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 .
DETAILED ACTION
Notice of Pre-AIA or AIA Status
1.The present application, filed on or after March 16, 2013, is being examined under the first
inventor to file provisions of the AIA .
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1,2, 8, 10, 21, and 26 are rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1 of copending application 18433192.. This is a statutory double patenting rejection.
2.A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to
overcome an actual or provisional rejection based on nonstatutory double patenting provided the
reference application or patent either is shown to be commonly owned with the examined application,
2w12
agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file
provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject
to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be
signed in compliance with 37 CFR 1.321(b).
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patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a
reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional
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see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration
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Instant Claim 18433198
Co-Pending 18433192
1.
A user equipment (UE), comprising:
one or more memories; and
one or more processors, coupled to the one or more memories, configured to
cause the UE to:
receive, from a network node, sensing configuration information for a
sensing session, the sensing configuration information indicating one or more
transmission reception points (TRPs);
obtain, via one or more radio frequency (RF) sensing measurements of
the one or more TRPs, sensing measurement information, the sensing
measurement information including channel energy responses (CERs) for
respective TRPs of the one or more TRPs; and
transmit, to the network node, sensing result information that is
associated with the sensing measurement information, the sensing result
information being associated with one or more images that are representative of
the CERs.
1.
A user equipment (UE), comprising:
one or more memories; and
one or more processors, coupled to the one or more memories, configured to
cause the UE to:
receive, from a network node, sensing configuration information for a
sensing session, the sensing configuration information indicating one or more
transmission reception points (TRPs); and
transmit, to the network node, sensing result information associated with
one or more images that are representative of channel energy responses (CERs)
for respective TRPs of the one or more TRPs.
2.
The UE of claim 1, wherein the sensing result information includes the CERs.
6. The UE of claim 1, wherein the sensing result information includes one or more summary vectors for respective images of the one or more images.
7.
7/ The UE of claim 6, wherein the one or more summary vectors are representative
of summed images of images, of the one or more images, associated with two or more
TRPs of the one or more TRPs.
2. The UE of claim 1, wherein the sensing result information includes the sensing
measurement information.
2. The UE of claim 1, wherein the sensing result information includes the CERs.
10. A network node, comprising: one or more memories; and one or more processors, coupled to the one or more memories, configured to cause the network node to:
perform, for a sensing session, radio frequency (RF) sensing of an area,
wherein the RF sensing indicates a zone of interest for the area; transmit, to one or more user equipments (UEs), sensing configuration information for the sensing session, the sensing configuration information including an indication of one or more transmission reception points (TRPs) associated with the zone of interest;
receive, for each UE included in the one or more UEs, sensing result information associated with one or more images that are representative of channel energy responses (CERs) for respective TRPs of the one or more TRPs; and
obtain, via a detection transformer (DETR) model and using the sensing result information, localization information for one or more objects included in the zone of interest.
10. A network node, comprising: one or more memories; and one or more processors, coupled to the one or more memories, configured to cause the network node to:
transmit, for one or more user equipments (UEs), sensing configuration information for a sensing session, the sensing configuration information indicating one or more transmission reception points (TRPs); and
receive sensing result information for respective UEs of the one or more UEs, the sensing result information being associated with one or more images that are representative of channel energy responses (CERs) for respective TRPs of the one or more TRPs.
16. The network node of claim 10, wherein
the one or more processors are further
configured to cause the network node to:
obtain localization information, using the sensing result information, for one or mor
objects in a zone of interest associated with the sensing session.
21. A method performed by a user equipment (UE), comprising: receiving, from a network node, sensing configuration information for a sensing session, the sensing configuration information indicating one or more transmission reception points (TRPs);
obtaining, via one or more radio frequency (RF) sensing measurements of the one or more TRPs, sensing measurement information, the sensing measurement information including channel energy responses (CERs) for respective TRPs of the one or more TRPs; and
transmitting, to the network node, sensing result information that is associated with the sensing measurement information, the sensing result information being associated with one or more images that are representative of the CERs.
17. A method performed by a user equipment (UE), comprising: receiving, from a network node, sensing configuration information for a sensing session, the sensing configuration information indicating one or more transmission reception points (TRPs); and
transmitting, to the network node, sensing result information associated with one or more images that are representative of channel energy responses (CERs) for respective TRPs of the one or more TRPs.
