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 .
Response to Amendment
The following is a final office action in response to applicant’s reply, filed on 06/22/2026, to the Non-Final Office Action mailed on 03/26/2026.
Claims 1, 8, 15, 16, 18, 19, 24, 29, and 30 are amended. Claims 7 and 23 are canceled. Claims 1-6, 8-22 and 24-30 are pending and addressed below.
Applicant’s amendment has overcome rejection under 112(b), previously set forth in the non-final office action.
Claim Rejections - 35 USC § 112
Claims 1-6, 8-22 and 24-30 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 16, 29 and 30 recite expressions “channel state information (CSI) comprising … a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector”. It is not clear about what the indications represent for the layers or singular vectors. Claims are, therefore, indefinite. Other claims are subjected to the same rejection because of their dependency on the above rejected claims.
Claims 31 and 32 recite first and second indication includes real values of the first/second layer or the first/second vector, which lacks clarity. It is not understood, what the real values represent for the first/second layer or the first/second vector and the characteristic of the real value.
Claims 1, 16, 29 and 30 recite expressions “the fractional RI value indicating a probability of each candidate rank of the set of candidate ranks, including separate probabilities for different candidate ranks in the set of candidate ranks”, which lacks clarity. It first recites that a single probability is assigned to each candidate rank indicated by a fractional RI value. Then it recites that the fractional RI value includes more than one probability for each candidate rank. It is not understood, how multiple probabilities of a candidate rank is represented by a single fractional RI value. Other claims are subjected to the same rejection because of their dependency on the above rejected claims.
Claims 16 recites limitation “obtaining a precoding matrix indicator (PMI) based on the first indication, the second indication, and weights or probabilities determined based on the fractional RI value”. In light of the amendment in the claim, fractional RI indicates probability. It is not clear about determining “weights” from the fractional RI value, and its representation and significance in the invention. Moreover, as explained above, the first indication and the second indication are not clear, therefore obtaining a PMI based on them are also not clear.
Claim Rejections - 35 USC § 103
Claims 1-2, 4-6, 9-10, 29 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over IDS Reference, Yu; Zhibin et al US 20210250069 A1, hereinafter Yu, in view of KIM; Hyungtae et al US 20160165466 A1, hereinafter KIM.
Regarding claim 1, 29 and 30, Yu teaches, a method (Yu Fig. 2) for wireless communications by a user equipment (UE), comprising:
generating channel state information (CSI) comprising a fractional rank indication (RI) value for a set of candidate ranks, a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector (Fractional RI or partial RI can be interpreted as probability or hypotheses based RI or soft RI, and first and second indication of layers is interpreted as PMI (Pre-coder Matrix Indicator) of layers, in line with the Spec. Yu Fig.2, step (6); [72] “ In step (6), instead of making the hard-decision on the RI value based on thresholds over eigenvalues for the rank estimation, soft-decision can be generated which maps the normalized eigenvalues into a confidence metric for each RI hypothesis. As one example, the RI confidence metric can be determined by Euclidean distances between the normalized eigenvalues obtained from EVD, and the theoretical optimal eigenvalues associated to a RI hypothesis.”, [78] “And for each CSI-RS resource, the required operation is a function mapped by: the number of down-sampled CSI-RS REs, the number of RI hypotheses to test, and the number of PMI hypotheses to compute per RI hypothesis.”, teaches generating a number of RI hypotheses and PMI corresponding to each RI i.e., rank layer);
the fractional RI value indicating a probability of each candidate rank of the set of candidate ranks, including separate probabilities for different candidate ranks in the set of candidate ranks (Yu [72]-[76], [78] “confidence level of an RI hypothesis” can indicate separate probabilities of candidate ranks).
Yu does not expressly teach, however, in the same field of endeavor, KIM teaches, transmitting the CSI to a network entity (KIM Claim 2 “calculating partial rank indicators (RIs) corresponding to the plurality of CSI-RSs; and reporting the partial RIs to the base station through the feedback chains”, Claim 5 “wherein the CSI items including the partial CQIs include information about partial precoding matrix indices (PMIs).”, Claim 6 “wherein the partial PMIs include a PMI for a vertical channel and a PMI for a horizontal channel”, teaches transmitting a CSI comprising partial (=fractional) RI and PMI for channels (=layers). Therefore, RI hypotheses values and PMI values of layers in Yu can also be transmitted to the base station (=network entity)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Yu to include the features as taught by KIM above in order to provide a method for feeding a partial channel quality indicator (CQI) back by a terminal in a wireless communication system (KIM [0003]).
