A communication method and apparatus

Abstract

A communication method and apparatus are disclosed. In this method, a sensing node obtains a second sensing spectrum by reducing the dimensionality of a first sensing spectrum; the sensing node then reports information corresponding to the second sensing spectrum to a fusion center node. For example, if the first sensing spectrum is a four-dimensional matrix, the second sensing spectrum can be a one-dimensional / two-dimensional / three-dimensional matrix by reducing the dimensionality of the first sensing spectrum. Compared to the above methods where the sensing node directly reports the four-dimensional sensing spectrum (i.e., the first sensing spectrum) to the fusion center node, the method of this application reduces the air interface overhead of the sensing node reporting the sensing spectrum.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a communication method and apparatus. Background Technology

[0002] In the fifth generation mobile communication system (the 5 th In the evolution from 5G (first generation, 5G) to 5G-advanced (5G-A) technology, integrated communication and sensing technology is considered one of the key technologies for expanding the service capabilities of mobile communication networks. The core idea of ​​this technology is to add sensing capabilities to the mobile communication network, building the ability to detect, track, and image targets, thereby integrating communication and sensing capabilities into a single network to achieve harmonious coexistence and even mutual benefit.

[0003] In scenarios involving multiple sensing nodes collaborating, each sensing node can perceive a target (or simply the target), obtain corresponding sensing results (such as a four-dimensional sensing spectrum), and report these results to the central fusion node. How sensing nodes report their sensing results to the central fusion node is a key research area. Summary of the Invention

[0004] This application provides a communication method and apparatus to reduce the air interface overhead of sensing nodes reporting sensing results (such as sensing spectra).

[0005] Firstly, a communication method is provided, applied to a sensing device. The sensing device can be a sensing node, a component applied to the sensing node (e.g., a communication module, processor, circuit, chip, or chip system), or a logic module or software capable of implementing all or part of the sensing node's functions. For example, the chip in the sensing node can be a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip. The method includes: determining a second sensing spectrum, obtained by fixing the value of at least one dimension of a first sensing spectrum, wherein the at least one dimension includes at least a velocity dimension; the first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional, two-dimensional, or three-dimensional matrix; and transmitting information from the second sensing spectrum.

[0006] Through the above design, the sensing device can reduce the dimensionality of the first sensing spectrum by fixing the value of at least one dimension of the first sensing spectrum to obtain the corresponding second sensing spectrum; the sensing device then reports the information corresponding to the second sensing spectrum to the fusion center device. For example, if the first sensing spectrum is a four-dimensional matrix, the second sensing spectrum obtained by reducing the dimensionality of the first sensing spectrum can be a one-dimensional / two-dimensional / three-dimensional matrix. Compared to the sensing device directly reporting a four-dimensional sensing spectrum (such as the first sensing spectrum) to the fusion center device, the method of this application can reduce the air interface overhead of the sensing device reporting the sensing spectrum.

[0007] In one possible design, the first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity, and the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle; wherein, the value of an element in the first or second sensing spectrum represents the intensity of the first target at the corresponding coordinates.

[0008] In one possible design, the fixed value corresponding to this velocity dimension is the first value.

[0009] Through the above design, the sensing device fixes the value of the first sensing spectrum in the velocity dimension to a first value to obtain the second sensing spectrum, thereby achieving dimensionality reduction of the first sensing spectrum. For example, if the first sensing spectrum is a four-dimensional matrix and the second sensing spectrum is a three-dimensional matrix, the overhead of the sensing device reporting the sensing spectrum is reduced.

[0010] In one possible design, the at least one dimension further includes at least one of the following: a distance dimension, a horizontal angle dimension, or a pitch angle dimension; wherein the fixed value corresponding to the distance dimension is a second value, the fixed value corresponding to the horizontal angle dimension is a third value, and the fixed value corresponding to the pitch angle dimension is a fourth value.

[0011] Through the above design, in addition to fixing the value of the first sensing spectrum in the velocity dimension to a first value, the sensing device can also fix the value of the first sensing spectrum in at least one of the following dimensions: distance dimension, horizontal angle dimension, or pitch angle dimension, thereby further reducing the air interface overhead of the sensing device reporting the sensing spectrum.

[0012] In one possible design, the method further includes: receiving first instruction information; and determining the fixed value based on the first instruction information.

[0013] In one possible design, the method further includes: sending a first point cloud set, which contains at least one point cloud, wherein one point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle, or velocity.

[0014] In one possible design, the first indication information is used to indicate at least one first point cloud, which belongs to the set of first point clouds.

[0015] Through the above design, the first point cloud can be a successfully clustered point cloud, or a point cloud contained within a successfully clustered class. The sensing device reduces the dimensionality of the first sensing spectrum based on the first point cloud and reports the corresponding second sensing spectrum. In scenarios with multi-sensor node collaboration, the fusion center device can merge, fuse, or overlay the second sensing spectra reported by each sensing device. Since the corresponding second sensing spectra reported by each sensing device are all for a successfully clustered class of point clouds, i.e., for the same scattering center, the fusion center device can merge the second sensing spectra of the same scattering center and determine the sensing result of the first target based on the merged second sensing spectrum, thereby improving the accuracy and precision of the sensing result, especially when the first target is an extended target.

[0016] In one possible design, the first point cloud satisfies at least one of the following: the first point cloud takes the first value in the velocity dimension;

[0017] The first point cloud takes the second value in the distance dimension; the first point cloud takes the third value in the horizontal angle dimension; or, the first point cloud takes the fourth value in the pitch angle dimension.

[0018] In one possible design, the method further includes: receiving second indication information, the second indication information being used to indicate a first condition; determining, in the point cloud of the first target, point clouds that satisfy the first condition; and the point clouds that satisfy the first condition forming the first point cloud set.

[0019] Through the above design, the fusion center device can send a first instruction information to the sensing device, which is used to instruct the sensing device to report the conditions that meet the first condition; the sensing device determines the point cloud that meets the first condition in the point cloud and reports the point cloud that meets the first condition; compared with the sensing device reporting all the point clouds, the air interface overhead of the sensing device reporting the point cloud can be reduced.

[0020] Secondly, a communication method is provided, which is applied to a fusion center device. The fusion center device can be a fusion center node, a component applied to the fusion center node (e.g., a communication module, processor, circuit, chip, or chip system), or a logic node, logic module, or software capable of implementing all or part of the functions of the fusion center node. The method includes: receiving information of at least one second sensing spectrum, which is obtained by determining the value of at least one dimension of a first sensing spectrum as a fixed value, the at least one dimension including at least a velocity dimension, the first sensing spectrum being a four-dimensional matrix, and the second sensing spectrum being a one-dimensional, two-dimensional, or three-dimensional matrix; and determining a first sensing result based on the at least one second sensing spectrum.

[0021] In one possible design, the at least one second sensing spectrum originates from at least one sensing device.

[0022] In one possible design, the first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity, and the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle; wherein, the value of an element in the first or second sensing spectrum represents the intensity of the first target at the corresponding coordinates.

[0023] In one possible design, the fixed value corresponding to this velocity dimension is the first value.

[0024] In one possible design, the at least one dimension further includes at least one of the following: a distance dimension, a horizontal angle dimension, or a pitch angle dimension; wherein the fixed value corresponding to the distance dimension is a second value, the fixed value corresponding to the horizontal angle dimension is a third value, and the fixed value corresponding to the pitch angle dimension is a fourth value.

[0025] In one possible design, there are multiple second sensing spectra, which are from multiple sensing devices. Determining the first sensing result based on the second sensing spectra includes: merging the multiple second sensing spectra to obtain a merged second sensing spectrum; and determining the first sensing result based on the merged second sensing spectrum.

[0026] In one possible design, it also includes sending first indication information, which is used at least to determine the fixed value.

[0027] In one possible design, the method further includes: receiving at least one first point cloud set, the first point cloud set containing at least one point cloud, wherein one point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle, or velocity; clustering the point clouds contained in the first point cloud set to determine at least one first point cloud belonging to the first point cloud set.

[0028] In one possible design, the at least one first point cloud set is from at least one sensing device.

[0029] In one possible design, the first indication information is used to indicate the at least one first point cloud.

[0030] In one possible design, the first point cloud satisfies at least one of the following: the first point cloud takes the first value in the velocity dimension;

[0031] The first point cloud takes the second value in the distance dimension; the first point cloud takes the third value in the horizontal angle dimension; or, the first point cloud takes the fourth value in the pitch angle dimension.

[0032] In one possible design, the method further includes: sending a second indication message, which indicates a first condition for reporting point clouds, and point clouds that satisfy the first condition constitute the first point cloud set.

[0033] The second aspect and its potential beneficial effects can be found in the explanation of the first aspect, and will not be repeated here.

[0034] Thirdly, an apparatus is provided that can implement the method of the first aspect described above. For example, the apparatus includes a module, unit, or component that performs the method described in the first aspect. The module, unit, or component can be implemented in hardware, software, or a combination of hardware and software.

[0035] In one design, the device includes a unit that performs the method described in the first aspect.

[0036] In one design, the device includes a processor for implementing the method of the first aspect described above. Optionally, the device further includes a memory, with the processor coupled to the memory, the processor executing a computer program or instructions stored in the memory, such that the device implements the method of the first aspect described above.

[0037] In one design, the device includes a processor and an interface circuit, the interface circuit being used to receive signals from other devices outside the device and transmit them to the processor or to send signals from the processor to other devices outside the device, the processor being used to implement the method of the first aspect described above through logic circuits or executing code instructions.

[0038] In one design, the device may be the first device, or a module, unit, or component (e.g., a chip, chip system, circuit, or processor, etc.) that corresponds one-to-one with the first device to perform the methods / operations / steps / actions described in the first aspect, or a device that can be used in conjunction with the first device.

[0039] Fourthly, an apparatus is provided capable of implementing the method of the second aspect described above. For example, the apparatus includes a module, unit, or component corresponding to the execution of the method described in the second aspect. Specifically, the module, unit, or component may be implemented in hardware, software, or a combination of hardware and software.

[0040] In one design, the device includes a unit that performs the method described in the second aspect.

[0041] In one design, the device includes a processor for implementing the method of the second aspect described above. Optionally, the device further includes a memory, with the processor coupled to the memory, the processor executing computer programs or instructions stored in the memory, such that the device implements the method of the second aspect described above.

[0042] In one design, the device includes a processor and an interface circuit. The interface circuit is used to receive signals from other devices outside the device and transmit them to the processor, or to send signals from the processor to other devices outside the device. The processor implements the method of the second aspect described above through logic circuits or executing code instructions.

[0043] In one design, the device can be a second device, or a module, unit, or component (e.g., a chip, chip system, circuit, or processor, etc.) that corresponds one-to-one with the method / operation / step / action described in the second aspect in the second device, or a device that can be used in conjunction with the second device.

[0044] Fifthly, a computer-readable storage medium is provided, storing a computer program or instructions that, when executed on a computer, cause the computer to implement the methods of the first or second aspect described above.

[0045] Sixthly, a computer program product is provided, comprising a computer program or instructions that, when executed by a computer, cause the methods described in the first or second aspect to be performed.

[0046] A seventh aspect provides a chip including a processor for implementing the methods of the first or second aspect described above. Optionally, the chip further includes a memory, the processor being coupled to the memory, the processor executing computer programs or instructions stored in the memory, causing the chip to implement the methods of the first or second aspect described above.

[0047] Eighthly, a communication system is provided, comprising: a first communication device and a second communication device; wherein the first communication device is used to implement the method of the first aspect; and the second communication device is used to implement the method of the second aspect. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the communication system provided in an embodiment of this application;

[0049] Figure 2 This is a schematic diagram of the ORAN system provided in an embodiment of this application;

[0050] Figure 3 This is a schematic diagram of the network element function division and protocol layer structure of the O-RAN equipment provided in the embodiments of this application;

[0051] Figure 4a This is a schematic diagram of single-station sensing provided in an embodiment of this application;

[0052] Figure 4b This is a schematic diagram of dual-station sensing provided in an embodiment of this application;

[0053] Figure 5a This is another schematic diagram of the sensing mode provided in the embodiments of this application;

[0054] Figure 5b This is a schematic diagram of the integrated communication and sensing scenario provided in the embodiments of this application;

[0055] Figure 6 This is a schematic diagram of a communication method provided in an embodiment of this application;

[0056] Figure 7 This is yet another schematic diagram of the communication method provided in the embodiments of this application;

[0057] Figure 8 This is a schematic diagram of a specific method provided in an embodiment of this application;

[0058] Figure 9 This is a schematic diagram of the structure of the device provided in an embodiment of this application;

[0059] Figure 10 This is another structural schematic diagram of the device provided in the embodiments of this application. Detailed Implementation

[0060] To make the objectives, technical solutions and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings. The specific operation methods and functional descriptions in the method embodiments can also be applied to the device embodiments or system embodiments.

[0061] I. In the description of this application, unless otherwise specified, the number of nouns refers to "singular nouns or plural nouns," that is, "one or more." "At least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates that the related objects before and after are in an "or" relationship; in the formulas of this application, the character " / " indicates that the related objects before and after are in a "division" relationship. "Including at least one of A, B, or C" or similar expressions can mean: including A; including B; including C; including A and B; including A and C; including B and C; including A, B, and C, where A, B, and C can be singular or plural.

[0062] II. In the description of this application, the various numerical designations are for ease of description and are not intended to limit the scope of the embodiments of this application. The order of the process numbers does not imply the order of execution; the execution order of each process should be determined by its function and internal logic. The ordinal numbers such as "first" and "second" used in the embodiments of this application are used to distinguish multiple objects and do not limit the size, order, timing, priority, or importance of the multiple objects.

