DETAILED ACTION
This office action is a response to the Request for Continued Examination (RCE) filed on 04/27/2026.
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/27/2026 has been entered.
Response to Amendment
The Amendment filed on 04/27/2026 has been entered.
Claims 1, 3-5, 7-11, 13-14 and 16-21 are pending
Claims 1, 8, 11, 18 and 20 are amended
Claims 2, 6, 12 and 15 are canceled
Claims 1, 3-5, 7-11, 13-14 and 16-21 remain rejected.
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.
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 of this title, 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, 3-5, 7-11, 13-14 and 16-21 are rejected under 35 U.S.C. 103 as being unpatentable over MARKHOVSKY et al. (WO 2019191318 A1), hereinafter referenced as Markhovsky, in view of Shi et al. (US 20200333424 A1), hereinafter referenced as Shi, in view of Happonen et al. (US 20020110199 A1), hereinafter referenced as Happonen.
Regarding claims 1, 11 and 20, Markhovsky teaches a positioning method applied to a communications device (Figs. 1-12, Para. [0002]-Markhovsky discloses unified framework/platform (architecture, functional entities and operations) that shall accommodate all- inclusive wireless devices wireless signals, positioning technologies, methods/techniques, including hybrid/fusion localizations), wherein the method comprises:
receiving first information (Para. [0351]-Markhovsky discloses UE position can be estimated in the handset (UE-based method) or in the network (NT-based, UE-assisted method) once the signals from three base stations are received. Abstact-Markhovsky discloses a detector within the device or another component of the environment receives signals including parameters for a localization signal of the device),
the first information comprises: first preprocessing model information (Para. [0051]-Markhovsky discloses the LSU also includes navigation processor a.k.a. positioning engine - receiving outputs from one or more signal processors and performing position estimation and position tracking calculations by utilizing numerous localization (geolocation). Para. [0739]-Markhovsky discloses performing target localization by applying location consistency algorithms, including machine learning algorithms, to the resulting multiple position estimates. Para. [0677]-Markhovsky discloses to retrieve, preprocess and send the digital samples of the downlink baseband reference signals to the LSU by the SUPL Positioning Calculation Function (SPCF). Also, SPCF modification may include preprocessing of these samples before transferring these to the LSU. Para. [0005]-Markhovsky discloses time synchronization errors impact locate accuracy, ... in the case of DL-OTDOA, that transmissions from multiple antennas be time synchronized, or in the case of U-TDOA, that multiple receivers be time synchronized. Para. [0356]-Markhovsky discloses reflected signals will induce an error in the estimated time difference of arrival (TDOA) and time of arrival (TOA) measurements, including RTT measurements. (See also Para. [0014, 0036, 0126, 0351, 0606, 0751 and Abstract)); and
determining, …, the information related to the location of the terminal device (Fig. 11, Para. [0351]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique the time of arrival of the signal coming from neighboring base stations (eNB) is calculated. The UE position can be estimated in the handset (UE-based method) or in the network (NT-based, UE-assisted method) once the signals from three base stations are received. The measured signal is the CPICH (Common Pilot Channel). The propagation time of signals is correlated with a locally generated replica. The peak of correlation indicates the observed time of propagation of the measured signal . Time difference of arrival values between two base stations determines a hyperbola. At least three reference points are needed to define two hyperbolas. The location of the UE is in the intersection of these five hyperbolas),
the first measurement information is obtained based on signal measurement (Fig. 11, Para. [0351-0352]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique ... The measured signal is the CPICH (Common Pilot Channel) … The pilot signal measurements will occur in idle period);
the information related to the location of the terminal device comprises: second measurement information determined based on the first measurement information (Fig. 11, Para. [0351-0352]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique ... The measured signal is the CPICH (Common Pilot Channel) … The pilot signal measurements will occur in idle period. Para. [0013-0014]-Markhovsky discloses the downlink OTDOA method provides more ubiquitous coverage. At the same time, uplink locate may also support the Angle of Arrival (AoA)/Direction of Arrival (DoA) method, where AoA/DoA is measured based on uplink transmissions from the UE and the known configuration of the eNodeB, aka eNoB/eNB, antenna array ... the UE must perform the downlink timing measurements);
the first measurement information comprises: a channel impulse response of the terminal device (Para. [0425]-Markhovsky discloses the LTE uplink signaling also includes reference signals, mobile device to base, which also contains reference subcarriers. In fact there is more than one mode in which contain these subcarriers from a full sounding mode used by the network to assign a frequency band to the uplink device to a mode where are reference subcarriers are used to generate a channel impulse responses to aid in demodulation of the uplink signal, etc. (See also Para. [0295-0297]). Fig. 1A, Para. [0149]-Markhovsky discloses the exemplary ranging signal employs different frequency components that are contiguous. Other waveforms, including pseudo random, spaced in frequency and/or time or orthogonal, etc. can be also used for as long as the ranging signal bandwidth remains narrow');
