DETAILED ACTION
This office action is in response to the amendments filed on 12/01/2025.
Claims 11-20, 22, 25 are cancelled.
Claims 1-10, 21, 23-14, and 26 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 12/01/2025 regarding 35 USC 101 abstract rejections and 35 USC 103 rejections in Remarks pg. 5-12 have been fully considered but they are not persuasive.
Applicant argues in essence:
[a] “The claims of the present invention define specific technical solutions, not "mental processes" grouping of abstract idea. Examiner's assertion that the core limitations of the claims can be "performed in the human mind and/or using pen or paper" confuses the fundamental distinction between "mental processes" and "network technical solutions." A "mental process" refers to pure logical reasoning that is detached from technical carriers and relies solely on intellectual activity.
Applicant further emphasizes the guidance set forth in the Memorandum, dated August 4, 2025, by Deputy Commissioner for Patents Charles Kim (hereinafter the "Aug 2025 Memo"), which states:
a claim does not recite a mental process when it contains limitation(s) that cannot practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitation(s). Here, the claims cannot be practically performed in the human mind nor with pen and paper. In contrast, the solutions defined in the claims revolve around specific network element interactions within network architecture, with each limitation requiring implementation based on network hardware, communication protocols, and technical specifications.” Pg. 5
In response to [a], examiner respectfully disagrees. The analysis for 35 USC 101 abstract idea for a mental process does not require “pure logical reasoning that is detached from technical carriers and relies solely on intellectual activity.”. The Mpep in 2106.04(a)(2) III (C) and (D) describes mental processes that require a computer or a computing environment. Therefore the concept that the mental process must be completely detached from technology or computers does not apply.
Secondly, applicant argues that based on the August 4th 2025 memorandum that because of the claims revolving around particular network architecture, hardware protocols and technical specifications, the claims cannot be practically performed in the human mind. Examiner respectfully disagrees. In short, the claims function around obtaining services, generating a list of these services, and in response to a request generating a subset of the list, and providing that list back to the requesting device for selection of a service from a network element. A person can reasonably determine a list of available services, and determine appropriate services to provide based on a request within the mind or with pen and paper. Regarding the remaining analysis of 35 USC 101 abstract idea in view of the additional limitations, these will be addressed in response to the particular arguments as set forth by the applicant, below.
[b] “Regarding claim 1, "generating a candidate Al service list" is not an abstract "determination of available services," but a process in which the NRF network element performs structured storage and organization based on specific technical information registered by Al network elements. It involves standardized formats for network element profiles, technical definitions of data fields, and compliance with, for example, 5G network interface protocols (such as service operations like NnrfNFManagement and Nnwdaf_MLModelProvision), which cannot be directly completed manually.” Pg. 5-6
In response to [b], examiner respectfully disagrees. Firstly, examiner notes that the claims that recite the particular NNRF services as argued by the applicant are not rejected under 35 USC 101 abstract idea, i.e. claims 3-4 and 6.
Secondly, in response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “a process in which the NRF network element performs structured storage and organization based on specific technical information registered by Al network elements. It involves standardized formats for network element profiles, technical definitions of data fields, and compliance with, for example, 5G network interface protocols”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Applicant argues that the NRF of claim 1 requires “structured storage and organization based on specific technical information registered by Al network elements. It involves standardized formats for network element profiles, technical definitions of data fields, and compliance with, for example, 5G network interface protocols… which cannot be directly completed manually” however Claim 1 is silent to any limitations that require this process. Under broadest reasonable interpretation, the NRF of claim 1 broadly generates a list of AI services and does not describe any structured storage, technical definitions or compliance. Therefore this argument does not apply to Claim 1.
[c] “"Generating an AI service list corresponding to the first network element based on the AI service query request and the candidate AI service list" in claim 1 is essentially a precise matching technical logic executed by the NRF network element. It involves technical links such as network slice compatibility verification, service area coverage determination, and AI model version adaptation, relying on processor computations and real-time interaction of network data-rather than a simple "subset selection" mental activity.” Pg. 6
In response to [c], examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “a precise matching technical logic executed by the NRF network element. It involves technical links such as network slice compatibility verification, service area coverage determination, and AI model version adaptation, relying on processor computations and real-time interaction of network data”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Claim 1 does not describe any requirements on how the matching is performed and what metrics are matched to generate the AI service list. Therefore this argument does not apply.
[d] “"The first network element selects the AI network element from the AI service list to provide the AI service" in claim 1 involves network technical operations such as establishing communication links between network elements, verifying service invocation permissions, and feeding back the execution status of AI services. It must comply with the service invocation specifications of the 5G core network, and is not a mere "selection act."” Pg. 6
In response to [d], examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “network technical operations such as establishing communication links between network elements, verifying service invocation permissions, and feeding back the execution status of AI services. It must comply with the service invocation specifications of the 5G core network,”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant argues that because the generating of the AI service list require a plurality of network technical operations and compliance with 5G, the process goes beyond that of a selection act. However none of these examples are claimed in Claim 1. Secondly, a selection act is never explicitly performed in Claim 1, i.e. some determination of reduction of the candidate ai service list based on the request. Therefore, under broadest reasonable interpretation, the AI service list may be the entirety of the candidate AI list, i.e. the AI service query may be a request for the entire AI service list, and the generating step may be merely generating a response including the entire candidate ai service list without any level of selection. Therefore examiner respectfully disagrees.
[e] “In summary, the limitations of the claim 1 all rely on specific network elements, protocols, algorithms, and hardware support, with clear technical carriers and implementation paths. They do not fall under the abstract concept of "mental processes." “ pg. 6
In response to [e], based on the responses to [a]-[d] arguments above, examiner respectfully disagrees that Claim 1 relies on each and every one of the examples provided by applicant above, as none of these requirements for structure and storage of the candidate service list, as well as the selection process for generating the ai service list and its matching and compliance requirements are claimed. Therefore examiner respectfully disagrees with applicant and maintains rejection under 35 USC 101 abstract idea.
