DETAILED ACTION
This Office action is in response to the application filed on 19 September 2024.
Claims 1-20 are presented for examination.
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.
the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because Independent claim 20 is directed to “the products that do not have physical or tangible form, such as information (often referred to as “data per se”) or a computer program per se (often referred to as “software per se”) when claimed as a product without any structural recitations” (MPEP 2601.03, subsection I).
The amended element of “A computer program stored in non-transitory computer readable medium comprising a set of instructions, which, when executed by an apparatus, cause the apparatus to perform the method of constructing a graph representing a communication network, the communication network comprising: ...” in independent claim 20 would overcome said 35 USC 101 issue.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipate by SALAUN et al. WO 2024/110042 A1. .
The applied reference has a common assignee with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
As to claim 1, SALAUN discloses substantially the invention as claimed, including an apparatus (Figures 1, 8, the power allocation apparatus 110/9000), comprising:
at least one processor (Figures 1, 8, the processor 9010); and
at least one memory (Figures 1, 8, the memory 9020) including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform operations comprising:
constructing a graph representing a communication network (Figure 1, communication network 100) (Figures 2, 4, and associated paragraphs, step 210), the communication network comprising a plurality of User Equipments (Figure 4, the _____ solid line for UE-type edges) and a plurality of access points (Figure 4, the ----------- broken line for AP-type edges), wherein the graph comprises a plurality of nodes and at least one edge connecting two nodes of the plurality of nodes, wherein each node represents a communication link between one user equipment of the plurality of User Equipments and one Access Point of the plurality of access points (Figures 1-4 and associated paragraphs), and wherein the edge represents an activity status of the two communication links represented by said two nodes (Figures 1-4 and associated paragraphs);
processing the graph through a graph neural network (Figure 2, and associated paragraphs, step 220) to determine a power control parameter (a power control coefficient) for the access point associated with at least one node of the plurality of nodes (Figures 2, 4, and associated paragraphs, step 220), and
transmitting the determined power control parameter to the access point associated with the at least one node (Figures 2, 4, and associated paragraphs, step 230).
As to claim 2, SALAUN discloses, wherein each node indicates a state of the associated communication link (Figures 2, 4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [3], [79]).
As to claim 3, SALAUN discloses, wherein each node stores a large-scale fading coefficient for the associated communication link (Figures 2, 4, and associated paragraphs, [43]).
As to claim 4, SALAUN discloses, wherein each node is classified as either: an active node, if the node represents an active communication link, or an inactive node, if the node represents an inactive communication link (Figures 2, 4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [3], [79])..
As to claim 5, SALAUN discloses, wherein the graph comprises a plurality of edges, and wherein each edge connects two nodes of the plurality of nodes and represents the activity status of the two communication links represented by said two nodes (Figures 1-4 and associated paragraphs).
As to claim 6, SALAUN discloses, wherein the activity status of the communication links represented by said two nodes are encoded in an edge attribute of the edge using a one-hot encoding scheme (Figures 2, 4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [3], [79])..
As to claim 7, SALAUN discloses, wherein each edge is classified as either: an access point type edge, if said edge connects two nodes associated with a same access point, or a user equipment type edge, if said edge connects two nodes associated with a same user equipment (Figures 2, 4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [3], [79]).
As to claim 8, SALAUN discloses, wherein processing the graph through the graph neural network comprises providing the graph and a target metric to the graph neural network (Figures 2-4, and associated paragraphs, [94]-[96], [79]).
As to claim 9, SALAUN discloses, wherein the operations further comprise: detecting a change in the communication network; evaluating whether the target metric is achieved for the plurality of user equipments; if the target metric is not achieved, updating the graph (Figures 2-4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [94]-[96], [79]).
As to claim 10, SALAUN discloses, wherein the change in the communication network comprises one or more of: an addition or suppression of a user equipment, an addition or suppression of an access point, a change of the state of at least one of the communication links, or a change of the target metric (Figures 2-4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [94]-[96], [79])..
As to claim 11, SALAUN discloses, wherein the operations further comprise: training the graph neural network on a training set comprising one or more sets of power coefficients determined using second order cone programming (Figures 2-4, and associated paragraphs, as the environment changes, and as the number of active UEs and serving APs changes, [94]-[96], [104]-[107]).
As to claim 12, SALAUN discloses, wherein the graph neural network comprises a multi-headed attention mechanism that captures a level of dependence between at least two of the user equipments or two of the access points, wherein the level of dependence is based one or more of: a relative geographic location and a respective state of the associated communication link (Figures 2-4, and associated paragraphs, [82]-[90], [94]-[102], [103]-[111]).
As to claim 13, SALAUN discloses, wherein the operations further comprise: determining, using a differentiable function of the graph neural network, an association between the plurality of user equipments and the plurality of access points, wherein the determining of the association comprises determining the activity status of at least one of the communication links (Figures 2-4, and associated paragraphs, [82]-[90], [95]-[102], [103]-[111]).
As to claim 14, SALAUN discloses, wherein the operations further comprise: repeating the determining of the association together with the determining of the power control parameter until the target metric is achieved (Figures 2-4, and associated paragraphs, 82]-[90], [95]-[102], [103]-[111]).
Claims 15,16,17,18,19 correspond to the method claims of the apparatus claims 1,3,4,5,9; therefore, they are rejected under the same rationale as in claims 1,3,4,5,9 shown above.
Claim 20 corresponds to the [[non-transitory]] computer-readable medium claim of the apparatus claim 1; therefore. It is rejected under the same rationale as in apparatus claim 1 shown above.
The prior art cited in this Office Action is : SALAUN et al. WO 2024/110042 A1.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAI V NGUYEN whose telephone number is (571)272-3901. The examiner can normally be reached M-F 6:00AM -3:30PM.
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, Kevin Pan can be reached at 571-272-7855. 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.
/HAI V NGUYEN/Primary Examiner, Art Unit 2649
Prosecution Insights