DETAILED ACTION
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 Amendment
Claims 1 and 8-9 are amended.
Claims 5-7 are cancelled.
Claims 21-23 are newly added.
Response to Arguments
On Page 8 of the Remarks filed June 24, 2026, Applicant asserts Xin fails to disclose the request including analytics ID information. Examiner finds this argument persuasive. In light of this argument, previous claim rejections are withdrawn.
Claim Interpretation
For claims 1-4, 8, 13-15 and 18 -19, the following limitation is interpreted as a Markush group:
“the federated learning capability information of the first network element comprises at least one of the following:
type information of federated learning training supported by the first network element,
time information of federated learning training supported by the first network element, or
metadata information possessed by the first network element.”
Each member is within the same art-recognized class as a registration parameter of a capabilities request. The members are interpreted as functionally equivalent and have a common use. See MPEP § 2117.
For claims 9-12,16-17 and 20, the following limitation is interpreted as a Markush group:
“at least one of the following:
type information of federated learning training supported by the first network element or
metadata information possessed by the first network element.”
Each member is within the same art-recognized class as a discovery response parameter. The members are interpreted as functionally equivalent and have a common use. See MPEP § 2117.
If Applicant disagrees with Examiner’s interpretation, Applicant is invited to provide alternative arguments/rationale.
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.
Claims 1-4, 8, 13-15 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Xin et al. U.S. Patent Application publication 2023/0083982 in view of Yue et al. U.S. Patent Application publication 2025/0119715.
Claims 1, 13, and 18,
Xin discloses
A network element registration method, wherein the method comprises:
sending, by a first network element, a registration request to a second network element (para 0307-Step 803 The client NWDAF triggers the network element management_network element registration request service operation to the NRF network element),
wherein the registration request is used to request registration of federated learning capability information of the first network element with the second network element (para 0307), and
the federated learning capability information of the first network element comprises at least one of the following:
type information of federated learning training supported by the first network element (para 0376-supported federated learning capability information),
time information of federated learning training supported by the first network element, or
metadata information possessed by the first network element.
Xin discloses A network element, comprising a processor and a memory, wherein a program or instructions executable on the processor are stored in the memory, and when the program or the instructions are executed by the processor (para 0416-0421)
Although Xin discloses substantial limitations of the claimed invention, it fails to disclose
wherein the registration request comprises analytics identification (ID) information supported by the first network element;
wherein the analytics ID information corresponds to the federated learning capability information of the first network element.
In an analogous art, Yue discloses
wherein the registration request comprises analytics identification (ID) information supported by the first network element (para 0019-NFprofile includes support Analytics IDs);
wherein the analytics ID information corresponds to the federated learning capability information of the first network element (para 0019- disclose Analytics IDs are support the Federated Learning).
One of ordinary skill in the art before the effective filing date would find it obvious to combine the registration parameters of Yue with the Xin system to exchange capabilities between network elements to enable Federated Learning. One of ordinary skill in the art would be motivated to combine Yue and Xin to establish connections between networking devices by exchanging capabilities.
Claims 2, and 14,
wherein the type information of the federated learning training supported by the first network element comprises at least one of the following: a federated learning server capability (Xin 0376- server), or a federated learning client capability.
Xin discloses A network element, comprising a processor and a memory, wherein a program or instructions executable on the processor are stored in the memory. (para 0421-0422)
Claim 3-4 are conditional limitations not required to disclose the invention.
Claims 8, 15, and 19,
Xin discloses
A network element registration method, wherein the method comprises:
receiving, by a second network element, a registration request sent by a first network element (para 0307-Step 803 The client NWDAF triggers the network element management_network element registration request service operation to the NRF network element),
wherein the registration request is used to request registration of federated learning capability information of the first network element with the second network element (para 0307), and the federated learning capability information of the first network element comprises at least one of the following:
type information of federated learning training supported by the first network element (para 0376-supported federated learning capability information),
time information of federated learning training supported by the first network element, or
metadata information possessed by the first network element.
Xin discloses A network element, comprising a processor and a memory, wherein a program or instructions executable on the processor are stored in the memory, and when the program or the instructions are executed by the processor (para 0416-0421)
Although Xin discloses substantial limitations of the claimed invention, it fails to disclose
wherein the registration request comprises analytics identification (ID) information supported by the first network element;
wherein the analytics ID information corresponds to the federated learning capability information of the first network element.
In an analogous art, Yue discloses
wherein the registration request comprises analytics identification (ID) information supported by the first network element (para 0019-NFprofile includes support Analytics IDs);
wherein the analytics ID information corresponds to the federated learning capability information of the first network element (para 0019- disclose Analytics IDs are support the Federated Learning).
One of ordinary skill in the art before the effective filing date would find it obvious to combine the registration parameters of Yue with the Xin system to exchange capabilities between network elements to enable Federated Learning. One of ordinary skill in the art would be motivated to combine Yue and Xin to establish connections between networking devices by exchanging capabilities.
Claims are 9-11, 16-17 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over Xin et al. U.S. Patent Application publication 2023/0083982 in view of XU et al. U.S. Patent Application publication 2024/0064611.
