Information processing method, network device, terminal, communication system and storage medium

Abstract

The embodiment of the invention provides an information processing method, network equipment, a terminal, communication equipment and a storage medium. The information processing method comprises: a terminal sends a first request to a first network element, the first request comprising first information, and the first information comprising a first identifier and / or auxiliary information indicating a first AI model; the first request is used for requesting to provide perception service; according to the embodiment of the invention, the first request can be sent to the first network element in the network through the terminal, so that the network determines to provide the perception service; therefore, on one hand, compared with the condition that the perception server is determined to be provided through the terminal and the like, the perception service can be processed by fully utilizing high-performance network resources, so that the problem of poor user experience caused by insufficient terminal capability when the perception service is processed by the terminal is solved; and on the other hand, compared with the method for providing the perception service through the application server of the terminal, the processing time delay and / or the network transmission time delay caused by the processing of the application server can be reduced.

Description

Information processing method, network device, terminal, communication system and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to an information processing method, network equipment, terminal, communication system, and storage medium. Background Art

[0002] With the development of artificial intelligence (AI) technology, the intelligence of many industries has been greatly promoted; among them, sensing technology has become an important technical foundation, bringing great convenience to people's work and life.

[0003] Summary of the Invention

[0004] The embodiments of the present disclosure need to solve the problem of insufficient terminal capabilities when the perception service is processed by the terminal or high latency overhead when the perception service is processed by the application server.

[0005] According to a first aspect of an embodiment of the present disclosure, an information processing method is proposed, including: a terminal sends a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0006] According to the second aspect of an embodiment of the present disclosure, an information processing method is proposed, including: a first network element receives a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0007] According to the third aspect of an embodiment of the present disclosure, an information processing method is proposed, including: a second network element receives a first request sent by a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0008] According to the fourth aspect of an embodiment of the present disclosure, an information processing method is proposed, including: a terminal sends a first request to a network device, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0009] According to the fifth aspect of an embodiment of the present disclosure, a terminal is proposed, comprising: a first transceiver module, configured to send a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0010] According to the sixth aspect of an embodiment of the present disclosure, a first network element is proposed, including: a second transceiver module, configured to receive a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request the provision of a perception service.

[0011] According to the seventh aspect of an embodiment of the present disclosure, a second network element is proposed, including: a third transceiver module, configured to receive a first request sent by a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0012] According to an eighth aspect of an embodiment of the present disclosure, a first network element is proposed, comprising: one or more processors; wherein the above-mentioned first network element is used to execute an optional implementation method of the second aspect.

[0013] According to a ninth aspect of an embodiment of the present disclosure, a second network element is proposed, comprising: one or more processors; wherein the second network element is used to execute an optional implementation of the second aspect.

[0014] According to the tenth aspect of an embodiment of the present disclosure, a communication system is proposed, comprising: a terminal, a first network element and a second network element; wherein the terminal is configured to execute the method described in the optional implementation manner of the first aspect, the first network element is configured to execute the method described in the optional implementation manner of the second aspect, and the second network element is configured to execute the method described in the optional implementation manner of the third aspect.

[0015] According to the eleventh aspect of an embodiment of the present disclosure, a storage medium is proposed, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the first aspect, the second aspect, the third aspect, or the optional implementation of the first aspect, the second aspect and the third aspect.

[0016] The embodiments of the present disclosure can fully utilize high-performance network resources to process perception services, thereby solving the problem of insufficient terminal capabilities when the perception services are processed by the terminal and reducing the delay when the perception services are processed by the application server. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0018] FIG1A is a schematic structural diagram of an information processing system according to an embodiment of the present disclosure.

[0019] FIG1B is a flow chart illustrating a method for locally processing perception data by a terminal according to an embodiment of the present disclosure.

[0020] FIG1C is a flow chart showing a method for processing perception data by a perception server according to an embodiment of the present disclosure.

[0021] FIG2 is an interactive schematic diagram illustrating an information processing method according to an embodiment of the present disclosure.

[0022] FIG3A is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0023] FIG3B is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0024] FIG4A is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0025] FIG4B is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0026] FIG4C is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0027] FIG5A is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0028] FIG5B is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0029] FIG5C is a flow chart illustrating an information processing method according to an embodiment of the present disclosure.

[0030] FIG6 is a flow chart showing an information processing method according to an embodiment of the present disclosure.

[0031] FIG7 is a flow chart showing an information processing method according to an embodiment of the present disclosure.

[0032] FIG8A is a schematic structural diagram of a terminal according to an embodiment of the present disclosure.

[0033] FIG8B is a schematic structural diagram of a first network element according to an embodiment of the present disclosure.

[0034] FIG8C is a schematic structural diagram of a first network element according to an embodiment of the present disclosure.

[0035] FIG9A is a schematic structural diagram of a communication device provided according to an embodiment of the present disclosure.

[0036] FIG9B is a schematic structural diagram of a chip provided according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] The embodiments of the present disclosure provide an information processing method, a network device, a terminal, a communication system, and a storage medium.

[0038] In a first aspect, an embodiment of the present disclosure proposes an information processing method, including: a terminal sends a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0039] In the above embodiment, a first request can be sent to a first network element in the network through the terminal so that the network determines to provide the perception service; in this way, on the one hand, compared with determining the provision of the perception server through the terminal, high-performance network resources can be fully utilized to process the perception service to overcome the problem of poor user experience caused by insufficient terminal capabilities when the perception service is processed by the terminal; on the other hand, compared with providing the perception service through the application server of the terminal, the processing delay and / or network transmission delay caused by the application server processing can be reduced.

[0040] In combination with some embodiments of the first aspect, in some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0041] In the above embodiment, the provided perception service may be a service for processing perception data and / or an AI model for negotiating processing perception data, so that network resources can be fully utilized to determine the service and / or AI model for processing perception data.

[0042] In combination with some embodiments of the first aspect, in some embodiments, the auxiliary information includes at least one of the following: a model of the sensing device; a device identification of the sensing device; manufacturer information of the sensing device; type information indicating a type of sensing data; and local configuration information.

[0043] In the above embodiment, the terminal sends a first request including auxiliary information to the first network element, which facilitates the first network element and other network devices to determine whether there is a suitable AI model to process the perception data.

[0044] In combination with some embodiments of the first aspect, in some embodiments, the method also includes: the terminal receives a first response sent by the first network element, wherein the first response includes one of the following: acceptance indication information, used to indicate acceptance of the request to provide perception service; and rejection indication information, used to indicate rejection of the request to provide perception service.

[0045] In the above embodiment, the terminal can accurately know whether the first network element and other network devices in the network accept the request for the perception service by receiving the first response sent by the first network element.

[0046] In combination with some embodiments of the first aspect, in some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0047] In the above embodiment, if the first response includes an acceptance indication, the first response may also include a second identifier of a second AI model for processing the sensory data; this allows accurate identification of the AI ​​model used to process the sensory data. Furthermore, if the second AI model is the same as the first AI model, it can be determined that the AI ​​model requested by the terminal to process the sensory data is an AI model that can actually process the sensory data. Alternatively, if the second AI model is different from the first AI model, if the network device cannot find the first AI model requested by the terminal to process the sensory data, another suitable second AI model can be used to process the sensory data.

[0048] In combination with some embodiments of the first aspect, in some embodiments, before sending the first request, it also includes: the terminal determines the first identifier based on the second information; wherein the second information includes at least one of the following: perception data, the model of the perception device, the device identifier of the perception device, the manufacturer information of the perception device, and type information indicating the type of perception data.

[0049] In the above embodiment, the terminal can determine the first identifier of the AI ​​model corresponding to the perception data, so that the terminal can request the network whether the first AI model corresponding to the first identifier is suitable for processing the perception data.

[0050] In combination with some embodiments of the first aspect, in some embodiments, the method includes: the terminal sends third information to the first network element, wherein the third information includes perception data; the terminal receives fourth information sent by the first network element, wherein the fourth information response includes a perception result determined based on the perception data.

[0051] In the above embodiment, after determining the second AI model suitable for processing the perception data, the perception data can be sent to the first network element so that the first network element processes the perception data based on the second AI model to successfully obtain the perception results of the perception data.

