DETAILED ACTION
Response to Arguments
1. Applicant's arguments filed 12 April 2026 have been fully considered but they are not persuasive.
Applicant asserts, on pages 11-12 of Remarks, that “According to the cited passages of Liu, the determination of a target cell is based on LIPA capability information and a priority list that is obtained via a "scanning unit" configured to scan broadcast information. In Liu's teachings, the priority list is a pre-existing entity determined by network configuration or broadcasted rules. In contrast, claim 1 recites "receiving a measurement report transmitted by a user equipment (UE) instructing the UE to execute a handover procedure to handover to the handover target and obtaining a handover result; obtaining handover parameters according to the handover result; and training a handover model according to the measurement report, the handover parameters and neighborhood information to update the handover priority list". While Liu is merely "checking" or "scanning" for a pre-configured list from broadcast messages via a scanning unit, the present invention is dynamically generating and refining the list through a machine-learning model that learns from procedural failures such as cancellations. Furthermore, Liu focuses on determining a target cell based on LIPA capability and the pre-existence of a priority list in broadcast information, providing no teaching or suggestion to update or train a list based on AI-processed handover results. This distinction highlights that the rule-based scanning taught by Liu is fundamentally different from what is recited in claim 1.”
On the contrary, the limitation in question, “determining the handover target according to the handover priority list;” merely requires that a handover target be determined using a handover priority list. There is no requirement in this limitation for “dynamically generating and refining the list through a machine-learning model that learns from procedural failures such as cancellations” or to “update or train a list based on AI-processed handover results”. Liu reads, at page 2 lines 32-39: “In the embodiment of the present invention, determining the target cell for handover according to the LIPA capability information includes: determining whether there is a handover priority list; and if the determination result is yes, according to the handover priority list, and the LIPA capability information determines a target cell for handover. In the embodiment of the present invention, determining the target cell for handover according to the handover priority list and the LIPA capability information includes: determining that a cell with a high priority is the target cell when the LIPA capability is supported.” [emphasis added]. Clearly, Liu discloses the limitation determining the handover target according to the handover priority list;”.
Applicant asserts, on page 12 of Remarks, that “Next, while the Examiner asserts that combining references Mach, Liu and Yoon would increase "efficiency" and "stability," the technical objectives of the cited references are logically incompatible with one another. Specifically, the primary objective of Liu is to ensure that a UE connects to a cell with specific LIPA capabilities, such as local network IDs or LGW addresses, which is a protocol-level access requirement. In contrast, the objective of Mach is to minimize RSRP coverage misalignment through physical layer optimization based on signal strength differences. Because these references address fundamentally different technical problems-local network access versus signal alignment-a person of ordinary skill in the art would find their combination technically inconsistent rather than a means to increase efficiency and stability. In other words, a person skilled in the art would not be motivated to feed a Layer 3 procedural "cancellation count" (from Yoon) into an RSRP-based signal optimization model (from Mach) to update a list that is supposed to be scanned from broadcast info (from Liu). Such a combination would disrupt the specialized control loops of each individual reference without a predictable technical gain in stability.”
In response to applicant's argument that the secondary and tertiary references are incompatible with the primary reference and each other, the test for obviousness is not whether the features of a secondary or tertiary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
Applicant asserts, on pages 12-13 of Remarks, that “Furthermore, none of the cited references, whether considered alone or in combination, teaches or suggests the specific functional sequence of executing a handover, obtaining cancellation results, training an AI model based on those results, and subsequently updating a priority list. Specifically, Mach lacks the requisite target selection logic, while Liu lacks an AI-driven update mechanism for its scanned broadcast lists, and Yoon fails to provide any teaching for a model-training application using its statistical parameters. This unique integrated feedback loop remains absent from the prior art, as the cited references do not suggest utilizing procedural cancellation data to drive a machine-learning model for the purpose of dynamically re-ranking handover targets.”