Claims 9, 16 and 20,
Xin discloses
A model determining method, wherein the method comprises:
sending, by a third network element, a discovery request to a second network element (para 0053-a communication unit sends to a service discovery network element, a first request that requests information about a second data analytics network element,),
wherein the discovery request is used to request to discover a network element capable of federated learning training (para 0053- where the first request includes one or more of information about distributed learning and first indication information indicates a type of the second data analytics network element, and the information about distributed learning includes a type of distributed learning requested by the first data analytics network element.), the discovery request comprises first information, and the first information comprises at least one of the following:
Xin discloses A network element, comprising a processor and a memory, wherein a program or instructions executable on the processor are stored in the memory, and when the program or the instructions are executed by the processor (para 0416-0421)
Although Xin discloses substantial limitations of the claimed invention, it fails to disclose
metadata information of a network element of the federated learning training corresponding to the target task, or
network element type requirement information;
wherein the network element type requirement information is used to indicate a network element type corresponding to a to-be-discovered network element capable of federated learning training, and the network element type comprises a federated learning server network element type.
In an analogous art, XU discloses
metadata information of a network element of the federated learning training corresponding to the target task (para 0070- discloses a data format and data range).
The teaching of Xin discloses evaluating the load requirements of a federated learning client and including the load information within a discovery response in step 808. (para 0334). One of ordinary skill in the art before the effective filing date of the invention would find it obvious to apply the data requirements of XU with the Xin system to produce the predictable result of presenting the valid range of data within the discovery results. The collection of the data and presentation of the result would operate in an ordinary predictable manner.
Claim 10,
The method according to claim 9, wherein the metadata information possessed by the network element of the federated learning training corresponding to the target task comprises a data range (XU para 0070-data range).
Claim 11,
wherein after the sending, by a third network element, a discovery request to a second network element, the method further comprises:
receiving, by the third network element, a discovery response sent by the second network element (Xin para 0325- The NRF network element sends a network element discovery response to the server NWDAF, where the network element discovery response includes the first client NWDAF list.),
wherein the discovery response comprises
identification information or address information of a target network element (Xin para 0322-slice instance, vendor, DNAI), and
the target network element is a network element supporting federated learning training (Xin para 0321- The NRF network element determines the first client NWDAF list that can perform horizontal federated learning. The first client NWDAF list includes information about each client NWDAF in a client NWDAF 1 to a client NWDAF n.); and
performing, by the third network element, federated learning training along with the target network element to obtain model information corresponding to the target task (Xin para 0335-a client NWDAF is selected to perform horizontal federated learning)
Claim 17,
Xin discloses
A network element, comprising a processor and a memory, wherein a program or instructions executable on the processor are stored in the memory, and when the program or the instructions are executed by the processor. (para 0416-0421)
Although Xin discloses substantial limitations of the claimed invention, it fails to disclose
wherein the discovery response further comprises second information, and the second information comprises at least one of the following:
type information of federated learning training supported by the target network element, or
time information of federated learning training supported by the target network element.
In an analogous art, XU discloses
Obtaining for federating learning period a valid time range of local data and data format. (para 0070).
The teaching of Xin discloses evaluating the load requirements of a federated learning client and including the load information within a discovery response in step 808. (para 0334). One of ordinary skill in the art before the effective filing date of the invention would find it obvious to apply the presentation of the candidate NF information of XIN to the valid range of data of XU to produce the predictable result of presenting the valid range of data within the discovery results. The collection of the data and presentation of the result would operate in an ordinary predictable manner.
Claim 21,
The method according to claim 9, wherein the first information further comprises time information of the federated learning training corresponding to the target task (XU para 0070-time).
Claim 22,
The method according to claim 9, wherein the network element type further comprises a federated learning client network element type (XU para 0070-time).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Xin et al. U.S. Patent Application publication 2023/0083982 in view of XU et al. U.S. Patent Application publication 2024/0064611 in view of Puente Pestaña et al. U.S. Patent publication 12,664,465.
Claim 12,
Although Xin/XU discloses substantial limitations of the claimed invention, it fails to disclose
wherein the discovery response further comprises second information, and the second information comprises at least one of the following:
type information of federated learning training supported by the target network element, or
time information of federated learning training supported by the target network element.
In an analogous art, Puente Pestaña discloses
type information of machine learning algorithm supported by the first data entities (Col 11, lines 42-55)
One of ordinary skill in the art before the effective filing date of the invention would find it obvious to apply the inclusion of the capabilities of the discovered entities within the discovery response of Puente Pestaña to the federated learning discovery of Xin/Xu system to produce the predictable result of providing the federated learning capability type within discovery responses.
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Xin et al. U.S. Patent Application publication 2023/0083982 in view of Yue et al. U.S. Patent Application publication 2025/0119715 in view of XU et al. U.S. Patent Application publication 2024/0064611.
Claim 23,
Although Xin/Yue discloses substantial limitations of the claimed invention, it fails to disclose
The method according to claim 8, wherein the metadata information possessed by the first network element comprises a data range.
In an analogous art, XU discloses
The method according to claim 8, wherein the metadata information possessed by the first network element comprises a data range. (para 0070)
One of ordinary skill in the art before the effective filing date would find it obvious to combine the request constraints of XU with the XIN/Yue system to produce the predictable result of limiting request results based on request requirements.
Conclusion
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/SCHQUITA D GOODWIN/Primary Examiner, Art Unit 2459
/JMC/Examiner, Art Unit 2459
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