[0063] III. In the description of this application, the numbering of steps in the various flowcharts is only for distinguishing different steps and is not intended to limit the order of steps. Furthermore, there is no limitation on the number of steps included in each flowchart; each flowchart may contain more or fewer steps than shown in the diagram, and multiple steps may be combined into one step, or one step may be broken down into multiple steps, etc. Related descriptions in different flowcharts can be referred to cross-referenced. The dashed arrows or boxes in the flowcharts indicate optional steps or optional modules.

[0064] IV. In this application, "sending information" can be understood as one device sending information to another device, or it can also be understood as one logical module within a device sending information to another logical module. For example, "sensing node sending information" can be understood as a sensing node sending information to another device (such as a central fusion node), or it can be understood as logical module 1 in a sensing node sending information to logical module 2 in a sensing node.

[0065] In this application, "receiving information" can be understood as one device receiving information from another device, or it can also be understood as a logical module within a device receiving information from another logical module. For example, "the fusion center node receiving information" can be understood as the fusion center node receiving information from another device (such as a sensing node), or it can be understood as logical module 1 in the fusion center node receiving information from logical module 2 in the fusion center node.

[0066] In this application, phrases such as "sending information to... (e.g., a fusion hub node)" or related illustrations in the accompanying drawings can be understood as indicating that the destination of the information is the fusion hub node. This can include sending information directly or indirectly to the fusion hub node. Similarly, phrases such as "receiving information from... (e.g., a fusion hub node)," "receiving information from... (e.g., a fusion hub node)," or "receiving information sent (e.g., by a fusion hub node)," or related illustrations in the accompanying drawings, can be understood as indicating that the source of the information is the fusion hub node. This can include receiving information directly or indirectly from the fusion hub node. Information may undergo necessary processing between the source and destination, such as format changes, but the destination node can understand the valid information from the source. Similar expressions in this application can be interpreted similarly and will not be elaborated further here.

[0067] V. In the description of this application, "for indicating" can include both direct indication (or explicit indication) and indirect indication (or implicit indication). For example, when describing a certain indication information for indicating information I, it can include whether the indication information directly indicates I or indirectly indicates I, but does not necessarily mean that the indication information carries I.

[0068] VI. In the description of this application, "when," "if," and "if" all refer to the device taking corresponding actions under certain objective circumstances, and are not time-limited, nor do they require the device to perform a judgment action, nor do they imply any other limitations. Unless otherwise specified, "if" and "if" are interchangeable, "when" is interchangeable with "in the case of," and "when" can also be replaced with "when," or "after," etc., and "when" can also be replaced with "if" / "if," etc. The words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0069] VII. In the description of this application, "preset," "predefined," or "preconfigured" can be implemented by pre-storing corresponding codes, tables, or other means that can be used to indicate relevant information in the device (e.g., including terminal devices and network devices), or it can be pre-defined in the protocol. This application does not limit the specific implementation method. "Stored" can mean stored in one or more memories. The one or more memories can be separate settings or integrated into the encoder or decoder, processor, or communication device. The one or more memories can also be partially separate settings and partially integrated into the decoder, processor, or communication device. The type of memory can be any form of storage medium, and this application does not limit this.

[0070] 8. In the description of this application: the terms “system” and “network” are used interchangeably, and “according to” and “based on” are used interchangeably. The terms “comprising,” “including,” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are expressly listed, but may include other steps or units that are not expressly listed or that are inherent to such process, method, product, or device.

[0071] 9. In the description of this application, words such as "exemplarily," "for example," and "e.g." are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as an "example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present concepts in a concrete manner. In the embodiments of this application, "of," "corresponding, relevant," and "corresponding" may sometimes be used interchangeably, and it should be noted that their intended meanings are consistent unless their distinction is emphasized.

[0072] 10. The embodiments of this application will be presented in the context of a system including multiple devices, components, modules, etc. It should be understood that the system may include other unmentioned devices, components, modules, etc., or may only include some of the devices, components, or modules mentioned in the embodiments. Optionally, the terms "component" and "part" in this application can be used interchangeably.

[0073] XI. In the description of this application, "storage" or "preservation" may refer to storage in one or more memory devices. These memory devices may be separately configured or integrated into a processor or communication device. Alternatively, some memory devices may be separately configured, while others may be integrated into the processor or communication device. The type of memory may be any form of storage medium, and this is not limited.

[0074] 12. The network architecture and business scenarios described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0075] Thirteen, the technical solutions of the embodiments of this application can be applied to various communication systems, such as integrated sensing and communication (ISAC), wireless local area network (WLAN), extended reality (XR) communication systems, short-range wireless communication systems (such as sidelink, wireless fidelity (Wi-Fi), Bluetooth, etc.), wired networks, vehicle to everything (V2X) communication systems, device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, 4th generation (4G) mobile communication systems (such as long term evolution (LTE) systems), LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, worldwide interoperability for microwave access (WiMAX) communication systems, and 5th generation (5G) mobile communication systems (such as new radio). No restrictions are imposed on radio (NR) systems, future communication systems, or other similar communication systems.

[0076] Figure 1 A possible, non-limiting system schematic diagram is shown. For example... Figure 1As shown, the communication system 1000 includes a radio access network (RAN) 100 and a core network (CN) 200. RAN 100 includes at least one RAN node (e.g., Figure 1 110a and 110b (collectively referred to as 110) and at least one terminal device (such as Figure 1 RAN100, denoted as RAN100, comprises RAN nodes 120a-120j, collectively referred to as RAN120. RAN100 may also include other RAN nodes, such as wireless relay equipment and / or wireless backhaul equipment. Figure 1 (Not shown in the image). Terminal device 120 is connected to RAN node 110 wirelessly. RAN node 110 is connected to core network 200 wirelessly or via wired connection. The core network equipment in core network 200 and RAN node 110 in RAN 100 can be different physical devices, or they can be the same physical device integrating core network logical functions and radio access network logical functions.

[0077] RAN100 can be a cellular system related to the 3rd Generation Partnership Project (3GPP), such as 4G, 5G mobile communication systems, or future-oriented evolution systems. RAN100 can also be an open RAN (O-RAN or ORAN), cloud RAN (CRAN), virtualized RAN (vRAN), artificial intelligence radio access network (AI RAN), or wireless fidelity (WiFi) system. RAN100 can also be a communication system that integrates two or more of the above systems.

[0078] RAN node 110, sometimes also referred to as access network equipment, RAN entity, or access node, constitutes part of the communication system and assists terminal equipment in achieving wireless access. Multiple RAN nodes 110 in the communication system 1000 can be of the same type or different types. In some scenarios, the roles of RAN node 110 and terminal equipment 120 are relative, for example... Figure 1 Network element 120i can be a helicopter or a drone, and it can be configured as a mobile base station. For terminal devices 120j that access RAN 100 through network element 120i, network element 120i is a base station; however, for base station 110a, network element 120i is a terminal device. RAN node 110 and terminal device 120 are sometimes referred to as communication devices, for example... Figure 1 Network elements 110a and 110b can be understood as communication devices with base station functions, while network elements 120a-120j can be understood as communication devices with terminal equipment functions.

[0079] In one possible scenario, a RAN node can be a base station, an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP), a next-generation NodeB (gNB), a base station in a future mobile communication system, or an access node in a WiFi system, etc. Figure 1 110a), micro base stations or indoor stations (such as Figure 1 The RAN node can be a relay node or donor node (as described in section 110b), a wireless controller in a CRAN scenario, a satellite, a drone, or a device that performs base station functions in device-to-device (D2D) and / or machine-to-machine (M2M) transmissions. Optionally, the RAN node can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, the access network equipment in vehicle-to-everything (V2X) technology can be a roadside unit (RSU). All or part of the functions of the RAN node in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (e.g., a cloud platform). The RAN node can also be equipped with communication modules, circuits, or chips that perform corresponding communication functions. The RAN node can also be configured with program instructions for performing corresponding communication functions and corresponding program instructions. The RAN node in this application may also be a logical node, logical module or software that can implement all or part of the access node functions, or a circuit or chip (such as a graphics processing unit (GPU), artificial intelligence (AI) processor, or application specific integrated circuit (ASIC)) in the access node that is responsible for communication and / or computing functions.

[0080] In another possible scenario, multiple RAN nodes collaborate to assist terminal devices in achieving wireless access, with different RAN nodes each implementing a portion of the base station's functions. For example, RAN nodes can be central units (CUs), distributed units (DUs), CU-control plane (CPs), CU-user plane (UPs), or radio units (RUs), etc. CUs and DUs can be set up separately or included in the same network element, such as a baseband unit (BBU). RUs can be included in radio frequency equipment or radio frequency units, such as remote radio units (RRUs), active antenna units (AAUs), or remote radio heads (RRHs).

[0081] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. For ease of description, this application uses CU, CU-CP, CU-UP, DU, and RU as examples. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.

[0082] A terminal device can be a device or module that connects to the aforementioned communication system and has corresponding communication functions. Terminal devices can also be called terminals, user equipment (UE), mobile stations, mobile terminal devices, etc. Terminal devices can be widely used in various scenarios, such as D2D, vehicle-to-everything (V2X) communication, machine-type communication (MTC), Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, smart cities, etc. Terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, drones, helicopters, airplanes, ships, robots, robotic arms, smart home devices, transportation vehicles with wireless communication capabilities, communication modules, etc. The embodiments of this application do not limit the device form of the terminal device. Terminal devices typically contain communication modules, circuits, or chips that perform corresponding communication functions. Furthermore, they can also contain modules, circuits, or chips (such as GPUs, AI processors, or ASICs) that perform corresponding communication and / or computing functions. The terminal device may also be configured with program instructions for performing corresponding communication and / or computing functions.

[0083] It is understood that RAN nodes are used to help terminal devices achieve wireless access, and they can also be referred to in other different ways, such as RAN entity, ORAN device, access node, access network device, etc. In the following description of the embodiments of this application, unless otherwise specified, the node or device that helps the terminal device achieve wireless access will be described as "access network device".

[0084] The core network 300 includes one or more network elements, such as user plane function (UPF) network elements, access and mobility management function (AMF) network elements, and sensing function (SF) network elements. Terminal equipment, access network equipment, and UPF network elements are generally referred to as user plane functions and entities. User data flows can be transmitted through the user plane channel established between the terminal equipment and the UPF network element. Other network elements in the core network 300, such as AMF and SF network elements, can be referred to as control plane functions and entities. They are mainly responsible for authentication and authorization, registration management, session management, mobility management, and policy control functions, thereby achieving reliable and stable transmission of user plane data flows. The SF network element mainly implements the sensing function. Furthermore, in scenarios where the control plane and user plane are separated, the network elements corresponding to the control plane can be called sensing control function (SCF) network elements, and the network elements corresponding to the user plane can be called sensing processing function (SPF) network elements, etc. In this application, the names of network elements such as UPF, AMF, and SF are not limited. For example, as the network develops and evolves, these network elements may be referred to by other names. In the description of this application, the names of various network elements are mainly described using a 5G communication system as an example.

[0085] It is understood that terminal equipment, access network equipment, and core network elements are sometimes referred to as communication devices. For example, terminal equipment can be understood as a communication device with terminal equipment functions, access network equipment can be understood as a communication device with access network equipment functions, and core network elements (such as SF network elements) can be understood as communication devices with core network functions. In the method of this application, the functions of access network equipment can also be performed by modules, units, or components (such as chips) within the access network equipment, or by a control subsystem containing access network equipment functions. This control subsystem containing access network equipment functions can be a control center in the aforementioned application scenarios such as smart grids, industrial control, intelligent transportation, and smart cities. The functions of terminal equipment can also be performed by modules, units, or components (such as chips or modems) within the terminal equipment, or by devices containing terminal equipment functions. The functions of core network elements can also be performed by modules, units, or components within the core network elements.

[0086] Figure 2 A schematic diagram of a possible, non-limiting ORAN system is shown. (e.g.) Figure 2As shown, the ORAN system includes: core network equipment, access network equipment, and terminal equipment. The access network equipment communicates with the core network equipment via a backhaul link and with the terminal equipment via an air interface.

[0087] The access network equipment includes BBUs and RUs. A BBU communicates with at least one RU via a fronthaul link. The BBU and RU may or may not be co-located. Specifically, the BBU communicates with core network equipment via a backhaul link, and the RU communicates with terminal equipment via an air interface. A BBU includes at least one CU and at least one DU, which can communicate via at least one midhaul link.

[0088] Figure 3 A schematic diagram of a possible, non-limiting O-RAN device's network element function division and protocol layer structure is shown.

[0089] In this context, O-RAN equipment can be understood as access network equipment using the O-RAN architecture, used to enable wireless access for terminal devices. It is understood that communication between O-RAN equipment and terminal devices follows a specific protocol layer structure. This protocol layer structure can include a control plane protocol layer structure and a user plane protocol layer structure. For example, the control plane protocol layer structure can include the functions of protocol layers such as Radio Resource Control (RRC), Packet Data Convergence Protocol (PDCP), Radio Link Control (RLC), Media Access Control (MAC), and the physical layer. Similarly, the user plane protocol layer structure can include the functions of protocol layers such as PDCP, RLC, MAC, and the physical layer. In one possible implementation, a Service Data Adaptation Protocol (SDAP) layer can be added above the PDCP layer.

