Sensing processing method and system, communication apparatus and storage medium

Abstract

Provided are a sensing processing method and system, a communication apparatus and a storage medium. The sensing processing method comprises: receiving a plurality of sensing results from a plurality of first nodes, each sensing result among the plurality of sensing results representing a sensing result in a sub-region managed by a corresponding first node; and on the basis of sensing results in a plurality of sub-regions, determining a sensing result of a sensing region, the sensing region comprising the plurality of sub-regions.

Description

Perception processing method and system, communication device and storage medium

[0001] This disclosure claims priority to Chinese patent application No. 202410029964.2, filed on January 8, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present disclosure relates to the field of communication technologies, and in particular to a perception processing method and system, a communication device, and a storage medium. Background Art

[0003] The integrated tele-sensing and computing network architecture builds on tele-sensing integration by introducing computing power equipment to support data processing in communication perception scenarios. This network architecture typically consists of a wireless access network, user devices (such as drones), computing power equipment, and a core network with perception servers. Summary of the Invention

[0004] In one aspect, an embodiment of the present disclosure provides a perception processing method. The perception processing method includes:

[0005] Receive multiple perception results from multiple first nodes, each of the multiple perception results represents a perception result within a sub-area managed by the corresponding first node; determine a perception result of a perception area based on the perception result of each sub-area within the multiple sub-areas, where the perception area includes multiple sub-areas.

[0006] On the other hand, the present disclosure provides another perception processing method. The perception processing method includes:

[0007] Acquire perception detection data of the perception node in the managed sub-area; when the perception detection data indicates that the perception target is located in the sub-area managed by the first node, determine the perception result of the sub-area based on the perception detection data; and send the perception result to the perception network element.

[0008] In another aspect, an embodiment of the present disclosure provides a perception communication system. The perception communication system includes: a first node and a perception network element;

[0009] The first node is used to determine the perception results of the sub-area it manages; send the perception results to the perception network element; the perception network element is used to receive multiple perception results from multiple first nodes; based on the perception results in the multiple sub-areas, determine the perception results of the perception area, where the perception area includes multiple sub-areas.

[0010] In another aspect, embodiments of the present disclosure provide a perception network element. The perception network element includes: a processing unit and a communication unit; the communication unit is configured to receive multiple perception results from multiple first nodes, each of the multiple perception results representing a perception result within a sub-area managed by the corresponding first node; and the processing unit is configured to determine a perception result for a perception area based on the perception results within the multiple sub-areas, where the perception area includes multiple sub-areas.

[0011] In another aspect, embodiments of the present disclosure provide a first node. The first node includes: a processing unit and a communication unit; the communication unit is configured to obtain perception detection data from perception nodes within a managed sub-area; the processing unit is configured to determine a perception result for the sub-area based on the perception detection data when the perception detection data indicates that a perception target is located within the sub-area managed by the first node; and the communication unit is configured to send the perception result to a perception network element.

[0012] In another aspect, an embodiment of the present disclosure provides a communication device comprising: a memory and a processor; the memory and the processor are coupled; the memory is configured to store a computer program; and the processor implements the perception processing method described in any of the above aspects when executing the computer program.

[0013] On the other hand, an embodiment of the present disclosure provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the perception processing method described in any of the above aspects is implemented.

[0014] On the other hand, an embodiment of the present disclosure provides a computer program product, which includes computer program instructions, and when the computer program instructions are executed by a processor, implements the perception processing method described in any of the above aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions of the present disclosure, the following briefly introduces the drawings required for use in some embodiments of the present disclosure. Obviously, the drawings described below are only drawings of some embodiments of the present disclosure, and those skilled in the art can also derive other drawings based on these drawings.

[0016] FIG1 is an architecture diagram of a perceptual communication system according to some embodiments.

[0017] FIG2 is an architecture diagram of another cognitive communication system according to some embodiments.

[0018] FIG3 is an architecture diagram of yet another cognitive communication system according to some embodiments.

[0019] FIG4 is an architecture diagram of yet another cognitive communication system according to some embodiments.

[0020] FIG5 is an architecture diagram of yet another cognitive communication system according to some embodiments.

[0021] FIG6 is an architecture diagram of yet another cognitive communication system according to some embodiments.

[0022] FIG7 is a flowchart of a perception processing method according to some embodiments.

[0023] FIG8 is a flowchart of another perception processing method according to some embodiments.

[0024] FIG9 is a flowchart of yet another perception processing method according to some embodiments.

[0025] FIG10 is a flowchart of yet another perception processing method according to some embodiments.

[0026] FIG11 is a flowchart of another perception processing method according to some embodiments.

[0027] FIG12 is a flowchart of yet another perception processing method according to some embodiments.

[0028] FIG13 is a flowchart of another perception processing method according to some embodiments.

[0029] FIG14 is a structural diagram of a perception network element according to some embodiments.

[0030] FIG15 is a structural diagram of a first node according to some embodiments.

[0031] FIG16 is a block diagram of a communication device according to some embodiments. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions of this disclosure in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of this disclosure, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0033] It should be noted that in this disclosure, expressions such as "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described in this disclosure as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of expressions such as "exemplarily" or "for example" is intended to present the relevant concepts in a detailed manner.

[0034] In the following, the terms "first," "second," etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the quantity of the technical features indicated. Therefore, a feature specified as "first," "second," etc. may explicitly or implicitly include one or more of the features.

[0035] In the description of this disclosure, unless otherwise specified, " / " means "or." For example, A / B can mean A or B. "And / or" herein is simply a way to describe an association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: only A, A and B, and only B. Furthermore, "at least one" means one or more, and "a plurality" means two or more.

[0036] The following explains the terms involved in the embodiments of the present disclosure to facilitate readers' understanding.

[0037] (1) Integrated sensing and communication (ISAC)

[0038] Synaesthesia integration refers to the integration of sensory capabilities into communication systems, enabling them to possess both sensory and communication capabilities. This technology is used to proactively understand and analyze the characteristics of wireless channels while transmitting information, thereby perceiving the physical characteristics of the surrounding environment and enhancing both communication and sensory functions.

[0039] Synaesthesia technology utilizes wireless signals transmitted by communication equipment. While completing the communication function, wireless signals can also be used for environmental perception. By collecting and analyzing the reflection, scattering, and multipath propagation of wireless signals in the surrounding environment, the surrounding environmental information can be analyzed, allowing the network side to make quick decisions, such as issuing control commands, triggering alarms, adjusting communication rates, etc.

[0040] (2) Integrated access and backhaul (IAB)

[0041] IAB is used for information integration, access, and backhaul between terminals, core networks, and servers in a communication system.

