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 .
1. This office action, in response to the request for continued examination (RCE) and the amendment filed 8/6/2026, is a non-final office action.
Continued Examination Under 37 CFR 1.114
2. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/9/2026 has been entered.
Response to Arguments
3. Independent claims 1, 11 and 23 have been amended. Claim 1 and 23 have been amended to add "wherein the receiver updates the state information pertaining to hardware over time based on one or more detected changes in hardware conditions or in response to a request from the transmitter". Applicant states Dehos does not teach all of the features of independent claim 1. The newly added limitations are addressed in the rejection of claim 1 stated below.
Applicant states, additionally, amended claims 11 and 23 recite, inter alia, features similar to those recited above in independent claim 1. Claim 23 does recite the newly added limitation and claim 23 is rejected for the same reasons as amended claim 1 as stated below. However, amended claim 11 does not recite the newly added features of claims 1 and 23. As stated in the advisory action mailed 7/15/2025, the amendment to claim 11 labels "information" as "updated information". This label of the information does not change the scope of the claim. In addition, Davos discloses a communication system. This system is continually updating the predistortion unit according to a set of parameters to account for the non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Claim 11 is rejected as stated below.
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)(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.
4. Claims 11, 12, 16, 17, 19 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dehos et al (WO 2012/013218 A1).
Regarding claim 11, Dehos discloses a method performed by a transmitter (Abstract: a set of parameters describing the nonlinear effect is estimated at the receiving side and the estimated values are sent to the transmitter on the return side. The transmitter then uses these estimated values to predistort the signal upstream of the stages where the nonlinear effect has occurred.), the method comprising:
transmitting a signal to a receiver configured to receive the signal (Abstract: a set of parameters describing the nonlinear effect is estimated at the receiving side and the estimated values are sent to the transmitter on the return side. The transmitter then uses these estimated values to predistort the signal upstream of the stages where the nonlinear effect has occurred.);
receiving from the receiver updated information indicating state information pertaining to hardware determined by the receiver based on the received signal (Abstract: a set of parameters describing the nonlinear effect is estimated at the receiving side and the estimated values are sent to the transmitter on the return side. The transmitter then uses these estimated values to predistort the signal upstream of the stages where the nonlinear effect has occurred. Subsequent iterations of this predistortion system will comprise updated information since the information will be updated from the previous information.);
and using the updated information indicating the state information pertaining to hardware to compensate for distortion caused by at least one of one or more hardware components of the transmitter or one or more hardware components of the receiver (Abstract: a set of parameters describing the nonlinear effect is estimated at the receiving side and the estimated values are sent to the transmitter on the return side. The transmitter then uses these estimated values to predistort the signal upstream of the stages where the nonlinear effect has occurred. Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Subsequent iterations of this predistortion system will comprise updated information since the information will be updated from the previous information.).
Regarding claim 12, Dehos discloses wherein using the information indicating the state information pertaining to hardware to compensate for the distortion comprises using the information indicating the state information pertaining to hardware to determine coefficients for a pre-distortion function that is used by the transmitter to compensate for the distortion (Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier.).
Regarding claim 16, Dehos discloses after using the information indicating the state information pertaining to hardware to determine the coefficients for the pre-distortion function, applying the pre-distortion function with the determined coefficients to a baseband signal to produce a pre-distorted signal (Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.ie., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier.).
Regarding claim 17, Dehos discloses wherein the pre-distorted signal is a digital signal and the method further comprises: converting the pre-distorted signal to an analog signal; using the analog signal and a modulator to produce a modulated signal; amplifying the modulated signal using a power amplifier, thereby producing an amplified signal; and transmitting the amplified signal (Figure 1 is the transmitter and comprises the DAC 120, modulators and filters shown. Page 9, lines 23-29: the non-linear characteristics are estimated as a list of parameters which is sent in digital form to the transmitter and provided to the predistortion means. Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier).).
Regarding claim 19, Dehos discloses triggering the receiver to provide the information indicating the state information pertaining to hardware to the transmitter (The feedback signal to the transmitter is trigger by receiving the signal from the transmitter and processing that signal as shown in figure 3.).
