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 .
Remarks
1. This office action is in response to communication filled on 03/09/2026. Claims 1-32 are pending on this application.
2. Applicant's arguments with respect to claims 1-32 have been fully considered but are not persuasive.
Response to Remarks
3. Regarding claim 1, applicants asserts that Rollins in view of Tanzil fails to disclose limitation “generating one or more predicted radio frequency (RF) circuit performance properties based at least on the calculated delta and using a machine learning model” (Remarks, page 9 paragraph 3).
Examiner respectfully disagrees.
While Rollins teach generating one or more predicted radio frequency (RF) circuit performance properties (Rollins, Fig. 1 item 14 and related text) based at least on the calculated delta (Rolins, Fig. 1 item output of 26) and using a training subsystem (Rollins, ¶0032 “The training subsystem”), Tanzil teaches adjusting transmission signals using estimated delta and machine learning model (Tanzil, Fig. 16 items 1642 1620 1641 and related text). Therefore, taking the combined teaching of Rollins and Tanzil as a whole, it would have been obvious to one having ordinary skill in the art at the time of the invention to implement the instant limitation for the benefit of improving the performance of the communication system by adaptively managing the accuracy of transmitted signal.
Applicant argument is not persuasive.
Regarding claim 8, applicants asserts that Rollins in view of Tanzil fails to disclose limitation “an amount of amplification applied to an RF signal based on a predistorted digital baseband signal” (Remarks, page 10 paragraph 4).
Examiner respectfully disagrees.
Rollins in view of Tanzil teaches predistortion by evaluation error signal which helps to predict and/or evaluate the performance and health of an RF circuit which includes amplifiers gain or amplification level. By comparing the power of the incoming signal to the output signal, it calculates amplifier gain or amplification level and ensure it meets design specification of amplifier. This is one of the purposes of predistortion and it’s required to know the amount that needs to be applied to remain within the range of the amplifier specification in order to maintain linearity and stability (see Rolins, ¶ 0003-0008 and Tanzil ¶0051-0052).
Applicant argument is not persuasive.
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.
4. Claims 1- 32 are rejected under 35 U.S.C. 103 as being unpatentable over Rollins (US 2015/0163079) in view of Tanzil (US 2024/0137258).
5. As per claim 1, Rollins teach a method for wireless communications, comprising: calculating a delta between a ground.truth digital baseband signal and a received digital baseband signal (Rollins, ¶0032 “combiner”); generating one or more predicted radio frequency (RF) circuit performance properties based at least on the calculated delta and using a machine learning model; and adjusting one or more parameters of a transmission chain for a subsequent wireless signal transmission based on the one or more predicted RF circuit performance properties (Rollins, ¶0074).
While Rollins teach generating one or more predicted radio frequency (RF) circuit performance properties based at least on the calculated delta (Rollins, ¶32 “erro”) and using a training subsystem (Rollins, ¶0032 “The training subsystem”), Rollins doesn’t explicitly mention machine learning. Tanzil teaches adjusting transmission signals using estimated delta and machine learning model (Tanzil, Fig. 16 items 1642 1620 1641). Therefore, taking the combined teaching of Rollins and Tanzil as a whole, it would have been obvious to one having ordinary skill in the art at the time of the invention to implement the instant limitation for the benefit of improving the performance of the communication system by adaptively managing the accuracy of transmitted signal.
6. Claims 12 and 30 are similarly analyzed as claim 1 for obviousness reasons discussed above.
7. As per claim 2, Rollins in view of Tanzil teaches the method of claim 1, wherein adjusting the one or more parameters of the transmission chain comprises adjusting parameters such that deltas between actual RF circuit performance properties associated with subsequent transmissions and threshold values for the RF circuit performance properties are minimized (Rollins, ¶0032).
8. Claims 13 and 24 are similarly analyzed as claim 2 for obviousness reasons discussed above.
9. As per claim 3, Rollins in view of Tanzil teaches the method of claim 1, wherein the delta between the ground.truth digital baseband signal and the received digital baseband signal comprises a determination of an amount of distortion in the received digital baseband signal relative to the ground.truth digital baseband signal (Rollins, ¶0032 “error”).
11. Claims 14 and 25 are similarly analyzed as claim 3 for obviousness reasons discussed above.
12. As per claim 4, Rollins in view of Tanzil teaches the method of claim 3, wherein the amount of distortion comprises at least one of a time difference, a gain difference, or a phase difference between the ground.truth digital baseband signal and the received digital baseband signal (Rollins, ¶0009).
13. Claim 15 is similarly analyzed as claim 4 for obviousness reasons discussed above.
14. As per claim 5, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more predicted RF circuit performance properties comprise an error vector magnitude (EVM) prediction (Tanzil, ¶0113).
15. Claims 16 and 26 are similarly analyzed as claim 5 for obviousness reasons discussed above.
16. As per claim 6, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more predicted RF circuit performance properties comprise a spectral mask margin prediction (Rollins, ¶0034 0038).
17. Claim 17 is similarly analyzed as claim 6 for obviousness reasons discussed above.
18. As per claim 7, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more predicted RF circuit performance properties comprise an emission prediction (Tanzil, ¶0098 0113).
19. Claim 18 is similarly analyzed as claim 7 for obviousness reasons discussed above.
20. As per claim 8, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more parameters of the transmission chain for the subsequent wireless signal transmission comprise an amount of amplification applied to an RF signal based on a predistorted digital baseband signal (Rollins, ¶0012).
21. Claims 19 and 27 are similarly analyzed as claim 8 for obviousness reasons discussed above.
22. As per claim 9, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more parameters of the transmission chain comprise one or more parameters of a digital predistorter in the transmission chain (Rollins, ¶0012).
23. Claim 20 is similarly analyzed as claim 9 for obviousness reasons discussed above.
24. As per claim 10, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more parameters of the transmission chain comprise one or more parameters based on which the ground.truth digital baseband signal is generated by a baseband processor (Rollins, ¶0011).
25. Claims 21 and 28 are similarly analyzed as claim 10 for obviousness reasons discussed above.
26. As per claim 11, Rollins in view of Tanzil teaches the method of claim 1, wherein the received digital baseband signal comprises a signal received from a receive chain based on a processed version of the ground.truth digital baseband signal via the transmission chain (Rollins, ¶0011).
27. Claims 22 and 29 are similarly analyzed as claim 1 for obviousness reasons discussed above.
28. Claim 30 is similarly analyzed as claim 1 for obviousness reason discussed above.
29. As per claim 31, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more predicted RF circuit performance properties comprise one or more predicted analog RF circuit performance (Rolins, ¶0098 0012).
30. As per claim 32, Rollins in view of Tanzil teaches the method of claim 1, wherein the one or more predicted RF circuit performance properties comprise one or more predicted transmission properties (Rolins, ¶0013 0014).
Conclusion
THIS ACTION IS MADE FINAL. 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 ZEWDU A KASSA whose telephone number is (571)270-5253. The examiner can normally be reached 9-5:30.
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ZEWDU A. KASSA
Examiner
Art Unit 2637
/ZEWDU A KASSA/Primary Examiner, Art Unit 2635
Prosecution Insights