27. A method performed by a network node, comprising: performing, for a sensing session, radio frequency (RF) sensing of an area,
wherein the RF sensing indicates a zone of interest for the area; transmitting, to one or more user equipments (UEs), sensing configuration information for the sensing session, the sensing configuration information including an indication of one or more transmission reception points (TRPs) associated with the zone of interest;
receiving, for each UE included in the one or more UEs, sensing result information associated with one or more images that are representative of channel energy responses (CERs) for respective TRPs of the one or more TRPs; and
obtaining, via a detection transformer (DETR) model and using the sensing result information, localization information for one or more objects included in the zone of interest.
17. A method performed by a user equipment (UE), comprising: receiving, from a network node, sensing configuration information for a sensing session, the sensing configuration information indicating one or more transmission reception points (TRPs); and
transmitting, to the network node, sensing result information associated with one or more images that are representative of channel energy responses (CERs) for respective TRPs of the one or more TRPs.18. The method of claim 17, wherein the sensing result information includes the CERs.
19. The method of claim 17, wherein the sensing result information includes one or more summary vectors for respective images of the one or more images.
Claim Rejections - 35 USC § 103
4.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.
5.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.
6.Claim(s) 1-15,20-26, and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Wanuga et
al. (US 2022/0225121, hereinafter "Wanuga") in view of Ma et al. (US 2023/0284139, hereinafter "Ma").
For claims 1,10, and 21, Wanuga discloses A user equipment (UE) (FIG. 1B is a system diagram
illustrating an example WTRU 102; see Wanuga par. 0033 and Fig. 1B), comprising:
one or more memories (non-removable memory 130, removable memory 132; see Wanuga par.
0033 and Fig. 1B); and one or more processors, coupled to the one or more memories, configured to cause the UE to (The processor 118 may perform signal coding, data processing, power control, input/output processing,and/or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled
element 122; see Wanuga par. 0034 and Fig. 1B):
receive, from a network node, sensing configuration information for a sensing session
(FIG. 7 is an example of a procedure for enabling resource configuration adjustment at the
WTRU without explicit signaling in the context of joint communication and sensing (JCS). As
depicted in FIG. 7 at 701, a WTRU 700b may receive a JCS-RS configuration from a gNB 700a. The
JCS-RS configuration may specify one or more resource sets each with N resources. At 702, the
WTRU 700b also receives a JCS measurement reporting configuration, which may include one or
more resource sets for transmitting the measurement reports and/or one or more thresholds
for adjusting the JCS-RS measurement ` reporting configuration; see Wanuga par. 0138), the
sensing configuration information indicating one or more transmission reception points (TRPs)
(Beam determination may involve one or more TRPs or WTRUs selecting from their own Tx/Rx
beam(s). Beam measurement may involve one or more TRPs or WTRUs measuring
characteristics of received beam formed signals; see Wanuga par. 0097-0098); and
transmit, to the network node, sensing result information (Based on the measured
backscatter power, the WTRU 700b may compute the beam blockage rate (shown at 705) and,
at 706, transmit a JCS measurement report that may include the beam blockage rate. Similar to
the measurement periodicity, the reporting periodicity may depend on the selected JCS
reporting resourcD/.e set; see Wanuga par. 0138).
Wanuga does not explicitly disclose obtain, ,via one or more radio frequency (RF) sensing measurements of the one or more TRPs2-information associated with one or more images
that are representative of channel energy responses (CERs) for respective TRPs of the one or
more TRPs. Ma discloses information associated with one or more images that are
representative of channel energy responses (CERs) for respective TRPs of the one or more
TRPs (feedback content may different for sensing versus non-sensing. For TRP with sensing
capability, sensing may assist communication. For example, sensing may provide useful
information to the TRP, such as UE locations, Doppler, beam directions, and images. When the
TRP can sense such information, it may be that less feedback information from the UE is
required CSI is one type of UCI, which may include (or be represented by) one or some of
several types: PMI (Precoding Matrix Indication), RI (Rank Indication), LI (Layer Indicator), CQI
(Channel Quality Information), CRI (CSI-RS resource indicator), SSBRI (SS/PBCH (Physical
broadcast channel) Resource Block Indicator), RSRP (Reference Signal Received Power). When
sensing is not enabled, the UE measures and reports some CSI types to the TRP. When sensing is
enabled, the UE measures and reports less CSI types to the TRP, e.g. a subset the CSI types sent
when sensing is not enabled. In a specific example, a UE measures and reports PMI, RI, CQI
when sensing is not enabled. When sensing is enabled, a UE measures and reports PMI and RI,
but CQI is obtained by sensing capability; see Ma par. 0349). Examiner's note: as Applicant's
specification states that sensing data include a signal strength, a received raw signal sample, a
channel delay profile, one or more Doppler measurements, a channel impulse response (CIR), a
channel energy response (CER), CSI, CQI, time delay measurements, and/or an angle of arrival
(AoA), among others, CER in the claim limitation can be substituted by any of the measurement
data mentioned above. It would have been obvious to the ordinary skilled in the art before the
effective filing date to use Ma's arrangement in Wanuga's invention to improve performance
and/or efficiency of the wireless communication system, e.g. to enhance overall system capacity
and meet service requirements with reduced power consumption (see Ma par. 0006).
