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 .
Remarks
The present Office Action is in response to Applicant’s amendment filed on 12/04/2025. Claims 1-14 and 16-21 are still pending in the present application. This Action is made FINAL.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1-14 and 16-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over FAN et al. - US 20160050608 A1- (hereinafter Fan) in view of KIM et al. -US 20210297178 A1- (hereinafter Kim).
Regarding claim 1, Fan discloses a device switching method, applied to a terminal device, the method comprising:
determining a device switching situation of switching between a source access network device and a target access network device by (FIG. 1 and FIG. 2, par. 0003, 0006, 0019 for the receiving powers can be represented by e.g., RSRP or RSRQ, “At step S110, the wireless device calculates a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station. Here, the receiving powers can be represented by e.g., RSRP or RSRQ”; par. 0034; par. 0038);
wherein the network device or the target access network device (par. 0019, 0034 and/or 0038, measured the RSRP or RSRQ from each base station can be considered as claimed maximum .
However, Fan fails to especially disclose taking an artificial intelligence (AI) computing power factor value.
In the same field of endeavor, Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 2, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a first (par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”).
Kim further discloses AI computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 3, as applied to claim 2 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the first AI computing power factor value as the forward offset parameter comprises at least one of: in response to determining that a sum of a first reference switching parameter of the target access network device and the first AI computing power factor value reaches a switching threshold, switching from the source access network device to the target access network device, wherein the first reference switching parameter comprises at least one of a reference signal receiving quality (RSRQ) and a reference signal receiving power (RSRP) of the target access network device; in response to determining that a product of the first reference switching parameter of the target access network device and the first (par. 0032, “the power offset and the TDD offset are combined such that a power offset equal to or higher than 6-0.816=5.184 dB will trigger the handover. That is, the determination as to whether to initiate a handover or not is now made based on the sum of the power offset and the TDD offset. More specifically, the wireless device initiates the handover when the sum of the power offset and the TDD offset exceeds the threshold.”); in response to determining that a sum of an opposite number of the first Al computing power factor value and a second reference switching parameter of the source access network device is less than a switching threshold, switching from the source access network device to the target access network device, wherein the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device; or in response to determining that a ratio of the second reference switching parameter of the source access network device to the first AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device.
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 4, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a first (par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 5, as applied to claim 4 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the first AI computing power factor value as the reverse offset parameter comprises at least one of: in response to determining that a sum of an opposite number of the first AI computing power factor value and a first reference switching parameter of the target access network device reaches a switching threshold, switching from the source access network device to the target access network device, wherein the first reference switching parameter comprises at least one of an RSRQ and an RSRP of the target access network device; in response to determining that a ratio of the first reference switching parameter of the target access network device to the first AI computing power factor value reaches a switching threshold, switching from the source access network device to the target access network device; in response to determining that a sum of a second reference switching parameter of the source access network device and the first AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device, wherein the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device (par. 0003, par. 0019, “the wireless device calculates a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station. Here, the receiving powers can be represented by e.g., RSRP or RSRQ as noted above, and can be measured using any appropriate process as known in the art”; par. 0031, “the wireless device initiates the handover when a combination of the power offset and the TDD offset exceeds a threshold. For example, the wireless device can initiate the handover by transmitting an A3 measurement report to the source base station”); or in response to determining that a product of the second reference switching parameter of the source access network device and the first AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device (par. 0032, “the power offset and the TDD offset are combined such that a power offset equal to or higher than 6-0.816=5.184 dB will trigger the handover. That is, the determination as to whether to initiate a handover or not is now made based on the sum of the power offset and the TDD offset. More specifically, the wireless device initiates the handover when the sum of the power offset and the TDD offset exceeds the threshold.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 6, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a second AI computing power factor value of the target access network device; and in response to determining that the second AI computing power factor value is less than or equal to a second threshold, determining the device switching situation of switching between the source access network device and the target access network device by taking the second AI computing power factor value as a reverse offset parameter (par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 7, as applied to claim 6 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the second AI computing power factor value as the reverse offset parameter comprises at least one of: in response to determining that a sum of an opposite number of the second AI computing power factor value and a first reference switching parameter of the target access network device reaches a switching threshold, switching from the source access network device to the target access network device, wherein the first reference switching parameter comprises at least one of an RSRQ and an RSRP of the target access network device; in response to determining