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 .
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 (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 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 non-obviousness.
The ordinarily skilled knows that a range Fourier transform (fast-time) taken within a sample (intra-frame) and the Doppler Fourier transform (slow-time) is taken sequence to sequence (interframe). See e.g., Lang (US 2020/0150260) Fig. 6; Chi (US 2018/0172816) Fig. 2. And, of course, it should now be readily apparent that a Fourier transforms across antenna elements along the azimuth and/or elevation direction would similarly provide for spectrum information in the frequency domain. See e.g., Alland (US 7639171).
Claims 1 – 4, 7 – 8, 10, 15 – 16, 18 – 19 and 23 are rejected under 35 U.S.C. 103 as being obvious over Raghavan (US 20240188025 A1) filed Dec. 6, 2022 in view of Harrison (US 20190331768 A1).
As to claims 1 and 23, Raghavan discloses the method for directional multi-gigabit (DMG) passive sensing (Para. 107 “passive sensing”) with multidirectional millimeter-wave (mm Wave) Wi-Fi beacon transmissions during directional beam training, comprising:
collecting a schedule of the multidirectional mm Wave Wi-Fi beacon transmissions including times and directional sector of each mm Wave packet in the directional beam training (Para. 123 “the perception information may include beamforming-related information (e.g., adaptive beam weights that have worked best in the last few time slots or frames).” Here, the beamforming weights would be indicative of direction and time slots indicate of times.);
statistically evaluating values of an occupancy map of an environment using a model connecting the schedule of the beacon transmissions (Note that for a passive system to receive reflections, the reflections must originate indirectly from a separate source, e.g., multipath. See Para. 110 “Each channel tap may be associated with a cluster of one or more rays and correspond to a multipath that the RF signal followed between the transmitter and the receiver.” Para. 123 “perception” Para. 45 “average delay” and Fig. 6) with:
intra- packet measurements and inter-packet measurements, of reflections of the multidirectional mm Wave Wi-Fi beacon transmissions (Not taught.);
determining parameters of an object in the environment based on the values of the occupancy map; and outputting the parameters of the object (Para. 107 “The sensing device 404 can measure various properties (e.g., times of arrival (ToAs), angles of arrival (AoAs), phase shift, etc.) of the reflections of the RF sensing signals 434 to determine characteristics of the target object 406 (e.g., size, shape, speed, motion state, etc.).”).
Raghavan does not teach the limitation intra- packet measurements and inter-packet measurements, of reflections of the multidirectional mm Wave Wi-Fi beacon transmissions.
In the same field of endeavor, Harrison teaches “Targets are shown in the point cloud representation as voxels, which are values in the multi-dimensional space of the radar data 606 (e.g., containing range, velocity, azimuth and elevation angles) (Para. 37).” Harrison further teaches “The radar data may be organized in sets of Range-Doppler (“RD”) map information, corresponding to 4D information that is determined by each RF beam radiated off targets, such as azimuthal angles, elevation angles, range and velocity (Para. 29).” Harrison further teaches “Fourier analysis” (Para. 29). Range dimension represents the intra-frame dimension and Doppler represents the inter-frame, e.g. pulse to pulse, dimension as discussed supra with respect to the Graham factors.
Based on Linear-Algebra concepts, the ordinarily skilled understands that the more dimensions that data is plotted in the better the resolution. For example, two targets may be close in range to one another or said two targets maybe close in velocity. Thus, having a plurality of dimensions allows for the sensor to separate and distinguish between said two targets from being mistakenly taken to be a single target.
In view of the teachings of Harrison, it would have been obvious to a person having ordinary skill before filing to apply multiple dimensions, e.g., range (intra) and Doppler (inter), in order to increase resolution thereby increasing the ability to correctly separate targets from being incorrectly determined to be a singular target.
The claimed terms “statistical” and “model” are broad in scope. Nonetheless, Harrison discloses probability related features as part of a convolution neural network CNN to better identify objects. See Harrison Para. 38. It would be obvious to apply the CNN to better identify objects, including multipath, in order to determine the source of said multipath as well as to better identify other sources of unwanted transmission to avoid thereby improving quality.
