Electronic device, method for a communication-cognition integrated system, and computer-readable storage medium

Abstract

The present disclosure relates to an electronic device, a method for a communication and sensing integrated system, and a computer readable storage medium. The electronic device includes at least one processor and at least one memory including computer program code. The at least one memory and the computer program code are configured to, with the at least one processor, cause the electronic device to perform: in response to a sensing result of a particular target among sensing targets being wrong using a first sensing signal, transmitting a cooperative sensing request to other electronic devices in order to sense the particular target using a second sensing signal based on information related to the particular target provided by the other electronic devices.

Description

Technical Field

[0001] This disclosure generally relates to the field of wireless communication, and more specifically to electronic devices and methods for integrated communication and sensing systems. More specifically, it relates to electronic devices and methods for multi-target sensing based on sensing cooperation within integrated communication and sensing systems. Background Technology

[0002] Integrated Communication and Sensing (ISAC, sometimes referred to herein as "Sensing Integration") is an emerging technology that integrates wireless communication and sensing capabilities. It utilizes the propagation characteristics of radio waves to depict and reconstruct the physical world, enabling sensing networks. Through the synergy of network sensing and terminal sensing, the entire physical world covered by the network can be modeled, providing sensing-assisted communication and communication-assisted sensing. Wireless sensing technologies acquire information about remote objects or environments and their characteristics without physical contact. 3GPP TR 22.837 provides use case scenarios and corresponding service requirements based on NR (New Radio) sensing, such as object (drone / human / vehicle) detection and tracking, environmental monitoring, and motion detection.

[0003] Currently, integrated communication and sensing technologies are increasingly being applied in fields such as low-altitude economy, vehicle-to-everything (V2X) communication, breath detection, posture recognition, and digital environmental reconstruction. Among these, target perception and tracking are fundamental to applications such as drones, intelligent transportation, and urban security. However, target perception and tracking still face many challenges, such as signal interference, target loss, and energy efficiency management.

[0004] For example, multi-target perception and tracking in target perception face serious interference problems. In one possible scenario, the echo signals generated by the direct reflection of the perceived signal from the target and the reflection of the perceived signal from environmental objects are very complex, posing a significant challenge to distinguishing echo signals from different targets. In scenarios where the distance between multiple tracked targets is relatively short, fading effects occur, leading to confusion between echo signals from different targets and a decrease in perception accuracy. Summary of the Invention

[0005] A brief overview of the invention is given below to provide a basic understanding of certain aspects of it. It should be understood that this overview is not an exhaustive summary of the invention. It is not intended to identify key or essential parts of the invention, nor is it intended to limit the scope of the invention. Its purpose is merely to present certain concepts in a simplified form as a prelude to the more detailed description that follows.

[0006] According to one aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured, via the at least one processor, to cause the electronic device to: in response to an error in the perception result of a specific target among the perception targets using a first sensing signal, send a collaborative sensing request to another electronic device to perceive the specific target using a second sensing signal based on feedback information provided by the other electronic device, including information related to the specific target.

[0007] According to another aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured, via the at least one processor, to cause the electronic device to perform: in the event that a source sensing electronic device errs in its perception of a specific target among sensing targets using a first sensing signal, the electronic device, in response to a collaborative sensing request sent by the source sensing electronic device, provides the source sensing electronic device with perceived feedback information, including information related to the specific target, such that the source sensing electronic device perceives the specific target using a second sensing signal based on the information related to the specific target.

[0008] According to another aspect of this disclosure, a method for a communication-sensing integrated system is provided, comprising: in response to an error in the sensing result of a specific target among sensing targets using a first sensing signal, a source sensing electronic device sends a collaborative sensing request to other sensing electronic devices to sense the specific target using a second sensing signal based on feedback information provided by the other sensing electronic devices, including information related to the specific target.

[0009] According to another aspect of this disclosure, a method for an integrated communication and sensing system is provided, comprising: when a source sensing electronic device makes an error in sensing a specific target among sensing targets using a first sensing signal, another sensing electronic device responds to a collaborative sensing request sent by the source sensing electronic device by providing the source sensing electronic device with feedback information that has been sensed and includes information related to the specific target, so that the source sensing electronic device senses the specific target using a second sensing signal based on the information related to the specific target.

[0010] In accordance with other aspects of this disclosure, computer program code and computer program products for implementing the above methods, as well as a computer-readable storage medium having the computer program code for implementing the above methods recorded thereon, are also provided.

[0011] The electronic devices, methods, and computer storage media for integrated sensing systems proposed in this disclosure solve one or more of the problems existing in the prior art by coordinating sensing through multiple sensing nodes when the sensing result is incorrect. They can achieve at least one of the following technical effects: improve the accuracy of target detection and tracking (including single target detection and tracking and multiple target detection and tracking), reduce power consumption, support multiple sensing coordination methods to adapt to different application scenarios, enhance the robustness of the system and its adaptability to environmental changes, and save bandwidth resources by utilizing semantic communication. Attached Figure Description

[0012] To further illustrate the above and other advantages and features of the present invention, specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. The accompanying drawings, together with the following detailed description, are included in and form a part of this specification. Elements having the same function and structure are indicated by the same reference numerals. It should be understood that these drawings only depict typical examples of the invention and should not be construed as limiting the scope of the invention. In the drawings:

[0013] Figure 1 This illustration schematically depicts a scenario where a target is lost during multi-target tracking in a communication-sensing integrated system.

[0014] Figure 2 An exemplary functional block diagram of an electronic device according to one embodiment of the present disclosure is shown;

[0015] Figure 3A An example of a processing flow for collaborative sensing among multiple sensing nodes according to one embodiment of the present disclosure is shown.

[0016] Figure 3B An example of a processing flow for collaborative sensing among multiple sensing nodes according to another embodiment of the present disclosure is shown;

[0017] Figure 4 An exemplary functional block diagram of an electronic device according to another embodiment of the present disclosure is shown;

[0018] Figure 5 A flowchart of a method for a communication-sensing integrated system according to one embodiment of the present disclosure is shown;

[0019] Figure 6 A flowchart of a method for a communication-sensing integrated system according to another embodiment of the present disclosure is shown;

[0020] Figure 7 This is a block diagram illustrating a first example of a schematic configuration of an eNB or gNB to which the technologies of this disclosure can be applied;

[0021] Figure 8 This is a block diagram illustrating a second example of a schematic configuration of an eNB or gNB to which the technologies of this disclosure can be applied;

[0022] Figure 9 This is a block diagram illustrating an example of a schematic configuration of a smartphone to which the technologies of this disclosure can be applied;

[0023] Figure 10 This is a block diagram illustrating an example of a schematic configuration of a car navigation device to which the technology of this disclosure can be applied; and

[0024] Figure 11 This is a block diagram of an exemplary structure of a general-purpose personal computer in which methods and / or apparatus and / or systems according to embodiments of the present invention can be implemented. Detailed Implementation

[0025] Exemplary embodiments of the invention will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of actual embodiments are described in the specification. However, it should be understood that many implementation-specific decisions must be made during the development of any such actual embodiment in order to achieve the developer's specific goals, such as complying with constraints related to the system and business, and these constraints may vary depending on the implementation. Furthermore, it should be understood that while development work can be very complex and time-consuming, such development work is merely a routine task for those skilled in the art who benefit from this disclosure.

[0026] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the device structure and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0027] In this disclosure, the terms "node" and "unit" refer to specific functional modules or entities deployed in an integrated communication and sensing system that are capable of performing specific functions. Furthermore, in the following description of specific embodiments, specific signaling and signals such as RRC signaling, sidelink Mode 2, RSRP (Reference Information Received Power), and RSRQ (Reference Information Received Quality) are mentioned in some scenarios. However, this disclosure is not limited to these; any signaling flow suitable for completing the collaborative sensing tasks of this disclosure should be considered to be within the scope of this disclosure.

[0028] In an integrated communication and sensing system, a Transmission and Receipt Point (TRP) can provide both communication services (sometimes called communication tasks) and sensing services (sometimes called sensing tasks). The nodes (or units) participating in sensing tasks can be base stations and / or User Equipment (UEs). For example, a base station is a specific implementation of a TRP. In D2D interaction scenarios, such as in Vehicle-to-Everything (V2X) networks, the vehicle, acting as a UE, can also be considered to provide both communication and sensing services. A sensing function management unit, which provides sensing service management functions, can be a sensing function (SF) unit deployed on the base station side or the core network side to uniformly manage sensing units within a given sensing service range. Application function (AF) units can be internal operator application functions or trusted third-party application functions. They can send sensing task requests to the sensing function management unit, which then allocates the sensing tasks to the base station and / or UE.

[0029] Based on the distribution of the sensing signal transmitters and receivers, there are three sensing modes: Mono-static sensing: the sensing transmitter and receiver are deployed on the same entity; Bi-static sensing: the sensing transmitter and receiver are deployed on different entities; and Multi-static sensing: multiple transmitters and receivers participate in sensing together.

[0030] Figure 1 This diagram illustrates a scenario where target loss occurs in a multi-base sensing mode when base station 1 is performing multi-target tracking in a communication-sensing integrated system. Figure 1 In the scenario shown, when base station 1 simultaneously tracks target 1 and target 2 (shown as triangles in the figure) using sensing signals, the paths of their sensing and echo signals almost overlap due to the close proximity of targets 1 and 2. This prevents base station 1 from distinguishing between the two targets based on their respective echo signals. In this case, the number of targets in base station 1's sensing results decreases, leading to target loss. However, as... Figure 1 As shown, base station 2 and UE can receive echo signals that can distinguish between target 1 and target 2. Therefore, base station 1 can request base station 2 and / or UE to perform collaborative sensing, thereby improving the accuracy of the sensing results.

[0031] Those skilled in the art will understand that, although Figure 1The example shows a scenario where target 1 and target 2 are too close together, but there are also scenarios where target 1 or target 2 cannot be perceived due to factors such as the background environment, resulting in target loss.

[0032] Figure 2 An exemplary functional block diagram of an electronic device 200 according to one embodiment of the present disclosure is shown.

[0033] like Figure 2 As shown, the electronic device 200 includes a processing unit 202 configured to send a collaborative sensing request to other electronic devices in response to an error in the sensing result of a specific target among the sensing targets using a first sensing signal. This request allows the device to sense the specific target using a second sensing signal based on feedback information provided by the other electronic devices, including information related to the specific target. The electronic device 200 can be implemented, for example, as a base station or UE in a communication-sensing integrated system. For example, when there are multiple targets, sensing multiple targets using the first sensing signal includes using multiple beams of the first sensing signal to sense the multiple targets separately.

[0034] The processing unit 202 can be implemented as one or more processing circuits and at least one memory. The processing circuits can be, for example, a processor or a chip, and the at least one memory can be RAM, ROM, etc. The at least one memory is used, for example, to store computer program code and data required for the processing circuits to perform processing. Furthermore, it should be understood that... Figure 2 The functional units in the electronic device 200 shown are logical modules divided according to the specific functions they implement, rather than being used to limit the specific implementation method.

[0035] The electronic device 200 can be implemented at the chip level or at the device level. As an example, the electronic device 200 can function as a base station or the UE itself, and may also include external devices such as memory and transceivers (not shown). The memory can be used to store programs and related data information that the electronic device 200 needs to execute to perform various functions. The transceiver may include one or more communication interfaces to support communication with different devices (e.g., UE, base station, core network side equipment, etc.), and the specific implementation of the transceiver is not limited here.

[0036] The phrase "error in the perception of a specific target" can refer to the loss of perception of that single target when the perceived target includes a single target. When the perceived target includes multiple targets, it can refer to the loss of perception of a specific target among the multiple targets; that is, the number of perceived targets is less than the intended number of targets. Alternatively, "error in the perception of a specific target" can also refer to the number of perceived targets being greater than the intended number of targets. For example, due to inaccurate perception results, the perceived targets include other targets different from the intended targets, similar to "false detection." For instance, when the perceived target includes a single target, the perception result indicates more than one target. Therefore, "error in the perception of a specific target" can be understood as a "mismatch" between the number of perceived targets and the intended number of targets.

[0037] Furthermore, it should be noted that when the sensing target includes multiple targets, the electronic device 200, acting as the source sensing electronic device, can determine which targets or targets are missing based on information related to a specific target, and its collaborative sensing request includes information related to that specific target. Other electronic devices acting as collaborative sensing electronic devices perform sensing based on the collaborative sensing request and discover the specific target. They then include information related to that specific target in the collaborative sensing result as feedback information and feed it back to the electronic device 200, enabling the electronic device 200 to correctly perceive the missing specific target using an appropriate second sensing signal.

