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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/03/2025 and 07/07/2025 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite a mental process. This judicial exception is not integrated into a practical application as analyzed below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception as analyzed below.
Independent Claim Analysis
STEP 1: YES. The claims meet the statutory categories.
Claims 1-13 fall within a statutory category of machine.
Claims 14-20 fall within a statutory category of process.
STEP 2A: PRONG ONE YES. The claims are directed to a judicial exception.
Claim 1 recites “determining determining at least one target channel feature from a determining a difference between the determining a weight for the ” These limitations as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process as this could be performed in the human mind using observation, evaluation (determining), judgment (determining a weight), and opinion or with the aid of pen and paper.
Claim 14 recites the same limitations of claim 1 in method form.
STEP 2A Prong Two: NO. Evaluating additional elements recited in the claim individually and in combination, the claim as a whole does not integrate the exception into a practical application.
In plain language, the claim steps above in the broadest reasonable interpretation (BRI) comprise determining features, determining a measurement , comparing the difference and assigning a weight to the difference.
These steps are merely a mental process (i.e. receiving and evaluating a difference). Examiner notes mental process includes describe mental observations and evaluations that can be performed in the human mind using observation, evaluation, judgment, and opinion and also those performed with a pen/pencil or a general purpose computer (i.e. graphing, mapping, calculations), as noted in the case law cited above. The elements in claim 1, i.e. at least one processor and at least one memory are merely generic computer components performing generic computer functions.
The claim does not recite:
A specific improvement to network technology (no network technology is claimed)
A special configuration that yields a technical benefit/implementation (no action is performed using the determined weight)
Any operational interaction among components beyond their ordinary use (i.e. determining conditions)
Accordingly, the claim is directed to an abstract idea.
STEP 2B: NO. Evaluating additional elements recited, the claim as a whole does not recite additional elements that amount to significantly more than the judicial exception.
The additional elements in claim 1, channel features, are not claimed in a way that improves a network technology or yield a technical benefit, see below. The limitations are merely data gathering and recited at a high level of generality and amount to a determination and a comparison which it well-understood, routine and conventional activity. See MPEP 2106.05(d), subsection II.
The claim does not amount to significantly more because:
Generic processor does not constitute a “particular machine”
No non-conventional technological implementation is disclosed
The limitations remain insignificant extra-solution activity even upon reconsideration. Even when considered in combination, the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept.
Dependent Claim Analysis
ANALYSIS 2A Dependent Claims 2-13, and 15-20
Dependent claims recite additional elements:
Claim 5: “performing”, no technical improvement to target positioning measurement nor the weight that was evaluated in claim 1
Claim 6: while LOS and NLOS are specific technologies, the claim is still an abstract idea because there’s technical improvement where the weight that was determined in claim is applied
Claim 10: “transmitting”, while transmitting is well-understood, routine and conventional activity, there is no technical improvement regarding the weight that was applied in claim 1.
The dependent claims further recite additional elements that are recited at a high level of generality and thus amount to determining features, determining a measurement , comparing the difference and assigning a weight to the difference. Thus the claims are mere data gathering and output recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering, evaluation, and judgment. See MPEP 2106.05.
ANALYSIS 2B Dependent Claims 2-13, and 15-20 NO. Evaluating additional elements recited, the claim as a whole does not recite additional elements that amount to significantly more than the judicial exception.
The analysis above in parts and re-evaluated again for the claims as a whole, the additional elements are mere determining, evaluating (comparing a difference), and judgement (assigning a weight) recited at a high level of generality and amount to receiving or transmitting data over a network, which is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
The limitations remain insignificant extra-solution activity even upon reconsideration. Even when considered in combination, the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept.
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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kudekar et al. (US Publication No. 20160249316 A1 and Kudekar hereinafter).
