Method and system for communication aware integration

Abstract

The invention relates to a method and a system for communication-aware integration. The method comprises the following steps of: processing an entity from artificial intelligence / machine learning (AI / ML) by using an application function (AF), and generating a migration model by using the AI / ML to process the entity; transmitting, by the AF, a correction demand for the generated migration model to a network data analysis function (NWDAF), the correction demand including information about the migration model generated from the AI / ML processing entity, and transmitting, by the AF, a correction demand for the generated migration model to a network data analysis function (NWDAF), the correction demand including information about the migration model generated from the AI / ML processing entity; receiving, by the AF, an analysis result from the NWDAF, the analysis result based at least on the transmitted information relating to the migration model generated from the AI / ML processing entity; and correcting, by the AF, the generated migration model based on the received analysis result.

Description

Technical Field

[0001] The present disclosure relates to Integrated Sensing And Communications (ISAC), and in particular to a method and system for ISAC. Background Art

[0002] As a key technology of the sixth generation (6G) mobile communication, the communication-awareness integrated network has been widely studied and paid attention to. Communication-awareness integration refers to the unified design of communication functions and perception functions through joint design of air interface and protocol, reuse of time-frequency-space resources, and sharing of hardware equipment, so that the wireless network can achieve high-precision and refined perception functions while performing high-quality communication interaction, thereby improving the overall performance and service capabilities of the network. The communication-awareness integrated network will go through three stages: service coexistence, capability mutual assistance, and network mutual benefit. In the most mature network mutual benefit stage, the communication-awareness integration can improve the spectrum utilization and equipment reuse rate while taking into account the communication-awareness function through the joint design of air interface and protocol, and the sharing of software and hardware equipment. Therefore, it is hoped that a reasonable and feasible protocol stack can be designed.

[0003] The introduction of perception functions will bring more data on the original basis. Although the existing computing resources are sufficient and powerful enough, it still brings great challenges to data processing and communication transmission. In recent years, wireless communication networks have begun to be equipped with edge intelligence, but these works are built on a designed training set. Learning performance depends on the work of the training set derived from traditional management methods, which leads to limitations in wireless resource management in some special cases. The current data set collection work is already underway. Transfer learning can effectively apply the knowledge learned in one field to another related field to improve the learning effect and the generalization ability of the model.

[0004] Downlink Control Information (DCI) is a signaling format used to control downlink data transmission. In wireless communication systems, DCI is used to transmit scheduling and configuration information about the downlink to terminal devices (such as mobile phones, wireless modules, etc.) so that the terminal devices can correctly receive and process downlink data. With the introduction of perception and computing resources, new DCI formats need to be designed to cope with the design of multi-modal communication perception integration solutions enabled by transfer learning. In the 5G standard, Demodulation Reference Signals (DMRS) can be used for perception. Among them, the staggered DMRS subcarriers of the Physical Downlink Shared Channel (PDSCH) are used for downlink perception, while the non-staggered DMRS subcarrier groups of the Physical Uplink Shared Channel (PUSCH) are used for uplink perception. However, there is a lack of integrated design for the Physical Downlink Control Channel (PDCCH) and the Physical Uplink Control Channel (PUCCH). These channels carry scheduling and other control information through downlink control information (DCI) and uplink control information (UCI), including transmission format, resource allocation, uplink and downlink scheduling, power control, and uplink and downlink retransmission information.

[0005] With the integration and development of 5G (Fifth Generation, 5G) and Artificial Intelligence (AI) technology, network intelligence has become one of the hottest topics for various standards and industry organizations. At the beginning of the formulation of 5G standards, 3GPP considered applying AI and big data analysis technologies to 5G networks. The Network Data Analytics Function (NWDAF) is a standardized network element newly introduced by 3GPP in the 5G R15 version. As a 5G network AI big data engine, NWDAF is responsible for data collection, model training, reasoning judgment and intelligent prediction, and outputs analysis results for network, gateway and application execution policy decisions.

[0006] Transfer learning can use the correlation and similarity information between different tasks to save energy and improve efficiency. Therefore, it is valuable to apply transfer learning to 6G wireless communications, especially to integrated communication and perception networks. At present, transfer learning has been widely used in access point switching energy efficiency, dynamic allocation of spectrum resources, content popularity prediction, indoor wireless positioning and network intrusion detection. Summary of the invention

[0007] This Summary is provided to introduce concepts in a simplified form that are described in detail later in the Detailed Description.

[0008] In one aspect of the present disclosure, a method for communication perception integration is provided, including: generating, by an application function (AF), a migration model from an artificial intelligence / machine learning (AI / ML) processing entity; sending, by the AF, a correction requirement for the generated migration model to a network data analysis function (NWDAF), the correction requirement including information related to the migration model generated from the AI / ML processing entity; receiving, by the AF, an analysis result from the NWDAF, the analysis result being based at least on the sent information related to the migration model generated from the AI / ML processing entity; and correcting, by the AF, the generated migration model based on the received analysis result.

[0009] In another aspect of the present disclosure, a storage medium storing instructions is provided, which, when executed by a processor, can cause the method for communication-aware integration as described herein to be performed.

[0010] Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The preferred embodiments of the present disclosure are described below with reference to the accompanying drawings. The drawings described herein are used to provide a further understanding of the present disclosure, and each drawing together with the following detailed description is included in this specification and forms a part of the specification for explaining the present disclosure. It should be understood that the drawings described below only relate to some embodiments of the present disclosure and do not constitute a limitation on the present disclosure.

[0012] Figure 1 An exemplary system and protocol stack for communication-aware integration according to an embodiment of the present disclosure are shown.

[0013] Figure 2 An example of segmented AI / ML inference according to an embodiment of the present disclosure is shown.

[0014] Figure 3 is a flowchart illustrating a method for model migration on a network layer according to an embodiment of the present disclosure.

[0015] Figure 4 is a flowchart illustrating a method for communication awareness integration according to an embodiment of the present disclosure.

[0016] Figure 5 is a block diagram showing a first example of a schematic configuration of a base station to which the technology of the present disclosure can be applied.

[0017] Figure 6 is a block diagram showing a second example of a schematic configuration of a base station to which the technology of the present disclosure can be applied.

[0018] Figure 7 is a block diagram showing an example of a schematic configuration of a smartphone to which the technology of the present disclosure can be applied.

[0019] Figure 8 is a block diagram showing an example of a schematic configuration of a car navigation device to which the technology of the present disclosure can be applied.

[0020] It should be understood that, for ease of description, the sizes of the various parts shown in the drawings are not necessarily drawn according to the actual proportional relationship. The same or similar reference numerals are used in the various drawings to represent the same or similar parts. Therefore, once an item is defined in one drawing, it may not be further discussed in subsequent drawings. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure, but it is obvious that the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. The drawings and the description of the embodiments below are actually only illustrative and are by no means any limitation to the present disclosure and its application or use. It should be understood that the present disclosure can be implemented in various forms and should not be interpreted as being limited to the embodiments set forth herein.