[0042] IAB includes two types of devices: IAB nodes and IAB donors. An IAB donor consists of a centralized unit (CU) and one or more distributed units (DUs).

[0043] The integrated tele-sensing and computing network architecture builds on tele-sensing integration by introducing computing power equipment to support data processing in communication perception scenarios. This network architecture typically consists of a wireless access network, user devices (such as drones), computing power equipment, and a core network with perception servers.

[0044] The current integrated synergy computing network architecture is difficult to handle various complex synergy computing scenarios, such as:

[0045] 1. In some cases, it is necessary to process the perception data through highly complex algorithms. However, the processing capacity of a single node is limited and it is difficult to meet the computing power requirements of highly complex algorithms.

[0046] 2. Faced with different perception needs, it is difficult to select suitable perception devices for perception, and it is difficult to select suitable computing power equipment to process the perception data measured by the perception devices.

[0047] 3. In actual network deployment, multiple base station devices usually have overlapping areas, which will generate perception information of multiple overlapping areas. The information represented by these perception information is often not exactly the same, so there is ambiguity.

[0048] In summary, the current integrated synaesthesia and computing network architecture is difficult to cope with various complex synaesthesia and computing scenarios, resulting in poor perception effects.

[0049] In view of this, the present disclosure provides a synergistic computing network architecture that is flexible and scalable, and supports collaboration between multiple synergistic computing nodes. Furthermore, the present disclosure provides an interactive process for communication, perception, and computing based on this network architecture to enhance perception.

[0050] The following describes in detail the implementation of the embodiments of the present disclosure in conjunction with the accompanying drawings.

[0051] FIG1 is an architecture diagram of a perceptual communication system 10 according to some embodiments. As shown in FIG1 , the perceptual communication system 10 includes: a perceptual network element 101 , a computing node 102 , and a perceptual node 103 .

[0052] The perception network element 101 may be located at the core network side of the perception communication system 10. The core network side is mainly used to support functions such as communication mobility management, perception management and control, etc.

[0053] The computing node 102 and the sensing node 103 may be located on the access network side of the sensing communication system 10. The access network side is mainly used to support functions such as communication, sensing, and computing. Devices on the core network side and the access network side transmit data through the transmission network.

[0054] In one implementation, the functional entity of the perception network element 101 may also be deployed on the access network side according to actual needs, and this disclosure does not limit this.

[0055] The perception network element 101 is used to manage the perception network, and has various perception-related functions, such as perception authorization, capability interaction, network element selection, control and data processing.

[0056] The computing node 102 refers to a node device that provides computing resources in the sensing communication system 10. For example, the computing node 102 may be a server, a computing board, or other types of computing devices.

[0057] The sensing node 103 refers to a device, module, or component in the sensing communication system 10 that has both communication and sensing capabilities and is used to transmit and receive data, communication signals, sensing signals, or control information. For example, the sensing node 103 can be an access network device such as a base station, relay station, or IAB node, or a user device such as a terminal.

[0058] It should be noted that the computing node 102 can be deployed independently or together with the sensing node 103. For example, the computing node 102 can be a base station, relay station, IAB node, or terminal that is allocated computing capabilities and resources. In this case, these devices belong to both the computing node 102 and the sensing node 103, and this disclosure does not limit this.

[0059] In one implementation, the perception communication system 10 may further include a communication network element. The communication network element is used to manage the communication network, for example, to implement core services such as data transmission, signaling processing, and network management within the communication network. The communication network element is capable of not only processing and forwarding large amounts of data traffic, but also supporting various signaling processing and network management functions, thereby ensuring the normal operation of the communication network. The functions of the perception network element may vary depending on the actual communication network and are not limited in this disclosure. For example, the communication-related functions of the perception network element may be implemented by a separate functional entity, namely, the communication network element.

[0060] Access network equipment includes, but is not limited to, access points (APs) in WiFi systems, such as home gateways, routers, servers, switches, bridges, etc., evolved NodeBs (eNBs), radio network controllers (RNCs), NodeBs (NBs), base station controllers (BSCs), base transceiver stations (BTSs), home base stations (e.g., home evolved NodeBs, or home NodeBs, HNBs), base band units (BBUs), wireless relay nodes, wireless backhaul nodes, transmission and reception points (TRPs or TPs), etc., and may also be 5G base stations, such as gNBs in new radio (NR) systems, or transmission points (TRPs or TPs), one or a group of antenna panels (including multiple antenna panels) of a base station in a 5G system, or network nodes constituting gNBs or transmission points, such as baseband units (BBUs), or distributed units (DUs), or road side units with base station functions. Access network equipment also includes base stations in different networking modes, such as master evolved NodeB (MeNB) and secondary eNB (SeNB, or secondary gNB, SgNB). Access network equipment also includes different types, such as ground base stations, aerial base stations, and satellite base stations.

[0061] A terminal is a device with wireless communication capabilities that can be deployed on land, indoors or outdoors, handheld, or in a vehicle. It can also be deployed on water (such as on ships) or in the air (for example, on airplanes, balloons, and satellites). A terminal, also known as user equipment (UE), mobile station (MS), mobile terminal (MT), or terminal device, provides voice and / or data connectivity to users. Examples include handheld devices and vehicle-mounted devices with wireless connectivity. Currently, terminals can be: mobile phones, tablet computers, laptop computers, PDAs, mobile internet devices (MIDs), wearable devices (such as smart watches, smart bracelets, pedometers, etc.), vehicle-mounted devices (such as cars, bicycles, electric vehicles, airplanes, ships, trains, high-speed trains, etc.), virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, smart home devices (such as refrigerators, televisions, air conditioners, electric meters, etc.), intelligent robots, workshop equipment, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, flying devices (such as intelligent robots, hot air balloons, drones, airplanes), etc. In one application scenario of the present disclosure, the terminal device is a terminal device that often works on the ground, such as a vehicle-mounted device. In this disclosure, for the sake of convenience, chips deployed in the above-mentioned devices, such as system-on-a-chip (SOC), baseband chips, etc., or other chips with communication functions may also be referred to as terminals.

[0062] The terminal can be a vehicle with corresponding communication functions, or a vehicle-mounted communication device, or other embedded communication devices, or a user's handheld communication device, including a mobile phone, tablet computer, etc.

[0063] As an example, in the embodiments of the present disclosure, the terminal may also be a wearable device. Wearable devices may also be referred to as wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear (such as glasses, gloves, watches, clothing, and shoes, etc.). A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include full-featured, large-sized, and independent of smartphones to achieve complete or partial functions, such as smart watches or smart glasses, as well as devices that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0064] As an embodiment, the perception network in this disclosure is divided and managed based on a grid-based approach. As shown in FIG2 , in conjunction with FIG1 , the coverage area of ​​the perception network is divided into multiple sub-areas. Each sub-area includes computing nodes 102 and perception nodes 103.

