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 .
Status of Claims
This is in response to applicant’s filing date of July 24, 2024, filed with a preliminary cancelling claims 1-16 and adding claims 17-33. Claims 17-33 are currently pending.
Priority
Acknowledgment is made of applicant’s claim for foreign priority to Application EP22305275.4, filed on March 11, 2022. The certified copy of the application as required by 37 CFR 1.55 has been received.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on July 24, 2024, is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority to Prio-File Application
Applicant’s claim for the benefit of a prior-filed application, PCT/JP2022/041280 filed on 10/28/2022, under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
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.
Claim 31 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to a " computer program " that can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. (See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 17-33 are rejected under 35 U.S.C. 103 as being unpatentable over Chatbonnier et al , (NPL:“Calibration of Ray-Tracing With Diffuse Scattering Against 28-GHz Directional Urban Channel Measurements")(“Chatbonnier”), provide by Applicant in the IDS filed on 7/24/2024, in view of Wu et al (US-20210190702-A1)(“Wu”).
As per claim 17, Chatbonnier discloses a computer implemented method for characterizing a radiofrequency environment (Figure 3), the method comprising:
obtaining measurements of geometrical properties of physical objects in the radiofrequency environment, said geometrical properties including at least respective positions and dimensions of said physical objects (Chatbonnier at Page 14269, section A , ray tracing settings, positions and dimensions are from OpenStreetMap and heights are estimated from number of floors),
simulating radiofrequency ray-tracings involving a multiplicity of simulated rays (Chatbonnier at Page 14269, ray tracing process), each ray being (Chatbonnier at Page 14270 disclosing that the same ray which was predicted will be mapped to a measured ray.):
emitted by a transmitter located in said radiofrequency environment in a transmitter position (Chatbonnier at Page 14266, section B, RX mounted on mobile device (robot) positioned using a GPS device.), and/or
received by a receiver located in said radiofrequency environment in a receiver position (Chatbonnier at Page 14266, section B, RX mounted on mobile device (robot) positioned using a GPS device at 1.6m.), each pair of a transmitter position and a receiver position defining therebetween a radiofrequency path where simulated rays possibly interact with at least a part of said physical objects (Figure 5), - selecting, among all the radiofrequency paths, at least one radiofrequency path (Page 14273, stronger diffuse reflections from vehicle selecting from rays.), - obtaining radiofrequency measurements of a radiofrequency channel defined by the selected path (Figure 1, from drive test) and estimating radiofrequency properties of physical objects interacting in said selected path (, Said radiofrequency properties and said geometrical properties of said physical objects characterizing thereby said radiofrequency environment (Table 1 with calibrated RF properties), wherein said selection comprises:
Chatbonnier does not explicitly disclose a process for assigning to the physical objects scores sk of interactions with the simulated rays, and - selecting, among all the radiofrequency paths, at least one radiofrequency path defined by simulated rays interacting with the physical objects having the highest scores sk.
Wu in the same field of endeavor of characterizing a radiofrequency environment discloses a process for obtaining object analytics from the reflected wireless signals.
In particular Wu discloses assigning to the physical objects scores sk of interactions with the simulated rays (Wu at Para. [0123] discloses clustering return signals and assigning a tag which in the broadest sense is a score for a particular object:” classifier may partition TSCI (or the characteristics/STI or other analytics or output responses) into clusters and associate the clusters to specific events/objects/subjects/locations/movements/activities. Labels/tags may be generated for the clusters. The clusters may be stored and retrieved.”) and - selecting, among all the radiofrequency paths, at least one radiofrequency path defined by simulated rays interacting with the physical objects having the highest scores sk (Wu at Para. [0194] discloses selecting an identified/scored object based on a high score such as peak value:” set of selected significant local peaks may be selected from the set of identified significant local peaks based on a selection criterion (e.g. a quality criterion, a signal quality condition). The characteristics/STI of the object may be computed based on the set of selected significant local peaks and frequency values associated with the set of selected significant local peaks. In one example, the selection criterion may always correspond to select the strongest peaks in a range. While the strongest peaks may be selected, the unselected peaks may still be significant (rather strong).”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify ray tracing engine as taught by Chatbonnier with the material analytics as taught by Wu with a reasonable expectation of success in order for the one or more method steps to select those materials/objects that have the highest characteristics/score for reflecting a wireless signal. The teaching suggestion/motivation to combine is that by selecting peak signal range accuracy and resolution of reflection signals can be improved as taught by Wu in Para. [0255] -[0256].