Regarding Claim 1, Kudekar discloses a first device comprising (i.e. The process illustrated in FIG. 4 can be implemented using the mobile device 120 illustrated in FIGS. 1-3) Para [0043]: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first device at least to perform (See Figure 2 and 3; i.e. The DSP 220 can be configured to process signals received from the wireless interface 225 and/or the GNSS interface 265 and may be configured to process signals for or in conjunction with one or more modules implemented as processor-readable, processor-executable software code stored in memory 260 and/or can be configured process signals in conjunction with the processor 210.) Para [0036]: determining a set of channel features and a set of reference values associated with the set of channel features (i.e. The range estimate can be determined by the mobile device 120 and/or the other wireless device 120 with which the mobile device 120 exchanges signals in stage 405. The position determination module 362 and/or the range classification module 364 of the mobile device 120 can be configured to determine the estimated range between the mobile device and the other wireless device using various techniques. For example, the estimated range between the mobile device 120 and the other wireless device can be determined using RTT and/or TOA techniques. The other wireless device can also be configured to determine the range estimate and to send the range estimate to the mobile device 120 based on signals from the mobile device 120 received by the other wireless device.) Para [0045]; determining at least one target channel feature from a target positioning measurement based on the set of channel features (i.e. The range estimate can be classified as a LOS range estimate or an NLOS range estimate by the other wireless device and/or the mobile device 120. For example, the range classification module 364 of the mobile device 120 can be configured to use the CIR data to classify the range estimate. The range classification module 364 can be configured to use one or more of the following features determined at least in part from the CIR information: (a) kurtosis: normalized (with respect to second moment) fourth moment of the CIR; (b) energy: the exponent of the path loss; (c) rise time: the time between the first peak above the noise threshold and the largest peak; and (d) delay spread: the time between the first peak above the noise threshold and the last peak above the noise threshold.) Para [0046]; determining a difference between the target positioning measurement and at least one reference value in the set of reference values based on the at least one target channel feature (i.e. the range classification module 364 can be configured to determine each of the four features discussed above and/or additional or other features. In other implementations, the classifier can be configured to take a subset of these features into consideration. One example implementation takes into account kurtosis and path loss to determine whether a range estimate is an NLOS range estimate or a LOS range estimate.) Para [0051]; and determining a weight for the target positioning measurement based on the difference (i.e. The range classification module 364 can be configured to determine a confidence level that the range classification module 364 has in a particular classification of a range estimate as a NLOS range estimate or a LOS range estimate. The range classification module 364 can be configured to determine a confidence level associated with the classification based on the weights. For example, if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate.) Para [0053].
Regarding Claim 14, Kudekar suggests all the limitations of claim 1 in method form rather than device form. Further Kudekar discloses a method (i.e. A method according to these techniques includes determining channel impulse response (CIR) information based on at least one measurement of signals exchanged between the mobile device and another wireless device) Abstract. Therefore, the rejection of claim 1 applies equally as well to the limitations of claim 14.
Regarding Claim 2 and Claim 15, Kudekar discloses all the limitations of claims 1 and 14, respectively, as discussed above. Further Kudekar discloses determining the set of channel features and the set of reference values associated with the set of channel features comprises: receiving from a second device first information indicating at least one of: the set of reference values and the set of channel features (i.e. The other (i.e. second device) wireless device can also be configured to determine the range estimate and to send the range estimate to the mobile device 120 (i.e. first device)…) Para [0045] and (i.e. The position determination module 362 can also be configured to request and receive almanac data from a network entity (i.e. second device), such as the location server 160. The position determination module 362 can also be configured to use measurements of signals received from wireless base stations 140 and/or wireless transmitters 115 to determine a position of the mobile device 120) Para [0040].
Regarding Claim 3 and Claim 16 Kudekar discloses all the limitations of claims 1 and 14, respectively, as discussed above. Further Kudekar discloses the first device is caused to perform: transmitting to a second device a request for at least one of: the set of channel features and the set of reference values associated with the set of channel features (i.e. The position determination module 362 can also be configured to request and receive almanac data from a network entity (i.e. second device), such as the location server 160. The position determination module 362 can also be configured to use measurements of signals received from wireless base stations 140 and/or wireless transmitters 115 to determine a position of the mobile device 120) Para [0040].
