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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/23/2025 has been entered.
Response to Arguments
Applicant’s Amendments and Arguments filed 12/23/2025 have been considered for examination.
With regard to the 112(b) rejections, Applicant’s arguments filed 12/23/2025 in view of the amendments have been fully considered and are persuasive. Thus, the 112(b) rejections have been withdrawn.
With regard to the 103 rejections, Applicant’s arguments filed 12/23/2025 in view of the amendments have been fully considered but are not persuasive at least in view of reasons set forth below.
On page 9 of Remarks, Applicant argued:
In the Final Office Action, the Examiner maps Chavva's feedback parameters to the
claimed "first information." However, this mapping is improper. While Chavva's feedback
parameters may include Rank Indicator (RI), Precoding Matrix Indicator (PMI), Channel Quality
Indicator (CQI), CSI-Reference Signals Indicator (CRI), and so on (see Chavva, para. [0107]),
Chavva does not disclose that each feedback parameter (mapped to the claimed "first information") is associated with a reference signal (RS) identifier, nor does Chavva disclose that such RS identifier, together with beam quality corresponding to the RS identifier, is included in a target object that is represented by the feedback parameters ("first information"). Therefore, Chavva's feedback parameters cannot be reasonably mapped to the claimed "first information," and Chavva fails to disclose all claim limitations of amended independent claim 1.
Guo is cited for its purported teaching of "beam quality," which is unrelated to the above discussed claim limitations. Indeed, Guo also fails to disclose that "the target object comprises a
first Reference Signal (RS) identifier and beam quality corresponding to the first RS identifier"
and "each of the N pieces of first information is associated with the first RS identifier," as required by amended independent claim 1. Accordingly, Applicant respectfully submits that Guo does not cure the deficiency of Chavva.
In response to the above Applicant’s argument, Examiner respectfully disagrees.
Unlike the applicant’s arguments above, it is proper to map Chavva’s feedback parameters to the claimed first information in light of the Chavva’s feedback parameters being properly read into “the first information obtained from an artificial intelligence network based on the beam measurement result”. Regarding the feature “RS identifier, together with beam quality corresponding to the RS identifier, is included in a target object that is represented by the feedback parameters”, Guo clearly discloses, “the target object comprises beam quality corresponding to the first RS identifier, and each of the N pieces of first information is associated with the first RS identifier”, as currently amended. See the examiner’s discussion.
On page 10 of Remarks, Applicant argued:
Islam is cited for reasons unrelated to the above discussed claim limitations. Indeed, Islam also does not disclose that "the target object comprises a first Reference Signal (RS) identifier and beam quality corresponding to the first RS identifier" and "each of the N pieces of first information is associated with the first RS identifier," as required by amended independent claim 1. Therefore, Islam does not cure the deficiency of Chavva and Guo.
In response to the above Applicant’s argument, Examiner respectfully disagrees.
Since claims 1, 15 and 19 are unpatentable over Chavva and Guo as set forth above, thus the other cited references do not necessarily be considered regarding patentability of the claims.
On page 10 of Remarks, Applicant argued:
Independent claims 15 and 19 are likewise allowable over Chavva, Guo, and Islam because they each recite similar claim limitations as those of independent claim 1.
In response to the above Applicant’s argument, Examiner respectfully disagrees.
Since claims 15 and 19 recite similar features to claim 1 without further patentable features, claims 15 and 19 are unpatentable in view of the same reasons set forth above regarding claim 1.
On page 10 of Remarks, Applicant argued:
Dependent claims 2, 4-14, 16, 18, and 20 are thus allowable over these cited references at least by virtue of their dependencies from their respective base claims 1, 15, or 19, and because they respectively recite additional distinct limitations.
In response to the above Applicant’s argument, Examiner respectfully disagrees.
Since claims 2, 4-14, 16, 18, and 20 are unpatentable over the cited references of record as set forth above, patentability of other dependent claims should be determined based on the claimed limitations recited thereon, rather than their respective independent claims. The dependent claims are also unpatentable in view of the corresponding cited references of records as set forth below.
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 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 factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-2, 4-10, 12-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chavva et al (US Publication No. 2021/0351885) in view of Guo et al (US Publication No. 2019/0190582).
