disclosure proposes a method of performing pilot free channel estimation by a receiver in a communication system. This method may obtain channel state information without placing a pilot signal, so that a receiver may eliminate warping of a data signal cause by a channel and improve accuracy of demodulation. The present disclosure may achieve similar accuracy in the pilot free communication as that of a pilot communication. Moreover, as this method avoids overhead caused by inserting pilots, it improves overall spectrum efficiency and increases system throughput. In the following, the exemplary embodiments of the present disclosure will be described in combination with Figs. 5-14.

[0121] FIG. 5 is a flowchart illustrating a method performed by a first node in a wireless communication system according to an exemplary embodiment of the present disclosure.

[0122] As an exemplary embodiment, a type of the first node may include but is not limited to at least one of a UE, a base station, a relay node, a Centralized Unit (CU) of the base station, and a Distributed Unit (DU) of the base station.

[0123] Referring to FIG. 5, in step S1000, first signals corresponding to received respective resource elements are demodulated to obtain second signals corresponding to the respective resource elements and confidence of the second signals corresponding to the respective resource elements.

[0124] As an exemplary embodiment, the first signals corresponding to the respective resource elements collectively constitute a target signal, which is a received signal that is required to be subjected to channel estimation. As an example, there is no pilot signal in the target signal. As an example, the target signal may be a single channel signal or a multiplexing signal (e.g. an N-channel multiplexing signal, wherein N is an integer greater than 1).

[0125] As an exemplary embodiment, the target signal may be a frequency domain signal on a plurality of time domain units, and the frequency domain signal includes modulated complex-valued symbols on one or more subcarriers. A granularity of the time-domain unit may be a symbol, a slot, a subframe, a frame, etc. The target signal containing one resource block is taken as an example, data contained in the target signal may be represented by one two-dimensional matrix with a dimension of [14,12], wherein the first dimension and second dimension correspond to 14 symbols in the time domain and 12 subcarriers in the frequency domain, respectively, and it contains total of 168 modulated complex-valued symbols. For example, the method of obtaining the frequency domain signal on each time domain symbol may obtain an OFDM baseband signal by demodulating and down-sampling a received RF signal within one time domain symbol gap, and then, convert the OFDM baseband signal into a frequency domain signal by fast Fourier transform.

[0126] As an exemplary embodiment, the resource elements may be elements on one or more resource dimensions, for example, the one or more resource dimensions may include but not be limited to at least one dimension in the time domain and the frequency domain. For example, a granularity of the resource elements may be but is not limited to a time-frequency resource unit.

[0127] As an exemplary embodiment, a manner of demodulating the first signals corresponding to the respective received resource elements may be blind demodulation. As an exemplary embodiment, a blind demodulated signal may represent complex-valued symbols obtained by directly deciding the target signal according to a constellation diagram corresponding to modulation and demodulation. The structure of the obtained blind demodulated signal is the same as that of the target signal, and may be represented by a tensor that includes one or more complex-valued symbols in the time domain and the frequency domain.

[0128] The blind demodulation refers to an operation of making a decision on the target signal without equalization. The method of the blind demodulation may be used in a situation where a receiver does not have available channel state information and therefore cannot equalize the target signal. The method of the decision may be a hard decision based on minimum distance, a logarithmic likelihood ratio based on maximum posterior probability criterion, etc. Taking Quadrature Phase Shift Keying (QPSK) modulation as an example, a coordinate of the constellation diagram isconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2). When a modulated complex-valued symbol on one time-domain symbol and one subcarrier in the target signal isdata_symbol=1-0.9j, a method of obtaining the demodulated complex-valued symbol using the minimum distance hard decision is to calculateconstellation[argmin(abs(constellation-data_symbol))], whereinabsrepresents a calculated absolute value,argminrepresents calculating minimum value and obtaining an index where the minimum value is located. Finally, in the constellation diagram, the demodulated complex-valued symbol of1-1jis obtained through the index in the constellation diagram.

[0129] As an exemplary embodiment, the second signals corresponding to the respective resource elements collectively constitute a demodulated signal (e.g. a blind demodulated signal). As an example, when the granularity of the resource elements is the time-frequency resource unit, the blind demodulated signal includes complex-valued symbols (i.e., complex-valued symbols after blind demodulation, also referred to as blind demodulated complex-valued symbols) obtained by the blind demodulation of the modulated complex-valued symbols corresponding to the respective time-frequency resource units.

[0130] The confidence of the second signal corresponding to each resource element may represent confidence that whether the demodulation (e.g. the blind demodulation) of the first signal corresponding to the resource element is accurate.

[0131] As an exemplary embodiment, step S1000 may include: obtaining probability information corresponding to respective constellation points in a constellation diagram by demodulating the first signals corresponding to the respective resource elements, and determining a second signal corresponding to the resource element and confidence of the second signal corresponding to the resource element based on the probability information.

[0132] As another exemplary embodiment, step S1000 may include: obtaining probability information of respective bits corresponding to the first signal by demodulating the first signals corresponding to the respective resource elements, determining a constellation point corresponding to a first signal in the constellation diagram based on the probability information, obtaining a second signal corresponding to the resource element based on the constellation point corresponding to the first signal, and determining the confidence of the second signal corresponding to the resource element based on the probability information.

[0133] As an example, a negative number or an inverse function of entropy of the probability information may be used as the confidence of the second signal corresponding to the resource element.

[0134] As an example, the first signal corresponding to each resource element may be input into one model (for example, a neural network model) to obtain the probability information corresponding to the respective constellation points in the constellation diagram or the probability information of the respective bits corresponding to the first signal, which is output by the model. For example, when the granularity of the resource elements is the time-frequency resource unit, after the target signal is input into the model, the model may output the probability distribution of each complex-valued symbol or the probability distribution of the demodulated bits corresponding to each complex-valued symbol. The exemplary embodiment of step S1000 will be described below in conjunction with FIGs. 7 and 8, which will not be further elaborated here.

[0135] As another example, the first and second signals corresponding to each resource element can be input into one model (for example, a neural network model), to obtain the confidence of the second signal corresponding to each resource element, which is output by the model. The exemplary embodiment of step S1000 will be described below in conjunction with FIG. 9, which will not be further elaborated here.

[0136] In step S2000, second signals corresponding to a first set of resource elements from among the second signals corresponding to the respective resource elements are selected according to the confidence of the second signals corresponding to the respective resource elements.

[0137] As an exemplary embodiment, the first set of resource elements may be a set including a part of all resource elements corresponding to the target signal. For example, for the target signal containing complex-valued symbols on one resource block with a dimension of [14, 12] (14 time-domain symbols and 12 frequency-domain subcarriers), the first set of resource elements may be a set of time-frequency resources with dimensions of [2, 12] containing all subcarriers on the 1st and 14th time-domain symbols of the target signal resource block.