that a ratio of the first reference switching parameter of the target access network device to the second AI computing power factor value reaches a switching threshold, switching from the source access network device to the target access network device ; in response to determining that a sum of a second reference switching parameter of the source access network device and the second AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device, wherein the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device; or in response to determining that a product of the second reference switching parameter of the source access network device and the second AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device (par. 0003, par. 0019, “the wireless device calculates a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station. Here, the receiving powers can be represented by e.g., RSRP or RSRQ as noted above, and can be measured using any appropriate process as known in the art”; par. 0031, “the wireless device initiates the handover when a combination of the power offset and the TDD offset exceeds a threshold. For example, the wireless device can initiate the handover by transmitting an A3 measurement report to the source base station”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 8, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a second second (par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 9, as applied to claim 8 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the second AI computing power factor value as the forward offset parameter comprises at least one of: in response to determining that a sum of a first reference switching parameter of the target access network device and the second AI computing power factor value reaches a switching threshold, switching from the source access network device to the target access network device, wherein the first reference switching parameter comprises at least one of an RSRQ and an RSRP of the target access network device; in response to determining that a product of the first reference switching parameter of the target access network device and the second AI computing power factor value reaches a switching threshold, switching from the source access network device to the target access network device; in response to determining that a sum of an opposite number of the second AI computing power factor value and a second reference switching parameter of the source access network device is less than a switching threshold, switching from the source access network device to the target access network device, wherein the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device; or in response to determining that a ratio of the second reference switching parameter of the source access network device to the second AI computing power factor value is less than a switching threshold, switching from the source access network device to the target access network device (par. 0003, par. 0019, “the wireless device calculates a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station. Here, the receiving powers can be represented by e.g., RSRP or RSRQ as noted above, and can be measured using any appropriate process as known in the art”; par. 0031, “the wireless device initiates the handover when a combination of the power offset and the TDD offset exceeds a threshold. For example, the wireless device can initiate the handover by transmitting an A3 measurement report to the source base station”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 10, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a first (par. 0028, “if the uplink-downlink traffic model of the wireless device indicates that more downlink than uplink traffic is desired by the wireless device, then the TDD offset is calculated as a positive value if the TDD configuration difference indicates that the target base station is able to provide more downlink resources than the source base station and the TDD offset is calculated as a negative value if the TDD configuration difference indicates that the target base station is able to provide less downlink resources than the source base station.” par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”; par. 0007 and 0043, “calculate a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station; obtain a Time Division Duplex (TDD) configuration difference between a TDD configuration of the target base station and a TDD configuration of the source base station; calculate a TDD offset based on the TDD configuration difference and an uplink-downlink traffic model of the wireless device; and initiate a handover from the source base station to the target base station when a combination of the power offset and the TDD offset exceeds a threshold.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 11, as applied to claim 10 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the computing power factor value difference as the forward offset parameter comprises at least one of: in response to determining that a sum of a switching parameter difference and the computing power factor value difference reaches a switching threshold, switching from the source access network device to the target access network device, wherein the switching parameter difference is a difference between a first reference switching parameter of the access network device and a second reference switching parameter of the source access network device, wherein the first reference switching parameter comprises at least one of an RSRQ and an RSRP of the target access network device, and the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device; or in response to determining that a product of the switching parameter difference and the computing power factor value difference reaches a switching threshold, switching from the source access network device to the target access network device (par. 0007 and 0043, “calculate a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station; obtain a Time Division Duplex (TDD) configuration difference between a TDD configuration of the target base station and a TDD configuration of the source base station; calculate a TDD offset based on the TDD configuration difference and an uplink-downlink traffic model of the wireless device; and initiate a handover from the source base station to the target base station when a combination of the power offset and the TDD offset exceeds a threshold.