Regarding claim 1, Chavva discloses, a beam reporting method [¶0091 (further see FIGS. 8-10, 12 and 13A and their related descriptions), a CSI reporting method], performed by a first device [¶0091 (further see FIGS. 8-10, 12 and 13A and their related descriptions), performed by user equipment (UE)], comprising:
performing beam measurement according to a beam measurement configuration to obtain a beam measurement result [¶0091-0092 (further see FIGS. 8-10, 12 and 13A and their related descriptions), performing measurements to CSI-RS or SSBs according to a feedback configuration to obtain channel metrics, baseband parameters and sensor measurements];
inputting the beam measurement result into an artificial intelligence (Al) network to obtain N pieces of first information, wherein N is a positive integer [¶0093 (further see FIGS. 8-10, 12 and 13A and their related descriptions), based on the baseband metrics, the channel metrics, RX beam pattern information and the sensor measurements, using the ML model, estimates the feedback parameters (i.e., first information); “The embodiments include estimating the feedback parameters using a Machine Learning (ML) model, such as a neural network. The computation of the feedback parameters is based on the baseband metrics, channel metrics, RX beam pattern information, and the sensor measurements. The embodiments include extracting feature vectors by processing the information in the measurement database. The embodiments include inputting the feature vectors to the ML model for computing the feedback parameters”]; and
sending a first beam measurement report to a second device [¶0095 (further see FIGS. 8-10, 12 and 13A and their related descriptions), the UE sends the CSI report including the estimated feedback parameters to gNB], wherein the first beam measurement report comprises the N pieces of first information, and the first information is used to determine beam information [¶0095 (further see FIGS. 8-10, 12 and 13A and their related descriptions), CSI report includes the estimated feedback parameters which are used to determine beam information (further see ¶0091, “the parameters can be Precoding Matrix Indicator (PMI), Channel Quality Indicator (CQI), CSI-Reference Signals (CSI-RS) Indicator (CRI), Rank Indicator (RI), and so on.)] and to represent a target object [¶0091, the estimated feedback parameters include a CSI-RS indicator].
Although Chavva further discloses, wherein the target object comprises a first reference signal (RS) identifier [¶0091, the estimated feedback parameters include a CSI-RS indicator (i.e., first RS identifier)], and wherein the first RS identifier is any one of the following: an RS identifier comprised in the first beam measurement report [¶0095 (further see FIGS. 8-10, 12 and 13A and their related descriptions), the estimated feedback parameters are included in the CSI report; further see ¶0091, the feedback parameters includes the CSI-RS indicator (i.e., first RS identifier)].
Chavva does not explicitly disclose (see, italicized and bold limitations), wherein N is a positive integer and is greater than 1, the target object comprises beam quality corresponding to the first RS identifier, and each of the N pieces of first information is associated with the first RS identifier.
However, Guo discloses, wherein N is a positive integer and is greater than 1, the target object comprises beam quality corresponding to the first RS identifier [¶0236, the UE can be configured to report N=4 selected RS IDs and their corresponding L1-RSRP measurements (i.e., beam quality)], and each of the N pieces of first information is associated with the first RS identifier [¶0236-0241, among the four (4) RSRP measurements, the largest RSRP measurement for the RS ID 1 (i.e., first RS identifier) is associated with the RS ID 1, and the rest RSRP measurements for the RS ID 2 to RS ID4 are represented as relative values to (i.e., associated with) the largest RSRP measurement for the RS ID 1; note that since the rest RSRP measurements are associated with the largest RSRP measurement, and the largest RSRP measurement is associated with the RS ID1, each of the RSRP measurements is associated with the RS ID 1/first RS identifier].
It is noted that the above-mentioned feature is a known technique in the field Applicant's endeavor, e.g., telecommunication art.
It is noted that the above-mentioned feature is a known technique in the field Applicant’s endeavor, e.g., telecommunication art. It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the system of Chavva with "the above-mentioned known feature(s)" taught by Guo to reach the claimed invention as set forth above. Since one having ordinary skill in the art could have recognized that applying the known technique taught by Guo into the system of Chavva would have yield predictable results and/or resulted in the improved system, such as e.g., ensure to enable optimal beam selection and maintain reliable high-quality communication by allowing the network to adapt to channel condition dynamically, such a modification (or application) would have involved the mere application of a known technique to a piece of prior art ready for improvement," the claim is unpatentable under 35 U.S.C. 103(a). Ex Parte Smith, 83 USPQ.2d 1509, 1518-19 (BPAI, 2007) (citing KSR v. Teleflex, 127 S.Ct. 1727, 1740, 82 USPQ2d 1385, 1396 (2007)).
Regarding claim 2, Chavva in view of Guo discloses, the beam reporting method according to claim 1 as set forth above. Chavva discloses, wherein the first beam measurement report [¶0095 (further see FIGS. 8-10, 12 and 13A and their related descriptions), the CSI report] further comprises at least one of the following: a reference signal (RS) identifier corresponding to a beam [¶0091 (further see FIGS. 8-10, 12 and 13A and their related descriptions), CSI-RS indicator (CRI) corresponding to a CSI-RS].
Regarding claim 4, Chavva in view of Guo discloses, the beam reporting method according to claim 1 as set forth above. Chavva discloses, wherein different types of beam quality correspond to different Al networks [FIG. 12; its related descriptions; ¶0173, different types of quality parameters such as CSI, RI, PMI, CQI, L1 and L1-RSRP correspond to different neural networks NM1 to NM6].