With respect to claim 29, claim recites the identical features of claim 1 for a corresponding apparatus. Therefore, it is subjected to the same rejection.
With respect to claim 30, claim recites the identical features of claim 1 for a corresponding computer-readable medium (CRM). Therefore, it is subjected to the same rejection.
Claims 16, 18, 20-22 and 25-26 are rejected under 35 U.S.C. 103 as being unpatentable over KIM; Hyungtae et al US 20160165466 A1, hereinafter KIM, in view of IDS Reference, Yu; Zhibin et al US 20210250069 A1, hereinafter Yu.
Regarding claim 16, Kim teaches, A method for wireless communications by a network entity, comprising:
receiving, from a user equipment (UE), channel state information (CSI) comprising a fractional rank indication (RI) value for a set of candidate ranks, a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector (Fractional RI or partial RI can be interpreted as probability or hypotheses based RI or soft RI, and first and second indication of layers is interpreted as PMI (Pre-coder Matrix Indicator) of layers, in line with the Spec. KIM Claim 2 “calculating partial rank indicators (RIs) corresponding to the plurality of CSI-RSs; and reporting the partial RIs to the base station through the feedback chains”, Claim 5 “wherein the CSI items including the partial CQIs include information about partial precoding matrix indices (PMIs).”, Claim 6 “wherein the partial PMIs include a PMI for a vertical channel and a PMI for a horizontal channel”, teaches transmitting a CSI comprising partial (=fractional) RI and PMI for channels (=layers) to the base station (=network entity)).
KIM does not expressly teach, however, in the same field of endeavor, Yu teaches, obtaining a precoding matrix indicator (PMI) based on the first indication, the second indication, and weights or probabilities determined based on the fractional RI value (Yu Fig. 2, (9)-(11); [81] “In step (10), the joint RI-PMI search is applied on the finally down-selected RI hypotheses for CSI-RS resources from all CCs. Note that the disclosed method in this disclosure is fully compatible with any additional multi-stage PMI search schemes. In step (11), the best RI-PMI combination is detected after the joint search and the associated CQI is measured to generate the CSI feedback report for each CC.”, [82] “As a result, instead of relying on simplified received power to identify the best CSI-RS resource per CC, soft-decisions e.g. RI confidence metrics can be generated over multiple candidate CSI-RS resources per CC and jointly sorted in step (10) to derive the best RI and PMI in step (11).”, teaches obtaining a RI-PMI based on sorting and searching of RI hypotheses and PMI values. This method, while done in the UE, can be executed in the network node, based on KIM’s teaching above about transferring the fractional RIs and PMIs per layer to the network node).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of KIM to include the features as taught by Yu above in order to provide a method for adaptive and hierarchical CSI acquisition for 5G NR (New Radio) UE (User Equipment) computation complexity reduction (Yu [0002]).
Regarding claim 2, Yu, in view of KIM, teaches the method, as outlined in the rejection of claim 1.
Yu further teaches, further comprising: deriving weights or probabilities for the first and second layers or first and second singular vectors; and selecting the fractional RI value as an indication of the weights or probabilities (Yu [72]-[76] defining a confidence level (that is, a probability) for each RI hypothesis, therefore for its associated ranks (=layers)).
Regarding claims 4 and 20, Yu/KIM, in view of KIM/Yu, teaches the methods, as outlined in the rejection of claims 1 and 16.
Yu further teaches, wherein the fractional RI value indicates a codepoint corresponding to a candidate rank of the set of candidate ranks, wherein the candidate rank is a fractional rank value or an integer rank value (Yu [61] discloses a confidence metric for each RI hypothesis (=candidate rank) and the confidence metric is according to Euclidean distance, therefore, an integer value, and a codepoint).