[0090] like Figure 3As shown, the O-RAN equipment includes logical nodes such as CU, DU, and RU. The CU can connect to the core network via an interface, for example, an E2 interface. Optionally, the CU can have some core network functions. The CU can control at least one DU, and the CU can connect to the DU via an interface, for example, an F1 interface. Further, the control plane (CP) interface can be called F1-C, and the user plane (UP) interface can be called F1-U. The DU can control at least one RU, and the DU can connect to the RU via an interface, for example, a fronthaul interface.

[0091] 1. CU

[0092] A CU can be a logical node that carries the RRC layer, SDAP layer, PDCP layer, and other control functions. In other words, a CU can implement the functions of the RRC layer, SDAP layer, PDCP layer, and certain control functions.

[0093] Furthermore, CU can be broken down into CU-CP and CU-UP. (See reference...) Figure 3 The CU-CP is a logical node that carries the control plane (control plane part of PDCP, PDCP-C) of the RRC and PDCP layers, and is used to implement the control plane functions of the CU. The CU-CP can interact with network elements in the core network used to implement control plane functions. These network elements in the core network can be access and mobility function network elements, such as the access and mobility management function (AMF) in a 5G communication system. (Continue to refer to...) Figure 3 The CU-UP is a logical node that carries the data plane (user plane part of PDCP, PDCP-U) layer of the SDAP and PDCP layers, and is used to implement the user plane functions of the CU. The CU-UP can interact with network elements in the core network used to implement user plane functions, such as the user plane function (UPF) in a 5G communication system.

[0094] 2. DU

[0095] A DU can be a logical node that carries the RLC layer, MAC layer, higher physical layer (Higher PHY) layer, and other functions. For example, the higher physical layer may include some of the processing functions of the PHY layer, such as forward error correction (FEC) encoding and decoding, scrambling, modulation, and demodulation. In other words, a DU can implement the functions of the RLC layer, MAC layer, higher physical layer, and other functions.

[0096] It is understood that the above CU and DU configurations are merely examples, and the functions of the CU and DU can be configured as needed. For instance, the CU or DU can be configured to have more protocol layer functions, or it can be configured to have only some protocol layer processing functions. For example, some functions of the RLC layer and the protocol layer functions above the RLC layer can be placed in the CU, while the remaining functions of the RLC layer and the protocol layer functions below the RLC layer can be placed in the DU. Furthermore, the functions of the CU or DU can be divided according to service type or other system requirements, such as by latency, placing functions that need to meet low latency requirements in the DU and functions that do not need to meet such latency requirements in the CU.

[0097] 3. RU

[0098] An RU can be a logical node that carries both lower physical layer (PHY) and radio frequency (RF) chain processing. For example, the lower physical layer includes some of the processing functions of the physical layer, such as fast Fourier transform (FFT), inverse fast Fourier transform (IFFT), digital beamforming, and filtering. In other words, an RU can implement both physical layer and RF functions.

[0099] In one possible implementation, the RU can be a 3GPP transmission reception point (TRP), a remote radio head (RRH), or other similar entity. The RU communicates with one or more terminal devices via a wireless link.

[0100] DU and RU can be co-located or not, without restriction. (See reference...) Figure 3The interaction between the DU and RU can include the O-RAN control user and synchronization (CUS-Plane) and the O-RAN management plane (M-Plane). The O-RAN CUS plane can be simply referred to as the CUS plane, and the O-RAN management plane as the management plane. Further, the CUS plane can be divided into a control plane (C-Plane) and a user plane (U-Plane). Optionally, the control plane refers to the real-time control plane between the DU and RU. The management plane refers to the non-real-time management operations between the DU and RU.

[0101] Reference Figure 3 The DU and RU exchange control plane and user plane information via the lower-layer split-control, user, and synchronization (LLS-CUS) interface through the fronthaul link. Furthermore, the LLS-CUS interface may include an LLS-C interface corresponding to the control plane and an LLS-U interface corresponding to the user plane. The DU and RU exchange management plane information through the LLS-M interface of the fronthaul link. (See reference...) Figure 3 It can also be connected to an external management system via the LLS-M interface.

[0102] It is understandable that DUs and RUs can cooperate to implement physical layer functions. A DU can be connected to one or more RUs. The functions of DUs and RUs can be configured in various ways depending on the design. For example, a DU can be configured to implement baseband functions, and an RU can be configured to implement mid-RF functions. Another example is that a DU can be configured to implement higher-level functions in the physical layer, and an RU can be configured to implement lower-level functions in the physical layer, or to implement both lower-level and RF functions. Higher-level functions in the physical layer may include a portion of the physical layer's functions that are closer to the MAC layer, while lower-level functions may include another portion of the physical layer's functions that are closer to the mid-RF side.

[0103] For ease of description, some communication terms, technical principles, and concepts involved in this application are explained. It is understood that this explanation is for understanding the methods of this application and is not intended to limit the embodiments of this application.

[0104] 1. The technical principles of perception.

[0105] In the field of sensing, sensing nodes can transmit radio waves in a specific direction; these radio waves can also be called sensing signals. When the radio waves illuminate or reach the surface of a target (such as a sensing target, or simply the target), they generate reflected radio waves, which can also be called echo signals. The receiving end receives the reflected radio waves and processes them to obtain the corresponding sensing results. These sensing results can include different levels of sensing outcomes. If the sensing results are classified, they can include at least one of the following:

[0106] Preliminary sensing data: This can be a four-dimensional sensing spectrum, which can be a four-dimensional matrix containing the following four dimensions: range, horizontal angle, pitch angle, or velocity. For example, this four-dimensional sensing spectrum could be a range-horizontal angle-pitch angle-velocity spectrum. For instance, sensing nodes can obtain initial sensing data by processing echo signals.

[0107] Perceiving intermediate data: This can refer to point clouds, such as perceiving nodes, which can extract corresponding point clouds from the initial perceiving data.

[0108] Perception result: This refers to the final perception result, which may include at least one of the following: information such as the type, location, angle, or velocity of the perceived target. For example, a perception node or fusion center node can obtain the final perception result by processing preliminary perception data (such as a four-dimensional perception spectrum) or intermediate perception data (such as point clouds).

[0109] 2. Perception Mode

[0110] In one example, sensing can generally be categorized into two modes: single-station sensing and dual-station sensing. Single-station sensing refers to a situation where the transmitting and receiving ends of the sensing signal are the same device. From the signal transmission flow perspective, this sensing node both transmits and receives the signals reflected from the target surface (i.e., echo signals). Therefore, single-station sensing mode is also called self-transmitting and self-receiving mode. Figure 4a As shown, an access network device (such as a base station) sends a sensing signal. This sensing signal reaches the target and is reflected by the target to form a corresponding echo signal. The access network device can also receive this echo signal. The access network device can process the echo signal to obtain the corresponding sensing result. Optionally, the access network device can also implement communication functions, such as communicating with terminal devices.

[0111] Dual-station sensing refers to a system where the transmitting and receiving ends of the sensing signal are two different devices. In terms of the sensing signal flow, sensing node A transmits the sensing signal, and the signal reflected from the target surface (i.e., the echo signal) is received by sensing node B. Therefore, dual-station sensing mode is also called A-transmit B-receive mode. Figure 4bAs shown, access network device A (such as base station A) sends a sensing signal, which reaches the target and is reflected by the target to form a corresponding echo signal. Access network device B (such as base station B) receives the echo signal. Access network device B can obtain the corresponding sensing result by processing the echo signal. Optionally, access network device A or access network device B can also implement communication functions, such as access network device A communicating with terminal devices.

[0112] The method provided in this application can be applied to either a single-site sensing mode or a dual-site sensing mode. In the single-site sensing mode, the "sensing node" in the method of this application embodiment can be an access network device (e.g., Figure 1 (The access network device shown). In the dual-site sensing mode, the "sensing node" in the method provided in this application may include access network device A and access network device B (e.g., Figure 1 Access network device A and access network device B are shown.

[0113] In another example: the method provided in this application can be applied to multiple sensing modes. For example... Figure 5a The diagram shows several possible sensing modes: Sensing mode (1) is the mode where the access network device transmits and receives signals independently; sensing mode (2) is the mode where the terminal device transmits and receives signals independently; sensing mode (3) is the mode where access network device A transmits and access network device B receives signals; sensing mode (4) is the mode where terminal device A transmits and terminal device B receives signals; sensing mode (5) is the mode where access network device transmits and terminal device receives signals; and sensing mode (6) is the mode where terminal device transmits and access network device receives signals. Here, "transmit" can be understood as "sending sensing signals," and "receive" can be understood as "receiving echo signals." The sensing target is a "vehicle."

[0114] The method provided in this application can be applied to any of the aforementioned sensing modes. The "sensing node" in the method provided in this application can be... Figure 5a The corresponding devices in any of the sensing modes shown, such as the access network device in sensing mode (1), the terminal device in sensing mode (2), access network device A and access network device B in sensing mode (3), terminal device A and terminal device B in sensing mode (4), and the access network device and terminal device in sensing mode (5) or sensing mode (6). Of course, the method provided in the embodiments of this application can also be applied to other than Figure 5a This application does not restrict other perception modes besides the one shown.

[0115] 3. Integrated communication and sensing scenarios.

[0116] The application scenarios of this application include, but are not limited to, integrated communication and sensing scenarios. The core idea of ​​integrated communication and sensing technology is to add sensing functionality to mobile communication networks. Besides traditional communication functions, it can also achieve target sensing, thus integrating communication and sensing capabilities onto a single network. The technical principles of sensing differ somewhat from those of communication. In communication, the transmitting end modulates information onto radio waves and sends it to the receiving end, which then demodulates the signal to obtain the information. In sensing, the transmitting end sends a sensing signal in a specific direction. When the sensing signal reaches the surface of the target, it forms an echo signal. The receiving end processes the echo signal to obtain the corresponding sensing result.

[0117] Figure 5b This diagram illustrates a possible, non-limiting scenario of integrated communication and sensing, where access network devices and terminal devices in a communication network can simultaneously communicate and sense targets. For example... Figure 5b As shown, while communicating with terminal device 1, terminal device 2, or terminal device 3, the access network device can also perceive targets such as drones, vehicles, and pedestrians. When the method of this application is applied... Figure 5b In the scenario shown, the sensing node in the method of this application can be an access network device.

[0118] 4. Perceptual spectrum

[0119] This application relates to the concepts of "first sensing spectrum" and "second sensing spectrum." For example, the first sensing spectrum can refer to the initial sensing spectrum, such as a four-dimensional sensing spectrum. The second sensing spectrum can refer to the sensing spectrum obtained after dimensionality reduction of the first sensing spectrum; for example, the second sensing spectrum can refer to a three-dimensional / two-dimensional / one-dimensional sensing spectrum. For example, the first sensing spectrum can be a four-dimensional matrix, specifically a distance-horizontal angle-pitch angle-velocity spectrum. For example, the first sensing spectrum can be represented as (R, θ, φ, v). The second sensing spectrum can be a three-dimensional matrix, and the second sensing spectrum is a distance-horizontal angle-pitch angle spectrum with a fixed velocity; the second sensing spectrum can be represented as (R, θ, φ, v). i ).

[0120] In one possible implementation, a sensing node (such as a base station) transmits a sensing signal. This sensing signal reaches the surface of a sensing target (such as a first target) and forms an echo signal through reflection. The sensing node receives and processes the echo signal to obtain a first sensing spectrum. A second sensing spectrum is obtained by processing the first sensing spectrum, such as through dimensionality reduction. This dimensionality reduction may include determining at least one dimension of the first sensing spectrum as a fixed value, for example, determining at least one of the following dimensions of the first sensing spectrum as a fixed value: distance dimension, horizontal angle dimension, pitch angle dimension, or velocity dimension. Of course, in the following description of this application, the example of determining at least the velocity dimension of the first sensing spectrum as a fixed value is used; there is no limitation on whether other dimensions of the first sensing spectrum are determined as fixed values.

[0121] 5. Point Clouds

[0122] A point cloud is a spatial dataset that can represent a sensing target. Optionally, a point cloud can also be called point cloud data. For example, a point cloud contains numerical values ​​corresponding to the sensing target in at least one of the following dimensions: distance, horizontal angle, pitch angle, or velocity. For instance, distance can be represented by the coordinates of the sensing target. Furthermore, the position of each point in the point cloud can be described by a set of Cartesian coordinates. For example, the horizontal angle refers to the angle between a direction in the horizontal plane and a reference direction (such as the X-axis of the coordinate system), used to describe the azimuth angle of the sensing target in the horizontal direction. The pitch angle refers to the angle between a direction in the vertical plane and the horizontal plane, used to describe the height angle of the sensing target. Velocity is used to describe the speed of the sensing target; for example, velocity may include information such as the Doppler value, velocity value, or phase change of the sensing target.

[0123] In one possible implementation, the sensing node can receive echo signals and, by analyzing the echo signals, obtain the corresponding sensing spectrum (such as a first sensing spectrum). The sensing node can then determine the corresponding point cloud (such as a first point cloud) based on the sensing spectrum (such as the first sensing spectrum). For example, it can extract the corresponding point cloud from the sensing spectrum.

[0124] 6. First objective

[0125] The first target can also be referred to as: the sensing target, the sensing object, the sensing point, the unit point, the reflection point, or the scattering point, etc. It can be understood that the sensing target can be simply referred to as the target. For ease of distinction, in this embodiment, the target to be sensed is referred to as the first target. The first target can be a static object, such as an environmental object like a building. Alternatively, the first target can be a dynamic object, such as a drone or a car; this application does not impose any limitations on this.

