CTNF 18/715,440 CTNF 73983 DETAILED ACTION This Office action is a response to an application filed on May 31, 2024. Claims 1-30 are currently pending and ready for examination. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Information Disclosure Statement The information disclosure statement (IDS) submitted on May 31, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner. Claim Rejections - 35 USC § 112 07-34-01 Claim 13 is 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. Claim 13 recites the limitation " the one or more processors, to obtain the performance-complexity tradeoff parameter value, the frequency domain granularity" in lines 1-2. There is insufficient antecedent basis for this limitation in the claim. For the purpose of further examination, this limitation is construed to mean “the one or more processors.” Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. §102 and §103 (or as subject to pre-AIA 35 U.S.C. §102 and §103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. §102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA Claim s 1-5 are rejected under 35 U.S.C. §102(a)(2) as being anticipated by Gan et al . (US Patent Publication No. 2009/0196379) 1 . Regarding claim 1 , Gan et al. discloses a user equipment (UE) for wireless communication ( See, e.g. , Fig. 1, #120; Fig. 4, #420; Fig. 7, #710; and ¶[0063]) , comprising: a memory (Fig. 7, #730; and ¶[0066]) ; and one or more processors, coupled to the memory (Fig. 7, #720; and ¶[0066]) , configured to: obtain one or more of a performance-complexity tradeoff parameter value (“δ,” See , ¶[0035], “where δ with ¼<δ<1 is a factor that can be selected to achieve a good quality-complexity tradeoff.” Alternatively, “ϵ” See , ¶[0043], “where 0<ϵ<1 is a user-defined adjustment factor introduced for further fine-tuning the performance-complexity tradeoff”) associated with a quantity of iterations and channel orthogonality ( See , ¶[0036], size reduction is … a process aimed at making basis vectors … closer to orthogonal …two consecutive basis vectors h k-1 and h k are swapped … size reduction and basis vector swapping steps can then iterate until Equation (9) is satisfied for all pairs of h k-1 and h k ” ) for an algorithm for a lattice reduction ( See, e.g., ¶[0005], “Various systems and methodologies presented herein can utilize a relaxed form of the Lenstra-Lenstra-Lovasz ( LLL ) lattice reduction algorithm”) of a first matrix (“H”, See , ¶[0022], “H is the nxm complex channel matrix”) for a downlink communication ( See , Fig. 1; and ¶[0019]); receive the downlink communication that corresponds to the first matrix ( See , Fig. 5, #502: and ¶[0059], “one or more signals received”) ; perform the lattice reduction to transfer the first matrix to a second matrix based at least in part on the one or more of the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity ( See , Fig. 5, #504; and ¶s[0038] and [0059]) ; and perform multiple-input-multiple-output detection of the downlink communication using the second matrix ( See , Fig. 5, #506; and ¶s[0038] and [0059]) . Regarding claim 2 , because this claim depend from claim 1, and because the additional recitation, “wherein the frequency domain granularity indicates one or more subbands,” is directed to an alternative limitation not considered in the above rejection of claim 1, the additional recitation does not further limit the scope of claim 1 as interpreted in the above rejection of claim 1. Accordingly, claim 2 is anticipated by Gan et al. for the reasons that claim 1 is anticipated. Regarding claim 3 , because this claim depend from claim 1, and because the additional recitation, “wherein the frequency domain granularity corresponds to a precoding resource block granularity,” is directed to an alternative limitation not considered in the above rejection of claim 1, the additional recitation does not further limit the scope of claim 1 as interpreted in the above rejection of claim 1. Accordingly, claim 3 is anticipated by Gan et al. for the reasons that claim 1 is anticipated. Regarding claim 4 , because this claim depend from claim 1, and because the additional recitation, “wherein the frequency domain granularity corresponds to a resource block group associated with a precoding resource block granularity,” is directed to an alternative limitation not considered in the above rejection of claim 1, the additional recitation does not further limit the scope of claim 1 as interpreted in the above rejection of claim 1. Accordingly, claim 4 is anticipated by Gan et al. for the reasons that claim 1 is anticipated. Regarding claim 5 , because this claim depend from claim 1, and because the additional recitation, “wherein the time domain granularity indicates one or more symbols or slots, and wherein the one or more processors, to perform the lattice reduction based at least in part on the time domain granularity, are configured to apply the lattice reduction identically across the one or more symbols or slots,” is directed to an alternative limitation not considered in the above rejection of claim 1, the additional recitation does not further limit the scope of claim 1 as interpreted in the above rejection of claim 1. Accordingly, claim 5 is anticipated by Gan et al. for the reasons that claim 1 is anticipated . 