[0138] As an exemplary embodiment, the first set of resource elements may include a resource element corresponding to a second signal with confidence greater than a pre-set confidence threshold. It should be understood that the specific value of the pre-set confidence threshold may be set according to an actual situation and specific needs, for example, it may be set to 0.5.

[0139] For example, when the granularity of resource elements is the time-frequency resource unit, step S2000 may include: determining the confidence threshold; and determining the first set of resource elements according to the confidence threshold and the confidence of the second signals corresponding to the respective time-frequency resource units. Specifically, the confidence of the second signal corresponding to each time-frequency resource unit is compared with the confidence threshold, and the time-frequency resource unit corresponding to the second signal with confidence greater than the confidence threshold is added to the first set of resource elements for channel estimation. The confidence threshold of 0.5 and the target signal containing complex-valued symbols on one resource block with a dimension of [14, 12] (14 time-domain symbols and 12 frequency-domain subcarriers) are taken as an example, wherein the confidence of the second signals corresponding to all subcarriers on the 1st and 14th time-domain symbols are 1, and the confidence of the second signals corresponding to other time-domain symbols are 0.1. Through the above method of comparing the confidence of the second signal corresponding to each time-frequency resource unit, it may be determined that the first set of resource elements for channel estimation may be a set of time-frequency resources with dimensions of [2,12] containing all subcarriers on the 1st and 14th time-domain symbols of the target signal resource block.

[0140] In step S3000, channel state information corresponding to the first set of resource elements is determined according to the second signals corresponding to the first set of resource elements.

[0141] In step S4000, channel state information corresponding to the respective resource elements is determined based on the channel state information corresponding to the first set of resource elements.

[0142] As an exemplary embodiment, the channel state information may be one of vector, matrix, or tensor that contains an estimated channel impulse response in one or more dimensions. Specifically, the one or more dimensions may include at least one dimension in the time domain and the frequency domain. The granularity of each unit channel impulse response in the time domain dimension may be a symbol, a slot, a subframe, a frame, and so on. The granularity of each unit channel impulse response in the frequency domain dimension may be a subcarrier, a resource block, a plurality of resource blocks having a fixed length, a sub-band, a wideband, and so on. It should be understood that channel state information is not limited to the channel impulse response, but may also be other types of channel state information, which is not limited by the present disclosure.

[0143] As an exemplary embodiment, step S3000 may include: for each resource element in the first set of resource elements, determining a second resource element associated with the resource element, and determining the channel state information corresponding to the resource element based on a second signal corresponding to the second resource element and the first signal corresponding to the second resource element.

[0144] As an example, the second resource element associated with the resource element may be at least one resource element adjacent to the resource element in the time domain and / or the frequency domain.

[0145] As an example, the step of determining the second resource element associated with the resource element may include: determining candidate second resource elements associated with the resource element; obtaining an eigenvalue of each of a plurality of matrices composed of second signals corresponding to the candidate second resource elements, based on the matrices; determining a target eigenvalue based on the eigenvalues of each matrix, and determining the second resource element from among the candidate second resource elements based on the target eigenvalue. For example, the determining the candidate second resource elements associated with the resource element may include determining the candidate second resource elements associated with the resource element based on at least one of an Euclidean distance from the resource element and the confidence of the corresponding second signal. For example, the determining the target eigenvalue based on the eigenvalues of each matrix, and determining the second resource element from among the candidate second resource elements based on the target eigenvalue may include: determining a minimum eigenvalue among the eigenvalues of each matrix; selecting a maximum eigenvalue from the minimum eigenvalues corresponding to respective matrices, and using a resource element corresponding to the maximum eigenvalue as the second resource element.

[0146] As an exemplary embodiment, step S4000 may include: eliminating abnormal channel state information among the channel state information corresponding to the first set of resource elements; then, determining the channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements of which the abnormal channel state information is eliminated. As an example, the abnormal channel state information may be channel state information with an amplitude exceeding a threshold. For example, the amplitude at a predetermined proportional location may be selected from a ranking result of amplitudes of the channel state information corresponding to resource elements in the first set of resource elements, as the threshold.

[0147] The exemplary embodiments of steps S3000 and S4000 will be described below in conjunction with FIGs.10 to 13, which will not be further elaborated here.

[0148] As an exemplary embodiment, the method performed by the first node in the wireless communication system according to the exemplary embodiment of the present disclosure may further include: obtaining an equalized signal, by performing equalization process on the first signals corresponding to the respective resource elements using the channel state information corresponding to the respective resource elements, and obtaining a demodulated signal by demodulating the equalized signal to.

[0149] FIG. 6 is a schematic diagram illustrating a method of pilot free channel estimation and subsequent equalization and demodulation according to an exemplary embodiment of the present disclosure.

[0150] Referring to FIG. 6, a demodulated signal may be obtained according to a target signal and channel state information corresponding to the respective resource elements. Specifically, firstly an equalized target signal may be obtained by performing equalization process on the target signal using the channel state information. For example, the method of equalization may be Zero-forcing equalization, Minimum Mean Square Error (MMSE) equalization, Viterbi equalization, etc. Then, a demodulated complex-valued symbol may be obtained, by making a decision on the equalized target signal according to a constellation diagram corresponding to modulation and demodulation. The method of decision may be a hard decision based on minimum distance, a logarithmic likelihood ratio based on maximum posteriori probability criterion, etc. A target signalYis taken as an example, the process of obtaining a demodulated symbol may include: obtaining a blind demodulated symbol and confidenceCby blind decoding and confidence calculation; obtaining a matrix H composed of channel state information on the respective resource elements by pilot free channel estimation; obtaining an equalized target signal =Y / H by the zero-forcing equalization method; and obtaining the demodulated symbol by demodulating the equalized target signal .

[0151] An exemplary embodiments for blind demodulation

[0152] FIG. 7 is a flowchart illustrating a method of demodulating first signals corresponding to the respective resource elements to obtain second signals corresponding to the respective resource elements.

[0153] Referring to FIG. 7, in step S1100, a transformed signal is obtained by transforming on a target signal.

[0154] As an exemplary embodiment, a signal (i.e., the transformed signal) which is consistent with a data format and a structure of an input layer of a first model, may be obtained, by transforming a data format and a structure of the target signal.

[0155] In step S1200, the transformed signal is input into the first model which is pre-trained, to obtain an output quantity of the first model.