[0126] 7. Sensing signals

[0127] The sensing signal is the signal used for sensing; it can be understood as the radio wave signal transmitted by the sensing node. The sensing signal can be a reference signal, such as a channel state information-reference signal (CSI-RS) or a sounding reference signal (SRS). For example, the sensing node can pre-acquire information such as the initial amplitude and / or phase of the sensing signal (reference signal). The sensing node can determine the sensing result by comparing the initial amplitude and / or phase information of the sensing signal and the echo signal. Alternatively, the sensing signal can be a data signal; the sensing node can calculate and acquire the initial amplitude and / or phase information of the data signal. The sensing node can then determine the sensing result by comparing the initial amplitude and / or phase information of the data signal and the echo signal.

[0128] In one possible method, a sensing node can send a sensing signal, which reaches the target and forms an echo signal. The sensing node processes this echo signal to obtain the corresponding sensing result. For example, the sensing result can refer to preliminary sensing data, such as a four-dimensional sensing spectrum (referred to as the first sensing spectrum in the method of this application). In a multi-node collaborative sensing scenario, multiple sensing nodes collaborate to sense the same target. Each sensing node reports its sensing result (i.e., the corresponding four-dimensional sensing spectrum) to a fusion center node. The fusion center node merges or fuses the four-dimensional sensing spectra reported by each sensing node to obtain the final sensing result, such as information about the type, position, angle, or velocity of the first target. Due to the large amount of data in the four-dimensional sensing spectrum, the air interface overhead of the sensing node directly reporting the four-dimensional sensing spectrum to the fusion center node is significant. How to reduce the overhead of the sensing node reporting the sensing spectrum is the technical problem to be solved in the embodiments of this application.

[0129] In view of the above, this application provides a communication method and apparatus. In this method, a sensing node can obtain a second sensing spectrum by reducing the dimensionality of a first sensing spectrum; the sensing node reports the information corresponding to the second sensing spectrum to a fusion center node. For example, if the first sensing spectrum is a four-dimensional matrix, the second sensing spectrum can be a one-dimensional / two-dimensional / three-dimensional matrix by reducing the dimensionality of the first sensing spectrum. Compared with the above method where the sensing node directly reports the four-dimensional sensing spectrum (i.e., the first sensing spectrum) to the fusion center node, the method of this application can reduce the air interface overhead of the sensing node reporting the sensing spectrum. It should be noted that the first sensing spectrum contains four dimensions, which include: distance dimension, horizontal angle dimension, pitch angle dimension, or velocity dimension. The sensing node can reduce the dimensionality of the first sensing spectrum by determining at least one dimension of the first sensing spectrum as a fixed value. That is, the sensing node can determine at least one of the following dimensions contained in the first sensing spectrum: distance dimension, horizontal angle dimension, pitch angle dimension, or velocity dimension as a fixed value to obtain the second sensing spectrum. In the following description of this application, the example of determining the value of at least the velocity dimension of the first sensing spectrum as a fixed value is used. Of course, in addition to setting the velocity dimension of the first sensing spectrum to a fixed value, other dimensions of the first sensing spectrum (such as at least one of the distance dimension, horizontal angle dimension, or pitch angle dimension) can also be set to fixed values.

[0130] The communication method and apparatus of this application will be further described below with reference to the accompanying drawings. It is understood that this application mainly uses a sensing node and a fusion center node as the interactive execution entities for illustration, but this application does not limit the specific execution entities. For example, the method executed by the sensing node in this application can also be implemented by a module (e.g., a circuit, chip, or chip system) in the sensing node, or a logic node, logic module, or software that can implement all or part of the functions of the sensing node, or a circuit or chip (e.g., a GPU, AI processor, or ASIC) in the sensing node responsible for communication and / or computing functions. Similarly, the method executed by the fusion center node in this application can also be implemented by a module (e.g., a circuit, chip, or chip system) in the fusion center node, or a logic node, logic module, or software that can implement all or part of the functions of the fusion center node, or a circuit or chip in the fusion center node responsible for communication and / or computing functions. For example, in the following description, the sensing node can also be replaced by a sensing device, and the fusion center node can also be replaced by a fusion center device.

[0131] like Figure 6 The diagram shows a flowchart of a communication method, including:

[0132] Step 610: The sensing node determines the second sensing spectrum.

[0133] The second perceptual spectrum is obtained by fixing the value of at least one dimension of the first perceptual spectrum. For example, the perceptual node determines or acquires the first perceptual spectrum. The specific process by which the perceptual node determines or acquires the first perceptual spectrum is not limited. The perceptual node determines the second perceptual spectrum based on the first perceptual spectrum. For example, the perceptual node performs dimensionality reduction on the first perceptual spectrum, fixing the value of at least one dimension of the first perceptual spectrum to a fixed value, thus obtaining the second perceptual spectrum.

[0134] For example, the aforementioned at least one dimension includes at least a velocity dimension. Optionally, the aforementioned at least one dimension also includes at least one of the following: a distance dimension, a horizontal angle dimension, or a pitch angle dimension. The first sensing spectrum includes the following four dimensions: a distance dimension, a horizontal angle dimension, a pitch angle dimension, or a velocity dimension. The first sensing spectrum is a four-dimensional matrix, such as a distance-horizontal angle-pitch angle-velocity spectrum. In the description of this application, "distance" can be replaced by "time delay," such as a distance dimension being replaced by a time delay dimension; "velocity" can be replaced by "Doppler," such as a velocity dimension being replaced by a Doppler dimension. The first sensing spectrum can also be alternatively described as a time delay-horizontal angle-pitch angle-Doppler spectrum.

[0135] In one possible implementation, the sensing node determines the velocity dimension in the first sensing spectrum to a fixed value (such as a first value) to obtain a second sensing spectrum. That is, at least one of the aforementioned dimensions includes the velocity dimension. The first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a three-dimensional matrix. For example, the second sensing spectrum may include the following three dimensions: distance dimension, horizontal angle dimension, and pitch angle dimension. The second sensing spectrum also includes the first value. For example, the first sensing spectrum may be represented as (R, θ, φ, V), where R represents the distance dimension, θ represents the horizontal angle dimension, φ represents the pitch angle dimension, and V represents the velocity dimension. In the embodiments of this application, the velocity dimension V in the first sensing spectrum is fixed to a first value (such as v). i The second perceptual spectrum is obtained, which can be represented as (R,θ,φ,v). i ).

[0136] Optionally, the first perceptual spectrum is a four-dimensional matrix, also known as the four-dimensional perceptual spectrum, or simply the four-dimensional spectrum. The second perceptual spectrum is a three-dimensional matrix, also known as the three-dimensional perceptual spectrum, or simply the three-dimensional spectrum. For example, a perceptual node can reduce the dimensionality of the four-dimensional perceptual spectrum (R,θ,φ,V) (i.e., the first perceptual spectrum) to obtain the three-dimensional perceptual spectrum (R,θ,φ,v). i (i.e., the second sensing spectrum). The sensing nodes report the aforementioned three-dimensional sensing spectrum to the fusion center node. Compared to directly reporting the four-dimensional sensing spectrum, this reduces the overhead of sensing nodes reporting the sensing spectrum.

[0137] In another possible implementation, the sensing node determines a fixed value (e.g., a first value) for the velocity dimension in the first sensing spectrum, and also determines a fixed value for any one of the following dimensions in the first sensing spectrum (e.g., distance dimension, horizontal angle dimension, or pitch angle dimension), thus obtaining a second sensing spectrum. That is, at least one of the aforementioned dimensions includes the velocity dimension and any one of the following dimensions (e.g., distance dimension, horizontal angle dimension, or pitch angle dimension). The first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a two-dimensional matrix. For example, the second sensing spectrum may contain two dimensions, which can be any two of the following: distance dimension, horizontal angle dimension, or pitch angle dimension. The second sensing spectrum also contains two values: a first value and a fixed value for one of the dimensions other than the velocity dimension. For example, the fixed value corresponding to the distance dimension is the second value, the fixed value corresponding to the horizontal angle dimension is the third value, and the fixed value corresponding to the pitch angle dimension is the fourth value.

[0138] For example, a sensing node can fix the velocity and distance dimensions in the first sensing spectrum to obtain a second sensing spectrum. For instance, in the first sensing spectrum, the velocity dimension is fixed (first value), and the distance dimension is fixed (second value). The second sensing spectrum is a two-dimensional matrix, containing horizontal and vertical angle dimensions. It can also contain the first and second values. For example, the first sensing spectrum can be represented as (R, θ, φ, V), and the sensing node fixes the distance dimension in the first sensing spectrum to the second value (R). i The velocity dimension is fixed at the first value (e.g., v). i The second perceptual spectrum is obtained, which can be represented as (Ri,θ,φ,v). i ).

[0139] For example, a sensing node can fix the velocity and horizontal angle dimensions in the first sensing spectrum to obtain a second sensing spectrum. For instance, the velocity dimension is fixed (e.g., the first value), and the horizontal angle dimension is fixed (e.g., the third value). The second sensing spectrum is a two-dimensional matrix containing a distance dimension and a pitch angle dimension. It also contains the first and third values. For example, the first sensing spectrum can be represented as (R, θ, φ, V), and the sensing node fixes the horizontal angle dimension in the first sensing spectrum to the third value (θ). i The velocity dimension is fixed at the first value (e.g., v). i The second perceptual spectrum is obtained, which can be represented as (R, θ). i ,φ,v i ).

[0140] For example, a sensing node can fix the velocity and pitch angle dimensions in the first sensing spectrum to obtain a second sensing spectrum. For instance, the velocity dimension is fixed (e.g., the first value), and the pitch angle dimension is fixed (e.g., the fourth value). The second sensing spectrum is a two-dimensional matrix containing a distance dimension and a horizontal angle dimension. It also contains the first and fourth values. For example, the first sensing spectrum can be represented as (R, θ, φ, V), and the sensing node fixes the pitch angle dimension in the first sensing spectrum to the fourth value (φ). i The velocity dimension is fixed at the first value (e.g., v). i The second perceptual spectrum is obtained, which can be represented as (R,θ,φ). i ,v i ).

[0141] In another possible implementation, the sensing node fixes the velocity dimension in the first sensing spectrum to a fixed value (such as a first value), and determines any two of the following dimensions in the first sensing spectrum (such as the distance dimension, horizontal angle dimension, or pitch angle dimension) to fixed values, thus obtaining a second sensing spectrum. That is, at least one of the above dimensions includes the velocity dimension and any two of the following dimensions (such as the distance dimension, horizontal angle dimension, or pitch angle dimension). The first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional matrix. For example, the second sensing spectrum may contain one dimension, which can be any one of the following dimensions: distance dimension, horizontal angle dimension, or pitch angle dimension.

[0142] For example, a sensing node sets the velocity, distance, and horizontal angle dimensions in the first sensing spectrum to fixed values, resulting in a second sensing spectrum. This second sensing spectrum includes the pitch angle dimension and also contains a second, third, and first value. Similarly, if a sensing node sets the velocity, distance, and pitch angle dimensions in the first sensing spectrum to fixed values, this second sensing spectrum also includes the horizontal angle dimension and further contains a second, fourth, and first value.

[0143] It is understood that, in the embodiments of this application, in addition to fixing the velocity dimension in the first sensing spectrum to a fixed value, the sensing node may optionally also fix any one of the following dimensions (distance dimension, horizontal angle dimension, or pitch angle dimension) in the first sensing spectrum to a fixed value. Optionally, the specific number of dimensions and / or which dimension the sensing node fixes in the first sensing spectrum can be predefined, such as those predefined by the protocol, or indicated to the sensing node by other nodes, such as those indicated to the sensing node by the fusion center node, etc., without limitation.

[0144] Optionally, the aforementioned fixed values, such as the first, second, third, or fourth value, can be predefined, such as those predefined in the protocol, or indicated to the sensing nodes by other nodes. For example, the fusion center node sends indication information to the sensing nodes, which is used to indicate the fixed value. Accordingly, the sensing nodes receive the first indication information; the sensing nodes determine the fixed value based on the first indication information.

[0145] As mentioned above, the first sensing spectrum is a four-dimensional matrix, containing the following four dimensions: distance, horizontal angle, pitch angle, and velocity. The second sensing spectrum is a one-dimensional, two-dimensional, or three-dimensional matrix, containing at least one of the following dimensions: distance, horizontal angle, or pitch angle. For example, if the second sensing spectrum is a one-dimensional matrix, it can contain any one of the following dimensions: distance, horizontal angle, or pitch angle. If the second sensing spectrum is a two-dimensional matrix, it can contain any two of the following dimensions: distance, horizontal angle, or pitch angle. If the second sensing spectrum is a three-dimensional matrix, it can contain three of the following dimensions: distance, horizontal angle, or pitch angle. The value of an element in the first or second sensing spectrum represents the intensity of the first target at the corresponding coordinates. The first target is the target sensed by the sensing node. For information about the first target, please refer to the explanation in the terminology or glossary (6) above. The intensity mentioned above can refer to: energy, power, or complex signal, etc. For example, the value of an element in the first or second sensing spectrum represents the energy, power, or complex signal of the first target at the corresponding coordinate. It can be understood that the energy or power of the first target at the corresponding coordinate can be obtained from the complex signal of the first target at that coordinate. For instance, calculating the amplitude of the complex signal of the first target at the corresponding coordinate yields the energy of the first target at that coordinate. Similarly, squaring the complex signal of the first target at the corresponding coordinate yields the power of the first target at that coordinate.