[0038] For example, information related to a specific target may include one or more of the target's size, shape, reflectivity (e.g., radar cross section (RCS)), position, velocity, orientation, trajectory, and / or predicted future trajectory. Electronic device 200 may determine which / which targets have been lost based on this information and appropriately configure relevant parameters of the second sensing signal, such as waveform, OFDM (frequency division multiplexing) subcarrier spacing, bandwidth, frequency, duty cycle, beamwidth, beam pointing, polarization parameters, power, and signal processing cycle, based on information received from the cooperative sensing electronic device related to the lost target. This enables electronic device 200 to accurately sense the specific target using the second sensing signal, thereby achieving the beneficial effect of improving the accuracy of multi-target detection and tracking.

[0039] It is readily understood that the feedback information returned by other electronic devices may include only information related to the specific target where the perception result is incorrect, or it may additionally include other information. The specific additional information that may be included can be configured according to requirements in practical applications, and this disclosure does not limit this. Furthermore, the feedback information returned by other electronic devices is sometimes referred to in this disclosure as a "perception response" to a collaborative perception request, or is included in the perception response.

[0040] As an example, electronic device 200 can be implemented as a base station or UE that performs single-base sensing of a sensing target (a single target or multiple targets). Processing unit 202 can be configured to send a cooperative sensing request to other base stations and / or UEs in response to an error in the sensing result of a specific target using a first sensing signal, and to sense the specific target using a second sensing signal based on information related to the specific target fed back by other base stations and / or user equipment.

[0041] As another example, the electronic device 200 can also be implemented as a base station or UE acting as a sensing receiver in a bi-base sensing mode for sensing targets (single or multiple targets). The processing unit 202 can be configured to send a cooperative sensing request to other base stations and / or UEs in response to an error in the sensing result of using the first sensing signal for a specific target, and to transmit information related to the specific target provided by other base stations and / or UEs to the sensing transmitter in the bi-base sensing mode for sensing targets, so that the sensing transmitter uses the second sensing signal to sense the specific target.

[0042] As an example, a cooperative sensing request includes information on the sensing coordination method, information related to a specific target, and information about errors in the sensing results. For instance, the sensing coordination method information may include sensing reference signal parameters and information indicating whether other electronic devices acting as cooperative sensing devices are transmitters or receivers. For example, other electronic devices may act as receivers to receive sensing signals from electronic device 200, or they may act as transmitters to send sensing signals (single-base sensing). For example, sensing reference signal parameters may include carrier frequency, bandwidth, waveform, modulation scheme, transmit power, synchronization information, and channel state information. For example, information about errors in the sensing results includes information indicating the number of specific targets for which the sensing results are incorrect. It should be noted that information about the number of specific targets is not necessarily required to be included in the cooperative sensing request; however, including this information can additionally provide the number of specific targets, in addition to providing the attributes of the specific targets (e.g., indicated by information related to the specific targets included in the cooperative sensing request). This number information can, for example, be used to mutually confirm between electronic device 200 and other electronic devices whether all specific targets for which the sensing results are incorrect have been found, thereby further improving the accuracy of cooperative sensing of specific targets.

[0043] In order to identify other electronic devices as cooperative sensing devices, as an example, the processing unit 202 can be configured to select other electronic devices whose distance from the electronic device 200 is greater than a predetermined threshold for cooperative sensing, such that the difference between the echo signal of a specific target received by the electronic device 200 and the echo signal of a specific target received by other electronic devices is greater than a predetermined degree.

[0044] In scenarios such as multi-base station collaborative sensing, determining a threshold distance between base stations is crucial to ensure sufficient differentiation between the echo signals received by each base station for effective joint processing and improved sensing performance. For example, the threshold can be set based on at least one of the following: the sensing signal frequency, the sensing environment, target characteristics, antenna characteristics, and desired sensing performance metrics. Specifically, higher signal frequencies result in higher spatial resolution, requiring relatively smaller base station spacing. Conversely, lower signal frequencies necessitate larger base station spacing to achieve sufficient spatial differentiation. In environments with rich scattering, multipath effects can lead to differences in the received echo signals even when base stations are close together. In environments dominated by line-of-sight propagation, larger base station spacing may be required to ensure differentiation between echo signals. The size, shape, reflection characteristics, and motion state of the target also affect the differentiation of echo signals. For example, for small or weakly reflective targets, larger base station spacing may be needed to improve the signal-to-noise ratio difference of the echo signals from each base station. Base station antenna characteristics include beamforming and antenna gain. Narrower antenna beams result in stronger directivity, requiring smaller base station spacing to cover the same sensing area. Conversely, wider beams may necessitate larger base station spacing to avoid excessive overlap and low echo signal diversity. Higher antenna gain can potentially expand the sensing signal coverage area, but it also affects the spatial diversity of the echo signal. Desired sensing performance metrics include, for example, desired positioning accuracy, target detection probability, and parameter estimation accuracy. Higher sensing performance metrics typically require greater echo signal diversity, thus necessitating larger base station spacing.

[0045] Methods for determining distance thresholds can be accomplished, for example, through theoretical analysis and modeling, simulation experiments, or field testing.

[0046] For example, a distance threshold can be set such that the signal-to-noise ratio difference between the echo signal of a specific target received by electronic device 200 and the echo signal of a specific target received by other electronic devices is greater than 3 dB.

[0047] As an example, in a scenario where electronic device 200 is a base station, processing unit 202 can be configured to: predict the possible search area of ​​a specific target within a predetermined time period after it is lost, based on one or more of the target's last known position, speed, direction, and trajectory before the perception result is incorrect; select candidate base stations capable of covering the possible search area as other candidate electronic devices; and arbitrarily select a base station from the candidate base stations as other electronic devices participating in collaborative sensing. Preferably, candidate base stations that meet the following conditions can be selected as other electronic devices participating in collaborative sensing: the candidate base station has the highest signal strength in the possible search area; and the difference between the echo signal of the specific target received by the candidate base station and the echo signal of the specific target received by the base station (which is electronic device 200) is greater than a predetermined level, for example, the signal-to-noise ratio difference between the echo signals of the base station and the candidate base station is greater than 3 dB.

[0048] After determining the possible search area, for example, the RSRP (Reference Signal Received Power) or RSRQ (Reference Signal Received Quality) of nearby base stations can be measured by the UE in the possible search area as an indicator of the signal strength of the candidate base station in the possible search area, and the base station with the largest RSRP or RSRQ can be selected as other electronic devices to participate in cooperative sensing.

[0049] For example, a base station capable of covering the potential search area can be a base station that covers the entire potential search area within its coverage area, or a base station whose RSRP is greater than -90dBm within 95% of the potential search area.

[0050] As an example, the processing unit 202 can be configured to select a candidate base station located in a position that can avoid obstructions or interference from the candidate base stations that can cover the possible search area when it is determined that the perception result is wrong due to environmental obstruction or interference, and adjust the distance between the candidate base station and the electronic device 200 according to the location and range of the obstruction or interference source.

[0051] The following is a brief description of an exemplary method for transmitting information about a specific target where the sensing result is incorrect between electronic device 200 and other electronic devices that are cooperating sensing devices.

[0052] As an example, the processing unit 202 can be configured to include semantic information about a specific target extracted from the perceptual semantic knowledge base based on the perceptual task type in a collaborative perceptual request, and send the collaborative perceptual request to other electronic devices, so that the other electronic devices can perform collaborative perceptualization based on the semantic information.

[0053] As an example, the processing unit 202 may be configured to obtain information related to a specific target based on the semantic information provided by other electronic devices after the electronic device 200 receives feedback information from other electronic devices, which includes semantic information about a specific target.

[0054] In other examples, encoding and decoding techniques can be applied to information transmission between electronic device 200 and other electronic devices. For instance, processing unit 202 can be configured to encode semantic information about a specific target extracted from a perceptual semantic knowledge base based on the perceptual task type, and include the encoded semantic information in a collaborative perception request sent to other electronic devices, enabling the other electronic devices to perform collaborative perception based on the information obtained by decoding the encoded semantic information.

[0055] As an example, the processing unit 202 may be configured to decode the encoded semantic information, which includes semantic information about a specific target, provided by another electronic device after the electronic device 200 receives it, in order to obtain information related to the specific target.

[0056] By using a perceptual semantic knowledge base, transmitting semantic information about a specific target between electronic device 200 (as a source sensing device) and other electronic devices (as cooperative sensing devices) (either by directly transmitting semantic information or by encoding semantic information before transmission) can achieve one of the following beneficial technical effects: avoiding the transmission of complex raw sensing results between sensing nodes; enhancing the robustness of the system and its adaptability to environmental changes; and saving system bandwidth resources by utilizing semantic communication.

[0057] As an example, the perception semantic knowledge base can be stored in at least one of the following: electronic device 200, other electronic devices acting as cooperative perception devices, and the perception management functional unit on the core network side. For example, the perception semantic knowledge base can be stored in a base station, a UE, or a perception management functional unit SF.

[0058] The perceptual semantic knowledge base used in the technical solution disclosed herein will be introduced below.

[0059] For example, a perceptual semantic knowledge base defines a semantic information model for integrated sensing scenarios. This semantic information model includes the format and encoding used to represent and transmit semantic data. For instance, in specific scenarios such as vehicle sensing and industrial sensing, the semantic information model can be based on JSON-LD or RDF serialization formats. JSON-LD (JSON for Linking Data) is a JSON-based serialization format used to represent linked data. RDF (Resource Description Framework) is a framework for describing network resources, often used to represent semantic knowledge. The basic unit of RDF is a triple (Subject-Predicate-Object), representing a "subject-predicate-object" relationship, and also includes URI (Uniform Resource Identifier) ​​identification, type declaration, and attribute usage.

[0060] As an example, the processing unit 202 can be configured to access the perceptual semantic knowledge base (reasoning process) through the following interfaces: a first input interface for querying the perceptual semantic knowledge base; and a first output interface for outputting semantic knowledge.

[0061] For example, a perceptual semantic knowledge base can be used to pre-train an artificial intelligence (AI) model and then the trained AI model can be incorporated into the perceptual semantic knowledge base. The first input interface and the first output interface are interfaces for the inference phase of the AI ​​model, used to utilize the knowledge base. For example, the first input interface could be an input interface for raw perceptual data, allowing different data sources (e.g., different types of perceptual nodes, different data acquisition modules) to input raw data into, for example, a knowledge extraction module included in the AI ​​model. For example, the raw data could include the following radar point cloud data: timestamp, sensor_id, point_id, x, y, z intensity, range, azimuth, elevation, and doppler.

[0062] For example, the first output interface could be a semantic knowledge output interface, which allows the knowledge extraction module to output the extracted semantic knowledge in a standardized format for use by the knowledge base storage or subsequent processing modules. For example, the first input interface and the first output interface could be streaming interfaces or APIs (Application Programming Interfaces) based on RDF format.

[0063] As an example, processing unit 202 can be configured to transmit semantically perceptual data required for constructing the perceptual semantic knowledge base between electronic device 200 and the perceptual semantic knowledge base via a second input / output interface during the construction of the perceptual semantic knowledge base. For example, in a scenario where the construction of the perceptual semantic knowledge base incorporates an AI model, the second input / output interface can be an interface for the AI ​​model training process, used to train the AI ​​model during the knowledge base construction process. For example, the second input / output interface can be a streaming interface based on RDF format or an API (Application Programming Interface).

[0064] As described above, for example, a perceptual semantic knowledge base (including training of AI models) can be constructed based on data provided by at least one of the electronic device 200, other electronic devices, and core network side devices, and at least one of these devices can also use the constructed perceptual semantic knowledge base for reasoning. Accordingly, electronic device 200 and other electronic devices can align the knowledge base information used by electronic device 200 and other electronic devices by using various interfaces of the perceptual semantic knowledge base.

[0065] A perceptual semantic knowledge base can be constructed, for example, by following these steps.

[0066] Step 1: Define the goals and scope, including clarifying the application scenarios, semantic granularity, and knowledge types. For example, application scenarios could include environmental monitoring, intelligent transportation, location services, and human activity recognition. Semantic granularity determines the level of detail and abstraction of the semantic information the semantic knowledge base needs to express. Knowledge types include entity semantics, relational semantics, event semantics, and rules and constraints.

[0067] Step 2: Construct a semantic ontology, including: designing the domain ontology, defining concepts, attributes, relationships, and constraints. More specifically, this includes the following:

[0068] a) Identify and define the core concepts of wireless sensing. These include, for example, "sensing target," "sensing environment," "sensing node," "sensing task," "sensing result," and "semantic description."

