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 .
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statement submitted on 03/21/2024 and 06/16/2025 has been considered by the Examiner and made of record in the application file.
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 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.
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.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Levy (US 20220038229 A1) in view of Li (US 20210243056 A1).
Consider claim 1, Levy discloses a transmitter paired with a receiver that performs non-linear distortion compensation (read as UE transmitter that transmits pilot signals to a base station receiver, and that the base station performs DPoD and utilizes the pilot signal to perform DPoD operation for mitigating non-linear signal processing, par [0003]-[0004], [0100] and [0111]), configured to:
separately generate a pilot signal for non-linear distortion compensation to be used by the receiver and a pilot signal for channel estimation to be used by the receiver (read as the UE would transmit a set of pilot signals separated into in-band resources and OOB resources, and that the base station uses those pilot signals to accurately estimate the channel and to perform DPoD operations, par [0100] and [0111]); and
transmit the generated pilot signals to the receiver (read as the UE transmitter would transmit the in-band and OOB pilot signals to the base station receiver, par [0100] and [0111]).
However, Levy discloses the claimed invention above but does not specifically disclose that the receiver performs non-linear distortion compensation by deep learning.
Nonetheless, Li discloses a receiver including an equalizer, comprising a deep neural network trained with respect to channel distortion, and perform nonlinear equalization using that deep neural network, par [0161]-[0163].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Li into teachings of Levy to modify Levy’s receiver-side nonlinear distortion compensation by implementing that compensation using Li’s deep neural network equalizer, in order to provide a known and established deep-learning-based technique for modeling and compensating nonlinear channel and power amplifier distortion at the receiver, which would improve nonlinear modeling capability while performing the same distortion mitigation function already required by Levy.
Consider claim 6, Levy discloses a method for execution by a transmitter paired with a receiver that performs non-linear distortion compensation (read as UE transmitter that transmits pilot signals to a base station receiver, and that the base station performs DPoD and utilizes the pilot signal to perform DPoD operation for mitigating non-linear signal processing, par [0003]-[0004], [0100] and [0111]), configured to:
separately generate a pilot signal for non-linear distortion compensation to be used by the receiver and a pilot signal for channel estimation to be used by the receiver (read as the UE would transmit a set of pilot signals separated into in-band resources and OOB resources, and that the base station uses those pilot signals to accurately estimate the channel and to perform DPoD operations, par [0100] and [0111]); and
transmit the generated pilot signals to the receiver (read as the UE transmitter would transmit the in-band and OOB pilot signals to the base station receiver, par [0100] and [0111]).
However, Levy discloses the claimed invention above but does not specifically disclose that the receiver performs non-linear distortion compensation by deep learning.
Nonetheless, Li discloses a receiver including an equalizer, comprising a deep neural network trained with respect to channel distortion, and perform nonlinear equalization using that deep neural network, par [0161]-[0163].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Li into teachings of Levy to modify Levy’s receiver-side nonlinear distortion compensation by implementing that compensation using Li’s deep neural network equalizer, in order to provide a known and established deep-learning-based technique for modeling and compensating nonlinear channel and power amplifier distortion at the receiver, which would improve nonlinear modeling capability while performing the same distortion mitigation function already required by Levy.
Consider claim 7, Levy discloses a non-transitory computer-readable storage medium storing a program for causing a computer to function as a transmitter paired with a receiver that performs non-linear distortion compensation (read as UE transmitter that transmits pilot signals to a base station receiver, and that the base station performs DPoD and utilizes the pilot signal to perform DPoD operation for mitigating non-linear signal processing, par [0003]-[0004], [0100] and [0111]), configured to:
separately generate a pilot signal for non-linear distortion compensation to be used by the receiver and a pilot signal for channel estimation to be used by the receiver (read as the UE would transmit a set of pilot signals separated into in-band resources and OOB resources, and that the base station uses those pilot signals to accurately estimate the channel and to perform DPoD operations, par [0100] and [0111]); and
transmit the generated pilot signals to the receiver (read as the UE transmitter would transmit the in-band and OOB pilot signals to the base station receiver, par [0100] and [0111]).
However, Levy discloses the claimed invention above but does not specifically disclose that the receiver performs non-linear distortion compensation by deep learning.
Nonetheless, Li discloses a receiver including an equalizer, comprising a deep neural network trained with respect to channel distortion, and perform nonlinear equalization using that deep neural network, par [0161]-[0163].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Li into teachings of Levy to modify Levy’s receiver-side nonlinear distortion compensation by implementing that compensation using Li’s deep neural network equalizer, in order to provide a known and established deep-learning-based technique for modeling and compensating nonlinear channel and power amplifier distortion at the receiver, which would improve nonlinear modeling capability while performing the same distortion mitigation function already required by Levy.