[0022] In addition, when describing exemplary embodiments of the present disclosure in conjunction with the accompanying drawings below, for the sake of clarity and conciseness, not all features of the embodiments are described in the specification. It should be noted that in order to avoid obscuring the present disclosure due to unnecessary details, only processing steps and / or device structures closely related to at least the scheme according to the present disclosure are shown in the accompanying drawings, while other details that are not closely related to the present disclosure are omitted.

[0023] It should be understood that the various steps recorded in the method embodiments of the present disclosure can be performed in different orders, and / or performed in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown in the execution. The scope of the present disclosure is not limited in this respect. Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments should be interpreted as being merely exemplary and do not limit the scope of the present disclosure.

[0024] In the present disclosure, the terms "first", "second", etc. are used merely to distinguish elements or steps, but are not intended to indicate time sequence, priority or importance.

[0025] Figure 1 An exemplary system 100 and protocol stack 110 for communication-aware integration according to an embodiment of the present disclosure is shown.

[0026] As shown in the figure, the communication-aware integrated system 100 may include an access point / base station (BS) 101 equipped with a communication-aware duplex antenna, a UE 102 based on communication technology perception, and other targets 103 perceived based on other technologies (such as radar, sensors, cameras, etc.).

[0027] Although not shown, those skilled in the art will appreciate that the communication and perception integrated system 100 may include a stationary unit or a mobile unit equipped with various sensors. The various sensors may include wireless communication sensors, radars, laser radars, GPS receivers, cameras, etc. operating in various frequency bands. The stationary unit may be, for example, a base station. The mobile unit may be, for example, a vehicle.

[0028] The communication perception integrated protocol stack 110 includes layer 1 (L1), layer 2 (L2) and layer 3 (L3). Layer 1 corresponds to the functions of the physical layer. Layer 2 corresponds to the data link layer, which implements migration signaling bearer and communication and perception data bearer respectively. Layer 3 corresponds to the network layer, the control plane implements migration learning training, and the user plane implements communication and perception data collection.

[0029] The present disclosure proposes a communication perception integrated protocol stack solution design under multi-modal empowerment. The solution includes: firstly, establishing a wireless interface protocol stack solution design for synaesthesia integration, scheduling time and frequency resources for the two functions of synaesthesia by designing downlink control information at the physical layer, realizing the preparation of different modal communication and perception data at the data link layer, and realizing migration model training at the network layer through the interaction of network data analysis functions.

[0030] Physical Layer

[0031] On the physical layer, DCI format 0_0 is modified for the physical uplink control channel (PUCCH); and DCI format 1_1 is modified for the physical downlink control channel (PDCCH).

[0032] First, let's discuss DCI format 0_0, which is used for scheduling PUSCH in a cell. The specific fields of DCI format 0_0 are shown in Table 1 below:

[0033] Table 1 DCI format 0_0 for arranging PUSCH

[0034]

[0035] For DCI format 0_0, the format indication field (length of 1 bit) of DCI is always 0, which indicates the UL DCI format.

[0036] The frequency domain resource allocation field is set to 4 bits, of which the first 3 bits are used for communication and the fourth bit is used for perception.

[0037] For the frequency domain resource allocation field, resource block group (RBG) level bitmap resource allocation (resource allocation Type 0) and continuous resource allocation (resource allocation Type 1) are supported, and the UE can configure one or both of them. The number of spectrum resource allocations is Bit. It is the size of the activated uplink bandwidth part (Bandwidth Part, BWP). The meaning of depends on the search space. The search space refers to the set of all PDCCH candidates under a certain aggregation level. The available control channel elements (CCE) are divided into two search spaces, namely the common search space and the UE-specific search space. CCE is the logical resource of PDCCH and needs to be mapped to the physical resource of CORESET for transmission. When transmitting in the common search space, Indicates the size of the initial BWP; when transmitting in the UE-specific search space, BWP needs to be activated when certain conditions are met.

[0038] For the time domain resource allocation field, this field indicates the scheduled time slot, starting symbol and duration. The bit length of the time domain resource allocation field is X, and the specific value configuration is determined according to the resource allocation list rules in the Radio Resource Control (RRC). For each PUSCH scheduling, the time domain resource allocation of DCI 0_0 corresponds to a specific row number (row index). If configured, the value provided here will override the value received in the corresponding PUSCH-ConfigCommon.

[0039] When the UE transmits a service block through DCI scheduling and does not report periodic channel state information (CSI) in PUSCH, or the UE transmits a service block in PUSCH and reports periodic CSI, the value m of the time domain resource assignment field is used to determine the row index m+1 in the time domain resource allocation table for searching in the allocation table (the normal cyclic prefix (NCP) can be found in 3GPPTR 38.214 Table 6.1.2.1.1-2, and the extended cyclic prefix (ECP) can be found in 3GPP TR 38.214 Table 6.1.2.1.1-3, where the index row defines the slot offset K2, the start and length indicator (SLIV), or the direct start symbol S and the allocation length L, and the PUSCH mapping type to be applied in the PUSCH transmission).

[0040] When the UE is scheduled by DCI and triggers the reporting of non-periodic CSI through the channel state information CSI request field (CSI RequestField) on PUSCH, but no service block is transmitted, the value m of the time domain resource assignment (Time domainresource assignment) field is used to determine the row index m+1 in the time domain resource allocation table for search in the allocation table. At this time, the allocation table is defined by the parameter pusch-TimeDomainAllocationList configured in the pusch-Config IE.

[0041] The uplink / supplementary uplink (UL / SUL) indication field is fixed to 1 bit and is used to indicate whether SUL is configured. For example, this bit can be set to 0 to indicate that SUL is not configured (i.e., only UL is configured), and this bit can be set to 1 to indicate that SUL is configured. The UE is configured with SUL, but there is only 1 carrier for PUSCH transmission. In other words, the SUL band can only be used for uplink, and is used as an auxiliary band in 5G NR. It has a wide coverage range and can be used to implement perception functions. Perception can be performed in the SUL band, but care should be taken to avoid conflicts with communication.

[0042] For DCI format 1_1, it is used for scheduling PDSCH in the cell. The specific fields of DCI format 1_1 are shown in Table 2 below:

[0043] Table 2 DCI format 1_1 used to schedule PDSCH

[0044]

[0045] The DCI format indication field (1 bit) is always 1, indicating the DL DCI format.

[0046] For frequency domain resource allocation, the resource allocation type indicates the resource allocation in the frequency domain, which is mainly divided into three types: type 0 (bitmap), type 1 (starting from RB, nRB) and dynamic switching. The resource allocation type is changed in the RRC through the DCI format identifier. Type 0 is configured in the bitmap format and type 1 is configured in the resource indicator value (RIV) format. The resource allocation type specifies how the scheduler allocates resource blocks for each transmission. In terms of flexibility, the way to give the greatest flexibility to resource block allocation is to use a string of bit maps (bit streams), in which each bit represents each resource block. This approach can achieve maximum flexibility, but it can make the resource allocation process too complicated or generate too much data (too long bit maps) when allocating resources.