[0146] It should be noted that the "second sensing spectrum" in this application embodiment can be a one-dimensional matrix (or one-dimensional sensing spectrum or one-dimensional spectrum), a two-dimensional matrix (or two-dimensional sensing spectrum or two-dimensional spectrum), or a three-dimensional matrix (or three-dimensional sensing spectrum or three-dimensional spectrum). In one method, the sensing node does not report a four-dimensional sensing spectrum to the fusion center node, but reports a one-dimensional, two-dimensional, or three-dimensional sensing spectrum. For example, a three-dimensional sensing spectrum can be a distance-angle spectrum. It can be understood that the above angle can include horizontal angle and pitch angle, so the above distance-angle spectrum is a three-dimensional sensing spectrum. Another example is a one-dimensional sensing spectrum, which can be a time delay spread spectrum, a Doppler spectrum, or an angle spectrum, etc. It should be noted that the "second sensing spectrum" in this application embodiment is not the same as the "one-dimensional, two-dimensional, or three-dimensional sensing spectrum" in the above method. Since the method in this application embodiment obtains the second sensing spectrum by determining or fixing a certain dimension (such as the velocity dimension) of the first sensing spectrum to a certain value, the second sensing spectrum includes not only the information of each corresponding dimension, but also the information of the corresponding fixed numerical value. For example, if the velocity dimension in the first sensing spectrum (a four-dimensional sensing spectrum) in this application embodiment is fixed, then the "second sensing spectrum" in this application embodiment is a three-dimensional sensing spectrum, which includes three dimensions: distance, horizontal angle, and pitch angle, as well as the corresponding fixed value of the velocity dimension. For example, in this application embodiment: the first sensing spectrum can be represented as (R,θ,φ,V), and the second sensing spectrum can be represented as (R,θ,φ,v). i However, the distance-angle spectrum in the above method can be represented as (R,θ,φ). It can be seen that the second sensing spectrum in this embodiment is not the same as the three-dimensional sensing spectrum in the above method.

[0147] As described above, the sensing node can determine the first sensing spectrum. The sensing node then determines at least the velocity dimension of the first sensing spectrum to a fixed value, thus obtaining the second sensing spectrum. This application does not limit the process by which the sensing node determines the first sensing spectrum. The above process is illustrated below with reference to the following examples. It should be understood that the following examples are only for understanding the methods of the embodiments of this application and are not intended to limit the embodiments of this application.

[0148] For example, a sensing node sends a sensing signal, which can be a reference signal such as CSI-RS or SRS. This sensing signal reaches a first target (e.g., the sensing target itself) and, after reflection, forms an echo signal. The echo signal can also be called a reflected signal. The sensing node receives the echo signal and determines a first sensing spectrum based on it. This determination may involve the sensing node analyzing or processing the received echo signal to determine the initial amplitude and / or phase of the echo signal. The sensing node then compares the initial amplitude and / or phase of the echo signal with the initial amplitude and / or phase of the sensing signal to determine the first sensing spectrum.

[0149] The first sensing spectrum is understood to be the sensing spectrum of the first target (i.e., the sensing target). For example, the first sensing spectrum can be a range-horizontal-pitch-velocity spectrum. The first sensing spectrum is a four-dimensional matrix, with the four dimensions being: range, horizontal angle, pitch angle, or velocity. The value of each element in this four-dimensional matrix represents the intensity of the first target at the corresponding coordinates. Specifically, the distance mentioned above represents the distance between the first target and the sensing node (e.g., straight-line distance). The horizontal angle mentioned above represents the azimuth angle of the first target on the horizontal plane. The pitch angle mentioned above represents the azimuth angle of the first target in the vertical direction. The velocity mentioned above represents the velocity of the first target or Doppler shift, etc.

[0150] Since the overhead of directly reporting the first sensing spectrum by the sensing node is relatively large, in this embodiment of the application, the sensing node determines at least one dimension (such as the velocity dimension) in the first sensing spectrum as a fixed value (such as a first value) to obtain a second sensing spectrum. The second sensing spectrum can be a one-dimensional matrix, a two-dimensional matrix, or a three-dimensional matrix. Compared with the sensing node directly reporting the four-dimensional matrix corresponding to the first sensing spectrum, the air interface overhead of the sensing node reporting the sensing spectrum can be reduced.

[0151] In one possible implementation, taking the inclusion of velocity as an example, the sensing node determines / fixes the velocity dimension in the first sensing spectrum as a first value to obtain a second sensing spectrum. Optionally, this first value can be predefined, such as protocol-predefined, or indicated to the sensing node by other nodes (such as the fusion center node). For example, the fusion center node sends first indication information to the sensing node, which indicates a fixed value (such as the first value). The sensing node determines the first value based on the first indication information. Alternatively, the sensing node determines the first value through other means, such as determining a point cloud set containing at least one point cloud based on the first sensing spectrum. For example, the sensing node can extract at least one point cloud from the first sensing spectrum to form a point cloud set. A point cloud contains the numerical values ​​corresponding to the first target in at least one of the following dimensions: distance, horizontal angle, pitch angle, or velocity, etc. The distance can be represented by the coordinates of the first target. The horizontal angle can refer to the azimuth of arrival (AOA) of the first target. The pitch angle can refer to the zenith angle of arrival (ZOA) of the first target, etc. The velocity may include information such as the Doppler value, velocity value, or phase change of the first target. In this embodiment, the sensing node can determine a first value based on the velocity information of the first target contained in the point cloud. For example, if the velocity information of the first target contained in the point cloud is value Vi, then the sensing node determines / fixes the velocity dimension value in the first sensing spectrum as Vi (i.e., the first value). As can be seen from the above, in this embodiment, the fusion center node sends first indication information to the sensing node, which is used to determine a fixed value. The sensing node determining a fixed value (such as the first value) based on the first indication information is a possible and optional implementation method. Because in addition to the above method, the sensing node can also determine a fixed value (such as the first value) through other methods.

[0152] Step 620: The sensing node sends information from the second sensing spectrum. Correspondingly, the fusion center node receives information from the second sensing spectrum.

[0153] In one possible implementation, at least one sensing node may send information about the second sensing spectrum to the fusion center node according to steps 610 and 620 described above. That is, in this embodiment, the fusion center node can receive information about the second sensing spectrum from at least one sensing node, or the second sensing spectrum information received by the fusion center node is from at least one sensing node, or the fusion center node can receive information about at least one second sensing spectrum.

[0154] Optionally, step 630: The fusion center node determines the first sensing result based on information from at least one second sensing spectrum.

[0155] For example, there may be multiple second sensing spectra, which originate from multiple sensing nodes, with one sensing spectrum corresponding to one sensing node, such as one sensing node sending one sensing spectrum. The fusion center node merges the multiple sensing spectra sent by the multiple sensing nodes to obtain a merged second sensing spectrum; optionally, "merging" can also be replaced by terms such as "fusion" or "overlay," for example, the above merging may refer to linearly adding or linearly multiplying multiple sensing spectra. The fusion center node determines the first sensing result based on the merged second sensing spectrum. The first sensing result is the final sensing result of the first target. For example, the first sensing result includes at least one of the following: the type information of the first target, the position information of the first target, the angle information of the first target, or the velocity information of the first target, etc.

[0156] Taking two sensing nodes as an example: these two sensing nodes can be referred to as the first sensing node and the second sensing node, respectively. The first sensing node can send information of the second sensing spectrum (e.g., information of the second sensing spectrum A) to the fusion center node according to the methods described in steps 610 and 620 above. The second sensing node can send information of the second sensing spectrum (e.g., information of the second sensing spectrum B) to the fusion center node according to the methods described in steps 610 and 620 above. The fusion center node merges the information of the two second sensing spectra (i.e., the information of the second sensing spectrum A and the information of the second sensing spectrum B) to obtain a merged sensing spectrum; based on the merged sensing spectrum, the first sensing result is determined.

[0157] In the above design, the fusion center node merges multiple perception spectra from multiple perception nodes, and determines the perception result of the first target (i.e., the first perception result) based on the merged perception spectra, which can improve the accuracy or precision of the perception result.

[0158] Optionally, prior to step 610, the following may also be included:

[0159] Step 600a: The sensing node sends the first point cloud set; correspondingly, the fusion center node receives the first point cloud set.

[0160] The first point cloud set contains at least one point cloud, and a point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle or velocity.

[0161] Understandably, the fusion center node can receive at least one first point cloud set, which comes from at least one sensing node. For example, multiple sensing nodes can send first point cloud sets to the fusion center node. The number of first point cloud sets is multiple, and the number of sensing nodes is also multiple. Each sensing node sends its corresponding first point cloud set to the fusion center node, with a one-to-one correspondence between the sensing node and the first point cloud set. For example, consider two sensing nodes: the first sensing node sends a first point cloud set (let's call it first point cloud set A) to the fusion center node. The second sensing node sends a first point cloud set (let's call it first point cloud set B) to the fusion center node. In this case, the fusion center node receives two first point cloud sets, which come from two different sensing nodes.

[0162] In one possible implementation, the sensing node can proactively send a first set of point clouds to the fusion center node. For example, the sensing node determines a first sensing spectrum based on the received echo signal. Based on the first sensing spectrum, the sensing node determines at least one point cloud. For instance, the sensing node extracts at least one point cloud from the first sensing spectrum. These at least one point cloud constitute the first set of point clouds. The sensing node then sends the first set of point clouds to the fusion center node.

[0163] In another possible implementation, the sensing node can identify point clouds that satisfy a first condition within the point cloud of the first target. The sensing node sends these point clouds that satisfy the first condition to the fusion center node, forming a first point cloud set. The first condition can be predefined or indicated to the sensing node by other nodes. For example, the fusion center node sends second indication information; correspondingly, the sensing node receives the second indication information, which is used to indicate the first condition. The content of the first condition is not specifically limited. For example, the first condition can include at least one of the following: the type of point cloud reported by the sensing node, the geographical area of ​​the point cloud reported by the sensing node, or the range of the point cloud reported by the sensing node (e.g., the range includes at least one of the following: the location range of the reported point cloud, the angular range of the reported point cloud (e.g., horizontal angle and / or pitch angle), or the velocity range of the reported point cloud, etc.). For example, the type of point cloud reported by the sensing node included or indicated by the first condition can be: a point cloud reporting at least one of the following coordinates (position coordinates, horizontal angular coordinates, pitch angle coordinates, velocity coordinates, or confidence coordinates, etc.). The geographical area of ​​the point cloud reported by the sensing node included or indicated by the first condition can be: a point cloud collected in a certain geographical area (such as geographical area A), or a point cloud collected within a geographical area range (such as geographical area A to geographical area B), etc.

[0164] Step 600b: The fusion center node clusters the point clouds contained in the first point cloud set to determine at least one first point cloud, and at least one first point cloud belongs to the first point cloud set.

[0165] For example, the fusion center node clusters the point clouds contained in the first point cloud set to determine at least one class. For instance, the fusion center node can use a clustering algorithm to cluster the point clouds contained in the first point cloud set. For example, the clustering algorithm could be the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Each of the aforementioned at least one class contains at least one point cloud. For example, the aforementioned at least one class means that the fusion center node obtains a class by clustering the point clouds contained in the first point cloud set. This class contains at least one point cloud, which can be considered the first point cloud. For example, the first point cloud set reported by the sensing node contains 5 point clouds, with indices from 1 to 5. The fusion center node clusters the 5 point clouds reported by the sensing node to obtain a class containing point cloud 1 and point cloud 2. Point cloud 1 and point cloud 2 are specific examples of the "first point cloud" in this application embodiment. For example, the aforementioned "at least one category" may contain multiple categories, meaning the fusion center node obtains multiple categories by clustering the point clouds contained in the first point cloud set. Each of these multiple categories contains at least one point cloud. The fusion center node can select one category from the multiple categories that meets certain conditions. The at least one point cloud contained in this category that meets the conditions can be considered a specific example of the "first point cloud" in this embodiment.

[0166] Step 600c: The fusion center node sends the first instruction information; correspondingly, the sensing node receives the first instruction information.

[0167] The first indication information is used to indicate at least one first point cloud, which belongs to a set of first point clouds. The fusion center node can indicate at least one first point cloud to the sensing node in various ways, without limitation. In one possible implementation, the fusion center node can use a binary bitmap to indicate at least one first point cloud to the sensing node. The first indication information mentioned above can be binary bits. For example, the set of first point clouds reported by the sensing node to the fusion center node contains 5 point clouds, whose indices are 1 to 5. The fusion center node clusters the 5 point clouds in the first point cloud set to determine a class containing point cloud 1 and point cloud 2. In this example, point cloud 1 and point cloud 2 are specific examples of "first point clouds" in this embodiment. The fusion center node sends a binary bitmap (11000) to the sensing node, which is used to indicate point cloud 1 and point cloud 2.

[0168] Understandably, as explained above, the first indication information is used to determine a fixed value. The sensing node can determine a fixed value based on the first indication information, such as a first value, a second value, a third value, or a fourth value. Here, it is introduced that the first indication information is specifically used to indicate at least one first point cloud. The sensing node can determine a fixed value, such as a first value, a second value, a third value, or a fourth value, based on at least one first point cloud. For example, the first point cloud satisfies at least one of the following: the first point cloud has a first value in the velocity dimension; the first point cloud has a second value in the distance dimension; the first point cloud has a third value in the horizontal angle dimension; or, the first point cloud has a fourth value in the pitch angle dimension. Taking the process of determining the first value as an example: when the sensing node receives the first indication information, it can determine at least one first point cloud based on the first indication information. The sensing node can determine a first value based on at least one first point cloud. For example, if the first point cloud has a value of Vi in the velocity dimension, then the sensing node fixes the velocity dimension in the first sensing spectrum to Vi, obtaining a second sensing spectrum. The sensing node sends the second sensing spectrum to the fusion center node.