[f] “Examiner submits that the concept of an NRF is well known and cannot provide an inventive concept, which fails to consider the application boundaries of common general knowledge and the innovative improvements of the claimed solutions. Although the basic storage function of NRF is well known, the claims of the present invention do not simply apply the known uses of NRF-instead, conduct innovative expansions of NRF's functions. Known NRF is only used to store basic service information of ordinary network elements, while in the claimed solutions, NRF is specifically adapted to the special attributes of AI services, and designed with registration data structures, query matching algorithms, and feedback data formats tailored for AI services, which significantly exceed the known application scenarios of NRF and form a new technical concept.” Pg. 6
In response to [f], examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “while in the claimed solutions, NRF is specifically adapted to the special attributes of AI services, and designed with registration data structures, query matching algorithms, and feedback data formats tailored for AI services”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Similar to the arguments above, the differences with ordinary NRF and the claimed NRF as described by the applicant are not properly described in the Claim. There is no description of any special attributes of AI services, registration data structures, query matching or feedback. The claims are silent to any particular difference between an ordinary service and an AI service that would cause matching or compliance analysis to return available services to operate differently than ordinary NRF. Therefore examiner respectfully disagrees and maintains 35 USC 101 abstract idea rejection.
[g] “The Office Action alleges that Lee discloses "generating an AI service list corresponding to the first network element based on the AI service query request and registered services" recited in claim 1. Office Action, pp. 13-14. Applicant respectfully submits that Lee fails to anticipate, teach or suggest this feature for at least the following reasons….
para.0238…para.0240…
The Office Action seems to interpret a request for searching the NWDAF device 803 from the NWDAF device 801 to the NRF device 802 in Lee as "AI service query request" as defined in claim 1, and interpret "instances of one or more candidate NWDAF devices 803" from the NRF device 802 to the NF consumer in Lee as the "AI service list" as defined in claim 1. Applicant respectfully disagrees.
Para.0242-0247…
As can be seen, in Lee, based on NnrfNFDiscoveryRequest from the NWDAF device 801 in operation 4, the NRF device 802 searches candidate NWDAF devices 803 from the NWDAF devices 803 that have registered with the NRF device earlier in operation 3. Then the NRF device 802 provides a list of instances of the candidate NWDAF devices 803 to the NWDAF device 801. That is, Lee generates a list of candidate NWDAF devices based on a discovery request and the registered NWDAF devices. In other words, Lee selects candidate network entities by querying registered network entities.
However, in the claim 1, the NRF device generate an AI service list corresponding to the first network element based on the AI service query request and the candidate AI service list. In other words, the NRF device selects and generates the AI service list by querying the candidate AI service list. Lee neither discloses a "candidate AI service list" as admitted by the Office Action, nor discloses the NRF device generate an AI service list corresponding to the first network element based on the AI service query request and the candidate AI service list.” Pg. 7-8
In response to [g], examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Here applicant has 2 main arguments, first that the list is of candidate NWDAF devices and second that Lee does not disclose a candidate AI service list.
Firstly, under broadest reasonable interpretation, the claim does not disclose that is within a candidate AI service list or an AI service list, only that the list is associated with AI services. Additionally, the only thing that the claim discloses that is within an AI service list is the AI network element, as in the last limitation, the AI network element is selected from the AI service list. Similarly Lee discloses providing a list of candidate device that perform various AI services in para.0238-0240 as cited in pg. 13-14 of the NF rejection 09/25/2025.
para.0240 "During discovery of the NWDAF device 803 that performs the MTLF, the NRF device 802 may return instances of one or more candidate NWDAF devices 803 to an NF consumer, and an instance of each candidate NWDAF device 803 may include analytics filter information on an ML model of an initial model that is untrained or an ML model that is trained for each Analytic ID.”
para.0008 "a discovery response service operation with respect to the ML model discovery request service operation, and selecting an NWDAF instance included in the discovery response service operation"
para.0120-0121 " In response to discovery, alternatively, when the NWDAF device 401 receives NWDAF device(s) 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability), the NWDAF device 401 may preferably select the NWDAF device 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability) with a large serving area.”
As seen in para.0240, para.0008, and para.0120-0121 above, Lee discloses providing an AI service list with various NWDAF devices, along with their service capabilities, such as aggregation, model update etc. and the recipient of the list selects the device providing a particular service. This is the same process as the claim wherein a network element providing a particular service is chosen from the AI service list.
Secondly, applicant argues that Lee does not explicitly disclose a candidate ai service. Examiner agrees, as Lee never explicitly generates a “list” of the services provided by NWDAF devices, only that it is made of aware of these services provided by various devices in para.0010, wherein NF profiles are maintained, and used to respond to NNWDAF queries for those services, therefore the limitation was mapped to “registered services” rather than the list. However functionally, other than that the comparison is with a candidate list in the claim, the query is compared to known profiles of device that provided the matching AI services as seen in para.0240 above, i.e. matching the analytics ID as requested by the requesting device. The list itself is taught by secondary reference Sapra and explained in more detail below in response to the arguments presented against Sapra.
[h] “The Office Action alleges that Lee discloses "feeding back the AI service list to the first network element" recited in claim 1. Office Action, pp. 14. Applicant respectfully submits that Lee fails to anticipate, teach or suggest this feature for at least the following reasons. Paragraph [0129] of Lee discloses that "During discovery of the NWDAF device 403 that supports the MTLF, the NRF device 402 may return instances of one or more candidate NWDAF devices 403 to an NF consumer". Pg 8-9
As mentioned above, Lee does not disclose the AI service list generated based on the candidate AI service list. Lee further does not disclose the NRF device feeds back the AI service list to the first network element. “
In response to [h], examiner respectfully disagrees. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
While an explicit list has not been used to generate the AI service list, a set of profiles of known NWDAF devices that provided services are used to determining matching devices that perform the requested services to generate the AI service list. That is, only the format in which the data is organized of candidate ai services is different, rather than the information itself. Sapra is relied upon to teach the list itself of NF profiles.
Sapra para.0060 “In some embodiments, the NRF accesses a NF profile repository containing a list of NF profiles corresponding to producer NFs that have previously registered with the NRF. More specifically, the NRF accesses the NF profile repository to acquire all NF profile objects associated with producer NFs that host, expose, and/or support the network service requested by the consumer NF in the single NFdiscovery request message received in block 602. In some embodiments, the NF profile objects obtained from the NF profile repository conform with the search attributes set forth in the NF discovery request message.”
The discovery request message is compared to the candidate service list. i.e. the list of NF profiles, to respond to the discovery request.
[i] “The Office Action alleges that Lee discloses "the first network element selects the AI network element from the AI service list to provide the AI service" recited in claim 1. Office Action, pp. 14. Applicant respectfully submits that Lee fails to anticipate, teach or suggest this feature for at least the following reasons.