Regarding Claim 4 and Claim 17 Kudekar discloses all the limitations of claims 1 and 14, respectively, as discussed above. Further Kudekar discloses determining the set of channel features and the set of reference values associated with the set of channel features comprises: determining the set of channel features from a set of measurements (i.e. the range classification module 364 of the mobile device 120 can be configured to use the CIR data to classify the range estimate. The range classification module 364 can be configured to use one or more of the following features determined at least in part from the CIR information: (a) kurtosis: normalized (with respect to second moment) fourth moment of the CIR; (b) energy: the exponent of the path loss; (c) rise time: the time between the first peak above the noise threshold and the largest peak; and (d) delay spread: the time between the first peak above the noise threshold and the last peak above the noise threshold.) Para [0046]; clustering the set of channel features into a number of classes based on the set of channel features (i.e. the range classification module 364 can be configured to determine each of the four features discussed above and/or additional or other features. In other implementations, the classifier can be configured to take a subset of these features into consideration.) Para [0051]; and determining the set of reference values for the classes (i.e. implementation takes into account kurtosis and path loss to determine whether a range estimate is an NLOS range estimate or a LOS range estimate.) Para [0051].
Regarding Claim 5 and Claim 18, Kudekar discloses all the limitations of claims 4 and 17, respectively, as discussed above. Further Kudekar discloses the first device is caused to perform: performing a contradiction check on the set of reference values (i.e. A determination whether the estimated range is greater than a range threshold can be made (stage 805). The range classification module 364 can be configured to use different factors for classifying a range estimate based on the distance that the mobile device 120 is from other wireless device. The range classification module 364 can use the range estimate to determine whether the mobile device 120 is more than a predetermined distance from the other wireless device and select which factors to consider when determining the classification of the range estimate based on those factors (i.e. the recited contradiction check on reference values). If the distance between the mobile device 120 and the other device is not greater than the predetermined threshold distance, then the process continues with stage 810. Otherwise, the process continues with stage 815.) Para [0067].
Regarding Claim 6 and Claim 19, Kudekar discloses all the limitations of claims 1 and 14, respectively, as discussed above. Further Kudekar discloses determining the difference between the target positioning measurement and the at least one reference value comprises: determining a first difference between the target positioning measurement and a first reference value which is associated with line-of-sight channel (i.e. if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate.) Para [0053]; and determining a second difference between the target positioning measurement and a second reference value which is associated with non-line-of-sight channel (i.e. if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate.) Para [0053].
Regarding Claim 7 and Claim 20, Kudekar discloses all the limitations of claims 1 and 14, respectively, as discussed above. Further Kudekar discloses determining the difference between the target positioning measurement and the at least one reference value comprises: determining from the set of reference values a third reference value which is associated with a more line-of-sight-like channel than other reference values in the set of reference values (i.e. if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate… if the range classification module 362 were configured to provide a hard classification, the range classification module 364 could be configured to determine that the range estimate is a LOS range estimate based on the weights associated with each of the factors.) Para [0053]; determining from the set of reference values a fourth reference value which is associated with a more non-line-of-sight-like channel than other reference values in the set of reference values (i.e. if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate. ) Para [0053] Examiner notes that in the above scenario, the example was given for a more LOS estimate, it is obvious that the values could also allow for a more NLOS estimate.; determining a third difference between the target positioning measurement and the third reference value (i.e. The particular weights associated with the factors in the example are intended to demonstrate the concepts discussed herein and are not intended to limit the weights that the range classification module 374 can associate with different factors used to classify the range estimate to these particular values.) Para [0053]; and determining a fourth difference between the target positioning measurement and the fourth reference value (i.e. The particular weights associated with the factors in the example are intended to demonstrate the concepts discussed herein and are not intended to limit the weights that the range classification module 374 can associate with different factors used to classify the range estimate to these particular values.) Para [0053].