[0069] b) Define relevant attributes for each concept. For example, a "perceived target" can have attributes such as "category", "shape", "size", and "motion state", while a "perceived node" can have attributes such as "type", "accuracy", and "coverage".

[0070] c) Define the possible relationships between concepts. For example, "perceived target," "located in," "perceived environment"; "perceived node," "perceived," "perceived target"; "perceived result," "description," "motion state" of the "perceived target"; and

[0071] d) Based on domain knowledge, establish axioms and constraints for the ontology. For example, define the range of attribute values, type constraints of relations, and logical relationships between concepts to ensure the consistency and effectiveness of the knowledge base.

[0072] Step 3: Data sources and acquisition, including collecting sensor node data, labeled data, domain knowledge, and simulation data.

[0073] Step 4: Determine the knowledge extraction pattern of the perceptual semantic knowledge base, including determining the pattern for extracting semantic knowledge from data using methods such as rules and machine learning. More specifically, this includes, for example:

[0074] a) Rule-based extraction model: Based on domain knowledge and ontology definitions, a series of rules are formulated to extract semantic knowledge from data. Examples include: data pattern recognition rules: based on statistical features of sensor data and pattern recognition algorithms, specific entities or events are identified; ontology mapping rules: features or attributes in the data are mapped to concepts and attributes defined in the ontology; relation extraction rules: based on spatial, temporal, logical, and other relationships, relationships between entities are extracted from the data; and...

[0075] b) Machine Learning-Based Extraction Models: Utilizing machine learning algorithms to learn semantic knowledge extraction models from labeled data. Examples include: Named Entity Recognition (NER): Training an NER model to identify entities from sensor data or text descriptions; Relation Extraction (RE): Training an RE model to identify relationships between entities; Event Extraction (EE): Training an EE model to identify events occurring in a perceived scene; Deep Learning Methods: Utilizing deep learning models (e.g., Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers, etc.) for feature extraction and semantic knowledge extraction. For example, using CNNs to process image data and RNNs to process time-series data. The NER, RE, EE, CNN, RNN, and Transformer models mentioned above can be implemented using existing model architectures, and will not be elaborated further here.

[0076] Step 5: Storage and management of the semantic knowledge base, including selecting a knowledge graph database, building a semantic index, and maintaining knowledge base updates.

[0077] For other content related to general knowledge bases and perceptual semantic knowledge bases, please refer to the existing general knowledge base content; it will not be elaborated here.

[0078] As an example, the processing unit 202 can be configured to send a signal supporting multi-target perception capability to the perception management function unit on the core network side before perceiving the target; and to receive multi-target perception tasks assigned by the perception management function unit.

[0079] After sending a collaborative sensing request to other electronic devices participating in collaborative sensing, the processing unit 202 can be configured to turn off the first sensing signal for sensing the specific target, or to turn off the beam in the first sensing signal used for sensing the specific target, while waiting for other electronic devices to provide information related to the specific target, thereby achieving the beneficial technical effect of reducing power consumption. For example, if the sensing target is a single target and the electronic device 200 has lost sensing of the target, the processing unit 202 can turn off the first sensing signal for sensing the specific target (i.e., the single target) while waiting for other electronic devices to provide information related to the specific target. If the sensing target is multiple targets, the processing unit 202 can turn off the beam in the first sensing signal used for sensing the specific target while waiting for other electronic devices to provide information related to the lost specific target.

[0080] If the sensing target includes multiple targets, the processing unit 202 can be configured to continuously sense other targets among the multiple targets, excluding the specific target, using the first sensing signal when sensing the specific target whose sensing result is incorrect using the second sensing signal. For example, the electronic device 200 continuously uses the first sensing information for sensing regardless of whether an error occurs in the sensing result, thereby ensuring the continuity of sensing processing for other targets.

[0081] As an example, when the perceived target includes two or more targets, and the electronic device 200 determines the second sensing signal for sensing the lost targets based on information related to the lost targets fed back by other electronic devices, if a single second sensing signal or a single beam within the second sensing signal cannot achieve correct sensing of all the lost targets, additional second sensing signals and / or additional second sensing beams can be added based on information fed back by other electronic devices to achieve sensing of all the lost targets. In other words, to achieve correct sensing of the lost targets, depending on the actual situation, the second sensing signal determined by the electronic device 200 for sensing the lost targets may include a single second sensing signal or sensing signal beam, or it may include multiple second sensing signals or sensing signal beams.

[0082] The following will describe in detail with reference to exemplary embodiments. Figure 2 The specific operation of the electronic device 200 shown in the figure.

[0083] Figure 3A An example of a processing flow for collaborative sensing among multiple sensing nodes in the event of an error in the sensing result of a perceived target, according to one embodiment of the present disclosure, is shown. In this example, the perceived target may include a single target or multiple targets. For ease of description, this example primarily describes the processing procedure when the perceived target is multiple targets, but similar processing can also be applied to scenarios where the perceived target includes a single target. The following description illustrates different processing procedures for single-target and multiple-target scenarios.

[0084] Figure 3A The main functional entities shown include a base station 1 (sometimes referred to as a "source sensing node" in this disclosure) performing multi-target sensing tasks, a base station 2 and a UE (sometimes referred to as a "cooperative sensing node" in this disclosure) participating in cooperative sensing, a sensing function management unit, and an application function unit. In this embodiment, the description is based on the example of base station 1 sensing multiple targets in single-base sensing mode, but this disclosure is not limited to this. The base station 1 performing multi-target sensing tasks and the base station 2 participating in cooperative sensing are, for example, specific manifestations of TRP. The sensing function management unit is implemented, for example, through a core network element SF deployed in the core network. The application function unit is implemented, for example, through an AF deployed within the operator or a trusted third party. Base stations can interact via the Xn interface, and base stations and UEs can interact via the Uu interface or based on RRC signaling. Communication between the base station and the sensing function management unit can be achieved, for example, through an interface commonly referred to as the Sensing Control Interface or the Sensor-Integrated Interface (ISAC Interface). The interaction between the application function unit and the sensing function management unit is typically accomplished via NEF (Network Exposure Function). NEF can expose various network services and capabilities to external entities or applications through standardized methods. Of course, this disclosure is not limited to this; various signaling and interaction methods used between base stations, UEs, perception management functional units, and application functional units are applicable.

[0085] The following section will describe in detail the processing flow of collaborative perception in the event of errors in the results of multi-target perception.

[0086] In step 1, base station 1 sends a multi-target sensing capability indication to the sensing function management unit (e.g., SF).

[0087] As an example, base station 1 may send a multi-target sensing capability indication based on a request from the sensing function management unit, or it may periodically send a multi-target sensing capability indication to the sensing function management unit.

[0088] As described above, in this example, base station 1 can sense multiple targets in single-base sensing mode.

[0089] In step 2, the application function unit (e.g., AF) sends a multi-target perception task request to the perception function management unit.

[0090] In step 3, the sensing function management unit assigns multi-target sensing tasks to base station 1.

[0091] In step 4, base station 1 uses the first sensing signal to perform multi-target sensing and detects an error in the sensing result for a specific target among the multiple targets.

[0092] An error in the perception of a specific target can include, for example, the situation where base station 1 detects that one or more targets among a plurality of targets are missing. For example, the distance between one or more targets is too close, which may cause the specific target to be lost, or the inability to perceive the target due to the influence of the background environment may also cause the specific target to be lost. In this disclosure, the lost specific target is sometimes also referred to as a "lost target". As mentioned above, an error in the perception of a specific target can be understood as a "mismatch" between the number of perceived targets and the predetermined number of targets.

[0093] In steps 5 and 5', base station 1 sends a cooperative sensing request to base station 2 and / or UE, which have multi-target sensing capabilities.

[0094] As an example, a cooperative sensing request includes sensing coordination method information, information related to lost targets, and information about errors in the sensing results. For instance, sensing coordination method information may include sensing reference signal parameters and information indicating whether base station 2 and / or the UE is a transmitter or a receiver. For example, base station 2 and / or the UE may act as a receiver to receive sensing signals from base station 1, or base station 2 and / or the UE may act as a transmitter to send sensing signals. For example, sensing reference signal parameters may include carrier frequency, bandwidth, waveform, modulation scheme, transmit power, synchronization information, and channel state information. For example, information about errors in the sensing results includes information indicating the number of lost targets and the number of sensing errors.

[0095] As an example, the distance between base station 1 and base station 2 and / or the UE is set to be greater than a predetermined threshold, such that the difference between the echo signal of the lost target received by base station 1 and the echo signal of the lost target received by base station 2 and / or the UE is greater than a predetermined level. For example, the signal-to-noise ratio difference between the echo signal received by base station 1 and the echo signal received by base station 2 and / or the UE is greater than 3 dB. The predetermined threshold for the distance that satisfies this predetermined level of difference can be determined, for example, through theoretical analysis and modeling, a finite number of experiments, or based on empirical values. The distance between base station 1 and base station 2 and / or the UE being greater than the predetermined threshold is actually to ensure that the channel conditions between base station 1 (as the source sensing node) and the lost specific target, and between base station 2 and / or the UE (as cooperative sensing nodes) and the lost specific target, are sufficiently large, thereby enabling the cooperative sensing nodes to obtain correct information about the lost specific target and notify the source sensing node.

[0096] As an example, base station 1 can predict the possible location of the lost target after a predetermined time based on one or more of its last known location, speed, direction of movement, and trajectory. A predetermined area (e.g., a circular area of ​​predetermined radius or a polygonal area of ​​predetermined size, etc.) can be defined as the possible search area centered on this location. Base station 2, capable of covering the possible search area, is selected to participate in cooperative sensing. Base station 2 can be any of the candidate base stations capable of covering the possible search area, or it can be the candidate base station with the strongest signal strength and / or the base station whose received echo signal of the lost target differs from that received by base station 1 by a predetermined degree. For example, the signal-to-noise ratio difference between the echo signals of the lost target received by base station 1 and base station 2 is greater than 3 dB.

[0097] In other examples, a UE can also be selected as an electronic device participating in collaborative sensing. For instance, based on one or more of the lost target's last known location, speed, direction, and trajectory, the possible location of the lost target after a predetermined time is predicted. A predetermined area (e.g., a circular area of ​​a predetermined radius or a polygonal area of ​​a predetermined size, etc.) is defined as the possible search area centered on this location. UEs within the coverage area of ​​base station 1 within this predetermined area are selected as candidate UEs. Candidate UEs whose distance from base station 1 is greater than a predetermined threshold are selected as collaborative sensing UEs, such that the difference between the echo signal of the lost target received by base station 1 and the echo signal of the lost target received by the selected collaborative sensing UE is greater than a predetermined degree.

[0098] As an example, if base station 1 determines that the sensing result is incorrect due to environmental obstruction or interference, it can select base station 2 and / or UE located in a position that can avoid obstructions or interference from candidate base stations that can cover the possible search area, and adjust the distance between base station 2 and / or UE and base station 1 according to the location and range of obstruction or interference source.

[0099] It is easy to understand that if both base station 2 and UE that meet the conditions are selected as cooperative sensing devices, then base station 1 can, for example, arbitrarily select one of the information fed back by base station 2 and UE to determine the second sensing signal for sensing a specific target, or base station 1 can combine the information fed back by base station 2 and UE to determine the second sensing signal.

[0100] As an example, base station 1 includes semantic information related to the lost target extracted from the perception semantic knowledge base based on the perception task type in a collaborative perception request and sends it to base station 2 and / or the UE, enabling base station 2 and / or the UE to perform collaborative perception based on the semantic information. The storage, construction, and access of the perception semantic knowledge base have been described in detail above and will not be repeated here.

[0101] In other examples, base station 1 uses a pre-trained AI model to encode semantic information related to the lost target extracted from the aforementioned perceptual semantic knowledge base based on the perceptual task type, and sends the encoded semantic information to base station 2 and / or UE in a collaborative perception request. This allows base station 2 and / or UE to decode the encoded semantic information using a pre-trained AI model deployed locally or obtained from base station 1, and to perform collaborative perception of the lost target based on the decoded information.

[0102] In steps 6 and 6', base station 2 and / or UE send a cooperative sensing response to base station 1 respectively.

[0103] Base station 2 and / or UE can analyze the echo signals of multiple targets according to the cooperative sensing request, find the lost target and obtain relevant information of the lost target, and send the cooperative sensing response containing relevant information of the lost target to base station 1 as feedback information.

