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 .
Claim Objections
As to claim 26, the term “its” is ambiguous and should be amended to directly reference the “cluster head” if that is what is being referred to by the term “its.”
As to claim 44, the term “its” is ambiguous and should be amended to directly reference the “cluster head” if that is what is being referred to by the term “its.”
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 26, 30, 32, 33, and 35-44 are rejected under 35 U.S.C. 103 as being unpatentable over Non-Patent Literature Document Citation No. 2 (hereafter referred to as “Hosseinalipour”) from the information disclosure statement filed on 8/27/24, in view of BALEVI et al. (hereafter referred to as “Balevi”), U.S. Patent No. 2023/0180152 A1.
As to claim 26, Hosseinalipour discloses a method for performing an iterative learning process (Pg. 41, § “FEDERATED LEARNING”, “The local learning at each device typically consists of gradient descent iterations to update the model”) with agent entities (Pg. 41, § “FEDERATED LEARNING,” “Local learning, in which each worker device updates the parameters of the ML model (e.g., weights on neurons) using its collected dataset”, wherein each worker device may be interpreted as an agent or the software required to operate the worker device in the manner described may be interpreted as an agent), the method being performed by a server entity (Pg. 41, § “FEDERATED LEARNING,” “Global aggregation, in which a main server determines the new global model from the local updates and synchronizes the devices with this aggregated version”), the method comprising:
partitioning the agent entities into clusters with one cluster head per each of the clusters (Pg. 45, Fig. 4; Pg. 46, right column, § “Block-Based Learning”, wherein the head node(s) are cluster head(s) and organized into clusters of the devices);
configuring the agent entities to, as part of performing the iterative learning process (Pg. 41, § “FEDERATED LEARNING”, “The local learning at each device typically consists of gradient descent iterations to update the model”), use over-the-air transmission (Pg. 44, right column, § “HYBRID LEARNING: VERTICAL AND HORIZONTAL COMMUNICATIONS”, ¶ 3, “Considering again the structure in Fig. 2, fog learning would intelligently cluster the devices in the bottom-most layer such that each cluster has the potential to form a wireless ad-hoc network for parameter sharing or data offloading. Similarly, the upper layers will be clustered such that the computing nodes in each layer are capable of communicating for parameter sharing, in some cases via low-latency wired connections (e.g., multiple local edge servers connected via fiber in a metropolitan area) and in other cases over the air (e.g., UAVs).”);
configuring the cluster head of each cluster to, as part of performing the iterative learning process: aggregate the local updates received from the agent entities within its cluster, and use unicast digital transmission for communicating aggregated local updates to the server entity (Pg. 44, right column, ¶ 4, “In Fig. 4, we represent the fog learning network architecture as a logical tree graph, the leaves of which are the edge devices and the root of which is the main server. Fog learning is a hybrid learning methodology which leverages horizontal communications among nodes in addition to vertical parameter transfers between the layers.”, Pg. 45, Fig. 4; Pg. 46, right column, § “Block-Based Learning”, wherein the head node(s) are cluster head(s) and have an aggregation frequency for vertical updates to the root server); and
performing at last one iteration of the iterative learning process with the agent entities and the cluster heads according to the configuration (Pg. 41, § “FEDERATED LEARNING”, “The local learning at each device typically consists of gradient descent iterations to update the model”; Pg. 45, Fig. 4; Pg. 46, right column, § “Block-Based Learning”, wherein the head node(s) are cluster head(s) and organized into clusters of the devices).
Hosseinalipour is silent on direct analog modulation.
However, Balevi discloses direct analog modulation (¶ [0035], “The federated learning component 140 may include a transmitting component 148 configured to transmit an amplitude modulated analog signal to the parameter server for each of the plurality of values.”).
It 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 to modify the teachings of Hosseinalipour in the aforementioned manner as taught by Balevi in order to utilize the existing structure for wireless transmission and a well-known means of doing so.
As to claim 30, Hosseinalipour is silent on wherein each of the agent entities is provided in a respective user equipment, and wherein the agent entities are partitioned into the clusters based on estimated pathloss values between pairs of the user equipment.