[0047] For time domain resource allocation, the bit length is 4, and its specific value configuration is determined according to the resource allocation list rules in RRC. For each PDSCH scheduling, the time domain resource allocation of DCI 1_1 corresponds to a specific row number (row index). If configured, the value provided here will override the value received in the corresponding PDSCH-ConfigCommon.

[0048] Transmission configuration indication, because the integration of communication perception requires the activation of the high-level parameter tci-PresentInDCI, when 0 or 3 bits can be selected, it is set to 3 bits. The base station will indicate the state of the transmission configuration indication to be adopted by the final UE through the field transmission configuration indication (FieldTransmissionConfigIndication) in the DCI to match the implementation of the high-precision perception function. In other words, when supporting communication perception integration, the transmission configuration indication is fixed to 3 bits, which enables the high-level parameter tci-PresentInDCI.

[0049] Data Link Layer

[0050] The communication perception integration method and system involve the collection and processing of multimodal communication perception data, and the transmission of the processed and encapsulated communication perception data via a data link layer. The multimodal communication perception data includes communication data and perception data. The communication data can come from wireless communication transceivers operating in various frequency bands.

[0051] The data collection process of multimodal communication and perception data from multiple sources can include two main stages: Off-line Planning and On-field Collection.

[0052] Similar to any experimental design, the field planning phase is critical to the success of any data collection. It mainly involves clearly defining the target set (e.g., the units to be collected (such as base stations or mobile vehicles, etc.) and the sensors deployed in each unit) and the convergence of the time and location of data collection. Sensors can include, for example, wireless and environmental sensors such as wireless communication transceivers (such as mmWave phased arrays or sub-6GHz MIMO), and sensor suites such as RGB cameras, lidars, radars, and GPS receivers.

[0053] Next comes the actual field data collection, which involves field of view (FoV) alignment / cropping, capture rate alignment, real-time monitoring, etc.

[0054] Different sensing devices, such as millimeter wave phased array, RGB camera, LiDAR, etc., have different fields of view (FoV) and ranges. Field of view alignment requires extracting and fusing the physical space information implicit in multimodal communication and perception data (such as millimeter wave received power vector, RGB image, depth map, laser point cloud, radar point cloud, GPS location signal), that is, the FoV and range of different sensory signals. In order to achieve high-quality multimodal datasets with multiple sources using multiple sensors, the sensor data on different devices must be aligned before starting the data collection process.

[0055] Different sensing devices, such as millimeter wave phased array, RGB camera, lidar, etc., may have different data capture rates. In some embodiments, cross-modal data alignment can be achieved using, for example, timestamps.

[0056] Data can then be collected through real-time monitoring.

[0057] The collected communication and perception data need to be processed as raw data, such as synchronizing data from different sources based on timestamps, filtering data based on application scenarios of interest, and verifying synchronized and filtered data.

[0058] The processed multi-source communication and perception data are encapsulated and transmitted through the data link layer. The data link layer includes four sublayers: the Medium Access Control (MAC) layer, the Radio Link Control (RLC) layer, the Packet Data Convergence Protocol (PDCP) layer, and the Service Data Adaptation Protocol (SDAP) layer.

[0059] The physical layer provides the MAC sublayer with the transport channel-level service, the MAC sublayer provides the radio link control sublayer with the logical channel-level service, the PDCP sublayer provides the SDAP sublayer with the radio bearer-level service, the SDAP sublayer provides the upper layer with the 5G core network QoS flow-level service, and the data link layer is responsible for the multiplexing function of multiple logical channels to the same transport channel. After the IP packet enters the SDAP sublayer, the SDAP packet header is added, and the SDAP packet data unit (PDU) is generated. This PDU is the service data unit (SDU) of the PDCP sublayer. After being processed by PDCP, the PDCP packet header is added, and the PDCP PDU is generated. This PDU is the SDU of the RLC sublayer. After being processed by RLC, the RLC sublayer packet header is added, and the RLC sublayer PDU is generated. The RLC sublayer segments the PDCP PDU and generates two RLC sublayer PDUs. The RLC sublayer PDUs of multiple resource blocks are processed at the data link layer, and multiple data link layer PDUs are placed in the same transport block for transmission.

[0060] Network Layer

[0061] The communication perception integration method and system of the disclosed embodiment may also involve an application data transfer (ADT) mechanism at the network layer, which supports application AI / ML data transmission by means of the ADT mechanism. The ADT transmission strategy includes a list of QoS profiles corresponding to their respective required time windows, and the time window list can be negotiated between the application function (AF) and the 5G core network.

[0062] AI / ML operations that are split between AI / ML endpoints are one of the three types of AI / ML operations that 5G systems can support. One use case for AI / ML operations that are split between AI / ML endpoints is split AI / ML inference. Figure 2 An example of segmented AI / ML inference according to an embodiment of the present disclosure is shown. Figure 2 The network AI / ML endpoints shown in are AI / ML processing entities (e.g., edge servers / cloud servers), but not the end devices, i.e., UEs.

[0063] UE triggers segmentation inference. UE and AI / ML server / application function (AF) negotiate segmentation inference operation via application layer. Auxiliary information from 5G core (5GC) is required to assist AI / ML server / AF in making corresponding decisions for segmentation inference, such as the number of layers used to process segmentation tasks (e.g., AI / ML operations) from UE and AI / ML processing entities (e.g., edge servers / cloud servers).

[0064] AF requests or subscribes to one or more NWDAFs for analysis to generate AI / ML auxiliary information. NWDAF collects information from AF about, for example, end-to-end performance between AI / ML processing entities in two adjacent layers (if multiple layers are involved). The collected information is used in NWDAF as a new input for analysis of one or more analysis IDs (e.g., Data Network (DN) performance, observed service experience). During the analysis process, NWDAF also interacts with other network functions (NetworkFunction) NF in 5GC to collect data.

[0065] The analysis results from the NWDAF can be converted into the auxiliary information required at the AF. Based on the auxiliary information and current system environment factors such as communication data rate, resources at the UE, etc., the AI / ML server / AF makes decisions on segmentation inference.

[0066] The communication-awareness integration method and system of the embodiments of the present disclosure may involve model migration at the network layer.

[0067] Figure 3 is a flow chart showing a method 300 for model migration on a network layer according to an embodiment of the present disclosure.

[0068] like Figure 3 As shown, the method 300 may include the following operations:

[0069] Operation 3000 : UE 301 and AI / ML server / AF 302 negotiate to trigger segmented AI / ML inference.

[0070] Operation 3001: AF 302 requests or subscribes to analysis from NWDAF 303. AF 302 can make a request to NWDAF 303 for model migration. AF 302 can include the following parameters in the subscription or request: (1) Analysis ID (i.e., "DN Performance", "Observed Service Experience"); (2) Area of ​​Interest; (3) Data Network Access Identifier (DNAI) and IP address or Fully Qualified Domain Name (FQDN) of the AI / ML processing entity. The AI / ML server / AF 302 can select which AI / ML processing entities are candidates for model migration and provide the Data Network Access Identifier and IP address or Fully Qualified Domain Name (FQDN) of the AI / ML processing entity as input parameters for the analysis.