[0065] Each sub-area corresponds to a first node, which is a computing node 102 in the sub-area. The first node is connected to other computing nodes 102 in the sub-area, and the computing node 102 is connected to one or more sensing nodes 103. The first node is connected to the sensing network element 101 through a transmission network.

[0066] It should be noted that the computing node 102 as the first node can also be connected to one or more sensing nodes 103.

[0067] The first node is configured to determine a perception result of the managed sub-area and send the perception result to the perception network element 101 .

[0068] The perception network element 101 is configured to receive multiple perception results from multiple first nodes, and determine a perception result of a perception area based on the perception results in multiple sub-areas.

[0069] Each perception result represents the perception result in the sub-area managed by the corresponding first node. The perception area includes multiple sub-areas. The first node corresponding to the sub-area is used to manage the perception nodes 103 and computing nodes 102 in the sub-area.

[0070] In one implementation, the perception network element 101 is further configured to send a first request message to multiple first nodes.

[0071] The first node is further configured to receive a first request message sent by the perception network element 101 and trigger the perception node 103 in the sub-area managed by the first node to perform perception detection.

[0072] The first request message is used to request the first node to trigger the perception node 103 in the sub-area managed by the first node to perform perception detection.

[0073] In this way, the perception network element 101 can determine the perception area based on the perception requirements of the application layer, thereby determining multiple sub-areas included in the perception area, and instruct the first nodes corresponding to the multiple sub-areas to trigger perception detection of the perception nodes 103 in the sub-areas.

[0074] Exemplarily, the perception network element 101 is further configured to send a resource configuration message to multiple first nodes.

[0075] The first node is further configured to receive a resource configuration message sent by the perception network element 101 .

[0076] The resource configuration message is used to configure the sensing resources of the computing nodes 102 and sensing nodes 103 in the sub-area. The sensing resources include signal resources in the time domain, frequency domain, beam and other dimensions, as well as signal transmission and reception mode configuration parameters.

[0077] In one implementation, the perception network element 101 is also used to obtain the coverage capability of each perception node 103 in the perception network and the computing capability of each computing node 102, and based on the coverage capability of each perception node 103 in the perception network and the computing capability of each computing node 102, the coverage range of the perception network is divided into multiple sub-areas.

[0078] In each of the multiple sub-areas, there is at least one computing node 102 and at least one sensing node 103 .

[0079] In one implementation, there is no uncovered area or overlapping area between any two adjacent sub-areas.

[0080] In other words, the sub-regions in this disclosure are seamlessly connected, with no coverage gaps or overlaps between sub-regions within the coverage area of ​​the sensing network. Therefore, the objects sensed by the sensing node 103 always belong to a particular sub-region, making it easier for the first node in each sub-region to manage and maintain the sensed objects.

[0081] For example, the sub-area can be a standard polygon, such as a cuboid, a triangular prism, a hexagonal prism, etc. As shown in FIG2 , the coverage area of ​​the sensing network is divided into four cuboid-shaped sub-areas ( FIG2 is a top-down view and does not reflect height information).

[0082] In this way, the perception network element 101 can define the location information of the sub-area based on the vertex coordinates of the standard polygon, such as shape, position, coverage, etc., to facilitate seamless connection between sub-areas and segmentation of the perception network.

[0083] The height of the sub-area can be set according to actual needs, for example, by setting a minimum height and a maximum height to determine the height of the sub-area.

[0084] The sub-areas may also be divided in other ways as long as there are coverage gaps between the sub-areas and there is no overlap between the sub-areas. This disclosure does not limit this.

[0085] For example, the sub-areas in the present disclosure may be divided in a horizontal dimension or in a vertical dimension.

[0086] In one implementation, the coverage area of ​​the sensing network can be divided into multiple sub-areas in the horizontal dimension. The division method can refer to the above description.

[0087] In another implementation, the coverage area of ​​the sensing network is divided into multiple layers vertically, and each layer is divided into one or more sub-areas horizontally. This allows signal sensing to be performed in service areas with special terrain, such as high-rise buildings like office buildings, using the technical solutions provided in this disclosure.

[0088] Exemplarily, the perception network element 101 may perform a sub-area division operation in an initialization phase or in a sub-area change phase. In addition, after performing the sub-area division, the perception network element 101 may further allocate a first node to each sub-area.

[0089] In one implementation, the perception network element 101 is also used to, when there is only one computing node 102 in the sub-area, use the computing node 102 as the first node corresponding to the sub-area; when there are multiple computing nodes 102 in the sub-area, select one computing node 102 from the multiple computing nodes 102 as the first node corresponding to the sub-area based on the location information of the multiple computing nodes 102.

[0090] Exemplarily, the perception network element 101 can determine the transmission link distance between each computing node 102 and the transmission link distance between the computing node 102 and the perception node 103, and thus determine the first node corresponding to the sub-area based on the transmission link distance, that is, select the computing node 102 with a shorter transmission link distance with other computing nodes 102 and a shorter transmission link distance with the perception node 103 as the first node, thereby ensuring data transmission efficiency.

[0091] Exemplarily, the perception network element 101 can also determine the coverage range of the perception node 103 to which each computing node 102 is connected, and use the computing node 102 whose coverage overlaps the largest area with the corresponding sub-area as the first node of the sub-area, thereby reducing the interaction requirements between the computing nodes 102.

[0092] In one implementation, the perception network element 101 may also determine the computing resource requirements of the first node corresponding to each sub-area based on the task category of the perception computing, for example, the perception computing task includes deduplication of targets in overlapping areas of the perception areas.

[0093] In one implementation, the perception network element 101 is further configured to send sub-area information to the first node corresponding to each sub-area.

[0094] The first node is further configured to receive the sub-area information sent by the perception network element 101 .

[0095] The sub-region information includes the identifier of each sub-region and the range information of each sub-region.

[0096] Exemplarily, the range information of the sub-region may be represented by vertex coordinates of the sub-region.

[0097] In one implementation, the first node is further configured to send the perception detection data of the perception target to the first nodes corresponding to the other sub-areas when the perception detection data indicates that the perception target is located in the other sub-areas.

[0098] The perception detection data includes at least one of the following: the identification of the perception target, longitude and latitude information, altitude, distance, speed, acceleration, azimuth, pitch angle, type of the perception target, signal strength of the perception target, and signal-to-noise ratio of the perception target. It should be noted that since the coverage area of ​​the perception node 103 is not directly related to the division of the sub-areas, the coverage area of ​​the perception node 103 may cover other sub-areas. Therefore, the perception target perceived by the first node may also be located in other sub-areas. At this time, the first node can send the data information related to the perception target to the first node corresponding to the other sub-areas, so that the first node corresponding to the other sub-areas can perform fusion processing on the data of the perception target.