Regarding claim 5, Chavva in view of Guo discloses, the reporting method according to claim 1 as set forth above. Chavva discloses, wherein the target object comprises at least one of the following: predicted beam quality [¶0115-0116 and 0122-0123, the CSI report comprising parameters such as CQI which is predicted].
Regarding claim 6, Chavva in view of Guo discloses, the beam reporting method according to claim 5 as set forth above. Chavva discloses, wherein when the target object comprises the predicted beam quality, the predicted beam quality comprises predicted beam quality of a third RS identifier within a preset time period [¶0115-0116 and 0124, predicted probable values of the feedback parameters at a future time instances configured in the CSI-ReportConfig IE (i.e., preconfigured); note that the predicted values include a value of CRI (a feedback parameter) (i.e., third RS identifier)], and the third RS identifier comprises any one of the following: an RS identifier comprised in the first beam measurement report [¶0124, since a CSI report (i.e., first beam measurement report) includes computed and/or predicted feedback parameters including the value of CRI].
Regarding claim 7, Chavva in view of Guo discloses, the beam reporting method according to claim 6 as set forth above. Chavva discloses, wherein when the first beam measurement report and a second beam measurement report meet a preset condition [¶0124-0128, the CSI report including computed and/or predicted feedback parameters including the value of CRI and CSI reports (i.e., second beam measurement report) transmitted in a periodic manner meet time conditions where the CSI reports are transmitted (further see ¶0140)], the third RS identifier comprises at least one of the following: a fourth RS identifier, wherein the fourth RS identifier is only associated with first information in a target measurement report, and the target beam measurement report is at least one of the first beam measurement report and the second beam measurement report [¶0115-0116 and 0124, note that the value of CRI is associated with information in the CSI report which is at least one of the CSI reports transmitted in a periodic manner], wherein the second beam measurement report is a beam measurement report that is closest to the first beam measurement report [¶0128 and 0140, each of the plurality of CSI reports can be sent to the gNB periodically during the reporting slots; note that the first CSI report of the periodic CSI report is closest to the CSI report including computed and/or predicted feedback parameters including the value (described in ¶0128)].
Regarding claim 8, Chavva in view of Guo discloses, the beam reporting method according to claim 7 as set forth above. Chavva discloses, wherein the preset condition comprises at least one of the following: the RS identifier associated with the first information in the first beam measurement report is different from an RS identifier associated with first information in the second beam measurement report [¶0124-0128 and 0140, the CRI in the CRI report including the computed and predicted feedback parameters is different from the CRI in the periodic CSI reports because Chavva describes variations of inputted beam measurement results which results in changes of the CRIs (see ¶0127, “the neural network 602 c can determine a pattern of variations in each of the baseband metrics, channel metrics, and RX beam pattern information, with respect to the variation in the sensor measurements” and ¶0128, “the neural network 602 c can predict the probable values of the feedback parameters at the future time instances, based on the determined pattern of variations, and variations in factors such as, but not limited to, (feedback) delay in scheduling the PDSCH, based on the CSI report, by the gNB 607”)].
Regarding claim 9, Chavva in view of Guo discloses, the beam reporting method according to claim 5 as set forth above. Chavva does not explicitly disclose (see, italicized limitations), but Guo discloses, wherein when the target object comprises the beam quality corresponding to the M second RS identifiers and M is greater than 1, the beam quality corresponding to the M second RS identifiers comprises any one of the following: beam quality of each RS identifier in the M second RS identifiers [¶0236, the UE can be configured to report N=4 selected RS IDs and their corresponding L1-RSRP measurements].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide the above-mentioned feature(s) as taught by Guo in the system of Chavva for similar rationales set forth above in claim 1.
Regarding claim 10, Chavva in view of Guo discloses, the beam reporting method according to claim 9 as set forth above. Chavva does not explicitly disclose (see, italicized limitations), but Guo discloses, wherein when the beam quality corresponding to the M second RS identifiers comprises the beam quality of each identifier in the at least one target RS identifier or the average beam quality of the at least one target RS identifier meets at least one of the following: when beam quality of L4 RS identifiers in the second RS identifier is greater than a second preset threshold, the at least one target RS is the L4 RS identifiers, wherein L4, L5, and L6 are all positive integers [¶0236, the UE can be configured to report N=4 selected RS IDs and their corresponding L1-RSRP measurements larger than X_1 dBm/a preset threshold].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide the above-mentioned feature(s) as taught by Guo in the system of Chavva for similar rationales set forth above in claim 1.