[0071] Operation 3002 : NWDAF 303 subscribes to event exposure of information from AI / ML processing entities to AF 302. The required information may include end-to-end network performance data (e.g., latency, throughput, and packet loss rate) between each pair of AI / ML processing entities in two adjacent layers.

[0072] Operation 3003 : AF 302 generates a migration model from the AI / ML processing entities. The AI / ML processing entities inform AF 302 of information including end-to-end network performance data (e.g., latency, throughput, and packet loss rate) between each pair of AI / ML processing entities in two adjacent layers.

[0073] Specifically, AF 302 inputs the communication and perception data transmitted via the data link layer into the AI / ML processing entity to generate a migration model. AF 302 uses the communication and perception data transmitted via the data link layer to perform model training on the AI / ML processing entity to obtain parameters of the trained migration model.

[0074] In other words, for transfer learning between different modalities, the network layer sends a request instruction to the network data analysis layer. After receiving the response from the network data analysis layer, the network layer starts to prepare the machine learning entity based on the prepared modal data from the data link layer, thereby generating a transfer model.

[0075] Operation 3004: AF 302 sends a notification to NWDAF 303. The notification may include a correction requirement for model migration, which may include information associated with the generated migration model, such as parameters of the trained migration model. The notification may include end-to-end network performance data (e.g., latency, throughput, and packet loss rate) between each pair of AI / ML processing entities in two adjacent layers informed by the AI / ML processing entity to AF 302.

[0076] Operation 3005 : NWDAF 303 collects data information from other NFs 304. The collection may be based on the information included in the notification sent by AF 302 to NWDAF 303 in operation 3004. The collection may also be based on the analysis ID included in operation 3001.

[0077] Operation 3006 : NWDAF 303 analyzes the analysis ID (i.e., "data network performance", "observed service experience") and generates analysis results. The analysis results can be statistical and / or predictive. The information obtained / generated from the AI / ML processing entity in operation 3003 can serve as new input for the analysis.

[0078] The generated analysis results may include: statistics and / or predictions of end-to-end network performance data (e.g., latency, throughput, and packet loss rate) between each pair of AI / ML processing entities in two adjacent layers; statistics and / or predictions of the service rate of the uplink from the UE to each AI / ML processing entity; statistics and / or predictions of the packet delay of the uplink from the UE to each AI / ML processing entity; statistics and / or predictions of the packet loss rate of the uplink from the UE to each AI / ML processing entity.

[0079] Operation 3007 : NWDAF 303 responds to AF 302 with the analysis result, so that AF 302 can modify the migration model according to the analysis result.

[0080] Operation 3008 : AF 302 generates AI / ML auxiliary information based on the received analysis results and the information received from the UE to make decisions on the segmented AI / ML operation, i.e., model migration. One AI / ML auxiliary information can be generated based on one or more analyses / information. The AI / ML auxiliary information can be, for example, statistics / predictions about network conditions (e.g., latency, bit rate, communication service capability, reliability, etc.).

[0081] Operation 3009 : The AI / ML server / AF 302 notifies the UE of the decision via the application layer for model migration.

[0082] Through the model migration process according to the embodiment of the present disclosure, the modality of the current time and place can be effectively migrated for rich environmental information.

[0083] Figure 4 is a flow chart showing a method 400 for communication-aware integration according to an embodiment of the present disclosure.

[0084] like Figure 4 As shown, method 400 includes operation 401, in which a migration model is generated by the AF from an AI / ML processing entity.

[0085] As described above, AF can use the communication and perception data transmitted via the data link layer as input to the AI / ML processing entity, train the network represented by the AI / ML processing entity, and thus generate a migration model.

[0086] The method 400 may further include an operation 402 , in which the AF sends a correction requirement for the generated migration model to the NWDAF, where the correction requirement includes information related to the migration model generated from the AI / ML processing entity.

[0087] In some embodiments, the information related to the migration model generated from the AI / ML processing entity includes model parameters of the trained migration model.

[0088] In some embodiments, before operation 401, an analysis request for model migration is sent by the AF to the NWDAF, and a subscription request for information from the AI / ML processing entity is received by the AF from the NWDAF. In response to the subscription request for information from the AI / ML processing entity sent by the NWDAF, end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers may be sent by the AF to the NWDAF. In some embodiments, the end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers may be sent by the AF to the NWDAF together with the correction requirements for the generated migration model.

[0089] The method 400 may further include an operation 403 , in which an analysis result is received by the AF from the NWDAF, the analysis result being based at least on the transmitted information related to the migration model generated from the AI / ML processing entity.

[0090] In some embodiments, the analysis result may be based at least on the transmitted information related to the migration model generated from the AI / ML processing entity and the correction requirements for the generated migration model.

[0091] Since the correction requirement for the generated migration model contains information related to the generated migration model and the analysis result is obtained by taking this information into consideration, the analysis result can be used to guide the correction of the migration model.

[0092] In some embodiments, the NWDAF collects data from other NFs in addition to receiving information about the migration model generated from the AI / ML processing entity and network performance data between the AI / ML processing entities. The NWDAF may perform analysis based on the received and / or collected data to generate analysis results. In other words, the analysis results may also be based on data collected from other NFs. In some embodiments, the process of collecting data from other NFs may be based on information about the migration model generated from the AI / ML processing entity.

[0093] The method 400 may further include an operation 404 in which the generated migration model is revised by the AF based on the received analysis results.

[0094] In some embodiments, the method 400 may further include the AF generating AI auxiliary information and making AI / ML decisions based on the received analysis results and information received from a user equipment (UE), and informing the UE of the made AI / ML decisions for model migration.

[0095] In some embodiments, the method for communication and perception integration according to an embodiment of the present disclosure further includes providing a pair of DCIs including DCI_format0_0 and DCI_format1_1 at the physical layer for resource scheduling for both communication and perception functions. That is, for a physical uplink control channel (PUCCH), a modified DCI format 0_0 is provided; and for a physical downlink control channel (PDCCH), a modified DCI format 1_1 is provided.

[0096] The frequency domain resource allocation field of DCI_format0_0 may include bits for sensing, and DCI_format0_0 may include UL / SUL indication.

[0097] DCI_format1_1 may include a fixed 3-bit transmission configuration indication that enables a higher layer parameter tci-PresentInDCI.

[0098] In some embodiments, the method for communication and perception integration according to an embodiment of the present disclosure further includes processing the collected multi-source communication and perception data (e.g., data synchronization, data filtering, data verification, etc.), encapsulating the processed multi-source communication and perception data, and transmitting the encapsulated communication and perception data via a data link layer. The AF can generate a migration model from the AI / ML processing entity using the communication and perception data transmitted via the data link layer.

[0099] [Exemplary Implementation of the Present Disclosure]

[0100] According to the embodiments of the present disclosure, various implementations of the concepts of the present disclosure can be conceived, including but not limited to:

[0101] 1. A method for communication perception integration, comprising:

[0102] The application function (AF) generates a migration model from the artificial intelligence / machine learning (AI / ML) processing entity;

[0103] Sending, by the AF, a correction requirement for the generated migration model to a Network Data Analytics Function (NWDAF), the correction requirement including information related to the migration model generated from the AI / ML processing entity;

[0104] receiving, by the AF from the NWDAF, an analysis result based at least on the transmitted information related to the migration model generated from the AI / ML processing entity; and

[0105] The generated migration model is modified by the AF based on the received analysis results.