As to claim 2, Raghavan in view of Harrison teaches the method of claim 1 further comprising collecting the intra-packet measurements and the inter-packet measurements of reflections of the multidirectional mm Wave Wi-Fi beacon transmissions within the environment (Raghavan Fig. 4b “reflections” – multipath. See Para. 33. In order to be a passive system to receive reflections, the reflections must be originating from another sources that reflects off of something in the environment before arriving at said passive system as shown in Raghavan’s Fig. 4b. Raghavan at Para. 107 teaches “passive sensing.” See also the modification with Harrison in claim 1.).
As to claim 3, Raghavan in view of Harrison teaches the method of claim 1 further comprising collecting the intra-packet measurements and the inter-packet measurements of an object-of-interest caused by the multidirectional beacon transmissions (Raghavan: Para. 107 “target object” and Para. 127 “region of interest”).
As to claim 4, Raghavan in view of Harrison teaches the method of claim 1 further comprising collecting the intra-packet measurements and the inter-packet measurements of permanently static objects caused by the multidirectional beacon transmissions (Raghavan see Para. 107 “motion state” and Para. 110 “multipath”; Harrison Para. 38 cites a “wall” that is identified.)
In view of Harrison, it would have been obvious to the ordinarily skilled before filing to identify a static object, e.g., as a wall, in order to determine a source of multipath so that correct information such as range can be taken into account for other objects, e.g., hidden object, that are of interest thus improving accuracy. Multipath, if known to be multipath, allows for non-line-of-sigh (NLOS) measurements to determine range so long as the source of multipath is known. The advantage is that the range to hidden objects can be determined.
As to claim 7 (contingent limitation), Raghavan in view of Harrison teaches the method of claim 1 further comprising updating knowledge of permanently static objects and intermittently static objects when there is no object-of-interest in the environment (Raghavan Para. 80 “updates.”).
Raghavan does not specify updates only for when there is no object-of-interest; however, this feature is a contingent limitation. Examiner recommends “further comprising determining that no object-of-interest is in the environment and in response to said determination updating knowledge of permanently static objects and intermittently static objects.” Looking at the specification at paragraphs 47 and 80, it appears that a background representation is used to enable the difference between intermittently static objects and objects of interest.
As to claim 8, Raghavan in view of Harrison teaches the method of claim 1, wherein the parameters of the object include at least: a velocity of the object, a distance of the object, and an angle of the object wherein the angle comprises an azimuth and an elevation (Raghavan Para. 45 Doppler, Para. 107 angles of arrival and Para. 112 distances; Harrison Para. 37 as cited in claim 1.).
As to claim 10, Raghavan in view of Harrison teaches the method of claim 1, further comprising: generating a joint signal model connecting a combination of the intra- packet measurements for all the inter-packet measurements, to at least a three- dimensional quantized space extending along a velocity dimension representing a velocity of the object, an angle dimension representing an angle of the object, and a distance dimension representing a distance to the object, wherein the velocity dimension and the angle dimension are quantized based on a number of inter-packet measurements in the beacon training, and wherein the distance dimension is quantized based on a number of intra-packet measurements within an inter-packet measurement, such that the quantized space is partitioned into bins defined by the velocity quantization, the angle quantization, and the distance quantization (as modified by Harrison in claim 1 and as evidenced by Graham factors’ discussed supra.).
As to claim 15, Raghavan in view of Harrison teaches the method of claim 1, comprising emitting a limited number of packets transmission in each of a multiple directions to perform the directional beacon training, wherein the limited number of packets comprises a predefined threshold value of the number of packets (Raghavan Para. 127 “reduced number of sensing beams” and Para. 58 “set number of chirps.” And Para. 148 “to more efficiently beamform towards each other (e.g., reduce the number of beams, reduce the search space, reduce beam sweeping time, and/or the like).”).