Regarding Claim 8, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses determining the difference between the target positioning measurement and the at least one reference value comprises: determining differences between the target positioning measurement and a plurality of reference values in the set of reference values (i.e. classify the range estimate as NLOS or LOS based on whether the value of a is closer to the expected LOS path-loss component or the expected NLOS path-loss component. For example, the expected NLOS path-loss component may be set to value of approximately 3 (i.e. reference value) for a typical indoor environment and the expected LOS path-loss component may be set to a value of approximately 1.6 for a typical indoor environment. If the exponent of the path-loss is determined to be 1.8 for a particular range estimate (i.e. target positioning measurement), the range classification module 364 can be configured to classify the range estimate as a LOS range estimate, because the value of the path-loss component is closer to the expected LOS path-loss exponent for this example scenario. The values of the expected NLOS path-loss component and the expected LOS path-loss component may vary) Para [0050], respectively.
Regarding Claim 9, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses determining the weight for the target positioning measurement comprises: determining the weight as a function of the difference (i.e. if the range classification module 364 has determined a weighted range classification where a first factor is associated with a weight of 0.25 and the range classification associated with the first factor is indicative that the range estimate is an NLOS range estimate, while a second factor is associated with a weight of 0.75 and is indicative that the range estimate is a LOS range estimate, the range classification module 362 can be configured to provide generate a soft classification with a confidence level indicative that the range estimate is 75% likely to be a LOS range estimate and 25% likely to be a NLOS range estimate.) Para [0053].
Regarding Claim 10, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses the first device is caused to perform: transmitting to a second device (i.e. The range classification module 364 can provide means for performing the various classification techniques discussed herein unless otherwise specified. The range classification module 364 can be configured to determine whether a range estimate between the mobile device 120 and another wireless device is an NLOS range estimate or a LOS range estimate based on various criteria (i.e. weights). The other (i.e. second device) wireless device may be a wireless transmitter 115, another mobile device 120, or a wireless base station 140.) Para [0041] second information indicating the weight for determining a position estimation by the second device (i.e. the range classification module 362 were configured to provide a hard classification, the range classification module 364 could be configured to determine that the range estimate is a LOS range estimate based on the weights associated with each of the factors.) Para [0053] and (i.e. the position determination module 362 can be configured to use the range estimate or estimates in conjunction with other sources of information, such as measurements collected from one or more GNSS satellites and/or other sources of information that can be used to determine the location of the mobile device, such as the location server 160.) Para [0054].
Regarding Claim 11, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses the first device is caused to perform: determining a position estimation based on the weight (i.e. The range estimate and the classification of the range estimate can be used to determine the position of the mobile device (stage 415). The range estimate and the classification of the range estimate can be passed to the position determination module 362 of the mobile device 120 which can be configured determine a position of the mobile device 120. The position determination module 362 can be configured to use the range estimate and the classification of the range estimate to determine the position of the mobile device in addition to other range estimates and classifications of range estimates provided by the range classification module 364. The range classification module 364 can be configured to provide the range estimate or range estimates to the position determination module 362 in response to a request from the position determination module 362 associated with one or more wireless devices proximate to the mobile device 120.) Para [0054].
Regarding Claim 12, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses the set of channel features comprises at least one of: a root mean square delay spread, a channel response or received waveform amplitude, a channel response or received waveform rise time, a channel response or received waveform kurtosis, a Rician K factor, an average energy of a channel response or received waveform, a total energy of the channel response or received waveform, an average amplitude of the channel response or received waveform, a total amplitude of the channel response or received waveform, a mean excess delay, a skewness of the channel response or received waveform, a standard deviation of the channel response or received waveform, or a standard variance of the channel response or received waveform (i.e. The range estimate can be classified as a LOS range estimate or an NLOS range estimate by the other wireless device and/or the mobile device 120. For example, the range classification module 364 of the mobile device 120 can be configured to use the CIR data to classify the range estimate. The range classification module 364 can be configured to use one or more of the following features determined at least in part from the CIR information: (a) kurtosis: normalized (with respect to second moment) fourth moment of the CIR; (b) energy: the exponent of the path loss; (c) rise time: the time between the first peak above the noise threshold and the largest peak; and (d) delay spread: the time between the first peak above the noise threshold and the last peak above the noise threshold.) Para [0046].