[0156] As an exemplary embodiment, the first model may be a neural network model, and it should be understood that it may also be other types of models, which is not limited by the present disclosure. For example, the type of the first model may include but is not limited to at least one of an auto-encoder, a denoising autoencoder, a bariational autoencoder, an adversarial neural network (GAN), a diffusion model, a multi-layer perceptron (MLP), a convolutional neural network (CNN), a deep neural network (DNN), a recursive neural network (RNN), a restricted Boltzmann machine (RBM), a graph neural network (GNN), a deep belief network (DBN), a bidirectional recursive deep neural network (BRDNN), a connector network (Transformer).

[0157] In step S1300, a blind demodulated signal is obtained according to the output quantity of the first model.

[0158] As an exemplary embodiment, step S1300 may include: deciding constellation points corresponding to respective modulated complex-valued symbols (i.e., the first signals corresponding to respective resource elements) in the target signal according to the output quantity of the first model; obtaining the respective blind demodulated complex-valued symbols (i.e., the second signal corresponding to each resource element) according to the decision result.

[0159] The output quantity of the first model is a quantity related to blind demodulation. Specifically, it will be illustrated by the following two exemplary embodiments.

[0160] As one exemplary embodiment, the output quantity of the first model may include probability distribution of the modulated complex-valued symbol on each time-frequency resource unit. As an example, the probability distribution may be a probability of all modulation constellation points occurring at a target modulated complex-valued symbol, that is, a probability of each modulated complex-valued symbol in the target signal corresponding to the respective constellation points in the preset constellation diagram (i.e., the constellation diagram corresponding to modulation and demodulation). For example, the number of output neurons of the first model isT*F*M, whereinTis the number of time domain symbols,Fis the number of frequency domain subcarriers, andMis the number of constellation points corresponding to the modulation method. The output neurons output a probability value, for example, using a Softmax function as an activation function for all output neurons. Reception of a signal using Quadrature Phase Shift Keying (QPSK) on a resource block of [14, 12] (14 time domain symbols and 12 frequency domain subcarriers) is taken as an example, a signal modulation includes four constellation points which areconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2), respectively. Therefore, the number of output neurons of the first model isT*F*M=14*12*4.

[0161] Correspondingly, step S1300 may include selecting a constellation point corresponding to the maximum probability in the output neurons associated with the modulated complex-valued symbols. A signal of Quadrature Phase Shift Keying (QPSK) modulation is taken as an example, the modulation manner includes four constellation points which areconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2), repectively, each modulated complex-valued symbol obtains four probabilitiesP=[p1,p2,p3,p4] corresponding to different constellation points, respectively, through a neural network. The method of obtaining the blind demodulated signal isconstellation(argmax(P)), whereinargmaxrepresents an index where the maximum probability is obtained.P=[0.7,0.1,0.1,0.1] is taken as an example, by introducing the probability distribution into the above equationconstellation(argmax([0.7,0.1,0.1,0.1])), the demodulated complex-valued symbol is finally obtained as1-1j, by indexing in the constellation diagram.

[0162] As another exemplary embodiment, the output quantity of the first model may include probability distribution of a bit sequence corresponding to a modulated complex-valued symbol on each time-frequency resource unit. As an example, the probability distribution may be a probability that each bit in the bit sequence corresponding to the modulation method represents 1 or 0, that is, a probability that each bit in the bit sequence corresponding to each modulated complex-valued symbol in the target signal carries 0 or 1. For example, the number of output neurons in a neural network model isT*F*B, whereinTis the number of time-domain symbols,Fis the number of frequency-domain subcarriers, andBis the number of bits corresponding to the modulation method. The output neurons output a scalar that represents the probability that a bit carries 1 or 0, for example, using a Sigmoid function as an activation function for all output neurons or without using the activation function. Reception of a signal using Quadrature Phase Shift Keying (QPSK) on a resource block of [14, 12] (14 time domain symbols and 12 frequency domain subcarriers) is taken as an example, a signal modulation manner includes four constellation points which areconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2), respectively, and the constellation points may be mapped into four types of 2-bit information, which areBI=[01,00,11,10], respectively, thus, the number of output neurons of the first model isT*F*B=14*12*2.

[0163] Correspondingly, step S1300 may include: obtaining bit information by making a decision of 0 or 1 on each output neuron associated with the modulated complex-valued symbols; then, obtaining the constellation points corresponding to the modulated complex-valued symbols by mapping according the bit information. The decision method realizes a binary decision of 0 or 1 according to a decision threshold specified by the first model training. The decision threshold beingγ=0.5is taken as an example, it represents a current bit of 1 when the output neuronb1>γ, and itrepresents the current bit of 0 when the output neuron b1 . The signal of Quadrature Phase Shift Keying (QPSK) modulation is taken as an example, the modulation manner includes four constellation points which areconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2), respectively, and the constellation points may be mapped into four types of 2-bit information, which areBI=[01,00,11,10], respectively, and the output neurons corresponding to the modulated complex-valued symbol on one time-frequency resource unit are [b1,b2]=[0.1, 0.9]. The method of obtaining the blind demodulated signal obtains the bit

[0001] corresponding to the modulated complex-valued symbol by making a decision on the output neurons [b1, b2], obtains the indexconstellation(BI==

[0001] ) of the bit in the constellation diagram by bit mapping of the constellation points, thereby obtaining the demodulated complex-valued symbol of1-1j.

[0164] An exemplary embodiments for obtaining confidence

[0165] FIG. 8 is a flowchart illustrating a method of obtaining confidence of second signals corresponding to respective resource elements according to an exemplary embodiment of the present disclosure.

[0166] Referring to FIGs. 7 and 8, in step S1400, confidence of the respective blind demodulated complex-valued symbols are obtained according to the output quantity of the first model.

[0167] As an exemplary embodiment, step S1400 may include step S1410 and / or step S1420.

[0168] In step S1410, in a case that the output quantity of the first model includes the probability corresponding to each modulated complex-valued symbol in the target signal and the respective constellation points in the preset constellation, for each blind demodulated complex-valued symbol, the maximum probability of the probabilities associated with the blind demodulated complex-valued symbol among the output quantity of the first model is taken as the confidence of the blind demodulated complex-valued symbol, or a negative number or an inverse function of entropy of the probabilities associated with the blind demodulated complex-valued symbol among the output quantity of the first model is taken as the confidence of the blind demodulated complex-valued symbol.

