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 .
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 (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.
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 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.
Claims 1, 6, 13 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Singh et al. (US 20190386759 A1) in view of Hess et al. (US 20210367681 A1).
Regarding claim 1, Singh teaches a system (Fig. 1), comprising: a processor and a memory (Fig. 11), the memory storing instructions executable by the processor (Fig. 11), including instructions to: obtain a sample of a first received signal (Fig. 5, S510 and Pars. 23-25); extract a suspected interference characteristic from the sample (Fig. 5, S530 Par. 81); generate a parameter for input to (Fig. 5, S550 and Par. 51-53, ML model (machine learning application) performs (generates) priority or weight (parameter)), the input parameter including a weight or a setting (Par. 53); and transmit a first request to a transmitter of the first received signal to modify a parameter of the transmitter responsive to the input parameter (Fig. 5 and Par. 97, an infrastructure element (transmitter)).
Singh does not mention a layer of the ML model.
However, it is very well-known the ML model has at least a layer for receiving and processing the input as taught by Hess (Fig. 3 and Par. 30).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the above teaching as taught Hess into Singh to process data.
Regarding claim 6, method of claim 6 is performed by the apparatus of claim 1. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 1.
Regarding claim 13, system of claim 13 is performed by the apparatus of claim 1. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 1.
Regarding claim 17, the modified Hess teaches previous claim. The modified Hess further teaches the system of claim 13, wherein extracting the suspected interference characteristic from the sample includes transmitting a request from the second processor to the first processor to supply signal power data (Pars. 46, 55).
2, 7-9 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Singh et al. (US 20190386759 A1) in view of Hess et al. (US 20210367681 A1) and in further view of Hermel et al. (US 20070243899 A1) and Olgaard (US 20070009021 A1).
Regarding claim 2, apparatus of claim 2 is performed by the method of claim 7. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 7.
Regarding claim 7, the modified Hess teaches previous claim.
However, the modified Hess does not teach the method of claim 6, wherein the suspected interference characteristic includes a deviation in received signal power over a first radio frequency (RF) spectrum of the first received signal
Hermel teaches determining a power loss versus RF frequency relationship comprises calculating a best fit curve equation and estimating a power loss for an RF signal in an RF frequency band based on the power loss versus RF frequency relationship (Fig. 7 and Par. 76). Olgaard teaches wherein the best fit curve calculation/estimation is well-known based on a linear relationship, and the best fit curve is compared to a predetermined expected or desired target to determine whether to perform an iterative adjustment (deviation) (Pars. 31 and 37).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the above teaching as taught Hermel and Olgaard into modified Singh for avoiding the interference.
Regarding claim 8, the modified Hess teaches previous claim. The modified Hess further teaches the method of claim 7, further comprising: determining a curve fit representing the deviation in a power of the first received signal over the first spectrum (Hermel, Fig. 7 and Par. 76).
Regarding claim 9, the modified Hess teaches previous claim. The modified Hess further teaches the method of claim 7, wherein the deviation in the received signal power is determined based on a curve fit representative of a power of the first received signal over of the first RF spectrum exceeding a threshold with respect to the linear approximation (Olgaard, Par. 37).
Regarding claim 14, system of claim 14 is performed by the method of claim 7. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 7.
Regarding claim 15, system of claim 15 is performed by the method of claim 8. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 8.
Regarding claim 16, system of claim 16 is performed by the method of claim 9. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claim 9.
Claims 3-4, 10-11 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Singh et al. (US 20190386759 A1) in view of Hess et al. (US 20210367681 A1) and in further view of Khati et al. (US 20250113327 A1).
Regarding claims 3-4, the modified Singh teaches previous claim.
However, the modified Hess does not teach the system of claim 1, wherein the transmitted first request includes a request to an orbiting satellite to discontinue transmitting the first received signal utilizing a first spectrum; and wherein the transmitted first request additionally comprises a request to initiate transmission of a second signal utilizing a second spectrum.
Khati teaches such feature (Figs. 8-9 and Pars. 58-59).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the above teaching as taught Khati into the modified Singh to mitigate interference in wireless communication.
Regarding claims 10-11, method of claims 10-11 are performed by the apparatus of claims 3-4. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claims 3-4.
Regarding claims 18-20, system of claims 18-19 are performed by the apparatus of claims 3-4. They recite same scope of limitations. Applicant is kindly advised to refer to rejection of claims 3-4.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Singh et al. (US 20190386759 A1) in view of Hess et al. (US 20210367681 A1) and in further view of Chen et al. (US 11255187 B1).
Regarding claim 5, the modified Singh teaches previous claim.
However, the modified Singh does not teach the system of claim 1, wherein the instructions additionally include instructions to generate a training input to the machine learning application, the training input including a square waveform or trapezoidal-shaped waveform modified via an addition of a selectable machine-generated noise signal.
Chen teaches such feature (Col. 10 Lines 1-15).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the above teaching as taught Chen into modified Singh for using patterns with more robust time interval detection.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Singh et al. (US 20190386759 A1) in view of Hess et al. (US 20210367681 A1) and in further view of Boghrat et al. (US 9831899 B1).
Regarding claim 12, the modified Singh teaches previous claim.
However, the modified Singh does not teach the method of claim 6, further comprising: transmitting a second request to an operator of a communications system generating the suspected interference, the second request to include a request to discontinue a transmit operation.
Boghrat teaches such feature (Col. 24 Lines 50-65).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the above teaching as taught Boghrat into modified Singh to prevent unacceptable co-site interference.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Zhang et al. US 20240073826 A1
[0100] In some embodiments, there is optimization or training on the large time-scale parameters, and the following example relates to optimization or training for P.sub.r_0 and α. This is a parameter optimization for the first-level or high-level reference power control model on (at least) large time-scale parameters {P.sub.r_0 and α} for a given carrier frequency or carrier component CC1. An optimization procedure on these parameters may be done as follows: for example, for any given UE location in a cell or coverage area, a UE may be able to measure path loss based on a reference signal from a network node or device (such as a base station), and transmit signals at predefined different levels of power to the network node. The network node may then be able to measure the received signal power levels {P.sub.r_0}. This procedure can be done for more than one UE location, and may involve more than one UE. Given the transmission power levels and the measurements, a best curve fitting can be done to obtain trained or optimized parameters {P.sub.r_0 and α} based on the following reference model.
Hamzeh et al. US 20210389474 A1
[0302] Shadow and corner effects will cause variance in the measured received signal power Ω.sub.dB(d) (e.g., by beacon detector 1214, FIG. 12). Accordingly, the statistical variation of the measured Ω.sub.dB(d), caused by shadowing, 0303] where on represents the shadow standard deviation. Thus, a more accurate path loss determination.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CINDY HUYEN TRANDAI whose telephone number is (571)270-1914. The examiner can normally be reached 8am -4:30pm.
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/Cindy Trandai/Primary Examiner, Art Unit 2648 1/23/2026