Regarding claim 20, Dehos discloses wherein the triggering is performed as a result of a change in a working condition of the transmitter (The feedback signal to the transmitter is trigger by receiving the signal from the transmitter and processing that received signal as shown in figure 3. The feedback signal will be used to update the predistortion means. This will change the previous working conditions of the predistortion means to the updated working conditions.).
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.
5. Claims 1, 2, 6 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Dehos et al (WO 2012/013218 A1) in view of Bai et al (US 2012/0328050).
Regarding claims 1 and 23, Dehos discloses a method performed by a receiver for hardware impairment compensation (Abstract: a set of parameters describing the nonlinear effect is estimated at the receiving side and the estimated values are sent to the transmitter on the return side. The transmitter then uses these estimated values to predistort the signal upstream of the stages where the nonlinear effect has occurred.) and a network node (Page 5, lines 14-27: a communication comprising a transmitter at a source terminal, a transmission channel and a receiver at a destination terminal. The term “terminal” should be understood here in its broadest sense and may encompass either a base station or a relay station.), the method comprising:
receiving a transmitted signal transmitted by a transmitter (Figure 3);
determining state information pertaining to hardware based on the received signal (Page 13, lines 19-27: as the receiver knows these symbols, it can estimate how they are distorted. Whereas channel estimation accounts for the linear response of the transmission channel, the non-linear estimation accounts for non-linear distortion of the transmitted signal. Page 1, lines 13-29: some components comprised in a communication system, either at the transmitter side, such as the power amplifier or at the receiver side, such as the low noise amplifier (LNA), may exhibit non-linear characteristics.); and
providing to the transmitter information indicating the state information pertaining to hardware (Page 9, lines 23-29: the non-linear characteristics are estimated as a list of parameters which is sent in digital form to the transmitter and provided to the predistortion means.),
wherein the state information pertaining to hardware comprises information that enables the transmitter to compensate for distortion caused by at least one of one or more hardware components of the transmitter or one or more hardware components of the receiver (Page 9, lines 23-29: It should be understood that if g is a function describing the non-linear effect, the list of parameters may define g or its inverse called the predistortion function used for predistorting the signal.).
Dehos does not explicitly disclose wherein the receiver updates the state information pertaining to hardware over time based on one or more detected changes in hardware conditions or in response to a request from the transmitter.
Bai discloses the predistortion system described in the abstract. Bai discloses qualities of the hardware used to construct a transmitter, and particularly the power amplifier, may change over time. As a result, over time, the model of the non-linearity of the power amplifier may gradually increase in error. In order to address this issue, adaptive predistortion schemes are utilized to compensate of changes in the non-linearity of the power amplifier over time. In these adaptive predistortion schemes, a result of the linearization, i.e., the output of the power amplifier, is monitored, and the predistortion is updated to reflect changes in the nonlinearity of the power amplifier as stated in paragraph 0005. Bai discloses the updates to the predistorter is based on one or more detected changes in hardware conditions as indicated by the output of the power amplifier over time. It would have been obvious for one of ordinary skill in the art at the time of the invention to incorporate the teachings of Bai into the method and apparatus of Davos to overcome the issues with the qualities of the hardware changing over time. The increased errors from these changes over time can be addressed, improving the function of the system.
Regarding claim 2, the combination discloses wherein the information indicating the state information pertaining to hardware comprises information that enables the transmitter to determine coefficients for a pre-distortion function that is used to compensate for the distortion (Devos: Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier.).
Regarding claim 6, the combination discloses wherein the one or more hardware components of the transmitter comprises: a power amplifier; a filter; a digital-to-analog converter; or an oscillator (Devos: Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Figure 1: DAC 120, oscillator 135 and filter are shown in the transmitter.).
6. Claims 3-5 and 7-10 are rejected under 35 U.S.C. 103 as being unpatentable over Dehos et al (WO 2012/013218 A1) in view of Bai et al (US 2012/0328050) further in view of McCormick et al (US 11,671,123).
