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
Applicant's amendment filed on 06/08/2026 has been entered. Claims 11-12 have been amended. No claims have been added or cancelled. Claims 1-18 are still pending in this application, of which claims 1-10 were withdrawn from consideration.
Response to Arguments
Applicant’s arguments with respect to claim(s) 11-18 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 102
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.
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 –
(a)(2) the claimed invention was described in a patent issued under section 151, 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.
Claim(s) 11 and 14-15 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Timo et al. (US 2024/0275519; hereinafter Timo). Note: Subject matter relied upon the in rejection is fully supported in the provisional application 63/215,081 of Timo.
Regarding claim 11, Timo shows a communication device (Figures 6 and 12 shows a RAN node/eNB performing in part the method of Figure 7.) comprising:
a receiver (Figure 12 shows RAN node/eNB includes a radio front-end circuitry.) configured to receive a superposition of sounding reference signals sent by a plurality of other communication devices (Figure 5-7; Par. 0120-0127, 0133; UL SRSs received from multiple UEs make up the dataset(s) used for training the ML-based decoder, wherein an importance weight for each dataset sample is considered.); and
a processor (Figure 12 shows eNB includes a processing circuitry.) configured to:
control a neural network trained to perform joint user separation and channel estimation (Figure 5-7; Par. 0120-0127, 0133; note ML-based decoder training considers the measurements of UL SRSs received from multiple UEs and further determines estimates of the UL channel from the UEs based on the measurements.), to determine, for each of the plurality of other communication devices, channel estimates from the superposition of sounding reference signals (Figure 5-7; Par. 0120-0127, 0133; note RAN node performs measurements of UL SRSs received from multiple UEs and further determines estimates of the UL channel from the UEs based on the measurements.);
supply an input according to the received superposition of sounding reference signals to the neural network (Figure 7; Par. 0148-0149, 0152; where for each of the one or more UEs, the RAN node can obtain estimates of one or more UL channels from the UE to the RAN node based on the UL RS measurements (e.g., obtained in block 750). In such case, training the one or more RAN node decoders in block 770 is based on the UL channel estimates for the respective UEs.); and
perform radio communication signal processing in accordance with the channel estimates output by the neural network in response to the input (Figure 7; Par. 0168-0169; where using a trained RAN node decoder, the RAN node can estimate an UL channel from one of the UEs to the RAN node based on further feedback from the UE that represents the DL channel from the RAN node to the UE and that is encoded by a UE encoder corresponding to the trained RAN node decoder.).
Regarding claim 14, Timo shows wherein the communication device is a base station (Figures 6 and 12 shows a RAN node/eNB performing in part the method of Figure 7.).
Regarding claim 15, Timo shows wherein the receiver is configured to receive the superposition of sounding reference signals via each of a plurality of receive antennas resulting in a superposition of sounding reference signals for each receive antenna (Figure 5-7; Par. 0124, 0221; the training can be based on data collected for multiple UEs that are served by the RAN node, e.g., in a cell. In some embodiments, multiple logs from different UEs and cells can be combined into larger datasets for training, validating, and testing decoders. In various embodiments, datasets can be collated over one or more UE's (using the same encoders), over multiple days, and over multiple cell sites using the same antenna array.) and wherein the processor is configured to generate the input to the neural network from the superpositions of sounding reference signals received for the receive antennas (Figure 7; Par. 0148-0149, 0152; where for each of the one or more UEs, the RAN node can obtain estimates of one or more UL channels from the UE to the RAN node based on the UL RS measurements (e.g., obtained in block 750). In such case, training the one or more RAN node decoders in block 770 is based on the UL channel estimates for the respective UEs.).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 12-13 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Timo in view of Chandrasekhar et al. (US 2019/0277957; hereinafter Chandrasekhar).
Regarding claim 12, Timo shows all of the elements except wherein the channel estimates comprise at least one of a channel frequency response, a channel frequency response averaged over multiple subcarriers, channel frequency responses for the plurality of other communication devices, and compressed channel frequency responses.
However, the above-mentioned claim limitations are well-established in the art as evidenced by Chandrasekhar. Specifically, Chandrasekhar shows wherein the channel estimates comprise at least one of a channel frequency response (Figure 9; Par. 0091-0098; the category output by the ML classifier includes at least one an estimate of either a Doppler frequency or a range of Doppler frequency of a dominant Radio Frequency (RF) propagation path. The Doppler frequency or a range of Doppler frequency of a dominant Radio Frequency (RF) propagation path is based at least in part on the Doppler PSD of the SRS signals.), a channel frequency response averaged over multiple subcarriers, channel frequency responses for the plurality of other communication devices, and compressed channel frequency responses
In view of the above, having the system of Timo, then given the well-established teaching of Chandrasekhar, it would have been obvious before the effective filing date of the claimed invention to modify the system of Timo as taught by Chandrasekhar, in order to provide motivation to provide localized frequency scheduling so as to maximize the system spectral efficiency (Par. 0003 of Chandrasekhar).
Regarding claim 13, Timo shows all of the elements except wherein the neural network is a recurrent neural network.
