DETAILED ACTION
The instant application having Application No. 18/175,464 filed on 02/27/2023 is presented for examination by the examiner.
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 .
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of applicant's claim for priority based on application filed on 02/28/2022 (CHINA 202210186961.0).
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
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 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 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 1-4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Higuchi et al. (Pub. No. US 2022/0116456 A1 hereinafter Higuchi) in view of Ali et al. (Pub. No. US 2022/0038157 A1 hereinafter Ali).
Regarding claim 1, Higuchi teaches “a computation offloading method for integrated sensing and communication, comprising: establishing an associated model of a terminal for computation offloading;” as [(Para. 0007), a system for value-anticipating task offloading includes one or more processors and a memory in communication with the one or more processors. The memory may include a task manager module. The task manager module may include instructions, that when executed by the one or more processors, cause the one or more processors to receive a task identifier of a computational task for an application being utilized by a vehicle processor of a vehicle and a state vector describing at least one state of the vehicle] “training the associated model by taking a to-be-computed task of the terminal, to obtain an offloading parameter of the terminal for the to-be-computed task,” [(Para. 0026), Using the identifier and the state vector, the utility function 14 generates a utility score that indicates the overall improvement in the functioning of the application if the computational task, identified by the identifier, is performed by offloading the computational task to an external system… (Para. 0051), the utility function(s) 250 may be a machine learning algorithm that was trained using reinforcement learning.] “wherein the to-be-computed task comprises to-be-computed communication data and to-be-computed sensing data,” [(Para. 0025), A computational task identifier that identifies a computational task for the application 12 is provided to a utility function 14. In addition to providing the identifier that identifies the computational task, information regarding the device, such as state information, referred to as a state vector, may be provided as well] “and the offloading parameter comprises a decision for offloading a computing task” [(Para. 0043), In one example, the utility function(s) 250 employees a reinforcement learning algorithm to learn the optimal decision policy. The utility function(s) 250 may be trained from the past history of <state, action, reward> tuples, where the state is the state vector for the time the offloading decision was made, the action signifies if the task was (a) offloaded (b) locally processed or (c) discarded and the reward indicates the gain in terms of (i) improvement of application performance and (ii) savings of network/compute resources. In some embodiments, one may train the utility function by reinforcement learning (e.g., Q learning). Different applications and/or computational tasks may have different criteria on the task utility. Therefore, the utility function(s) 250 are preferably trained on a per-task-type basis.] “offloading the to-be-computed task to an edge side according to the offloading parameter” [(Para. 0052), The task manager module 220 may then cause the processor(s) 110 to evaluate the utility score and determine if the computational task should be offloaded to an external system for processing, process the computational task locally by the processor(s) 110 of the vehicle 100, or discard the computational task altogether].
However, Higuchi does not specifically disclose an uplink communication channel gain, a sensing pulse response and an angle difference between a communication beam and a sensing beam as input, and a decision for offloading radio frequency transmission power.
In an analogous art, Ali teaches “an uplink communication channel gain,” as [(Para. 0133), The channel gain of the new particles can be decided based on the reference signal measurements, including but not limited to the most recent measurement] “a sensing pulse response” [(Para. 0140), The LOS/NLOS channel state can be detected from the channel impulse response estimation. The channel impulse response estimation can be from a wireless modem] “and an angle difference between a communication beam and a sensing beam as input,” [(Para. 0118), Other tracking filters such as Extended Kalman Filter, Unscented Kalman Filter, and the like can be used to track the angle-of-arrival (AoA) of the beams when combining the reference signal measurements and motion measurements to identify a beam for wireless communication] “and a decision for offloading radio frequency transmission power” [(Para. 0104), to optimize a certain performance metric (e.g., the received signal power), the UE usually conducts an exhaustive search over all candidate beam codewords in the beam codebook, and selects the one that results in the best performance metric (e.g., the highest received signal power) to receive the data].
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the teachings as in Higuchi to provide an effective technique as taught by Ali for effectively design an effective beam selection method at the user terminal side to reduce the access delay and implementation complexity [Ali: Para. 0106].