As to claim 16, Raghavan in view of Harrison teaches the method of claim 1, wherein statistically evaluating values of the occupancy map comprises executing a neural network trained to output one or more parameters of the object based on the schedule of the beacon transmissions (Harrison Para. 43 “The idea is to have DNN 604 choose an action for a given state such that its reward is maximized. In this case, the state is the output of the CNN 602, the action is a selection of beam parameters for the radar module 402 to know where to direct its next beams with the selected parameters (e.g., beam width, direction, etc.), and the reward is the performance of the DNN 604 following the selections.”).
In view of the teachings of Harrison, it would have been obvious to the ordinarily skilled before filing to include the CNN as taught to train toward the maximum reward thereby improving accuracy.
As to claim 18, Raghavan in view of Harrison teaches the method of claim 1, wherein the environment is an indoor environment (Para. 120 “indoor”).
As to claim 19, Raghavan in view of Harrison teaches the method of claim 18, wherein the occupancy map comprises a plurality of grids partitioning the indoor environment into different sections (Range-Doppler maps/cubes meets the scope of a partitioned grid. See modification with Harrison in claim 1.).
Claims 5 – 6 are rejected under 35 U.S.C. 103 as being obvious over Raghavan in view of Harrison and in further view Vaishnav (US 20210080557 A1).
As to claim 5, Raghavan in view of Harrison teaches the method of claim 1 further comprising collecting the intra-packet measurements and the inter-packet measurements of intermittently static objects caused by the multidirectional beacon transmissions (Raghavan see Para. 107 “motion state”, Para. 45 “Doppler shift” and Para. 123 “the motion state of the device (e.g., moving, stationary)”).
Sensor systems collect data on whatever is within said sensor system’s field-of-view or coverage area. The claims do not require that anything in particular be done to said collected data due to the fact that said collected data contains data related to an intermittent static object. However, claims 5 – 6 are method claims and required an intermittent static object. As such, a reference will be provided.
In the same field of endeavor, Vaishnav teaches “The objects in scene 108 may include static humans, such as lying human no, humans exhibiting low and infrequent motions, such as standing human 112, and moving humans, such as running or walking human 114 and 116 (Para. 38).”
In view of the teachings of Vaishnav, it would be obvious to the ordinarily skilled before filing to determine which objects are actually static as opposed to intermittently static so that the system does not confuse objects capable of motion with that of objects not capable of motion such as a wall. As discussed in claim 4, a wall could be used to determine a position of a non-LOS object. It should be apparent, that the system would not want to label a standing person as a source for such non-LOS position of other objects because the person may move.
As to claim 6, Raghavan in view of Harrison and Vaishnav (As applied in claim 5, the motivation being the same.) teaches the method of claim 1 further comprising utilizing knowledge of permanently static objects and intermittently static objects to assist the detection of an object-of-interest.
Claim 9 is rejected under 35 U.S.C. 103 as being obvious over Raghavan in view of Harrison and in further view Pao (US 20180035438 A1).
As to claim 9, Raghavan in view of Harrison teaches the method of claim 1, wherein the schedule of the multidirectional mm Wave Wi-Fi beacon transmissions corresponds to a beacon transmission interval (BTI) of the IEEE 802.11 ad/ay standard protocol (Raghavan Para. 29 IEEE 802.11).
Raghavan did not specify ad/ay.
In the same field of endeavor, Pao teaches “beam information referring to IEEE 802.11ad/ax/ay may include: (1) discovery information including a configuration of beacon interval in terms of time units, (2) feedback information for coarse beam training including countdown indication, sector ID, antenna ID, codebook, index of codebook, weight vectors (in digital or analog domain), antenna pattern, antenna configuration, antenna port layout, antenna array model, slot selection in association beamforming time for beamforming training, and etc., where ID may be a number, sequence, code, name, pattern, index, and etc., … (Pao Para. 99).”
Raghavan discloses “The wireless communications system 100 may further include a millimeter wave (mmW) base station 180 that may operate in mmW frequencies and/or near mmW frequencies in communication with a UE 182. Extremely high frequency (EHF) is part of the RF in the electromagnetic spectrum. EHF has a range of 30 GHz to 300 GHz and a wavelength between 1 millimeter and 10 millimeters (Para. 43).”