[0169] As an exemplary embodiment, when the output quantity of the first model is the probability distribution of each complex-valued symbol, the method of obtaining the confidence that whether the blind demodulation of the modulated complex-valued symbol corresponding to each time-frequency resource unit is accurate may be one of the following: taking the maximum probability in the output neurons associated with the modulated complex-valued symbol as the confidence of the blind demodulated complex-valued symbol corresponding to the modulated complex-valued symbol; or taking a negative number or an inverse function of entropy calculated by all output neurons associated with the modulated complex-valued symbol as the confidence of the blind demodulated complex-valued symbol corresponding to this modulated complex-valued symbol. The solving of the maximum probability of the output neuron as the confidence is taken as an example, for each modulated complex-valued symbol, four probabilitiesP=[p1,p2,p3,p4] which are corresponding to different constellation points, respectively, are obtained through a neural network, the method of obtaining the confidence isP(argmax(P)), whereinargmaxrepresents an index where the maximum probability is obtained.P=[0.7,0.1,0.1,0.1]is taken as an example, by introducing the probability distribution into the above equationP(argmax([0.7,0.1,0.1,0.1])), the confidence is finally obtained as 0.7 by indexing in the probability distribution.

[0170] In step S1420, in a case that the output quantity of the first model includes the probability that each bit in the bit sequence corresponding to each modulated complex-valued symbol in the target signal carries 0 or 1, for each blind demodulated complex-valued symbol, a sum of absolute values of probabilities associated with the blind demodulated complex-valued symbol in the output quantity of the first model is taken as the confidence of the blind demodulated complex-valued symbol.

[0171] As an exemplary embodiment, when the output quantity of the first model includes the probability distribution of the bit sequence corresponding to the modulated complex-valued symbol on each time-frequency resource unit (that is, the probability distribution of the bit sequence after blind demodulation corresponding to each modulated complex-valued symbol), the method of obtaining the confidence that whether the blind demodulation of the modulated complex-valued symbol corresponding to each time-frequency resource unit is accurate may firstly calculate an absolute value of output of each output neuron corresponding to the modulated complex-valued symbol, and then accumulate all the absolute values as the confidence. Taking the signal of Quadrature Phase Shift Keying (QPSK) modulation as an example, the modulation manner includes four constellation points which areconstellation=[1-1j,1+1j,-1-1j,-1+1j] / sqrt(2), respectively, and the constellation points may be mapped into four types of 2-bit information, which areBI=[01,00,11,10], respectively, values of the output neurons corresponding to one modulated complex-valued symbol is [b1,b2]=[-0.5, 0.9]. The method of obtaining the confidence firstly calculates the absolute values of the neuron outputs as [0.5, 0.9], and then obtains confidence of 1.4 by accumulating the absolute values.

[0172] FIG. 9 is a flowchart illustrating a method of obtaining confidence of second signals corresponding to respective resource elements according to another exemplary embodiment of the present disclosure.

[0173] Referring to FIG. 9, in step S1500, a model input quantity is generated according to a target signal and a blind demodulated signal.

[0174] As an exemplary embodiment, step S1500 may include: obtaining a merged signal by directly concatenating or superimposing the target signal and the blind demodulated signal; and obtaining the model input quantity by transforming the merged signal, that is, a transformation result is used as the model input quantity. Specifically, the target signal and the blind demodulated signal may be merged, and the merging method may directly concatenate the two signals or that use one signal as location code for the other signal (i.e., the two signals on the same time-frequency resource unit is added point by point). For example, a signal with a data format and a structure consistent with the input layer of the second model described below may be obtained, by transforming the data format and the structure of the merged signal.

[0175] In step S1600, the model input quantity generated in step S1500 is input into a second model which is pre-trained, to obtain the confidence of each blind demodulated complex-valued symbol output by the second model.

[0176] As an exemplary embodiment, the second model may be a neural network model, and it should be understood that it may also be other types of models, which is not limited by the disclosure. For example, the type of the second model may include but is not limited to at least one of a auto-encoder, a denoising autoencoder, a variational autoencoder, adversarial neural network (GAN), a diffusion model, a multi-layer perceptron (MLP), a convolutional neural network (CNN), a deep neural network (DNN), a recursive neural network (RNN), a restricted Boltzmann machine (RBM), a graph neural network (GNN), a deep belief network (DBN), a bidirectional recursive deep neural network (BRDNN), a connector network (Transformer).

[0177] An exemplary embodiments for obtaining channel state information

[0178] As an exemplary embodiment, step S3000 may include: performing channel estimation on the first set of resource elements, according to the modulated complex-valued symbols corresponding to the first set of resource elements (i.e., the first signals corresponding to the first set of resource elements) and the blind demodulated complex-valued symbols (i.e., the second signals corresponding to the first set of resource elements) among the target signal and the blind demodulated signal, and obtaining the channel state information corresponding to the first set of resource elements. That is, according to the modulated complex-valued symbols and demodulated complex-valued symbols on the resource elements included in the first set of resource elements, the channel state information on the resource elements included in the first set of resource elements is obtained.

[0179] As an exemplary embodiment, the channel state information corresponding to the first set of resource elements may include channel state information corresponding to each resource element in the first set of resource elements.

[0180] For example, if the first set of resource elements for channel estimation of the target signal is a set of time-frequency resources with dimensions of [2,12] that contain all subcarriers on the 1st and 14th time-domain symbols of a target signal resource block, the obtained channel state information corresponding to the first set of resource elements may be a tensor with dimensions of [2,12], each dimension corresponds to a channel impulse response corresponding to a different time-domain symbol and a subcarrier, respectively.

[0181] An exemplary embodiment of step S3000 in a case that the target signal is an N-channel multiplexed signal (i.e., a signal of multiplexed data) will be described below in conjunction with FIG. 10. This will not be further elaborated here.

[0182] As an exemplary embodiment, step S4000 may include: obtaining the channel state information corresponding to all resource elements of the target signal through interpolation method, according to the channel state information corresponding to the first set of resource elements.

[0183] As an exemplary embodiment, firstly, channel estimation (CE) is performed on time-frequency resource units in the first set of resource elements for channel estimation, and channel state information corresponding to the time-frequency resource units contained in the set is obtained. Then, the channel state information on all time-frequency resource units of the target signal may be obtained using the interpolation method. For example, the method based on the channel estimation may include but are not limited to at least one of least squares channel estimation (LS CE), minimum mean square error channel estimation (MMSE CE), maximum likelihood estimation channel estimation (ML CE), Kalman filter estimation channel estimation (KF CE), etc. The interpolation method may also be referred to as interpolation method, extrapolation method, or super-resolution. For example, the interpolation method may include but are not limited to at least one of piecewise constant interpolation, linear interpolation, polynomial interpolation, spline interpolation, analog interpolation, neural network interpolation, super-resolution imaging, etc. Reception of a signal on one resource block of [14,12] (14 time-domain symbols and 12 frequency-domain subcarriers) is taken as an example, if the first set of resource elements for channel estimation is a set of time-frequency resources with dimensions of [2,12] for all subcarriers on the 1st and 14th time-domain symbols of the resource block, the process of obtaining channel state information on all time-frequency resources may include: firstly, obtaining channel state information with dimensions of [2,12] through channel estimation; afterwards, by using linear interpolation, obtaining the channel state information covering all time-frequency resources, the channel state information having dimensions of [14,12].