Regarding claim 12, Chavva in view of Guo discloses, the beam reporting method according to claim 1 as set forth above. Chavva discloses, wherein inputting the beam measurement result into the Al network comprises: inputting target information into the Al network, wherein the target information comprises at least one of the following: beam quality [¶0093 (further see FIGS. 8-10, 12 and 13A and their related descriptions), based on the baseband metrics, the channel metrics, RX beam pattern information and the sensor measurements (i.e., beam quality), using the ML model, estimates the feedback parameters; “The embodiments include estimating the feedback parameters using a Machine Learning (ML) model, such as a neural network; further see FIGS. 9A-9B and their related description] of a sub-band [¶0093, note that the beam quality is associated with at least one frequency band (sub-band)].
Regarding claim 13, Chavva in view of Guo discloses, the beam reporting method according to claim 12 as set forth above. Chavva discloses, wherein the target information further comprises at least one of the following: first information in a third beam measurement report [¶0128 and 0140, each of the plurality of CSI reports can be sent to the gNB periodically during the reporting slots; note that the first CSI report of the periodic CSI report is considered as a third beam measurement report which has a value of CSI-RS indicator (CRI) (i.e., first information)], wherein the third beam measurement report is a beam measurement report within K time units from a current moment, and K is a positive integer [¶0128 and 0140, note that the first CSI report of the periodic CSI report is within time units/future time instances from a moment where the computation of the feedback parameters is performed and reported (further ¶0123-0124)].
Regarding claim 14, Chavva in view of Guo discloses, the beam reporting method according to claim 5 as set forth above. Chavva discloses, determining the target object according to an indication of a network device [¶0091-0092 (further see FIGS. 8-10, 12 and 13A and their related descriptions), performing measurements to CSI-RS or SSBs according to a feedback configuration to obtain channel metrics, baseband parameters and sensor measurements and compute the feedback parameters including including the CRI].
Regarding claim 15, Chavva discloses, a communications device [¶0092, user equipment (UE)], wherein the communications device is a first communications device [¶0092, user equipment (UE)], comprising:
a memory storing a computer program [FIG. 23; its related descriptions; ¶0228 and 0234, memory 2330 storing a computer program; note that every UE has at least one memory]; and
a processor coupled to the memory and configured to execute the computer program to perform operations [FIG. 23; its related descriptions; ¶0228 and 0234, processor 2310 coupled to the memory and executed to the program to perform action(s); note that every UE has at least one processor].
Since claim 15 recites similar features to claim 1 without further additional features, claim 15 is rejected at least based on a similar rationale applied to claim 1.
Regarding claim 16, claim 16 is rejected at least based on a similar rationale applied to claim 2.
Regarding claim 18, claim 18 is rejected at least based on a similar rationale applied to claim 4.
Regarding claim 19, Chavva discloses, a non-transitory computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor of a first device, causes the processor to perform operations [FIG. 23; its related descriptions; ¶0228 and 0234, memory 2330 storing a computer program; note that every UE has at least one memory]. Since claim 19 recites similar features to claim 1 without further additional features, claim 19 is rejected at least based on a similar rationale applied to claim 1.
Regarding claim 20, claim 20 is rejected at least based on a similar rationale applied to claim 2.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Chavva et al (US Publication No. 2021/0351885) in view of Guo et al (US Publication No. 2019/0190582) and further in view of Islam et al (US Publication No. 2019/0245605).
Regarding claim 11, Chavva in view of Guo discloses, the beam reporting method according to claim 5 as set forth above. Chavva in view of Guo does not explicitly disclose (see, italicized limitations), but Islam discloses, wherein the stability comprises at least one of the following: time domain stability [¶0131, the UE 604 may convey information regarding the variation of beam quality (e.g., fluctuations in a strength of a transmit beam) in the time domain to the base station 602].
It is noted that the above-mentioned feature is a known technique in the field Applicant's endeavor, e.g., telecommunication art.
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the system of Chavva in view of Guo with "the above-mentioned known feature(s)" taught by Islam to reach the claimed invention as set forth above. Since one having ordinary skill in the art could have recognized that applying the known technique taught by Isalm into the system of Chavva in view of Guo would have yield predictable results and/or resulted in the improved system, such as e.g., ensure the base station assess channel quality variation and adjust link adaption or beam management strategies for more stable and efficient communication, such a modification (or application) would have involved the mere application of a known technique to a piece of prior art ready for improvement," the claim is unpatentable under 35 U.S.C. 103(a). Ex Parte Smith, 83 USPQ.2d 1509, 1518-19 (BPAI, 2007) (citing KSR v. Teleflex, 127 S.Ct. 1727, 1740, 82 USPQ2d 1385, 1396 (2007)).
Conclusion
The prior art made of record and not relied upon are considered pertinent to applicant's disclosure.
Fakoorian et al (US Publication No. 2020/0112357) [¶0078 and 0086].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUN JONG KIM whose telephone number is (571)270-3216. The examiner can normally be reached on 7:30am-5:30pm (M-T).
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/SUN JONG KIM/Primary Examiner, Art Unit 2469