[0099] For example, the first nodes corresponding to the other sub-areas perform data fusion processing on the sensing target and report it to the sensing network element 101. At the same time, they return the processed data information to the first node of the original sub-area. At this point, the first node of the original sub-area can send the sensing result to the sensing network element 101 within a preset time.

[0100] In one implementation, the first node is further configured to send abnormality alarm information to the perception network element 101 when an abnormality occurs in the first node.

[0101] The perception network element 101 is used to receive abnormal alarm information sent by the first node.

[0102] It should be noted that when an abnormal situation occurs, the first node cannot work normally. At this time, it can be determined whether the first node of the adjacent sub-area has computing power redundancy. When there is no computing power redundancy, the first node can send an abnormal alarm information to the perception network element 101, thereby indicating that the sub-area managed by the first node is an invalid area.

[0103] The first node is further configured to send a second request message to an adjacent first node when an abnormality occurs on the first node. The second request message is used to request the adjacent first node to assist in managing the sub-area corresponding to the first node.

[0104] When computing power is redundant in a first node in an adjacent sub-region, the first node can send a request message to the adjacent first node to request assistance in managing the sub-region to which the first node corresponds. At this point, the adjacent first node can establish a transmission link with other computing nodes 102 and sensing nodes 103 in the sub-region to uniformly handle sensing tasks for the sub-region and its own corresponding sub-region.

[0105] In the case where the perception node 103 cannot work normally, the first node is used to treat the coverage area corresponding to the perception node 103 as an invalid area and send abnormal alarm information to the perception network element 101.

[0106] In one implementation, the adjacent first node is further configured to send a third request message to the first node when an abnormality occurs in the adjacent first node.

[0107] Correspondingly, the first node is configured to receive the third request message sent by the adjacent first node.

[0108] The third request message is used to request the first node to assist in managing the sub-area corresponding to the adjacent first node.

[0109] The first node is further configured to determine a target perception result based on the perception detection data of the perception nodes 103 in the sub-area corresponding to the first node and the sub-area corresponding to the adjacent first node, and send the target perception result to the perception network element 101 .

[0110] The following describes the perception communication system provided by the present disclosure in combination with scenarios.

[0111] As shown in FIG3 , FIG3 is an architecture diagram of a perception communication system 30 according to some embodiments, corresponding to the application scenario of rectangular sub-area division and a single computing node.

[0112] The coverage of the sensing network is divided into four sub-areas, which can be represented by {sub-area #1, sub-area #2, sub-area #3, sub-area #4}, and each sub-area is a rectangular parallelepiped.

[0113] Each sub-region meets the following characteristics:

[0114] 1. The shape of the sub-region is a standard polyhedron;

[0115] 2. Seamless connection between perception grids, that is, there are no coverage holes between sub-areas within the coverage of the perception network, and there is no overlap;

[0116] 3. There is a one-to-one correspondence between the sub-region and the first node.

[0117] Exemplarily, the one-to-one mapping relationship between the sub-area and the first node can be expressed as: {{sub-area #1: computing node #1}; {sub-area #2: computing node #2}; {sub-area #3: computing node #3}; {sub-area #4: computing node #4}}. Since there is only one computing node in each sub-area, the computing node is the first node corresponding to the sub-area.

[0118] The first node corresponding to each sub-area maintains information about the sub-areas within the sensing network's coverage area. For example, computing node #1 maintains information about {{sub-area #1: computing node #1}; {sub-area #2: computing node #2}; {sub-area #3: computing node #3}; {sub-area #4: computing node #4}}. When sub-area information is generated and updated, the first node corresponding to each sub-area also needs to be generated and updated.

[0119] Exemplarily, the dotted box in Figure 3 represents the perception area that needs to be perceived, involving 4 sub-areas. The perception network element determines based on the perception area that the above-mentioned computing node #1, computing node #2, computing node #3, and computing node #4 all need to perform perception detection.

[0120] For example, when computing node #1 detects a target within the subarea corresponding to computing node #2, it sends the target's detection data to computing node #2. Computing node #2 fuses the target's detection data and reports the fused results to the sensing network element. It also returns the fused results to computing node #1. Computing node #1 does not need to report this data.

[0121] The first node corresponding to each sub-area only reports the perception results within the sub-area it manages. For example, computing node #1 only reports the perception results within sub-area #1. The perception network element obtains the perception results of each sub-area and then splices them to obtain the perception results of the perception area corresponding to the perception requirement.

[0122] When computing node #1 fails to work properly and computing node #2 has redundant computing resources, computing node #2 can establish a transmission link with each perception node under sub-area #1 and merge sub-area #1 and sub-area #2 into one sub-area.

[0123] As shown in FIG4 , FIG4 is an architecture diagram of a perception communication system 40 according to some embodiments, corresponding to the application scenario of rectangular sub-area division and multiple computing nodes.

[0124] The coverage of the sensing network is divided into two sub-areas, which can be represented by {sub-area #1, sub-area #2}, and each sub-area is a rectangular parallelepiped.

[0125] Each sub-region meets the following characteristics:

[0126] 1. The shape of the sub-region is a standard polyhedron;

[0127] 2. Seamless connection between perception grids, that is, there are no coverage holes between sub-areas within the coverage of the perception network, and there is no overlap;

[0128] 3. There is a one-to-one correspondence between the sub-region and the first node.

[0129] Exemplarily, a one-to-one mapping relationship between a sub-region and a first node may be expressed as: {{sub-region #1: computing node #1}; {sub-region #2: computing node #2}}.

[0130] Because there are multiple computing nodes in each sub-area, the sensing network element needs to select a computing node from the multiple computing nodes as the first node corresponding to the sub-area. This first node can be connected to the sensing node or not, serving as a pure computing node.

[0131] The first node corresponding to each sub-area maintains information about the sub-areas within the sensing network's coverage area. For example, Computing Node #1 maintains the information {{Sub-area #1: Computing Node #1}; {Sub-area #2: Computing Node #2}}. When sub-area information is generated and updated, the first node corresponding to each sub-area also needs to be generated and updated.

[0132] Exemplarily, the dotted box in FIG4 represents a perception area that needs to be perceived, involving two sub-areas. The perception network element determines that both computing node #1 and computing node #2 need to perform perception detection based on the perception area.

[0133] For example, when computing node #1 detects a target within the subarea corresponding to computing node #2, it sends the target's detection data to computing node #2. Computing node #2 fuses the target's detection data and reports the fused results to the sensing network element. It also returns the fused results to computing node #1. Computing node #1 does not need to report this data.