[0052] In combination with some embodiments of the first aspect, in some embodiments, the first network element includes at least one of the following: a sensing function (SF), a location management function (LMF), and a network data analysis function (NWDAF); and / or the second network element includes at least one of the following: an AI functional entity, an AI server, and a core network device.

[0053] In the above embodiment, it is clarified which network elements or devices the first network element and the second network element may be, so that the application scope of introducing the perception service into the network is more extensive.

[0054] In the second aspect, an embodiment of the present disclosure proposes an information processing method, including: a first network element receives a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0055] In combination with some embodiments of the second aspect, in some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0056] In combination with some embodiments of the second aspect, in some embodiments, the auxiliary information includes at least one of the following: the model of the sensing device; the device identification of the sensing device; the manufacturer information of the sensing device; type information indicating the type of sensing data; and local configuration information.

[0057] In combination with some embodiments of the second aspect, in some embodiments, the method also includes: the first network element receives a first response sent by the second network element, wherein the first response includes acceptance indication information or rejection indication information; the acceptance indication information is used to indicate acceptance of the request to provide perception service; the rejection indication information is used to indicate rejection of the request to provide perception service.

[0058] In combination with some embodiments of the second aspect, in some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0059] In combination with some embodiments of the second aspect, in some embodiments, the method also includes one of the following: the first network element determines a second AI model for processing the perception data based on the first identifier and / or auxiliary information; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; and based on the first identifier and / or auxiliary information, determines a second AI model that does not process the perception data.

[0060] In the above embodiment, the first network element can determine whether there is a second AI model for processing perception data based on the first identifier and / or auxiliary information; if so, it can introduce the perception service into the network for processing while further reducing latency.

[0061] In combination with some embodiments of the second aspect, in some embodiments, the method further includes: the first network element sends a first response to the terminal.

[0062] In combination with some embodiments of the second aspect, in some embodiments, the method also includes: the first network element receives third information sent by the terminal, wherein the third information includes perception data; the first network element processes the perception data based on a second AI model determined by the second identifier to obtain a perception result; the first network element sends fourth information to the terminal, wherein the fourth information includes the perception result.

[0063] In the above embodiments, the first network element can complete the processing of perception data based on the second AI model, thereby utilizing high-performance network resources to process perception services. This can overcome the shortcomings of insufficient terminal capabilities and reduce the latency of obtaining perception results. In conjunction with some embodiments of the second aspect, in some embodiments, the first network element includes at least one of the following: SF, LMF, and NWDAF; and / or the second network element includes at least one of the following: an AI functional entity, an AI server, and a core network device.

[0064] In a third aspect, an embodiment of the present disclosure proposes an information processing method, including: a second network element receives a first request sent by a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0065] In combination with some embodiments of the third aspect, in some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0066] In combination with some embodiments of the third aspect, in some embodiments, the auxiliary information includes at least one of the following: the model of the sensing device; the device identification of the sensing device; the manufacturer information of the sensing device; type information indicating the type of sensing data; and local configuration information.

[0067] In combination with some embodiments of the third aspect, in some embodiments, the method also includes one of the following: the second network element determines a second AI model for processing the perception data based on the first identifier and / or auxiliary information; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; and the second network element determines an AI model that does not process the perception data based on the first identifier and / or auxiliary information.

[0068] In the above embodiment, the first network element can determine whether there is a second AI model for processing perception data based on the first identifier and / or auxiliary information; if so, it can introduce the perception service into the network for processing.

[0069] In combination with some embodiments of the third aspect, in some embodiments, the method also includes: the second network element sends a first response to the first network element, wherein the first response includes one of the following: acceptance indication information, used to indicate acceptance of the request to provide perception service; and rejection indication information, used to indicate rejection of the request to provide perception service.

[0070] In combination with some embodiments of the third aspect, in some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0071] In combination with some embodiments of the third aspect, in some embodiments, the first network element includes at least one of the following: SF, LMF and NWDAF; and / or the second network element includes at least one of the following: AI functional entity, AI server and core network equipment.

[0072] In a fourth aspect, an embodiment of the present disclosure proposes an information processing method, including: a terminal sends a first request to a network device, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of a perception service.

[0073] In the fifth aspect, an embodiment of the present disclosure proposes a terminal, including: a first transceiver module, configured to send a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of perception services.

[0074] In the sixth aspect, an embodiment of the present disclosure proposes a first network element, including: a second transceiver module, configured to receive a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request the provision of a perception service.

[0075] In the seventh aspect, an embodiment of the present disclosure proposes a second network element, including: a third transceiver module, configured to receive a first request sent by a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request the provision of perception services.

[0076] In an eighth aspect, an embodiment of the present disclosure proposes a first network element, comprising: one or more processors; wherein the above-mentioned first network element is used to execute the optional implementation method of the second aspect.

[0077] In a ninth aspect, an embodiment of the present disclosure proposes a second network element, comprising: one or more processors; wherein the above-mentioned second network element is used to execute the optional implementation method of the second aspect.

[0078] In the tenth aspect, an embodiment of the present disclosure proposes a communication system, comprising: a terminal, a first network element and a second network element; wherein, the above-mentioned terminal is configured to execute the method described in the optional implementation manner of the first aspect, the above-mentioned first network element is configured to execute the method described in the optional implementation manner of the second aspect, and the above-mentioned second network element is configured to execute the method described in the optional implementation manner of the third aspect.

[0079] In the eleventh aspect, an embodiment of the present disclosure proposes a storage medium, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the first aspect, the second aspect, the third aspect, or the optional implementation of the first aspect, the second aspect and the third aspect.

[0080] In the tenth aspect, an embodiment of the present disclosure proposes a program product. When the program product is executed by a communication device, the communication device executes the method described in the first aspect, the second aspect, the third aspect, or the optional implementation of the first aspect, the second aspect and the third aspect.

[0081] In the eleventh aspect, an embodiment of the present disclosure proposes a computer program, which, when running on a computer, enables the computer to execute the information processing method described in the first aspect, the second aspect, the third aspect, or the optional implementation of the first aspect, the second aspect and the third aspect.

[0082] In the twelfth aspect, an embodiment of the present disclosure proposes a chip or a chip system; the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the above-mentioned first aspect, second aspect and third aspect.

[0083] It is understood that the aforementioned network devices, terminals, communication systems, storage media, program products, computer programs, chips, or chip systems are all used to execute the methods provided by the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

[0084] The present disclosure provides an information processing method, a network device, a terminal, a communication system, and a storage medium. In some embodiments, the terms information processing method and communication method are interchangeable, the terms information processing device and communication device are interchangeable, and the terms information processing system and communication system are interchangeable.

[0085] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0086] In each embodiment of the present disclosure, unless otherwise specified or provided for, the terms and / or descriptions between the embodiments are consistent and can be used interchangeably. The technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0087] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0088] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0089] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0090] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0091] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0092] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0093] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0094] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0095] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0096] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0097] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0098] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0099] In some embodiments, the terms "access network device (AN device)", "radio access network device (RAN device)", "base station (BS)", "radio base station" "fixed station", "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission / reception point (TRP)", "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "carrier", "component carrier", "bandwidth part (BWP)" and the like may be used interchangeably.

[0100] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc. can be used interchangeably.

[0101] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, it can also be called device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it can also be set as a structure in which the terminal has all or part of the functions of the access network device. In addition, language such as "uplink" and "downlink" can also be replaced by language corresponding to communication between terminals (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels, and uplinks, downlinks, etc. can be replaced by side links.

[0102] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, the core network device, or the network device may have a structure that has all or part of the functions of the terminal.

[0103] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0104] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0105] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0106] FIG1A is a schematic diagram showing the structure of an information processing system 100 according to an embodiment of the present disclosure. As shown in FIG1A , the information processing system 100 may include: a terminal 101 and a network device 102 .

[0107] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0108] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things (IOT) device or terminal, a car with communication function, a smart car, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0109] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a wireless fidelity (WiFi) system, but is not limited thereto.

[0110] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0111] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0112] In some embodiments, the core network device may be a single device including a first network element, a second network element, etc., or may be a plurality of devices or a group of devices, each including all or part of the first network element and the second network element. The network element may be virtual or physical. The core network may include, for example, at least one of an evolved packet core (EPC), a 5G core network (5GCN), and a next generation core (NGC).

[0113] In some embodiments, the first network element is, for example, SF, LMF or NWDAF, and its name is not limited thereto.