As per claim 18, Chatbonnier and Wu disclose a method according to claim 17, further comprising: generating a radio propagation digital twin from said characterization of the radiofrequency environment (Chatbonnier at Page 14272, calibrate ray-tracing in column 2, the ray-tracing is the digital twin since a model is used.).
As per claim 19, Chatbonnier and Wu disclose a method according to claim 17, wherein said selected radiofrequency path defines a transmitter position and a receiver position, and the method further comprises: piloting at least one robot carrying at least one of a transmitting antenna and a receiving antenna, so as to position said robot at one of said transmitter position and receiver position, and control the robot to carry out said radiofrequency measurements at said one of said transmitter position and receiver position (Chatbonnier at Page 14266, discloses positioning the rover for data collection:” rover enabled rapid and continuous collection of channel data while recording the location, velocity, and heading of the Rx array per acquisition essential to the analysis of the data collected.”).
As per claim 20, Chatbonnier and Wu disclose a method according to claim 19, wherein a plurality of radiofrequency paths are selected and wherein - a fixed transmitting antenna is provided (Chatbonnier at Page 14266 disclosing that the transmitter is placed at a fixed/stationary location:” stationary Tx was mounted on a tripod at 2.5 m in a parking lot; the Rx was mounted on the mobile rover at 1.6 m.”), and the robot is equipped with a receiving antenna and is piloted to occupy successive receiver positions defined by said selected paths (Chatbonnier at 14266 discloses that the rover/robot has receiving antenna and is positioned at various locations to receive a transmitted signal:” rover followed a linear trajectory along the sidewalk(shown in Fig. 1(b)) with an average speed of 0.35 m/s, under a canopy of trees and aligned by cars on both sides. TheTx-Rx distance ranged from 6.1 m to 66.1 m, over which 61channel captures were collected, with an average of 1.1 m in between.”).
As per claim 21, Chatbonnier and Wu disclose a method according to claim 17, wherein said simulation of ray-tracings comprises:
subdividing each simulated ray into subpaths where the simulated ray is deemed to encounter a physical object of the radiofrequency environment, - estimating an interaction of the simulated ray with the physical object encountered in a subpath, and - for each interaction, estimating and recording at least (Wu at Figure 1B, transmitted signal shown with sub-paths from TX to RX, and Para. [0249] disclosing that the signal is reflected by an object and that the interaction can be estimated:” Bot 111 may transmit a wireless signal 114, which is reflected by a surface of an object 115. The object 115 may be a wall, a piece of furniture, a device, a person, an animal, etc. The surface material of the object 115 may impact the wireless signal 114, such that the reflected wireless signal 116 after the reflection at the surface can include information related to the type of the surface material.”):
a nature of interaction among at least a reflection, a refraction, a diffraction, " an incident angle of the ray relatively to the encountered physical object, and " data of the encountered physical object (Wu at Paras. [0248]-[0249] discloses that certain parameters of the material/object can be determined from the reflected signal:” mSense exploits the signals reflecting off the target and employs a single commodity mmWave networking radio. Different objects, depending on their specific materials, reflect the incident electromagnetic waves at distinct extents. For example, metals typically reflect much more energy than woods. The mSense system circumvents the need to put up two or more radios on both sides of the target or to instrument it with any device, and thus allows everyday usage in ubiquitous environments. To identify the target material, a user can simply point the radio towards the target, either holding it still or moving it for a short distance. The mSense system can then measure Channel Impulse Response (CIR) of the reflected signals and calculates a novel parameter from the extracted CIR to determine the material type, without involving any unexplainable features or machine learning.”).
As per claim 22, Chatbonnier and Wu disclose a method according to claim 17, wherein said scores of interactions of said physical objects are given by scores sk of impact of said physical objects on an estimation of a radiofrequency channel h modelled by rays that depart from a transmitter, interact with physical objects of the radiofrequency environment, and successfully arrive to a receiver, said impact being related to a global variation of the estimation of said radiofrequency channel h (Wu at Para. [0251] discloses measuring the impulse response of the channel which is an indication of the interaction of the signal with the physical environment:” estimate the MRF precisely and reliably may entail various challenges in practice. Particularly, the CIR measured using an mmWave platform offers limited range resolution (4.26 cm given the bandwidth of 3.52 GHz), contains synchronization drifts, and suffers from significant measurement noises, all leading to errors in the estimation of the propagation distance and the signal amplitude. To overcome these challenges, the mSense system first up samples the measured CIR to break down the range estimation precision to the sub-centimeter level. A novel synchronization scheme by leveraging the direct path, i.e., direct leakage between the co-located transmitter (Tx) and receiver (Rx), to synchronize all the CIRs is then presented.”).