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 12, as applied to claim 1 above, Fan discloses wherein determining the device switching situation comprises: determining a first AI computing power factor value of the source access network device and a second AI computing power factor value of the target access network device; determining a computing power factor value difference between the second Al computing power factor value and the first AI computing power factor value; and in response to determining that the computing power factor value difference is less than or equal to a third threshold, determining the device switching situation of switching between the source access network device and the target access network device by taking the computing power factor value difference as a reverse offset parameter (par. 0028, “if the uplink-downlink traffic model of the wireless device indicates that more downlink than uplink traffic is desired by the wireless device, then the TDD offset is calculated as a positive value if the TDD configuration difference indicates that the target base station is able to provide more downlink resources than the source base station and the TDD offset is calculated as a negative value if the TDD configuration difference indicates that the target base station is able to provide less downlink resources than the source base station.” par. 0020 for any case of “a power offset of 10 dB means that the receiving power from the target base station is 10 dB higher than the receiving power from the source base station, whereas a power offset of −10 dB means that the receiving power from the target base station is 10 dB lower than the receiving power from the source base station”; par. 0007 and 0043, “calculate a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station; obtain a Time Division Duplex (TDD) configuration difference between a TDD configuration of the target base station and a TDD configuration of the source base station; calculate a TDD offset based on the TDD configuration difference and an uplink-downlink traffic model of the wireless device; and initiate a handover from the source base station to the target base station when a combination of the power offset and the TDD offset exceeds a threshold.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 13, as applied to claim 12 above, Fan discloses wherein determining the device switching situation of switching between the source access network device and the target access network device by taking the computing power factor value difference as the reverse offset parameter comprises: in response to determining that a sum of an opposite number of the computing power factor value difference and a switching parameter difference reaches a switching threshold, switching from the source access network device to the target access network device, wherein the switching parameter difference is a difference between a first reference switching parameter of the target access network device and a second reference switching parameter of the source access network device, wherein the first reference switching parameter comprises at least one of an RSRQ and an RSRP of the target access network device, and the second reference switching parameter comprises at least one of an RSRQ and an RSRP of the source access network device; or in response to determining that a ratio of the switching parameter difference and the computing power factor value difference reaches a switching threshold, switching from the source access network device to the target access network device (par. 0007 and 0043, “calculate a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station; obtain a Time Division Duplex (TDD) configuration difference between a TDD configuration of the target base station and a TDD configuration of the source base station; calculate a TDD offset based on the TDD configuration difference and an uplink-downlink traffic model of the wireless device; and initiate a handover from the source base station to the target base station when a combination of the power offset and the TDD offset exceeds a threshold.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 14, as applied to claim 1 above, Fan discloses converting an AI computing power of the at least one access network device according to a preset conversion to acquire the (par. 0031, “if the receiving power from the target base station as measured by the wireless device is x dBm and the TDD offset is y dB, the receiving power from the target base station in the A3 measurement report can be (x+y) dBm. Upon receiving the A3 measurement report, the source base station can transmit a handover request to the target base station. The subsequent handover procedure is known in the art and the description thereof will be omitted here.”).
Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 16, Fan discloses a terminal, comprising:
a processor; and a memory having stored therein instructions executable by the processor, wherein the processor is configured to (FIG. 6 for processor 620 and memory 630, par. 0042):
determining a device switching situation of switching between a source access network device and a target access network device by (FIG. 1 and FIG. 2, par. 0006, “calculating a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station… and initiating the handover when a combination of the power offset and the TDD offset exceeds a threshold.”).
However, Fan fails to especially disclose taking an artificial intelligence (AI) computing power factor value.
Ine the same field of endeavor, Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claim 16, Fan discloses a non-transitory computer-readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions that, when loaded and executed by a processor, causes the processor to perform a device switching method (FIG. 6 for processor 620 and memory 630, par. 0042), the method comprising:
determining a device switching situation of switching between a source access network device and a target access network device by (FIG. 1 and FIG. 2, par. 0006, “calculating a power offset indicative of a difference between a receiving power from the target base station and a receiving power from the source base station… and initiating the handover when a combination of the power offset and the TDD offset exceeds a threshold.”).
However, Fan fails to especially disclose taking an artificial intelligence (AI) computing power factor value.
Ine the same field of endeavor, Kim discloses taking an artificial intelligence (AI) computing power factor value (par. 0159, “The UE may measure RSRP, RSSI, and SNR when data is received by applying AI”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate applying AI (artificial intelligence) when measuring RSRP, RSSI, and/or SNR as disclosed by Kim to the receiving powers such as RSRP as disclosed by Fan for purpose of applying AI for measured RSRP.
Regarding claims 18-21, as applied to claim 16 above, the claim is rejected for the same reason(s) as set forth claim 2/4, 6/8 and 10/12 above.
Response to Arguments
Applicant’s amendment to the specification as filed 12/04/2025 have been considered, but the new title is objected since it is NOT clearly indicative of the invention to which the claims are directed.
Applicant’s arguments with respect to claim(s) 1, 16 and 17 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 ALLAHYAR KASRAIA N whose telephone number is (571)270-1772. The examiner can normally be reached Monday - Friday, 8:00 am - 5: 00 pm.
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, RAFAEL PEREZ-GUTIERREZ can be reached at (571)272-7915. 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.
/ALLAHYAR KASRAIA N/Primary Examiner, Art Unit 2642