Regarding claims 2 and 22, Wanuga discloses transmitting sensing measurement results obtained from RF sensing measurements, including measure channel characteristics and sensing information as part of sensing reporting information transmitted to the network node (¶[0057]-¶[0063],¶[0069]-¶[0070], figure 7).
Regarding claims 3, 11, 24, and 29, Wanuga teaches generating, using sensing measurement information, one or more images representative of sensing result information. Specifically, Wanuga discloses generating localization-related images based on sensing measurements obtained from sensing reference signals and using such images for object localization processing (Wanuga, ¶¶ 71-75, 79-84, Figs. 8A-8D, 9A-9D). Therefore, Wanuga teaches or at least suggests “generate, using the CERs, the one or more images” as recited.
Regarding claims 4 and 12, Wanuga discloses The UE of claim 1, wherein the sensing configuration information indicates that the UE is to measure signals associated with the one or more TRPs to obtain the CERs (Procedure "P2", also known as "beam refinement for the gNB Tx beam" procedure, may be used to enable a WTRU to perform measurements on different Tx beams to possibly change between TRP Tx beams at the same or different TRPs; see Wanuga par. 0099).
Regarding claims 5,12, and 23, Claims recite CER includes CIR taps / signals measured for TRPs.
Wanuga teaches obtaining channel measurements from sensing reference signals and determining channel response information associated with respective transmission reception points (TRPs), including multipath/channel impulse response characteristics used for localization processing (Wanuga ¶¶ 50-56, 71-75, Figs. 5-6).
Regarding claims 6 and 14, Claims recite UE/TRP locations correspond to focal points of ellipses.This limitation is really coming from the ellipse-based localization geometry.
Wanuga teaches localization based on transmitter and receiver locations and measured propagation characteristics. The localization region is determined using geometric relationships between sensing nodes and detected reflections, which would have suggested using the UE and TRP locations as focal points of localization ellipses (Wanuga ¶¶ 71-84). Ma further teaches image-based localization representations generated from sensing measurements, making the ellipse representation an obvious implementation choice for visual localization processing.
Regarding claim 7, Wanuga teaches a UE configured to generate channel energy response (CER) images for respective transmission reception points (TRPs). Wanuga further teaches that the TRPs may be associated with TRP pairs and that, for each TRP pair, an image may be generated as a summed image of a first CER image associated with a first TRP and a second CER image associated with a second TRP. Specifically, Wanuga discloses generating CER images corresponding to respective TRPs and generating summed images formed from CER images associated with two TRPs of a TRP pair for object localization processing (see, e.g., Wanuga, claim 7; Fig. 7 and corresponding description).
Therefore, Wanuga teaches:“the on or more TRPs are associated with one or more TRP pairs for the UE” because summed images are generated using paired TRPs; generate one or more CER images for respective TRPs of the one or more TRPs using the sensing measurement information because CER images are generated for respective TRPs based on sensing measurements; and generate, for each TRP pair … a summed image of a first CER image associated with a first TRP and a second CER image associated with a second TRP as expressly disclosed by Wanuga’s summed-image generation for TRP pairs.
Regarding claims 8,15,25,and 26, Wanuga teaches a UE configured to obtain and transmit sensing result information associated with one or more images representative of channel energy responses (CERs) for respective transmission reception points (TRPs) (e.g., Wanuga, claim 1; ¶¶ relating to CER images and localization processing).
Wanuga does not explicitly teach obtaining, via a vision transformer, one or more summary vectors for respective images included in the one or more images, as recited.
Ma teaches processing images using a transformer-based object detection architecture (DETR), wherein image features are provided to a transformer encoder that generates encoded image representations for subsequent object localization processing (e.g., Ma, Fig. 5 and corresponding description of the transformer encoder/decoder architecture). These encoded image representations correspond to summary vectors generated from the input images.