As per claim 23, Chatbonnier and Wu disclose a method according to claim 22, wherein the estimation of the radiofrequency channel h is given by: [See equation presented in claim 23]. At Para. [0299] Wu teaches calculating the response function for the radiofrequency using the same claimed equation:” Channel Impulse Response (CIR) profiles the propagation delays and the channel responses of different signal paths between Tx and Rx, which is denoted by … the Dirac delta function.”)
As per claim 24, Chatbonnier and Wu disclose a method according to claim 23, wherein said selecting of the radiofrequency path comprises:
- counting a number K of physical objects in the environment and assigning to each object a value ()1,.., of a predetermined parameter of a radiofrequency property to be determined by said radiofrequency measurements (Chatbonnier at 14265 discloses accounting for the objects in the environment:” precisely characterize– in a controlled manner within an anechoic chamber– the material characteristics of discrete objects typically found in an environment, bypassing the need to collect data in the field and map objects a posteriori. However, the outdoor environment, for example, is composed from hundreds of objects with a wide range of materials– a building façade alone is a complex composite of concrete, metal, and glass …”), -
defining a possible range Zk for each given value of said predetermined parameter varying thereby according to said range Zk, while fixing all other values of said predetermined parameter to assigned respective default values (Chatbonnier at Page 14266 positioning the receiver with a range of distances:” Tx-Rx distance ranged from 6.1 m to 66.1 m, over which 61channel captures were collected, with an average of 1.1 m in between. Each large-scale channel capture consisted of eight small-scale channel acquisitions (about one wavelength apart)triggered sequentially, producing a rich data set for the accurate characterization of diffuse scattering.”), -
evaluating a variation for all channels h(rik) in the radiofrequency environment by using rays resulting from said simulation of ray-tracings, when said given value varies in said range (Wu at Para. [0314] discloses using multiples frames of data to evaluate the variations in the data for material evaluation:” ŷ(k) is the estimation from the kth CIR frame and K is total number of available frames. The device could be either moving or static during the measurements of successive frames.”), -
estimating, for each physical object, the score sk of impact of said physical object on the estimation of the radiofrequency channel h, said score sk being given by Sk [equation shown in claims of filed application] where mh is an average of channel h(r1k), when value 1k varies in range Zk, - selecting, among possible paths, at least one path interacting with physical objects having highest scores of impact sk (Wu at Para. [0316] discloses that the estimation is done for each object:” Given a set of materials of interests, the system can perform a “scan” on each of them and store the distribution of the estimated γ. To reduce the data amount needed for training, one can build a histogram, rather than fitting a certain distribution, for each material type T, denoted as {<γ.sub.i(T), p.sub.i(T)>, i=1, 2, . . . , P}, where γ.sub.i(T) is the bin value and p.sub.i(T) is the corresponding probability (normalized count of observations), and P is the total number of bins. In some embodiments, a median filter is applied to remove the outlier estimates from the training samples in prior to building the histogram.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify ray tracing engine as taught by Chatbonnier with the material analytics as taught by Wu with a reasonable expectation of success in order for the one or more method steps to select those materials/objects that have the highest characteristics/score for reflecting a wireless signal. The teaching suggestion/motivation to combine is that by selecting peak signal range accuracy and resolution of reflection signals can be improved as taught by Wu in Para. [0255] -[0256].
As per claim 25, Chatbonnier and Wu disclose a method according to claim 17, wherein said score of interactions of a physical object sk is determined by counting a number of interactions of the physical object with simulated rays (Wu at Para. [0203] discloses that various methods can be used to calculate the interaction with objects such as simulation and the like:” simulation based optimization, variational calculus, and/or variant. The search for local extremum may be associated with an objective function, loss function, cost function, utility function, fitness function, energy function, and/or an energy function.”).