to perform sparsification or dimensionality reduction on the first measurement information, generating the second measurement information (Para. [0330-0331]-Markhovsky discloses issues when applying any subspace decomposition algorithm is the dimension of the signal subspace that can be taken as the number of frequency components present … Because of real-world measurement imperfections there always will be an error in the model size estimation ... To improve the distance measurement accuracy, one embodiment includes ... the methodology of subspace decomposition high resolution estimation. Para. [0707-0712]-Markhovsky discloses using our coherent compression scheme, the size of the resultant data used for TOA estimation is reduced to the non-zero portion of the cross-correlation output, times the number of emitters detected. Tire size of the data is reduced to I x 200 x 32 bits, or 6400 bits per emitter detected ... the detector may be configured to perform additional pre processing (to further reduce data size), including matched filtering of signals used for device localization. Para. [0044]-Markhovsky discloses the signal processing, localization, tracking and navigation is carried out in the LSU, while pre-processing of a snap-shot of signals include sending the snap-shot data to the LSU and, optionally, performing compression operations to reduce the amount of the snap-shot data to be sent to the LSU. (See also Para. [0691-0696]));
the second measurement information comprises at least one of the following: a sparse channel impulse response, and a multipath-represented channel impulse response (Para. [0425]-Markhovsky discloses to generate a channel impulse responses to aid in demodulation of the uplink signal, etc. Also, similarly to the DL PRS added in rel.9 additional UL reference signals might be added in the upcoming and future standard releases. In this embodiment, the uplink signal is processed by multiple base units (eNB) using the same range to phase, multipath mitigation processing to generate range related observables).
Markhovsky fails to teach determining, based on the first information … step length.
However, Shi teaches determining, based on the first information and first measurement information of a terminal device, the information related to the location of the terminal device (Para. [0010]-Shi discloses the measurement data is obtained based on a downlink reference signal received by the terminal device, the measurement data is used by the positioning service function entity to estimate a location of the terminal device, and the measurement data includes at least one of the following: a channel estimation and a channel impulse response),
the first measurement information is obtained based on signal measurement (Para. [0010]-Shi discloses the measurement data is obtained based on a downlink reference signal received by the terminal device, the measurement data is used by the positioning service function entity to estimate a location of the terminal device, and the measurement data includes at least one of the following: a channel estimation and a channel impulse response);
the information related to the location of the terminal device comprises: second measurement information determined based on the first measurement information (Para. [0010]-Shi discloses the measurement data is obtained based on a downlink reference signal received by the terminal device, the measurement data is used by the positioning service function entity to estimate a location of the terminal device, and the measurement data includes at least one of the following: a channel estimation and a channel impulse response);
the parameter of the channel impulse processing method comprises a step length (Para. [0077-0080]-Shi discloses to obtain a sequence having a length L, namely, a channel impulse response. Optionally, to reduce a sending amount, the channel impulse response whose length is L may be filtered, to extract valid information for transmission. A specific process may be as follows: ... Perform an IDFT or IFFT operation on the zero-padded sequence h′ to obtain a channel impulse response sequence f′=[f′.sub.1, . . . , f′.sub.l, . . . f.sub.L′] whose length is also L);
the step length is used to perform sparsification or dimensionality reduction on the first measurement information, generating the second measurement information (Para. [0075-0081]-Shi discloses if a coefficient of the Fourier transform is L and L≥M, L-point IDFT or IFFT is performed for the channel estimation to obtain a sequence having a length L, namely, a channel impulse response. Optionally, to reduce a sending amount, the channel impulse response whose length is L may be filtered, to extract valid information for transmission. A specific process may be as follows: ... The channel estimation obtained from the reference signal is h=[h.sub.1, . . . , h.sub.m, . . . h.sub.M]);
the second measurement information comprises at least one of the following: a sparse channel impulse response, and a multipath-represented channel impulse response (Para. [0075-0081]-Shi discloses if a coefficient of the Fourier transform is L and L≥M, L-point IDFT or IFFT is performed for the channel estimation to obtain a sequence having a length L, namely, a channel impulse response. Optionally, to reduce a sending amount, the channel impulse response whose length is L may be filtered, to extract valid information for transmission. A specific process may be as follows: ... The channel estimation obtained from the reference signal is h=[h.sub.1, . . . , h.sub.m, . . . h.sub.M]).