However, Balevi discloses wherein each of the agent entities is provided in a respective user equipment, and wherein the agent entities are partitioned into the clusters based on estimated pathloss values between pairs of the user equipment (¶ [0066], “In an aspect, the base station 402 and/or the parameter server component 120 may divide the UEs 404 into one or more groups based on a common received power property for each group. Example received power properties may include pathloss or power budget. A common received power property may refer to properties that are substantially the same or within a range. For example, the base station 402 and/or the parameter server component 120 may place UE 404a and UE 404b in a first group 410. For instance, the UE 404a and UE 404b may have similar pathloss, e.g., because they are approximately the same distance from the base station 402 or experience similar channel conditions.”).
It 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 to modify the teachings of Hosseinalipour in the aforementioned manner as taught by Balevi in order to group devices by common properties for proper organization and utilization.
As to claims 32 and 33, the claims are rejected for reasons similar to those given for claim 30 above.
As to claim 35, Hosseinalipour is silent on wherein, within each of the clusters, the agent entity of the user equipment having lowest maximum estimated pathloss to the other user equipment of the agent entities within the same cluster is selected as cluster head.
However, Balevi discloses wherein, within each of the clusters, the agent entity of the user equipment having lowest maximum estimated pathloss to the other user equipment of the agent entities within the same cluster is selected as cluster head (¶ [0117]).
It 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 to modify the teachings of Hosseinalipour in the aforementioned manner as taught by Balevi in order to ensure a device with acceptable pathloss is placed in charge of transmission.
As to claims 36-39, the claims are rejected for reasons similar to those given for claim 35 above.
As to claim 40, Hosseinalipour discloses wherein the server entity is provided in any of: an access network node, a core network node, an Operations, Administration and Maintenance node, a Service Management and Orchestration node (Pg. 41, left column, § “INTRODUCTION”, ¶ 1, “Fog computing is an emerging architecture which aims to orchestrate and manage processing resources across nodes in the cloud-to-things continuum, encompassing the cloud, core, metro, edge, clients, and things”).
As to claims 41-44, the claims are rejected for reasons similar to those given for claim 26 above.
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Hosseinalipour and Balevi as applied above, and further in view of Okuyama et al. (hereafter referred to as “Okuyama”), U.S. Patent App. Pub. No. 2019/0082354 A1.
As to claim 27, the combination of Hosseinalipour and Balevi disclose wherein at least two of the clusters are assigned (See the rejection of claim 26 above).
Hosseinalipour and Balevi are silent on mutually orthogonal transmission resources.
However, Okuyama discloses mutually orthogonal transmission resources (¶¶ [0051] and [0077]).
It 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 to modify the teachings of Hosseinalipour and Balevi in the aforementioned manner as taught by Okuyama in order to gain the benefits of orthogonal transmission such as enhanced noise reduction.
Claim 31 is rejected under 35 U.S.C. 103 as being unpatentable over Hosseinalipour and Balevi as applied above, and further in view of KARJALAINEN et al. (hereafter referred to as “Karjalainen”), U.S. Patent App. Pub. No. 2021/0105725 A1.
As to claim 31, Hosseinalipour and Balevi are silent on wherein the estimated pathloss values are estimated based on in which beams the user equipment are served by a network node, and wherein the pathloss value of a first pair of user equipment served in the same beam is lower than the pathloss value of a second pair of user equipment served in different beams.
However, Karjalainen discloses wherein the estimated pathloss values are estimated based on in which beams the user equipment are served by a network node, and wherein the pathloss value of a first pair of user equipment served in the same beam is lower than the pathloss value of a second pair of user equipment served in different beams (¶ [0025]).
It 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 to modify the teachings of Hosseinalipour and Balevi in the aforementioned manner as taught by Karjalainen in order to mitigate uplink interference.
Allowable Subject Matter
Claims 28, 29, and 34 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: the prior art fails to teach or reasonably suggest the invention as claimed. This is not a statement that any one limitation in a vacuum is allowable subject matter, but rather that the combination of the claim limitations as a whole are not obvious over the prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Brian Whipple whose telephone number is (571)270-1244. The examiner can normally be reached Mondays-Fridays from 9:30 AM to 3:30 PM ET and Saturdays from 10:30 AM to 8:30 PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Joon Hwang can be reached at (571)272-4036. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Brian Whipple/
Primary Examiner
Art Unit 2447
1/27/26