[0106] 2. The method for communication perception integration as described in item 1, further comprising:

[0107] AF sends an analysis request for model migration to NWDAF;

[0108] receiving, by the AF from the NWDAF, a subscription request for information from the AI / ML processing entity; and

[0109] The end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers is sent by AF to NWDAF.

[0110] 3. A method for communication-aware integration as described in item 2, wherein end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers is sent together with correction requirements for the generated migration model.

[0111] 4. A method for communication-aware integration as described in item 3, wherein the analysis result is based at least on the information sent related to the migration model generated from the AI / ML processing entity and the end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers.

[0112] 5. The method for communication perception integration as described in item 4, further comprising:

[0113] Data collected by NWDAF from other Network Functions (NF); and

[0114] Analytical results are also generated based on the collected data.

[0115] 6. The method for communication perception integration as described in item 5, further comprising:

[0116] The AF generates AI-assisted information and makes AI / ML decisions based on the received analysis results and information received from the User Equipment (UE);

[0117] The AI / ML decisions made by AF are informed to UE for model migration.

[0118] 7. The method for communication perception integration as described in item 1, further comprising:

[0119] A pair of DCIs including DCI_format0_0 and DCI_format1_1 is provided at the physical layer for resource scheduling for both communication and sensing functions.

[0120] 8. A method for communication perception integration as described in item 6, wherein the frequency domain resource allocation field of DCI_format0_0 includes bits for perception, and DCI_format0_0 includes an uplink / supplementary uplink (UL / SUL) indication.

[0121] 9. A method for communication awareness integration as described in item 6, wherein DCI_format1_1 includes a transmission configuration indication of a fixed number of bits, which enables a high-level parameter tci-PresentInDCI.

[0122] 10. The method for communication perception integration as described in item 1, further comprising:

[0123] Process the collected multi-source communication and perception data;

[0124] Packaging processed multi-source communication and sensory data; and

[0125] Encapsulated communication and sensing data are transmitted via the data link layer.

[0126] 11. The method for communication perception integration as described in item 10, further comprising:

[0127] The migration model is generated by the AF from the AI / ML processing entity using the communication and perception data transmitted via the data link layer.

[0128] 12. A non-volatile computer-readable storage medium storing computer-readable instructions, wherein the computer-readable instructions, when executed by a processor, perform the method as described in any one of items 1-11.

[0129] Application examples of the present disclosure

[0130] The techniques described in this disclosure can be applied to a variety of products.

[0131] For example, the electronic device according to the embodiments of the present disclosure may be implemented as various base stations or installed in a base station, or may be implemented as various user equipments or installed in various user equipments.

[0132] The communication method according to the embodiments of the present disclosure can be implemented by various base stations or user equipment; the methods and operations according to the embodiments of the present disclosure can be embodied as computer-executable instructions, stored in a non-temporary computer-readable storage medium, and can be executed by various base stations or user equipment to implement one or more functions described above.

[0133] The technology according to the embodiments of the present disclosure can be made into various computer program products, which can be used in various base stations or user equipments to implement one or more functions described above.

[0134] The base station mentioned in the present disclosure may be implemented as any type of base station, preferably, such as macro gNB and ng-eNB defined in the 5G NR standard of 3GPP. The gNB may be a gNB that covers a cell smaller than a macro cell, such as a pico gNB, a micro gNB, and a home (femto) gNB. Alternatively, the base station may be implemented as any other type of base station, such as a NodeB, an eNodeB, and a base transceiver station (BTS). The base station may also include: a main body configured to control wireless communication and one or more remote radio heads (RRHs) arranged at a place different from the main body, a wireless relay station, a drone tower, a control node in an automated factory, and the like.

[0135] The user equipment may be implemented as a mobile terminal (such as a smart phone, a tablet personal computer (PC), a notebook PC, a portable game terminal, a portable / dongle-type mobile router, and a digital camera) or a vehicle-mounted terminal (such as a car navigation device). The user equipment may also be implemented as a terminal that performs machine-to-machine (M2M) communication (also known as a machine type communication (MTC) terminal), a drone, a sensor and an actuator in an automated factory, etc. In addition, the user equipment may be a wireless communication module (such as an integrated circuit module including a single chip) installed on each of the above terminals.

[0136] Examples of base stations and user equipment to which the technology of the present disclosure can be applied are briefly introduced below.

[0137] It should be understood that the term "base station" used in this disclosure has the full breadth of its usual meaning and includes at least a wireless communication station used as part of a wireless communication system or radio system to facilitate communication. Examples of base stations may be, for example, but not limited to, the following: one or both of a base transceiver station (BTS) and a base station controller (BSC) in a GSM communication system; one or both of a radio network controller (RNC) and a NodeB in a 3G communication system; eNBs in 4G LTE and LTE-A systems; gNBs and ng-eNBs in a 5G communication system. In D2D, M2M, and V2V communication scenarios, a logical entity that has a control function for communication may also be referred to as a base station. In a cognitive radio communication scenario, a logical entity that plays a role in spectrum coordination may also be referred to as a base station. In an automated factory, a logical entity that provides a network control function may be referred to as a base station.

[0138] First application example of base station

[0139] Figure 5 is a block diagram showing a first example of a schematic configuration of a base station to which the technology of the present disclosure can be applied. Figure 5 In the embodiment, the base station can be implemented as a gNB 1400. The gNB 1400 includes a plurality of antennas 1410 and a base station device 1420. The base station device 1420 and each antenna 1410 can be connected to each other via an RF cable.

[0140] Antenna 1410 includes multiple antenna elements, such as multiple antenna arrays for massive MIMO. Antenna 1410 can be arranged into an antenna array matrix, for example, and used for base station device 1420 to send and receive wireless signals. For example, multiple antennas 1410 can be compatible with multiple frequency bands used by gNB 1400.

[0141] The base station device 1420 includes a controller 1421 , a memory 1422 , a network interface 1423 , and a wireless communication interface 1425 .

[0142] The controller 1421 may be, for example, a CPU or a DSP, and operates various functions of the higher layers of the base station device 1420. For example, the controller 1421 generates a data packet based on the data in the signal processed by the wireless communication interface 1425, and transmits the generated packet via the network interface 1423. The controller 1421 may bundle data from a plurality of baseband processors to generate a bundled packet, and transmit the generated bundled packet. The controller 1421 may have a logical function to perform the following control: the control may be such as radio resource control, radio bearer control, mobility management, admission control, and scheduling. The control may be performed in conjunction with a nearby gNB or core network node. The memory 1422 includes a RAM and a ROM, and stores programs executed by the controller 1421 and various types of control data (such as a terminal list, transmission power data, and scheduling data).