However, the above-mentioned claim limitations are well-established in the art as evidenced by Chandrasekhar. Specifically, Chandrasekhar shows wherein the neural network is a recurrent neural network (Par. 0123; recurrent neural network utilized.).
In view of the above, having the system of Timo, then given the well-established teaching of Chandrasekhar, it would have been obvious before the effective filing date of the claimed invention to modify the system of Timo as taught by Chandrasekhar, in order to provide motivation to provide localized frequency scheduling so as to maximize the system spectral efficiency (Par. 0003 of Chandrasekhar).
Regarding claim 17, Timo shows all of the elements except wherein the superposition of sounding reference signals comprises a signal component for each of a plurality of subcarriers.
However, the above-mentioned claim limitations are well-established in the art as evidenced by Chandrasekhar. Specifically, Chandrasekhar shows wherein the superposition of sounding reference signals comprises a signal component for each of a plurality of subcarriers (Par. 0115; the extracted features are outputs of a linear or non-linear function of real and imaginary portions of channel measurements derived from UL SRS measurements per transmit and receive antenna pair during each UL SRS transmission occasion, wherein the linear or non-linear function comprises a pre-processing process of applying a fusion function of the real and imaginary portions of the channel measurements, wherein the fusion function is configured to output the real and imaginary portions of the channel measurements in a frequency domain, or a subcarrier domain.).
In view of the above, having the system of Timo, then given the well-established teaching of Chandrasekhar, it would have been obvious before the effective filing date of the claimed invention to modify the system of Timo as taught by Chandrasekhar, in order to provide motivation to provide localized frequency scheduling so as to maximize the system spectral efficiency (Par. 0003 of Chandrasekhar).
Regarding claim 18, Timo shows all of the elements except wherein the processor is configured to divide, for each of the other communication devices, the superposition of sounding reference signals by the sounding reference signal sent by the other communication device, wherein the input comprises the results of the division for each of the other communication devices.
However, the above-mentioned claim limitations are well-established in the art as evidenced by Chandrasekhar. Specifically, Chandrasekhar shows wherein the processor is configured to divide, for each of the other communication devices, the superposition of sounding reference signals by the sounding reference signal sent by the other communication device, wherein the input comprises the results of the division for each of the other communication devices (Figure 7; Par. 0080-0083; the input features to the AI classifier are derived from the SRS measurements spaced P ms apart where P is the spacing between consecutive SRS transmissions. The dataset comprising the input features are divided into a training dataset for a training phase and a test dataset for a test phase. The flowchart is divided into a training stage (steps 740 and 750) and a test stage (steps 760 and 770).).
In view of the above, having the system of Timo, then given the well-established teaching of Chandrasekhar, it would have been obvious before the effective filing date of the claimed invention to modify the system of Timo as taught by Chandrasekhar, in order to provide motivation to provide localized frequency scheduling so as to maximize the system spectral efficiency (Par. 0003 of Chandrasekhar).
Claim(s) 16 is rejected under 35 U.S.C. 103 as being unpatentable over Timo in view of Wang et al. (US 2023/0082795; hereinafter Wang).
Regarding claim 16, Timo shows all of the elements except wherein the processor is configured to compress the superpositions of sounding reference signals received for the receive antennas to superpositions of sounding reference signals received for a set of virtual antennas with a lower number than the number of receive antennas and to generate the input to the neural network from the superpositions of sounding reference signals received for the set of virtual antennas.
However, the above-mentioned claim limitations are well-established in the art as evidenced by Wang. Specifically, Wang shows wherein the processor is configured to compress the sounding reference signals received for the receive antennas to sounding reference signals received for a set of virtual antennas with a lower number than the number of receive antennas and to generate the input to the neural network from the sounding reference signals received for the set of virtual antennas (Figure 10; Par. 0116, 0134-0137, 0145; The gNB 102 can check one or more power statistics of each antenna and determine whether this antenna will be selected. Given the power statistics of antennas, the gNB 102 can either pick Y.sub. 1 antennas with the largest power statistics or pick antennas with power statistics satisfying certain criterion. Given the received SRS signals 605, the TdXcorr function, the TdACF function, and the power fluctuation on different antennas can be used for the channel classification operation 640. Additionally or alternatively, the features 635 derived from TdXcorr, TdACF and power fluctuation on different antennas can be used for the channel classification operation 640. By using the features 635 instead of raw TdXcorr, TdACF and power fluctuation on different antennas, the channel classification operation 640 can be performed using simpler machine learning (ML) tools.).
In view of the above, having the system of Timo, then given the well- established teaching of Wang, it would have been obvious before the effective filing date of the claimed invention to modify the system of Timo as taught by Wang, in order to provide motivation to reduce the computational complexity for ML applications (Par. 0103 of Wang).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20250030612 A1 - METHODS, DEVICES, AND MEDIUM FOR COMMUNICATION
US 20240283509 A1 - COMBINING PROPRIETARY AND STANDARDIZED TECHNIQUES FOR CHANNEL STATE INFORMATION (CSI) FEEDBACK
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REDENTOR M PASIA whose telephone number is (571)272-9745. The examiner can normally be reached Mondays-Fridays 5am-245pm.
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/REDENTOR PASIA/Primary Examiner, Art Unit 2413
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