Shi is considered to be analogous because it is in the same field of communications technologies, dealing with terminal device positioning technology in a communications system.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Markhovsky to incorporate the teachings of Shi on step length, with a motivation to perform sparsification, dimensionality reduction, or image transformation on the first measurement information, generating the second measurement information, and guarantee high-accuracy and low-limitation terminal device positioning by using more valid measurement data, (Shi, Para. [0008]).
Markhovsky fails to teach the first preprocessing model information comprises: a parameter of a channel impulse processing method; the parameter of the channel impulse processing method comprises a step length.
However, Happonen teaches the first preprocessing model information comprises: a parameter of a channel impulse processing method (Para. [0071]-Happonen discloses a signal h representing the channel impulse response function and/or the channel impulse response taps is output and supplied to the further processing unit 2b which is adapted to output the energy/symbol Emax of the channel impulse response taps based on the results of the preprocessing of the unit 2a. Para. [0033-0046]-Happonen discloses h denotes an estimated channel impulse responses ... the energy of the signal/symbol can be rewritten to read 1 E ( h H X H Xh ) / N = E ( h H h ) / N = ( i ( Re { h i } 2 + Im { h i } 2 ) ) / N = Emax ( 4 ) … N representing the length of the sequence Y in equation (3) above. Para. [0030]-Happonen discloses the length of a symbol sequence is represented by a number N of symbols contained in the sequence);
the parameter of the channel impulse processing method comprises a step length (Para. [0033-0046]-Happonen discloses h denotes an estimated channel impulse responses ... the energy of the signal/symbol can be rewritten to read 1 E ( h H X H Xh ) / N = E ( h H h ) / N = ( i ( Re { h i } 2 + Im { h i } 2 ) ) / N = Emax ( 4 ) … N representing the length of the sequence Y in equation (3) above. Para. [0030]-Happonen discloses the length of a symbol sequence is represented by a number N of symbols contained in the sequence).
Markhovsky and Happonen are both considered to be analogous to the claimed invention because they are in the same field of radio telecommunication system, dealing with method and corresponding device for noise energy estimation and/or variance estimation of a signal transmitted via a transmission channel.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Markhovsky in view of Shih to incorporate the teachings of Happonen on channel impulse processing, with a motivation for the procession parameter to comprise step length, and guarantee estimating a signal variance of a received signal transmitted via a transmission channel, (Happonen, Para. [0015]).
Regarding claims 3 and 13, Markhovsky in view of Shih and Happonen teaches the method according to claim 1 and the method according to claim 11 respectively.