[0143] The network interface 1423 is a communication interface for connecting the base station device 1420 to the core network 1424 (e.g., a 5G core network). The controller 1421 can communicate with the core network node or another gNB via the network interface 1423. In this case, the gNB 1400 and the core network node or other gNBs can be connected to each other through logical interfaces such as NG interfaces and Xn interfaces. The network interface 1423 can also be a wired communication interface or a wireless communication interface for a wireless backhaul line. If the network interface 1423 is a wireless communication interface, the network interface 1423 can use a higher frequency band for wireless communication compared to the frequency band used by the wireless communication interface 1425.

[0144] The wireless communication interface 1425 supports any cellular communication scheme (such as 5G NR) and provides wireless connection to a terminal located in the cell of the gNB 1400 via the antenna 1410. The wireless communication interface 1425 may generally include, for example, a baseband (BB) processor 1426 and an RF circuit 1427. The BB processor 1426 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing of each layer (e.g., physical layer, MAC layer, RLC layer, PDCP layer, SDAP layer). Instead of the controller 1421, the BB processor 1426 may have part or all of the above-mentioned logical functions. The BB processor 1426 may be a memory for storing a communication control program, or a module including a processor configured to execute a program and related circuits. Updating the program may change the function of the BB processor 1426. The module may be a card or a blade inserted into a slot of the base station device 1420. Alternatively, the module may also be a chip mounted on a card or a blade. Meanwhile, the RF circuit 1427 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via the antenna 1410. Figure 5 An example is shown in which one RF circuit 1427 is connected to one antenna 1410 , but the present disclosure is not limited to this illustration, and one RF circuit 1427 may be connected to a plurality of antennas 1410 at the same time.

[0145] like Figure 5 As shown, the wireless communication interface 1425 may include multiple BB processors 1426. For example, the multiple BB processors 1426 may be compatible with multiple frequency bands used by the gNB 1400. Figure 5 As shown, the wireless communication interface 1425 may include multiple RF circuits 1427. For example, the multiple RF circuits 1427 may be compatible with multiple antenna elements. Figure 5 An example is shown in which the wireless communication interface 1425 includes a plurality of BB processors 1426 and a plurality of RF circuits 1427 , but the wireless communication interface 1425 may also include a single BB processor 1426 or a single RF circuit 1427 .

[0146] exist Figure 5In the gNB 1400 shown in FIG. 1 , one or more units (e.g., transmitting unit 1003, receiving unit 2002, receiving unit 3003, etc.) included in the processing circuit 1001, 2001, 3001, or 4001 may be implemented in the wireless communication interface 1425. Alternatively, at least a portion of these components may be implemented in the controller 1421. For example, the gNB 1400 includes a portion (e.g., BB processor 1426) or the entirety of the wireless communication interface 1425, and / or includes a module of the controller 1421, and one or more components may be implemented in the module. In this case, the module may store a program for allowing the processor to function as one or more components (in other words, a program for allowing the processor to perform the operation of one or more components), and the program may be executed. As another example, a program for allowing the processor to function as one or more components may be installed in the gNB 1400, and the wireless communication interface 1425 (e.g., BB processor 1426) and / or the controller 1421 may execute the program. As described above, as a device including one or more components, the gNB 1400, the base station device 1420, or the module may be provided, and a program for allowing the processor to function as one or more components may be provided. In addition, a readable medium in which the program is recorded may be provided.

[0147] Second application example of base station

[0148] Figure 6 is a block diagram showing a second example of a schematic configuration of a base station to which the technology of the present disclosure can be applied. Figure 6 In FIG. 1 , the base station is shown as gNB 1530. gNB 1530 includes multiple antennas 1540, base station device 1550, and RRH 1560. RRH 1560 and each antenna 1540 may be connected to each other via an RF cable. Base station device 1550 and RRH 1560 may be connected to each other via a high-speed line such as an optical fiber cable.

[0149] Antenna 1540 includes multiple antenna elements, such as multiple antenna arrays for massive MIMO. Antenna 1540 can be arranged in an antenna array matrix, for example, and is used for base station device 1550 to send and receive wireless signals. For example, multiple antennas 1540 can be compatible with multiple frequency bands used by gNB 1530.

[0150] The base station device 1550 includes a controller 1551, a memory 1552, a network interface 1553, a wireless communication interface 1555, and a connection interface 1557. The controller 1551, the memory 1552, and the network interface 1553 are similar to the reference Figure 6 The controller 1421, memory 1422, and network interface 1423 described are the same.

[0151] The wireless communication interface 1555 supports any cellular communication scheme (such as 5G NR) and provides wireless communication to a terminal located in a sector corresponding to the RRH 1560 via the RRH 1560 and the antenna 1540. The wireless communication interface 1555 may generally include, for example, a BB processor 1556. In addition to the BB processor 1556 being connected to the RF circuit 1564 of the RRH 1560 via the connection interface 1557, the BB processor 1556 is connected to the reference RF circuit 1564 of the RRH 1560. Figure 7 The same as the BB processor 1426 described above. Figure 6 As shown, the wireless communication interface 1555 may include multiple BB processors 1556. For example, the multiple BB processors 1556 may be compatible with multiple frequency bands used by the gNB 1530. Figure 6 An example is shown in which the wireless communication interface 1555 includes a plurality of BB processors 1556 , but the wireless communication interface 1555 may also include a single BB processor 1556 .

[0152] The connection interface 1557 is an interface for connecting the base station device 1550 (wireless communication interface 1555) to the RRH 1560. The connection interface 1557 may also be a communication module for connecting the base station device 1550 (wireless communication interface 1555) to the RRH 1560 for communication in the above-mentioned high-speed line.

[0153] The RRH 1560 includes a connection interface 1561 and a wireless communication interface 1563 .

[0154] The connection interface 1561 is an interface for connecting the RRH 1560 (wireless communication interface 1563) to the base station device 1550. The connection interface 1561 may also be a communication module for communication in the above-mentioned high-speed line.

[0155] The wireless communication interface 1563 transmits and receives wireless signals via the antenna 1540. The wireless communication interface 1563 may generally include, for example, an RF circuit 1564. The RF circuit 1564 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives wireless signals via the antenna 1540. Figure 6 An example is shown in which one RF circuit 1564 is connected to one antenna 1540 , but the present disclosure is not limited to this illustration, and one RF circuit 1564 may be connected to a plurality of antennas 1540 at the same time.

[0156] like Figure 6 As shown, the wireless communication interface 1563 may include multiple RF circuits 1564. For example, the multiple RF circuits 1564 may support multiple antenna elements. Figure 6An example is shown in which the wireless communication interface 1563 includes a plurality of RF circuits 1564 , but the wireless communication interface 1563 may also include a single RF circuit 1564 .

[0157] exist Figure 6 In the gNB 1500 shown in FIG. 1 , one or more units (e.g., transmitting unit 1003, receiving unit 2002, receiving unit 3003, etc.) included in the processing circuit 1001, 2001, 3001, or 4001 may be implemented in the wireless communication interface 1525. Alternatively, at least a portion of these components may be implemented in the controller 1521. For example, the gNB 1500 includes a portion (e.g., BB processor 1526) or the entirety of the wireless communication interface 1525, and / or includes a module of the controller 1521, and one or more components may be implemented in the module. In this case, the module may store a program for allowing the processor to function as one or more components (in other words, a program for allowing the processor to perform the operation of one or more components), and the program may be executed. As another example, a program for allowing the processor to function as one or more components may be installed in the gNB 1500, and the wireless communication interface 1525 (e.g., BB processor 1526) and / or the controller 1521 may execute the program. As described above, as a device including one or more components, the gNB 1500, the base station device 1520, or a module may be provided, and a program for allowing a processor to function as one or more components may be provided. In addition, a readable medium in which the program is recorded may be provided.