Regarding Claim 13, Kudekar discloses all the limitations of claim 1, as discussed above. Further Kudekar discloses the first device comprises one of: a first terminal device (i.e. The process illustrated in FIG. 4 can be implemented using the mobile device 120 illustrated in FIGS. 1-3) Para [0043], a first core network device or a first network device; and wherein the second device comprises one of: a second terminal device, a second core network device, or a second network device (i.e. The wireless transmitter of the mobile device 120 (i.e. first terminal device) can be configured to send data to and/or receive data from other (i.e. second terminal device) mobile devices 120, the wireless transmitters 115, and/or one or more wireless base stations 140 (i.e. second network device).) Para [0024].
Pertinent Prior Art
The prior art made of record is considered pertinent to applicant's disclosure.
Kudekar et al. (US Publication No. 20160249316 A1) “NON-LINE-OF-SIGHT (NLOS) AND LINE-OF-SIGHT (LOS) CLASSIFICATION TECHNIQUES FOR INDOOR RANGING” (August 25, 2016) is directed to techniques for use in determining a position of a mobile device are provided in which a range estimate can be classified as a line-of-sight (LOS) range estimate or a non-line-of-sight (NLOS) range estimate and the range estimate and classification can be used to determine the position of the mobile device. A method according to these techniques includes determining channel impulse response (CIR) information based on at least one measurement of signals exchanged between the mobile device and another wireless device; classifying a range estimate representing an estimated distance between the mobile device and the other wireless device as a line-of-sight (LOS) range estimate or a non-line-of-sight (NLOS) range estimate based at least in part on the CIR information; and using the range estimate and the classification of the range estimate to determine the position of the mobile device.
Irvine et al. (US Publication No. 20200142025 A1) “Observed time difference of arrival angle of arrival discriminator” (May 7, 2020) is directed to a method, user equipment (UE) and location server for estimating position of a UE based on observed angles of arrival. According to one embodiment, angles of arrival of signals from a plurality of base stations are received by a UE are observed by scanning for position reference signals (PRS) by adjusting a phase difference between antennas to cause a null of a beam of the UE to be incremented through an angular sector. For each of a plurality of base stations, an angle of arrival at which the null is steered when a PRS is suppressed by the null and a reference signal time difference, RSTD, are determined. Each angle of arrival and corresponding RSTD is transmitted to a location server which estimates UE position based on the observed angles of arrival. Further, the location server may instruct the UE to suppress a non-line-of-sight PRS signal.
Yerramalli et al (US Publication No. 20220070028 A1) “NEURAL NETWORK BASED LINE OF SIGHT DETECTION AND ANGLE ESTIMATION FOR POSITIONING” (March 3, 2022) is directed to neural network based positioning of a mobile device. An example method for determining a line of sight delay, an angle of arrival, or an angle of departure value includes receiving reference signal information, determining one or more windowed channel impulse responses based on the reference signal information and one or more window functions, processing the one or more windowed channel impulse responses with a neural network, and determining an output of the neural network.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Iyonda L. Lewis whose telephone number is (571)272-4440. The examiner can normally be reached Monday - Friday 8:00am - 4:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alison Slater can be reached at (571) 270-0375. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/IYONDA L LEWIS/Patent Examiner, Art Unit 2647
Iyonda.Lewis@USPTO.gov
/DIANE D MIZRAHI/Primary Examiner, Art Unit 2647
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