Paragraph [0008] of Lee discloses that "a discovery response service operation with respect to the ML model discovery request service operation, and selecting an NWDAF instance included in the discovery response service operation". Paragraphs [0120]-[0121] of Lee discloses that "In response to discovery, alternatively, when the NWDAF device 401 receives NWDAF device(s) 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability), the NWDAF device 401 may preferably select the NWDAF device 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability) with a large serving area".
As mentioned above, Lee only disclose that the NRF returns instances of one or more candidate NWDAF devices 403 to an NF consumer (i.e., the NWDAF device 401). According to the above content in Lee, Lee can only teach that the NWDAF device 401 then selects a target NWDAF device 403 from candidate NWDAF device(s) received. That is, Lee selects a target network entity by querying candidate network entities.
Nowhere does Lee disclose that the first network element selects the AI network element from the AI service list to provide the AI service.” Pg. 9
In response to [i], examiner respectfully disagrees. As argued by the applicant, the limitation requires that a the first network element selects the AI network element, i.e. a service providing device, that provides the AI service from the list. This is the same as what is taught by Lee, wherein a NWDAF device is selected from the provided list to provide the AI service.
[j] “Sapra does not remedy the above-discussed deficiencies of Lee. The Office Action further alleges that Sapra discloses "generating a candidate service list" and "generating an AI service list corresponding to the first network element based on the AI service query request and the candidate AI service list" recited in claim 1. Office Action, pp. 14-15. Applicant respectfully submits that Sapra also fails to anticipate, teach or suggest this feature for at least the following reasons. Para.0036, para.0060 The Office Action seems to interpret "a list of NF profiles" in Sapra as "a candidate service list" in claim 1. Applicant respectfully disagrees.
Sapra only discloses the NF profile repository containing a list of NF profiles corresponding to producer NFs that have previously registered with the NRF, and each NF profile in the list of NF profiles may include NF profile objects related to the corresponding producer NF. However, Sapra does not disclose that the NRF may generate a candidate service list based on NF profile objects.” Pg.9-10
In response to [j], examiner respectfully disagrees. Para.0060-0061 as cited by examiner explicitly show this process:
Para.0060 “In block 608, NF profiles for each of the indicated NF target types is discovered. In some embodiments, the NRF executes the NF discovery service operation. In some embodiments, the NRF is configured to execute the NFDiscover procedure specified in the TS29.510 standard in order to obtain NF profiles corresponding to each of the producer NF types that provides the network services requested by the consumer NF in block 602. In some embodiments, the NRF accesses a NF profile repository containing a list of NF profiles corresponding to producer NFs that have previously registered with the NRF. More specifically, the NRF accesses the NF profile repository to acquire all NF profile objects associated with producer NFs that host, expose, and/or support the network service requested by the consumer NF in the single NFdiscovery request message received in block 602. In some embodiments, the NF profile objects obtained from the NF profile repository conform with the search attributes set forth in the NF discovery request message.”
Para.0061 “In block 610, the plurality of NF profiles are added to a discovery response message. In some embodiments, the NRF will then generate a NF discovery response message that includes a number of NF profiles (e.g., obtained in block 608) that pertain to the plurality of NF target types specified in the consumer NF's original discovery request message criteria. The NF profiles provided in the response message will also comply to the search attribute features (e.g., PLMN, network slice, and/or preferred locality) specified in the original discovery request message originally sent to the NRF.”
As seen above, Sapra explicitly receives a request with a requested network service, and the NRF returns a list of NF profiles that meet the original discovery request for the requested network services. Therefore Sapra meets the requirements of the claim.
[k] “Furthermore, according to paragraphs [0059] to [0061] of Sapra, "the NRF is configured to inspect the discovery request massage for a listing of NF target types requested by the consumer NF", "NF profiles for each of the indicated NF target types is discovered", "the NRF will then generate a NF discovery response message that includes a number of NF profiles (e.g., obtained in block 608 ) that pertain to the plurality of NF target types specified in the consumer NF's original discovery request message criteria".
It can be seen that the essence of Sapra lies in the NRF acquiring the target NF(s) according to the discovery request and further obtaining the NF profile(s) corresponding to the target NF(s). Sapra does not disclose the candidate AI service list or the AI service list, nor does it disclose the above-mentioned distinguishing technical features between Lee and the claim 1. The combination of Lee and Sapra also fails to obtain the above-mentioned distinguishing technical features.” Pg.10-11
In response to [k], examiner respectfully disagrees. The essence of Sapra that the applicant argues is the same process as what is described in the claim. The discover request is for particular NF target types para.0030 “ In addition, the indication may also include a list of producer network function types (e.g., NF target type) in the custom header portion (e.g., {list(NFType}) for which the network function profiles are sought.”, and matching NF profiles that provide that particular functions are provided in response to the discovery request. This is the same process as the claim. The only difference is that Sapra does not explicitly disclose AI services, which is taught by Lee, with the only difference being that the NF profiles are not organized in a list as in Sapra.
Lee teaches every limitation in Claim 1 aside from the concept that a list is used rather than a general repository of NF profiles being used to compare to generate a discovery response for the NWDAFs that provide the services. Therefore in combination Lee and Sapra teach Claim 1. Therefore examiner respectfully disagrees and maintains rejection in view of Lee and Sapra.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 2, 5, 7, 9, 21, 23-24, 26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims 1, 21 and 23 recite in part “An artificial intelligence (Al) service providing method… generating a candidate Al service list; … generating an Al service list corresponding to the first network element based on the Al service query request and the candidate Al service list; and … wherein the first network element selects the Al network element from the Al service list to provide the Al service.”