07-15-03-aia AIA Claim s 16-23 and 30 are rejected under 35 U.S.C. §102(a)(2) as being anticipated by Nammi et al . (US Patent Publication No. 2024/0260028) . Regarding claim 16 , Nammi et al. discloses a network entity ( See , e.g., Fig. 1a, “gNB” and Fig. 13a, “Network Node 110”) for wireless communication, comprising: a memory ( See , Fig. 13a, #1360; and ¶[0225]) ; and one or more processors, coupled to the memory (Fig. 13a, #1350; and ¶s[0224]-[0225]) , configured to: generate an indication of one or more of a performance-complexity tradeoff parameter value associated with a quantity of iterations and channel orthogonality for an algorithm for a lattice reduction of a first matrix for a downlink communication, a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction ( See , Fig. 1a, step #14, “MCS, Power, PRBs, etc.”; and ¶[0015]-[0016]) 2 ; transmit the indication ( See , ¶[0016], “The network sends 15 the scheduling parameters to the UE in the downlink control channel.”) ; and transmit the downlink communication ( See, ¶[0016], “After that actual data transfer 16 takes place from network to the UE.”) . Regarding claim 17 , because this claim depend from claim 16, and because the additional recitation, “wherein the frequency domain granularity indicates one or more subcarriers,” is directed to an alternative limitation not considered in the above rejection of claim 16, the additional recitation does not further limit the scope of claim 16 as interpreted in the above rejection of claim 16. Accordingly, claim 17 is anticipated by Nammi et al. for the reasons that claim 16 is anticipated. Regarding claim 18 , because this claim depend from claim 16, and because the additional recitation, “wherein the frequency domain granularity corresponds to a precoding resource block granularity,” is directed to an alternative limitation not considered in the above rejection of claim 16, the additional recitation does not further limit the scope of claim 16 as interpreted in the above rejection of claim 16. Accordingly, claim 17 is anticipated by Nammi et al. for the reasons that claim 16 is anticipated. Regarding claim 19 , because this claim depend from claim 16, and because the additional recitation, “wherein the frequency domain granularity corresponds to a resource block group associated with a precoding resource block granularity,” is directed to an alternative limitation not considered in the above rejection of claim 16, the additional recitation does not further limit the scope of claim 16 as interpreted in the above rejection of claim 16. Accordingly, claim 17 is anticipated by Nammi et al. for the reasons that claim 16 is anticipated. Regarding claim 20 , because this claim depend from claim 16, and because the additional recitation, “wherein the time domain granularity indicates one or more symbols or slots,” is directed to an alternative limitation not considered in the above rejection of claim 16, the additional recitation does not further limit the scope of claim 16 as interpreted in the above rejection of claim 16. Accordingly, claim 17 is anticipated by Nammi et al. for the reasons that claim 16 is anticipated. Regarding claim 21 , Nammi et al. further discloses that the one or more processors, to transmit the indication, are configured to transmit the indication via a downlink grant downlink control information, a radio resource control configuration, or a medium access control element (MAC CE) ( See , ¶[0016], “The network sends 15 the scheduling parameters to the UE in the downlink control channel;” and ¶[0023]) . Regarding claim 22 , Nammi et al. further discloses that the one or more processors, to generate the indication, are configured to generate the indication based at least in part on channel state information or a measurement of a reference signal ( See , Fig. 1a, step 14, “based on the CSI;” and ¶[0015]) . Regarding claim 23 , Nammi et al. further discloses that the indication indicates one or more of a block error rate, a size, a modulation and coding scheme, or channel profile information ( See , ¶[0034], MCS, included in DCI, also indicates the constellation size.) . Regarding claim 30 , Nammi et al. discloses a method of wireless communication ( See , Fig. 1a) performed by a network entity (Fig. 1a, “gNB”) , comprising: generating an indication of one or more of a performance-complexity tradeoff parameter value associated with a quantity of iterations and channel orthogonality for an algorithm for a lattice reduction of a first matrix for a downlink communication, a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction ( See , Fig. 1a, step #14, “MCS, Power, PRBs, etc.”; and ¶[0015]-[0016]. See, also footnote 3 above.) ; transmitting the indication ( See , ¶[0016], “The network sends 15 the scheduling parameters to the UE in the downlink control channel.”) ; and transmitting the downlink communication ( See, ¶[0016], “After that actual data transfer 16 takes place from network to the UE.”) . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1-5, 13, 14 and 29 are rejected under 35 U.S.C. §103 as being unpatentable over Gan et al. in view of Lee et al. (US Patent Publication No. 2014/0341312) . Regarding claim 1 , Gan et al. teaches a user equipment (UE) for wireless communication ( See, e.g. , Fig. 1, #120; Fig. 4, #420; Fig. 7, #710; and ¶[0063]) , comprising: a memory (Fig. 7, #730; and ¶[0066]) ; and one or more processors, coupled to the memory (Fig. 7, #720; and ¶[0066]) , configured to: obtain one or more of a performance-complexity tradeoff parameter value (“δ,” See , ¶[0035], “where δ with ¼<δ<1 is a factor that can be selected to achieve a good quality-complexity tradeoff.” Alternatively, “ϵ” See , ¶[0043], “where 0<ϵ<1 is a user-defined adjustment factor introduced for further fine-tuning the performance-complexity tradeoff”) associated with a quantity of iterations and channel orthogonality ( See , ¶[0036], size reduction