Regarding claim 2, Higuchi teaches “wherein the associated model comprises: a task model of the to-be-computed task,” as (Para. 0007), a system for value-anticipating task offloading includes one or more processors and a memory in communication with the one or more processors. The memory may include a task manager module] “a computing model of the terminal and a computing model of the edge side” [(Para. 0056), the task scheduler module 230 causes the processor(s) 110 to receive a plurality of task identifiers from multiple devices, such as other vehicles. In addition to receiving identifiers of different computational tasks, the processor(s) 110 may also receive utility scores for each of the identifiers of the different computational tasks… (Para. 0038), the task scheduler module 230 may be operated on an external system, such as a vehicle micro cloud, edge server, remote server, and the like].
However, Higuchi does not specifically disclose an inter beam interference model, a sensing model, an uplink communication model of the terminal
In an analogous art, Ali teaches “an inter beam interference model,” as [(Para. 0036), For example, the UE can measure the multiple reference signals to find a beam with the strongest signal. The strongest reference signal can be identified by comparing gain of multiple reference signals or any other type of metric such as RSRP, SINR, SNR, RSRQ, and the like. The beam that has the best reference signal measurement is selected and used for the signal reception and/or transmission.] “a sensing model,” [(Para. 0038), embodiments of the present disclosure utilize additional sensors of the UE for finding the best beam more efficiently. For example, embodiments of the present disclosure provide an apparatus and method for combining (or fusing) the reference signal measurements (such as RSRP information) with sensor information, (such as the orientation information coming from one or more motion sensors of the UE) to find a beam for performing wireless communication] “an uplink communication model of the terminal” [(Para. 0035), an UpLink (UL) that conveys signals from UEs to reception points such as eNodeBs].
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the teachings as in Higuchi to provide an effective technique as taught by Ali for effectively design an effective beam selection method at the user terminal side to reduce the access delay and implementation complexity [Ali: Para. 0106].
Regarding claim 3, the combination of Higuchi and Ali, specifically Ali teaches “wherein the inter beam interference model is a sector antenna model for characterizing a beam interference gain between the communication beam and the sensing beam” as [(Para. 0036), In certain embodiments, a BS can transmit multiple pilot signals. The UE can receive the transmitted pilot signals from the beams and then identify the beam with the highest received power as the best beam. The UE can then measure reference signals (such as reference signal received power (RSRP), signal-to-interference-and-noise ratio (SINR), signal-to-noise ratio (SNR), reference signal received quality (RSRQ), and the like) either one beam at a time or multiple beams at a time. For example, the UE can measure the multiple reference signals to find a beam with the strongest signal. The strongest reference signal can be identified by comparing gain of multiple reference signals or any other type of metric such as RSRP, SINR, SNR, RSRQ, and the like. The beam that has the best reference signal measurement is selected and used for the signal reception and/or transmission.].
Regarding claim 4, the combination of Higuchi and Ali, specifically Ali teaches “wherein the sensing model of the terminal comprises: a model for an orthogonal frequency division multiplexing sensing signal transmitted by the terminal” as [(Para. 0040), FIGS. 1-4 below describe various embodiments implemented in wireless communications systems and with the use of orthogonal frequency division multiplexing (OFDM) or orthogonal frequency division multiple access (OFDMA) communication techniques] “and a model for an echo signal received by the edge side,” [(Para. 0050), The RF transceivers 210 a-210 n receive, from the antennas 205 a-205 n, incoming RF signals, such as signals transmitted by UEs in the network 100… (Para. 0061), the processor 340 could control the reception of forward channel signals and the transmission of reverse channel signals by the RF transceiver 310, the RX processing circuitry 325] “and an output of the sensing model is conditional mutual information between a target pulse response and the received signal” [(Para. 0082), The sensor module 476 may detect an operational state (e.g., power or temperature) of the electronic device 401 or an environmental state (e.g., a state of a user) external to the electronic device 401, and then generate an electrical signal or data value corresponding to the detected state.].
Regarding claim 7, the combination of Higuchi and Ali, specifically Higuchi teaches “wherein the computing model of the terminal is used to characterize a time delay of the terminal for processing the to-be-computed task and a sensing performance of the terminal” as [(Para. 0032), Additionally, the process flow 10 also indicates that the task scheduler 16 can generate a performance log 26 that contains information regarding the performance of certain tasks that have been offloaded and/or not offloaded. For example, the task scheduler 16 could record information regarding the task that was offloaded, the state vector associated with the task, and the general improvement by offloading the task in the performance log. This can be utilized to update the utility function to improve the precision of the utility scores, as indicated in element 28.].
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Higuchi in view of Ali, and further in view of Jung et al. (Pub. No. US 2005/0254457 A1 hereinafter Jung).