The limitations as drafted above is a process that under broadest reasonable interpretation covers performance of the limitations in the mind, but for recitation of generic computer component and extra solution activities. That is, other than the limitations of “a network repository function (NRF) network element… obtaining an Al service provided by an Al network element… receiving an Al service query request from a first network element … and feeding back the Al service list to the first network element” “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, and “A non-transitory computer-readable storage medium having instructions stored thereon” the claim comprises limitations that can be performed in the human mind and/or using pen or paper. In this case, a person can reasonably determine available services, determine a subset of those services that are relevant to a request, and selecting a service among the subset of services. If a claim under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic components and extra solution activities, then it falls within “mental processes” grouping of abstract idea. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular the claims on recite the additional features of “a network repository function (NRF) network element… obtaining an Al service provided by an Al network element… receiving an Al service query request from a first network element … and feeding back the Al service list to the first network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, and “A non-transitory computer-readable storage medium having instructions stored thereon”. Regarding the steps of “obtaining an Al service provided by an Al network element… receiving an Al service query request from a first network element … and feeding back the Al service list to the first network element”, these are merely sending and receiving of information that are merely extra solution activities that initiate the abstract idea by obtaining the information required to perform the abstract idea and outputting the results of the abstract idea. Regarding the elements of “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, and “A non-transitory computer-readable storage medium having instructions stored thereon”, these are generic computer hardware elements recited as performing routine activities. Regarding the first network element, it is merely a generic hardware or software element that performs the extra solution activity in the network. Regarding the NRF network element it is merely a hardware or software element in the network that acts as a storage for the services, performing the abstract idea and extra solution activities in the claim. Regarding the AI services themselves, it is merely a description of the type of service that is listed in the service list, and not recited as using AI/machine learning in a meaningful way that affects the performance of the abstract idea. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in respect to the integration of the abstract idea into a practical application, the elements of “a network repository function (NRF) network element… obtaining an Al service provided by an Al network element… receiving an Al service query request from a first network element … and feeding back the Al service list to the first network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, and “A non-transitory computer-readable storage medium having instructions stored thereon” amounts to no more than mere instructions to apply the abstract idea to generic network elements, generic computer elements and extra solution activities. Further, the concept of an NRF is well known since at least 2016, as described in Son et al. US 2018/0103368, being described in para.0011, Mere instructions to apply the abstract idea to generic/well-known hardware/software components and extra solution activities cannot provide an inventive concept. The claims are not patent eligible.
Regarding Claim 7, 24, and 26, they recite in part “An artificial intelligence (Al) service providing method, selecting an Al service that matches the Al service information from the Al service list, determining at least one Al network element corresponding to the Al service.”
The limitations as drafted above is a process that under broadest reasonable interpretation covers performance of the limitations in the mind, but for recitation of generic computer component and extra solution activities. That is, other than the limitations of “a first network element…receiving an Al service request from a terminal device, wherein the Al service request comprises required Al service information; sending an Al service query request to a network repository function (NRF) network element; receiving an Al service list fed back by the NRF network element, … sending a policy request to the Al network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, “A non-transitory computer-readable storage medium having instructions stored thereon” the claim comprises limitations that can be performed in the human mind and/or using pen or paper. In this case, a person can reasonably select a service amongst a list of services, and determine a provider for that service. If a claim under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic components and extra solution activities, then it falls within “mental processes” grouping of abstract idea. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular the claims on recite the additional features of “a first network element…receiving an Al service request from a terminal device, wherein the Al service request comprises required Al service information; sending an Al service query request to a network repository function (NRF) network element; receiving an Al service list fed back by the NRF network element, … sending a policy request to the Al network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, “A non-transitory computer-readable storage medium having instructions stored thereon”. Regarding the steps of “receiving an Al service request from a terminal device, wherein the Al service request comprises required Al service information; sending an Al service query request to a network repository function (NRF) network element; receiving an Al service list fed back by the NRF network element, … sending a policy request to the Al network element”, these are merely sending and receiving of information that are merely extra solution activities that initiate the abstract idea by obtaining the information required to perform the abstract idea and outputting the results of the abstract idea. Regarding the elements of “first a network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, “A non-transitory computer-readable storage medium having instructions stored thereon”, these are generic computer hardware elements recited as performing routine activities. Regarding the NRF network element it is merely a hardware or software element in the network that acts as a storage for the services, performing the abstract idea and extra solution activities in the claim. Regarding the AI services themselves, it is merely a description of the type of service that is listed in the service list, and not recited as using AI/machine learning in a meaningful way that affects the performance of the abstract idea. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in respect to the integration of the abstract idea into a practical application, the elements of “a first network element…receiving an Al service request from a terminal device, wherein the Al service request comprises required Al service information; sending an Al service query request to a network repository function (NRF) network element; receiving an Al service list fed back by the NRF network element, … sending a policy request to the Al network element”, “A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor”, “A non-transitory computer-readable storage medium having instructions stored thereon” amounts to no more than mere instructions to apply the abstract idea to generic network elements, generic computer elements and extra solution activities. Further, the concept of an NRF is well known since at least 2016, as described in Son et al. US 2018/0103368, being described in para.0011, Mere instructions to apply the abstract idea to generic/well-known hardware/software components and extra solution activities cannot provide an inventive concept. The claims are not patent eligible.
Regarding Claims, 2, 5, 9, 14 they recite in part “generating the candidate Al service list based on the registration request” “obtaining a network function and an Al service that the network function supports in the Al service query request; and generating the Al service list by performing filtering and matching on the candidate Al service list based on the network function and the Al service that the network function supports in the Al service query request”
The limitations as drafted above is a process that under broadest reasonable interpretation covers performance of the limitations in the mind, but for recitation of generic computer component and extra solution activities. That is, other than the limitations of “receiving a registration request from the Al network element, wherein the registration request comprises at least one Al service provided by the Al network element” “receiving policy information fed back by the Al network element, wherein the policy information is generated by the Al service; and sending the policy information to the terminal device” “wherein the policy information is generated;” the claims comprise limitations that can be performed in the human mind and/or using pen or paper. In this case, a person can reasonably analyze a request, determine an appropriate list of service based on the request by filtering and matching the request to known services, and determine policies in view of information. If a claim under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic components and extra solution activities, then it falls within “mental processes” grouping of abstract idea. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular the claims on recite the additional features of “receiving a registration request from the Al network element, wherein the registration request comprises at least one Al service provided by the Al network element” “receiving policy information fed back by the Al network element, wherein the policy information is generated by the Al service; and sending the policy information to the terminal device” “receiving Al service information of a terminal device sent by a first network element… and sending the policy information to the first network element.” Regarding the steps of “receiving a registration request from the Al network element, wherein the registration request comprises at least one Al service provided by the Al network element” “receiving policy information fed back by the Al network element, and sending the policy information to the terminal device” these are merely sending and receiving of information that are merely extra solution activities that initiate the abstract idea by obtaining the information required to perform the abstract idea and outputting the results of the abstract idea. Regarding the step of “wherein the policy information is generated by the Al service;”, the AI service is merely generic software that performs the abstract idea, in this case determining policy information. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in respect to the integration of the abstract idea into a practical application, the elements of “receiving a registration request from the Al network element, wherein the registration request comprises at least one Al service provided by the Al network element” “receiving policy information fed back by the Al network element, wherein the policy information is generated by the Al service; and sending the policy information to the terminal device” amounts to no more than mere instructions to apply the abstract idea to generic network elements, generic computer elements and extra solution activities. Mere instructions to apply the abstract idea to generic hardware/software components and extra solution activities cannot provide an inventive concept. The claims are not patent eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-6, 21, 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (hereinafter Lee, US 2022/0108214 A1) in view of Sapra et al. (hereinafter Sapra, US 2022/0286949 A1).