[0114] In some embodiments, the second network element is, for example, an AI function, an AI function entity, an AI server, or a core network device, and its name is not limited thereto.

[0115] It can be understood that the information processing system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of system architecture and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0116] The following embodiments of the present disclosure may be applied to the information processing system 100 shown in FIG1A , or a portion thereof, but are not limited thereto. The various entities shown in FIG1A are illustrative only. The information processing system may include all or a portion of the entities shown in FIG1A , or may include other entities other than those shown in FIG1A . The number and configuration of the entities may be arbitrary. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0117] The embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G New Radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Future Generation Radio Access (FX), Global System for Mobile Communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), systems utilizing other communication methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0118] In some embodiments, sensing technology can be applied in many industries, such as smart transportation, autonomous driving, smart furniture, etc. When a sensing device generates data, it can be processed by a terminal or sent to an application server for processing.

[0119] In some embodiments, as shown in FIG1B , a method for locally processing sensing data by a terminal is provided. The method is applied to a sensing system, which includes a sensing device, a terminal, a network device, and a sensing server. The method includes the following steps:

[0120] Step S1101: The terminal downloads an application for processing sensing data in advance;

[0121] Step S1102: The terminal initiates a sensing service and collects sensing data from the sensing device;

[0122] Step S1103: The terminal processes the perception data through the downloaded application.

[0123] In the above embodiment, if a terminal processes sensing data from multiple sensing devices, it must download multiple applications from the application server in advance, which consumes too many terminal resources. Furthermore, the processing capabilities of different terminals vary. For sensing services with large data volumes, such as those on mobile phones, the processing capacity is limited, which can seriously affect the user experience.

[0124] In some embodiments, as shown in FIG1C , a method for processing perception data by a perception server is provided; the method is applied to a perception system, the perception system including a perception device, a terminal, a network device, and a perception server; the method includes the following steps:

[0125] Step S1201: The terminal initiates a sensing service and collects sensing data from the sensing device;

[0126] Step S1202: The terminal establishes a protocol data unit (PDU) session with the perception server.

[0127] Step S1203: The perception server processes the received perception data;

[0128] Step S1204: The perception server completes the processing and sends the perception result to the UE.

[0129] In the above embodiment, the terminal needs to send the perception data to the perception service for processing, and then return the perception result to the UE, which will increase the delay overhead (for example, the delay overhead includes the perception server processing delay and the network transmission delay), and cannot meet the requirements of some perception services with high real-time requirements.

[0130] In some embodiments, the terminal may be a UE.

[0131] An information processing method is provided in the embodiments of the present disclosure, which can introduce the perception data processing function into the mobile network through AI technology, and make full use of high-performance network resources to process perception data. This can overcome the problem of insufficient terminal capabilities and reduce the processing delay of application servers (such as perception servers).

[0132] FIG2 is an interactive diagram of an information processing method according to an embodiment of the present disclosure. As shown in FIG2 , the present disclosure embodiment relates to an information processing method for an information processing system 100, and the method includes:

[0133] Step S2101: The terminal determines the first identifier based on the second information.

[0134] In some embodiments, the second information includes at least one of the following: sensing data, a model of the sensing device, a device identification of the sensing device, manufacturer information of the sensing device, and type information indicating a type of the sensing data.

[0135] Optionally, the perception data may be various data participating in the perception service, and / or the perception data may be data related to the perception service. Exemplarily, the perception data may be one of the following: location information of the terminal, speed of the terminal, channel parameters of the terminal, identification of the terminal, permanent identification of the terminal, various attribute information of the terminal and / or various environmental data. Exemplarily, the environmental data may be various indoor, outdoor and / or surrounding environmental information, such as air quality information and / or traffic route information. Exemplarily, the environmental data may be environmental information related to participating in the perception service, such as a person's breathing rate and / or breathing depth and / or current time information.

[0136] Optionally, the device identifier can be used to uniquely identify the sensing device. Exemplarily, the device identifier can be any number, index, or string.

[0137] Optionally, the type information may include one of the following: smart transportation type, smart driving type, smart furniture type, smart office type, etc. Optionally, the type information may also be determined based on the type of the sensing service or the data format of the sensing data, etc., and the type information is not limited here.

[0138] In some embodiments, the second information is used to determine an AI model.

[0139] In some embodiments, the second information is used to determine the first identifier corresponding to the AI ​​model.

[0140] In some embodiments, the second information is used to determine auxiliary information of the AI ​​model.

[0141] In some embodiments, the name of the second information is not limited, and it can be, for example, perception-related information, AI model information, etc.

[0142] In some embodiments, the first identifier is used to identify or indicate an AI model. Optionally, the first identifier can be used to indicate a recommended AI model.

[0143] In some embodiments, the first identifier may be any number, index, or character string.

[0144] In some embodiments, the name of the first identifier is not limited, and it can be, for example, an AI model identifier.

[0145] Step S2102: The terminal sends a first request to the first network element.

[0146] In some embodiments, the first network element receives a first request sent by the terminal.

[0147] In some embodiments, the first network element may be a SF, a LMF, or a NWDAF, etc. Optionally, the SF may be a network element, function, or entity related to perception.

[0148] In some embodiments, the first request includes first information.

[0149] In some embodiments, the first request is a perception-related request.

[0150] In some embodiments, the first request is for requesting provision of a perception service, and / or the first request is for requesting provision of an AI model. Optionally, the first request is for requesting provision of a service for processing perception data. Optionally, the first request is for requesting provision of a service for processing perception data. Optionally, the first request is for requesting provision of an AI model for processing perception data. Optionally, the first request is for requesting provision of an AI model for negotiating processing of perception data. Optionally, the first request is for requesting provision of an AI model for negotiating processing of perception data.

[0151] In some embodiments, the first request is for requesting provision of a perception service. Optionally, the request for provision of a perception service includes requesting a service for processing perception data and / or requesting negotiation of an AI model for processing perception data. Optionally, the service is a perception service.

[0152] Optionally, the first request is used to request a service for providing perception data.

[0153] Optionally, the first request is used to request negotiation of an AI model for processing the perception data. Exemplarily, the negotiation may be between the first network element and the second network element; or, the negotiation may be between the terminal and the first network element.

[0154] In some embodiments, the first request may be used to establish a PDU session. Exemplarily, when the terminal sends the first request to the first network element, the first request may establish a PDU session between the terminal and the first network element.

[0155] In some embodiments, the name of the first request is not limited, and it can be, for example, a perception service request, a PDU session establishment request, a perception business request, an AI model request, etc.

[0156] In some embodiments, the first information includes a first identifier and / or auxiliary information. Optionally, the first identifier and / or auxiliary information can be used to determine an AI model for processing the perception data.

[0157] Optionally, the auxiliary information includes at least one of the following: a model of the sensing device, a device identification of the sensing device, manufacturer information of the sensing device, type information indicating the type of the sensing data, and local configuration information.

[0158] Optionally, the local configuration information may be used to indicate a locally configured or unconfigured AI model. Optionally, the local configuration information may include a first identifier corresponding to the first AI model and auxiliary information.

[0159] In some embodiments, the name of the first information is not limited, and it can be, for example, an AI model identifier, AI auxiliary information, etc.

[0160] Step S2103: The first network element sends a first request to the second network element.

[0161] In some embodiments, the second network element receives the first request sent by the first network element.

[0162] In some embodiments, the second network element may be an AI function, an AI function entity, an AI server, or a core network device, etc.

[0163] Optionally, when the first network element sends the first request to the second network element, the first request may be used to establish a PDU session between the first network element and the second network element. Optionally, the PDU session may be a perception-related PDU session.

[0164] In step S2104A, the first network element determines whether there is a second AI model for processing the perception data.

[0165] In some embodiments, the first network element determines whether there is a second AI model that perceives the data based on the first information.

[0166] Optionally, the first network element determines a second AI model for processing the perception data based on the first identifier and / or the auxiliary information.

[0167] Optionally, the first network element determines, based on the first identifier and / or the auxiliary information, a second AI model that does not process the perception data.

[0168] Optionally, the second AI model is the same as the first AI model. Exemplarily, if the first network element queries locally or from the second network element and finds an AI model corresponding to the same identifier as the first identifier, then the AI ​​model is the first AI model.