is … a process aimed at making basis vectors … closer to orthogonal …two consecutive basis vectors h k-1 and h k are swapped … size reduction and basis vector swapping steps can then iterate until Equation (9) is satisfied for all pairs of h k-1 and h k ” ) for an algorithm for a lattice reduction ( See, e.g., ¶[0005], “Various systems and methodologies presented herein can utilize a relaxed form of the Lenstra-Lenstra-Lovasz ( LLL ) lattice reduction algorithm”) of a first matrix (“H”, See , ¶[0022], “H is the nxm complex channel matrix”) for a downlink communication ( See , Fig. 1; and ¶[0019]); receive the downlink communication that corresponds to the first matrix ( See , Fig. 5, #502: and ¶[0059], “one or more signals received”) ; perform the lattice reduction to transfer the first matrix to a second matrix based at least in part on the one or more of the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity ( See , Fig. 5, #504; and ¶s[0038] and [0059]) ; and perform multiple-input-multiple-output detection of the downlink communication using the second matrix ( See , Fig. 5, #506; and ¶s[0038] and [0059]) . Gan et al. , however, fails 3 to explicitly teach that the UE is configured to obtain a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction. Lee et al. teaches a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction ( See , ¶s[0005]-[0007], “The spatial channel matrix (or channel matrix) can be represented as follows.” PNG media_image1.png 147 317 media_image1.png Greyscale “i represents an OFDM (or SC-FDMA) symbol index and k represents a subcarrier index.” Lee et al. thus teaches that the channel matrix H is applicable for i number of symbols and k number of subcarriers, that is across all resources allocated for the downlink channel by the network. That is, the UE needs to receive and detect (using the matrix H), all of the i symbols across all of k subcarriers. See, also, below footnote 3) . 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]). Regarding claim 2 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Lee et al. further teaches that the frequency domain granularity indicates one or more subbands ( See , e.g., ¶[0016], “the frequency granularity of the second precoding matrix may be subband.”) , and wherein the one or more processors, to perform the lattice reduction based at least in part on the frequency domain granularity, are configured to apply the lattice reduction identically across the one or more subbands ( See , ¶[0105], “A first precoding matrix index corresponding to the determined n 1 or n 2 and a second precoding matrix index corresponding to α or β can be selected for different frequency granularities or selected with different time periods”. While this cited portion discussed the concept of precoding resource group (PRG), i.e., in the context of a precoding matrix rather than a channel matrix, as discussed above, to the extent one or more subbands can be differentiated for the purpose of determining the precoding matrices, as discussed above in footnote 3, the channel matrix H would be applicable across the subbands, and the lattice reduction taught by Gan et al. would be performed on the channel matrix H as a whole.) . 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]). Regarding claim 3 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Lee et al. further teaches that the frequency domain granularity corresponds to a precoding resource block granularity ( See , Lee et al., ¶[0105], As discussed above, Lee et al. teaches the grouping of resources for the purposes of precoding matrices, which group(s) as also discussed above, would all be detected by applying a channel matrix H, which is subjected to the lattice reduction taught by Gan et al. ). 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect a PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]). Regarding claim 4 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Lee et al. teaches that the frequency domain granularity corresponds to a resource block group associated with a precoding resource block granularity ( See , ¶[0105] and the discussion above in connection to claim 3). 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect a PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]). Regarding claim 5 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Lee et al. teaches that the time domain granularity indicates one or more symbols or slots, and wherein the one or more processors, to perform the lattice reduction based at least in part on the time domain granularity, are configured to apply the lattice reduction identically across the one or more symbols or slots ( See , Lee et al., ¶s[0005]-[0007], “i represents an OFDM (or SC-FDMA) symbol index,” See, discussion above in connection to claim 1. The subject of the lattice reduction, i.e., the channel matrix H, is applicable for detection of i number of symbols) . 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect a PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]). Regarding claim 13 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Gan et al. further teaches that the one or more processors, to obtain the performance-complexity tradeoff parameter value, the frequency domain granularity, are configured to perform machine learning with one or more model inputs ( See , ¶[0058], “Furthermore, as will be appreciated various portions of the disclosed systems above and methods below may include or consist of artificial intelligence or knowledge or rule based components.” Gan et al. teaches, for example, when performing the machine learning with respect to the lattice reduction, the estimated channel matrix H could be an input for such machine learning model. See, e.g., Gan et al., ¶[0025], “a lattice reduction component 240 can be utilized … to analyze channel matrices obtained by channel estimation component 230 and obtain reduced lattice bases for those channel matrices that can be more efficiently utilized by the signal detection component 220”) . Regarding claim 14 . Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 13 as discussed above. Lee et al. further teaches that the one or more model inputs include one or more of: packet data protocol information, a coarse frequency selectivity level, an actual frequency selectivity level, a coarse channel singularity level, an actual channel singularity level, coarse Doppler information, actual Doppler information, coarse Doppler spread information, actual Doppler spread information, channel coherence time information, a target block error rate, a constellation size, a modulation and coding scheme, a quantity of layers, a quantity of receive antennas, or a history of channel measurements ( See , ¶[0005], “r is an Rx antenna index,” corresponding to the claim limitation, a quantity of receive antennas. The number of receiving antennas would be used for a channel estimation model, for example) . 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 machine learning model UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to determine a channel matrix taking into account the number of receive antennas. Regarding claim 29 , Gan et al. teaches a method of wireless communication (Fig. 5) performed by a user equipment (UE) ( See, e.g. , Fig. 1, #120; Fig. 4, #420; Fig. 7, #710; and ¶[0063]) , comprising: obtaining one or more of a performance-complexity tradeoff parameter value (“δ,” See , ¶[0035], “where δ with ¼<δ<1 is a factor that can be selected to achieve a good quality-complexity tradeoff.” Alternatively, “ϵ” See , ¶[0043], “where 0<ϵ<1 is a user-defined adjustment factor introduced for further fine-tuning the performance-complexity tradeoff”) associated with a quantity of iterations and channel orthogonality ( See , ¶[0036], size reduction is … a process aimed at making basis vectors … closer to orthogonal …two consecutive basis vectors h k-1 and h k are swapped … size reduction and basis vector swapping steps can then iterate until Equation (9) is satisfied for all pairs of h k-1 and h k ” ) for an algorithm for a lattice reduction ( See, e.g., ¶[0005], “Various systems and methodologies presented herein can utilize a relaxed form of the Lenstra-Lenstra-Lovasz ( LLL ) lattice reduction algorithm”) of a first matrix (“H”, See , ¶[0022], “H is the nxm complex channel matrix”) for a downlink communication ( See , Fig. 1; and ¶[0019]); receiving the downlink communication that corresponds to the first matrix ( See , Fig. 5, #502: and ¶[0059], “one or more signals received”) ; performing the lattice reduction to transfer the first matrix to a second matrix based at least in part on the one or more of the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity ( See , Fig. 5, #504; and ¶s[0038] and [0059]) ; and performing multiple-input-multiple-output detection of the downlink communication using the second matrix ( See , Fig. 5, #506; and ¶s[0038] and [0059]) . Gan et al. , however, fails to explicitly teach that the UE is configured to obtain a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction ( See , footnote 3 above) . Lee et al. teaches a frequency domain granularity for the lattice reduction, or a time domain granularity for the lattice reduction ( See , ¶s[0005]-[0007], “The spatial channel matrix (or channel matrix) can be represented as follows.” PNG media_image1.png 147 317 media_image1.png Greyscale “i represents an OFDM (or SC-FDMA) symbol index and k represents a subcarrier index.” Lee et al. thus teaches that the channel matrix H is applicable for i number of symbols and k number of subcarriers, that is across all resources allocated for the downlink channel by the network. That is, the UE needs to receive and detect (using the matrix H), all of the i symbols across all of k subcarriers. See, also, footnote 3 above) . 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 UE taught by Gan et al. to incorporate the above teaching of Lee et al in order for such UE to be able to receive and detect PDSCH in compliance to the 3GPP specifications, which compliance is also contemplated by Lee et al. ( See, e.g ., Lee et al. ¶[0028]) . 07-21-aia AIA Claim s 6, 9 and 10-12 are rejected under 35 U.S.C. §103 as being unpatentable over Gan et al. and Lee et al . in further view of Nammi et al . Regarding claim 6 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above, but fails to explicitly teach that the one or more processors [of the UE], to perform the lattice reduction, are configured to perform the lattice reduction based at least in part on a determination that the downlink communication includes a demodulation reference signal. Nammi et al. teaches the one or more processors, to perform the lattice reduction, are configured to perform the lattice reduction based at least in part on a determination that the downlink communication includes a demodulation reference signal ( See , ¶[0017], “In 5G ….Demodulation reference signals (DM-RS also referred to as DMRS)….. are specifically intended to be used by UEs for channel estimat ion for data channel.” As the determination of channel matrix H (the first matrix in claim 1), i.e., a channel estimation, is based on the DMRS for 5G, it follows that the lattice reduction, an iterative operations on the vectors of the matrix H, is also necessarily based on the DMRS.) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Nammi et al in order ensure so modified UE would be compatible to the downlink communication scheme specified in the 3GPP specifications, including the 5G NR, which compliance is also contemplated by Nammi et al. ( See, e.g ., Nammi et al. ¶[0006]). Regarding claim 9 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above, but fails to explicitly teach that the one or more processors, to obtain the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity, are configured to receive an indication of the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity via a downlink grant downlink control information, a radio resource control configuration, or a medium access control element (MAC CE). Nammi et al . teaches that the one or more processors, to obtain the performance-complexity tradeoff parameter value, the frequency domain granularity, or the time domain granularity, are configured to receive an indication ( See , ¶[0034]. See also Applicant’s disclosure at ¶[0137]) of the performance-complexity tradeoff parameter value, the frequency domain granularity ( See , ¶[0028]) , or the time domain granularity ( See , ¶[0029]) via a downlink grant downlink control information, a radio resource control configuration, or a medium access control element (MAC CE) ( See , ¶[0024]) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Nammi et al in order ensure so modified UE would be compatible to the downlink communication scheme specified in the 3GPP specifications, including the 5G NR, which compliance is also contemplated by Nammi et al. ( See, e.g ., Nammi et al. ¶[0006]). Regarding claim 10 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above, but fails to explicitly teach that the one or more processors are configured to receive an indication of one or more of a block error rate, a constellation size, a modulation and coding scheme, or channel profile information. Nammi et al . teaches that the one or more processors are configured to receive an indication of one or more of a block error rate, a constellation size, a modulation and coding scheme, or channel profile information ( See , ¶[0034], teaching the MCS included in DCI, thus the constellation size is taught as well) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Nammi et al in order ensure so modified UE would be compatible to the downlink communication scheme specified in the 3GPP specifications, including the 5G NR, which compliance is also contemplated by Nammi et al. ( See, e.g ., Nammi et al. ¶[0006]). Regarding claim 11 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above, but fails to explicitly teach that the performance-complexity tradeoff parameter value is specific to a frequency subband, a bandwidth part, or a serving cell. Nammi et al. teaches that the performance-complexity tradeoff parameter value is specific to a frequency subband, a bandwidth part, or a serving cell ( See , ¶s[0023], [0024] and [0027], showing DCI including an indication for the active BWP for a PDSCH. As discussed above, in connection to claim 1, the channel matrix H (and the lattice reduction thereof) is applicable for the PDSCH, and is thus specific to the active BWP) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Nammi et al. in order ensure so modified UE would be compatible to the downlink communication scheme specified in the 3GPP specifications, including the 5G NR, which compliance is also contemplated by Nammi et al. ( See, e.g ., Nammi et al. ¶[0006]). Regarding claim 12 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Gan et al. further teach the performance-complexity tradeoff parameter value is associated with (“a communication dimension.” Gan et al . clearly recognizes the complexity of the lattice reduction increases proportionally with the communication dimension. See , Gan et al ., ¶[0003] “the lattice reduction complexity of conventional lattice-based signal detection techniques often dominates the overall detection complexity,” and such dominance “generally becomes more significant as the dimension of the associated communication system increases.” Gan et al . further teaches that a constellation size is a factor to be considered in a lattice reduction based channel detection See , Gan et al., ¶[0039]. Accordingly, Gan et al., teaches that the communication dimension is a factor that needs to be considered when making the performance-complexity trade off, i.e., selecting the “δ,” and thus teaches the association of the δ with the communication dimension) . Gan et al. and Lee et al. , however, fail to explicitly teach that such communication dimension is a constellation size or a quantity of layers. Nammi et al. further teaches one or more of a constellation size or a quantity of layers (being provided by a network to a UE. See , Nammi et al., ¶[0023], “The Physical Downlink Control Channel (PDCCH) carries information …. comprises the number of MIMO layers scheduled” and ¶[0034], “ Modulation and coding scheme,” which defines the constellation size.) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to recognize that the constellation size and the number of MIMO layers taught by Nammi et al. would be utilizable by a UE in order to determine the communication dimension taught by Gan et al ., and associate the same to the performance-complexity tradeoff value, such association as also taught by Gan et al . 