[0169] It should be noted that the number of first point clouds indicated by the fusion center node to the sensing node can be one or more, that is, the first indication information can indicate one or more first point clouds. If the first indication information indicates one first point cloud, the sensing node can directly obtain the value of the first point cloud in the velocity dimension, which is taken as the first value. The sensing node sends the value of the first sensing spectrum in the velocity dimension, fixed as the first value, to the fusion center node. Alternatively, if the first indication information indicates multiple first point clouds. Further, if the multiple first point clouds indicated by the first indication information have the same value in the velocity dimension, all being the first value, then the above method can be used for processing. Alternatively, if the multiple first point clouds indicated by the first indication information have different values ​​in the velocity dimension, the sensing node can report multiple corresponding second sensing spectra. Continuing with the example above, the first indication information is specifically a binary bitmap (11000), which is used to indicate point cloud 1 and point cloud 2. The value of point cloud 1 in the velocity dimension is (first value A). The sensing node can send the value of the first sensing spectrum in the velocity dimension, fixed as the first value A, to the fusion center node. Point cloud 2 has a velocity dimension value (first value B). The sensing node can fix the velocity dimension value of the first sensing spectrum as first data B and send it to the fusion center node. In this example, the sensing node sends two second sensing spectra to the fusion center node. One second sensing spectrum is obtained by fixing or determining the velocity dimension of the first sensing spectrum as the first value A; the other second sensing spectrum is obtained by fixing or determining the velocity dimension of the first sensing spectrum as the first value B. The above process describes in detail the process by which the sensing node determines the first value based on at least one first point cloud indicated by the first indication information. The principle is similar; the sensing node can also determine a second, third, or fourth value, etc., based on at least one first point cloud indicated by the first indication information, which will not be listed here.

[0170] For example, consider two sensing nodes, designated as the first sensing node and the second sensing node. The first sensing node or the second sensing node can be determined according to... Figure 6 The method shown reports the corresponding second sensing spectra to the fusion center node. The fusion center node merges or fuses the second sensing spectra reported by the two sensing nodes to determine the first sensing result. Figure 7 The diagram shows a flowchart of a communication method, including:

[0171] Optionally, in step 710: the fusion center node sends first information. Correspondingly, the first sensing node and the second sensing node receive the first information.

[0172] For example, the method in this application embodiment can be applied to scenarios of multi-node collaborative sensing. For instance, a first sensing node and a second sensing node can collaborate to sense a first target. Both the first and second sensing nodes can be access network devices (such as base stations), in which case the two access network devices collaborate to sense. Alternatively, both the first and second sensing nodes can be terminal devices, in which case the two terminal devices collaborate to sense. Or, the first sensing node can be an access network device (such as a base station), and the second sensing node can be a terminal device; or, the first sensing node can be a terminal device, and the second sensing node can be an access network device (such as a base station), etc., in which case the access network device and the terminal device collaborate to sense. There are no restrictions on the fusion center node. For example, the fusion center node can be an access network device (such as a base station), a core network element, or a sensing network element (such as an SF network element). It should be noted that when the fusion center node is an access network device, the access network device can adopt an ORAN architecture, and the access network device can include logical units such as CU, DU, and RU. The implementation process of "the fusion center node sending information (such as indication information) to the sensing node (such as the first sensing node or the second sensing node)" in the embodiments of this application may include: the CU sending the corresponding information to the DU, and then the DU sending the corresponding information to the RU, which finally reaches the sensing node side. Optionally, at this time, the information can be sent through RRC signaling, that is, the information is carried in the RRC signaling. Alternatively, the DU sends the corresponding information to the RU, which finally reaches the sensing node side. Optionally, at this time, the information can be sent through downlink control information (DCI), that is, the information can be carried in the DCI.

[0173] In one possible implementation, the fusion center node can select collaborative sensing nodes from among multiple sensing nodes based on certain rules. The specific content of these rules is not limited. For example, the fusion center node can select nodes whose coverage areas overlap and where the overlapping area contains the first target as collaborative sensing nodes. It is understood that in... Figure 7 In the schematic diagram, the first sensing node and the second sensing node act as collaborative sensing nodes, jointly sensing the first target. For example, the coverage areas of the first sensing node and the second sensing node overlap, and the first target is contained within this overlapping area. When the fusion center node selects the first sensing node and the second sensing node as collaborative sensing nodes, the fusion center node can send first information to the first sensing node and the second sensing node respectively. This first information is used to instruct the first sensing node or the second sensing node to perform sensing. Specifically, this first information can be used to instruct the first sensing node or the second sensing node to sense the first target within its coverage area. Optionally, the first information may also include an identifier for the first target.

[0174] Step 720: The first sensing node sends a sensing signal to sense the first target and obtains the corresponding sensing result; similarly, the second sensing node sends a sensing signal to sense the first target and obtains the corresponding sensing result.

[0175] For example, a first sensing node or a second sensing node sends a sensing signal, which reaches a first target and is reflected by the target to form an echo signal. The first or second sensing node can receive this echo signal. By analyzing the echo signal, a first sensing spectrum can be obtained. Furthermore, by analyzing / processing the first sensing spectrum, the first or second sensing node can obtain the point cloud corresponding to the first target.

[0176] Optionally, in step 730: the fusion center node sends second indication information. Accordingly, the first sensing node or the second sensing node receives the second indication information.

[0177] The second indication information is used to indicate the first condition. The first or second sensing node can select or determine point clouds that satisfy the first condition from the point cloud of the first target; these point clouds that satisfy the first condition form the first point cloud set. The first condition can be referred to the previous explanation. In this design, the first or second sensing node reports the point clouds that satisfy the first condition to the fusion center node, without needing to report the entire point cloud, thereby reducing the overhead of the first or second sensing node reporting point clouds (or sensing results).

[0178] In another possible implementation, the fusion center node may not send the second indication information (such as the first or second sensing node) to the sensing nodes (such as the first or second sensing node) to indicate the first condition. The sensing nodes (such as the first or second sensing node) can report the entire point cloud to the fusion center node. The advantage of this implementation is that the fusion center node does not need to send corresponding indication information to the sensing nodes to indicate the conditions (such as the second condition) for the sensing nodes to report the point cloud, thus saving indication overhead.

[0179] Step 740: The first sensing node and the second sensing node send the first point cloud set; correspondingly, the fusion center node receives the first point cloud set.

[0180] Step 750: The fusion center node clusters the first point cloud set sent by the first sensing node and the first point cloud set sent by the second sensing node to determine at least one first point cloud.

[0181] For ease of description / explanation, the first point cloud set sent by the first sensing node is called the first point cloud set A, and the first point cloud set sent by the second sensing node is called the first point cloud set B. First point cloud set A contains at least one point cloud, and first point cloud set B contains at least one point cloud. The fusion center node clusters the point clouds contained in first point cloud set A and first point cloud set B to obtain at least one cluster. For example, first point cloud set A contains 5 point clouds, with indices 1A to 5A. First point cloud set B contains 6 point clouds, with indices 1B to 6B. Through clustering, point cloud 1A and point cloud 2B are clustered into one cluster. The fusion center node can then send indication information (as described below) to the first sensing node A to indicate point cloud 1A, such as a binary bitmap (10000). The fusion center node sends indication information (hereinafter referred to as the first indication information) to the first sensing node B to indicate the point cloud 2B. This indication information can be a binary bitmap (010000).

[0182] Optionally, in step 760: the fusion center node sends first instruction information; correspondingly, the first sensing node or the second sensing node receives the first instruction information.

[0183] It is understandable that the first indication information sent by the fusion center node to the first sensing node is used to instruct the first sensing node to report the point clouds in the first point cloud set that have been successfully clustered (or clustered into one class). In the example above, the first indication information could be 10000. The first indication information sent by the fusion center node to the second sensing node is used to instruct the second sensing node to report the point clouds in the first point cloud set that have been successfully clustered (or clustered into one class). In the example above, the first indication information could be 010000. The first indication information sent by the fusion center node to the first sensing node and the first indication information sent by the fusion center node to the second sensing node can be the same or different, without restriction. For ease of distinction, the first indication information sent by the fusion center node to the first sensing node is called first indication information A, and the first indication information sent by the fusion center node to the second sensing node is called first indication information B.

[0184] Step 770: The first sensing node determines a second sensing spectrum (referred to as second sensing spectrum A) based on the first indication information (such as first indication information A) and sends the second sensing spectrum. Similarly, the second sensing node determines a second sensing spectrum (referred to as second sensing spectrum B) based on the first indication information (such as first indication information B) and sends the second sensing spectrum. Accordingly, the fusion center node receives the second sensing spectrum (such as second sensing spectrum A and second sensing spectrum B).

[0185] For example, when a first sensing node receives a first indication information A, it can determine at least one point cloud indicated by the first indication information A (e.g., referred to as at least one first point cloud). The first sensing node can determine the value of the first point cloud in the velocity dimension (e.g., a first value). The first sensing node determines the value of the first sensing spectrum (e.g., referred to as the first sensing spectrum A) in the velocity dimension as the first value, and obtains a second sensing spectrum (e.g., the second sensing spectrum A). Optionally, the first sensing node can also determine at least one of the following: the value of the first point cloud in the distance dimension (e.g., a second value), the value of the first point cloud in the horizontal angle dimension (e.g., a third value), or the value of the first point cloud in the pitch angle dimension (e.g., a fourth value). Optionally, in the process of determining the second sensing spectrum, the first sensing node further includes at least one of the following: determining the value of the first sensing spectrum in the distance dimension as the second value, determining the value of the first sensing spectrum in the horizontal angle dimension as the third value, or determining the value of the first sensing spectrum in the pitch angle dimension as the fourth value.

[0186] When the second sensing node receives the first indication information B: the second sensing node can determine the second sensing spectrum B based on the first indication information B. The implementation process is similar to that of the first sensing node determining the second sensing spectrum A based on the first indication information A, and will not be described in detail here.

[0187] In one possible implementation, the fusion center node may not indicate the first indication information related to the clustering results to the sensing nodes (such as the first sensing node or the second sensing node). The sensing nodes can report the acquired point clouds and the corresponding dimensionality-reduced sensing spectra to the fusion center node. For example, a sensing node may acquire five point clouds, each with a velocity dimension value from 1 to 5. The sensing node can then determine or fix the velocity dimension values ​​of the four-dimensional first sensing spectrum to values ​​from 1 to 5, obtaining five dimensionality-reduced sensing spectra. The sensing nodes report these five dimensionality-reduced sensing spectra to the fusion center node, which is one possible implementation of the second sensing spectrum provided in this application embodiment. The advantage of this implementation is that it reduces the indication overhead of the fusion center node. Furthermore, when the fusion center node receives the five dimensionality-reduced sensing spectra, it can select the sensing spectra corresponding to the successfully clustered point clouds from these five dimensionality-reduced sensing spectra, and further merge the sensing spectra corresponding to the successfully clustered point clouds.

[0188] Step 780: The fusion center node determines the perception result (such as the first perception result) of the first target based on the second perception spectrum (such as the second perception spectrum A) reported by the first perception node and the second perception spectrum (such as the second perception spectrum B) reported by the second perception node.

[0189] For example, the fusion center node merges the second perception spectrum A and the second perception spectrum B to obtain a merged perception spectrum. Based on the merged perception spectrum, the fusion center node determines the perception result of the first target. For example, the perception result of the first target (i.e., the first perception result) includes at least one of the following: the type of the first target (e.g., whether the first target is a dynamic object, such as a vehicle, or a stationary object, such as a tree, road fence, etc.), the position of the first target, the velocity of the first target, or the angle of the first target (e.g., horizontal angle and / or pitch angle, etc.).

[0190] The methods provided in the embodiments of this application, such as Figure 6 The method shown or Figure 7 The methods illustrated are explained in the scenarios in which they are applied. It is understood that these application scenarios are merely illustrative and not intended to limit the scope of the embodiments of this application. The methods provided in the embodiments of this application can be applied to other scenarios in addition to the ones described below.

[0191] In the field of perception, there is a concept of "extended target." An extended target refers to a target whose physical size (e.g., the first target) is larger than the perception resolution, resulting in multiple scattering centers. The perception resolution can refer to the minimum resolution of the perception system, such as minimum distance resolution or minimum angular resolution. It can be understood that one scattering center corresponds to one or a type of echo signal. Therefore, an extended target can also be understood as a physical entity with multiple scattering centers. For example, a "vehicle" can be considered an extended target, possessing multiple scattering centers. For instance, a vehicle may have five scattering centers, corresponding to the front, rear, left, right, and top of the vehicle. When perceiving a vehicle: the perception node sends a perception signal, which reaches the vehicle. All five scattering centers of the vehicle reflect the perception signal, forming corresponding echo signals. These echo signals can be considered as the echo signals corresponding to the five scattering centers. Then, the perception node receives the echo signals, processes them, and generates the corresponding perception spectrum or point cloud. The perception node then sends the corresponding perception spectrum or point cloud to the fusion center node. The fusion center node merges the perception spectra or point clouds reported by multiple perception nodes (also known as collaborative perception nodes) to generate corresponding perception results. The perception results may include at least one of the following information: vehicle type, vehicle position, vehicle speed, or vehicle angle (such as horizontal angle and / or pitch angle).