As per claim 26, Chatbonnier and Wu disclose a method according to claim 25, wherein said selecting of the radiofrequency path comprises:
- assigning to each object k a value 1k of a predetermined parameter of a radiofrequency property to be determined by said radiofrequency measurements, - for each ray p defined by said simulation of ray-tracings, counting a number n(p, k) of times that said ray p interacts with an object k (Wu at Paras. [0290]-[0296] determines the material based on various indexes that are calculated using the claimed equation:” γ is a linear function of the target reflection coefficient r, an intrinsic characteristic of the target material, and is independent of the propagation distance. As shown by the middle term, except for three constants, i.e., the transmitting amplitude A.sub.0, the Tx and Rx antenna gains g.sub.t and g.sub.r, γ is only related to the reflection coefficient r and is thus unique to a particular material. Second, implied by the right term, one can easily estimate γ as long as one can obtain the range d of the target and the corresponding signal amplitude A.sub.d.”)
- selecting, among possible paths, at least one path interacting with physical objects having highest scores sk (Wu at Para. [0299] discloses determining possible paths based on the interaction of the RF signal with the material:” phase and time delay of the lth path, respectively; L is the total number of paths and δ(τ) is the Dirac delta function. FIG. 17 shows an example of the CIR measured by an mmWave device.”).
As per claim 27, Chatbonnier and Wu disclose a method according to claim 24, wherein, before selecting said at least one path interacting with physical objects having highest scores sk and once said scores are estimated, a filtering is implemented to eliminate objects having values of said predetermined parameter below a negligence threshold (Wu at Para. [0209] discloses thresholding as the basis for selecting objects and scoring the signal from the object/material:” quantity may be compared with a reference data or a reference distribution, such as an F-distribution, central F-distribution, another statistical distribution, threshold, threshold associated with probability/histogram, threshold associated with probability/histogram of finding false peak, threshold associated with the F-distribution, threshold associated the central F-distribution, and/or threshold associated with the another statistical distribution.”).
As per claim 28, Chatbonnier and Wu disclose a method according to claim 24, wherein said selecting of at least one path interacting with physical objects having highest scores sk is performed by minimizing a number of radiofrequency measurements to perform while guaranteeing that physical object having values of said predetermined parameter which are above a significance threshold are captured (Wu at Para. [0193] discloses using a local minimum as a threshold:” Significant local peaks may be identified or selected. Each significant local peak may be a local maximum with SNR-like parameter greater than a threshold T1 and/or a local maximum with amplitude greater than a threshold T2. The at least one local minimum and the at least one local minimum in the frequency domain may be identified/computed using a persistence-based approach.”).
As per claim 29, Chatbonnier and Wu disclose a method according to claim 28, wherein, before selecting said at least one path interacting with physical objects having highest scores sk and once said scores are estimated, a filtering is implemented to eliminate objects having values of said predetermined parameter below a negligence threshold, and wherein the significance threshold is higher than the negligence threshold (Wu at Para. [0150 discloses using various filters to filter those signals that are below or above a certain frequency range:” modem parameters may comprise parameters that indicate settings or an overall configuration for the operation of a radio subsystem or a baseband subsystem of a wireless sensor device (or both). The modem parameters may include one or more of: a gain setting, an RF filter setting, an RF front end switch setting, a DC offset setting, or an IQ compensation setting for a radio subsystem, or a digital DC correction setting, a digital gain setting, and/or a digital filtering setting (e.g. for a baseband subsystem). The CI may also be associated with information associated with a time period, time signature, timestamp, time amplitude, time phase, time trend, and/or time characteristics of the signal. The CI may be associated with information associated with a time-frequency partition, signature, amplitude, phase, trend, and/or characteristics of the signal.”).
As per claim 30, Chatbonnier and Wu disclose a method according to claim 24, wherein said value of said predetermined parameter of radiofrequency property is a value of a radiofrequency permittivity, said radiofrequency properties comprising at least respective radiofrequency permittivity of said physical objects (Wu at Para. [0290] discloses the use of permittivity as a measurement variable:” refractive index n is an intrinsic characteristic of a material related to the material's complex permittivity ε.sub.r=ε′.sub.r+ε″.sub.r:”).
As per claim 31, Chatbonnier and Wu disclose a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method according to claim 17 (See above rejection of claim 17).