Markhovsky further teaches the first information further comprises: first machine learning model information, and first error model information (Para. [0051]-Markhovsky discloses the LSU also includes navigation processor a.k.a. positioning engine - receiving outputs from one or more signal processors and performing position estimation and position tracking calculations by utilizing numerous localization (geolocation). Para. [0739]-Markhovsky discloses performing target localization by applying location consistency algorithms, including machine learning algorithms, to the resulting multiple position estimates. Para. [0677]-Markhovsky discloses to retrieve, preprocess and send the digital samples of the downlink baseband reference signals to the LSU by the SUPL Positioning Calculation Function (SPCF). Also, SPCF modification may include preprocessing of these samples before transferring these to the LSU. Para. [0005]-Markhovsky discloses time synchronization errors impact locate accuracy, ... in the case of DL-OTDOA, that transmissions from multiple antennas be time synchronized, or in the case of U-TDOA, that multiple receivers be time synchronized. Para. [0356]-Markhovsky discloses reflected signals will induce an error in the estimated time difference of arrival (TDOA) and time of arrival (TOA) measurements, including RTT measurements. (See also Para. [0014, 0036, 0126, 0351, 0606, 0751 and Abstract));
the information related to the location of the terminal device further comprises at least one of the following: positioning result information of the terminal device; second machine learning model information determined based on the first machine learning model information; and second preprocessing model information determined based on the first preprocessing model information (Para. [0051]-Markhovsky discloses the LSU also includes navigation processor a.k.a. positioning engine - receiving outputs from one or more signal processors and performing position estimation and position tracking calculations by utilizing numerous localization (geolocation). Para. [0739]-Markhovsky discloses performing target localization by applying location consistency algorithms, including machine learning algorithms, to the resulting multiple position estimates. Para. [0677]-Markhovsky discloses to retrieve, preprocess and send the digital samples of the downlink baseband reference signals to the LSU by the SUPL Positioning Calculation Function (SPCF). Also, SPCF modification may include preprocessing of these samples before transferring these to the LSU. Para. [0005]-Markhovsky discloses time synchronization errors impact locate accuracy, ... in the case of DL-OTDOA, that transmissions from multiple antennas be time synchronized, or in the case of U-TDOA, that multiple receivers be time synchronized. Para. [0356]-Markhovsky discloses reflected signals will induce an error in the estimated time difference of arrival (TDOA) and time of arrival (TOA) measurements, including RTT measurements. Fig. 11, Para. [0351]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique the time of arrival of the signal coming from neighboring base stations (eNB) is calculated. The UE position can be estimated in the handset (UE-based method) or in the network (NT-based, UE-assisted method) once the signals from three base stations are received. The measured signal is the CPICH (Common Pilot Channel). The propagation time of signals is correlated with a locally generated replica. The peak of correlation indicates the observed time of propagation of the measured signal . Time difference of arrival values between two base stations determines a hyperbola. At least three reference points are needed to define two hyperbolas. The location of the UE is in the intersection of these five hyperbolas).
Regarding claims 4 and 14, Markhovsky in view of Shih and Happonen teaches the method according to claim 3 and the method according to claim 13 respectively.
Markhovsky further teaches the positioning result information of the terminal device comprises terminal location information determined based on the first machine learning model information and the first measurement information (Para. [0739]-Markhovsky discloses performing target localization by applying location consistency algorithms, including machine learning algorithms, to the resulting multiple position estimates. Fig. 11, Para. [0351-0352]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique ... The measured signal is the CPICH (Common Pilot Channel) … The pilot signal measurements will occur in idle period).
Regarding claims 5, Markhovsky in view of Shih and Happonen teaches the method according to claim 3.
Markhovsky further teaches the second machine learning model information comprises the first machine learning model information that has been error compensated based on the first error model information (Para. [00048]-Markhovsky discloses unified framework/platform … Enabling machine learning to improve the localization reliability and position fix accuracy. Para. [0696]-Markhovsky discloses Deploying state-of-the-art machine learning to further improve the localization reliability and position fix accuracy. Para. [0754]-Markhovsky discloses data processing unit may also be configured to utilize the observables’ metrics discussed above to mitigate ambiguities of the multilateration position fix, as well as applying location consistency algorithms, including machine learning algorithms).
Regarding claims 7 and 17, Markhovsky in view of Shih and Happonen teaches the method according to claim 3 and the method according to claim 13 respectively.