07-21-aia AIA Claim s 7 and 8 are rejected under 35 U.S.C. §103 as being unpatentable over Gan et al. and Lee et al . in further view of Bhattad et al . (US Patent Publication No. US 2021/0051052) . Regarding claim 7 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Gan et al. teaches one or more processors configured to perform a lattice reduction ( See, Gan et al. Fig. 7, #720; ¶[0066]; and ¶[0005], “the Lenstra-Lenstra-Lovasz ( LLL ) lattice reduction algorithm”) . Gan et al. further teaches that the lattice reduction is performed on the channel matrix obtained during a channel estimation, in order to improve the detection of the received signal ( See, Gan et al., ¶[0025], “to reduce the required complexity of the signal detection component 220 and/or to improve the performance of the signal detection component 220, a lattice reduction component 240 can be utilized at station 200 to analyze channel matrices obtained by channel estimation component 230 and obtain reduced lattice bases for those channel matrices that can be more efficiently utilized by the signal detection component 220”) . Gan et al. and Lee et al. , however, fails to explicitly teach that such lattice reduction is performed based at least in part on a determination that the downlink communication does not include multiple demodulation reference signals. Bhattad et al. teaches performing a channel estimation based at least in part on a determination that the downlink communication does not include multiple demodulation reference signals ( Bhattad et al. teaches that; i) for a type-B, the PDSCH length can be configured to be L=2, 4 or 7, ii) a double symbol DMRS is supported only when L=7 (See, ¶[0065]); and iii) for the cases of L=2 or L=4, not performing the channel estimation, but to rely on a previously obtained channel estimation. See , ¶[0066], “Moreover, double symbol DMRS may not be supported for various durations of Type-B PDSCH. It may be advantageous to reuse existing channel estimate interpolation tables that may correspond to existing time domain resource patterns ,” Emphasis added . Accordingly, when a PDSCH is determined not containing multiple DMRS symbols, a channel estimation would be performed. A lattice reduction would be performed on the channel matrix resulting from the channel estimation as taught by Gan et al. ) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Bhattad et al in order enhance the detection of the type-B PDSCH, e.g., which type is utilized in 5G NR ( See, e.g ., Bhattad et al. ¶[0064]). Regarding claim 8 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 1 as discussed above. Gan et al. teaches one or more processors configured to perform the lattice reduction ( See, Gan et al. Fig. 7, #720; ¶[0066]; and ¶[0005], “Various systems and methodologies presented herein can utilize a relaxed form of the Lenstra-Lenstra-Lovasz ( LLL ) lattice reduction algorithm”) . Gan et al. further teaches that the lattice reduction is performed on the channel matrix obtained during a channel estimation, in order to improve the detection of the received signal ( See, Gan et al., ¶[0025], “to reduce the required complexity of the signal detection component 220 and/or to improve the performance of the signal detection component 220, a lattice reduction component 240 can be utilized at station 200 to analyze channel matrices obtained by channel estimation component 230 and obtain reduced lattice bases for those channel matrices that can be more efficiently utilized by the signal detection component 220”) . Gan et al. and Lee et al. , however, fails to explicitly teach disabling a lattice reduction of a next downlink communication based at least in part on a determination that the next downlink communication includes multiple demodulation reference signals. Bhattad et al. teaches disabling a channel estimation a next downlink communication based at least in part on a determination that the next downlink communication includes multiple demodulation reference signals ( Bhattad et al. teaches that; i) for a type-B, the PDSCH length can be configured to be L=2, 4 or 7, ii) a double symbol DMRS is supported only when L=7 (See, ¶[0065]); and iii) for the cases of L=2 or L=4, not performing the channel estimation, but to rely on a previously obtained channel estimation. See , ¶[0066], “Moreover, double symbol DMRS may not be supported for various durations of Type-B PDSCH. It may be advantageous to reuse existing channel estimate interpolation tables that may correspond to existing time domain resource patterns ,” Emphasis added . Accordingly, when a PDSCH is determined containing multiple DMRS symbols, a channel estimation would not be performed. A lattice reduction also would not be performed because there would be no new channel matrix upon which to perform the lattice reduction. Such non-performance of a channel estimation, according to Bhattad et al. would be advantageous for all PDSCH containing multiple symbol DMRS, whenever such PDSCH occurs.) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Bhattad et al in order enhance the detection of the type-B PDSCH, e.g., which type is utilized in 5G NR ( See, e.g ., Bhattad et al. ¶[0064]) . 07-21-aia AIA Claim 15 is rejected under 35 U.S.C. §103 as being unpatentable over Gan et al. and Lee et al . in further view of Mu (US Patent Publication No. 2025/0048137) . Regarding claim 15 , Gan et al. and Lee et al. teach a UE for wireless communication comprising all elements recited in claim 13 as discussed above, but fail to explicitly teach that the one or more processors are configured to receive one or more models for the machine learning. Mu teaches one or more processors (Fig. 11, #820, ¶[0294]) configured to receive one or more models for the machine learning ( See , Abstract, “an Artificial Intelligence (AI) model to perform channel estima tion;” Fig. 6; and ¶[0137]) . 