Regarding Claim 1, Lee discloses An artificial intelligence (Al) service providing method, applied to a network repository function (NRF) network element (Lee para.0008 “invoking, from an NRF device, an ML model discovery request service operation, invoking, from the NRF device, a discovery response service operation with respect to the ML model discovery request service operation” the NRF provides machine learning services to a requesting device. Examiner notes applicants specification para.0074 “For example, the Al service provided by the AI network element may include machine learning (ML)” includes machine learning as an AI service), comprising:
obtaining an Al service provided by an Al network element (Lee para.0010 “The NRF device may be configured to store an NF profile for the MTLF by invoking, from the second NWDAF device, a registration request service operation with an NF, and the registration request service operation may include at least one of (i) a list of Analytic IDs, (ii) a supported service, (iii) a serving area, (iv) S-NSSAI, and (v) ML model information including at least one of an ML model file address, an ML model file, a model ID, and a model version.” Via a registration operation, the NRF obtains a machine learning model from an NWDAF/MTLF device)
receiving an Al service query request from a first network element (Lee: para.0008 “According to an aspect, there is provided a method for discovering an ML model, the method performed by a first NWDAF device including invoking, from an NRF device, an ML model discovery request service operation,”);
generating an Al service list corresponding to the first network element based on the Al service query request and registered services (Lee: para.0238 “When the NWDAF device 801 needs to search for the NWDAF device 803 with a data collection exposure capability, the NWDAF device 801 may search for, through the NRF device 802, the NWDAF device 803 that provides an Nnwdaf DataManagement service operation and an ID of a related NF type data source or related NF set data source.” Para.0239 “In order to search for the NWDAF device 803 that performs the MTLF, the NWDAF device 801 that performs the MTLF may include at least one of analytics filter information, a trainable and providable ML model ID, an ML model version, and an ML model aggregation capability with respect to an ML model” para.0240 “During discovery of the NWDAF device 803 that performs the MTLF, the NRF device 802 may return instances of one or more candidate NWDAF devices 803 to an NF consumer, and an instance of each candidate NWDAF device 803 may include analytics filter information on an ML model of an initial model that is untrained or an ML model that is trained for each Analytic ID.” Based on the service query request from the NWDAF device, matching instances of NWDAF devices that provides a list of the NWDAF devices for the requested NFs providing Machine learning services, from the NWDAF devices that have registered with the NRF earlier in Fig. 8 in step 1-3)
feeding back the Al service list to the first network element (Lee: para.0008 “invoking, from the NRF device, a discovery response service operation with respect to the ML model discovery request service operation” para.0129 “During discovery of the NWDAF device 403 that supports the MTLF, the NRF device 402 may return instances of one or more candidate NWDAF devices 403 to an NF consumer,” each NWDAF device supports one or more machine learning models as seen in para.0010 wherein each NWDAF registers an ML model, and a discovery response, such that that of step 5 in Fig. 4, may include a plurality of instances, i.e. an AI service list.),
wherein the first network element selects the Al network element from the Al service list to provide the Al service (Lee: para.0008 “a discovery response service operation with respect to the ML model discovery request service operation, and selecting an NWDAF instance included in the discovery response service operation” see also para.0120-0121 “ In response to discovery, alternatively, when the NWDAF device 401 receives NWDAF device(s) 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability), the NWDAF device 401 may preferably select the NWDAF device 403 having an aggregation capability (for example, an ML model aggregation capability and an ML model update capability) with a large serving area.” In response to the discovery response, the device 401 selects a NWDAF providing the appropriate machine learning model service..).
However Lee does not explicitly disclose generating a candidate Al service list; generating an Al service list corresponding to the first network element based on the Al service query request and the candidate Al service list.
Sapra discloses generating a candidate service list (Sapra: para.0036 “For example, producer NF 240 can send a NF register message (not shown) to NRF 200 that indicates the producer NF's provided network service 210, PLMN, network slice (if applicable), locality, and other NF specific information. NRF 200 may be configured to store the NF registration information as NF profile objects in a local NF profile repository (NFPR) 208.” Para.0060 “In some embodiments, the NRF accesses a NF profile repository containing a list of NF profiles corresponding to producer NFs that have previously registered with the NRF.” Registered NF profiles objects are stored as a list in the repository, thereby generating a candidate service list. For example, the new NF can be added to an existing list, generating a new candidate service list, or this may be the first NF to register, also generating a candidate service list);
generating an service list corresponding to the first network element based on the service query request and the candidate service list (Sapra: pra.0060 “More specifically, the NRF accesses the NF profile repository to acquire all NF profile objects associated with producer NFs that host, expose, and/or support the network service requested by the consumer NF in the single NFdiscovery request message received in block 602. In some embodiments, the NF profile objects obtained from the NF profile repository conform with the search attributes set forth in the NF discovery request message.” Pra.0061 “In block 610, the plurality of NF profiles are added to a discovery response message. In some embodiments, the NRF will then generate a NF discovery response message that includes a number of NF profiles (e.g., obtained in block 608) that pertain to the plurality of NF target types specified in the consumer NF's original discovery request message criteria.” The plurality of NF profiles that match the discovery request message, i.e. service list, from the list of registered NFs, candidate service list, is included into a discovery response message.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lee and Sapra in order to incorporate generating a candidate service list; generating an service list corresponding to the first network element based on the service query request and the candidate service list, and apply this concept to the AI services of Lee.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit of improving NF service discovery (Sapra: para.0001).
Regarding Claim 2, Lee-Sapra discloses claim 1 as set forth above.
Lee further discloses wherein obtaining the Al service provided by the Al network element comprise: receiving a registration request from the Al network element, wherein the registration request comprises at least one Al service provided by the Al network element (Lee para.0010 “The NRF device may be configured to store an NF profile for the MTLF by invoking, from the second NWDAF device, a registration request service operation with an NF, and the registration request service operation may include at least one of (i) a list of Analytic IDs, (ii) a supported service, (iii) a serving area, (iv) S-NSSAI, and (v) ML model information including at least one of an ML model file address, an ML model file, a model ID, and a model version.” Via a registration operation, the NRF obtains a machine learning model from an NWDAF/MTLF device via a registration operation including the ML model file and information regarding the ML model).
However Lee does not explicitly disclose wherein generating the candidate Al service list, comprise: generating the candidate Al service list based on the registration request.