On the contrary, as outlined in the rejections of the independent claims, the primary reference, Mach discloses this functional sequence, sans the requirement that the claimed handover parameters comprise handover cancellations, which is disclosed by Yoon. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Claim Rejections - 35 USC § 103
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, 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. 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.
4. Claims 1, 6, 11, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Mach et al., U.S. Patent Application Publication 2022/0386206 (hereinafter Mach), in view of Liu, WO 2016086624 A1 (hereinafter Liu), further in view of Yoon et al., KR 20100063271 A (hereinafter Yoon).
Regarding claim 1, Mach discloses a method for determining a handover target (disclosed is a method wherein a network determines a second cell for a UE to handover to from a first cell, according to Abstract, [0087], [0118]), comprising:
receiving a measurement report transmitted by a user equipment (UE) (the network receives a measurement report transmitted by the UE, according to [0185], Fig. 7A [step 705]);
obtaining a handover priority list according to the measurement report (after receiving the measurement report, the network identifies idle state parameters required for cell reselection evaluation, according to [0186], Fig. 7A [step 706], whereby said idle state parameters include inter-RAT cell reselection priorities that the network controls based on UE cell measurements, according to [0072], [0107], Table 1);
instructing the UE to execute a handover procedure to handover to a handover target and obtaining a handover result (the network configures periodic serving and neighbor cell measurement reporting in the UE, as part of a handover procedure, whereby the network obtains an RSRP_difference value based on reported RSRP measurements and an emulated cell reselection evaluation, according to [0187]-[0195], Figs. 7A-7B, [steps 707-715]);
obtaining handover parameters according to the handover result (the network obtains updated cell reselection/handover parameters based on the result of the handover evaluation, according to [0196]-[0198], Fig. 7B [steps 716-718]); and
training a handover model according to the measurement report, the handover parameters and neighborhood information to update the handover priority list (an AI cell reselection algorithm is trained, based on RSRP_difference values reported from various UEs, and based on cell reselection and handover parameters, according to [0142]-[0148], [0196]).
Mach does not expressly disclose determining the handover target according to the handover priority list, nor that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
Liu discloses determining the handover target according to the handover priority list (a target cell for handover is determined according to a handover priority list, according to page 2 lines 32-39).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach with Liu by determining the handover target according to the handover priority list.
One of ordinary skill in the art would have been motivated to make this modification in order to facilitate a high efficiency handover that has reduced resource consumption and signaling overhead and has increased speed (Liu: page 2 lines 4-20).
Neither Mach nor Liu expressly discloses that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
Yoon discloses that the handover parameters at least comprise handover attempts, handover success and handover cancellations (handover statistics information includes a handover attempt count, a handover success count, and a handover cancel count, according to page 6 lines 25-33).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu with Yoon such that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
One of ordinary skill in the art would have been motivated to make this modification in order to increase the stability of operation of a neighbor base station (Yoon: page 3 lines 23-28).
Regarding claim 6, Mach discloses a method for determining a handover target (disclosed is a method wherein a network determines a second cell for a UE to handover to from a first cell, according to Abstract, [0087], [0118]), comprising:
training a handover model according to handover data (an AI cell reselection algorithm is trained, based on RSRP_difference values reported from various UEs, and based on cell reselection and handover parameters, according to [0142]-[0148], [0196]);
generating a handover priority list using the handover model according to a measurement report and neighborhood information when receiving the measurement report transmitted by a user equipment (UE) (after receiving a measurement report from the UE, the network identifies idle state parameters required for cell reselection evaluation, according to [0186], Fig. 7A [step 706], whereby said idle state parameters include inter-RAT cell reselection priorities that the network controls based on UE cell measurements, according to [0072], [0107], Table 1);
instructing the UE to execute a handover procedure to handover to a handover target and obtaining a handover result (the network configures periodic serving and neighbor cell measurement reporting in the UE, as part of a handover procedure, whereby the network obtains an RSRP_difference value based on reported RSRP measurements and an emulated cell reselection evaluation, according to [0187]-[0195], Figs. 7A-7B, [steps 707-715]);
obtaining handover parameters according to the handover result (the network obtains updated cell reselection/handover parameters, such as Qoffset, based on the result of the handover evaluation, according to [0196]-[0198], Fig. 7B [steps 716-718]); and
updating the handover priority list using the handover model according to the measurement report, the neighborhood information and the handover parameters (an optimized cell reselection/handover parameter value is updated based on the measurements of the serving cell and neighbor cells, according to [0198], Fig. 7B [step 718], whereby cell reselection ranks are a function of cell reselection/handover parameter values, such as Qoffset, according to Table 1).