[0169] Optionally, the second AI model is different from the first AI model. Exemplarily, if the first network element does not find an AI model corresponding to the same identifier as the first identifier locally or from the second network element, the second AI model can be determined based on auxiliary information.

[0170] Optionally, the first AI model and the second AI model may process the perception data. Exemplarily, the second AI model may be used to process the perception data to obtain a perception result.

[0171] Optionally, the perception result may be a result obtained by processing the perception data. For example, if the perception data is the position and / or speed of the vehicle during autonomous driving, the perception result may be the result of whether there is an obstacle in front of the vehicle and / or whether it will collide with other vehicles. For example, if the perception data is the temperature in the room, the perception result may be whether the space needs to be closed, etc. For example, if the perception result is the humidity of a crop field in agriculture, the humidity and / or temperature of the surrounding air, etc., the perception result may be a prediction of the germination time and / or growth condition of the crop, etc. The embodiments of the present disclosure do not limit the perception results.

[0172] In some optional embodiments, the first network element determines whether to accept the request to provide the perception service based on the first request. Optionally, the first network element determines whether to accept the request to provide the perception service based on the first information. Exemplarily, if the first network element determines based on the first information that the second AI model exists, the first network element determines to accept the request to provide the perception service; or, if the first network element determines based on the first information that the second AI model does not exist, the first network element determines to reject the request to provide the perception service.

[0173] In some optional embodiments, the first network element may download a second AI model to process the perception data.

[0174] In some optional embodiments, the second network element may be an internal logic function in the first network element. Exemplarily, the first network element integrates an AI functional entity.

[0175] In some optional embodiments, the first network element and the second network element are independent network elements.

[0176] All embodiments of the above step S2104A may be executed by the second network element, as shown in the following step S2104B.

[0177] In step S2104B, the second network element determines whether there is a second AI model for processing the perception data.

[0178] In some optional embodiments, the second network element determines whether to accept the request to provide the awareness service based on the first request. Optionally, the second network element determines whether to accept the request to provide the awareness service based on the first information. Exemplarily, if the second network element determines based on the first information that the second AI model exists, the second network element determines to accept the request to provide the awareness service; or, if the second network element determines based on the first information that the second AI model does not exist, the second network element determines to reject the request to provide the awareness service.

[0179] In some embodiments, the second network element determines whether there is a second AI model that perceives the data based on the first information.

[0180] Optionally, the second network element determines a second AI model for processing the perception data based on the first identifier and / or the auxiliary information.

[0181] Optionally, the second network element determines, based on the first identifier and / or the auxiliary information, a second AI model that does not process the perception data.

[0182] In some optional embodiments, the second network element determines whether to accept the request to provide the awareness service based on the first request. Optionally, the second network element determines whether to accept the request to provide the awareness service based on the first information.

[0183] In some optional embodiments, the second network element may download a second AI model to process the perception data.

[0184] The above-mentioned step S2104A and / or step S2104B may be step S2104.

[0185] Step S2105: The second network element sends a first response to the first network element.

[0186] In some embodiments, the first network element receives a first response sent by the second network element.

[0187] In some embodiments, the first response is used to indicate whether the request to provide the awareness service is accepted.

[0188] In some embodiments, the first response includes an acceptance indication message or a rejection indication message. Optionally, the acceptance indication message is used to indicate acceptance of the request to provide the perception service. Optionally, the rejection indication message is used to indicate rejection of the request to provide the perception service.

[0189] Optionally, both the acceptance indication information and the rejection indication information may be one or more bits.

[0190] In some embodiments, the first response is used to instruct an AI model to process the sensory data.

[0191] In some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing the perception data.

[0192] Optionally, the second identifier is used to uniquely identify the second AI model. Exemplarily, the second identifier can be any number, index, or string.

[0193] Optionally, the second identifier is the same as the first identifier, or the second identifier is different from the first identifier.

[0194] In some embodiments, the first response may be used to indicate whether to establish a PDU session. For example, if the first response includes an acceptance indication, it is determined that the first response indicates that the PDU session is established; or if the first response includes a rejection indication, it is determined that the first response indicates that the PDU session is not established.

[0195] In some embodiments, the name of the first response is not limited, and it can be, for example, a perception service response, a PDU session establishment response, a perception business response, an AI model response, etc.

[0196] Step S2106: The first network element sends a first response to the terminal.

[0197] In some embodiments, the terminal receives a first response sent by the first network element.

[0198] Step S2107: The terminal sends third information to the first network element.

[0199] In some embodiments, the first network element receives third information sent by the terminal.

[0200] In some embodiments, the third information includes the sensing data. Optionally, the third information may further include the second identifier and / or information related to the PDU session.

[0201] In some embodiments, the name of the third information is not limited.

[0202] In some embodiments, the terminal sends the third information to the first network element through the user plane.

[0203] In some embodiments, the terminal sends the third information to the first network element through the control plane.

[0204] Step S2108: The first network element sends fourth information to the terminal.

[0205] In some embodiments, the terminal receives fourth information sent by the first network element.

[0206] In some optional embodiments, the first network element determines a perception result based on the fourth information.

[0207] Optionally, the first network element processes the perception data based on the second AI model determined by the second identifier to obtain a perception result. Exemplarily, the first network element obtains the second AI model locally or from the second network element based on the second identifier.

[0208] In some embodiments, the fourth information includes a sensing result. Optionally, the fourth information may further include a third identifier and / or PDU session related information.

[0209] In some embodiments, the first network element sends the third information to the terminal through the user.

[0210] In some embodiments, the first network element sends the third information to the terminal via a control plane.

[0211] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0212] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0213] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0214] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "some", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "some A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, some A, any A, or first A, etc., but not limited to this.

[0215] In some embodiments, the determination or judgment can be performed by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value) represented by true or false, or by comparison of numerical values ​​(for example, comparison with a predetermined value), but is not limited thereto.

[0216] The information processing method involved in the embodiment of the present disclosure may include at least one of steps S2101 to S2108. For example, step S2101 can be implemented as an independent embodiment, step S2102 can be implemented as an independent embodiment; step S2103 can be implemented as an independent embodiment; step S2104 can be implemented as an independent embodiment; step S2105 can be implemented as an independent embodiment; step S2106 can be implemented as an independent embodiment; step S2107 can be implemented as an independent embodiment; step S2108 can be implemented as an independent embodiment; the combination of step S2101 and step S2102 can be implemented as an independent embodiment; the combination of step S2102 and step S2103 can be implemented as an independent embodiment; the combination of step S2101, step S2102, and step S2103 can be implemented as an independent embodiment. The combination can be implemented as an independent embodiment; the combination of step S2103 and step S2104 can be implemented as an independent embodiment; the combination of step S2102, step S2103 and step S2104 can be implemented as an independent embodiment; the combination of step S2104 and step S2105 can be implemented as an independent embodiment; the combination of step S2104, step S2105 and step S2106 can be implemented as an independent embodiment; the combination of step S2107 and step S2108 can be implemented as an independent embodiment; the combination of step S2102 to step S2108 can be implemented as an independent embodiment; the combination of step S2101 to step S2108 can be implemented as an independent embodiment.

[0217] In some embodiments, step S2101 and step S2107 may be executed in an interchanged order or simultaneously.

[0218] In some embodiments, step S2101, step S2104, step S2105, step S2106, step S2107, and step S2108 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0219] In some embodiments, step S2101, step S2102, step S2103, step S2107, and step S2108 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0220] In some embodiments, step S2101, step S2102, step S2103, step S2104, step S2105, and step S2106 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0221] FIG3A is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG3A , the present disclosure embodiment relates to an information processing method, which is executed by a terminal. The method includes:

[0222] Step S3101: Determine the first identifier based on the second information.

[0223] The optional implementation of step S3101 can refer to the optional implementation of step S2101 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0224] Step S3102: Send a first request.

[0225] The optional implementation of step S3102 can refer to the optional implementation of step S2102 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0226] In some embodiments, the terminal sends the first request to the first network element, but is not limited thereto, and the first request may also be sent to other entities.

[0227] Step S3103: Get the first response.

[0228] The optional implementation of step S3103 can refer to the optional implementation of step S2106 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0229] In some embodiments, the terminal receives the first request sent by the first network element, but is not limited thereto and may also receive the first request sent by other entities.

[0230] In some embodiments, the terminal obtains a first request specified by the protocol.