[0158] First application example of user equipment

[0159] Figure 7 16 is a block diagram showing an example of a schematic configuration of a smartphone 1600 to which the technology of the present disclosure can be applied.

[0160] The smart phone 1600 includes a processor 1601, a memory 1602, a storage device 1603, an external connection interface 1604, a camera 1606, a sensor 1607, a microphone 1608, an input device 1609, a display device 1610, a speaker 1611, a wireless communication interface 1612, one or more antenna switches 1615, one or more antennas 1616, a bus 1617, a battery 1618 and an auxiliary controller 1619.

[0161] The processor 1601 may be, for example, a CPU or a system on a chip (SoC), and controls the functions of the application layer and other layers of the smartphone 1600. The processor 1601 may include or function as any of the processing circuits 1001, 2001, 3001, 4001 described with reference to the drawings. The memory 1602 includes a RAM and a ROM, and stores data and a program executed by the processor 1601. The storage device 1603 may include a storage medium such as a semiconductor memory and a hard disk. The external connection interface 1604 is an interface for connecting an external device (such as a memory card and a universal serial bus (USB) device) to the smartphone 1600.

[0162] The camera 1606 includes an image sensor such as a charge coupled device (CCD) and a complementary metal oxide semiconductor (CMOS), and generates a captured image. The sensor 1607 may include a group of sensors such as a measurement sensor, a gyro sensor, a geomagnetic sensor, and an acceleration sensor. The microphone 1608 converts the sound input to the smart phone 1600 into an audio signal. The input device 1609 includes, for example, a touch sensor, a keypad, a keyboard, a button, or a switch configured to detect a touch on the screen of the display device 1610, and receives an operation or information input from a user. The display device 1610 includes a screen such as a liquid crystal display (LCD) and an organic light emitting diode (OLED) display, and displays an output image of the smart phone 1600. The speaker 1611 converts an audio signal output from the smart phone 1600 into sound.

[0163] The wireless communication interface 1612 supports any cellular communication scheme (such as 4G LTE or 5G NR, etc.) and performs wireless communication. The wireless communication interface 1612 may generally include, for example, a BB processor 1613 and an RF circuit 1614. The BB processor 1613 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing for wireless communication. Meanwhile, the RF circuit 1614 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via an antenna 1616. The wireless communication interface 1612 may be a chip module on which the BB processor 1613 and the RF circuit 1614 are integrated. Figure 7 As shown, the wireless communication interface 1612 may include multiple BB processors 1613 and multiple RF circuits 1614. Figure 7 An example is shown in which the wireless communication interface 1612 includes a plurality of BB processors 1613 and a plurality of RF circuits 1614 , but the wireless communication interface 1612 may also include a single BB processor 1613 or a single RF circuit 1614 .

[0164] In addition, in addition to the cellular communication scheme, the wireless communication interface 1612 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 1612 can include a BB processor 1613 and an RF circuit 1614 for each wireless communication scheme.

[0165] Each of the antenna switches 1615 switches a connection destination of the antenna 1616 between a plurality of circuits (eg, circuits for different wireless communication schemes) included in the wireless communication interface 1612 .

[0166] Antenna 1616 includes multiple antenna elements, such as multiple antenna arrays for massive MIMO. Antenna 1616 can be arranged in an antenna array matrix, for example, and used for wireless communication interface 1612 to transmit and receive wireless signals. Smartphone 1600 may include one or more antenna panels (not shown).

[0167] In addition, the smartphone 1600 may include an antenna 1616 for each wireless communication scheme. In this case, the antenna switch 1615 may be omitted from the configuration of the smartphone 1600.

[0168] The bus 1617 connects the processor 1601, the memory 1602, the storage device 1603, the external connection interface 1604, the camera 1606, the sensor 1607, the microphone 1608, the input device 1609, the display device 1610, the speaker 1611, the wireless communication interface 1612, and the auxiliary controller 1619 to each other. Figure 7 The various blocks of the smartphone 1600 shown are supplied with power, the feed lines being partially shown as dashed lines in the figure. The auxiliary controller 1619 operates the minimum necessary functions of the smartphone 1600, for example in a sleep mode.

[0169] exist Figure 7In the smart phone 1600 shown in FIG. 1 , one or more units (e.g., sending unit 1003, receiving unit 2002, receiving unit 3003, etc.) included in the processing circuit 1001, 2001, 3001, or 4001 may be implemented in the wireless communication interface 1612. Alternatively, at least a portion of these components may be implemented in the processor 1601 or the auxiliary controller 1619. As an example, the smart phone 1600 includes a portion (e.g., BB processor 1613) or the entirety of the wireless communication interface 1612, and / or a module including the processor 1601 and / or the auxiliary controller 1619, and one or more components may be implemented in the module. In this case, the module may store a program that allows the processing to function as one or more components (in other words, a program for allowing the processor to perform the operation of one or more components), and the program may be executed. As another example, a program for allowing the processor to function as one or more components may be installed in the smart phone 1600, and the wireless communication interface 1612 (e.g., BB processor 1613), the processor 1601, and / or the auxiliary controller 1619 may execute the program. As described above, as a device including one or more components, a smart phone 1600 or a module may be provided, and a program for allowing the processor to function as one or more components may be provided. In addition, a readable medium in which the program is recorded may be provided.

[0170] Second application example of user equipment

[0171] Figure 8 17 is a block diagram showing an example of a schematic configuration of a car navigation device 1720 to which the technology of the present disclosure can be applied. The car navigation device 1720 includes a processor 1721, a memory 1722, a global positioning system (GPS) module 1724, a sensor 1725, a data interface 1726, a content player 1727, a storage medium interface 1728, an input device 1729, a display device 1730, a speaker 1731, a wireless communication interface 1733, one or more antenna switches 1736, one or more antennas 1737, and a battery 1738.

[0172] The processor 1721 may be, for example, a CPU or a SoC, and controls a navigation function and other functions of the car navigation device 1720. The memory 1722 includes a RAM and a ROM, and stores data and a program executed by the processor 1721.

[0173] The GPS module 1724 measures the position (such as latitude, longitude and altitude) of the car navigation device 1720 using GPS signals received from GPS satellites. The sensor 1725 may include a group of sensors such as a gyro sensor, a geomagnetic sensor and an air pressure sensor. The data interface 1726 is connected to, for example, the vehicle network 1741 via an unshown terminal and acquires data (such as vehicle speed data) generated by the vehicle.