[0184] An exemplary embodiment of step S4000 will be described below in conjunction with FIG. 13, which will not be further elaborated here.

[0185] An exemplary embodiment for channel estimation in a multi-layer transmission case

[0186] In some cases, the first node may also receive a signal containing 2 or more channels of multiplexed data. The multiplexing represents a method of parallel transmission and reception of multi-channel data using spatial multiplexing technology on the same time-frequency resources at both ends of the transmitter and receiver. The 2 or more channels of multiplexed data may also be referred to as 2 or more streams of multiplexed data, 2 or more layers of multiplexed data, etc. A signal for the implementation of multiplexing transmission and reception of 2 or more channels of multiplexed data requires the number of antenna ports included in the apparatuses at both ends are not less than the number of channels of data carried by the signal. The received signal containing 2 channels of multiplexed data is taken as an example, in one resource block, data contained in the target signal may be represented by a three-dimensional tensor with dimensions of [2, 14, 12], wherein the dimensions correspond to 2 channels of data in a spatial domain, 14 symbols in the time domain, and 12 subcarriers in the frequency domain, total of 336 modulated complex-valued symbols.

[0187] As an exemplary embodiment, in a case that the target signal is a multiplexed signal, step S1000 may include: according to the signal containing 2 or more channels of multiplexed data, obtaining confidence of the blind demodulated signal containing 2 or more channels of multiplexed data and confidence of each blind demodulated complex-valued symbol. A structure of the obtained blind demodulated signal is the same as that of the target signal, and may be represented by a tensor that includes one or more complex-valued symbol in the spatial, temporal, and frequency domains. The received signal containing 2 channels of multiplexed data is taken as an example, on one resource block, the blind demodulated signal may be represented by a three-dimensional tensor with dimensions of [2, 14, 12]. The confidence of each the blind demodulated complex-valued symbols represents confidence that whether the blind demodulation of the modulated complex-valued symbol corresponding to each signal is accurate on each time-frequency resource.

[0188] As an exemplary embodiment, in a case that the target signal is a multiplexed signal, the target signal containing two channels of signals on one resource block is taken as an example, the target signal may be represented by a three-dimensional tensor with dimensions of [2, 14, 12] (two channels of data in the spatial domain, 14 time-domain symbols, and 12 frequency-domain subcarriers), and the first set of resource elements for channel estimation may be a set of time-frequency resources with dimensions of [2, 2, 12] that includes all subcarriers on the 1st and 14th time-domain symbols of the two channels of signals.

[0189] As an exemplary embodiment, in a case that the target signal is a multiplexed signal, the channel state information may be a tensor containing an estimated channel impulse response in the spatial (multiplexing), temporal, and frequency domain dimensions. The granularity of the spatial dimension may be a channel, a stream, a layer, an antenna port, etc. The granularity of each unit channel impulse response in the time domain dimension may be a symbol, a time slot, a subframe, a frame, etc.. The granularity of each unit channel impulse response in the frequency domain dimension may be a subcarrier, a resource block, a plurality of resource blocks having a fixed length, a sub-band, a broadband, etc. For example, if the first set of resource elements for channel estimation of a target signal containing two channels of data is a set of time-frequency resources with dimensions of [2,12] that include all subcarriers on the 1st and 14th time-domain symbols of the target signal resource block, the channel state information corresponding to the first set of resource elements obtained is a tensor with dimensions of [2,12], and each dimension corresponds to a channel impulse response corresponding to a different spatial data layer, time-domain symbol, and subcarrier.

[0190] As an exemplary embodiment, in a case that the target signal is a multiplexed signal, step S3000 may include: firstly, by performing channel estimation on the time-frequency resource units in the first set of resource elements for channel estimation for each channel of data, obtaining channel state information for all time-frequency resource units in the first set of resource elements for each channel of data; Then, obtaining the channel state information of all time-frequency resource units for each channel of data through an interpolation method. Reception of a signal containing 2 streams of data on one resource block of [14, 12] (14 time-domain symbols and 12 frequency-domain subcarriers) is taken as an example, the first set of resource elements for channel estimation is a set of time-frequency resources with dimensions of [2,12] for all subcarriers on the 1st and 14th time-domain symbols of the resource block. The process of obtaining channel state information on all time-frequency resources may include: firstly, through channel estimation, obtaining channel state information with dimensions of [2, 12], each dimension corresponds to a channel impulse responses corresponding to a different spatial data layer, time-domain symbol, and subcarrier; afterwards, obtaining the channel state information covering all time-frequency resources through linear interpolation, the channel state information has dimensions of [2,14,12].

[0191] As an exemplary embodiment, in a case that the target signal is a multiplexed signal, the demodulated signal may be obtained based on the target signal including 2 or more channels of multiplexed data and the channel state information corresponding to the respective resource elements. For example, firstly, by equalizing the target signal on each antenna port using the channel state information, the equalized target signal may be obtained; afterwards, the complex-valued symbols are obtained by directly deciding the equalized target signal according to the constellation diagram corresponding to modulation and demodulation. For example, the following are taken as an example: the first node includes two antenna ports, the target signal contains two channels of multiplexed data. the target signal is , wherein y1and y2represent the received signals of an antenna port 1 and an antenna port 2, respectively; a blind demodulated symbol and confidenceCare obtained by blind decoding and confidence calculation; a matrix composed of channel state information on all time-frequency resources is obtained by pilot free channel estimation, wherein h11and h12represent the channel state information corresponding to the first channel and second channel of signals received by the antenna port 1, h21and h22represent the channel state information corresponding to the first channel and second channel of signals received by the antenna port 2, respectively; the equalized target signal may be obtained by Zero-forcing equalization method, represents the inverse of the matrix, , and represent the first channel and second channel of the equalized signals, respectively; by demodulating each equalized signal, the demodulated symbol is obtained, wherein and represent the first channel and second channel of demodulated signals, respectively.

[0192] FIG. 10 is a flowchart illustrating method of determining channel state information corresponding to first set of resource elements according to second signals corresponding to the first set of resource elements, in a case that a target signal is an N-channel multiplexed signal, according to an exemplary embodiment of the present disclosure.

[0193] Referring to FIG. 10, in step S3100, each time-frequency resource unit in the first set of resource elements is taken as a target time-frequency resource unit, and an associated resource combination of the target time-frequency resource unit is obtained.

[0194] The associated resource combination of the target time-frequency resource unit includes the target time-frequency resource unit and at least one other time-frequency resource unit (i.e., a second resource element) in the first set of resource elements. As an exemplary embodiment, the at least one other time-frequency resource unit may be (N-1) time-frequency resource units adjacent to the target time-frequency resource unit in the time and / or frequency domain.