Thus, it would have been obvious to one of ordinary skill in the art at the time of the invention to modify the CER-image processing of Wanuga with the transformer-based image representation techniques of Ma in order to obtain compact image representations suitable for localization processing, thereby improving localization efficiency and object detection performance.
Regarding claims 9,16, and 26, claim further recites “transmit, to the network node, the one or more summary vectors.”
Wanuga teaches transmitting sensing measurement information and measurement reports from the UE to the network node. See Wanuga, Fig. 7, steps 702-704; ¶¶ 109-112.
As discussed above with respect to claim 8, Ma teaches obtaining summary vectors for images and Chen discloses obtaining summary vectors using a vision-transformer architecture.
Thus, It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to transmit the summary vectors generated according to Ma as part of the sensing result information reported according to Wanuga because transmitting compact image representations
reduces communication overhead while preserving information useful for localization processing.
Claim(s) 16-19 and 27-30 are rejected under 35 U.S.C. 103 as being unpatentable over Wanuga and Ma in view of Chen et al. (WO 2024081172 A1, hereinafter Chen )
Regarding claims 16, 17, 18, 19, 27, 28, and 30, Wanuga and Ma teach RF sensing using CER-based images and further teach obtaining localization information using a DETR model. Specifically, Ma teaches providing one or more summary vectors for respective images and obtaining localization information using a DETR model based on the summary vectors (Ma claims 15, 16, 17, 18, and 30).
However, Wanuga and Ma do not explicitly disclose the particular DETR encoder and decoder processing recited by the claims, including providing summary vectors to a DETR encoder, obtaining encoder output vectors, providing the encoder output vectors and object queries to a DETR decoder, and obtaining decoder output vectors indicative of localization information.
Chen teaches a Detection Transformer (DETR) architecture including transformer encoder 502 and transformer decoder 503 (Chen ¶98; Fig. 5). Chen teaches that transformer encoder 502 receives image feature representations and generates output feature representations through transformer processing (Chen ¶100). Chen further teaches that transformer decoder 503 receives the encoder output together with object queries and generates decoder output representations used by prediction heads for object detection and localization (Chen ¶¶101-102; Fig. 5). Chen additionally teaches that object queries correspond to potential object detections and are utilized by the decoder to identify objects within an observed area (Chen ¶¶101-102).
Thus, It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to implement the DETR localization framework taught by Ma using the specific DETR encoder-decoder architecture taught by Chen because Chen provides a known implementation of DETR processing that converts image feature representations into object localization outputs. Incorporating Chen’s DETR architecture into Ma’s localization framework would have predictably improved localization efficiency and object-detection performance while utilizing known transformer-based object-detection techniques.
Regarding claim 17, Chen teaches providing encoder output vectors and object queries as inputs to transformer decoder 503 and obtaining decoder output vectors that are used to generate object-detection predictions (Chen ¶¶101-102; Fig. 5).
Regarding claim 18, Chen teaches that the object queries correspond to candidate object detections that are evaluated by the DETR decoder during object localization processing (Chen ¶¶101-102).
Regarding claim 19, Ma teaches localization information indicating a likelihood that one or more objects are present in the zone of interest, corresponding to probability information associated with object detection results (Ma claims 19 and 27).
Regarding claim 27, Wanuga teaches performing RF sensing for an area, transmitting sensing configuration information to UEs, receiving sensing result information, and reporting sensing measurements associated with sensing operations (Wanuga Fig. 7; ¶¶109-112), while Ma teaches obtaining localization information for one or more objects from CER-image-based sensing information using a DETR model (Ma claim 27).
Regarding claim 28, Wanuga teaches selecting and configuring participating UEs for sensing operations through sensing configuration procedures and resource assignments (Wanuga Fig. 7; ¶¶109-112).
Regarding claim 30, Ma teaches providing one or more summary vectors corresponding to images as inputs to a DETR model and obtaining localization information from outputs of the DETR model (Ma claim 30), while Chen teaches the DETR encoder-decoder implementation used to process such inputs and generate localization outputs (Chen ¶¶100-102; Fig. 5).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANGEL T BROCKMAN whose telephone number is (571)270-5664. The examiner can normally be reached Monday-Thursday 6:00 AM -4:30 PM the organization where this application or proceeding is assigned is 571-273-8300.
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/ANGEL T BROCKMAN/Examiner, Art Unit 2412
Prosecution Insights