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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 4 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 4 recites the limitation "the path description" in line 1. There is insufficient antecedent basis for this limitation in the claim.
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.
Claims 1, 3-13 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over YANG et al PG PUB 2025/0039725 in view of TANG et al PG PUB 2021/0099196.
Re Claims 1, 19 and 20, YANG et al teaches a UE (a first apparatus comprising memory and processor/controller) for wireless communication receives a first configuration (measurement configuration) for performing sensing measurement [0110] wherein the configuration includes a time-frequency resources (one or more first parameters) associated with a sensing signal; one or more beam indication information (one or more second and third parameters) for first and second signals [0114-0118] wherein the UE performs sensing measurement based at least in part on the received measurement configuration wherein based on application of the reference beam and sensing beam, the network may select a receive beam according to a current channel status to improve energy efficiency function [0111 0122 0123]. YANG et al fails to explicitly teach that the sensing measurement is passive. However, TANG et al teaches in a passive mode sensing measurement can save power [0111] and operate in higher gain and lower bandwidth than active mode. By combining the teachings, the UE in YANG et al can be modified or configured with passive mode to conserver power. One skilled in the art would have been motivated to conserve power. Therefore, it would have been obvious to one skilled to have combined the teachings.
Re Claim 3, YANG et al teaches receiving the reporting configuration [0110], in view of TANG, the passive sensing measurement and transmitting a report accordingly.
Re Claim 4, YANG et al teaches transmit beams associated with the first and second signals may be different [0073] wherein each transmit beams of the UE are among one or more propagation paths. One skilled in the art would have been motivated to have ID the transmit beams so that the beam can be differentiated.
Re Claims 5, 7, YANG et al teaches in multi-beam sensing scheme associated with Doppler characteristics (path description) [0074].
Re Claim 6, YANG et al teaches the sensing node determines a status of a sensing target position (object position) [0048].
Re Claim 8, YANG et al teaches the UE determining the sensing beam within an indicated time delay [0061-0070].
Re Claim 9, YANG et al teaches sensing capability to sense information whereby the UE can report its capability to the network [0046].
Re Claim 10, YANG et al teaches the sensing information includes orientation, distance or image of a target object [0046].
Re Claim 11, YANG et al teaches the measurement configuration comprises angle information [0061 0062 0089].
Re Claim 12, YANG et al teaches based on the current channel status [0111], the UE ](the processor) can determine a preference of one or more of the sensing signal, in view of TANG et al, for performing passive sensing measurements.
Re Claim 13, YANG et al teaches the network-side device configuring or indicating to the UE to perform the application function of sensing the reference beam and sensing beam (indication of the function) [0111]. TANG et al teaches in figure 24, machine learning of a passive wireless sensing network [0112] wherein the machine learning helps to improve robustness to noisy variable conditions [0095]. The machine learning algorithm employed in TANG et al is associated with a computational AI machine learning model which can be applied to YANG et al to improve the robustness in the sensing network. One skilled in the art would have been motivated to have modified YANG et al to have indicated the AL model in its sensing operation.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over YANG et al PG PUB 2025/0039725 in view of TANG et al PG PUB 2021/0099196 as applied to Claim 1 above and further view of ROSE PG PUB 2013/0106650.
Re Claim 2, YANG et al in view of TANG et al fails to explicitly teach “…to illuminate a sensing target area of interest.”. However, ROSE teaches a transmitted beam has an illumination angle designed to illuminate a target area of interest to generate moving target indications [0025]. By combining the teachings, the sensing signal in YANG et al in view of TANG et al can be modified to illuminate the sensing target area of interest to generate the moving target indications. One skilled in the art would have been motivated to illuminate the sensing signal for displaying the target area of interest to a network operator for ease of operation. Therefore, it would have been obvious to one skilled to have combined the teachings.
Claims 14, 15 are rejected under 35 U.S.C. 103 as being unpatentable over YANG et al PG PUB 2025/0039725 in view of TANG et al PG PUB 2021/0099196 as applied to Claim 1 above and further view of WANG et al PG PUB 2025/0192849.
Re Claims 14, 15, See Claim 13, YANG et al in view of TANG et al the AI learning model can be configured for performing passive sensing measurement by the UE. YANG et al in view of TANG et al fails to explicitly teach “…an index from a codebook of known computational AI machine learning models”. However, WANG et al teaches in figure 14, an AI/ML models have a model identifier and a version identifier associated with CSI generation wherein the network device acquires a specific codebook vector or index [0207 0211 0218]. By combining the teachings, the AL/ML model can be adaptive to different predefined codebooks in NR. One skilled in the art would have been motivated to be adaptive to different AI/ML models to accommodate for the different codebooks in NR. Therefore, it would have been obvious to one skilled to have combined the teachings.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over STEFANATOS et al PG PUB 2025/0151045 in view of TANG et al PG PUB 2021/0099196.
Re Claim 18, STEFANATOS et al teaches in figure 4, a network entity 105-b (a first apparatus) for receiving a scheduling request (a request) indicating an angular area of interest for radar sensing (a sensing task) [0097] from a UE 115 (a second apparatus) ; the network entity 105-b receiving a capability information (a suitable indication) for performing sensing measurement of the area of interest such as being capable of supporting radar sensing [0132]; based on the capability information, the network entity transmits configuration information 410 to the UE for performing the radar sensing measurement of the area of interest. Examiner takes notice that the capability information is responsive to a capability request (a suitability query) from the network entity. STEFANATOS et al fails to explicitly teach that the sensing measurement is passive. However, TANG et al teaches in a passive mode sensing measurement can save power [0111] and operate in higher gain and lower bandwidth than active mode. By combining the teachings, the UE in STEFANATOS et al can be modified with passive mode to conserver power. One skilled in the art would have been motivated to conserve power. Therefore, it would have been obvious to one skilled to have combined the teachings.
Allowable Subject Matter
Claims 16-17 are 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 following is a statement of reasons for the indication of allowable subject matter:
Re Claim 16, prior art fails to teach performing training of the AI model based on on the received sensing signal and the received training configuration as claimed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW LEE whose telephone number is (571)272-3130. The examiner can normally be reached Monday-Friday 8:30AM-5PM ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, KASSIM KHALAD can be reached at 5712703770. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW LEE/ Primary Examiner, Art Unit 2475
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