[0231] In some embodiments, the terminal obtains the first request from upper layer(s).

[0232] In some embodiments, the terminal performs processing to obtain the first request.

[0233] In some embodiments, step S3103 is omitted, and the terminal autonomously implements the function indicated by the first request, or the above function is default or acquiescent.

[0234] Step S3104, sending the third information.

[0235] The optional implementation of step S3104 can refer to the optional implementation of step S2107 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0236] In some embodiments, the terminal sends the third information to the first network element, but is not limited thereto, and the third information may also be sent to other entities.

[0237] Step S3105, obtain the fourth information.

[0238] The optional implementation of step S3105 can refer to the optional implementation of step S2108 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0239] In some embodiments, the terminal receives the fourth information sent by the first network element, but is not limited thereto, and may also receive the fourth information sent by other entities.

[0240] In some embodiments, the terminal obtains fourth information specified by the protocol.

[0241] In some embodiments, the terminal obtains the fourth information from an upper layer(s).

[0242] In some embodiments, the terminal performs processing to obtain the fourth information.

[0243] In some embodiments, step S3105 is omitted, and the terminal autonomously implements the function indicated by the fourth information, or the above function is default or by default.

[0244] The information processing method involved in the embodiments of the present disclosure may include at least one of steps S3101 to S3105. For example, step S3101 can be implemented as an independent embodiment, step S3102 can be implemented as an independent embodiment; step S3103 can be implemented as an independent embodiment; step S3104 can be implemented as an independent embodiment; step S3105 can be implemented as an independent embodiment; the combination of step S3101 and step S3102 can be implemented as an independent embodiment; the combination of step S3102 and step S3103 can be implemented as an independent embodiment; the combination of step S3101, step S3102, and step S3103 can be implemented as an independent embodiment; the combination of step S3103 and step S3104 can be implemented as an independent embodiment; the combination of step S3102, step S3103, step S3104, and step S3105 can be implemented as an independent embodiment; the combination of step S3101 to step S3105 can be implemented as an independent embodiment.

[0245] In some embodiments, step S3101 and step S3104 may be executed in an interchanged order or simultaneously.

[0246] In some embodiments, step S3101, step S3103, step S3104, and step S3105 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0247] In some embodiments, step S3101, step S3104, and step S3105 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0248] In some embodiments, step S3101, step S3102, and step S3103 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0249] FIG3B is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG3B , the present disclosure embodiment relates to an information processing method, which is executed by a terminal and includes:

[0250] Step S3201, sending a first request.

[0251] The optional implementation of step S3201 can be found in step S2102 in FIG. 2 , or the optional implementation of step S3102 in FIG. 3A , and other related parts in the embodiments involved in FIG. 2 and FIG. 3A , which will not be described in detail here.

[0252] In some embodiments, sending a first request includes: sending a first request to a first network element; wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request provision of a perception service.

[0253] In some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0254] In some embodiments, the auxiliary information includes at least one of the following: a model of the sensing device; a device identification of the sensing device; manufacturer information of the sensing device; type information indicating a type of sensing data; and local configuration information.

[0255] In some embodiments, the method also includes: the terminal receives a first response sent by the first network element, wherein the first response includes one of the following: acceptance indication information, used to indicate acceptance of the request to provide the perception service; and rejection indication information, used to indicate rejection of the request to provide the perception service.

[0256] In some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing the perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0257] In some embodiments, before sending the first request, it also includes: the terminal determines the first identifier based on the second information; wherein the second information includes at least one of the following: perception data, the model of the perception device, the device identifier of the perception device, the manufacturer information of the perception device, and type information indicating the type of perception data.

[0258] In some embodiments, the method includes: the terminal sends third information to the first network element, wherein the third information includes perception data; the terminal receives fourth information sent by the first network element, wherein the fourth information response includes a perception result determined based on the perception data.

[0259] In some embodiments, the first network element includes at least one of the following: SF, LMF and NWDAF; and / or the second network element includes at least one of the following: AI functional entity, AI server and core network equipment.

[0260] The above embodiments may be implemented individually or in combination with each other. For optional implementations, please refer to the optional implementations of the steps in FIG. 2 and FIG. 3A , which will not be described in detail here.

[0261] FIG4A is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG4A , the embodiment of the present disclosure relates to an information processing method, which is executed by a first network element. The method includes:

[0262] Step S4101, obtain the first request.

[0263] The optional implementation of step S4101 can refer to the optional implementation of step S2102 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0264] In some embodiments, the first network element receives the first request sent by the terminal, but is not limited thereto and may also receive the first request sent by other entities.

[0265] In some embodiments, the first network element obtains a first request specified by a protocol.

[0266] In some embodiments, the first network element obtains the first request from an upper layer(s).

[0267] In some embodiments, the first network element performs processing to obtain the first request.

[0268] In some embodiments, step S4101 is omitted, the first network element autonomously implements the function indicated by the first request, or the above function is default or by default.

[0269] Step S4102: Send a first request.

[0270] The optional implementation of step S4102 can refer to the optional implementation of step S2103 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0271] In some embodiments, the first network element sends the first request to the second network element, but is not limited thereto, and the first request may also be sent to other entities.

[0272] Step S4103: Determine whether there is a second AI model for processing the perception data.

[0273] Optionally, the first network element determines whether there is a second AI model for processing the perception data based on the first information.

[0274] The optional implementation of step S4103 can refer to the optional implementation of step S2104A in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0275] Step S4104, obtain the first response.

[0276] The optional implementation of step S4104 can refer to the optional implementation of step S2105 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0277] In some embodiments, the first network element receives the first response sent by the second network element, but is not limited thereto and may also receive the first response sent by other entities.

[0278] In some embodiments, the first network element obtains a first response specified by the protocol.

[0279] In some embodiments, the first network element obtains the first response from an upper layer(s).

[0280] In some embodiments, the first network element performs processing to obtain a first response.

[0281] In some embodiments, step S4104 is omitted, the first network element autonomously implements the function indicated by the first response, or the above function is default or by default.

[0282] Step S4105: Send a first response.

[0283] The optional implementation of step S4105 can refer to the optional implementation of step S2106 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0284] In some embodiments, the first network element sends the first response to the terminal, but is not limited thereto, and the first response may also be sent to other entities.

[0285] Step S4106, obtain third information.

[0286] The optional implementation of step S4106 can refer to the optional implementation of step S2107 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0287] In some embodiments, the first network element receives the third information sent by the terminal, but is not limited thereto, and may also receive the third information sent by other entities.

[0288] In some embodiments, the first network element obtains third information specified by the protocol.

[0289] In some embodiments, the first network element obtains the third information from an upper layer(s).

[0290] In some embodiments, the first network element performs processing to obtain the third information.

[0291] In some embodiments, step S4106 is omitted, the first network element autonomously implements the function indicated by the third information, or the above function is default or by default.

[0292] Step S4107, sending the fourth information.

[0293] The optional implementation of step S4107 can refer to the optional implementation of step S2108 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0294] In some embodiments, the first network element sends the fourth information to the terminal, but is not limited thereto, and the fourth information may also be sent to other entities.

[0295] The information processing method involved in the embodiment of the present disclosure may include at least one of steps S4101 to S4108. For example, step S4101 can be implemented as an independent embodiment, step S4102 can be implemented as an independent embodiment; step S4103 can be implemented as an independent embodiment; step S4104 can be implemented as an independent embodiment; step S4105 can be implemented as an independent embodiment; step S4106 can be implemented as an independent embodiment; step S4107 can be implemented as an independent embodiment; the combination of step S4101 and step S4102 can be implemented as an independent embodiment; the combination of step S4102 and step S4103 can be implemented as an independent embodiment. The combination of step S4101, step S4102 and step S4103 can be implemented as an independent embodiment; the combination of step S4103 and step S4104 can be implemented as an independent embodiment; the combination of step S4102, step S4103 and step S4104 can be implemented as an independent embodiment; the combination of step S4104 and step S4105 can be implemented as an independent embodiment; the combination of step S4106 and step S4107 can be implemented as an independent embodiment; the combination of step S4101 to step S4107 can be implemented as an independent embodiment.

[0296] In some embodiments, step S4101 and step S4106 may be executed in an interchanged order or simultaneously.