[0192] Currently, in scenarios involving collaboration among multiple sensing nodes, the fusion center node can fuse the sensing results (such as sensing spectra or point clouds) reported by multiple sensing nodes to determine the final sensing result. However, both the methods for reporting sensing spectra or point clouds have corresponding problems for extending the perception of targets. A detailed analysis follows:

[0193] Method 1: Point clouds are reported by each sensing collaboration node. The fusion center node fuses the point clouds reported by each sensing collaboration node to obtain the final sensing result, such as information on the type, location, velocity, or angle of the sensed target. This method may suffer from low sensing accuracy for extended targets.

[0194] For example, there are three sensing collaborative nodes, each sensing an extended target (such as a vehicle). Sensing nodes 1 to 3 obtain point clouds 1 to 3, respectively, and a confidence level for each point cloud, based on their sensing of the extended target. Optionally, the confidence level can also be called the reliability, used to indicate the reliability of the corresponding point cloud data. The confidence level can be represented by the estimated error covariance R. Any one of point clouds 1 to 3 contains the location information of the extended target, which can be represented by coordinates L. For example, sensing node 1 obtains point cloud 1 by sensing the extended target, which can be represented as (L1), and its corresponding confidence level is represented as R1. Similarly, sensing node 2 obtains point cloud 2 by sensing the extended target, which can be represented as (L2), and its corresponding confidence level is represented as R2. Sensing node 3 obtains point cloud 3 by sensing the extended target, which can be represented as (L3), and its corresponding confidence level is represented as R3. The fusion center node merges the point clouds and their corresponding confidence scores reported by the three sensing collaboration nodes to obtain the merged sensing result. The merged sensing result satisfies Formula 1:

[0195]

[0196] Wherein, L1 represents point cloud 1 reported by sensing collaboration node 1, and R1 represents the confidence level of point cloud 1; L2 represents point cloud 2 reported by sensing collaboration node 2, and R2 represents the confidence level of point cloud 2; L3 represents point cloud 3 reported by sensing collaboration node 3, and R3 represents the confidence level of point cloud 3; L represents the merged sensing result, such as the coordinates corresponding to the location information of the merged extended target.

[0197] For extended targets, the fusion center node uses Method 1 to merge the point clouds reported by various sensing collaboration nodes, which may lead to low sensing accuracy, even lower than that of a single sensing node. The reason is as follows: Formula 1 is applicable to merging or fusing point cloud data with the same scattering center. In Method 1, applying Formula 1, the three point clouds come from three different sensing collaboration nodes. Due to the difference in perspective between the sensing collaboration nodes, the point clouds generated by each node may originate from different scattering centers. For example, point cloud 1 reported by sensing collaboration node 1 may originate from scattering center 1 of the extended target (e.g., the scattering center corresponding to the front of the vehicle), point cloud 2 reported by sensing collaboration node 2 may originate from scattering center 2 of the extended target (e.g., the scattering center corresponding to the top of the vehicle), and point cloud 3 reported by sensing collaboration node 3 may originate from scattering center 3 of the extended target (e.g., the scattering center corresponding to the left end of the vehicle). Therefore, when using Formula 1 to merge or fuse point clouds from multiple sensing collaboration nodes, effective correlation is difficult to achieve. For example, point cloud 1 at the front of the vehicle reported by perception node 1, point cloud 2 at the top of the vehicle reported by perception node 2, and point cloud 3 at the left side of the vehicle reported by perception node 3 cannot be directly fused. Even if forced to fuse them, there will be problems such as large errors and low perception accuracy.

[0198] Method 2: Each sensing collaboration node reports a basic sensing spectrum, which refers to a four-dimensional spectrum including distance, horizontal angle, pitch angle, and velocity, or a transformed XYZ spectrum (primarily considering the perception of stationary targets). After obtaining the sensing spectra reported by each sensing collaboration node, the fusion center node can perform superposition of the sensing spectra, such as linear superposition or multiplicative superposition, and then perform detection on the superimposed sensing spectrum to obtain a new detection result, which can be considered the final sensing result. The disadvantages are as follows: Firstly, directly reporting the four-dimensional sensing spectrum by each sensing collaboration node incurs significant overhead. Secondly, due to the differences in the perspectives of each sensing collaboration node, the sensing spectra reported by each node may originate from different scattering centers of the extended target. Superposition of sensing spectra from different scattering centers of the extended target may not be possible, and even if forced superposition, the superimposed sensing spectrum may have large errors, ultimately leading to low sensing accuracy. It is understood that in the description of this application, the descriptions of merging, fusing, and superimposing are not specifically distinguished, and the descriptions of the above three are interchangeable.

[0199] In the method of this application, as in this application Figure 7In the method shown: Each collaborative sensing node, such as the first sensing node and the second sensing node, reports a first point cloud set to the fusion center node. For example, the first sensing node reports a first point cloud set A, and the second sensing node reports a first point cloud set B. The fusion center node clusters the point clouds reported by each collaborative sensing node, obtaining at least one class; it can be understood that the point clouds clustered into one class can be considered to originate from a scattering center of the extended target. Further, the fusion center node notifies / instructs each collaborative sensing node of the point clouds clustered into one class. Each collaborative sensing node performs dimensionality reduction on the basic sensing spectrum (such as a four-dimensional spectrum or the first sensing spectrum) based on the point clouds indicated by the fusion center node, and reports the dimensionality-reduced sensing spectrum (such as the second sensing spectrum). Since the dimensionality-reduced sensing spectrum (such as the second sensing spectrum) reported by each collaborative sensing node originates from / corresponds to a scattering center, the fusion center node can fuse or superimpose the reduced sensing spectra reported by each collaborative sensing node, and determine the final sensing result based on the fused or superimposed sensing spectrum, thereby improving the sensing accuracy of the extended target. The method of this application, compared to method 1 or method 2 described above, can improve the perception accuracy of the extended target. On the other hand, the reporting of the dimensionality-reduced perception spectrum by each cooperative perception node to the fusion center node can reduce the air interface overhead of reporting the perception spectrum compared to directly reporting the basic four-dimensional perception spectrum in method 2 described above.

[0200] Taking a vehicle as the extended target, the method provided in this application will be described as follows: Figure 8 As shown, the fusion center node receives point clouds from various sensing collaboration nodes. For example, in Figure 8 In this diagram, point clouds of the same color represent those from the same sensing collaboration node. The fusion center node clusters the point clouds reported by each sensing collaboration node, generating a cluster containing four point clouds. The black circle ● represents the actual location of the vehicle. That is, of the four point clouds in this cluster, one point cloud represents the actual location of the vehicle's roof. The remaining three point clouds in this cluster come from two sensing collaboration nodes. For example, these two sensing collaboration nodes are referred to as the first sensing collaboration node and the second sensing collaboration node. The fusion center node sends point cloud indication information to the first sensing collaboration node. This indication information indicates the point clouds included in the successfully clustered cluster, such as point cloud A. Upon receiving the indication information for point cloud A, the first sensing collaboration node can obtain the value of point cloud A in the velocity dimension (e.g., the first value). The first sensing collaboration node determines / fixes the first value in the velocity dimension of the four-dimensional sensing spectrum (i.e., the first sensing spectrum) to obtain the second sensing spectrum. This process can be called dimensionality reduction of the four-dimensional sensing spectrum. For example, reducing the four-dimensional perceptual spectrum (R,θ,φ,V) to a three-dimensional spectrum (R,θ,φ,v) i ), where v i This represents the value of point cloud A in the velocity dimension (such as the first value).

[0201] On the fusion center node side, a successfully clustered class includes two point clouds reported by the second sensing collaboration node, such as point cloud B and point cloud C. In one possible implementation, the fusion center node can send indication information to the second sensing collaboration node to indicate point cloud B and point cloud C. The second sensing node obtains the value of point cloud B in the velocity dimension. The second sensing collaboration node fixes the value of the four-dimensional sensing spectrum in the velocity dimension to the value of point cloud B in the velocity dimension and reports the corresponding sensing spectrum. Similarly, the second sensing node can also obtain the value of point cloud C in the velocity dimension. The second sensing collaboration node fixes the value of the four-dimensional sensing spectrum in the velocity dimension to the value of point cloud C in the velocity dimension and reports the corresponding sensing spectrum. At this time, the fusion center node fuses one sensing spectrum reported by the first sensing collaboration node and two sensing spectra reported by the second sensing collaboration node. Alternatively, in another possible implementation (in Figure 8 (This mainly illustrates one possible implementation method). The fusion center node selects a point cloud from point cloud B and point cloud C, and sends the indication information of the selected point cloud to the second sensing node. The second sensing node obtains the value of the selected point cloud in the velocity dimension, fixes or determines the value of the four-dimensional sensing spectrum in the velocity dimension to the aforementioned value, and reports it to the fusion center node. In this embodiment, the rule for the fusion center node to select point cloud B or point cloud C is not limited. For example, if point cloud B and point cloud C have the same value in the velocity dimension, the fusion center node can arbitrarily select one point cloud from point cloud B or point cloud C for indication.

[0202] exist Figure 8 In the schematic diagram, the first and second sensing collaboration nodes each report a three-dimensional sensing spectrum. The fusion center node superimposes these two three-dimensional sensing spectra, which can be linear or multiplicative, to obtain a superimposed sensing spectrum. "Superimposition" can also be replaced with terms like "fusion" or "merging." The fusion center node analyzes the superimposed sensing spectrum to obtain the final vehicle sensing results, such as vehicle type, position, angle, or speed.

[0203] It should be noted that, in Figure 8In the first schematic diagram (the point cloud diagram), the black circle ● represents the actual points of the vehicle. It can be seen that one vehicle corresponds to five actual points, which correspond to the front, rear, left, right, and roof of the vehicle, respectively. Optionally, one actual point of a vehicle can correspond to one scattering center of the vehicle. In this embodiment, the fusion center node clusters the point cloud corresponding to the roof into one cluster. Further, the fusion center node indicates to each sensing collaboration node the point cloud contained in the successfully clustered cluster (i.e., the roof-corresponding cluster). Each sensing collaboration node performs dimensionality reduction on the four-dimensional sensing spectrum based on the point cloud indicated by the fusion center node and reports the dimensionality-reduced sensing spectrum. The fusion center node fuses the dimensionality-reduced sensing spectra reported by each sensing collaboration node. Since the dimensionality-reduced sensing spectra reported by each sensing node are for the same scattering center (i.e., the roof), the sensing spectra reported by each sensing collaboration node can be fused. The fusion center node determines the final sensing result of the vehicle based on the fused sensing spectrum, improving the accuracy of the sensing result.

[0204] exist Figure 8 In the coordinate systems of the various schematic diagrams, the horizontal axis is the X-axis, and the vertical axis is the Y-axis. The coordinate system can be a global coordinate system, such as a Cartesian coordinate system. The X-axis represents the horizontal direction (or left-right direction), and the Y-axis represents the vertical direction (or up-down direction). For example, as explained earlier, each sensing collaboration node reports a dimensionality-reduced sensing spectrum (second sensing spectrum) to the fusion center node. The fusion center node can perform coordinate system transformation on the aforementioned dimensionality-reduced sensing spectrum (second sensing spectrum), such as converting it to a global coordinate system. The fusion center node then fuses the sensing spectra in the transformed coordinate system.

[0205] Through the above design, the fusion center node first clusters the point clouds reported by each sensing collaboration node to find the point clouds belonging to the same scattering center; then, the fusion center node instructs each sensing collaboration node to report the sensing spectrum corresponding to the above point clouds; finally, the sensing spectra reported by each sensing collaboration node are fused, and the final sensing result of the extended target is determined based on the fused sensing spectrum, thereby improving the accuracy and precision of the sensing result of the extended target.

[0206] In the embodiments provided above, the methods provided by this application are described from the perspective of the interaction between the sensing node and the fusion center node. To implement the functions of the methods provided in this application, the sensing node or the fusion center node may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the design constraints of the specific application of the technical solution.

[0207] Based on the same design concept as the above method embodiments, Figure 9 and Figure 10 This is a schematic diagram of the possible communication devices provided in the embodiments of this application. These communication devices can realize the functions implemented by the sensing node or fusion center node in the above method embodiments, and therefore may achieve the beneficial effects of the above method embodiments. In the embodiments of this application, the communication device can be a sensing node or fusion center node, or a unit, module, or component (such as a chip, chip system, circuit, processor, or others) applied in the sensing node or fusion center node. In the following description, the term "unit" is used as an example. For example, in the following description, the communication device includes a processing unit and a transceiver unit as an example. The processing unit can also be replaced by a processing module or processing component. The transceiver unit can also be replaced by a transceiver unit or transceiver component. For example, the transceiver component can refer to a communication module.

[0208] like Figure 9 As shown, the communication device 9000 includes a processing unit 9010 and a transceiver unit 9020. The communication device 9000 is used to implement the above-mentioned... Figure 6 The transceiver unit 9020 functions as a sensing node or fusion center node. Optionally, it can also be referred to as an output unit, interface unit, or communication unit, etc. In one possible implementation, the transceiver unit 9020 includes at least one of a transmitting unit or a receiving unit. The transmitting unit and the receiving unit can be integrated together, or they can be two independent units, etc.

[0209] When communication device 9000 is used to achieve Figure 6 Specifically, the function of the sensing node is as follows: a processing unit 9010 is used to determine a second sensing spectrum, which is obtained by determining the value of at least one dimension of the first sensing spectrum as a fixed value. The at least one dimension includes at least a velocity dimension. The first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional matrix, a two-dimensional matrix, or a three-dimensional matrix. A transceiver unit 9020 is used to send information about the second sensing spectrum.