[0195] An exemplary embodiment of step S3100 will be described below in conjunction with FIG. 11, which will not be further elaborated here.

[0196] In step S3200, by performing channel estimation on the target time-frequency resource unit according to a modulated complex-valued symbol and a blind demodulated complex-valued symbol corresponding to the associated resource combination among the target signal and the blind demodulated signal, the channel state information corresponding to the target time-frequency resource unit is obtained.

[0197] As an exemplary embodiment, step S3200 may include: assuming that channels of all time-frequency resource units in the associated resource combination are consistent with each other, according to the modulated complex-valued symbol and the blind demodulated complex-valued symbol corresponding to the associated resource combination among the target signal and the blind demodulated signal, by solving the channel estimation equation constructed for the respective time-frequency resource units in the associated resource combination, the channel state information corresponding to the target time-frequency resource unit is obtained. That is, based on the assumption that the channels of all time-frequency resources in the associated resource combination are consistent with each other, the channel estimation equation is constructed and solved to obtain the channel state information.

[0198] As an exemplary embodiment, the method of obtaining the channel state information for the respective time-frequency resource units in the first set of resource elements of each channel of data may include: obtaining an associated resource combination for each time-frequency resource unit in the first set of resource elements for channel estimation, wherein the associated resource combination includes a target time-frequency resource unit and one or more other time-frequency resource unit presented in the first set of resource elements for channel estimation; and obtaining channel state information on the target time-frequency resource unit according to the associated resource combination. For example, the number of time-frequency resource units included in the associated resource combination is the same as the number of channels for multiplexing.

[0199] As an exemplary embodiment, the associated resource combination includes the target time-frequency resource unit and one or more other time-frequency resource unit present in the first set of resource elements for channel estimation. The other time-frequency resource unit may be a time-frequency resource unit adjacent to the target time-frequency resource unit in the time domain and / or frequency domain. For example, a signal containing 2 streams of data on one resource block of [14,12] (14 time-domain symbols and 12 frequency-domain subcarriers) is taken as an example, the first set of resource elements for channel estimation is a set of time-frequency resources with dimensions of [2,12] for all subcarriers on the 1st and 14th time-domain symbols of the resource block. A resource unit located at [1, 1] (1st time-domain symbol, 1st subcarrier) in the time-frequency domain may be combined with a resource unit located at [1, 2] (1st time-domain symbol, 2nd subcarrier) in the time-frequency domain as the associated resource combination located at [1, 1] target time-frequency resource unit, wherein the resource units located at [1,1] and [1,2] both present in the first set of resource elements for channel estimation.

[0200] As an exemplary embodiment, the method of obtaining the channel state information on the target time-frequency resource unit according to the associated resource combination may include: based on the assumption that the channels of all time-frequency resources in the associated resource combination are consistent with each other, obtaining the channel state information by constructing and solving a channel estimation equation. As an example, for each channel of signal, the constructed equation is ,Yis a vector composed of the received signal from each time-frequency resource unit in the associated resource combination,Nis noise, is a matrix composed of each channel of signal on each time-frequency resource unit after blind demodulation,His a matrix composed of the channels experienced by each channel of signal on each time-frequency resource unit, and based on the assumption that each signal subjects to the same channel in different time-frequency resource units. Based on the above assumptions, the required channel state information may be obtained by solving the above constructed equation. For example, the target signal including two channels for multiplexed signals is taken as an example, wherein ,ain represents an index of a receiving antenna port,brepresents an index of the time-frequency resource unit, for example, represents the received signal of the time-frequency resource unit 1 at a second antenna port; by blind demodulation and confidence calculation, the blind demodulated symbols are obtained, whereinain represents an index of the number of channels of the signal, andbrepresents the index of the time-frequency resource unit, for example, represents symbols carried on a first channel of signal on the second time-frequency resource unit, wherein matrices composed of the channel state information on the first and second time-frequency resource units are represented by matrices and , respectively,ain represents an index of the receiving antenna port,brepresents the index of the number of channels of the signal, andcrepresents the index of the time-frequency resource unit. For example, represents the channel experienced by the first signal on the first time-frequency resource unit on the second receiving antenna port. Through the above combination, the constructed equation may be expressed as:

[0201] ,

[0202] ,

[0203] ,

[0204] .

[0205] Wherein,Yand are known variables, and the equation is used to solve for eight parameters and inH. Due to the presence of 8 unknown variables in the above 4 equations, they are unsolvable. An equation set as followings is obtained by assuming that the above equations are :

[0206] ,

[0207] ,

[0208] ,

[0209] .

[0210] The above equation set may be simplified in a form of matrix multiplication , more specifically, expressed as:

[0211] .

[0212] By solving the above equation set, the required channel state information may be obtained asH. Specifically, The method of obtaining the channel state information by solving the above equations may be one of least squares channel estimation (LS CE), minimum mean square error channel estimation (MMSE CE), maximum likelihood estimation channel estimation (ML CE), etc. For example, the method of obtaining the channel state information by using least squares channel estimation to solve the above equation set is , wherein represents an inverse matrix for solving *.

[0213] FIG. 11 is a flowchart illustrating method of obtaining associated resource combination of a target time-frequency resource unit according to an exemplary embodiment of the present disclosure.

[0214] Referring to FIG. 11, in step S3110, a plurality of candidate associated resource combinations of the target time-frequency resource unit are obtained.

[0215] As an exemplary embodiment, step S3110 may include selecting M time-frequency resource units as candidate second resource elements in the time domain and / or frequency domain according to a principle of Euclidean distance from the target time-frequency resource unit in an ascending order, wherein in a case that there are a plurality of time-frequency resource units with similar Euclidean distance from the target time-frequency resource unit in selection, a time-frequency resource unit with a higher confidence in the corresponding blind demodulated complex-valued symbols is selected in priority; then, according to the M time-frequency resource units, the plurality of candidate associated resource combinations are obtained, wherein each candidate associated resource combination includes (N-1) time-frequency resource units and the target time-frequency resource unit among the M time-frequency resource units, wherein M is an integer greater than or equal to N.