Regarding claim 5, the combination of Higuchi and Ali does not specifically disclose wherein the uplink communication model of the terminal is used to characterize an uplink transmission rate and the uplink communication channel gain between the terminal and the edge side.
In an analogous art, Jung teaches “wherein the uplink communication model of the terminal is used to characterize an uplink transmission rate and the uplink communication channel gain between the terminal and the edge side” as [(Para. 0143), As illustrated in FIG. 3, the subchannel and bit allocation method computes channel gain and transmission rate information using feedback information from terminals in Step S301, and computes an average channel gain according to a computed channel gain for each user in Step S302].
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the teachings as in Higuchi and Ali to provide an effective technique as taught by Jung to provide a subchannel and bit allocation method for efficiently allocating subchannels in an orthogonal frequency division multiple access (OFDMA) system using multiple antennas [Jung: Para. 0008].
Claim 5 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Higuchi in view of Ali, and further in view of Wang et al. (CN114281544A hereinafter Wang).
Regarding claim 6, the combination of Higuchi and Ali does not specifically disclose wherein the task model is used to characterize the number of to-be-computed tasks within a preset time period, a size of each to-be-computed task, the number of CPU cycles required to execute one bit of the to-be-computed task, and a time delay threshold of each to-be-computed task.
In analogous art, Wang teaches “wherein the task model is used to characterize the number of to-be-computed tasks within a preset time period,” as [(Page 18, Para. 4), the advantage of the method provided by the embodiment of the present invention is more obvious, and when the number of tasks is 20, the time delay required by the method provided by the embodiment of the present invention is about 12.5 s.] “a size of each to-be-computed task,” [(Page 18), The method provided by the embodiment of the invention can allocate the optimal spectrum resource and the optimal calculation resource according to the size of the input data of the power task, so that the total time delay when the power tasks in all the terminal devices are executed is the lowest] “the number of CPU cycles required to execute one bit of the to-be-computed task,” [(Page 7, Para. 10), Total number of CPU cycles required, λi Representing the amount of data for the power task] “and a time delay threshold of each to-be-computed task” [(Page 4, Para. 5), according to the calculation time delay when each terminal device executes the power task respectively, the power task is unloaded to the edge server by the terminal device, and an optimization target is established through the total calculation time delay function when the edge server executes the power task].
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the teachings as in Higuchi and Ali to provide an effective technique as taught by Wang to provide a method and an apparatus for executing power tasks based on edge computing for mitigating excessive power tasks that will bring extra load to service nodes in an edge computing system and avoiding affecting network delay [Wang: Page 4, Para. 2-4].
Regarding claim 8, he combination of Higuchi, Ali and Wang, specifically Wang teaches “wherein the computing model of the edge side is used to characterize a time delay of the edge side for processing the to-be-computed task and a sensing performance of the terminal;” as [(Page 4, Para. 2), the method comprises the following steps: according to the calculation time delay when each terminal device executes the power task respectively, the power task is unloaded to the edge server by the terminal device, and an optimization target is established through the total calculation time delay function when the edge server executes the power task] “wherein the time delay of the edge side for processing the to-be-computed task includes: a first time delay for transmitting the to-be-computed task from the terminal to the edge side, a second time delay for the edge side processing the to-be-computed task, and a third time delay for the edge side transmitting the processed to-be-computed task to the terminal” [(Page 4, Para. 2), calculation time delay when each terminal device executes the power task… (Page 4, Para. 4), Optionally, in the method for executing an electric power task based on edge computing provided by the present invention, the total computation delay function is established according to the sum of a transmission delay function when the terminal device transmits data to the base station and a computation delay function when the electric power task is executed in the edge server; establishing a transmission delay function by combining with a frequency spectrum resource distributed by a base station for terminal equipment; and the calculation time delay function is established by combining the calculation resources distributed by the edge server for the terminal equipment.].
Allowable Subject Matters
Claims 9 and 10 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, and the claim objection(s) are overcome.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATALI N PASCUAL PEGUERO whose telephone number is (571)272-4691. The examiner can normally be reached Monday-Friday 11AM-9PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ASAD M NAWAZ can be reached at (571)272-3988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NATALI PASCUAL PEGUERO/Examiner, Art Unit 2463
/ASAD M NAWAZ/Supervisory Patent Examiner, Art Unit 2463