[0134] The first node corresponding to each sub-area only reports the perception results within the sub-area it manages. For example, computing node #1 only reports the perception results within sub-area #1. The perception network element obtains the perception results of each sub-area and then splices them to obtain the perception results of the perception area corresponding to the perception requirement.

[0135] When some of the sensing nodes under computing node #1 are damaged and cannot work, computing node #1 regards the coverage areas corresponding to these sensing nodes as invalid areas and reports abnormal alarm information to the sensing network element.

[0136] As shown in FIG5 , FIG5 is an architecture diagram of a perception communication system 50 according to some embodiments, corresponding to the application scenario of hexagonal prism sub-area division and a single computing node.

[0137] The coverage area of ​​the sensing network is divided into multiple hexagonal prism-shaped sub-areas.

[0138] Each of the multiple sub-regions satisfies the following characteristics:

[0139] 1. The shape of the sub-region is a standard polyhedron;

[0140] 2. Seamless connection between perception grids, that is, there are no coverage holes between sub-areas within the coverage of the perception network, and there is no overlap;

[0141] 3. There is a one-to-one correspondence between the sub-region and the first node.

[0142] Exemplarily, the sub-regions are mapped one-to-one to the first nodes. Since there is only one computing node in each sub-region, the computing node is the first node corresponding to the sub-region.

[0143] The first node corresponding to each sub-area will maintain the sub-area information within the coverage area of ​​the sensing network. When the sub-area information is generated and updated, the first node corresponding to each sub-area also needs to be generated and updated.

[0144] Exemplarily, the dotted box in FIG5 represents a sensing area that needs to be sensed, and the sensing network element determines each first node that needs to perform sensing detection based on the sensing area.

[0145] For example, when computing node #1 detects a target within the subarea corresponding to computing node #2, it sends the target's detection data to computing node #2. Computing node #2 fuses the target's detection data and reports the fused results to the sensing network element. It also returns the fused results to computing node #1. Computing node #1 does not need to report this data.

[0146] The first node corresponding to each sub-area only reports the perception results within the sub-area it manages. For example, computing node #1 only reports the perception results within sub-area #1. The perception network element obtains the perception results of each sub-area and then splices them to obtain the perception results of the perception area corresponding to the perception requirement.

[0147] As shown in FIG6 , FIG6 is an architecture diagram of a perception communication system 60 according to some embodiments, corresponding to the application scenario of rectangular sub-area division and a single computing node.

[0148] Compared to the perception communication system 30 shown in FIG3 , the perception communication system 60 shown in FIG6 has a larger number of computing nodes, a smaller number of perception nodes, and a larger number of sub-areas divided by perception network elements. All other details are similar to those of the perception communication system 30 and are not described here.

[0149] It should be pointed out that the various embodiments of the present disclosure can refer to each other, for example, the same or similar steps, method embodiments, system embodiments and device embodiments can refer to each other, and the embodiments of the present disclosure are not limited thereto.

[0150] FIG7 is a flow chart of a perception processing method according to some embodiments. As shown in FIG7 , the method includes: Step 701 to Step 702 .

[0151] Step 701: A perception network element receives multiple perception results from multiple first nodes.

[0152] Each perception result represents a perception result in a sub-area managed by the corresponding first node. The first node corresponding to the sub-area is used to manage the perception nodes and computing nodes in the sub-area.

[0153] It should be noted that the coverage of the perception network is composed of multiple sub-areas, and there is no uncovered area or overlapping area between any two adjacent sub-areas. In other words, the sub-areas in this disclosure are seamlessly connected, and there are no coverage holes or overlaps between sub-areas within the coverage of the perception network.

[0154] For example, the sub-regions can be standard polygons, such as cuboids, triangular prisms, hexagonal prisms, etc. In this way, the sensing network element can define the location information of the sub-regions, such as shape, position, coverage, etc., based on the vertex coordinates of the standard polygons, to facilitate seamless connection between sub-regions and segmentation of the sensing network.

[0155] The height of the sub-area can be set according to actual needs, for example, by setting a minimum height and a maximum height to determine the height of the sub-area.

[0156] The sub-areas may also be divided in other ways as long as there are coverage gaps between the sub-areas and there is no overlap between the sub-areas. This disclosure does not limit this.

[0157] For example, the sub-areas in the present disclosure may be divided in a horizontal dimension or in a vertical dimension.

[0158] In one implementation, the coverage area of ​​the sensing network can be divided into multiple sub-areas in the horizontal dimension. The division method can refer to the above description.

[0159] In another implementation, the coverage area of ​​the sensing network is divided into multiple layers vertically, and each layer is divided into one or more sub-areas horizontally. This allows signal sensing to be performed in service areas with special terrain, such as high-rise buildings like office buildings, using the technical solutions provided in this disclosure.

[0160] Step 702: The sensing network element determines a sensing result of the sensing area based on the sensing results in the multiple sub-areas.

[0161] The perception area consists of multiple sub-areas.

[0162] In one implementation, the perception network element may determine the perception area according to the perception requirement.

[0163] It should be noted that the perception area has no direct relationship with the sub-areas divided into which the coverage area of ​​the perception network is divided. The perception area is determined by the perception network element based on current needs. When there is a perception demand, the perception network element can determine the relevant perception area based on the perception demand. In this way, the perception network element can instruct the first nodes corresponding to the multiple sub-areas covered by the perception area to perform relevant perception detection operations, thereby obtaining corresponding perception results.

[0164] Based on the above technical solution, the present disclosure can divide the perception network into regions using a perception grid. Since each sub-region corresponds to a first node, the perception network element can obtain the perception results within the corresponding sub-region from the multiple first nodes involved, and determine the perception results of the perception region based on the perception results of the multiple sub-regions. In this way, the technical solution proposed by the present disclosure can flexibly perform perception operations to cope with various synaesthesia computing scenarios, thereby improving the perception effect.

[0165] The following describes a process in which the perception network element instructs the first node to perform perception detection.

[0166] As an embodiment of the present disclosure, in combination with FIG. 7 , as shown in FIG. 8 , before the above step 701 , the method further includes step 801 .

[0167] Step 801: The perception network element sends a first request message to multiple first nodes.

[0168] The first request message is used to request the first node to trigger the perception nodes in the sub-area managed by the first node to perform perception detection.

[0169] Exemplarily, when a transmission link exists between the first node and the perception node, after receiving the first request message, the first node may directly instruct the perception node to perform perception detection.

[0170] When the first node establishes a connection with the perception node through other computing nodes, the first node can instruct the perception node to perform perception detection through the other computing nodes.

[0171] In one implementation, the perception network element may also send resource configuration messages to multiple first nodes.