[0104] As an example, base station 2 and / or the UE can extract semantic features related to the lost target from a perception semantic knowledge base based on the perception task type, according to the semantic information related to the lost target included in the collaborative perception request. After completing collaborative perception, the semantic information related to the lost target is included in the collaborative perception response. Base station 1 can obtain the semantic information related to the lost target from the received collaborative perception response. Base station 2 and / or the UE can obtain the relevant semantic information, for example, by looking up a table.

[0105] Alternatively, base station 2 and / or UE can utilize a pre-trained AI model to encode semantic information related to the lost target extracted from the perceptual semantic knowledge base, and include the encoded semantic information in the collaborative sensing response. Base station 1 can obtain information related to the lost target by decoding the encoded semantic information contained in the received collaborative sensing response.

[0106] As an example, base station 1, base station 2 and UE can either store the perception semantic knowledge base locally, or request the perception semantic knowledge base from the perception management function unit according to the perception task type if they do not have a locally stored perception semantic knowledge base.

[0107] In step 7, base station 1 sends a second sensing signal to sense the lost target based on information related to the lost target.

[0108] As an example, in a scenario where the perceived target is a single target, base station 1 can turn off the first sensing signal that previously sensed the lost target while waiting for base station 2 and / or UE to provide information related to the lost target (which in this case is the single target), thereby achieving the beneficial technical effect of reducing power consumption.

[0109] As another example, in a scenario where the sensing target is multiple targets, base station 1 can use the first sensing signal to continuously sense other targets among the multiple targets besides the lost target, while using the second sensing signal to sense the lost target, for example, during a continuous time period before and after the target is lost. This ensures the continuity of sensing of other targets.

[0110] For example, information related to the lost target includes one or more of the lost target's size, shape, reflection characteristics, location, velocity, trajectory, and / or predicted future trajectory. Based on this information, base station 1 can appropriately configure relevant parameters of the second sensing signal, such as waveform, OFDM (Frequency Division Multiplexing) subcarrier spacing, bandwidth, frequency, duty cycle, beamwidth, beam pointing, polarization parameters, power, and signal processing cycle, etc., so that base station 1 can accurately sense the lost target based on the echo signal of the second sensing signal from the lost target, thereby achieving the beneficial effect of improving the accuracy of target detection and tracking.

[0111] It is readily understood by those skilled in the art, although Figure 3AThe embodiment described above uses base station 1 as the source sensing device as an example. However, those skilled in the art will understand that the source sensing device can also be implemented by a UE. For example, in a V2X scenario, the lead vehicle in a convoy (the UE as the source sensing device) senses (e.g., tracks) a specific vehicle in the convoy. If it loses sense of that specific vehicle, the lead vehicle can send a cooperative sensing request to appropriate sensing electronic devices in the vicinity, such as other vehicles or roadside units (RSUs) capable of sensing that specific vehicle, and use the information fed back by the cooperative sensing device to recover sense of that specific vehicle. The details regarding determining candidate sensing devices, selecting a cooperative sensing device from among them, sending a cooperative sensing request, and recovering sense of the lost specific vehicle based on the feedback from the cooperative sensing device are similar to the description above using base station 1 as the source sensing device, and will not be repeated here.

[0112] Figure 3B An example of a processing flow for collaborative sensing between sensing nodes according to another embodiment of this disclosure is shown. Figure 3B The main functional entities shown and the signaling types used in the interactions between these functional entities are as follows: Figure 3A Similarly, and will not be repeated here. A detailed description will follow. Figure 3B The collaborative sensing processing flow is shown. In this embodiment, base station 1 and UE1 sense multiple targets in a dual-base sensing mode. For example, base station 1 acts as a sensing transmitter and UE1 acts as a sensing receiver.

[0113] Similar to Figure 3A The implementation method, in Figure 3B In the example, the perceived target may include a single target or multiple targets. For ease of description, this example primarily describes the processing when the perceived target is multiple targets, but similar processing can also be applied to scenarios where the perceived target includes a single target. The following description illustrates the different processing methods for single-target and multiple-target scenarios.

[0114] In step 1, base station 1 sends a multi-target sensing capability indication to the sensing function management unit (e.g., SF).

[0115] As an example, base station 1 may send a multi-target sensing capability indication based on a request from the sensing function management unit, or it may periodically send a multi-target sensing capability indication to the sensing function management unit.

[0116] In step 2, the application function unit (e.g., AF) sends a multi-target perception task request to the perception function management unit.

[0117] In step 3, the sensing function management unit assigns multi-target sensing tasks to base station 1.

[0118] In step 4, base station 1 and UE 1 perform a sensing task through bi-base sensing operation, wherein base station 1 transmits a first sensing signal to sense the corresponding target, and UE 1, as a sensing receiver, receives the echo returned by the corresponding target.

[0119] In step 5, UE 1 detects an error in the perception result for a specific target among multiple targets. For example, UE 1 detects that one or more targets are missing.

[0120] In step 6, UE 1 sends a cooperative sensing request to UE 2.

[0121] UE 1 can, for example, determine UE 2 within a possible search area that can communicate with it via a sidelink and meets predetermined conditions through UE discovery processing, and send a cooperative awareness request to UE 2 via sidelink (sidelink Mode 2). Alternatively, UE 1 can also determine a base station within a possible search area that can communicate with it and meets predetermined conditions as a cooperative awareness base station, and send a cooperative awareness request to that cooperative awareness base station, for example, through an RRC signaling procedure. The method for determining the possible search area, and the predetermined conditions for selecting a cooperative awareness UE or base station from candidate UEs or base stations, can be similar to those described above. Figure 3A It will proceed as described, and will not be repeated here.

[0122] Those skilled in the art will understand that UE 1 and / or UE 2 can also be replaced by a base station. In this case, the base station, acting as a sensing receiver, can be referenced as described above. Figure 3A The cooperative sensing base station is determined as described above, that is, a base station whose distance from base station 1 is greater than a threshold distance is selected as the cooperative sensing base station, such that the difference between the echo signal of the lost target received by base station 1 and the echo signal of the lost target received by the cooperative sensing base station is greater than a predetermined degree.

[0123] As an example, UE 1 sends the semantic information related to the lost target extracted from the aforementioned semantic knowledge base based on the perception task type to UE 2 in a collaborative perception request, so that UE 2 can perform collaborative perception based on the information related to the lost target obtained from the semantic information.

[0124] Alternatively, UE 1 uses a pre-trained AI model deployed locally or obtained from base station 1 to encode semantic information related to the lost target extracted from the aforementioned perception semantic knowledge base based on the perception task type, and sends the encoded semantic information to UE 2 in a collaborative perception request. This allows UE 2 to decode the encoded semantic information using a pre-trained AI model deployed locally or obtained from base station 1 or UE 1, and obtain information about the lost target that needs to be collaboratively perceived based on the decoded information, thereby achieving collaborative perception of the lost target.

[0125] In step 7, UE 2 sends a cooperative sensing response to UE 1.

[0126] As an example, UE 2 can analyze the echo signal of a lost target and obtain relevant information about the lost target based on a cooperative sensing request, and send the cooperative sensing response containing relevant information about the lost target as feedback information to UE 1. For example, the information related to the lost target includes one or more of the lost target's size, shape, reflection characteristics, location, speed, trajectory, and / or predicted future trajectory.

[0127] As an example, UE 2 can extract semantic features related to the semantic information of the lost target from the perception semantic knowledge base based on the perception task type, according to the semantic information related to the lost target included in the collaborative perception request, and perform collaborative perception accordingly. After completing the collaborative perception task, UE 2 will include the semantic information related to the lost target in the collaborative perception response and feed it back to UE 1. UE 1 can obtain the semantic information related to the lost target from the received collaborative perception response. For example, UE 1 and UE 2 can obtain the semantic information by, for example, looking up a table.

[0128] Alternatively, UE 2 can utilize a pre-trained AI model to encode semantic information related to the lost target extracted from the perceptual semantic knowledge base, and include the encoded semantic information in the collaborative perception response. UE 1 can obtain information related to the lost target by decoding the encoded semantic information contained in the received collaborative perception response.

[0129] As an example, UE 1 and UE 2 can either store the perception semantic knowledge base locally, or request the perception semantic knowledge base from the perception management function unit or base station 1 according to the perception task type if they do not have the perception semantic knowledge base stored locally. For example, they can download the perception semantic knowledge base from the perception management function unit or base station 1.

[0130] In step 8, UE 1 reports relevant information about the lost target to base station 1.

[0131] In step 9, base station 1 sends a second sensing signal to sense the lost target.

[0132] As an example, in a scenario where the sensed target includes a single target, base station 1 can turn off the first sensing signal previously used to sense the lost target (i.e., the single target) while waiting for UE 2 to provide and UE 1 to report information related to the lost target, thereby achieving the beneficial technical effect of reducing power consumption.

[0133] As an example, in a scenario where the sensing target includes multiple targets, base station 1 can use the first sensing signal to continuously sense other targets among the multiple targets besides the lost target while using the second sensing signal to sense the lost target (e.g., during a continuous time period before and after the loss of sensing of a specific target), thereby ensuring the continuity of sensing of other targets.

[0134] For example, information related to the lost target includes one or more of the lost target's size, shape, reflection characteristics, location, velocity, trajectory, and / or predicted future trajectory. Based on this information, base station 1 can appropriately configure relevant parameters of the second sensing signal, such as waveform, OFDM (Frequency Division Multiplexing) subcarrier spacing, bandwidth, frequency, duty cycle, beamwidth, beam pointing, polarization parameters, power, and signal processing cycle, etc., enabling base station 1 to accurately sense the lost target based on the echo signal from the lost target to the second sensing signal, thereby achieving the beneficial effect of improving the accuracy of target detection and tracking.

[0135] Figure 4 An exemplary functional block diagram of an electronic device 400 according to another embodiment of the present disclosure is shown.

[0136] like Figure 4 As shown, the electronic device 400 includes a processing unit 402, which can be configured to, in response to a collaborative sensing request sent by the source sensing electronic device, provide feedback information, including information related to the specific target, to the source sensing electronic device when the source sensing electronic device makes an error in sensing a specific target using a first sensing signal. This allows the source sensing electronic device to sense the specific target using a second sensing signal based on the information related to the specific target. The electronic device 400 can be implemented, for example, as a base station and / or UE in a communication-sensing integrated system, operating as a collaborative sensing electronic device that performs collaborative sensing processing with the source sensing electronic device.

[0137] The processing unit 402 can be implemented as one or more processing circuits and at least one memory. The processing circuits can be, for example, a processor or a chip, and the at least one memory can be RAM, ROM, etc. The at least one memory is used, for example, to store computer program code and data required for the processing circuits to perform processing. Furthermore, it should be understood that... Figure 4 The functional units in the electronic device 400 shown are logical modules divided according to the specific functions they implement, rather than being used to limit the specific implementation method.

[0138] Electronic device 400 can be implemented at the chip level or at the device level. As an example, electronic device 400 can function as a base station or UE itself, and may also include external devices such as memory and transceivers (not shown). The memory can be used to store programs and related data information that electronic device 400 needs to execute to perform various functions. The transceiver may include one or more communication interfaces to support communication with different devices (e.g., UE, base station, core network side equipment, etc.), and the specific implementation of the transceiver is not limited here.

[0139] For example, information related to a specific target may include one or more of the target's size, shape, reflectivity, position, velocity, trajectory, and / or predicted future trajectory. Electronic device 400 provides this information to source sensing electronic device, allowing it to appropriately configure relevant parameters of the second sensing signal based on this information. This enables accurate detection of the specific target based on its echo signal to the second sensing signal, thereby improving the accuracy of multi-target detection and tracking. For details regarding the relevant parameters of the second sensing signal, please refer to the above. Figure 2 , Figure 3A and Figure 3B The described embodiments will not be repeated here.

[0140] For example, the perceived target may include a single target or multiple targets. The electronic device 400, acting as a cooperative sensing electronic device, may function as a base station or UE acting as a cooperative sensing receiver in a dual-base sensing mode for the perceived target. In the event that the source sensing electronic device fails to perceive a specific target using the first sensing signal, the processing unit 402, in response to a cooperative sensing request sent by the source sensing electronic device, provides feedback information, including information related to the specific target, to the source sensing electronic device. This allows the source sensing electronic device to perceive the specific target using a second sensing signal based on the information related to the specific target.