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 UE taught by Gan et al. and Lee et al. to incorporate the above teaching of Mu in order enhance the channel estimation, which can adapt to different PRB bundling configuration, e.g., utilized in 5G NR ( See, e.g ., Mu ¶[0004]) . 07-21-aia AIA Claim s 24-27 are rejected under 35 U.S.C. §103 as being unpatentable over Nammi et al . in view of Gan et al . Regarding claim 24 , Nammi et al. teach a network entity comprising all elements recited in claim 16 as discussed above. Nammi et al. further teaches a transmission of a PDSCH is specific to a bandwidth part ( See , Nammi et al. , ¶s[0023], [0024] and [0027], showing DCI including an indication for the active BWP for a PDSCH) . Nammi et al. , but fails to explicitly teach a performance-complexity tradeoff parameter value is specific to the transmission of the PDSCH. Gan et al. teaches a performance-complexity tradeoff parameter value is specific to the transmission of the PDSCH (“δ,” See , ¶[0035], “where δ with ¼<δ<1 is a factor that can be selected to achieve a good quality-complexity tradeoff.” Alternatively, “ϵ” See , ¶[0043], “where 0<ϵ<1 is a user-defined adjustment factor introduced for further fine-tuning the performance-complexity tradeoff.” As discussed in footnote 3 above, a channel matrix H (the lattice reduction, and the performance-complexity tradeoff parameter value (δ) thereof) is useable for detection of a PDSCH, which is specific to an active BWP as taught by Nammi et al.) . 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 network entity taught by Nammi et al. to incorporate the above teaching of Gan et al. in order for such modified network entity to enable UEs with which it communicates an improved channel estimation (and PDSCH detection) with reduced complexity ( See, e.g ., Gan et al. ¶[0003]). Regarding claim 25 , Nammi et al. and Gan et al. teach a network entity comprising all elements recited in claim 16 as discussed above. Gan et al. further teach the performance-complexity tradeoff parameter value is associated with a communication dimension ( See , Gan et al ., ¶[0003] “the lattice reduction complexity of conventional lattice-based signal detection techniques often dominates the overall detection complexity,” and such dominance “generally becomes more significant as the dimension of the associated communication system increases.” That is, Gan et al., teaches that the communication dimension is a factor that needs to be considered when making the performance-complexity trade off, i.e., when selecting the “δ”) . Nammi et al. further teaches one or more of a constellation size or a quantity of layers ( See , Nammi et al., ¶[0023], “The Physical Downlink Control Channel (PDCCH) carries information …. comprises the number of MIMO layers scheduled” and ¶[0034], “ Modulation and coding scheme,” i.e., which defines the constellation size. As these parameters, the constellation size and the number of layers, are information a UE would use to gauge the communication dimension, the UE would consider the parameters when selecting the performance-complexity trade off parameter value) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to recognize that the constellation size and the number of MIMO layers taught by Nammi et al. would be utilizable by a UE in order to determine the communication dimension taught by Gan et al ., and associate the same to the performance-complexity tradeoff value, such association being taught by Gan et al. Regarding claim 26 , Nammi et al. and Gan et al. teach a network entity comprising all elements recited in claim 16 as discussed above. Gan et al. further teaches that the one or more processors, to generate the indication, are configured to perform machine learning with one or more model inputs ( See , ¶[0058], “Furthermore, as will be appreciated various portions of the disclosed systems above and methods below may include or consist of artificial intelligence or knowledge or rule based components.” Gan et al. teaches, for example, when performing the machine learning with respect to the lattice reduction, the estimated channel matrix H could be an input for such machine learning model. See, e.g., Gan et al., ¶[0025], “a lattice reduction component 240 can be utilized … to analyze channel matrices obtained by channel estimation component 230 and obtain reduced lattice bases for those channel matrices that can be more efficiently utilized by the signal detection component 220”) . 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 network entity taught by Nammi et al. to incorporate the above teaching of Gan et al. in order for such modified network entity to enable UEs with which it communicates an improved channel estimation (and PDSCH detection) with reduced complexity ( See, e.g ., Gan et al. ¶[0003]). Regarding claim 27 , Nammi et al. and Gan et al. teach a network entity comprising all elements recited in claim 26 as discussed above. Nammi et al. further teaches that the one or more model inputs include one or more of: packet data protocol information, a coarse frequency selectivity level, an actual frequency selectivity level, a coarse channel singularity level, an actual channel singularity level, coarse Doppler information, actual Doppler information, coarse Doppler spread information, actual Doppler spread information, channel coherence time information, a target block error rate, a constellation size, a modulation and coding scheme, a quantity of layers, a quantity of receive antennas, or a history of channel measurements ( See , ¶[0005], “r is an Rx antenna index,” corresponding to the claim limitation, a quantity of receive antennas. The number of receiving antennas would be used for a channel estimation model, for example). 