[0174] The content player 1727 reproduces content stored in a storage medium such as a CD and a DVD, which is inserted into the storage medium interface 1728. The input device 1729 includes, for example, a touch sensor, a button, or a switch configured to detect a touch on the screen of the display device 1730, and receives an operation or information input from a user. The display device 1730 includes a screen such as an LCD or an OLED display, and displays an image of a navigation function or reproduced content. The speaker 1731 outputs a sound of a navigation function or reproduced content.

[0175] The wireless communication interface 1733 supports any cellular communication scheme (such as 4G LTE or 5G NR) and performs wireless communication. The wireless communication interface 1733 may generally include, for example, a BB processor 1734 and an RF circuit 1735. The BB processor 1734 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing for wireless communication. Meanwhile, the RF circuit 1735 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via an antenna 1737. The wireless communication interface 1733 may also be a chip module on which the BB processor 1734 and the RF circuit 1735 are integrated. Figure 8 As shown, the wireless communication interface 1733 may include multiple BB processors 1734 and multiple RF circuits 1735. Figure 8 An example is shown in which the wireless communication interface 1733 includes a plurality of BB processors 1734 and a plurality of RF circuits 1735 , but the wireless communication interface 1733 may also include a single BB processor 1734 or a single RF circuit 1735 .

[0176] In addition, in addition to the cellular communication scheme, the wireless communication interface 1733 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 1733 can include a BB processor 1734 and an RF circuit 1735.

[0177] Each of the antenna switches 1736 switches a connection destination of the antenna 1737 between a plurality of circuits included in the wireless communication interface 1733 , such as circuits for different wireless communication schemes.

[0178] The antenna 1737 includes multiple antenna elements, such as multiple antenna arrays for massive MIMO. The antenna 1737 can be arranged in an antenna array matrix, for example, and is used for the wireless communication interface 1733 to transmit and receive wireless signals.

[0179] In addition, the car navigation device 1720 may include an antenna 1737 for each wireless communication scheme. In this case, the antenna switch 1736 may be omitted from the configuration of the car navigation device 1720.

[0180] Battery 1738 is fed via a feed line to Figure 8 The respective blocks of the illustrated car navigation device 1720 are supplied with electric power, and feed lines are partially illustrated as dotted lines in the figure. The battery 1738 accumulates electric power supplied from the vehicle.

[0181] exist Figure 8 In the car navigation device 1720 shown in FIG. 1 , one or more units (e.g., sending unit 1003, receiving unit 2002, receiving unit 3003, etc.) included in the processing circuit 1001, 2001, 3001, or 4001 may be implemented in the wireless communication interface 1733. Alternatively, at least a portion of these components may be implemented in the processor 1721. As an example, the car navigation device 1720 includes a portion (e.g., BB processor 1734) or the entirety of the wireless communication interface 1733, and / or a module including the processor 1721, and one or more components may be implemented in the module. In this case, the module may store a program that allows the processor to function as one or more components (in other words, a program for allowing the processor to perform the operation of one or more components), and the program may be executed. As another example, a program for allowing the processor to function as one or more components may be installed in the car navigation device 1720, and the wireless communication interface 1733 (e.g., BB processor 1734) and / or the processor 1721 may execute the program. As described above, as a device including one or more components, the car navigation device 1720 or a module may be provided, and a program for allowing a processor to function as one or more components may be provided. In addition, a readable medium having the program recorded therein may be provided.

[0182] The technology of the present disclosure may also be implemented as an in-vehicle system (or vehicle) 1740 including a car navigation device 1720, an in-vehicle network 1741, and one or more blocks in a vehicle module 1742. The vehicle module 1742 generates vehicle data (such as vehicle speed, engine speed, and fault information), and outputs the generated data to the in-vehicle network 1741.

[0183] The exemplary embodiments of the present disclosure are described above with reference to the accompanying drawings, but the present disclosure is certainly not limited to the above examples. Those skilled in the art may obtain various changes and modifications within the scope of the appended claims, and it should be understood that these changes and modifications will naturally fall within the technical scope of the present disclosure.

[0184] For example, a plurality of functions included in one unit in the above embodiments may be implemented by separate devices. Alternatively, a plurality of functions implemented by a plurality of units in the above embodiments may be implemented by separate devices, respectively. In addition, one of the above functions may be implemented by a plurality of units. Needless to say, such a configuration is included in the technical scope of the present disclosure.

[0185] In this specification, the steps described in the flowchart include not only the processing performed in time series in the order described, but also the processing performed in parallel or individually rather than necessarily in time series. In addition, even in the steps processed in time series, it goes without saying that the order can be appropriately changed.

[0186] Although the present disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions and transformations can be made without departing from the spirit and scope of the present disclosure as defined by the appended claims. Moreover, the terms "including", "comprising" or any other variants of the embodiments of the present disclosure are intended to cover non-exclusive inclusions, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the statement "including one..." do not exclude the presence of other identical elements in the process, method, article or equipment including the elements.

Claims

1. A method for communication perception integration, comprising: The application function (AF) generates a migration model from the artificial intelligence / machine learning (AI / ML) processing entity; Sending, by the AF, a correction requirement for the generated migration model to a Network Data Analytics Function (NWDAF), the correction requirement including information related to the migration model generated from the AI / ML processing entity; receiving, by the AF from the NWDAF, analysis results based at least on the sent information related to the migration model generated from the AI / ML processing entity; as well as The generated migration model is modified by the AF based on the received analysis results.

2. The method for communication awareness integration according to claim 1, further comprising: AF sends an analysis request for model migration to NWDAF; Receiving, by the AF, a subscription request for information from the AI / ML processing entity from the NWDAF; as well as The end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers is sent by AF to NWDAF.

3. The method for communication perception integration as claimed in claim 2, wherein: End-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers is sent along with the correction requirements for the generated migration model.

4. The method for communication perception integration as claimed in claim 3, wherein: The analysis result is based at least on the transmitted information related to the migration model generated from the AI / ML processing entities and the end-to-end network performance data between each pair of AI / ML processing entities in two adjacent layers.

5. The method for communication awareness integration according to claim 4, further comprising: Data is collected by NWDAF from other network functions (NF); and Analytical results are also generated based on the collected data.

6. The method for communication awareness integration according to claim 5, further comprising: The AF generates AI-assisted information and makes AI / ML decisions based on the received analysis results and information received from the User Equipment (UE); The AI / ML decisions made by AF are informed to UE for model migration.

7. The method for communication awareness integration according to claim 1, further comprising: A pair of DCIs including DCI_format0_0 and DCI_format1_1 is provided at the physical layer for resource scheduling for both communication and sensing functions.

8. The method for communication awareness integration as claimed in claim 6, wherein: The frequency domain resource allocation field of DCI_format0_0 includes bits for sensing, and DCI_format0_0 includes an uplink / supplementary uplink (UL / SUL) indication.

9. The method for communication awareness integration as claimed in claim 6, wherein: DCI_format1_1 includes a fixed number of bits of transmission configuration indication, which enables the higher layer parameter tci-PresentInDCI.

10. The method for communication awareness integration according to claim 1, further comprising: Process the collected multi-source communication and perception data; Encapsulate processed multi-source communication and perception data; as well as Encapsulated communication and sensing data are transmitted via the data link layer.

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