Markhovsky further teaches the first error model information comprises at least one of second error model information and third error model information (Para. [0007]-Markhovsky discloses a combination of ranging measurements errors and errors caused by the lack of precision synchronization, e.g time synchronization errors. Para. [0019]-Markhovsky discloses limitations like accuracy degradation in target moving scenarios, the constant need of laborious human involvement to build and update the so-called fingerprint maps and also the existence of localization ambiguity and error floor phenomenon),
the second error model information comprises at least one of location error compensation information, measurement error compensation information, device error compensation information, and parameter adjustment information (Para. [0407]-Markhovsky discloses up to 5 OX ranging/locate accuracy improvement for a given signal bandwidth over the performance achieved by the Release 9 DL- OTDOA method and the UL-PRS method of Chen et al. described in the Background section. Thus, applying embodiments of the methods described herein to the Release 9 PRS processing reduces the locate error down to 3 meters or better in 95% of all possible cases. In addition, this accuracy gain will reduce the scheduling complexity and the time between UE position fixes. Fig. 37, Para. [0094]-Markhovsky discloses Timing Advance adjustments. Para. [0449-0450]-Markhovsky discloses time synchronization offsets will be used by the UE and/or eNB(s) involved in the process of obtaining a location fix to adjust the location fix ... The TMO Server will then return an accurate (adjusted) position (locate) fix. Para. [0644]-Markhovsky discloses the UE adjusting its transmission timing with 4 x T.sub.s accuracy, where T.sub.s is the LTE system timing, which is equal to 32.55 ns); and
the third error model information comprises at least one of machine learning model compensation information, preprocessing model compensation information, location error model compensation information, measurement error model compensation information, device error model compensation information, and parameter adjustment model compensation information (Para. [0366-0367]-Markhovsky discloses the multi-path mitigation processor/algorithms (see U.S. Patent No. 7,872,583) that allow separating the DLOS signal and reflected signals, even when DLOS signal is significantly attenuated (10 dB - 20 dB lower) relatively to one or more reflected signals. Thus, the embodiments significantly lower the error in the estimated ranging signal DLOS time-of-flight and consequently TO A, RTT and DTOA measurements ... The remnants of the multi-path interference error can be further reduced by applying the postprocessing techniques, such as, maximum likelihood estimation (e.g., Viterbi Algorithm), minimal variance estimation (Kalman Filter), etc. Para. [0585]-Markhovsky discloses Combining these two position fixes by averaging and/or other means/methods will fiirther reduce the UE position fix error. One estimate is that the error reduction is proportional to the square root of the number of the UE position fixes. In the present disclosure, this number is equal two and the final UE position fix error (T.sub.POS_FINAL *.sup.S 2 21 meter; obtained as: 3.12 / v'2).
Regarding claims 8 and 18, Markhovsky in view of Shih and Happonen teaches the method according to claim 1 and the method according to claim 11 respectively.
Markhovsky further teaches the first measurement information further comprises at least one of the following: a signal measurement result of the terminal device; a signal waveform of the terminal device; a correlation sequence or waveform of the terminal device (Fig. 11, Para. [0351-0352]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique ... The measured signal is the CPICH (Common Pilot Channel). The propagation time of signals is correlated with a locally generated replica. The peak of correlation indicates the observed time of propagation of the measured signal … The pilot signal measurements will occur in idle period. Para. [0295]-Markhovsky discloses to determine the phase of tire one-w'ay from the roundtrip phas.sub.* measurements observation: ... Let h (t) be the one-way impulse response of a communications channel. Para. [0210]-Markhovsky discloses chirp waveforms can be also used. Para. [0108]-Markhovsky discloses the signal processing software combined with minimal hardware, allows assembling the radios that have transmitted and received waveforms defined by the software).
Regarding claims 9 and 19, Markhovsky in view of Shih and Happonen teaches the method according to claim 1 and the method according to claim 11 respectively.