Sapra discloses wherein generating the candidate service list, comprise: generating the candidate service list based on the registration request (Sapra: para.0036 “For example, producer NF 240 can send a NF register message (not shown) to NRF 200 that indicates the producer NF's provided network service 210, PLMN, network slice (if applicable), locality, and other NF specific information. NRF 200 may be configured to store the NF registration information as NF profile objects in a local NF profile repository (NFPR) 208.” Para.0060 “In some embodiments, the NRF accesses a NF profile repository containing a list of NF profiles corresponding to producer NFs that have previously registered with the NRF.” When an NF register message is received, it is recorded into the NF profile repository, thereby generating the candidate service list. For example the new NF can be added to an existing list, generating a candidate service list, or this may be the first NF to register, also generating a candidate service list).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lee and Sapra in order to incorporate wherein generating the candidate service list, comprise: generating the candidate service list based on the registration request, and apply this concept to the AI services of Lee.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit of improving NF service discovery (Sapra: para.0001).
Regarding Claim 3, Lee-Sapra discloses claim 2 as set forth above.
Lee further discloses wherein the registration request is an Nnrf_NFManagement_NFRegister request (Lee: para.0242 “In operation 1, the NWDAF device 803 may invoke, from the NRF device 802, a registration service operation (Nnrf_NFManagement_NFRegister request) for the NWDAF device 803. ” Fig. 8, and Fig. 4 shows the Nnrf_NFManagement_NFRegister request).
Regarding Claim 4, Lee-Sapra discloses claim 2 as set forth above.
Lee further discloses wherein after receiving the registration request from the Al network element, the method further comprises: sending an Nnrf_NFManagementNFRegister response to the Al network element (Lee: para.0244 “In operation 3, the NRF device 802 may invoke, from the NWDAF device 803, a registration response service operation (Nnrf_NFManagement_NFRegister response).” An Nnrf_NFManagement_NFRegister response is sent in response to the registration).
Regarding Claim 5, Lee-Sapra discloses claim 1 as set forth above.
Lee further discloses wherein generating the Al service list corresponding to the first network element based on the Al service query request and the registered services, comprises: obtaining a network function and an Al service that the network function supports in the Al service query request (Lee: para.0245 “In operation 4, the NWDAF device 801 may invoke, from the NRF device 802, a request service operation (Nnrf_NFDiscovery_Request) for searching for the NWDAF device 803. At this time, the request service operation may include at least one of (i) a list of supported Analytic IDs, (ii) a service supported by the NWDAF device 803 (for example, an Nnwdaf_MLModelProvision service and an Nnwdaf_MLModelInfo service), (iii) a serving area where an ML model is provided, (iv) S-NSSAI, (v) ML model information including at least one of an ML model file address, an ML model file, a model ID, and a model version, and (vi) a federation learning capability (aggregation capability for a result of training an ML model (for example, an ML model update capability)).” Para.0134 “An Analytic ID, A supportable service for each Analytic ID (for example, an ML model provision/training service)” The network function of the machine learning model is the analytic ID, and supportable services for each analytic id, is provided in the request service operation); and
generating the Al service list by performing filtering and matching on the registered services based on the network function and the Al service that the network function supports in the Al service query request (Lee: para.0238 “When the NWDAF device 801 needs to search for the NWDAF device 803 with a data collection exposure capability, the NWDAF device 801 may search for, through the NRF device 802, the NWDAF device 803 that provides an Nnwdaf DataManagement service operation and an ID of a related NF type data source or related NF set data source.” Para.0239 “In order to search for the NWDAF device 803 that performs the MTLF, the NWDAF device 801 that performs the MTLF may include at least one of analytics filter information, a trainable and providable ML model ID, an ML model version, and an ML model aggregation capability with respect to an ML model” para.0240 “During discovery of the NWDAF device 803 that performs the MTLF, the NRF device 802 may return instances of one or more candidate NWDAF devices 803 to an NF consumer, and an instance of each candidate NWDAF device 803 may include analytics filter information on an ML model of an initial model that is untrained or an ML model that is trained for each Analytic ID.” Based on the service query request from the NWDAF device, matching instances of NWDAF devices that provides a list of the NWDAF devices for the requested NFs providing Machine learning services, from the NWDAF devices that have registered with the NRF earlier in Fig. 8 in step 1-3 that matches the query).
However Lee does not explicitly disclose generating the Al service list by performing filtering and matching on the candidate Al service list based on the network function and the Al service that the network function supports in the Al service query request.
Sapra discloses generating the service list by performing filtering and matching on the candidate service list based on the search attributes in the service query request (Sapra: pra.0060 “More specifically, the NRF accesses the NF profile repository to acquire all NF profile objects associated with producer NFs that host, expose, and/or support the network service requested by the consumer NF in the single NFdiscovery request message received in block 602. In some embodiments, the NF profile objects obtained from the NF profile repository conform with the search attributes set forth in the NF discovery request message.” Pra.0061 “In block 610, the plurality of NF profiles are added to a discovery response message. In some embodiments, the NRF will then generate a NF discovery response message that includes a number of NF profiles (e.g., obtained in block 608) that pertain to the plurality of NF target types specified in the consumer NF's original discovery request message criteria.” The plurality of NF profiles that match the discovery request message, i.e. service list, from the list of registered NFs, candidate service list, is included into a discovery response message, therefore the non matching, i.e. not conforming to the search attributes are filtered out.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lee and Sapra in order to incorporate generating the service list by performing filtering and matching on the candidate service list based on the search attributes in the service query request and apply this concept to the AI services and each of the search attributes (i.e. network function and ai service) of Lee.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit of improving NF service discovery (Sapra: para.0001).
Regarding Claim 6, Lee-Sapra discloses claim 1 as set forth above.
However Lee does not explicitly disclose wherein the Al service query request is received via an HTTP GET message, and the Al service list is sent to the first network element via an HTTP RESPONSE message.