[0172] Resource configuration messages are used to configure the sensing resources of computing nodes and sensing nodes within a sub-area. For example, sensing resources include signal resources in the time domain, frequency domain, beamformation, and other dimensions, as well as signal transmission and reception mode configuration parameters.

[0173] The following describes the process of dividing the sensing network elements into regions.

[0174] As an embodiment of the present disclosure, in combination with FIG. 7 , as shown in FIG. 9 , the method further includes steps 901 and 902 .

[0175] Step 901: The sensing network element obtains the coverage capability of each sensing node and the computing capability of each computing node in the sensing network.

[0176] The coverage capability of a sensing node refers to the maximum range within which it can perceive a target. The greater the coverage capability of a sensing node, the greater its target perception range and the larger the sub-areas that can be divided into sensing network elements. The greater the computing power of a computing node, the greater the amount of sensing detection data it can process and the greater the number of sensing nodes it can manage.

[0177] Step 902: The sensing network element divides the coverage area of ​​the sensing network into multiple sub-areas based on the coverage capability of each sensing node and the computing capability of each computing node in the sensing network.

[0178] Each sub-area has at least one computing node and at least one sensing node.

[0179] It should be noted that the present disclosure does not limit the execution order of steps 901 to 902 and steps 701 to 702 above. The perception network element can perform sub-area division operations during the initialization phase or during the sub-area change phase. For example, as shown in Figure 9, when the perception network element performs sub-area division during the initialization phase, steps 901 to 902 above are performed before step 701. Steps 901 to 902 above can also be performed at any other time, and this disclosure does not limit this.

[0180] In addition, after dividing the sub-areas, the sensing network element may also allocate a first node to each sub-area.

[0181] As an embodiment of the present disclosure, in combination with FIG9 , as shown in FIG10 , the method further includes steps 1001 to 1002 .

[0182] Step 1001: When there is only one computing node in a sub-area, the sensing network element uses the computing node as the first node corresponding to the sub-area.

[0183] Step 1002: When there are multiple computing nodes in the sub-area, the sensing network element selects one computing node from the multiple computing nodes as the first node corresponding to the sub-area based on location information of the multiple computing nodes.

[0184] Exemplarily, the perception network element can determine the transmission link distance between each computing node and the transmission link distance between the computing node and the perception node, and thus determine the first node corresponding to the sub-area based on the transmission link distance, that is, select the computing node with a shorter transmission link distance with other computing nodes and a shorter transmission link distance with the perception node as the first node, thereby ensuring data transmission efficiency.

[0185] Exemplarily, the perception network element may also determine the coverage of the perception nodes to which each computing node is connected, and use the computing node whose coverage overlaps the largest area with the corresponding sub-area as the first node of the sub-area, thereby reducing the need for interaction between computing nodes.

[0186] In one implementation, the sensing network element sends sub-area information to a first node corresponding to each sub-area.

[0187] The sub-region information includes the identifier of each sub-region and the range information of each sub-region.

[0188] Based on the above technical solution, when the perception network is initialized or when the perception network needs regional update, the perception network element can divide the perception network into sub-areas and assign corresponding first nodes to the divided sub-areas, thereby enabling flexible expansion and scaling of the perception network to adapt to various perception scenarios, thereby improving the perception effect.

[0189] FIG11 is a flow chart of a perception processing method according to some embodiments. As shown in FIG11 , the method includes steps 1101 to 1103 .

[0190] Step 1101: The first node obtains sensing detection data of sensing nodes in the managed sub-area.

[0191] The perception detection data includes at least one of the following: the identification, latitude and longitude information, altitude, distance, speed, acceleration, azimuth, pitch angle, type of the perception target, signal strength of the perception target, and signal-to-noise ratio of the perception target.

[0192] Exemplarily, when a transmission link exists between the first node and the sensing node, the first node may receive sensing detection data from the sensing node.

[0193] When the first node establishes a connection with the perception node through other computing nodes, the first node can obtain the perception detection data of the perception node connected to the other computing nodes through the other computing nodes.

[0194] In one implementation, after receiving the first request message sent by the perception network element, the first node triggers the perception nodes in the managed sub-area to perform perception detection.

[0195] The first request message is used to request the first node to trigger the perception nodes in the sub-area managed by the first node to perform perception detection.

[0196] Step 1102: When the perception detection data indicates that the perception target is located in the sub-area managed by the first node, the first node determines a perception result of the sub-area based on the perception detection data.

[0197] Because the coverage areas of sensing nodes may overlap, the first node may obtain multiple sensing detection data for the same sensing target. Therefore, after obtaining the sensing detection data, the first node can fuse the sensing detection data to determine the sensing result for the sub-area. This not only eliminates ambiguity in the sensing results, but also improves sensing accuracy.

[0198] It should be noted that since the coverage area of ​​a sensing node is not directly related to the division of sub-areas, the coverage area of ​​a sensing node may cover other sub-areas. Therefore, the sensing target sensed by the first node may also be located in other sub-areas.

[0199] In one implementation, when the perception detection data indicates that the perception target is located in other sub-areas, the first node sends the perception detection data to the first nodes corresponding to the other sub-areas.

[0200] For example, the first nodes corresponding to the other sub-areas perform data fusion processing on the perceived target and report it to the perception network element. They also return the processed data to the first node in the original sub-area. The first node in the original sub-area can then send the perception results to the perception network element within a preset time. In this way, the first nodes corresponding to the other sub-areas can perform fusion processing based on the perceived detection data to improve perception accuracy.

[0201] Step 1103: The first node sends the perception result to the perception network element.

[0202] Based on the above technical solution, the first node in this disclosure can obtain perception detection data from the perception nodes within the managed sub-area, process the perception detection data, determine the perception result of the sub-area, and send the perception result to the perception network element. In this way, the technical solution proposed in this disclosure can flexibly perform perception operations to cope with various synaesthesia computing scenarios, thereby improving perception effects.

[0203] The following describes the exception handling process of the first node.

[0204] As an embodiment of the present disclosure, in combination with 11, as shown in FIG12 , the method further includes step 1201 .

[0205] Step 1201: When an abnormality occurs on the first node, the first node sends abnormality alarm information to the perception network element.

[0206] The abnormal alarm information is used to indicate that the sub-area corresponding to the first node is an invalid area.

[0207] In one implementation, when a sensing node in a sub-area corresponding to a first node experiences an abnormality, the first node treats the coverage area corresponding to the sensing node as an invalid area and may also report the abnormality alarm information to a sensing network element.

[0208] It should be noted that when an abnormal situation occurs, the first node cannot work normally. At this time, it can be determined whether the first node in the adjacent sub-area has computing power redundancy. When there is no computing power redundancy, the first node can send abnormal alarm information to the perception network element, thereby indicating that the sub-area managed by the first node is an invalid area.