Claims 2 and 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Levy (US 20220038229 A1) in view of Li (US 20210243056 A1), and in further view of Kim (US 20200267743 A1).
Consider claim 2, as applied to claim 1 above, Levy, as modified by Li, discloses transmitter generating separate pilot signals for channel estimation and non-linear distortion compensation (read as the UE would transmit a set of pilot signals separated into in-band resources and OOB resources, and that the base station uses those pilot signals to accurately estimate the channel and to perform DPoD operations, par [0100] and [0111]) but does not specifically disclose wherein the transmitter, when generating the pilot signals, is further configured to increase a second frequency for generating the pilot signal for channel estimation to higher than a first frequency for generating the pilot signal for non-linear distortion compensation.
Nonetheless, Kim discloses that one reference signal (CRS) is transmitted in every subframe while another reference signal (CSI-RS) is transmitted at a defined periodicity over multiple subframes, such that one pilot signal is generated at a higher temporal frequency than another pilot signal, par [0206] and [0210].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Kim into teachings of Levy, which modified by Li, to modify the pilot signal generation by configuring the channel-estimation pilot to be generated at a higher temporal frequency than the distortion-related pilot, in order to apply known LTE reference signal scheduling techniques to balance channel tracking accuracy and signaling overhead, which allows control of pilot transmission frequency within Levy’s wireless communication system.
Consider claim 3, as applied to claim 2 above, Levy, as modified by Li and Kim, discloses transmitter generating separate pilot signals for channel estimation and non-linear distortion compensation (read as the UE would transmit a set of pilot signals separated into in-band resources and OOB resources, and that the base station uses those pilot signals to accurately estimate the channel and to perform DPoD operations, par [0100] and [0111]) but does not specifically disclose wherein the transmitter increases the second frequency to higher than the first frequency, by intermittently generating the pilot signal for channel estimation within a plurality of consecutive frames, and generating the pilot signal for non-linear distortion compensation within a pilot block that is intermittently generated between the plurality of consecutive frames.
Nonetheless, Kim further discloses that CSI-RS reference signals are generated only in subframes (i.e. 5, 10, 20, 40 and 80 subframes as shown in table 6) that satisfy a defined periodicity and offset condition, par [0210]-[0211].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to further incorporate the teachings of Kim into teachings of Levy, which modified by Li and Kim, to modify the pilot signal generation to occur intermittently across consecutive frames according to defined periodic scheduling parameters, in order to implement known LTE-compliant frame-level reference signal scheduling that reduce unnecessary pilot transmission while maintaining required estimation functionality, which would improve signaling efficiency within the wireless communication system.
Claim 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Levy (US 20220038229 A1) in view of Li (US 20210243056 A1), and in further view of Sagi (US 20190190552 A1).
Consider claim 4, as applied to claim 1 above, Levy, as modified by Li, discloses the claimed invention above and the pilot signal for non-linear distortion compensation (par [0003], [0100] and [0111])) but does not specifically disclose wherein the transmitter generates the pilot signal for non-linear distortion compensation as a sequence of non-constant envelopes.
Nonetheless, Sagi discloses a reference signal used for estimating transmitter nonlinearity is configured to have a non-constant envelope, par [0037].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Sagi into teachings of Levy, which modified by Li, to further modify the distortion-related pilot signal to comprise a sequence of non-constant envelope, in order to apply a known reference-signal design technique that improve estimation of nonlinear transmitter behavior, which would enhance nonlinear distortion compensation performance within the receiver-side processing system.
Claim 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Levy (US 20220038229 A1) in view of Li (US 20210243056 A1), and in further view of Nagarajan (US 20220239427 A1).
Consider claim 5, as applied to claim 1 above, Levy, as modified by Li, discloses the claimed invention above and the pilot signal for channel estimation (par [0100] and [0111]) but does not specifically disclose wherein the transmitter generates the pilot signal for channel estimation as a ZC sequence.
Nonetheless, Nagarajan discloses a demodulation reference signal used for channel estimation maybe a Zadoff-Chu (ZC) sequence, par [0042] and [0056].
Therefore, it would have been obvious for a person with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Nagarajan into teachings of Levy, which modified by Li, to further modify the channel-estimation pilot signal to use Zadoff-Chu sequence, in order to apply a known reference signal sequence structure widely use din LTE/NR systems for reliable channel estimation, which would achieve predictable correlation properties and channel estimation performance within the wireless communication system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Junpeng Chen whose telephone number is (571) 270-1112. The examiner can normally be reached on Monday - Thursday, 8:00 a.m. - 5:00 p.m., EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anthony S Addy can be reached on 571-272-7795. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Junpeng Chen/
Primary Examiner, Art Unit 2645