Mach does not expressly disclose determining the handover target according to the handover priority list, nor that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
Liu discloses determining the handover target according to the handover priority list (a target cell for handover is determined according to a handover priority list, according to page 2 lines 32-39).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach with Liu by determining the handover target according to the handover priority list.
One of ordinary skill in the art would have been motivated to make this modification in order to facilitate a high efficiency handover that has reduced resource consumption and signaling overhead and has increased speed (Liu: page 2 lines 4-20).
Neither Mach nor Liu expressly discloses that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
Yoon discloses that the handover parameters at least comprise handover attempts, handover success and handover cancellations (handover statistics information includes a handover attempt count, a handover success count, and a handover cancel count, according to page 6 lines 25-33).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu with Yoon such that the handover parameters at least comprise handover attempts, handover success and handover cancellations.
One of ordinary skill in the art would have been motivated to make this modification in order to increase the stability of operation of a neighbor base station (Yoon: page 3 lines 23-28).
Claim 11 recites a device, comprising one or more processors, and one or more computer storage media for storing one or more computer-readable instructions, wherein the processor is configured to drive the computer storage media (the network disclosed by Mach necessarily comprises one or more processors and one or more computer storage media that store computer-readable instructions that are executed by the one or more processors) to perform the method recited in claim 1, and is therefore rejected on the same grounds as claim 1.
Claim 16 recites a device, comprising one or more processors, and one or more computer storage media for storing one or more computer-readable instructions, wherein the processor is configured to drive the computer storage media (the network disclosed by Mach necessarily comprises one or more processors and one or more computer storage media that store computer-readable instructions that are executed by the one or more processors) to perform the method recited in claim 6, and is therefore rejected on the same grounds as claim 6.
5. Claims 2, 7, 12, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Mach in view of Liu in view of Yoon as applied to claims 1, 6, 11, and 16 above, further in view of Thomas et al., U.S. Patent Application Publication 2023/0305099 (hereinafter Thomas).
Regarding claim 2, the combination of Mach, Liu, and Yoon discloses all the limitations of claim 1. Additionally, Mach discloses that the measurement report comprises signal references, and the signal references at least comprise: a Signal to Interference-plus-noise Ratio (SINR), a Received Signal Strength Indication (RSSI), and a Reference Signal Receiving Power (RSRP) (the reported cell measurements include measurements of SINR, RSSI, and RSRP, according to [0063]-[0067]).
Neither Mach, Liu, nor Yoon expressly discloses that the signal references at least comprise: a user equipment address, a Side-link Channel Occupancy Ratio and a Side-link Channel Busy Ratio.
Thomas discloses that the signal references at least comprise: a user equipment address, a Side-link Channel Occupancy Ratio and a Side-link Channel Busy Ratio (measurement report information comprises UE ID, SL Channel Occupancy Ration, and SL Channel Busy Ratio, according to [0190], Table 7).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu as modified by Yoon with Thomas such that the signal references at least comprise: a user equipment address, a Side-link Channel Occupancy Ratio and a Side-link Channel Busy Ratio.
One of ordinary skill in the art would have been motivated to make this modification in order to facilitate sidelink positioning (Thomas: [0004]-[0008]).
Claims 7, 12, and 17 do not differ substantively from claim 2, and are therefore rejected on the same grounds as claim 2.
