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 Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 is rejected under 112 second paragraph since claim 1 recited in optional format (i.e “such that” and “can be” at line 8 in claim 1) and not a positive recitation. Words “such as, such that, may, might, can, could, in case, when, potentially, possibly” are optional language and do not narrow claim limitations (In re Johnston, 77 USPQ2d 1788 (Fed Cir 2006)).
Claims 3-18 are rejected under 112 second paragraph since claims 3-18 are dependent on claim 1.
Claim Rejections - 35 USC § 103
1. 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 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.
2. 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 of this title, 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.
3. Claim 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Publication No US 2021/0158151 to Wang et al. (hereinafter Wang) in view of U.S. Publication No US 2022/0108014 to Schiffman et al. (hereinafter Schiffman) in view of U.S. Publication No US 2022/0400371 to Elshafie et al. (hereinafter Elshafie)
As to claim 19, Wang discloses a method of artificial intelligence (AI) setting within a communication system with a base station and several user equipments (UEs), the method comprising:
reporting, by each of the several user equipments, an artificial intelligence parameter for universal communications identifier (UCI) capabilities to the base station (Wang; [0168]; Fig.13:1305 shows and discloses plurality of UEs reports metric and capability information to a base station using machine-learning architectures. [0158] discloses machine-learning architectures for broadcast and multicast communications. In implementations, a network entity determines a configuration of a deep neural network (DNN) for processing broadcast or multicast communications transmitted over a wireless communication system, where the communications are directed to a targeted group of user equipments (UEs));
grouping, by the base station, the user equipments into groups based on the artificial intelligence parameter for the universal communications identifier capabilities (Wang; [0168]; Fig.13:1305 shows and discloses plurality of UEs reports metric and capability information to a base station using machine-learning architectures. [0158] discloses machine-learning architectures for broadcast and multicast communications. In implementations, a network entity determines a configuration of a deep neural network (DNN) for processing broadcast or multicast communications transmitted over a wireless communication system, where the communications are directed to a targeted group of user equipments (UEs));
Wang discloses wherein the user equipments are grouped by the base station, but fails to disclose wherein UEs report universal communications identifier capabilities. However, Schiffman discloses
wherein the user equipments are grouped by the base station based on the universal communications identifier capabilities (Schiffman; [0044] discloses the remote party 302 may obtain information regarding the capabilities of each of the computing devices 300a-d from the attestation, as well as potentially being able to obtain the identity of each of the computing devices 300a-d and their individual capabilities from the attestation. Information regarding the capabilities may be conveyed by the attestation in the form of an indicator or Universal Resource Identifier (URI) to more complete information about the capability).
It is obvious for a person of ordinary skilled in the art to combine the teachings before the effective filing date of the invention. One would be motivated to combine the teachings in order to report more complete information about the capability.
Wang- Schiffman discloses a base station sending information to a plurality of UEs, but fails to disclose multicasting, by the base station, a respective artificial intelligence configuration to each group of user equipments separately in dependency of the artificial intelligence parameter for the universal communications identifier capabilities of the respective group. However, Elshafie discloses
multicasting, by the base station, a respective artificial intelligence configuration to each group of user equipments separately in dependency of the artificial intelligence parameter for the universal communications identifier capabilities of the respective group (Elshafie; [0074] discloses each UE may transmit, to the base station, information that indicates whether the respective UE has a capability to support machine learning algorithms. one or more UEs may have a capability to perform one or more tasks in a machine learning mode. Accordingly, because a UE generally needs to support machine learning algorithms in order to participate in federated learning, each UE may signal machine learning or federated learning capabilities to the base station (e.g., using radio resource control (RRC) signaling and/or a medium access control (MAC) control element (MAC-CE). For example, as described herein, the machine learning or federated learning capabilities may at least indicate whether a UE supports machine learning and/or federated learning algorithms. Furthermore, in some aspects, the machine learning or federated learning capabilities may vary over time for a particular UE (e.g., a UE may indicate support for machine learning algorithms when the UE is willing to participate in federated learning because the UE has computational resources available for local training, and may indicate that machine learning algorithms are unsupported at other times when the UE may be unwilling to participate in federated learning. [0079]-[0080] discloses the base station may transmit, and the UEs may receive, configuration information that indicates one or more tasks to be performed in the machine learning mode or the non-machine learning mode. For example, UEs that lack support for machine learning algorithms may be configured to perform wireless communication tasks and/or other suitable tasks in the non-machine learning mode only, and UEs that support machine learning algorithms may be configured to perform wireless communication tasks and/or other suitable tasks in the machine learning mode or the non-machine learning mode. The base station may configure the same set of CSI-RS resources and/or SRS resources to be used for channel sounding in the machine learning mode and the non-machine learning mode, or the base station may configure different CSI-RS resources and/or SRS resources to be used for channel sounding in the machine learning mode and the non-machine learning mode. In either case, the base station and the UE may coordinate which CSI-RS and/or SRS resources are to be used in each mode)
It is obvious for a person of ordinary skilled in the art to combine the teachings before the effective filing date of the invention. One would be motivated to combine the teachings in order to use machine learning mode or non-machine learning mode by a group of UEs based on the information received from a base station and thus use the limited resources in an effective way.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/FAISAL CHOUDHURY/Primary Examiner, Art Unit 2478
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