Markhovsky further teaches the method further comprises: reporting third information to a network device (Para. [0026]-Markhovsky discloses the WLAN infrastructure to provide the intennediate and/or other locate information to die LSU, to determine the wireless device location ... processing updates),
the third information is used for the network device to determine the information related to the location of the terminal device, and/or used by the network device to update the first information (Para. [0546]-Markhovsky discloses signal strength approach is fingerprinting, which requires creating and continuously updating an enormous, continuously changing (in time) fingerprint database ... fingerprinting is UE based technology. Claim 5-Markhovsky discloses the positioning engine is continuously providing updates to the position estimation and position tracking calculations, the position estimation, and position related metrics provided to the location management processor. Para. [0026]-Markhovsky discloses the WLAN infrastructure to provide the intennediate and/or other locate information to die LSU, to determine the wireless device location ... processing updates).
Regarding claim 10, Markhovsky in view of Shih and Happonen teaches the method according to claim 1.
Markhovsky further teaches the method further comprises: receiving second information (Para. [0704]-Markhovsky discloses the detection process examines the magnitude and phase of the output of the cross-correlation to determine whether or not the reference signal sent by the emitter and captured at the receiver has sufficient properties in order for the TOA of the received signal to be correctly estimated. (See also Para. [0007-0008 and 0398])),
the second information is used to indicate whether third information is to be reported to a network device (Para. [0704-0705]-Markhovsky discloses the detection process examines the magnitude and phase of the output of the cross-correlation to determine whether or not the reference signal sent by the emitter and captured at the receiver has sufficient properties in order for the TOA of the received signal to be correctly estimated ... [0705] Compression: If the properties of the signal are sufficient, the output of the cross- correlation is marked as valid and the non-zero portion of the complex vector is sent to a secondary' processing block for TOA estimation. In this method, the TOA estimation block can be remotely located from the Emitter detection engine. Para. [0622]-Markhovsky discloses Additional information may include whether the serving cell is the closest cell and whether the serving cell has the highest SNR/SNIR. (See also Para. [0007-0008 and 0398])).
Regarding claim 16, Markhovsky in view of Shih and Happonen teaches the method according to claim 11.
Markhovsky further teaches the first preprocessing model information further comprises at least one of the following: a filter parameter or model; a convolutional layer parameter or model; a pooling layer parameter or model; a discrete cosine transform DCT parameter or model; a wavelet transform parameter or model; a model of a channel impulse processing method; a parameter or model of a waveform processing method; and a parameter or model of a signal correlation sequence processing method (Para. [0712]-Markhovsky discloses the detector may be configured to perform additional pre processing (to further reduce data size), including matched filtering of signals used for device localization, calculating singular-value decomposition (SVD) principle eigenvalues of a matrix formed from one or more of the signals.sup.’ digital samples. This additional pre-processing is a tradeoff between the computational load/resources vs reduction of communication bandwidth with a localization server).
Regarding claim 21, Markhovsky in view of Shih and Happonen in view of Happonen teaches the method according to claim 3.
Markhovsky further teaches the second preprocessing model information comprises the first preprocessing model information that has been error compensated based on the first error model information (Para. [0754]-Markhovsky discloses data processing unit may also be configured to utilize the observables’ metrics discussed above to mitigate ambiguities of the multilateration position fix, as well as applying location consistency algorithms, including machine learning algorithms. Para. [0677]-Markhovsky discloses to retrieve, preprocess and send the digital samples of the downlink baseband reference signals to the LSU by the SUPL Positioning Calculation Function (SPCF). Also, SPCF modification may include preprocessing of these samples before transferring these to the LSU. Para. [0007]-Markhovsky discloses a combination of ranging measurements errors and errors caused by the lack of precision synchronization, e.g time synchronization errors. Para. [0407]-Markhovsky discloses up to 5 OX ranging/locate accuracy improvement for a given signal bandwidth over the performance achieved by the Release 9 DL- OTDOA method and the UL-PRS method of Chen et al. described in the Background section. Thus, applying embodiments of the methods described herein to the Release 9 PRS processing reduces the locate error down to 3 meters or better in 95% of all possible cases. In addition, this accuracy gain will reduce the scheduling complexity and the time between UE position fixes. Fig. 37, Para. [0094]-Markhovsky discloses Timing Advance adjustments. Para. [0449-0450]-Markhovsky discloses time synchronization offsets will be used by the UE and/or eNB(s) involved in the process of obtaining a location fix to adjust the location fix ... The TMO Server will then return an accurate (adjusted) position (locate) fix. Para. [0644]-Markhovsky discloses the UE adjusting its transmission timing with 4 x T.sub.s accuracy, where T.sub.s is the LTE system timing, which is equal to 32.55 ns).