As per claim 32 Chatbonnier discloses a system for implementing the method according to claim 17, comprising:
a physical object sensor for obtaining measurements of said (Chatbonnier at Page 14269, section A , ray tracing settings, positions and dimensions are from OpenStreetMap and heights are estimated from number of floors),
a computer connected to said physical object sensor to receive data of said geometrical properties ( Chatbonnier at Page 14266 discloses the hardware at Figure 1 and discloses the processing of gathered signals:” refer to a single acquisition as a set of 16CIRs associated with the Rx array. Factoring in the Tx power, the antenna gains, the Rx noise figure, and the processing gain of the PN sequence, the maximum measurable path loss of the system was 170 dB.”), and comprising a computing circuit for simulating said radiofrequency ray- tracings (Chatbonnier at Page 14269, ray tracing process) and for selecting said at least one radiofrequency defining respective positions of a transmitter and of a receiver (Chatbonnier at Page 14270 disclosing that the same ray which was predicted will be mapped to a measured ray.), , and - a transmitting antenna and a receiving antenna respectively located in said respective positions of a transmitter and of a receiver, for carrying out said radiofrequency measurements (Chatbonnier at Figure 5 and Page 14266, section B, RX mounted on mobile device (robot) positioned using a GPS device at 1.6m.).
While determining the ray tracing of signals, Chatbonnier does not explicitly disclose a process for determining geometrical properties of the physical objects.
Wu in the same field of endeavor of characterizing a radiofrequency environment discloses a process for obtaining object analytics from the reflected wireless signals.
In particular Wu discloses determining the geometrical properties of the physical objects (Wu at Para. [0194] discloses selecting an identified/scored object based on a high score such as peak value:” set of selected significant local peaks may be selected from the set of identified significant local peaks based on a selection criterion (e.g. a quality criterion, a signal quality condition). The characteristics/STI of the object may be computed based on the set of selected significant local peaks and frequency values associated with the set of selected significant local peaks. In one example, the selection criterion may always correspond to select the strongest peaks in a range. While the strongest peaks may be selected, the unselected peaks may still be significant (rather strong).”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify ray tracing engine as taught by Chatbonnier with the material analytics as taught by Wu with a reasonable expectation of success in order for the one or more method steps to select those materials/objects that have the highest characteristics/score for reflecting a wireless signal. The teaching suggestion/motivation to combine is that by selecting peak signal range accuracy and resolution of reflection signals can be improved as taught by Wu in Para. [0255] -[0256].
As per claim 33, Chatbonnier and Wu disclose a system according to claim 32, further comprising at least one robot carrying at least one of a transmitting antenna and a receiving antenna (Chatbonnier at Page 14266, section B, RX mounted on mobile device (robot) positioned using a GPS device.), and connected to the computer for receiving control data comprising points coordinates of at least one of said positions of a transmitter and of a receiver (Chatbonnier at Page 14266, discloses positioning the rover for data collection:” rover enabled rapid and continuous collection of channel data while recording the location, velocity, and heading of the Rx array per acquisition essential to the analysis of the data collected.”), so as to position said robot at one of said transmitter position and receiver position, and control the robot to carry out said radiofrequency measurements at said one of said transmitter position and receiver position (Chatbonnier at Page 14269, section A , ray tracing settings, positions and dimensions are from OpenStreetMap and heights are estimated from number of floors).
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Wu; Chenshu et al. (US-20220026531-A1) METHOD, APPARATUS, AND SYSTEM FOR SOUND SENSING BASED ON WIRELESS SIGNALS;
Hollar; Seth Edward-Austin et al. (US-20210243564-A1) REAL TIME TRACKING SYSTEMS IN THREE DIMENSIONS IN MULTI-STORY STRUCTURES AND RELATED METHODS AND COMPUTER PROGRAM PRODUCTS;
LEE; Soonyoung et al. (US-20180138996-A1) METHOD AND APPARATUS FOR ANALYSING COMMUNICATION CHANNEL IN CONSIDERATION OF MATERIAL AND CONTOURS OF OBJECTS;
Wen; Zhu et al. (US-20100063791-A1) System And Method For Channel Emulator Performance Measurement And Evaluation;
Pao; Hsueh-Yuan et al. (US-20100003991-A1) Physics-based statistical model and simulation method of RF propagation in urban environments;
Chizhik; Dmitry et al. (US-20080224930-A1) Methods for locating transmitters using backward ray tracing;
Rossoni; Philip G. et al. (US-6487417-B1) Method and system for characterizing propagation of radiofrequency signal;
Baranger; Harold Urey et al. (US-6119009-A) Method and apparatus for modeling the propagation of wireless signals in buildings;
Rahmatullah; Muhammad M. et al. (US-6026130-A) System and method for estimating a set of parameters for a transmission channel in a communication system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELLIS B. RAMIREZ whose telephone number is (571)272-8920. The examiner can normally be reached 7:30 am to 5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramon Mercado can be reached at 571-270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ELLIS B. RAMIREZ/Primary Examiner, Art Unit 3658
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