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 .
Claims 1-20 are presented for examination.
Claim Rejections - 35 USC § 102
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 1-3, 11-13, 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by You et al. U.S. Patent Application Publication Number 2024/0114408 A1 (hereinafter You).
As per claims 1, 11, 20, You discloses an artificial intelligence (AI) model information transmission method (see step 306 network device transmit the first information, or AI model information as claimed, to the terminal on page 4 section [0101] and Figure 3), comprising:
sending, by a first communication device, first AI model information to a second communication device (see step 306 network device, or first communication device as claimed, transmit the first information, or AI model information as claimed, to the terminal, or second communication device as claimed, on page 4 section [0101] and Figure 3), wherein the first AI model information is used to indicate a first AI model and/or related information of the first AI model (see network device trains or learns the input information based on a first AI model to obtain the first information on page 4 section [0089]), and the first AI model is an AI model stored in a user equipment (UE) (see network device trains or learns the input information based on a first AI model to obtain the first information, or first AI model stored on the first device as claimed, on page 4 section [0089]);
wherein the first communication device is the UE, and the second communication device is a communication peer end of the UE (see source cell on page 3 section [0053] and see random access target cell on page 3 section [0040] are all communication peer ends as claimed, capable of performing handovers such as selecting a random target cell on page 3 section [0025]); or
the first communication device is a source cell in a handover for the UE (see first information is a handover command on page 4 section [0093]), and the second communication device is a target cell in the handover for the UE (see command to instructing handover from a serving cell to a target cell on page 4 section [0094]); or
the first communication device is a historical access cell (see source cell, or historical access cell as claimed, in at RRC cell handover on page 3 section [0053]) in a radio resource control (RRC) resume procedure of the UE (see Radio Resource Control RRC messaging for condition handover on page 3 section [0053]), and the second communication device is a new access cell in the RRC resume procedure of the UE (see conditional handover to random target network device that fits the trigger condition on page 3 section [0052]).
As per claims 2, 12, You discloses the AI model information transmission method according to claim 1, wherein the first AI model information comprises at least one of the following: a model identifier of the first AI model, used to uniquely identify the first AI model; a model functionality of the first AI model; a model applicable condition for the first AI model; a model activation state of the first AI model; a model size of the first AI model; model authentication information of the first AI model, used for the second communication device to identify or authenticate the first AI model; or model structural information of the first AI model (see first information including measurement configuration including neighbor cells, frequency points, time, and frequency, or application condition as claimed, on page 4 section [0096] and see first information including configuration of the target cell such as identifier of the target cell and system information of the target cell on page 4 section [0098]).
As per claims 3, 13, You discloses the AI model information transmission method according to claim 2, wherein the model applicable condition comprises at least one of the following: an applicable area; an applicable time; an applicable configuration; or an applicable channel environment parameter (see first information including measurement configuration including neighbor cells, frequency points, time, frequency on page 4 section [0096] see first information including configuration of the target cell such as identifier of the target cell and system information of the target cell on page 4 section [0098]).
Allowable Subject Matter
Claims 4-10, 14-19 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kumar et al. U.S. Patent Application Publication Number 2023/0403588 A1. Machine learning associated with model ID, machine learning function, machine learning use case and report data (see Abstract).
Geng et al. U.S. Patent Application Publication Number 2023/00422124 A1. Cell handover method with predicted serving cell (see Abstract).
Madadi U.S. Patent Application Publication Number 2022/0286927 A1. BS sending configuration information about AI/ML to UE (see section [0139] and Figure 6).
Li et al. U.S. Patent Application Publication Number 2024/0205781 A1. User equipment trajectory assisted handovers including AI to predict UE location information (see Abstract).
Echigo et al. U.S. Patent Application Publication Number 2025/0158765 A1. Channel state information CSI report (see Abstract).
Echigo et al. U.S. Patent Application Publication Number 2025/0350539 A1. BS and UE exchange information for AI model identification (see section [0121]).
Zhu et al. U.S. Patent Application Publication Number 2023/0100253 A1. User equipment request for a machine learning configuration for a network based neural network model (see section [0133]).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALAN S CHOU whose telephone number is (571)272-5779. The examiner can normally be reached Monday-Friday 9:00-5:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chris L Parry can be reached at (571)272-8328. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALAN S CHOU/Primary Examiner, Art Unit 2451
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