[0297] In some embodiments, step S4102, step S4103, step S4104, step S4105, step S4106, and step S4107 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0298] In some embodiments, step S4106 and step S4107 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0299] In some embodiments, step S4101, step S4102, step S4103, step S4104, and step S4105 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0300] FIG4B is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG4B , the embodiment of the present disclosure relates to an information processing method, which is executed by a first network element. The method includes:

[0301] Step S4201, receiving a first request.

[0302] The optional implementation of step S4201 can be found in step S2101 in FIG. 2 , or the optional implementation of step S4101 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0303] In some embodiments, receiving a first request includes: a first network element receives a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request provision of a perception service.

[0304] In some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0305] In some embodiments, the auxiliary information includes at least one of the following: a model of the sensing device; a device identification of the sensing device; manufacturer information of the sensing device; type information indicating a type of sensing data; and local configuration information.

[0306] In some embodiments, the method also includes: the first network element receives a first response sent by the second network element, wherein the first response includes acceptance indication information or rejection indication information; the acceptance indication information is used to indicate acceptance of the request to provide perception service; the rejection indication information is used to indicate rejection of the request to provide perception service.

[0307] In some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing the perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0308] In some embodiments, the method also includes one of the following: the first network element determines a second AI model for processing the perception data based on the first identifier and / or auxiliary information; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; and the first network element determines the second AI model that does not process the perception data based on the first identifier and / or auxiliary information.

[0309] In some embodiments, the method further includes: the first network element sending a first response to the terminal.

[0310] In some embodiments, the method also includes: the first network element receives third information sent by the terminal, wherein the third information includes perception data; the first network element processes the perception data based on the second AI model determined by the second identifier to obtain a perception result; the first network element sends fourth information to the terminal, wherein the fourth information includes the perception result.

[0311] In some embodiments, the first network element includes at least one of the following: SF, LMF and NWDAF; and / or the second network element includes at least one of the following: AI functional entity, AI server and core network equipment.

[0312] The above embodiments may be implemented individually or in combination with each other. For optional implementations, please refer to the optional implementations of the steps in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0313] FIG4C is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG4C , the embodiment of the present disclosure relates to an information processing method, which is executed by a first network element. The method includes:

[0314] Step S4301: Determine whether there is a second AI model for processing the perception data.

[0315] The optional implementation of step S4301 can be found in step S2104A in FIG. 2 , or the optional implementation of step S4103 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0316] The above embodiments may be implemented individually or in combination with each other. For optional implementations, please refer to the optional implementations of the steps in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0317] FIG5A is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG5A , the embodiment of the present disclosure relates to an information processing method, which is executed by a second network element. The method includes:

[0318] Step S5101, obtain the first request.

[0319] The optional implementation of step S5101 can refer to the optional implementation of step S2103 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0320] In some embodiments, the second network element receives the first request sent by the first network element, but is not limited thereto and may also receive the first request sent by other entities.

[0321] In some embodiments, the second network element obtains a first request specified by the protocol.

[0322] In some embodiments, the second network element obtains the first request from upper layer(s).

[0323] In some embodiments, the second network element performs processing to obtain the first request.

[0324] In some embodiments, step S5101 is omitted, and the second network element autonomously implements the function indicated by the first request, or the above function is default or by default.

[0325] Step S5102: Determine whether there is a second AI model for processing the perception data.

[0326] The optional implementation of step S5102 can refer to the optional implementation of step S2104B in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0327] Step S5103: Send a first response.

[0328] The optional implementation of step S5103 can refer to the optional implementation of step S2105 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0329] In some embodiments, the second network element sends the first response to the first network element, but is not limited thereto, and the first response may also be sent to other entities.

[0330] The information processing method involved in the embodiments of the present disclosure may include at least one of steps S5101 to S5103. For example, step S5101 can be implemented as an independent embodiment, step S5102 can be implemented as an independent embodiment, step S5103 can be implemented as an independent embodiment, the combination of step S5101 and step S5102 can be implemented as an independent embodiment, the combination of step S5102 and step S5103 can be implemented as an independent embodiment, the combination of step S5101 and step S5103 can be implemented as an independent embodiment, and the combination of step S5101, step S5102, and step S5103 can be implemented as an independent embodiment.

[0331] In some embodiments, step S5102 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0332] In some embodiments, step S5101 and step S5103 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0333] FIG5B is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG5B , the embodiment of the present disclosure relates to an information processing method, which is executed by a second network element. The method includes:

[0334] Step S5201, receiving a first request.

[0335] The optional implementation of step S5201 can be found in step S2103 in FIG. 2 , or the optional implementation of step S5101 in FIG. 5A , and other related parts in the embodiments involved in FIG. 2 and FIG. 5A , which will not be described in detail here.

[0336] In some embodiments, receiving a first request includes: a second network element receiving a first request sent by a first network element; wherein the first request includes first information, the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request provision of a perception service.

[0337] In some embodiments, requesting provision of a perception service includes at least one of: requesting a service for processing perception data; and requesting negotiation of an AI model for processing perception data.

[0338] In some embodiments, the auxiliary information includes at least one of the following: a model of the sensing device; a device identification of the sensing device; manufacturer information of the sensing device; type information indicating a type of sensing data; and local configuration information.

[0339] In some embodiments, the method also includes one of the following: the second network element determines a second AI model for processing the perception data based on the first identifier and / or auxiliary information; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; and the second network element determines an AI model that does not process the perception data based on the first identifier and / or auxiliary information.

[0340] In some embodiments, the method also includes: the second network element sends a first response to the first network element, wherein the first response includes one of the following: acceptance indication information, used to indicate acceptance of the request to provide perception service; and rejection indication information, used to indicate rejection of the request to provide perception service.

[0341] In some embodiments, when the first response includes acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing the perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

[0342] In some embodiments, the first network element includes at least one of the following: SF, LMF and NWDAF; and / or the second network element includes at least one of the following: AI functional entity, AI server and core network equipment.

[0343] The above embodiments may be implemented individually or in combination with each other. For optional implementations, please refer to the optional implementations of the steps in FIG. 2 and FIG. 5A , which will not be described in detail here.

[0344] FIG5C is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG5C , the embodiment of the present disclosure relates to an information processing method, which is executed by a second network element. The method includes:

[0345] Step S5301: Determine whether there is a second AI model for processing perception data.

[0346] The optional implementation of step S5301 can be found in step S2104B in FIG. 2 , or the optional implementation of step S5102 in FIG. 5A , and other related parts in the embodiments involved in FIG. 2 and FIG. 5A , which will not be described in detail here.

[0347] The above embodiments may be implemented individually or in combination with each other. For optional implementations, please refer to the optional implementations of the steps in FIG. 2 and FIG. 5A , which will not be described in detail here.

[0348] FIG6 is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG6, the embodiment of the present disclosure relates to an information processing method for a communication system, the method comprising:

[0349] Step S6101: The terminal sends a first request to the network device.

[0350] Optionally, the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first AI model; the first request is used to request provision of a perception service.

[0351] The optional implementation method of step S6101 can be found in the optional embodiment of step S2102 in Figure 2, the optional implementation method of step S3101 in Figure 3A, or step S4101 in Figure 4A, and other related parts in the embodiments involved in Figures 2, 3A, and 4A, which will not be repeated here.

[0352] In some embodiments, the above method may include the method described in the above-mentioned embodiments of the information processing system 100 side, the terminal side, the first network element side, the second network element side, etc., which will not be repeated here.

[0353] FIG7 is a flow chart of an information processing method according to an embodiment of the present disclosure. As shown in FIG7 , the embodiment of the present disclosure relates to an information processing method, which includes:

[0354] Step S7101: The UE initiates a sensing service to the sensing device and collects sensing data.

[0355] Optionally, the UE may be the terminal in the previous embodiment. The UE determines that the sensing data needs to be sent to the network for processing based on the processing capability of the UE or sensing service requirements.

[0356] Step S7102: The UE determines the AI ​​model identifier.

[0357] Optionally, the UE determines the AI ​​model identifier based on the perception information; wherein the perception information includes the model of the perception device, the device identifier of the perception device, the device manufacturer and / or the perception data type, etc.

[0358] Optionally, the UE determines AI model auxiliary information based on perception information and / or local configuration information.