One of ordinary skill knows that IEEE 802.11 ad is a standard that defines at least some of the frequencies 30 GHz to 300 GHz in order to improve speed for enhance MIMO and improved range for beamforming. As such, it would have been obvious, in view of Raghava, to apply ad of IEEE 802.11 in order to improve beamforming speed and range performance.
Claims 17 and 20 are rejected under 35 U.S.C. 103 as being obvious over Raghavan in view of Harrison and in further view of Razaviyayn (US 20120170442 A1).
As to claim 17, Raghavan in view of Harrison does not explicitly teach the method of claim 1, further comprising initiating by at least one of an access point (AP) or a station (STA), the collecting of the schedule of the multidirectional mm Wave Wi-Fi beacon transmissions.
Although Raghavan discloses the server 570 configuring the UE for sensing, Raghavan doesn’t specify a schedule as part of that configuration. See Fig. 5 item 525. Although, time slots are mentioned, e.g., see Raghavan at Para. 123, it would be best to introduce a new reference to expedite prosecution.
In the same field of endeavor, Razaviyayn teaches “while a technique performed at a communications controller designs transmitter beamforming vectors, schedules users, and/or allocates transmit power to maximize communications system performance (para. 25).” Razaviyayn further teaches “According to an example embodiment, the controller may determine the transmit beamforming vectors for each of the scheduled UE (Para. 74).”
In view of the teachings of Razaviyayn, it would have been obvious to Razaviyayn to schedule users in order to prevent users from interfering with one another thereby improving accuracy.
As to claim 20, Raghavan in view of Harrison does not explicitly teach the method of claim 1, further comprising: transmitting, by an access point (AP), the schedule of the multidirectional mmWave Wi-Fi beacon transmissions in a beacon frame, wherein the beacon frame comprises a sensing support field.
Although Raghavan discloses the server 570 configuring the UE for sensing, Raghavan doesn’t specify a schedule as part of said configuration. See Fig. 5 item 525. Although, time slots are mentioned, e.g., see Raghavan at Para. 123, it would be best to introduce a new reference to expedite prosecution. The Examiner believes the configuration of sensing would be indicative a sensing support field.
In the same field of endeavor, Razaviyayn teaches “while a technique performed at a communications controller designs transmitter beamforming vectors, schedules users, and/or allocates transmit power to maximize communications system performance (para. 25).” Razaviyayn further teaches “According to an example embodiment, the controller may determine the transmit beamforming vectors for each of the scheduled UE (Para. 74).”
In view of the teachings of Razaviyayn, it would have been obvious to Razaviyayn to schedule user in order to prevent users from interfering with one another thereby improving accuracy. Also, the transmit beamforming vectors for each scheduled UE would be indicative of a sensing support field, wherein the motivation would be to prevent interference via user via scheduling or in offset in frequency or phase or coding, etc.
Claim 21 is rejected under 35 U.S.C. 103 as being obvious over Raghavan in view of Harrison and in further view of Barbu (US 20250294461 A1) having an effective filing data and Han (US 20220066018 A1).
As to claim 21, Raghavan in view of Harrison does not teach the method of claim 20, wherein the sensing support field is set to I to indicate that the AP supports DMG passive sensing.
Raghavan teaches the request of sensing capabilities as shown in Fig. 5. Raghavan also indicates that different types of sensing include “active sensing” and “passive sensing.” See Raghavan Para. 107. As such, the Examiner believes that it is implied that the sensing capabilities request would include an indication of whether the UE is capable of passive sensing. In order to expedite prosecution, another reference is introduced.
In the same field of endeavor, Barbu teaches “At 300, the UE may inform the serving gNB about the WRx capabilities for passive or active detection (Para. 49).”
One of ordinary skill understands that software is made up of bits and that bits carry information. Thus, the capabilities as taught by Barbu would be indicated by bits in software as would be expected by that of the ordinarily skilled person. For example, Han teaches “the second radar capability indication information may be implemented by using one bit. That a value of the second radar capability indication information is “0” indicates that the STA does not support radar measurement (Para. 284).”