Regarding claim 3, the combination of Dehos and Bai discloses the method stated above. Dehos discloses parameters are determined that correspond to the distortion caused by the hardware components and uses those parameters to compensate for that distortion in the predistorter. The combination does not recite that a model is used to carry out these functions.
McCormick discloses the communication system shown in figures 4 and 10. The transmitter includes a predistortion actuator 402 and a plurality of power amplifiers for transmitting a signal to a receiver. The receiver 430 receives the transmitted signal. The received signal is processed and a feedback signal is provided back to the transmitter via a feedback data link 416. The feedback signal is utilized by the transmitter to update the predistortion activator as shown in the figures. McCormick further discloses the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model as stated in column 2, lines 1-20. Column 2, lines 21-30 discloses the system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator. The adaption engine can be configured to use a combination of direct learning and indirect learning to improve the predistortion actuator in column 2, lines 31-40. The nonlinearities can be associated with the phase antenna array, the power amplifiers and the coupling between the antenna elements as stated in column 2, lines 48-54. Therefore, McCormick discloses the feedback information providing these updates comprise model parameters and enable the transmitter to determine the model parameters. 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 teaching of using a model and model parameters to update the predistortion means based on a feedback signal from a receiver of McCormick into the predistortion system of the combination of Dehos and Bai. The behavioral model or GMF model being utilized will allow for more accurate updates to take place in the predistortion means and improve function of the communication system.
Regarding claim 4, the combination discloses the information enabling the transmitter to determine the model parameters, and the information enabling the transmitter to determine the model parameters comprises information pertaining to the received signal (Dehos: Page 9, lines 23-29: the non-linear characteristics are estimated as a list of parameters which is sent in digital form to the transmitter and provided to the predistortion means. Page 9, lines 23-29: It should be understood that if g is a function describing the non-linear effect, the list of parameters may define g or its inverse called the predistortion function used for predistorting the signal. McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
Regarding claim 5, the combination discloses wherein information pertaining to the received signal comprises at least one of: information indicating a phase shift between the transmitted signal and the received signal, or information indicating an amplitude change between the transmitted signal the received signal (Dehos: Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.ie., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier. McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
Regarding claim 7, the combination of Dehos and Bai discloses the method stated above. Dehos discloses parameters are determined that correspond to the distortion caused by the hardware components and uses those parameters to compensate for that distortion in the predistorter. The combination does not recite that a model is used to carry out these functions.
McCormick discloses the communication system shown in figures 4 and 10. The transmitter includes a predistortion actuator 402 and a plurality of power amplifiers for transmitting a signal to a receiver. The receiver 430 receives the transmitted signal. The received signal is processed and a feedback signal is provided back to the transmitter via a feedback data link 416. The feedback signal is utilized by the transmitter to update the predistortion activator as shown in the figures. McCormick further discloses the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model as stated in column 2, lines 1-20. Column 2, lines 21-30 discloses the system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator. The adaption engine can be configured to use a combination of direct learning and indirect learning to improve the predistortion actuator in column 2, lines 31-40. The nonlinearities can be associated with the phase antenna array, the power amplifiers and the coupling between the antenna elements as stated in column 2, lines 48-54. Therefore, McCormick discloses the feedback information providing these updates comprise model parameters and enable the transmitter to determine the model parameters. 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 teaching of using a model and model parameters to update the predistortion means based on a feedback signal from a receiver of McCormick into the predistortion system of the combination of Dehos and Bai. The behavioral model or GMF model being utilized will allow for more accurate updates to take place in the predistortion means and improve function of the communication system.
Regarding claim 8, the combination discloses wherein the signal transmitted by the transmitter is a reference signal known to the receiver prior to the transmission (Dehos: Page 13, lines 19-27: as the receiver knows these symbols, it can estimate how they are distorted. Whereas channel estimation accounts for the linear response of the transmission channel, the non-linear estimation accounts for non-linear distortion of the transmitted signal. Page 1, lines 13-29: some components comprised in a communication system, either at the transmitter side, such as the power amplifier or at the receiver side, such as the low noise amplifier (LNA), may exhibit non-linear characteristics.).