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 network entity taught by Nammi et al. to incorporate the above teaching of Gan et al. in order for such modified network entity to enable UEs with which it communicates an improved channel estimation (and PDSCH detection) with reduced complexity ( See, e.g ., Gan et al. ¶[0003]) . 07-21-aia AIA Claim 28 is rejected under 35 U.S.C. §103 as being unpatentable over Nammi et al . and Gan et al . in view of Mu . Regarding claim 28 , Nammi et al. and Gan et al. teach a network entity comprising all elements recited in claim 26 as discussed above. Gan et al. teaches further a user equipment obtaining a performance-complexity tradeoff parameter value (utilizing a machine learning model. See , Gan et al. , ¶[0035], “δ,” and ¶[0058]) . Nammi et al. and Gan et al. , however, fails to explicitly teach that the one or more processors are configured to transmit one or more machine learning models [to] a user equipment. Mu teaches one or more processors (Fig. 12, #922, ¶[0304]) configured to transmit one or more machine learning models to a user equipment ( See , Abstract, “an Artificial Intelligence (AI) model to perform channel estima tion;” Fig. 6; and ¶[0137]) . 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 UE taught by Nammi et al. and Gan et al. to incorporate the above teaching of Mu in order enhance the channel estimation, which can adapt to different PRB bundling configuration, e.g., utilized in 5G NR, by adaptably providing the appropriate model to the UE ( See, e.g ., Mu ¶[0004]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to KI S KIM whose telephone number is (571)272-9141. The examiner can normally be reached M-Th 7:00AM - 5:30PM. 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, Moo R Jeong can be reached at (571) 272-9617. 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. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /K.S.K./Examiner, Art Unit 2418 April 17, 2026 /Moo Jeong/Supervisory Patent Examiner, Art Unit 2418 Application/Control Number: 18/715,440 Page 2 Art Unit: 2418 Application/Control Number: 18/715,440 Page 3 Art Unit: 2418 Application/Control Number: 18/715,440 Page 4 Art Unit: 2418 Application/Control Number: 18/715,440 Page 5 Art Unit: 2418 Application/Control Number: 18/715,440 Page 6 Art Unit: 2418 Application/Control Number: 18/715,440 Page 7 Art Unit: 2418 Application/Control Number: 18/715,440 Page 8 Art Unit: 2418 Application/Control Number: 18/715,440 Page 9 Art Unit: 2418 Application/Control Number: 18/715,440 Page 10 Art Unit: 2418 Application/Control Number: 18/715,440 Page 11 Art Unit: 2418 Application/Control Number: 18/715,440 Page 12 Art Unit: 2418 Application/Control Number: 18/715,440 Page 14 Art Unit: 2418 Application/Control Number: 18/715,440 Page 15 Art Unit: 2418 Application/Control Number: 18/715,440 Page 16 Art Unit: 2418 Application/Control Number: 18/715,440 Page 17 Art Unit: 2418 Application/Control Number: 18/715,440 Page 18 Art Unit: 2418 Application/Control Number: 18/715,440 Page 19 Art Unit: 2418 Application/Control Number: 18/715,440 Page 20 Art Unit: 2418 Application/Control Number: 18/715,440 Page 21 Art Unit: 2418 Application/Control Number: 18/715,440 Page 22 Art Unit: 2418 1 Because the limitations: i) a frequency domain granularity for the lattice reduction; and ii) a time domain granularity for the lattice reduction, are recited in the alternative manner, these limitations need not be disclosed in order for the claims to be anticipated. 2 1) The recited limitation “an indication of one or more of a performance-complexity tradeoff parameter value associated with a quantity of iterations and channel orthogonality for an algorithm for a lattice reduction of a first matrix for a downlink communication” is construed, in light of Applicant’s disclosure at ¶¶[0095] and [0137], as an indication for a UE for performing a lattice reduction, and to encompass one or more of a BLER, a [constellation] size, an MCS, or channel profile information; and 2) Because the limitations: i) a frequency domain granularity for the lattice reduction; and ii) a time domain granularity for the lattice reduction, are recited in the alternative manner, these limitations need not be disclosed in order for the claims to be anticipated. 3 It should be noted that Gan et al. does discuss a “flat fading” assumption for a channel, and that the channel matrix H is used to model, “[i]n full,” such channel ( See , Gan et al. ¶[0022]) . As suggested by Gan et al. a channel matrix represents the physical “fading’ condition for each of the possible communication paths between the transmit and receive antennas, such condition is assumed stable over a period of time. It should also be noted that, to the extent Applicant’s claim 1 language contemplates the UE receiving a “downlink communication that corresponds to the first matrix,” and using the first matrix for detecting such downlink communication received, it follows that it would be necessary that the resource allocation for the downlink communication must have been made in order for the UE to so receive. The resource allocation is typically provided for the downlink communication, i.e., PDSCH(s) in LTE and 5G NR, by the network, e.g., through the PDCCH or DCI.
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