[0209] As an embodiment of the present disclosure, in combination with 11, as shown in FIG13 , the method further includes step 1301 .

[0210] Step 1301: When an abnormality occurs in a first node, a second request message is sent to an adjacent first node.

[0211] The second request message is used to request the adjacent first node to assist in managing the sub-area corresponding to the first node.

[0212] When computing power is redundant in a first node in an adjacent sub-region, the first node can send a request message to the adjacent first node, requesting assistance in managing the sub-region to which it corresponds. At this point, the adjacent first node can establish a transmission link with other computing nodes and sensing nodes in the sub-region to centrally handle sensing tasks for the sub-region and its own corresponding sub-region.

[0213] For example, the sensing network element may further re-divide the sub-areas after changes occur in the sensing nodes and computing nodes deployed in the sensing network. After the sub-area division is completed, each first node re-acquires the sub-area information to facilitate the sensing detection operation.

[0214] When an adjacent first node is abnormal, the first node may also assist the adjacent first node in managing the corresponding sub-area based on the above method.

[0215] In one implementation, when an abnormality occurs in an adjacent first node, the adjacent first node sends a third request message to the first node. Correspondingly, the first node receives the third request message sent by the adjacent first node.

[0216] The third request message is used to request the first node to assist in managing the sub-area corresponding to the adjacent first node.

[0217] The first node determines a target perception result based on the sensing detection data from the sensing nodes in the sub-area corresponding to the first node and the sub-area corresponding to the adjacent first node, and transmits the target perception result to the sensing network element. The sensing network element, in turn, receives the target perception result sent by the first node. This allows the sensing network element to continue to obtain data from its sub-area to achieve target perception, even if an adjacent first node experiences an anomaly.

[0218] In one implementation, the first node receives sub-area information sent by the perception network element.

[0219] The sub-region information includes the identifier of each sub-region and the range information of each sub-region.

[0220] Based on the above technical solution, after an abnormality occurs, the first node can report the abnormal information to the perception network element, or request the adjacent first node to assist in managing the sub-area corresponding to the first node, thereby avoiding affecting the target perception and ensuring the normal execution of the target perception.

[0221] It is understandable that, in order to implement the above functions, the communication device includes hardware structures and / or software modules corresponding to the execution of each function. It should be readily apparent to those skilled in the art that, in conjunction with the algorithmic steps of the various examples described in the embodiments of the present disclosure, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present disclosure.

[0222] The embodiments of the present disclosure can divide the functional modules of the communication device according to the above-mentioned method embodiments. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one functional module. The above-mentioned integrated modules can be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiments of the present disclosure is schematic and is only a logical functional division. In actual implementation, there may be other division methods. The following is an example of dividing each functional module corresponding to each function.

[0223] For example, taking the communication device as the perception network element in the above method embodiment as an example, Figure 14 is a structural diagram of a perception network element according to some embodiments. The perception network element can execute the perception processing method provided in the above method embodiment. As shown in Figure 14, the perception network element 140 includes: a processing unit 1401 and a communication unit 1402.

[0224] The communication unit 1402 is configured to receive multiple perception results from multiple first nodes, where each perception result in the multiple perception results represents a perception result in a sub-area managed by the corresponding first node.

[0225] The processing unit 1401 is configured to determine a perception result of a perception area based on the perception results in the multiple sub-areas, where the perception area includes the multiple sub-areas.

[0226] In some embodiments, the first node corresponding to the sub-area is used to manage the sensing nodes and computing nodes in the sub-area.

[0227] In some embodiments, the communication unit 1402 is used to send a first request message to multiple first nodes, where the first request message is used to request the first node to trigger the perception nodes in the sub-area managed by the first node to perform perception detection.

[0228] In some embodiments, the communication unit 1402 is used to obtain the coverage capability of each perception node and the computing capability of each computing node in the perception network; the processing unit 1401 is used to divide the coverage range of the perception network into multiple sub-areas based on the coverage capability of each perception node and the computing capability of each computing node in the perception network, and each sub-area has at least one computing node and at least one perception node.

[0229] In some embodiments, the processing unit 1401 is used to use the computing node as the first node corresponding to the sub-area when there is only one computing node in the sub-area; the processing unit 1401 is used to select a computing node from multiple computing nodes as the first node corresponding to the sub-area based on the location information of the multiple computing nodes when there are multiple computing nodes in the sub-area.

[0230] In some embodiments, the communication unit 1402 is configured to send sub-region information to the first node corresponding to each sub-region, where the sub-region information includes an identifier of each sub-region and range information of each sub-region.

[0231] In some embodiments, there is neither uncovered area nor overlapping area between any two adjacent sub-areas.

[0232] In some embodiments, the coverage area of ​​the sensing network is divided into multiple sub-areas in the horizontal dimension.

[0233] In some embodiments, the coverage of the perception network is divided into multiple layers in a vertical dimension, and each of the multiple layers is divided into one or more sub-areas in a horizontal dimension.

[0234] Taking the perception communication device as the first node in the above method embodiment as an example, Figure 15 is a structural diagram of a first node according to some embodiments. The first node can perform the perception processing method provided in the above method embodiment. As shown in Figure 15, the first node 150 includes a processing unit 1501 and a communication unit 1502. Communication unit 1502 is configured to obtain perception detection data from perception nodes within the managed sub-area.

[0235] The processing unit 1501 is configured to determine a perception result of the sub-area based on the perception detection data when the perception detection data indicates that the perception target is located in the sub-area managed by the first node.

[0236] The communication unit 1502 is used to send the perception result to the perception network element.

[0237] In some embodiments, the communication unit 1502 is configured to send the perception detection data to the first node corresponding to the other sub-area when the perception detection data indicates that the perception target is located in the other sub-area.

[0238] In some embodiments, the communication unit 1502 is configured to send the perception result to the perception network element within a preset time.

[0239] In some embodiments, the perception detection data includes at least one of the following: identification, latitude and longitude information, altitude, distance, speed, acceleration, azimuth, pitch angle, type of perception target, signal strength of perception target, and signal-to-noise ratio of perception target.

[0240] In some embodiments, the communication unit 1502 is configured to send abnormality alarm information to the perception network element when an abnormality occurs in the first node.

[0241] In some embodiments, the communication unit 1502 is used to send a second request message to an adjacent first node when an abnormality occurs in the first node, where the second request message is used to request the adjacent first node to assist in managing the sub-area corresponding to the first node.