[0359] Optionally, the AI ​​model identifier can be the first identifier in the previous embodiment; the perception information can be the second information in the previous embodiment; the device manufacturer can be the manufacturer information in the previous embodiment; the perception data type can be the type information in the previous embodiment; and the AI ​​model auxiliary information can be the auxiliary information in the previous embodiment.

[0360] Step S7103: The UE sends a perception service request to the SF.

[0361] Optionally, the UE sends a perception service request to the SF through the access network device and the AMF. For example, the UE sends a perception service request to the access network device; the access network device sends a perception service request to the AMF; and the AMF sends a perception service request to the SF.

[0362] Optionally, the perception service request includes an AI model identifier and / or AI model auxiliary information; the AI ​​model identifier and / or AI model auxiliary information are used to assist the network device (e.g., SF, AI functional entity) in selecting a suitable AI model (e.g., the second AI model in the previous embodiment).

[0363] Optionally, the awareness service request may be the first request in the previous embodiment; or, the awareness service request may be a PDU session establishment request.

[0364] Step S7104: SF sends an AI model request to the AI ​​functional entity.

[0365] Optionally, the AI ​​model request includes an AI model identifier and / or AI model auxiliary information; the AI ​​model identifier and / or AI model auxiliary information are used by the AI ​​functional entity to determine a suitable AI model (eg, the second AI model in the previous embodiment).

[0366] Optionally, the AI ​​model request may be the first request in the previous embodiment.

[0367] Step S7105: The AI ​​functional entity sends an AI model response to the SF.

[0368] Optionally, the AI ​​model response includes an AI model identifier of the appropriate AI model determined by the network device; the AI ​​model identifier may be the second identifier in the previous embodiment. Optionally, the SF may download corresponding AI model processing data based on the AI ​​model identifier.

[0369] Optionally, the AI ​​functional entity determines that there is no suitable AI model based on the AI ​​model identifier and / or the AI ​​model auxiliary information, and sends an acceptance indication to the SF; alternatively, the AI ​​model entity determines that there is a suitable AI model based on the AI ​​model identifier and / or the AI ​​model auxiliary information, and sends a rejection indication to the SF. Optionally, the acceptance indication may be the acceptance indication information in the previous embodiment; the rejection indication may be the rejection indication information in the previous embodiment.

[0370] Step S7106: SF sends a perception service response to the UE.

[0371] Optionally, the sensing service response includes: accepting an indication or rejecting an indication.

[0372] In some optional embodiments, the further embodiment includes: the UE sending the perception data to the SF through the user plane, so that the SF processes the perception data; after the SF completes the processing, the SF sends the processing result to the UE through the user plane.

[0373] In some optional embodiments, the further embodiment includes: the UE sending the perception data to the SF through the control plane, so that the SF processes the perception data; after the SF completes the processing, the SF sends the processing result to the UE through the user plane.

[0374] Optionally, the perception service response may be the second request in the previous embodiment; and the processing result may be the perception result in the previous embodiment.

[0375] The information processing method involved in the embodiment of the present disclosure may include at least one of steps S7101 to S7106. For example, step S7101 can be implemented as an independent embodiment, step S7102 can be implemented as an independent embodiment; step S7103 can be implemented as an independent embodiment; step S7104 can be implemented as an independent embodiment; step S7105 can be implemented as an independent embodiment; step S7106 can be implemented as an independent embodiment; the combination of step S7101 and step S7102 can be implemented as an independent embodiment; the combination of step S7102, step S7103 and step S7104 can be implemented as an independent embodiment; the combination of step S7104 and step S7105 can be implemented as an independent embodiment; the combination of step S7104, step S7105 and step S7106 can be implemented as an independent embodiment; the combination of step S7102 to step S7106 can be implemented as an independent embodiment; the combination of step S7101 to step S7106 can be implemented as an independent embodiment.

[0376] In some embodiments, step S7101, step S7102, step S7104, step S7105, and step S7106 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0377] In some embodiments, step S7101 and step S7102 may be optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0378] In the embodiments of the present disclosure, some or all of the steps and their optional implementations may be arbitrarily combined with some or all of the steps in other embodiments, and may also be arbitrarily combined with the optional implementations of other embodiments.

[0379] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0380] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), and the functions of some or all of the above units or modules are realized by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0381] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of a hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0382] Figure 8A is a schematic structural diagram of a terminal 8100 provided in an embodiment of the present disclosure. As shown in Figure 8A, the terminal 8100 includes: a first transceiver module 8101 and a first processing module 8102. In some embodiments, the first transceiver module 8101 is used to send a first request. Optionally, the first transceiver module 8101 is used to execute at least one of the steps of receiving and / or sending (such as step S2102, step S2106, step S2107 and / or step S2108, but not limited thereto) executed by the terminal 8100 in any of the above methods, which are not described in detail here. Optionally, the first processing module 8102 is used to execute at least one of the steps of processing (such as step S2101, but not limited thereto) executed by the terminal 8100 in any of the above methods, which are not described in detail here.

[0383] Figure 8B is a schematic structural diagram of the first network element 8200 provided in an embodiment of the present disclosure. As shown in Figure 8B, the first network element 8200 includes: at least one of a second transceiver module 8201 and a second processing module 8202. In some embodiments, the second transceiver module 8201 is used to obtain a first request. Optionally, the second transceiver module 8201 is used to execute at least one of the receiving and / or sending steps (such as steps S2102, S2103, S2105, S2106, S2107, and / or S2108, but not limited thereto) performed by the first network element in any of the above methods, which are not described in detail here. Optionally, the second processing module 8202 is used to execute at least one of the processing steps (such as steps S2104A, but not limited thereto) performed by the first network element in any of the above methods, which are not described in detail here.

[0384] Figure 8C is a structural diagram of the second network element 8300 provided in an embodiment of the present disclosure. As shown in Figure 8C, the second network element 8300 includes: at least one of a third transceiver module 8301 and a third processing module 8302. In some embodiments, the third transceiver module 8301 is used to obtain the first request. Optionally, the third transceiver module 8301 is used to execute at least one of the steps of receiving and / or sending (such as step S2103 and / or step S2105, but not limited thereto) executed by the second network element in any of the above methods, which are not described in detail here. Optionally, the third processing module 8302 is used to execute at least one of the steps of processing (such as step S2104B, but not limited thereto) executed by the second network element in any of the above methods, which are not described in detail here.

[0385] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module. The transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module and the transceiver may be interchangeable. Exemplarily, the first transceiver module includes a first transmitting module and / or a first receiving module. Exemplarily, the second transceiver module includes a second transmitting module and / or a second receiving module.

[0386] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0387] Figure 9A is a schematic diagram of the structure of a communication device 9100 proposed in an embodiment of the present disclosure. Communication device 9100 can be a network device (e.g., an access network device, a core network device, a first network element, a second network element, etc.), or a terminal (e.g., a user equipment, etc.), or a chip, chip system, or processor that supports a network device to implement any of the above methods, or a chip, chip system, or processor that supports a terminal to implement any of the above methods. Communication device 9100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0388] As shown in Figure 9A, the communication device 9100 includes one or more processors 9101. The processor 9101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 9100 is used to perform any of the above methods. Optionally, one or more processors 9101 are used to call instructions to enable the communication device 9100 to perform any of the above methods.

[0389] In some embodiments, the communication device 9100 further includes one or more transceivers 9102. When the communication device 9100 includes one or more transceivers 9102, the transceiver 9102 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, step 2101, but not limited thereto), and the processor 9101 performs at least one of the other steps (for example, step 2102 and / or step 2103, but not limited thereto). In an optional embodiment, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be interchangeable, the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be interchangeable, and the terms receiver, receiving unit, receiver, and receiving circuit may be interchangeable.

[0390] In some embodiments, the communication device 9100 further includes one or more memories 9103 for storing data. Alternatively, all or part of the memories 9103 may be located outside the communication device 9100. In alternative embodiments, the communication device 9100 may include one or more interface circuits 9104. Optionally, the interface circuits 9104 are connected to the memories 9103 and may be configured to receive data from the memories 9103 or other devices, or to send data to the memories 9103 or other devices. For example, the interface circuits 9104 may read data stored in the memories 9103 and send the data to the processor 9101.

[0391] The communication device 9100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 9100 described in the present disclosure is not limited thereto, and the structure of the communication device 9100 may not be limited by FIG. 9A. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (9) others, etc.