Response to Arguments
Applicant's Arguments/Remarks, filed on 04/27/2026, with respect to the 35 USC § 103 rejection of claims 1, 3-5, 7-11, 13-14 and 16-21 have been fully considered. Applicant’s arguments are not persuasive.
In the remarks, on page 11, Line [8], Applicant argues that, “…Markhovsky is not associated with the "channel impulse response."” Examiner respectfully disagrees for the following reasons:
In Para. [0425]-Markhovsky discloses the LTE uplink signaling also includes reference signals, mobile device to base, which also contains reference subcarriers. In fact there is more than one mode in which contain these subcarriers from a full sounding mode used by the network to assign a frequency band to the uplink device to a mode where are reference subcarriers are used to generate a channel impulse responses to aid in demodulation of the uplink signal, etc. (See also Para. [0295-0297]). Fig. 1A, Para. [0149]-Markhovsky discloses the exemplary ranging signal employs different frequency components that are contiguous. Other waveforms, including pseudo random, spaced in frequency and/or time or orthogonal, etc. can be also used for as long as the ranging signal bandwidth remains narrow'.….
In the remarks, on page 11, Lines [15-18], Applicant argues that, “…Markhovsky does not disclose, teach or suggest "determining information related to the location of the terminal device based on the channel impulse response of the terminal device," as involved in amended claim 1 of the present application.”
However, Markhovsky teaches the location of the terminal device (Fig. 11, Para. [0351]-Markhovsky discloses in the Observed Time Difference of Arrival (OTDOA) technique the time of arrival of the signal coming from neighboring base stations (eNB) is calculated. The UE position can be estimated in the handset (UE-based method) or in the network (NT-based, UE-assisted method) once the signals from three base stations are received. The measured signal is the CPICH (Common Pilot Channel). The propagation time of signals is correlated with a locally generated replica. The peak of correlation indicates the observed time of propagation of the measured signal. Time difference of arrival values between two base stations determines a hyperbola. At least three reference points are needed to define two hyperbolas. The location of the UE is in the intersection of these five hyperbolas), while
Shih discloses determining, based on the first information and first measurement information of a terminal device, the information related to the location of the terminal device (Para. [0010]-Shi discloses the measurement data is obtained based on a downlink reference signal received by the terminal device, the measurement data is used by the positioning service function entity to estimate a location of the terminal device, and the measurement data includes at least one of the following: a channel estimation and a channel impulse response).
In the remarks, on page 11, Lines [21-24], Applicant argues that, “…Markhovsky therefore also fails to disclose, teach or suggest the second measurement information, wherein the second measurement information is obtained by performing sparsification or dimensionality reduction on the channel impulse response using the step length.”
However, Markhovsky teaches the second measurement information comprises at least one of the following: a sparse channel impulse response, and a multipath-represented channel impulse response (Para. [0425]-Markhovsky discloses to generate a channel impulse responses to aid in demodulation of the uplink signal, etc. Also, similarly to the DL PRS added in rel.9 additional UL reference signals might be added in the upcoming and future standard releases. In this embodiment, the uplink signal is processed by multiple base units (eNB) using the same range to phase, multipath mitigation processing to generate range related observables), while
Shih teaches the second measurement information comprises at least one of the following: a sparse channel impulse response, and a multipath-represented channel impulse response (Para. [0075-0081]-Shi discloses if a coefficient of the Fourier transform is L and L≥M, L-point IDFT or IFFT is performed for the channel estimation to obtain a sequence having a length L, namely, a channel impulse response. Optionally, to reduce a sending amount, the channel impulse response whose length is L may be filtered, to extract valid information for transmission. A specific process may be as follows: ... The channel estimation obtained from the reference signal is h=[h.sub.1, . . . , h.sub.m, . . . h.sub.M]).