Sapra discloses wherein the service query request is received via an HTTP GET message (Sapra: para.0038 “In particular, consumer NF 202 can send a single NFdiscovery request message that requests discovery of a plurality of producer NF types. Notably, the single NF discover request message includes an indication or notation (e.g., a “multiple NF discovery requests” tag) in a customized header portion of the message. In some embodiments, the NF discovery request message comprises an HTTP GET request message that is sent by the NF service consumer to the NRF.” The service discovery is send via an HTTP GET request message),
and the service list is sent to the first network element via an HTTP RESPONSE message (Sapra: para.0056 “FIG. 5 also illustrates an NF discovery response message 509 that may be generated by an NRF in response to receiving an NF discovery request message 501 or 505. In some embodiments, discovery response message 509 is an HTTP response message generated by the NRF. Notably, message portion 510 is a customer header portion of the discovery response message 509 and includes an indication that the “MultipleDiscoveryRequests” feature is indeed supported by the sending entity (e.g., the NRF). NF discovery response message 509 further includes body portion 512 that contains a plurality of NF profiles.” In response to the discovery request, an HTTP response message may be received comprising a plurality of NF profiles, i.e. the service list.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lee with Sapra to incorporate wherein the service query request is received via an HTTP GET message, and the service list is sent to the first network element via an HTTP RESPONSE message, and apply this technique to the AI services in Lee, and thereby perform the simple substitution of (using NNRF discovery requests and responses with an NRF) in Lee with (using HTTP get and response messages with an NRF) in Sapra.
The simple substitution of (using NNRF discovery requests and responses with an NRF) for another (using HTTP get and response messages with an NRF) would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention because the substitution would have yielded predictable results, namely, obtaining services registered at the NRF (Lee: para.0242-0244, and Sapra: para.0038, para.0056).
Regarding Claim 21, Lee-Sapra discloses the method of claim 1 as set forth above.
Lee further discloses A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor, the communication apparatus is caused to perform the method (Lee: para.0382-0383).
Regarding Claim 23, Lee-Sapra discloses claim 1 as set forth above.
Lee further discloses A non-transitory computer-readable storage medium having instructions stored thereon, wherein when the instructions are executed, the method (Lee: para.0383-0384).
Claim(s) 7, 9, 24, 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karampatsis et al. (hereinafter Kar, US 2023/0345297 A1) in view of Lee et al. (hereinafter Lee2, US 2020/0396678 A1) in view of Li (US 2022/0408280 A1).
Regarding Claim 7, Kar discloses An artificial intelligence (Al) service providing method, applied to a first network element (Kar: Fig. 3A para.0076 method of Fig. 3A providing ML services by AGF-NWDAF 255, the first network element), comprising:
receiving an Al service request from a terminal device, wherein the Al service request comprises required Al service information (Kar: para.0079 “At Step 1, a consumer NF 210 requests analytics from an AGF-NWDAF 255 (see messaging 319). In some embodiments, the consumer NF 210 may subscribe to notifications of Analytic Output feedback, i.e. provide feedback whether previously provided analytics validity time or confidence level changes.” Para.0081 “ At Step 2, the AGF-NWDAF 255 determines the training ML model required based on the requested Analytic ID (see block 321)” Consumer NF sends to the AGF-NWDAF required ai service information, i.e. regarding the ML model, such as analytic ID);
sending an Al service query request to a network repository function (NRF) network element (Kar: para.0083 “At Step 4, the AGF-NWDAF 255 sends an Nnrf_discovery request including the NF-type set to the NRF 301 and may also include the Analytic ID for the requested ML model (see messaging 325).” The AGF sends to the NRF a discovery request for the ML model);
receiving an Al service list fed back by the NRF network element (Kar: para.0084 “At Step 5, the NRF 301 provides a list of MMTF-NWDAFs 260 that contains trained ML models for this Analytic ID (see messaging 327).” A list of the NWDAFs comprising the ML models is received, i.e. the ai service list.); and
determining at least one Al network element corresponding to the Al service (Kar: para.0084 “At Step 5, the NRF 301 provides a list of MMTF-NWDAFs 260 that contains trained ML models for this Analytic ID (see messaging 327).” para.0085 “At Step 6, the AGF-NWDAF 255 requests the ML model from the MMTF-NWDAF 260 using a new service-based Nnwdaf procedure, e.g., sending a Nnwdaf_Model_Request message (see messaging 329).” An MMTF NWDAF is selected from the list received in step 5, and a request is sent in step 6.).
However, while Kar discloses a PCF, policy control function, Kar does not explicitly disclose selecting an Al service that matches the Al service information from the Al service list, sending a policy request to the Al network element.
Lee2 discloses selecting a service that matches the terminal device information from the service list (Lee2: para.0055 “For example, in operation 227a, in the case where the AMF 120 requests discovering a PCF capable of performing DNN replacement for the UE 100, the NRF 300 may select one or more PCFs capable of performing DNN replacement among PCFs registered in the NRF 300. In addition, the NRF 300 may select one or more PCFs, close to the current location of the UE 100 and/or the location of the AMF 120, among one or more PCFs capable of performing DNN replacement. The Nnrf_NFDiscovery response message, which is transmitted by the NRF 300 to the AMF 120 in operation 227c, may include one or more pieces of PCF information selected by the NRF 300 (for example, the NF ID of the PCF, and NF services supported by the PCF… The AMF 120 may select one PCF based on PCF information received from the NRF 300…. Alternatively, in the case where multiple pieces of PCF information are received from the NRF 300, the AMF 120 may select a PCF based on the local configuration of the AMF 120, the location of the UE 100, and the location of the PCF and the like.” A plurality of PCFs and services provided by each PCF is obtained. The AMF then selects a PCF based on the information provided, i.e. including the service information, based on the information of the UE that the AMF serves.)
sending a policy request to the network element (Lee: para.0057 “In operations 230a to 236ba, Npcf_AMPolicyControl_Create to Npcf_UEPolicyControl_Create message, transmitted by the AMF 120 to the PCF 140” a policy request is then sent to the selected PCF)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Kar with Lee2 in order to incorporate selecting a service that matches the service information from the service list; sending a policy request to the network element, and apply this concept to the AI services and the AI network element of Kar, such that the requesting device may have access to the PCF 134 in Fig. 1 of Kar.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit improving communication (Lee2: para.0003, para.0011-0012).
However Kar-Lee does not explicitly disclose sending a policy request to the Al network element, in other words Kar-Lee2 does not explicitly disclose an AI network element that provides a policy.
Li discloses the Al network element (Li: para.0044 “In a first version of the fifth-generation (5G) standard, an NWDAF entity based on machine learning is used by the third Generation Partnership Project (3GPP) as a basis for a network slice selection function and a policy control function. In other words, execution of the network slice selection function and the policy control function depends on the NWDAF entity.” The NWDAF entity is machine learning based, and implements a policy control function.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Kar-Lee2 with Li in order to incorporate the AI network element of a PCF.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit that comes with machine learning such as learning and improving based on collected metrics (Li: para.0044).