[0210] In one possible design, the first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity, and the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle; wherein, the value of an element in the first sensing spectrum or the second sensing spectrum represents the intensity of the first target at the corresponding coordinates.

[0211] In one possible design, the fixed value corresponding to the velocity dimension is a first value.

[0212] In one possible design, the at least one dimension further includes at least one of the following: a distance dimension, a horizontal angle dimension, or a pitch angle dimension; wherein the fixed value corresponding to the distance dimension is a second value, the fixed value corresponding to the horizontal angle dimension is a third value, and the fixed value corresponding to the pitch angle dimension is a fourth value.

[0213] In one possible design, the transceiver unit 9020 is further configured to receive first indication information; the processing unit 9010 is further configured to determine the fixed value based on the first indication information.

[0214] In one possible design, the transceiver unit 9020 is also used to transmit a first point cloud set, the first point cloud set containing at least one point cloud, wherein a point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle or velocity.

[0215] In one possible design, the first indication information is used to indicate at least one first point cloud, which belongs to the first point cloud set.

[0216] In one possible design, the first point cloud satisfies at least one of the following: the first point cloud has a first value in the velocity dimension; the first point cloud has a second value in the distance dimension; the first point cloud has a third value in the horizontal angle dimension; or, the first point cloud has a fourth value in the pitch angle dimension.

[0217] In one possible design, the transceiver unit 9020 is further configured to receive second indication information, the second indication information being used to indicate the first condition; the processing unit 9010 is further configured to determine, in the point cloud of the first target, point clouds that satisfy the first condition; wherein, the point clouds that satisfy the first condition constitute the first point cloud set.

[0218] When communication device 9000 is used to achieve Figure 6 When integrating the functions of the central node, specifically: a transceiver unit 9020 is used to receive information of at least one second sensing spectrum, which is obtained by determining the value of at least one dimension of the first sensing spectrum as a fixed value, wherein the at least one dimension includes at least a velocity dimension, the first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional matrix, a two-dimensional matrix, or a three-dimensional matrix; a processing unit 9010 is used to determine the first sensing result based on the at least one second sensing spectrum.

[0219] In one possible design, the at least one second sensing spectrum originates from at least one sensing device.

[0220] In one possible design, the first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity, and the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle; wherein, the value of an element in the first sensing spectrum or the second sensing spectrum represents the intensity of the first target at the corresponding coordinates.

[0221] In one possible design of the method, the fixed value corresponding to the velocity dimension is a first value.

[0222] In one possible design, the at least one dimension further includes at least one of the following: a distance dimension, a horizontal angle dimension, or a pitch angle dimension; wherein the fixed value corresponding to the distance dimension is a second value, the fixed value corresponding to the horizontal angle dimension is a third value, and the fixed value corresponding to the pitch angle dimension is a fourth value.

[0223] In one possible design, there are multiple second sensing spectra, which are from multiple sensing devices. Determining the first sensing result based on the second sensing spectra includes: merging the multiple second sensing spectra to obtain a merged second sensing spectrum; and determining the first sensing result based on the merged second sensing spectrum.

[0224] In one possible design, the transceiver unit 9020 is also configured to transmit first indication information, which is at least used to determine the fixed value.

[0225] In one possible design, the transceiver unit 9020 is further configured to receive at least one first point cloud set, the first point cloud set containing at least one point cloud, wherein a point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle or velocity; the processing unit 9010 is further configured to cluster the point clouds contained in the first point cloud set to determine at least one first point cloud, the at least one first point cloud belonging to the first point cloud set.

[0226] In one possible design, the at least one first point cloud set is from at least one sensing device.

[0227] In one possible design, the first indication information is used to indicate the at least one first point cloud.

[0228] In one possible design, the first point cloud satisfies at least one of the following: the first point cloud has a first value in the velocity dimension; the first point cloud has a second value in the distance dimension; the first point cloud has a third value in the horizontal angle dimension; or, the first point cloud has a fourth value in the pitch angle dimension.

[0229] In one possible design, the transceiver unit 9020 is also used to send second indication information, which is used to indicate a first condition for reporting point clouds, and point clouds that meet the first condition constitute the first point cloud set.

[0230] It is understood that the division of units in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. In addition, the functional units in this application embodiment can be integrated into a physical device (e.g., in a processor), or each functional unit can be a separate physical device, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module, etc.

[0231] like Figure 10 As shown, the communication device 10000 includes a processor 10010 and an interface circuit 10020. The processor 10010 and the interface circuit 10020 are coupled to each other. It is understood that the interface circuit 10020 can be a transceiver or an input / output interface. Optionally, the communication device 10000 may also include a memory 10030 for storing instructions executed by the processor 10010, or storing input data required by the processor 10010 to execute instructions, or storing data generated after the processor 10010 executes instructions.

[0232] When communication device 10000 is used to achieve Figure 6 In the method shown, the processor 10010 is used to implement the functions of the processing unit 9010, and the interface circuit 10020 is used to implement the functions of the transceiver unit 9020.

[0233] When the aforementioned communication device is a module applied to a sensing node, the chip implements the functions of the sensing node in the above method embodiments. This module receives information sent to the sensing node by the fusion center node through other modules (such as an RF module or antenna) in the sensing node; or, this module sends information to other modules (such as an RF module or antenna) in the sensing node, which is information sent by the sensing node to the fusion center node. It is understood that when the sensing node is an access network device, the module of the sensing node can be a chip of the access network device, or a DU or other modules. Here, the DU can be a DU under the O-RAN architecture.

[0234] When the aforementioned communication device is a module applied to the convergence central node, the module implements the functions of the convergence central node in the above method embodiments. This module receives information from other modules (such as radio frequency modules or antennas) within the convergence central node, information sent from the sensing node to the convergence central node; or, the module sends information to other modules (such as radio frequency modules or antennas) within the convergence central node, information sent from the convergence central node to the sensing node. It is understood that when the sensing node is an access network device, the module of the convergence central node can be a chip of the access network device, or a DU (Distributed Unit) or other modules. Here, the DU can be a DU under the O-RAN architecture.

[0235] This application also provides a communication device, which includes a processor for implementing the above-described embodiments. Figure 6 The communication device may include a sensing node or a fusion center node. Optionally, the communication device further includes a memory, with a processor coupled to the memory. The processor executes computer programs or instructions stored in the memory to implement the above-mentioned functions. Figure 6 The communication device can function as a sensing node or fusion center node. Optionally, the communication device may be a chip or a chip system.

[0236] This application also provides a communication device, including a processor and an interface circuit. The interface circuit is used to receive signals from other devices outside the device and transmit them to the processor, or to send signals from the processor to other devices outside the device. The processor implements the above through logic circuits or executable code instructions. Figure 6 The functions of the sensing node or fusion center node.

[0237] This application also provides a computer-readable storage medium storing instructions, which may also be referred to as computer programs, computer program code, etc. These instructions, when executed on a computer, cause the computer to perform the aforementioned... Figure 6 The functions of the sensing node or fusion center node.

[0238] This application also provides a computer program product, including a computer program or instructions, which, when run on a computer, implement the above-described functionality. Figure 6 The functions of the sensing node or fusion center node.

[0239] This application also provides a chip, including a processor, for implementing the above. Figure 6 The chip includes a sensing node or fusion center node. Optionally, the chip also includes a memory, with a processor coupled to the memory. The processor executes computer programs or instructions stored in the memory, enabling the chip to perform the aforementioned functions. Figure 6 The functions of the sensing node or fusion center node.

[0240] It is understood that the processor in the embodiments of this application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0241] The memory in the embodiments of this application may be random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), register, hard disk, portable hard disk, CD-ROM, or any other form of storage medium known in the art.

[0242] The method steps in the embodiments of this application can be implemented in hardware or in software instructions executable by a processor. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. The storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0243] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. This computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center integrating one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

[0244] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

Claims

1. A communication method, characterized in that, include: A second sensing spectrum is determined by fixing the value of at least one dimension of the first sensing spectrum, wherein the at least one dimension includes at least a velocity dimension, the first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional matrix, a two-dimensional matrix, or a three-dimensional matrix. Send information from the second sensing spectrum.

2. The method as described in claim 1, characterized in that, The first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity; the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle. Wherein, the value of an element in the first or second perception spectrum represents the intensity of the first target at the corresponding coordinate.

3. The method as described in claim 1 or 2, characterized in that, The fixed value corresponding to the velocity dimension is the first value.

4. The method as described in claim 3, characterized in that, The at least one dimension further includes at least one of the following: distance dimension, horizontal angle dimension, or pitch angle dimension; Wherein, the fixed value corresponding to the distance dimension is the second value, the fixed value corresponding to the horizontal angle dimension is the third value, and the fixed value corresponding to the pitch angle dimension is the fourth value.

5. The method according to any one of claims 1 to 4, characterized in that, Also includes: Receive the first instruction message; The fixed value is determined based on the first indication information.

6. The method according to any one of claims 1 to 5, characterized in that, Also includes: Send a first point cloud set, which contains at least one point cloud, wherein a point cloud in the first point cloud set contains a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle, or velocity.

7. The method as described in claim 6, characterized in that, The first indication information is used to indicate at least one first point cloud, which belongs to the first point cloud set.

8. The method as described in claim 7, characterized in that, The first point cloud satisfies at least one of the following: The first point cloud takes the first value in the velocity dimension; The first point cloud takes the second value in the distance dimension; The first point cloud takes the third value in the horizontal angular dimension; or, The first point cloud takes the fourth value in the pitch angle dimension.

9. The method according to any one of claims 6 to 8, characterized in that, Also includes: Receive second indication information, the second indication information being used to indicate the first condition; In the point cloud of the first target, identify the point cloud that satisfies the first condition; The point clouds that satisfy the first condition constitute the first point cloud set.

10. A communication method, characterized in that, include: Receive information of at least one second sensing spectrum, which is obtained by determining the value of at least one dimension of the first sensing spectrum to a fixed value, wherein the at least one dimension includes at least a velocity dimension, the first sensing spectrum is a four-dimensional matrix, and the second sensing spectrum is a one-dimensional matrix, a two-dimensional matrix, or a three-dimensional matrix. The first perception result is determined based on the at least one second perception spectrum.

11. The method as described in claim 10, characterized in that, The at least one second sensing spectrum comes from at least one sensing device.

12. The method as described in claim 10 or 11, characterized in that, The first sensing spectrum includes the following four dimensions: distance, horizontal angle, pitch angle, and velocity; the second sensing spectrum includes at least one of the following dimensions: distance, horizontal angle, or pitch angle. Wherein, the value of an element in the first or second perception spectrum represents the intensity of the first target at the corresponding coordinate.

13. The method according to any one of claims 10 to 12, characterized in that, The fixed value corresponding to the velocity dimension is the first value.

14. The method as described in claim 13, characterized in that, The at least one dimension further includes at least one of the following: distance dimension, horizontal angle dimension, or pitch angle dimension; Wherein, the fixed value corresponding to the distance dimension is the second value, the fixed value corresponding to the horizontal angle dimension is the third value, and the fixed value corresponding to the pitch angle dimension is the fourth value.

15. The method according to any one of claims 10 to 14, characterized in that, The second sensing spectrum is multiple, and the multiple sensing spectra come from multiple sensing devices. Determining the first sensing result based on the second sensing spectrum includes: The multiple second sensing spectra are merged to obtain a merged second sensing spectrum; The first perception result is determined based on the merged second perception spectrum.

16. The method according to any one of claims 10 to 15, characterized in that, Also includes: Send a first indication message, which is used at least to determine the fixed value.

17. The method according to any one of claims 10 to 16, characterized in that, Also includes: Receive at least one first point cloud set, the first point cloud set containing at least one point cloud, and a point cloud in the first point cloud set containing a value corresponding to at least one of the following dimensions of the first target: distance, horizontal angle, pitch angle or velocity; Cluster the point clouds contained in the first point cloud set to determine at least one first point cloud, wherein the at least one first point cloud belongs to the first point cloud set.

18. The method as described in claim 17, characterized in that, The at least one first point cloud set comes from at least one sensing device.

19. The method according to any one of claims 16 to 18, characterized in that, The first indication information is used to indicate the at least one first point cloud.

20. The method according to any one of claims 17 to 19, characterized in that, The first point cloud satisfies at least one of the following: The first point cloud takes the first value in the velocity dimension; The first point cloud takes the second value in the distance dimension; The first point cloud takes the third value in the horizontal angular dimension; or, The first point cloud takes the fourth value in the pitch angle dimension.

21. The method according to any one of claims 17 to 20, characterized in that, Also includes: Send a second indication message, which is used to indicate a first condition for reporting point clouds, and point clouds that meet the first condition form the first point cloud set.

22. A communication device, characterized in that, Includes units for implementing the method as described in any one of claims 1 to 9.

23. A communication device, characterized in that, Includes a processor configured to cause the communication device to perform the method as described in any one of claims 1 to 9.

24. A communication device, characterized in that, Includes units for implementing the method as described in any one of claims 10 to 21.

25. A communication device, characterized in that, Includes a processor configured to cause the communication device to perform the method as described in any one of claims 10 to 21.

26. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, cause the communication device to perform the method as described in any one of claims 1 to 9, or the method as described in any one of claims 10 to 21.

27. A computer program product, characterized in that, The computer program product includes instructions that, when executed, cause the communication device to perform the method as described in any one of claims 1 to 9, or the method as described in any one of claims 10 to 21.

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