[0141] The collaborative sensing request sent from the source sensing electronic device may include, for example, sensing collaboration mode information, information related to a specific target, and information about errors in the sensing results. For instance, the sensing collaboration mode information may include sensing reference signal parameters and information indicating whether the electronic device 400 is a transmitter or a receiver. In this example, the electronic device 400 may act as a receiver to receive sensing signals from the source sensing electronic device. It is readily understood that in other examples, the electronic device 400 may also act as a sensing transmitter, receiving collaborative sensing requests from the source sensing electronic device and thereby performing collaborative sensing of a lost specific target. It then returns feedback information, including information related to the specific target, to the source electronic device so that the source electronic device can regain correct sensing of the lost specific target. Details regarding sensing reference signal parameters and information about errors in the sensing results can be found, for example, in the above-described combination. Figure 2 , Figure 3A and Figure 3B The specific details of the process will not be elaborated upon here.

[0142] As an example, the distance ratio between electronic device 400 and the source sensing electronic device is set to be greater than a predetermined threshold, such that the difference between the echo signal of the specific target received by electronic device 400 and the echo signal of the specific target received by the source sensing electronic device is greater than a predetermined level. For example, this predetermined threshold makes the signal-to-noise ratio difference between the echo signal of the specific target received by electronic device 400 and the echo signal of the specific target received by the source sensing electronic device greater than 3 dB. This predetermined threshold can be, for example, similar to the combination described above. Figure 2 , Figure 3A and Figure 3B The configuration is as described in the embodiments, and the details will not be repeated here.

[0143] The source sensing electronic device and electronic device 400 can be implemented, for example, as a base station. In this case, electronic device 400 is located within a possible search area for a predetermined period after the sensing result of a specific target is incorrect. This possible search area is predicted based on one or more of the specific target's last known position, speed, direction of movement, and trajectory before the sensing result error. Furthermore, the signal strength of electronic device 400 is maximum in the possible search area, and / or the difference between the echo signal of the specific target received by electronic device 400 and the echo signal of the specific target received by the source sensing electronic device is greater than a predetermined degree.

[0144] For example, processing unit 402 can receive target-related semantic information contained in a collaborative sensing request from a source sensing electronic device, so as to extract target-related semantic information from a sensing semantic knowledge base based on the obtained semantic information, and perform collaborative sensing of the target based on the extracted target-related semantic information. The target-related semantic information mentioned above is extracted from the sensing semantic knowledge base based on the sensing task type. By extracting target-related semantic information from the sensing semantic knowledge base, the transmission of complex raw sensing results from the source sensing electronic device is avoided, saving system bandwidth.

[0145] As an example, processing unit 402 can be configured to receive encoded semantic information contained in a collaborative sensing request from a source sensing electronic device, in order to perceive a specific target based on information obtained by decoding the encoded semantic information. For example, the encoded semantic information is obtained by the source sensing electronic device encoding semantic information about a specific target extracted from a sensing semantic knowledge base based on the sensing task type.

[0146] As an example, the encoded semantic information is obtained by encoding semantic information about a specific target using a pre-trained AI model through a source sensing electronic device. The processing unit 402 can be configured to decode the encoded semantic information using a pre-trained AI model deployed locally or obtained from the source sensing electronic device to obtain semantic information about the specific target. Since the encoded semantic information related to the specific target is obtained from the source sensing electronic device, in addition to further saving the bandwidth required for information transmission, the robustness and adaptability of the system to environmental changes can also be enhanced.

[0147] After the electronic device 400 obtains information related to the lost specific target through collaborative sensing processing, for example, the processing unit 402 may be configured to extract the perceived semantic information related to the specific target from the sensing semantic knowledge base based on the sensing task type, encode the extracted semantic information to generate encoded semantic information, and provide the encoded semantic information to the source sensing electronic device so that the source sensing electronic device can decode it to obtain information related to the specific target, thereby using an appropriate second sensing signal to sense the specific target for which the previous sensing result was incorrect (e.g., lost).

[0148] As can be seen from the above description, by encoding and transmitting the semantic information about a specific target extracted from the perceptual semantic knowledge base, the electronic device 400 can achieve one of the following beneficial technical effects: enhancing the robustness and adaptability to environmental changes of the system, and saving bandwidth resources by utilizing semantic communication.

[0149] The above text has already combined Figure 2 , Figure 3A The storage, construction, and access of the perceptual semantic knowledge base are described in detail in the implementation of the electronic device 200 described in Figure B, and will not be repeated here.

[0150] Electronic device 400 may, for example, be implemented as described above. Figure 3A In the described embodiments, the base station 2 or UE is a cooperative sensing electronic device. Upon detecting target loss, the base station 1, for example, acting as a source sensing device, can determine that the base station 2 and / or UE (different implementations of electronic device 400) are cooperative sensing devices and send a cooperative sensing request to the base station 2 and / or UE. After the base station 2 and / or UE completes the cooperative sensing process, feedback information including information related to the lost target is transmitted to the base station 1, enabling the base station 1 to sense the lost target using a sensing signal different from the previously used sensing signal. For operational details of electronic device 400, please refer to the above description regarding... Figure 3A The detailed description of the process will not be repeated here.

[0151] In another example, the electronic device 400 may also be implemented as described above. Figure 3B In the described embodiment, UE 2 is a cooperative sensing electronic device. When performing a multi-target sensing task in a bi-base sensing mode with the source sensing base station (base station 1) and UE 1, in the event of target loss, UE 1, acting as the source sensing device (operating as a receiver), can determine UE 2 (an example of electronic device 400) near the lost target as a cooperative sensing device through, for example, UE discovery processing, in a possible search area after a predetermined time, based on one or more of the lost target's last known position, speed, direction, and trajectory before loss, and send a cooperative sensing request to UE 2 via a sidechain. After completing the cooperative sensing processing, UE 2 transmits feedback information including information related to the lost target to UE 1, which UE 1 reports to base station 1, causing base station 1 to use a sensing signal different from the previously used sensing signal to sense the lost target. For operational details of electronic device 400, please refer to the documentation for... Figure 3B The detailed description of the process will not be repeated here.

[0152] In the process of describing electronic devices 200 and 400 in the above embodiments, some processes or methods have obviously also been disclosed. Hereinafter, without repeating some details already discussed above, a summary of these methods is given. However, it should be noted that although these methods are disclosed in the description of the above electronic devices, these methods do not necessarily employ or are performed by the components described. For example, the embodiments of the above electronic devices can be implemented partially or entirely using hardware and / or firmware, while the methods discussed below can be implemented entirely by computer-executable programs, although these methods can also be implemented using the hardware and / or firmware of the electronic device.

[0153] Figure 5 A flowchart of a method S500 for a communication-sensing integrated system according to one embodiment of the present disclosure is shown. Method S500 begins at step S501. In step S502, in response to an error in the sensing result of a specific target among the sensing targets using a first sensing signal, a source sensing electronic device sends a cooperative sensing request to other sensing electronic devices to sense the specific target using a second sensing signal based on information related to the specific target provided by the other sensing electronic devices. Method S500 ends at step S503.

[0154] This method can be, for example, combined with the above. Figure 2 , Figure 3A The various embodiments of the electronic device 200 described in Figure B are executed, and the specific details can be found in the above description of the relevant processing of the electronic device 200, which will not be repeated here.

[0155] Figure 6 A flowchart of method S600 for a communication-sensing integrated system according to another embodiment of the present disclosure is shown. Method S600 begins at step S601. In step S602, if the source sensing electronic device errs in sensing a specific target using a first sensing signal, another sensing electronic device, in response to a collaborative sensing request sent by the source sensing electronic device, provides the source sensing electronic device with information related to the specific target, enabling the source sensing electronic device to sense the specific target using a second sensing signal based on the information related to the specific target. Method S600 ends at step S603.

[0156] This method can be, for example, combined with the above. Figure 4 The various embodiments of the described electronic device 400 are implemented, and the specific details can be found in the above description of the relevant processing of the electronic device 400, which will not be repeated here.

[0157] Those skilled in the art will readily understand that the above methods can be used in combination or individually.

[0158] As noted above, although some of the embodiments described above are based on multi-target perception, those skilled in the art will understand that the technical solutions of the embodiments of this disclosure are also applicable to the case of single-target perception. For example, if the source sensing device cannot perceive the single target and thus loses perception of it, a cooperative sensing request can be sent to other suitable sensing devices in the vicinity (e.g., base stations and / or UEs), and after receiving information about the lost single target from other sensing devices, the second signal can be used to achieve correct perception of the single target.

[0159] It should be noted that the technology disclosed herein can be applied to a variety of products.

[0160] For example, the above combination Figures 2 to 4 The described electronic devices 200 and 400 can be implemented as various base stations. Base stations can be implemented as any type of evolved NodeB (eNB) or gNB (5G base station). eNBs include, for example, macro eNBs and small eNBs. Small eNBs can be eNBs covering cells smaller than macro cells, such as pico eNBs, micro eNBs, and femtocell eNBs. A similar situation can occur with gNBs. Alternatively, base stations can be implemented as any other type of base station, such as NodeBs and base transceiver stations (BTSs). A base station may include: a subject configured to control wireless communication (also called base station equipment); and one or more remote radio heads (RRHs) located in a different location from the subject. Additionally, various types of user equipment can operate as base stations by temporarily or semi-persistently performing base station functions.

[0161] Electronic devices 200 and 400 can also be implemented as various user devices, for example. User devices can be implemented as mobile terminals (such as smartphones, tablet PCs, laptop PCs, portable gaming terminals, portable / dongle-type mobile routers, and digital camera devices) or in-vehicle terminals (such as car navigation devices). User devices can also be implemented as terminals performing machine-to-machine (M2M) communication (also known as machine-type communication (MTC) terminals). Furthermore, user devices can be wireless communication modules (such as integrated circuit modules comprising a single chip) installed on each of the aforementioned terminals.

[0162] The following will briefly introduce specific application scenarios of the technology disclosed herein.

[0163] Application Scenario Example 1: Drone Collision Avoidance and Intrusion Detection

[0164] For example, in complex urban environments, drone swarms need to perform a variety of tasks, including delivery, environmental monitoring, and security patrols. In such environments, it is necessary to avoid drone collisions and detect intrusions. To ensure the safe operation of drones and the efficient completion of tasks, the multi-target cooperative perception technology of this disclosure can be applied through the following steps.

[0165] 1. Initialization: Deploy multiple sensing nodes, such as 5G terminals on ground base stations and drones; base stations send instructions to the sensing management function to support multi-target sensing capabilities, preparing to receive sensing tasks.

[0166] 2. Task Execution: Upon receiving the multi-target perception task, the base station uses the initial perception signal to perform multi-target detection and tracking of the UAV and its surrounding environment. If an error is detected in the perception result, the base station immediately sends a cooperative perception request to other base stations and the UAV, including the perception cooperation method and information related to the lost targets. The cooperative perception request may also additionally include information related to the perception result error, such as the number of lost targets.

[0167] 3. Collaborative Perception: Upon receiving a collaborative perception request, the base station and the UAV execute perception algorithms to detect and report lost target information. The base station sends a second perception signal based on the feedback results to perceive the lost target, ensuring all targets are within the monitoring range. While awaiting results from other perception nodes, the perception transmitter shuts off the beam in the first perception signal used for detecting the lost target to conserve energy. Furthermore, the base station can extract semantic information about the lost target from a perception semantic knowledge base based on the perception task type, and use a pre-trained artificial intelligence model to encode and decode the semantic information, achieving efficient information processing and transmission. The base station can then feed back the processed perception results to the UAV, guiding it to avoid obstacles or adjust its flight path, thereby ensuring the successful completion of the mission.

[0168] Application Scenario Example 2: Intelligent Transportation

[0169] For example, in intelligent transportation systems, real-time perception and dynamic monitoring of vehicles, pedestrians, and other obstacles are crucial for ensuring traffic safety and efficiency. The multi-target cooperative perception technology of this disclosure enables efficient detection and tracking of multiple targets in complex traffic environments. For instance, multiple ground base stations and roadside units (RSUs) are installed at a busy urban intersection, while vehicles and intelligent traffic lights on the road are also equipped with perception nodes. Intelligent transportation systems require real-time monitoring of the position and dynamics of vehicles, pedestrians, and other obstacles to optimize traffic flow, prevent traffic accidents, and support autonomous vehicles. The multi-target cooperative perception technology of this disclosure can be applied through the following steps.

[0170] 1. Initialization: Deploy multiple sensing nodes at urban intersections, including ground base stations, roadside units, and 5G terminals on vehicles; base stations or vehicles send instructions to the sensing management function to support multi-target sensing capabilities, preparing to receive multi-target sensing tasks.