Regarding claims 5 and 21, Yu/KIM, in view of KIM/Yu, teaches the methods, as outlined in the rejection of claims 1 and 16.
Yu further teaches, wherein the fractional RI value indicates a codepoint corresponding to a condition number based on singular values of channel estimates (Yu [74][76] calculation of a metric based on eigenvalues (formula (3) in paragraph [0075]). Said metric can be viewed as a condition number; Moreover, eigenvalues can be singular values.).
Regarding claims 6 and 22, Yu/KIM, in view of KIM/Yu, teaches the methods, as outlined in the rejection of claims 1 and 16.
Yu further teaches, wherein the fractional RI value indicates a codepoint corresponding to a probability profile of the set of candidate ranks
CLM-6/1, 22/16 (Yu [76] “confidence level of an RI hypothesis” can be probability profile of candidate ranks).
Regarding claims 9 and 25, Yu/KIM, in view of KIM/Yu, teaches the methods, as outlined in the rejection of claims 1 and 16.
Yu further teaches, wherein the fractional RI value indicates a codepoint corresponding to a weight or probability profile of a set of layers corresponding to the set of candidate ranks (see claim 6, 22 rejections above, where YU teaches confidence level as probability profile. Satisfies “or” criteria).
Regarding claims 10 and 26, Yu/KIM, in view of KIM/Yu, teaches the methods, as outlined in the rejection of claims 1 and 16.
Yu further teaches, wherein the fractional RI value indicates separate weights or probabilities for each of a set of layers corresponding to the set of candidate ranks (see rejection above for claims 7, 23 for separate probability. Satisfies “or” criteria).
Regarding claim 18, KIM, in view of Yu, teaches the methods, as outlined in the rejection of claim 16.
Yu further teaches, comprising: obtaining the PMI using a precoding matrix indicator (PI) decoder which takes the fractional RI value and first and second indications as input (Yu Fig. 2, step (9)-(11), [81] teaches obtaining PMI by sorting and searching, therefore, implying a PMI decoder).
Allowable Subject Matter
Claims 3, 8, 11, 17, 19, 24 and 27 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. Claims 12-15 and 28 are subjected to the same object because of their dependency on the above objected claims 11 and 27.
Response to Arguments
Applicant's arguments filed on 06/22/2026 with respect to claim 1 have been fully considered but they are not persuasive.
Applicant argues in Remarks page 9, “As amended, claim 1 recites generating CSI comprising "a fractional RI value for a set of candidate ranks, a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector". Read in light of the Specification, a person of ordinary skill would understand these indications to be values representing the respective layer or singular vector information used by the network entity in subsequent PMI processing. The Specification explains that "the output of the encoder 904 at the UE side is L real values represented by s," and that after dequantization "s' represent[s] L real values, prior to decoding." Spec. [0071]-[0072]. The Specification likewise explains that "the PMI encoder 1004 generates L real values for each layer (e.g., s0 for layer 0 and sl layer 1)," while a separate RI classification block generates the soft RI output. Spec. [0074]. The Specification likewise describes that the network entity obtains PMI based on those indications and the fractional RI value. Spec. [0004]-[0005]. Thus, read in light of the amended claim language and the Specification, a person of ordinary skill in the art would understand that the claimed first and second indications represent corresponding real-valued indications for respective layers or singular vectors, with reasonable certainty as to claim scope.”.
Examiner respectfully disagrees. The claim limitations do not clearly define all the parameters and the techniques to obtain those parameters for determining PMI. Lack of definitions and techniques make the claims not clear to understand the inventive concept in line with the specification.
Applicant further argues in Remarks page 10-11 that Yu and Kim does not render obvious the limitation of amended claim.
Examiner respectfully disagrees. Under BRI of the broad limitations of the claim, Yu and Kim suggests the teaching of the claims under obviousness criteria, as explained in the rejection of the claims above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
XIA; Liang, US 20160249244 A1 - INFORMATION NOTIFICATION, INFORMATION REPORTING, AND DATA RECEIVING METHODS AND DEVICES.
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 extension fee 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 date of this final action.
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/MAHBUBUL BAR CHOWDHURY/Primary Examiner, Art Unit 2475
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