[0242] In some embodiments, the communication unit 1502 is used to receive a third request message sent by an adjacent first node; the third request message is used to request the first node to assist in managing the sub-area corresponding to the adjacent first node; the processing unit 1501 is used to determine the target perception result based on the perception detection data of the perception node in the sub-area corresponding to the first node and the sub-area corresponding to the adjacent first node; the communication unit 1502 is used to send the target perception result to the perception network element.

[0243] In some embodiments, the communication unit 1502 is configured to receive sub-area information sent by a sensing network element, where the sub-area information includes an identifier of each sub-area and range information of each sub-area.

[0244] In the case of implementing the functions of the above-mentioned integrated modules in hardware, the embodiments of the present disclosure provide a structure of the communication device involved in the above-mentioned embodiments. As shown in Figure 16, the communication device 160 includes: a processor 1602 and a bus 1604. In some embodiments, the communication device 160 may also include a memory 1601; in some embodiments, the communication device 160 may also include a communication interface 1603.

[0245] Processor 1602 may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of this disclosure. Processor 1602 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Processor 1602 may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of this disclosure. Processor 1602 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0246] The communication interface 1603 is used to connect to other devices via a communication network, such as Ethernet, wireless access network, or wireless local area network (WLAN).

[0247] The memory 1601 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0248] As an implementation, memory 1601 may exist independently of processor 1602. Memory 1601 may be connected to processor 1602 via bus 1604 to store instructions or program codes. When processor 1602 calls and executes the instructions or program codes stored in memory 1601, the perception processing method provided in the embodiments of the present disclosure can be implemented.

[0249] In another implementation, the memory 1601 may also be integrated with the processor 1602 .

[0250] Bus 1604 can be an Extended Industry Standard Architecture (EISA) bus, etc. Bus 1604 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, FIG16 shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0251] Some embodiments of the present disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium), which stores computer program instructions. When the computer program instructions are executed on a computer, the computer executes the perception processing method described in any of the above embodiments.

[0252] Exemplarily, the above-mentioned computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes, etc.), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memories (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in the present disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0253] An embodiment of the present disclosure provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the perception processing method described in any one of the above embodiments.

[0254] The above is only a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or replacements within the technical scope disclosed in the present disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A perception processing method, comprising: Receiving multiple perception results from multiple first nodes, where each perception result in the multiple perception results represents the perception result within the sub-region managed by the corresponding first node; Determining the perception result of the perception region based on the perception results of each sub-region within the multiple sub-regions, where the perception region includes the multiple sub-regions.

2. The method according to claim 1, wherein The first node corresponding to the sub-region is used to manage the perception nodes and computing nodes within the sub-region.

3. The method according to claim 1, wherein, Before the receiving the multiple perception results from the multiple first nodes, the method further comprises: Sending a first request message to the multiple first nodes, where the first request message is used to request the first nodes to trigger the perception nodes within the sub-regions managed by the first nodes to perform perception detection.

4. The method according to claim 1, further comprising: Obtaining the coverage capabilities of the perception nodes in the perception network and the computing capabilities of the computing nodes; Based on the coverage capabilities of the perception nodes and the computing capabilities of the computing nodes in the perception network, dividing the coverage range of the perception network into multiple sub-regions, where there is at least one computing node and at least one perception node in each sub-region of the multiple sub-regions.

5. The method according to claim 4, further comprising: In the case where there is only one computing node in each sub-region, using the computing node as the first node corresponding to the sub-region; In the case where there are multiple computing nodes in each sub-region, based on the location information of the multiple computing nodes, selecting one computing node from the multiple computing nodes as the first node corresponding to the sub-region.

6. The method according to claim 1, further comprising: Sending sub-region information to the first node corresponding to each sub-region in the multiple sub-regions, where the sub-region information includes the identifier of each sub-region in the multiple sub-regions and the range information of each sub-region in the multiple sub-regions.

7. The method according to claim 1, wherein There is neither an uncovered region nor an overlapping region between any two adjacent sub-regions among the multiple sub-regions.

8. The method according to claim 1, wherein, The coverage range of the perception network is divided into multiple sub-regions in the horizontal dimension.

9. The method according to claim 1, wherein The coverage range of the perception network is divided into multiple layers in the vertical dimension, and each layer in the multiple layers is divided into one or more sub-regions in the horizontal dimension.

10. A perception processing method, wherein, The method is applied to a first node and comprises: Obtaining the perception detection data of the perception nodes within the managed sub-region; In the case where the perception detection data represents that the perception target is within the sub-region managed by the first node, determining the perception result of the sub-region based on the perception detection data; Sending the perception result to the perception network element.

11. The method according to claim 10, further comprising: In the case where the perception detection data represents that the perception target is within other sub-regions, sending the perception detection data to the first node corresponding to the other sub-regions.

12. The method according to claim 11, further comprising: Sending the perception result to the perception network element within a preset time.

13. The method according to claim 11, wherein, The sensed detection data includes at least one of the following: the identifier of the sensed target, longitude and latitude information, altitude, distance, speed, acceleration, azimuth angle, pitch angle, the type of the sensed target, the signal strength of the sensed target, and the signal-to-noise ratio of the sensed target.

14. The method according to claim 10 further includes: When an abnormality occurs in the first node, sending an abnormality warning message to the sensing network element.

15. The method according to claim 10 further includes: When an abnormality occurs in the first node, sending a second request message to an adjacent first node, where the second request message is used to request the adjacent first node to assist in managing the sub-region corresponding to the first node.

16. The method according to claim 10 further includes: Receiving a third request message sent by an adjacent first node; The third request message is used to request the first node to assist in managing the sub-region corresponding to the adjacent first node; Determining a target sensing result based on the sensing detection data of the sensing nodes in the sub-region corresponding to the first node and the sub-region corresponding to the adjacent first node; Sending the target sensing result to the sensing network element.

17. The method according to claim 10 further includes: Receiving sub-region information sent by the sensing network element, where the sub-region information includes the identifiers of the sub-regions and the range information of the sub-regions.

18. A sensing communication system includes: A first node, configured to determine the sensing result of the managed sub-region; Sending the sensing result to the sensing network element; The sensing network element is configured to receive multiple sensing results from multiple first nodes; and based on the sensing results in multiple sub-regions, determine the sensing result of the sensing region, where the sensing region includes the multiple sub-regions.

19. A communication device includes a memory and a processor; the memory is coupled to the processor; the memory is used to store instructions executable by the processor; when the processor executes the instructions, it executes the method according to any one of claims 1 to 9, or the method according to any one of claims 10 to 17.

20. A computer-readable storage medium, wherein, Computer program instructions are stored in the computer-readable storage medium, and when the computer program instructions run on the computer, the computer is caused to execute the method according to any one of claims 1 to 9, or the method according to any one of claims 10 to 17.

Images