6. Claims 3, 8, 13, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Mach in view of Liu in view of Yoon as applied to claims 1, 6, 11, and 16 above, further in view of Sillanpaa et al., U.S. Patent Application Publication 2019/0394683 (hereinafter Sillanpaa).
Regarding claim 3, the combination of Mach, Liu, and Yoon discloses all the limitations of claim 1.
Neither Mach, Liu, nor Yoon expressly discloses that the handover parameters further comprise network reasons.
Sillanpaa disclose that the handover parameters further comprise network reasons (handover parameters include cancelled handovers and the associated network reason, and successful handovers and the associated network reason, according to Tables 5 and 6).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu as modified by Yoon with Sillanpaa such that the handover parameters at least comprise handover attempts, handover success, handover cancellations, and network reasons.
One of ordinary skill in the art would have been motivated to make this modification in order to improve the quality of handovers and statistics for call sessions that move between RANs (Sillanpaa: [0015]).
Claims 8, 13, and 18 do not differ substantively from claim 3, and are therefore rejected on the same grounds as claim 3.
7. Claims 4, 9, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Mach in view of Liu in view in view of Yoon as applied to claims 1, 6, 11, and 16 above, further in view of Choi et al., U.S. Patent Application Publication 2016/0014661 (hereinafter Choi).
Regarding claim 4, the combination of Mach, Liu, and Yoon discloses all the limitations of claim 1. Additionally, Mach discloses that the neighborhood information is transmitted by a base station or a core network (the base station transmits neighbor cell power information to the SON/AI entity, according to [0181], [0194]-[0196], Fig. 7B [steps 714-716]).
Neither Mach, Liu, nor Yoon expressly discloses that the neighborhood information at least comprises: General Packet Radio Service (GPRS), a cell type, time and a cell capacity.
Choi discloses that the neighborhood information at least comprises: General Packet Radio Service (GPRS), a cell type, time and a cell capacity (disclosed is a GPRS network, according to [0056]-[0057], whereby a message comprises a field that identifies source cells and destination cells, according to [0141], [0149], whereby the message comprises a field indicating a time, according to [0151], whereby the message comprises a cause field that indicates cell capacity, according to [0141], [0166]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu as modified by Yoon with Choi such that the neighborhood information is transmitted by a base station or a core network.
One of ordinary skill in the art would have been motivated to make this modification in order to facilitate energy saving in a cellular network (Choi: [0006]).
Claims 9, 14, and 19 do not differ substantively from claim 4, and are therefore rejected on the same grounds as claim 4.
8. Claims 5, 10, 15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Mach in view of Liu in view of Yoon as applied to claims 1, 6, 11, and 16 above, further in view of Talwar et al., U.S. Patent Application Publication 2024/0092292 (hereinafter Talwar).
Regarding claim 5, the combination of Mach, Liu, and Yoon discloses all the limitations of claim 1.
Neither Mach, Liu, nor Yoon expressly discloses that the handover model is based on a Recursive Neural Network (RNN) model or a Deep Recursive Neural Network (DRNN) model.
Talwar discloses that the handover model is based on a Recursive Neural Network (RNN) model or a Deep Recursive Neural Network (DRNN) model (a handoff routine is arranged as an arbitration module in the form of a recursive neural network, according to [0056]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mach as modified by Liu as modified by Yoon with Talwar such that the handover model is based on a Recursive Neural Network (RNN) model or a Deep Recursive Neural Network (DRNN) model.
One of ordinary skill in the art would have been motivated to make this modification in order to facilitate user support in a vehicle cabin (Talwar: [0003]).
Claims 10, 15, and 20 do not differ substantively from claim 5, and are therefore rejected on the same grounds as claim 5.
Conclusion
9. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W GENACK whose telephone number is (571)272-7541. The examiner can normally be reached Monday through Friday, 9:00 AM to 5:00 PM Eastern Time.
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/MATTHEW W GENACK/Primary Examiner, Art Unit 2645
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