Regarding claim 9, the combination discloses determining the parameter values of the parametrized model comprises: applying the model to the received signal to produce a model output signal; and using the received signal and the model output signal to determine the parameter values of the parametrized model (McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
Regarding claim 10, the combination discloses wherein using the received signal and the model output signal to determine the parameter values of the parametrized model comprises determining parameter values of the parametrized model that minimize a difference metric between the received signal and the model output signal produced by the parametrized model (Dehos: Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.e., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier. McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
7. Claims 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Dehos et al (WO 2012/013218 A1) in view of McCormick et al (US 11,671,123).
Regarding claim 13, Dehos discloses the method stated above. Dehos discloses parameters are determined that correspond to the distortion caused by the hardware components and uses those parameters to compensate for that distortion in the predistorter. Dehos does not recite that a model is used to carry out these functions.
McCormick discloses the communication system shown in figures 4 and 10. The transmitter includes a predistortion actuator 402 and a plurality of power amplifiers for transmitting a signal to a receiver. The receiver 430 receives the transmitted signal. The received signal is processed and a feedback signal is provided back to the transmitter via a feedback data link 416. The feedback signal is utilized by the transmitter to update the predistortion activator as shown in the figures. McCormick further discloses the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model as stated in column 2, lines 1-20. Column 2, lines 21-30 discloses the system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator. The adaption engine can be configured to use a combination of direct learning and indirect learning to improve the predistortion actuator in column 2, lines 31-40. The nonlinearities can be associated with the phase antenna array, the power amplifiers and the coupling between the antenna elements as stated in column 2, lines 48-54. Therefore, McCormick discloses the feedback information providing these updates comprise model parameters and enable the transmitter to determine the model parameters. 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 teaching of using a model and model parameters to update the predistortion means based on a feedback signal from a receiver of McCormick into the predistortion system of Dehos. The behavioral model or GMF model being utilized will allow for more accurate updates to take place in the predistortion means and improve function of the communication system.
Regarding claim 14, the combination discloses the information enabling the transmitter to determine the model parameters, and the information enabling the transmitter to determine the model parameters comprises information pertaining to the received signal (Dehos: Page 9, lines 23-29: the non-linear characteristics are estimated as a list of parameters which is sent in digital form to the transmitter and provided to the predistortion means. Page 9, lines 23-29: It should be understood that if g is a function describing the non-linear effect, the list of parameters may define g or its inverse called the predistortion function used for predistorting the signal. McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
Regarding claim 15, the combination discloses wherein information pertaining to the received signal comprises at least one of: information indicating a phase shift between the transmitted signal and the received signal, or information indicating an amplitude change between the transmitted signal the received signal (Dehos: Page 17, line 10 to page 18, line 6: more generally, it will be understood that the amplitude predistortion applied at the transmitter side can account for any non-linear effects affecting the amplitude of the signal downstream (i.ie., not only the power amplifier). Similarly, phase compensation may be combined with phase predistortion to remove non-linear effects affecting the phase of the signal downstream. The complex coefficients are used to multiply the amplified signal so as the rectify the phase distortion introduced by the power amplifier. McCormick: Column 2, lines 1-30: the predistortion actuator can be configured to generate the output signal by applying a correction to the carrier-modulated input signal that cancels out nonlinearities. The predistortion actuator can include a behavioral model or generalized memory functions (GMF) model. The predistortion actuator can include a plurality of look-up table values that can include parameters of the behavioral model or GMF model. The system can further include an adaptation engine electronically coupled to the predistortion actuator and a receiver configured to receive the output signal and to generate a feedback signal based on the output signal. The adaptation engine is configured to update the predistortion actuator based on the feedback to yield an updated predistortion actuator.).
Conclusion
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/KEVIN M BURD/Primary Examiner, Art Unit 2632 9/15/2026
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