[0392] 9B is a schematic diagram of the structure of a chip 9200 according to an embodiment of the present disclosure. If the communication device 9100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 9200 shown in FIG9B , but the present disclosure is not limited thereto.

[0393] The chip 9200 includes one or more processors 9201. The chip 9200 is configured to execute any of the above methods.

[0394] In some embodiments, chip 9200 further includes one or more interface circuits 9202. Terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 9200 further includes one or more memories 9203 for storing data. Alternatively, all or part of memory 9203 may be located external to chip 9200. Optionally, interface circuit 9202 is connected to memory 9203 and may be used to receive data from memory 9203 or other devices, or may be used to send data to memory 9203 or other devices. For example, interface circuit 9202 may read data stored in memory 9203 and send the data to processor 9201.

[0395] In some embodiments, the interface circuit 9202 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method (e.g., steps S2102, S2103, S2105, S2106, S2107, and / or S2108, but not limited thereto). The interface circuit 9202 performing the communication steps, such as sending and / or receiving, in the above-described method, for example, means that the interface circuit 9202 performs data exchange between the processor 9201, chip 9200, memory 9203, or a transceiver device. In some embodiments, the processor 9201 performs at least one of the other steps (e.g., steps S2101 and / or S2104, but not limited thereto).

[0396] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0397] The present disclosure also proposes a storage medium having instructions stored thereon, which, when executed on the communication device 9100, causes the communication device 9100 to execute any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a temporary storage medium.

[0398] The present disclosure also provides a program product, which, when executed by the communication device 9100, enables the communication device 9100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0399] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

Claims

1. An information processing method, characterized in that: The method comprises: The terminal sends a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request provision of a perception service.

2. The method according to claim 1, characterized in that: The request provides a perception service, including at least one of the following: Requesting services to process sensor data; Request negotiation of an AI model for processing the perception data.

3. The method according to claim 1 or 2, characterized in that: The auxiliary information includes at least one of the following: The model of the sensing device; The device identification of the sensing device; The manufacturer information of the sensing device; Type information indicating the type of the sensed data; Local configuration information.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: The terminal receives a first response sent by the first network element, wherein the first response includes one of the following: Acceptance indication information, used to indicate acceptance of the request for providing the perception service; The rejection indication information is used to indicate the rejection of the request to provide the perception service.

5. The method according to claim 4, characterized in that When the first response includes the acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing the perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

6. The method according to any one of claims 1 to 5, characterized in that: Before sending the first request, the method further includes: The terminal determines the first identifier based on second information; wherein the second information includes at least one of the following: the perception data, the model of the perception device, the device identifier of the perception device, the manufacturer information of the perception device, and type information indicating the type of perception data.

7. The method according to any one of claims 4 to 6, characterized in that: The method comprises: The terminal sends third information to the first network element, wherein the third information includes perception data; The terminal receives fourth information sent by the first network element, wherein the fourth information response includes a perception result determined based on the perception data.

8. The method according to any one of claims 1 to 7, characterized in that: The first network element includes at least one of the following: a sensing function SF, a location management function LMF, and a network data analysis function NWDAF; and / or, The second network element includes at least one of the following: an AI functional entity, an AI server, and a core network device.

9. An information processing method, characterized in that: The method comprises: The first network element receives a first request sent by a terminal, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request provision of a perception service.

10. The method according to claim 9, characterized in that The request provides a perception service, including at least one of the following: Requesting services to process sensor data; Request negotiation of an AI model for processing the perception data.

11. The method according to claim 9 or 10, characterized in that: The auxiliary information includes at least one of the following: The model of the sensing device; The device identification of the sensing device; The manufacturer information of the sensing device; Type information indicating the type of the sensed data; Local configuration information.

12. The method according to any one of claims 9 to 11, characterized in that: The method further comprises: The first network element receives a first response sent by the second network element, wherein the first response includes acceptance indication information or rejection indication information; the acceptance indication information is used to indicate acceptance of the request for providing the perception service; the rejection indication information is used to indicate rejection of the request for providing the perception service.

13. The method according to claim 12, characterized in that When the first response includes the acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

14. The method according to any one of claims 9 to 11, characterized in that: The method also Includes one of the following: The first network element determines, based on the first identifier and / or the auxiliary information, a second AI model for processing the perception data; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; The first network element determines, based on the first identifier and / or the auxiliary information, that the second AI model has not processed the perception data.

15. The method according to claim 12 or 13, characterized in that The method also includes: the first network element sending the first response to the terminal.

16. The method according to claim 15, characterized in that The method further comprises: The first network element receives third information sent by the terminal, wherein the third information includes perception data; The first network element processes the perception data based on a second AI model determined by the second identifier to obtain a perception result; The first network element sends fourth information to the terminal, wherein the fourth information includes the perception result.

17. The method according to any one of claims 9 to 14, characterized in that The first network element includes at least one of the following: a sensing function SF, a location management function LMF, and a network data analysis function NWDAF; and / or, The second network element includes at least one of the following: an AI functional entity, an AI server, and a core network device.

18. An information processing method, characterized in that: The method comprises: The second network element receives a first request sent by the first network element, wherein the first request includes first information, the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; and the first request is used to request provision of a perception service.

19. The method according to claim 18, characterized in that The request provides a perception service, including at least one of the following: Requesting services to process sensor data; Request negotiation of an AI model for processing the perception data.

20. The method according to claim 18 or 19, characterized in that The auxiliary information includes at least one of the following: The model of the sensing device; The device identification of the sensing device; The manufacturer information of the sensing device; Type information indicating the type of the sensed data; Local configuration information.

21. The method according to any one of claims 18 to 20, characterized in that The method also Includes one of the following: The second network element determines, based on the first identifier and / or the auxiliary information, a second AI model for processing the perception data; wherein the second AI model is the same as the first AI model, or the second AI model is the same as the first AI model; The second network element determines, based on the first identifier and / or the auxiliary information, that there is no AI model that processes the perception data.

22. The method according to claim 18, characterized in that The method further comprises: The second network element sends a first response to the first network element, wherein the first response includes one of the following: Acceptance indication information, used to indicate acceptance of the request for providing the perception service; The rejection indication information is used to indicate the rejection of the request to provide the perception service.

23. The method according to claim 22, characterized in that When the first response includes the acceptance indication information, the first response also includes a second identifier; wherein the second identifier is used to indicate a second AI model for processing perception data; the second AI model is the same as the first AI model, or the second AI model is different from the first AI model.

24. The method according to any one of claims 18 to 23, characterized in that The first network element includes at least one of the following: a sensing function SF, a location management function LMF, and a network data analysis function NWDAF; and / or, The second network element includes at least one of the following: an AI functional entity, an AI server, and a core network device.

25. An information processing method, characterized in that: include: The terminal sends a first request to the network device, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request provision of a perception service.

26. A terminal, characterized in that: include: The first transceiver module is configured to send a first request to a first network element, wherein the first request includes first information, and the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; the first request is used to request provision of a perception service.

27. A first network element, characterized in that: include: The second transceiver module is configured to receive a first request sent by the terminal, wherein the first request includes first information, the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; and the first request is used to request provision of a perception service.

28. A second network element, characterized in that: include: The third transceiver module is configured to receive a first request sent by a first network element, wherein the first request includes first information, the first information includes a first identifier and / or auxiliary information indicating a first artificial intelligence AI model; and the first request is used to request provision of a perception service.

29. A terminal, characterized in that: include: one or more processors; The terminal is used to execute the information processing method according to any one of claims 1 to 8.

30. A first network element, characterized in that: include: one or more processors; The first network element is used to execute the information processing method according to any one of claims 9 to 17.

31. A second network element, characterized in that: include: one or more processors; The second network element is used to execute the information processing method according to any one of claims 18 to 24.

32. A communication system, characterized in that: include: A terminal, a first network element and a second network element; wherein the terminal is configured to implement the information processing method described in any one of claims 1 to 8, the first network element is configured to implement the information processing method described in any one of claims 9 to 17, and the second network element is configured to implement the information processing method described in any one of claims 18 to 24.

33. A storage medium storing instructions, characterized in that: When the instruction is executed on the communication device, the communication device executes the information processing method according to any one of claims 1 to 8, claims 9 to 17, claims 18 to 24, or claim 25.

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