[0216] As an exemplary embodiment, the method of obtaining the plurality of candidate associated resource combinations may select a certain number of time-frequency resource units near to the target time-frequency resource unit from among the first set of resource elements for channel estimation to form a plurality of candidate associated resource combinations. The method of selecting the certain number of time-frequency resource units near to the target time-frequency resource unit may make a selection following the principle of Euclidean distance in an ascending order, in any one of the time-domain, the frequency-domain, or the time-frequency domains. When there are two or more time-frequency resource units with similar Euclidean distance, a time-frequency resource unit with the higher confidence may be selected in priority according to the confidence of the corresponding to the blind demodulated complex-valued symbols. For example, reception of a signal on one resource block of [14, 12] (14 time-domain symbols and 12 frequency-domain subcarriers) is taken as an example, the first set of resource elements for channel estimation is a set of time-frequency resources with dimensions of [2, 12] for all subcarriers on the 1st and 14th time-domain symbols of the resource block. When the target time-frequency resource unit is [1, 1] (the first time-domain symbol, the first subcarrier), the time-frequency resource units are matched sequentially from the 2nd to the 12th subcarriers in the first time-domain symbol to obtain the plurality of candidate associated resource combinations. As an example, the number of candidate associated resource combinations may be pre-set according to actual situations and specific needs, and the value ofMmay be set according to the number of candidate associated resource combinations. FIG. 12 is a schematic diagram illustrating a method of matching a plurality of candidate associated resource combinations according to an exemplary embodiment of the present disclosure.

[0217] In step S3120, one optimal candidate associated resource combination is selected from among the a plurality of candidate associated resource combinations, as the associated resource combination of the target time-frequency resource unit, that is, one optimal associated resource combination of the target time-frequency resource unit is selected.

[0218] As an exemplary embodiment, one or more eigenvalue may be obtained by matrix decomposition method according to a matrix composed of the demodulated complex-valued symbols; then, according a minimum eigenvalue of each candidate associated resource combination, the optimal associated resource combination is selected. As an example, step S3120 may include: obtaining a minimum eigenvalue of the matrix composed of blind demodulated complex-valued symbols corresponding to each candidate associated resource combination by performing eigenvalue decomposition on the matrix ,; then, determining the maximum value among minimum eigenvalues corresponding to all candidate associated resource combinations, and taking a candidate associated resource combination corresponding to the maximum value as the optimal associated resource combination. For example, the method of selecting the optimal associated resource combination may include: determining a plurality of candidate associated resource combinations for the target time-frequency resource unit; obtaining the minimum eigenvalue of the matrix composed of the blind demodulated symbols in each candidate associated resource combination by performing eigenvalue decomposition on the matrix,; by comparing the minimum eigenvalues of all candidate associated resource combinations, selecting the candidate associated resource combination corresponding to the maximum value from among the minimum eigenvalues as the optimal associated resource combination.

[0219] As an exemplary embodiment, the method of obtaining the minimum eigenvalue of the matrix composed of the blind demodulated symbols in each candidate associated resource combination by performing eigenvalue decomposition on the matrix, may include: for each candidate associated resource combination, obtain one or more eigenvalue by performing eigenvalue decomposition on the matrix; then, obtain the minimum eigenvalue by ranking the eigenvalues of the candidate associated resource combinations. The matrix includes a matrix of multi-channel blind demodulated symbols corresponding to each time-frequency resource unit in the candidate associated resource combination, and the matrix includes two dimensions of time-frequency resource unit and signal channel for multiplexing. For example, reception of a signal that includes two channels for multiplexing is taken as an example, the candidate associated resource combination includes two time-frequency resource units, the matrix composed of blind demodulated symbols may be represented as:

[0220] ,

[0221] Whereinain represents an index of the number of channels of signal, andbrepresents an index of a time-frequency resource unit, for example, represents a symbol carried on a first signal on a second time-frequency resource unit.

[0222] FIG. 13 is a flowchart illustrating a method of determining channel state information corresponding to respective resource elements based on channel state information corresponding to a first set of resource elements according to an exemplary embodiment of the present disclosure.

[0223] Referring to FIG. 13, instep S4100, abnormal channel state information among channel state information corresponding to a first set of resource elements is eliminated.

[0224] Before obtaining channel state information on all time-frequency resources, the channel state information of which outlier is eliminated may also be obtained using a method of outlier detection and elimination, according to the channel state information on the first set of resource elements for channel estimation.

[0225] As an exemplary embodiment, step S4100 may include: eliminating channel state information with an amplitude exceeds an amplitude threshold from the channel state information corresponding to the first set of resource elements, wherein the amplitude threshold is a preset percentile value after ranking the amplitudes of the channel state information corresponding to the first set of resource elements from in an ascending order. As an example, the method of outlier detection and elimination may set the amplitude threshold for the channel state information and removing channel state information that exceeds the amplitude threshold. For example, the method of determining the amplitude threshold may calculate the amplitude of channel state information on each time-frequency resource unit in the first set of resource elements for channel estimation, and rank all amplitudes in an ascending order and obtain a percentile number amplitude as the amplitude threshold. The percentile of the percentile number may be a constant, and its value may be set according to actual situations and specific needs. The first set of resource elements for channel estimation is taken as an example, which includes all subcarriers on the 1st and 14th time-domain symbols of the resource block, the first set of resource elements includes 28 time-frequency resource units, a 90% percentile is taken as an example, the method of obtaining the amplitude threshold ranks the amplitudes of the channel state information on the 28 time-frequency resource units in an ascending order, and takes the amplitude ranked at 25th as the amplitude threshold.

[0226] As another exemplary embodiment, step S4100 may include: eliminating channel state information of which a variance between an amplitude and a median amplitude exceeds a preset variance threshold (i.e., a median variance threshold), from the channel state information corresponding to the first set of resource elements, wherein the median amplitude is a median of the amplitudes of the channel state information corresponding to the first set of resource elements, ranked in an ascending order. As an example, the method of outlier detection and elimination may obtain the variance between the amplitude and the median amplitude of channel state information, and remove channel state information that exceeds the median variance threshold according to the median variance threshold. For example, the method may include: calculating the amplitude of channel state information on each time-frequency resource unit in the first set of resource elements for channel estimation; ranking all amplitudes in ascending order and obtain the median amplitude; calculating the variance between each amplitude and the median amplitude; comparing each variance with the median variance threshold and remove channel state information of which the corresponding variance exceeds the median variance threshold. The median variance threshold may be a constant, and its value may be set according to actual situations and specific needs. The first set of resource elements for channel estimation is taken as an example, which includes 5 time-frequency resource units with a median variance threshold of 1, the amplitudes of the channel state information corresponding to the 5 time-frequency resource units are [0.5, 0.4, 0.3, 0.2, 100], the median amplitude is 0.4, and the variance between all amplitudes and the median amplitude is [0.01, 0, 0.01, 0.04, 9920.16]. By comparing the variance with the median variance threshold of 1, it may be determined to remove the channel state information corresponding to the 5th time-frequency resource unit.

[0227] In step S42000, the channel state information corresponding to all resource elements is obtained through interpolation method, according to the channel state information corresponding to the first set of resource elements of which abnormal channel state information is eliminated.

[0228] FIG. 14 is a block diagram illustrating an electronic apparatus according to an exemplary embodiment of the present disclosure.