Regarding Claim 9, Kar-Lee2-Li discloses claim 7 as set forth above.
However Kar does not explicitly disclose receiving policy information fed back by the Al network element, wherein the policy information is generated by the Al service; and sending the policy information to the terminal device.
Lee2 discloses receiving policy information fed back by the network element, wherein the policy information is generated by the service (Lee: para.0091 “In operation 509, the PCF 140 may transmit a Namf_Communication_N1N2MessageTransfer message to the AMF 120. The policy container included in the Namf_Communication_N1N2MessageTransfer message may include at least one of DNN information associated with an application (for example, identified by a combination of OSId and OSAppId), a DNN priority, equivalent DNN information that can be used in the same manner as the DNN, and the identifier of the UE 100 (e.g., SUPI, 5G-GUTI, and the like).” Policy information is received from the PCF); and
sending the policy information to the terminal device (Lee: para.0093 “ In operation 515, the AMF 120 may transmit a policy container received from the PCF 140 to the UE 100.” Policy is fed back to the terminal device 100.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Kar-Lee2-Li in order to incorporate receiving policy information fed back by the network element, wherein the policy information is generated by the service, and apply this concept to the AI network element and the AI service as set forth in Kar-Lee2-Li.
One of ordinary skill in the art would have been motivated to combine because of the expected benefit of implementing required updates (Park: para.0573).
Regarding Claim 24, Kar-Lee2-Li discloses the method of claim 7 as set forth above.
Kar further discloses A communication apparatus comprising: a processor, and a memory having computer programs stored thereon, wherein when the computer programs are executed by the processor, the communication apparatus is caused to perform the method (Kar: para.0024 para.0102-0103).
Regarding Claim 26, Kar-Lee2-Li discloses claim 7 as set forth above.
Kar further discloses A non-transitory computer-readable storage medium having instructions stored thereon, wherein when the instructions are executed, the method (Kar: para.0018).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karampatsis et al. (hereinafter Kar, US 2023/0345297 A1) in view of Lee et al. (hereinafter Lee2, US 2020/0396678 A1) in view of Li (US 2022/0408280 A1) in view of Sapra et al. (hereinafter Sapra, US 2022/0286949 A1).
Regarding Claim 8, Kar-Lee2-Li discloses claim 1 as set forth above.
However Kar does not explicitly disclose wherein the Al service query request is sent to the NRF network element via an HTTP GET message, and the Al service list fed back by the NRF network element is received via an HTTP RESPONSE message.
Sapra discloses wherein the service query request is sent to the NRF network element via an HTTP GET message (Sapra: para.0038 “In particular, consumer NF 202 can send a single NFdiscovery request message that requests discovery of a plurality of producer NF types. Notably, the single NF discover request message includes an indication or notation (e.g., a “multiple NF discovery requests” tag) in a customized header portion of the message. In some embodiments, the NF discovery request message comprises an HTTP GET request message that is sent by the NF service consumer to the NRF.” The service discovery is send via an HTTP GET request message),
the service list fed back by the NRF network element is received via an HTTP RESPONSE message (Sapra: para.0056 “FIG. 5 also illustrates an NF discovery response message 509 that may be generated by an NRF in response to receiving an NF discovery request message 501 or 505. In some embodiments, discovery response message 509 is an HTTP response message generated by the NRF. Notably, message portion 510 is a customer header portion of the discovery response message 509 and includes an indication that the “MultipleDiscoveryRequests” feature is indeed supported by the sending entity (e.g., the NRF). NF discovery response message 509 further includes body portion 512 that contains a plurality of NF profiles.” In response to the discovery request, an HTTP response message may be received comprising a plurality of NF profiles, i.e. the service list.).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Kar-Lee2-Li with Sapra to incorporate wherein the service query request is sent to the NRF network element via an HTTP GET message, and the service list fed back by the NRF network element is received via an HTTP RESPONSE message, and apply this technique to the AI services in Kar, and thereby perform the simple substitution of (using NNRF discovery requests and responses with an NRF) in Kar with (using HTTP get and response messages with an NRF) in Sapra.
The simple substitution of (using NNRF discovery requests and responses with an NRF) for another (using HTTP get and response messages with an NRF) would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention because the substitution would have yielded predictable results, namely, obtaining services registered at the NRF (Kar: Fig. 3A step 4-5, para.0083-0084, and Sapra: para.0038, para.0056).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karampatsis et al. (hereinafter Kar, US 2023/0345297 A1) in view of Lee et al. (hereinafter Lee2, US 2020/0396678 A1) in view of Li (US 2022/0408280 A1) in view of Xu et al. (hereinafter Xu, US 2022/0272068 A1).
Regarding Claim 10, Kar-Lee2-Li-Park discloses claim 9 as set forth above.
However Kar-Lee2-Li-Park does not explicitly disclose wherein the Al service information of the terminal device is sent to the Al network element via an HTTP POST message, and the policy information fed back by the Al network element is received via an HTTP RESPONSE message.
Xu discloses wherein the service information of the terminal device is sent to the network element via an HTTP POST message (Xu: para.0125 “For example, when requesting the PCF to create an Individual Application Session Context resource, the NF service consumer shall indicate the optional features the NF service consumer supports for the Npcf_PolicyAuthorization service by including the “suppFeat” attribute in the “App SessionContextReqData” data type of the HTTP POST request.” The NF service consumer information is sent via HTTP Post information), and
the policy information fed back by the network element is received via an HTTP RESPONSE message (Xu: para.0126 “The PCF shall determine the supported features for the created Individual Application Session Context resource as specified in subclause 6.6.2 of 3GPP TS 29.500 V16.0.0. The PCF shall indicate the supported features in the HTTP response confirming the creation of the Individual Application Session Context resource by including the “suppFeat” attribute in the “App SessionContextRespData” data type.” The policy information is fed back at an HTTP response message).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Kar-Lee2-Li-Park with Xu in order to incorporate wherein the service information of the terminal device is sent to the network element via an HTTP POST message, the policy information fed back by the network element is received via an HTTP RESPONSE message, and apply this concept to the AI service information and the AI network element of Kar-Sapra-Li-Park.
One of ordinary skill in the art would have been motivated to combine because of the known benefits of the simplicity and easy of use of HTTP in data transfer (Xu: para.0125-0126).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Yang et al. US 2022/0191294 see Fig. 3 regarding registration and discovery para.0037 using HTTP get requests
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/EUI H KIM/ Examiner, Art Unit 2453
/KAMAL B DIVECHA/ Supervisory Patent Examiner, Art Unit 2453