In view of the teachings of Barbu and Han, it would have been obvious to the ordinarily skilled before filing to send data indicating the type of sensing capabilities so that the user knows how to correctly determine range because range determination is different for active and passive systems and that the passive systems that are receiving indirect reflections have to account for the extra time traveled due to multipath.
Claim 22 is rejected under 35 U.S.C. 103 as being obvious over Raghavan in view of Harrison and in further view of Barbu and Born (US 20250216506 A1) filed Feb. 14, 2022.
As to claim 22, Raghavan in view of Harrison does not teach the method of claim 20, further comprising: transmitting, by at least one station (STA) device, an information request frame for obtaining information associated with the transmission of the beacon frame by the AP; receiving, by the at least one STA device, an information response frame from the AP, the information response frame including at least (Raghavan: Fig. 5):
Raghavan teaches the request of sensing capabilities as shown in Fig. 5. Raghavan also indicates that different types of sensing include “active sensing” and “passive sensing.” See Raghavan Para. 107. As such, the Examiner believes that it is implied that the sensing capabilities request would include and indication as to whether the UE is capable of passive sensing. In order to expedite prosecution, another reference is introduced.
In the same field of endeavor, Barbu teaches “At 300, the UE may inform the serving gNB about the WRx capabilities for passive or active detection (Para. 49).”
In view of the teachings of Barbu, it would have been obvious to the ordinarily skilled before filing to send data indicating the type of sensing capabilities so that the user knows how to correctly determine range because range determination is different for active and passive systems and that the passive systems that are receiving indirect reflections have to account for the extra time traveled due to multipath.
Raghavan in view of Harrison and Born does not teach one or more DMG beacon sector descriptor elements, wherein the DMG beacon sector descriptor elements comprises: a sector azimuth field, a sector elevation field, an azimuth beamwidth field, and an elevation beamwidth field; and determining the parameters of the object based on the received information response frame.
In the same field of endeavor, Born teaches “The parameters of the radar device 130 can be provided by the user or looked up from one or more databases 120 and/or information source computer devices 125. The radar parameters could include, but are not limited to, radar antenna pattern of radar (azimuths and elevations), radar beam characteristics (transmitter frequency, transmitter power, receiver frequency, receiver minimum power, range product, frame time, azimuth field of view, elevation field of view, range accuracy, azimuth accuracy, operating frequency, antenna type, peak power output, pulse width, pulse repetition rate, antenna rotation, antenna shape & size, gain, beam width, cross-polarization isolation, nominal R.sub.max, range resolution, range oversampling, RF receiver gain, transmitted wavelength, peak transmitted power, antenna efficiency, transmitted pulse length, pulse repetition frequency, number of coherent averages, first calibration coefficient, and second calibration coefficient (Para. 68).” Born further teaches “The RPAC computer device 110 computes 2550 the probability of detection of the target based on the plurality of parameters of the radar device 130, the plurality of target parameters, the geographic data, the weather information, the plurality of travel parameters of the radar device 130, the plurality of travel parameters for the target, and the measures of performance (Para. 58).”
One of ordinary skill understands that beamwidth would encompass each dimension disclosed by Born, namely azimuth and elevation. To the extent necessary, the Examiner takes official notice of beamwidth being in multiple dimensions, elevation and azimuth, wherein the motivation to use beamwidth is to give more confidence to signals-of-interest located within the beamwidth to prevent error associated with false detections, such as multipath from the ground or sidelobes, thereby improving accuracy.
In view of the teachings Born, it would have been obvious to the ordinarily skilled before filing to account for azimuth, beamwidth, elevation, etc., in order to better determine whether a signal-of-interest is more likely to be a true detection as opposed to a false detection thereby improving detection accuracy.
Allowable Subject Matter
Claims 11 – 14 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The prior art does not teach all of the claimed features.
Conclusion
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/MICHAEL W JUSTICE/Examiner, Art Unit 3648