In the remarks, on pages 11 and 12, Lines [25-26 and 16-17 respectively], Applicant argues that, “…regarding the Patent Office's assertion that Happonen discloses the step length in claim 1, Applicant respectfully disagrees,” and “…regarding the Patent Office's assertion that Shi discloses the step length in claim 1, Applicant respectfully disagrees” respectively.
However, Happonen teaches the parameter of the channel impulse processing method comprises a step length (Para. [0033-0046]-Happonen discloses h denotes an estimated channel impulse responses ... the energy of the signal/symbol can be rewritten to read 1 E ( h H X H Xh ) / N = E ( h H h ) / N = ( i ( Re { h i } 2 + Im { h i } 2 ) ) / N = Emax ( 4 ) … N representing the length of the sequence Y in equation (3) above. Para. [0030]-Happonen discloses the length of a symbol sequence is represented by a number N of symbols contained in the sequence), while
Shih teaches the parameter of the channel impulse processing method comprises a step length (Para. [0077-0080]-Shi discloses to obtain a sequence having a length L, namely, a channel impulse response. Optionally, to reduce a sending amount, the channel impulse response whose length is L may be filtered, to extract valid information for transmission. A specific process may be as follows: ... Perform an IDFT or IFFT operation on the zero-padded sequence h′ to obtain a channel impulse response sequence f′=[f′.sub.1, . . . , f′.sub.l, . . . f.sub.L′] whose length is also L).
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant`s disclosure.
LAVY LEV et al. (WO 2018225067 A1)-discloses A sensor processing device located within a vehicle that is being driven, the processing device communicating with plural sensors, each sensor generating signal data, the processing device including a transceiver transmitting data derived by the processing device from the sensor signal data, to one or more remote servers, and receiving sensor-related information from the one or more remote servers, a synchronizer evaluating latencies of the sensors, an error estimator estimating accuracies of the sensor signal data, a sensor validator determining if one or more of the sensors are failed, and a calibrator transforming the sensor signal data to a common vehicle reference system…. …Fig. 1-5
Wu et al. (US 20220026519 A1)-discloses at least one sensor configured to generate at least one sensing information (SI); a memory; a processor communicatively coupled to the memory and the at least one sensor; and a set of instructions stored in the memory. The set of instructions, when executed by the processor, cause the processor to: obtain at least one time series of SI (TSSI) from the at least one sensor, analyze the at least one TSSI, track a movement of an object in a venue based on the at least one TSSI, compute an incremental distance associated with the movement of the object in a first incremental time period based on the at least one TSSI, compute a direction associated with the movement of the object in a second incremental time period based on the at least one TSSI, and compute a next location of the object at a next time based on at least one of: a current location of the object at a current time, a current orientation of the object at the current time, the incremental distance, the direction, or a map of the venue…. …Fig. 1-5
Chen et al. (CN 106851821 A)-discloses establishing a station weighted-voting model. Time of arrival (TOA) model pre-treatment splitting process is performed for splitting a real time delay model, a noise model and an interference time delay model. A machine learning a metric adjustment model is established for optimizing TOA data. A precise multi-point three- dimensional positioning model is established to calculate a terminal precisely coordinate to detect indoor three-dimensional location. A base station positioning region coordinate is calculated according to a cross degree defined location region.… …Fig. 1
Shi et al. (US 20200333424 A1)-discloses a method, an apparatus, and a system for positioning a terminal device. Location measurement data for a to-be-positioned terminal device is obtained by a terminal-side measurement function entity and/or an access-side measurement function entity, where the location measurement data includes a channel estimation and/or a channel impulse response that are/is obtained based on a corresponding downlink/uplink reference signal. The terminal-side measurement function entity and/or the access-side measurement function entity report/reports the location measurement data to a positioning service function entity in a network, so that the positioning function entity can estimate a location of the terminal device based on the location measurement data, thereby positioning the terminal device and improving positioning accuracy. This technical solution can be applied to both a single-base-station-based positioning environment and a multi-base-station-based positioning environment, to position the terminal device…. …Fig. 1-5
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/OO/
Examiner, Art Unit 2472
/NICHOLAS A JENSEN/Supervisory Patent Examiner, Art Unit 2472