[0171] 2. Data Acquisition: Ground base stations, roadside units, and 5G terminals on vehicles collect environmental data in real time, including vehicle speed, direction, pedestrian positions, and other obstacles; multiple sensing nodes such as radar, LiDAR, and cameras can also be used to ensure the comprehensiveness and accuracy of the data.

[0172] 3. Data sharing: Sensing nodes share the collected data through the 5G network to ensure fast and low-latency communication.

[0173] 4. Multi-target detection and tracking: The source sensing base station uses the first sensing signal to perform multi-target detection and tracking, updating the location and dynamics of vehicles and pedestrians in real time. In case of an error in the sensing result, the base station immediately sends a collaborative sensing request to other base stations and vehicles, including the sensing collaboration method and information related to the lost target. The collaborative sensing request may also additionally include information related to the sensing result error, such as the number of lost targets. For example, when using a 5G terminal on a vehicle to perform a sensing task, if a target leaves the terminal's sensing range, the target is not identified as lost, and collaborative sensing is not required.

[0174] 5. Collaborative Perception: Base stations and vehicles receiving collaborative perception requests perform perception processing, discovering and reporting lost target information. The source perception base station sends a second perception signal based on the received lost target information to perceive the lost target, ensuring all targets are within the monitoring range. While waiting for results from other perception nodes, the perception transmitter, acting as the source perception device, shuts off the beam in the first perception signal used for sensing the lost target to conserve energy. The source perception base station can extract semantic information about the lost target from the perception semantic knowledge base according to the perception task type, and uses a pre-trained artificial intelligence model to encode and decode the semantic information, achieving efficient information processing and transmission. The source perception base station feeds back the processed perception results to the intelligent traffic control system to optimize traffic signals and flow management. Autonomous vehicles adjust their routes based on the latest perception information to avoid collisions, ensuring driving safety. Pedestrian safety is particularly important in schools and residential areas. Intelligent transportation systems can detect pedestrian positions and movements in real time and issue warnings to vehicles to prevent collisions.

[0175] As can be seen from the above description, the electronic devices 200 and 400 according to embodiments of this disclosure can be implemented, for example, by a base station or a user equipment (UE). Application examples related to base stations and UEs will be described below.

[0176] [Application examples of base stations]

[0177] (First application example)

[0178] Figure 7 This is a block diagram illustrating a first example of a schematic configuration of an eNB or gNB to which the technologies of this disclosure can be applied. Note that the following description uses an eNB as an example, but it can also be applied to a gNB. The eNB 800 includes one or more antennas 810 and a base station device 820. The base station device 820 and each antenna 810 can be connected to each other via RF cables.

[0179] Each of the antennas 810 includes one or more antenna elements (such as multiple antenna elements included in a multiple-input multiple-output (MIMO) antenna) and is used by the base station equipment 820 to transmit and receive wireless signals. Figure 7 As shown, the eNB 800 may include multiple antennas 810. For example, the multiple antennas 810 may be compatible with multiple frequency bands used by the eNB 800. Although Figure 7 An example is shown in which the eNB 800 includes multiple antennas 810, but the eNB 800 may also include a single antenna 810.

[0180] The base station equipment 820 includes a controller 821, a memory 822, a network interface 823, and a wireless communication interface 825.

[0181] The controller 821 can be, for example, a CPU or a DSP, and operates various higher-level functions of the base station equipment 820. For example, the controller 821 generates data packets based on data in signals processed by the wireless communication interface 825, and transmits the generated packets via the network interface 823. The controller 821 can bundle data from multiple baseband processors to generate bundled packets and transmit the generated bundled packets. The controller 821 may have logical functions that perform controls such as radio resource control, radio bearer control, mobility management, admission control, and scheduling. This control can be performed in conjunction with nearby eNBs or core network nodes. The memory 822 includes RAM and ROM, and stores programs executed by the controller 821 and various types of control data (such as terminal lists, transmission power data, and scheduling data).

[0182] Network interface 823 is a communication interface used to connect base station equipment 820 to core network 824. Controller 821 can communicate with core network nodes or other eNBs via network interface 823. In this case, eNB 800 and core network nodes or other eNBs can be connected to each other through logical interfaces (such as S1 and X2 interfaces). Network interface 823 can also be a wired communication interface or a wireless communication interface for wireless backhaul. If network interface 823 is a wireless communication interface, it can use a higher frequency band for wireless communication compared to the frequency band used by wireless communication interface 825.

[0183] The wireless communication interface 825 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless connectivity to terminals located in the cell of eNB 800 via antenna 810. The wireless communication interface 825 typically includes, for example, a baseband (BB) processor 826 and RF circuitry 827. The BB processor 826 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing at layers such as L1, Media Access Control (MAC), Radio Link Control (RLC), and Packet Data Convergence Protocol (PDCP). Instead of controller 821, the BB processor 826 may have some or all of the above-described logical functions. The BB processor 826 may be a memory storing communication control programs, or a module including a processor and associated circuitry configured to execute programs. Updates can change the functionality of the BB processor 826. The module may be a card or blade inserted into a slot in base station equipment 820. Alternatively, the module may be a chip mounted on a card or blade. Meanwhile, the RF circuit 827 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives wireless signals via the antenna 810.

[0184] like Figure 7 As shown, the wireless communication interface 825 may include multiple BB processors 826. For example, the multiple BB processors 826 may be compatible with multiple frequency bands used by the eNB 800. Figure 7 As shown, the wireless communication interface 825 may include multiple RF circuits 827. For example, the multiple RF circuits 827 may be compatible with multiple antenna elements. Although Figure 7 An example is shown in which the wireless communication interface 825 includes multiple BB processors 826 and multiple RF circuits 827, but the wireless communication interface 825 may also include a single BB processor 826 or a single RF circuit 827.

[0185] In the electronic devices 200 and 400 according to embodiments of the present disclosure, for example by... Figure 7In the case of the eNB 800 shown, at least a portion of the functions of the processing units 202 and 402 included in electronic devices 200 and 400, respectively, can also be implemented by the controller 821. For example, the controller 821 can execute the functions of the processing units 202 or 402 to request other electronic devices to perform cooperative sensing or cooperate with the source sensing electronic device to perform cooperative sensing when the sensing result is wrong during the execution of the target sensing task, thereby achieving at least one of the following beneficial effects: improving the accuracy of target detection (e.g., including single target detection and multiple target detection) and tracking, reducing power consumption, supporting multiple sensing cooperation methods to adapt to different application scenarios, enhancing the robustness of the system and adaptability to environmental changes, and saving bandwidth resources by utilizing semantic communication.

[0186] (Second application example)

[0187] Figure 8 This is a block diagram illustrating a second example of a schematic configuration of an eNB or gNB to which the technologies of this disclosure can be applied. Note that, similarly, the following description uses an eNB as an example, but it can also be applied to a gNB. The eNB 830 includes one or more antennas 840, a base station device 850, and an RRH 860. The RRH 860 and each antenna 840 can be connected to each other via RF cables. The base station device 850 and the RRH 860 can be connected to each other via high-speed lines such as fiber optic cables.

[0188] Each of the antennas 840 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used by the RRH 860 to transmit and receive wireless signals. Figure 8 As shown, the eNB 830 may include multiple antennas 840. For example, the multiple antennas 840 may be compatible with multiple frequency bands used by the eNB 830. Although Figure 8 An example is shown in which the eNB 830 includes multiple antennas 840, but the eNB 830 may also include a single antenna 840.

[0189] The base station equipment 850 includes a controller 851, a memory 852, a network interface 853, a wireless communication interface 855, and a connection interface 857. The controller 851, memory 852, and network interface 853 are connected to a reference... Figure 7 The controller 821, memory 822, and network interface 823 described are the same.

[0190] The wireless communication interface 855 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless communication to terminals located in the sector corresponding to the RRH 860 via the RRH 860 and antenna 840. The wireless communication interface 855 may typically include, for example, a BB processor 856. In addition to the BB processor 856 being connected to the RF circuitry 864 of the RRH 860 via a connection interface 857, the BB processor 856 is connected to the reference... Figure 7 The described BB processor 826 is the same. Figure 8 As shown, the wireless communication interface 855 may include multiple BB processors 856. For example, the multiple BB processors 856 may be compatible with multiple frequency bands used by the eNB 830. Although Figure 8 An example is shown in which the wireless communication interface 855 includes multiple BB processors 856, but the wireless communication interface 855 may also include a single BB processor 856.

[0191] Connection interface 857 is an interface for connecting base station device 850 (wireless communication interface 855) to RRH 860. Connection interface 857 can also be a communication module for connecting base station device 850 (wireless communication interface 855) to the aforementioned high-speed line of RRH 860.

[0192] The RRH 860 includes a connectivity interface 861 and a wireless communication interface 863.

[0193] Connection interface 861 is an interface for connecting RRH 860 (wireless communication interface 863) to base station equipment 850. Connection interface 861 can also be a communication module for communication in the aforementioned high-speed line.

[0194] The wireless communication interface 863 transmits and receives wireless signals via antenna 840. The wireless communication interface 863 typically includes, for example, RF circuitry 864. RF circuitry 864 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives wireless signals via antenna 840. Figure 8 As shown, the wireless communication interface 863 may include multiple RF circuits 864. For example, the multiple RF circuits 864 may support multiple antenna elements. Although Figure 8 An example is shown in which the wireless communication interface 863 includes multiple RF circuits 864, but the wireless communication interface 863 may also include a single RF circuit 864.

[0195] In the electronic devices 200 and 400 according to embodiments of the present disclosure, for example by... Figure 8In the case of the eNB 830 shown, at least a portion of the functions of the processing units 202 and 402 included in electronic devices 200 and 400, respectively, can also be implemented by the controller 851. For example, the controller 851 can execute the functions of the processing units 202 or 402 to request other electronic devices to perform cooperative sensing or cooperate with the source sensing electronic device to perform cooperative sensing when the sensing result is wrong during the execution of a multi-target sensing task, thereby achieving at least one of the following beneficial effects: improving the accuracy of target detection (e.g., including single target detection and multiple target detection) and tracking, reducing power consumption, supporting multiple sensing cooperation methods to adapt to different application scenarios, enhancing the robustness and adaptability of the system to environmental changes, and saving bandwidth resources by utilizing semantic communication.

[0196] [Application examples related to user equipment]

[0197] (First application example)

[0198] Figure 9 This is a block diagram illustrating an example of a schematic configuration of a smartphone 900 to which the technologies of this disclosure can be applied. The smartphone 900 includes a processor 901, a memory 902, a storage device 903, an external connection interface 904, a camera device 906, a sensor 907, a microphone 908, an input device 909, a display device 910, a speaker 911, a wireless communication interface 912, one or more antenna switches 915, one or more antennas 916, a bus 917, a battery 918, and an auxiliary controller 919.

[0199] The processor 901 can be, for example, a CPU or a system-on-a-chip (SoC), and controls the application layer and other functions of the smartphone 900. The memory 902 includes RAM and ROM, and stores data and programs executed by the processor 901. The storage device 903 can include storage media such as semiconductor memory and hard disks. The external connectivity interface 904 is an interface for connecting external devices, such as memory cards and Universal Serial Bus (USB) devices, to the smartphone 900.

[0200] The camera device 906 includes an image sensor (such as a charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS)) and generates captured images. The sensor 907 may include a set of sensors, such as a measurement sensor, a gyroscope sensor, a magnetometer sensor, and an accelerometer sensor. The microphone 908 converts sound input to the smartphone 900 into an audio signal. The input device 909 includes, for example, a touch sensor, keypad, keyboard, buttons, or switches configured to detect touches on the screen of the display device 910 and receives operations or information input from the user. The display device 910 includes a screen (such as a liquid crystal display (LCD) and an organic light-emitting diode (OLED) display) and displays the output image of the smartphone 900. The speaker 911 converts the audio signal output from the smartphone 900 into sound.

[0201] The wireless communication interface 912 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communication. The wireless communication interface 912 typically includes, for example, a BB processor 913 and RF circuitry 914. The BB processor 913 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing for wireless communication. Meanwhile, the RF circuitry 914 can include, for example, mixers, filters, and amplifiers, and transmits and receives wireless signals via antenna 916. Note that although the figure shows a scenario where one RF link is connected to one antenna, this is only illustrative; scenarios where an RF link is connected to multiple antennas via multiple phase shifters are also included. The wireless communication interface 912 can be a single chip module on which the BB processor 913 and RF circuitry 914 are integrated. Figure 9 As shown, the wireless communication interface 912 may include multiple BB processors 913 and multiple RF circuits 914. Although Figure 9 An example is shown in which the wireless communication interface 912 includes multiple BB processors 913 and multiple RF circuits 914, but the wireless communication interface 912 may also include a single BB processor 913 or a single RF circuit 914.

