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 Interpretation
Claims 32 and 40 discloses, “wherein the determining of the target base station comprises in response to it being determined that the UE is not present in a cell of a last known base station in an active mode, determining the target base station among the base stations comprised in the base station list according to a paging service type corresponding to the UE”, This is contingent/conditional limitation(s). The contingent/conditional limitations are not positively recited in the claim(s) and are thus only executed [or performed or implemented], when the condition is true/met.
[See, (MPEP 2111.04) II. CONTINGENT LIMITATIONS
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent is not met.]
In present claim 21 for instance determining the target base station among the base stations comprised in the base station list according to a paging service type corresponding to the UE, is only performed determined that the UE is not present in a cell of a last known base station in an active mode; otherwise, this step is not performed, and the prior art is not required to teach this element when the condition is not met.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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 non-obviousness.
Claim(s) 21-24 are rejected under 35 U.S.C. 103 as being unpatentable over Masini et al. (US 2015/0181481)(hereafter Masini) in view of Yu et al. (US 2017/0164225)(hereafter Yu).
Regarding claim 21, Masini discloses a method of operating a network server, the method comprising:
collecting mobility data of a user equipment (UE); inputting the mobility data to a neural network-based prediction model to generate a base station list comprising base stations serving a target location to which the UE is expected to move (see, para [0069], the common UE position and/or trajectory information of a UE mobility group may be used to predict a handover event and the likely target eNB(s) and target cell(s) for the handover event); and
But the does not explicitly disclose transferring the base station list to the UE.
However, in same field of endeavor, YU teaches [0043] FIG. 3 shows timing chart 300 detailing an OTDOA procedure. LPP server 130 may first transmit an OTDOA configuration (OTDOA reference cell, OTDOA neighbor cell list, PRS configuration, etc.) to UE 102 (e.g. via core network interface 132, base station 104/serving cell 104a, and wireless channel 114a). UE 102 may receive and process the OTDOA configuration in order to determine the parameters to be used in RSTD measurement and reporting. [0032] Each of base stations 104-110 may be composed of respective cells 104a-104c, 106a-106c, 108a-108c, and 110a-110c
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to combine the teachings of Yu with the Masini, as a whole, so as to transmit the base station list the UE, based on the prediction determined from mobility of the UE , the motivation is to performing reference signal measurements.
Regarding claim 22, Masini further discloses the method, wherein the mobility data comprises: at least one of:
location information on a location to which the UE has moved in an active mode in which the UE performs communication (see, para [0101] Positioning information: if location information such as GPS location or any information derived from the techniques described in section 1.6 is available to the serving eNB, or the node in charge of managing mobility groups, for some or all of the UEs included in the Mobility Group, the eNB may check whether such information provided by each of the UEs is sufficiently similar. Those UEs showing discrepancies in their location with respect to other UEs in the Mobility Group may be removed from the Mobility Group. [0102] Location information may also be used by the serving eNB, or the node in charge of managing mobility groups, to deduce the overall mobility patterns of the Mobility Group); a first elapsed time that the UE is in the active mode; and
a second elapsed time that the UE is in an idle mode in which the UE does not perform the communication.
Regarding claim 23, Masini further discloses the method, wherein the location information comprises: at least one of: identification information of the UE (see, para [0057], The first UE is having access to a first identifier, identifying the UE group in which the first UE is comprised. By "having access to" is meant that the UE has been informed of to which UE group it belongs), information on a first base station corresponding to a first location from which the UE has departed in the active mode, and information on a second base station corresponding to a second location at which the UE has arrived by moving from the first location in the active mode.
Regarding claim 24, Masini further discloses the method of claim 21, wherein the prediction model is trained to predict the base station list at least by preprocessing and inputting the mobility data (see, para [0069], the common UE position and/or trajectory information of a UE mobility group may be used to predict a handover event and the likely target eNB(s) and target cell(s) for the handover event)).
8. Claim(s) 27 is rejected under 35 U.S.C. 103 as being unpatentable over Masini and Yu and further in view of Senarath et al. (US 2014/0185581) (hereafter Senarath).
Regarding claim 27, the combined teachings do not disclose the method, wherein the prediction model is trained to predict the base stations serving the target location using mobility data sampled over a fixed time interval and the first elapsed time that the UE is in the active mode.
However, in same field of endeavor, Senarath teaches [0057], Migration probabilities may indicate the likelihood that a mobile station having a certain mobility parameter (or set of parameters) will travel from one geographic location to another over a fixed period of time. Next, the method 300 proceeds to step 330, where the network device obtains current mobility parameters for mobile stations in the wireless network. The mobility parameters may be associated with a specific instance or period in time, such as the first interval.