[0229] Referring to FIG. 14, the electronic apparatus according to an exemplary embodiment of the present disclosure may include a transceiver 1000 and a processor 2000.

[0230] Specifically, the transceiver 1000 is used for transmitting and receiving signals.

[0231] The processor 2000 is coupled to the transceiver 1000 and configured to perform the method performed by the first node in the wireless communication system in the exemplary embodiments as described above.

[0232] As an exemplary embodiment, the electronic apparatus according to the exemplary embodiment of the present disclosure may be an electronic apparatus serving as a receiver in a communication system, for example, may include but not limited to a UE, a base station, a relay node, a centralized unit (CU) of the base station, and a distribution unit (DU) of the base station.

[0233] A computer-readable storage medium storing instructions is provided in the present embodiment of the present disclosure, the instructions when executed by at least one processor, causes the at least one processor to perform the method performed by the first node in the wireless communication system in the exemplary embodiments as described above.

[0234] A computer program product including computer programs is also provided in an embodiment of the present disclosure, the computer programs, when executed by a processor, may implement the steps and corresponding content of the aforementioned method embodiments.

[0235] The terms "first", "second", "third", "fourth", "1", "2" and the like (if exists) in the specification and claims of the present disclosure and the above drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequence. It should be understood that, terms used as such may be interchanged in appropriate situations, so that the embodiments of the present disclosure described here may be implemented in an order other than the illustration or text description.

[0236] It should be understood that, although each operation step is indicated by an arrow in the flowcharts of the embodiments of the present disclosure, an implementation order of these steps is not limited to an order indicated by the arrows. Unless explicitly stated herein, in some implementation scenarios of the embodiments of the present disclosure, the implementation steps in the flowcharts may be executed in other orders according to requirements. In addition, some or all of the steps in each flowchart may include a plurality of sub steps or stages, based on an actual implementation scenario. Some or all of these sub steps or stages may be executed at the same time, and each sub step or stage in these sub steps or stages may also be executed at different times. In scenarios with different execution times, an execution order of these sub steps or stages may be flexibly configured according to a requirement, which is not limited by the embodiment of the present disclosure.

[0237] The above text and accompanying drawings are provided as examples only to assist readers in understanding the present disclosure. They are not intended and should not be interpreted as limiting the scope of the present disclosure in any way. Although certain embodiments and examples have been provided, based on the content disclosed herein, it is apparent to those skilled in the art that, changes can be made to the illustrated embodiments and examples without departing from the scope of the present disclosure, and other similar implementation methods based on the technical concepts of the present disclosure also belongs to a protection scope of the embodiments of the present disclosure.

Claims

1.A method performed by a first node in a wireless communication system, characterized in that, the method comprises:demodulating first signals corresponding to received respective resource elements to obtain second signals corresponding to the respective resource elements and confidence of the second signals corresponding to the respective resource elements;selecting second signals corresponding to a first set of resource elements from among the second signals corresponding to the respective resource elements, according to the confidence of the second signals corresponding to the respective resource elements;determining channel state information corresponding to the first set of resource elements, according to the second signals corresponding to the first set of resource elements;determining channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements.2.The method of claim 1, characterized in that, the demodulating first signals corresponding to received respective resource elements to obtain the second signals corresponding to the respective received resource elements and the confidence of the second signals corresponding to the respective resource elements comprises:obtaining probability information corresponding to respective constellation points in a constellation diagram by demodulating the first signals corresponding to the respective resource elements, and determining a second signal corresponding to the resource element and confidence of the second signal corresponding to the resource element based on the probability information;and / or,obtaining probability information of respective bits corresponding to the first signal by demodulating the first signals corresponding to the respective resource elements, determining a constellation point corresponding to the first signal in the constellation diagram based on the probability information, obtaining a second signal corresponding to the resource element based on the constellation point corresponding to the first signal, and determining the confidence of the second signal corresponding to the resource element based on the probability information.3.The method of claim 2, characterized in that, the determining the confidence of the second signal corresponding to the resource element based on the probability information, comprises:using a negative number or an inverse function of entropy of the probability information as the confidence of the second signal corresponding to the resource element.4.The method of claim 1, characterized in that, the determining the channel state information corresponding to the first set of resource elements according to the second signals corresponding to the first set of resource elements comprises:for each resource element in the first set of resource elements, determining a second resource element associated with the resource element, and determining the channel state information corresponding to the resource element based on a second signal corresponding to the second resource element and the first signal corresponding to the second resource element.5.The method of claim 4, characterized in that, the second resource element associated with the resource element is at least one resource element adjacent to the resource element in the time domain and / or the frequency domain.6.The method of claim 4, characterized in that, the determining the second resource element associated with the resource element comprises:determining candidate second resource elements associated with the resource element;obtaining an eigenvalue of each matrix of a plurality of matrices composed of second signals corresponding to the candidate second resource elements, based on the plurality of matrices;determining a target eigenvalue based on the eigenvalue of each matrix, and determining the second resource element from among the candidate second resource elements based on the target eigenvalue.7.The method of claim 6, characterized in that the determining the candidate second resource elements associated with the resource element comprises:determining the candidate second resource elements associated with the resource element based on at least one of:an Euclidean distance from the resource element;confidence of the corresponding second signal.8.The method of claim 6, characterized in that, the determining the target eigenvalue based on the eigenvalues of each matrix and determining the second resource element from among the candidate second resource elements based on the target eigenvalue comprises:determining a minimum eigenvalue among the eigenvalues of each matrix;selecting a maximum eigenvalue from the minimum eigenvalues corresponding to respective matrixes, and using a resource element corresponding to the maximum eigenvalue as the second resource element.9.The method of claim 1, characterized in that, the determining channel state information corresponding to the respective resource elements based on the channel state information corresponding to the first set of resource elements comprises:eliminating abnormal channel state information among the channel state information corresponding to the first set of resource elements, wherein the abnormal channel state information is channel state information with amplitude exceeding a threshold;determining the channel state information corresponding to the respective resource elements, based on the channel state information corresponding to the first set of resource elements of which abnormal channel state information is eliminated.10.The method of claim 9, characterized in that, the method further comprises determining the threshold, wherein the determining the threshold comprises:selecting an amplitude at a predetermined proportional location from a ranking result of amplitudes of the channel state information corresponding to resource elements in the first set of resource elements, as the threshold.11.An electronic apparatus, characterized in that, which comprises:a transceiver for transmitting and receiving signals; anda processor coupled with the transceiver, and configured to perform the method performed by the first node in the wireless communication system according to any one of claims 1 to 10.12.A computer-readable storage medium storing instructions, characterized in that, the instructions, when performed by at least one processor, cause the at least one processor to perform the method performed by the first node in the wireless communication system according to any one of claims 1 to 10.

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