[0202] In addition to cellular communication schemes, the wireless communication interface 912 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near-field communication schemes, and wireless local area network (LAN) schemes. In this case, the wireless communication interface 912 may include a BB processor 913 and RF circuitry 914 for each wireless communication scheme.

[0203] Each of the antenna switches 915 switches the connection destination of the antenna 916 among multiple circuits (e.g., circuits for different wireless communication schemes) included in the wireless communication interface 912.

[0204] Each of the antennas 916 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used by the wireless communication interface 912 to transmit and receive wireless signals. Figure 9 As shown, the smartphone 900 may include multiple antennas 916. Although Figure 9 An example is shown in which the smartphone 900 includes multiple antennas 916, but the smartphone 900 may also include a single antenna 916.

[0205] Furthermore, the smartphone 900 may include an antenna 916 for each wireless communication scheme. In this case, the antenna switch 915 can be omitted from the configuration of the smartphone 900.

[0206] Bus 917 connects processor 901, memory 902, storage device 903, external connection interface 904, camera device 906, sensor 907, microphone 908, input device 909, display device 910, speaker 911, wireless communication interface 912, and auxiliary controller 919 to each other. Battery 918 supplies power to... Figure 9 The various blocks of the smartphone 900 shown are powered, and the feeders are partially shown as dashed lines in the figure. The auxiliary controller 919 operates the minimum necessary functions of the smartphone 900, for example, in sleep mode.

[0207] In the electronic devices 200 and 400 according to embodiments of the present disclosure, for example by... Figure 9 In the case of the illustrated smartphone 900, at least a portion of the functions of the processing units 202 and 402 included in electronic devices 200 and 400, respectively, can also be implemented by the processor 901 or the auxiliary controller 919. For example, the processor 901 or the auxiliary controller 919 can execute the functions of the processing units 202 or 402 to request other electronic devices to perform cooperative sensing or to cooperate with the source sensing electronic device to perform cooperative sensing when the sensing result is incorrect during the execution of the target sensing task, thereby achieving at least one of the following beneficial effects: improving the accuracy of target detection (e.g., including single target detection and multiple target detection) and tracking, reducing power consumption, supporting multiple sensing cooperation methods to adapt to different application scenarios, enhancing the robustness of the system and its adaptability to environmental changes, and saving bandwidth resources by utilizing semantic communication.

[0208] (Second application example)

[0209] Figure 10This is a block diagram illustrating an example of a schematic configuration of a car navigation device 920 to which the technology of this disclosure can be applied. The car navigation device 920 includes a processor 921, a memory 922, a Global Positioning System (GPS) module 924, a sensor 925, a data interface 926, a content player 927, a storage medium interface 928, an input device 929, a display device 930, a speaker 931, a wireless communication interface 933, one or more antenna switches 936, one or more antennas 937, and a battery 938.

[0210] The processor 921 can be, for example, a CPU or a SoC, and controls the navigation functions and other functions of the car navigation device 920. The memory 922 includes RAM and ROM, and stores data and programs executed by the processor 921.

[0211] GPS module 924 uses GPS signals received from GPS satellites to measure the location (such as latitude, longitude, and altitude) of car navigation device 920. Sensor 925 may include a set of sensors, such as a gyroscope sensor, a geomagnetic sensor, and an air pressure sensor. Data interface 926 is connected to, for example, an in-vehicle network 941 via a terminal not shown, and acquires data generated by the vehicle (such as vehicle speed data).

[0212] Content player 927 reproduces content stored on storage media (such as CDs and DVDs), which is inserted into storage media interface 928. Input device 929 includes, for example, a touch sensor, button, or switch configured to detect touch on the screen of display device 930, and receives operations or information input from the user. Display device 930 includes a screen such as an LCD or OLED display and displays images or reproduced content for navigation functions. Speaker 931 outputs sound for navigation functions or reproduced content.

[0213] The wireless communication interface 933 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communication. The wireless communication interface 933 typically includes, for example, a BB processor 934 and RF circuitry 935. The BB processor 934 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing for wireless communication. Meanwhile, the RF circuitry 935 can include, for example, a mixer, filters, and amplifiers, and transmits and receives wireless signals via an antenna 937. The wireless communication interface 933 can also be a chip module on which the BB processor 934 and RF circuitry 935 are integrated. Figure 10 As shown, the wireless communication interface 933 may include multiple BB processors 934 and multiple RF circuits 935. Although Figure 10An example is shown in which the wireless communication interface 933 includes multiple BB processors 934 and multiple RF circuits 935, but the wireless communication interface 933 may also include a single BB processor 934 or a single RF circuit 935.

[0214] In addition to cellular communication schemes, the wireless communication interface 933 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near-field communication schemes, and wireless LAN schemes. In this case, for each wireless communication scheme, the wireless communication interface 933 may include a BB processor 934 and an RF circuit 935.

[0215] Each of the antenna switches 936 switches the connection destination of the antenna 937 among multiple circuits (such as circuits for different wireless communication schemes) included in the wireless communication interface 933.

[0216] Each of the antennas 937 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used by the wireless communication interface 933 to transmit and receive wireless signals. Figure 10 As shown, the car navigation device 920 may include multiple antennas 937. Although Figure 10 An example is shown in which the car navigation device 920 includes multiple antennas 937, but the car navigation device 920 may also include a single antenna 937.

[0217] Furthermore, the car navigation device 920 may include an antenna 937 for each wireless communication scheme. In this case, the antenna switch 936 can be omitted from the configuration of the car navigation device 920.

[0218] Battery 938 via feeder to Figure 10 The various blocks of the car navigation device 920 shown are powered, and the feeders are partially shown as dashed lines in the figure. Battery 938 accumulates the power supplied from the vehicle.

[0219] In the electronic devices 200 and 400 according to embodiments of the present disclosure, for example by... Figure 10In the case of the illustrated car navigation device 920, at least a portion of the functions of the processing units 202 and 402 included in electronic devices 200 and 400, respectively, can also be implemented by the processor 921. For example, the processor 921 can execute the functions of processing unit 202 or 402 to request other electronic devices to perform cooperative sensing or to cooperate with the source sensing electronic device to perform cooperative sensing when the sensing result is incorrect during the execution of the target sensing task, thereby achieving at least one of the following beneficial effects: improving the accuracy of target detection (e.g., including single target detection and multiple target detection) and tracking, reducing power consumption, supporting multiple sensing cooperation methods to adapt to different application scenarios, enhancing the robustness of the system and its adaptability to environmental changes, and saving bandwidth resources by utilizing semantic communication.

[0220] The technology disclosed herein can also be implemented as an in-vehicle system (or vehicle) 940 comprising one or more of the following blocks: a car navigation device 920, an in-vehicle network 941, and a vehicle module 942. The vehicle module 942 generates vehicle data (such as vehicle speed, engine speed, and fault information) and outputs the generated data to the in-vehicle network 941.

[0221] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that those skilled in the art will understand that all or any step or component of the methods and apparatus of this disclosure can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in the form of hardware, firmware, software or a combination thereof. This is something that those skilled in the art can achieve by using their basic circuit design knowledge or basic programming skills after reading the description of this disclosure.

[0222] Furthermore, this disclosure also proposes a program product storing machine-readable instruction code. When the instruction code is read and executed by a machine, the method described above according to embodiments of this disclosure can be performed.

[0223] Accordingly, the storage medium used to carry the program product storing machine-readable instruction code is also included in this disclosure. The storage medium includes, but is not limited to, floppy disks, optical disks, magneto-optical disks, memory cards, memory sticks, etc.

[0224] In the case of implementing this disclosure through software or firmware, transmission from a storage medium or network to a computer with a dedicated hardware architecture (e.g., Figure 11 The general-purpose computer 1700 shown is equipped with the programs constituting the software. When various programs are installed on the computer, it is able to execute programs such as those described above. Figures 2 to 10 The description includes various functions, etc.

[0225] exist Figure 11In this configuration, the Central Processing Unit (CPU) 1701 performs various processes based on programs stored in the Read-Only Memory (ROM) 1702 or programs loaded into the Random Access Memory (RAM) 1703 from the Storage Section 1708. The RAM 1703 also stores data required as needed when the CPU 1701 performs various processes. The CPU 1701, ROM 1702, and RAM 1703 are interconnected via a bus 1704. An Input / Output Interface 1705 is also connected to the bus 1704.

[0226] The following components are connected to the input / output interface 1705: input section 1706 (including keyboard, mouse, etc.), output section 1707 (including monitor, such as cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.), storage section 1708 (including hard disk, etc.), and communication section 1709 (including network interface card, such as LAN card, modem, etc.). The communication section 1709 performs communication processing via a network, such as the Internet. If necessary, a drive 1710 may also be connected to the input / output interface 1705. Removable media 1711, such as disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on the drive 1710 as needed, so that computer programs read from them can be installed into the storage section 1708 as needed.

[0227] When the above series of processes are implemented by software, the program constituting the software is installed from a network such as the Internet or a storage medium such as removable media 1711.

[0228] Those skilled in the art will understand that such storage media are not limited to Figure 11 The illustration shows a removable medium 1711 containing a program, distributed separately from the device to provide the program to the user. Examples of removable media 1711 include disks (including floppy disks (registered trademark)), optical disks (including optical disc read-only memory (CD-ROM) and digital versatile disks (DVD)), magneto-optical disks (including mini-discs (MD) (registered trademark)), and semiconductor memory. Alternatively, the storage medium may be ROM 1702, a hard disk included in storage section 1708, etc., containing programs and distributed to the user along with the device containing them.

[0229] In addition, this technology can also be implemented as follows.

[0230] Option 1. An electronic device, comprising:

[0231] At least one processor; and

[0232] At least one memory, including computer program code, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute via the at least one processor:

[0233] In response to an error in the perception result of a specific target among the sensing targets using the first sensing signal, a collaborative sensing request is sent to other electronic devices so that the specific target can be perceived using a second sensing signal based on feedback information provided by the other electronic devices, including information related to the specific target.

[0234] Option 2. The electronic device according to Option 1, wherein the electronic device is a base station or user equipment performing single-base sensing of the sensing target, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0235] In response to an error in the perception result of the specific target using the first sensing signal, a collaborative sensing request is sent to other base stations and / or user equipment, and the second sensing signal is used to perceive the specific target based on feedback information from other base stations and / or user equipment, including information related to the specific target.

[0236] Solution 3. The electronic device according to Solution 1, wherein the electronic device is a base station or user equipment acting as a sensing receiver in a dual-base sensing mode for the sensing target, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0237] In response to an error in the perception result of the specific target using the first sensing signal, a cooperative sensing request is sent to other base stations and / or user equipment, and feedback information provided by other base stations and / or user equipment, including information related to the specific target, is transmitted to the sensing transmitter in the bi-base sensing mode of the sensing target, so that the sensing transmitter uses the second sensing signal to perceive the specific target.

[0238] Option 4. The electronic device according to any one of Options 1-3, wherein the collaborative sensing request includes sensing collaboration method information, information related to the specific target, and information about errors in the sensing result.

[0239] Option 5. The electronic device according to Option 4, wherein the sensing coordination method information includes sensing reference signal parameters and information indicating whether the other electronic device is a transmitter or a receiver.

[0240] Option 6. The electronic device according to Option 5, wherein the sensing reference signal parameters include: carrier frequency, bandwidth, waveform, modulation scheme, transmit power, synchronization information and channel state information, and information regarding errors in the sensing results including information indicating the number of specific targets in which the sensing results are erroneous.

[0241] Option 7. An electronic device according to any one of Options 1 to 6, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0242] Other electronic devices that are at a distance greater than a predetermined threshold are selected for collaborative sensing, such that the difference between the echo signal of a specific target received by the electronic device and the echo signal of the specific target received by the other electronic devices is greater than a predetermined degree.

[0243] Option 8. The electronic device according to Option 7, wherein the predetermined threshold is set based on at least one of the following: the sensing signal frequency, the sensing environment, the target characteristics, the antenna characteristics, and the desired sensing performance index.

[0244] Option 9. The electronic device according to Option 8, wherein the electronic device is a base station, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0245] Based on one or more of the specific target's last known position, speed, direction, and trajectory before the perception result erred, the possible search area for the specific target after a predetermined time is predicted.

[0246] Other electronic devices will be selected as candidates, including candidate base stations capable of covering the possible search area.