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to combine the teachings of Senarath with the Masini and Yu, as a whole, so as to determine the mobility parameters based on the UE movement over a fixed period of time, the motivation is to prediction the resources based on such UE mobility.
9. Claim(s) 28 is rejected under 35 U.S.C. 103 as being unpatentable over Masini and Yu and further in view of Svennebring et al. (US 2022/0303331)(hereafter Svennebring).
Regarding claim 28, the combined teachings do not disclose the method, wherein the prediction model comprises: an input layer and hidden layers comprised in deep neural network (DNN) cells; a stacked DNN configured to receive the preprocessed mobility data as input and learn spatiotemporal features of a mobility of the UE; and fully connected layers configured to output a base station list comprising a probability that the UE is at each base station from an output of the stacked DNN.
However, in same field of endeavor, Svennebring [0392], [0392] Any suitable ML model may be used for the BW prediction model 3601 and the data fusion model 3603. In one example implementation, the BW prediction model 3601 is an LTSM neural network (NN) such as an LTSM RNN, and the data fusion model 3603 is another suitable NN, which may include a convolutional NN (CNN), a deep CNN (DCN), a deconvolutional NN (DNN) teaches [0324], These predictions may be based on spatio-temporal history data associated with the UE 1511, 1521 (e.g., mobility data) and/or the current cell. The cell transition prediction layer returns data including the expected future cells the UE 1511, 1521 may visit, the expected probability of visiting each cell in a given region, a predicted time interval (or amount of time) for the UE 1511, 1521 to travel to each cell, and a predicted amount time that the UE 1511, 1521 will remain in each cell.
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to combine the teachings of DNN prediction model to predict the base station based on mobility parameters, the motivation is to predict cell/link characteristics and/or behaviors for each cell to determine a predicted link performance given the current and future cell load as well as expected deviation(s).
10. Claim(s) 31, 32, 39 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Masini et al. (US 2015/0181481)(hereafter Masini) in view of Quick, Jr et al. (US 2015/0038180)(hereafter Quick).
Regarding claims 31 and 39, Masini discloses a method of operating a user equipment (UE), the method comprising:
receiving a base station list comprising base stations serving a target location to which the UE is expected to move, predicted by the network server comprising a neural network-based trained prediction model based on the mobility data (see, para [0069], the common UE position and/or trajectory information of a UE mobility group may be used to predict a handover event and the likely target eNB(s) and target cell(s) for the handover event); and;
but does not disclose transmitting mobility data to a network server and determining a target base station to perform per-level paging of multi-level paging among the base stations comprised in the base station list; and performing the multi-level paging with the target base station.
However, in same field of endeavor, Quick teaches in Fig. 5, the mobile device, 115-d sends the mobility information or state to the network entity 505. See, para [0067], The mobile device 115-b may communicate the mobility state to a base station, e.g., the serving base station. The mobile device 115-b may receive page(s) from a subset of base stations of a paging group that are selected based on the communicated mobility state. Based on the communicated mobile state, the number of base stations of the paging group may be increased to, for example, ensure paging coverage for the mobile device 115-b along the path 205-a. [0078], The network entity 505 may determine or otherwise select a subset of base stations of a paging group based on the mobility state at 515. The network entity 505 may assign the subset of base stations to the paging group at 520 and send signals to the second base station 105-h at 525 and to the first base station 105-g at 530.
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to combine the teachings of Quick with the Masini, as a whole, so as to page the target base station after transmitting mobility data to a network server , the motivation is to perform paging area reduction based predictive mobility.
Regarding claims 32 and 40, the combined teachings further discloses the method of claim 31, wherein the determining of the target base station comprises in response to it being determined that the UE is not present in a cell of a last known base station in an active mode, determining the target base station among the base stations comprised in the base station list according to a paging service type corresponding to the UE (the prior arts, teaches all the limitations of the claim 32, the Examiner did not need to present evidence of the method steps that are not required to be performed under a broadest reasonable interpretation of the claim, See MPEP 2111.04 II. Ex parte Schulhauser).
Allowable Subject Matter
11. Claim 25-26, 29-30, 33-38 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
12. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Liu et al. (US2025/0048203) discloses detecting and reducing ping-pong handover.
Gopalkrishnan et al. (US 2024/0179671) discloses server to base station configuration of feature processing neural network for positioning.
Roeland et al. (US 2024/0015697) discloses handing paging device based on predictive model of future need to page the device.
Xue et al. (US 2020/0229128) discloses sending positioning signal.
Jain et al. (US 2020/0084569) discloses method and system for enhancement of positioning related protocols.
Xu et al. (US 2018/0159641) discloses electron device and wireless communication method in wireless communication system.
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/DHAVAL V PATEL/Primary Examiner, Art Unit 2631
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