[0247] Alternatively, a base station arbitrarily selected from the candidate base stations can be used as the other electronic device participating in cooperative sensing; or, a candidate base station satisfying at least one of the following conditions can be used as the other electronic device participating in cooperative sensing:

[0248] The candidate base station has the highest signal strength in the possible search area; and

[0249] The difference between the echo signal of a specific target received by the candidate base station and the echo signal of the specific target received by the base station is greater than a predetermined degree.

[0250] Option 10. An electronic device according to any one of Options 1 to 9, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0251] Semantic information about the specific target extracted from the perceptual semantic knowledge base based on the perceptual task type is encoded, and the encoded semantic information is included in the collaborative perception request and sent to the other electronic devices, so that the other electronic devices can perform collaborative perception of the specific target based on the information obtained by decoding the encoded semantic information.

[0252] Option 11. An electronic device according to any one of Options 1 to 9, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0253] The semantic information about the specific target extracted from the perceptual semantic knowledge base based on the perceptual task type is sent to the other electronic devices so that the other electronic devices can perform collaborative perception based on the semantic information about the specific target.

[0254] Option 12. An electronic device according to any one of Options 1 to 9, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0255] After receiving encoded semantic information about the specific target from the other electronic device, the electronic device decodes the encoded semantic information to obtain information related to the specific target.

[0256] Scheme 13. An electronic device according to any one of Schemes 10 to 12, wherein the perceptual semantic knowledge base is stored in at least one of the following: the electronic device, the other electronic device, and the perceptual management function unit on the core network side.

[0257] Scheme 14. An electronic device according to any one of Schemes 10 to 13, wherein the perceptual semantic knowledge base defines a semantic information model in a synesthetic integration scenario, the semantic information model including a format and encoding for representing and transmitting semantic data.

[0258] Option 15. An electronic device according to any one of Options 10 to 14, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0259] The perceptual semantic knowledge base can be accessed through the following interfaces: a first input interface for querying the perceptual semantic knowledge base; and a first output interface for outputting semantic knowledge.

[0260] Option 16. An electronic device according to any one of Options 10 to 15, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0261] During the construction of the perceptual semantic knowledge base, semantic perceptual data required for constructing the perceptual semantic knowledge base is transmitted between the electronic device and the perceptual semantic knowledge base through a second input / output interface.

[0262] Option 17. An electronic device according to any one of Options 1 to 16, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0263] Before sensing the target, a signal supporting multi-target sensing capability is sent to the sensing management function unit on the core network side; and

[0264] Receive the multi-target perception task assigned by the perception management function unit.

[0265] Option 18. An electronic device according to any one of Options 1 to 17, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0266] While waiting for the other electronic devices to provide collaborative sensing information related to the specific target, the first sensing signal is turned off, or the beam in the first sensing signal used for sensing the specific target is turned off.

[0267] Option 19. An electronic device according to any one of Options 1 to 17, wherein the sensing target comprises a plurality of targets, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0268] When the specific target is perceived using the second sensing signal, the other targets among the plurality of targets, excluding the specific target, are continuously perceived using the first sensing signal.

[0269] Option 20. An electronic device according to any one of Options 1 to 19, wherein the information associated with the particular target includes one or more of the particular target's shape, size, reflectivity, position, speed, trajectory, and / or predicted future trajectory.

[0270] Option 21. An electronic device, comprising:

[0271] At least one processor; and

[0272] At least one memory, including computer program code, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0273] If the source sensing electronic device makes a mistake in sensing a specific target among the sensing targets using the first sensing signal, the electronic device responds to the collaborative sensing request sent by the source sensing electronic device by providing feedback information, including information related to the specific target, to the source sensing electronic device, so that the source sensing electronic device uses the second sensing signal to sense the specific target based on the information related to the specific target.

[0274] Option 22. The electronic device according to Option 21, wherein the collaborative sensing request includes sensing collaboration method information, information related to the specific target, and errors in the sensing result.

[0275] Option 23. The electronic device according to Option 22, wherein the sensing coordination mode information includes sensing reference signal parameters and information indicating whether the electronic device is a transmitter or a receiver.

[0276] Solution 24. The electronic device according to Solution 21, wherein the distance between the electronic device and the source sensing electronic device is greater than a predetermined threshold, such that the difference between the echo signal of the specific target received by the electronic device and the echo signal of the specific target received by the source sensing electronic device is greater than a predetermined degree.

[0277] Option 25. The electronic device according to Option 24, wherein the predetermined threshold is set based on at least one of the following: the sensing signal frequency, the sensing environment, target characteristics, antenna characteristics, and desired sensing performance indicators.

[0278] Option 26. The electronic device according to Option 25, wherein the source sensing electronic device and the electronic device are base stations, and the electronic device is located within a possible search area for a predetermined period after the perception result of the specific target is erroneous, the possible search area being predicted based on one or more of the specific target's last known position, movement speed, movement direction, and movement trajectory before the perception result is erroneous, and the electronic device satisfies the following condition:

[0279] The electronic device has the strongest signal strength in the possible search area; and

[0280] The difference between the echo signal of a specific target received by the electronic device and the echo signal of the specific target received by the source sensing electronic device is greater than a predetermined degree.

[0281] Option 27. An electronic device according to any one of Options 21 to 26, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0282] The source sensing electronic device receives encoded semantic information contained in the collaborative sensing request to perceive the specific target based on information obtained by decoding the encoded semantic information.

[0283] The encoded semantic information is obtained by encoding semantic information related to the specific target extracted from the perceptual semantic knowledge base based on the perceptual task type by the source perceptual electronic device.

[0284] Option 28. The electronic device according to Option 27, wherein the encoded semantic information is obtained by encoding the semantic information about the specific target using a pre-trained artificial intelligence model by the source-aware electronic device, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0285] The encoded semantic information is decoded using a pre-trained artificial intelligence model deployed locally or obtained from the source sensing electronic device.

[0286] Option 29. An electronic device according to any one of Options 21 to 26, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0287] The source sensing electronic device receives semantic information related to the specific target contained in the collaborative sensing request, so as to extract semantic features related to the specific target from the sensing semantic knowledge base based on the obtained semantic information and perform collaborative sensing of the specific target based on the extracted semantic features, wherein the semantic information related to the specific target is extracted from the sensing semantic knowledge base based on the sensing task type.

[0288] Option 30. An electronic device according to any one of Options 21 to 26, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0289] Based on the perception task type, semantic information related to the perceived specific target is extracted from the perception semantic knowledge base. The extracted semantic information is encoded to generate encoded semantic information, and the encoded semantic information is provided to the source perception electronic device so that the source perception electronic device can decode it to obtain information related to the specific target.

[0290] Scheme 31. An electronic device according to any one of Schemes 27 to 30, wherein the perceptual semantic knowledge base defines a semantic information model in a synesthetic integration scenario, the semantic information model including a format and encoding for representing and transmitting semantic data.

[0291] Option 32. An electronic device according to any one of Options 27 to 31, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0292] The perceptual semantic knowledge base can be accessed through the following interfaces: a first input interface for querying the perceptual semantic knowledge base; and a first output interface for outputting semantic knowledge.

[0293] Option 33. An electronic device according to any one of Options 27 to 32, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor:

[0294] During the construction of the perceptual semantic knowledge base, semantic perception training data required for training the perceptual semantic knowledge base to complete the construction is transmitted between the electronic device and the perceptual semantic knowledge base through a second input / output interface.

[0295] Scheme 34. An electronic device according to any one of Schemes 27 to 33, wherein the perceptual semantic knowledge base is stored in at least one of: the electronic device, the source perceptual electronic device, and the perceptual management function unit on the core network side.

[0296] Option 35. An electronic device according to any one of Options 21 to 34, wherein the information related to the particular target includes one or more of the particular target's shape, size, reflectivity, position, speed, trajectory, and / or predicted future trajectory.

[0297] Option 36. A method for an integrated communication and sensing system, comprising:

[0298] In response to an error in the perception result of a specific target among the sensing targets using the first sensing signal, the source sensing electronic device sends a collaborative sensing request to other sensing electronic devices so as to perceive the specific target using a second sensing signal based on feedback information provided by the other sensing electronic devices, including information related to the specific target.

[0299] Option 37. A method for an integrated communication and sensing system, comprising:

[0300] If the source sensing electronic device fails to perceive a specific target within the sensing target using the first sensing signal, other sensing electronic devices respond to the collaborative sensing request sent by the source sensing electronic device by providing feedback information, including information related to the specific target, to the source sensing electronic device. This allows the source sensing electronic device to perceive the specific target using the second sensing signal based on the information related to the specific target.

[0301] Scheme 38. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed, perform the method according to Scheme 37 or 38.

[0302] It should also be noted that in the apparatus, method, and system of this disclosure, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of this disclosure. Furthermore, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order. Some steps can be performed in parallel or independently of each other.

[0303] Finally, it should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Furthermore, unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0304] While embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, it should be understood that the embodiments described above are merely illustrative and do not constitute a limitation thereof. Those skilled in the art can make various modifications and alterations to the above embodiments without departing from the spirit and scope of the present disclosure. Therefore, the scope of the present disclosure is defined only by the appended claims and their equivalents.

Claims

1. An electronic device, comprising: At least one processor; and At least one memory, including computer program code, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute via the at least one processor: In response to an error in the perception result of a specific target among the sensing targets using the first sensing signal, a collaborative sensing request is sent to other electronic devices so that the specific target can be perceived using a second sensing signal based on feedback information provided by the other electronic devices, including information related to the specific target.

2. The electronic device according to claim 1, wherein, The electronic device is a base station or user equipment that performs single-base sensing of the sensing target, and the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor: In response to an error in the perception result of the specific target using the first sensing signal, a collaborative sensing request is sent to other base stations and / or user equipment, and the second sensing signal is used to perceive the specific target based on feedback information from other base stations and / or user equipment, including information related to the specific target.

3. The electronic device according to claim 1, wherein, The electronic device is a base station or user equipment acting as a sensing receiver in a dual-base sensing mode for the sensing target. The at least one memory and the computer program code are configured to, through the at least one processor, cause the electronic device to execute: In response to an error in the perception result of the specific target using the first sensing signal, a cooperative sensing request is sent to other base stations and / or user equipment, and feedback information provided by other base stations and / or user equipment, including information related to the specific target, is transmitted to the sensing transmitter in the bi-base sensing mode of the sensing target, so that the sensing transmitter uses the second sensing signal to perceive the specific target.

4. The electronic device according to any one of claims 1 to 3, wherein, The at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor: Other electronic devices that are at a distance greater than a predetermined threshold are selected for collaborative sensing, such that the difference between the echo signal of the specific target received by the electronic device and the echo signal of the specific target received by the other electronic devices is greater than a predetermined degree.

5. The electronic device according to any one of claims 1 to 3, wherein, The at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor: Semantic information about the specific target extracted from the perceptual semantic knowledge base based on the perceptual task type is encoded, and the encoded semantic information is included in the collaborative perception request and sent to the other electronic devices, so that the other electronic devices can perform collaborative perception of the specific target based on the information obtained by decoding the encoded semantic information.

6. An electronic device, comprising: At least one processor; and At least one memory, including computer program code, wherein the at least one memory and the computer program code are configured to cause the electronic device to execute, via the at least one processor: If the source sensing electronic device makes a mistake in sensing a specific target among the sensing targets using the first sensing signal, the electronic device responds to the collaborative sensing request sent by the source sensing electronic device by providing feedback information, including information related to the specific target, to the source sensing electronic device, so that the source sensing electronic device uses the second sensing signal to sense the specific target based on the information related to the specific target.

7. The electronic device according to claim 6, wherein, The distance between the electronic device and the source sensing electronic device is greater than a predetermined threshold, such that the difference between the echo signal of the specific target received by the electronic device and the echo signal of the specific target received by the source sensing electronic device is greater than a predetermined degree.

8. A method for an integrated communication and sensing system, comprising: In response to an error in the perception result of a specific target among the sensing targets using the first sensing signal, the source sensing electronic device sends a collaborative sensing request to other sensing electronic devices so as to perceive the specific target using a second sensing signal based on feedback information provided by the other sensing electronic devices, including information related to the specific target.

9. A method for an integrated communication and sensing system, comprising: If the source sensing electronic device fails to perceive a specific target within the sensing target using the first sensing signal, other sensing electronic devices respond to the collaborative sensing request sent by the source sensing electronic device by providing feedback information, including information related to the specific target, to the source sensing electronic device. This allows the source sensing electronic device to perceive the specific target using the second sensing signal based on the information related to the specific target.

10. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed, perform the method according to claim 8 or 9.

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