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 § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 6- 7, 9-16, 18-19, 22-23 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wang (WO2023020516)
Regarding claim 1,
Wang teaches a method for determining an AI-based CSI processing capability, performed by a network device, the method comprising:
receiving a reported Artificial Intelligence (AI) based static capability of a terminal; and (interpreted as the terminal device can request a first AI model from the first device or request an evaluation of its own capability through the embodiment in Figure 4. In this case, the request message sent by the terminal device to the first device may carry the parameters carried by the first information. For example, the request message may include one or more of the following: first threshold, second threshold, hardware model, hardware version, storage capacity, computing power, and support for heterogeneous computing., see para [0164])
determining the AI-based Channel State Information (CSI) processing capability of the terminal based on the static capability. (Interpreted as in this communication scenario, the third threshold represents the maximum delay when the network device uses the AI model for CSI decoding. If the terminal device's delay in CSI decoding using the second AI model exceeds the maximum delay indicated by the third threshold, it is considered that applying the second AI model for communication services does not meet the delay requirements, see para [0237])
Regarding claim 11,
Wang teaches a method for determining an AI-based CSI processing capability, performed by a terminal, the method comprising:
reporting an Artificial Intelligence (AI) based static capability of the terminal to a network device, wherein the AI-based static capability is configured to be used for determination of the AI-based Channel State Information (CSI) processing capability. (Interpreted as in this communication scenario, the third threshold represents the maximum delay when the network device uses the AI model for CSI decoding. If the terminal device's delay in CSI decoding using the second AI model exceeds the maximum delay indicated by the third threshold, it is considered that applying the second AI model for communication services does not meet the delay requirements, see para [0237])
Regarding claim 2 and 12,
Wang teaches the method according to claim 1, wherein the AI-based CSI processing capability comprises a minimum latency for AI-based CSI processing, and wherein determining the AI-based CSI processing capability of the terminal based on the static capability comprises:
determining the minimum latency for the AI-based CSI processing of the terminal corresponding to the static capability from a corresponding relationship, wherein the corresponding relationship comprises a mapping relationship between the static capability and the minimum latency for the AI-based CSI processing. (Interpreted as in this communication scenario, the third threshold represents the maximum delay when the network device uses the AI model for CSI decoding. If the terminal device's delay in CSI decoding using the second AI model exceeds the maximum delay indicated by the third threshold, it is considered that applying the second AI model for communication services does not meet the delay requirements, see para [0237]. Delay requirements para [0187])
Regarding claim 3 and 13,
Wang teaches the method according to claim 2, wherein the static capability comprises at least one of: information of hardware with the AI-based processing capability; a support status for an AI processing platform; or a support status for a third-party AI model library. (Interpreted as the request message sent by the terminal device to the first device may carry the parameters carried by the first information. For example, the request message may include one or more of the following: first threshold, second threshold, hardware model, hardware version, storage capacity, computing power, and support for heterogeneous computing. The method for the first device to determine whether the first AI model meets the hardware requirements of the terminal device based on the request message can refer to the method for network devices to determine whether the first AI model meets the hardware requirements of the terminal device, and will not be repeated here., see para [0164])
Regarding claim 4 and 14,
Wang teaches the method according to claim 1, further comprising: receiving a reported AI processing speed of the terminal; and determining the AI-based CSI processing capability of the terminal based on the AI processing speed and model information of an AI model used for CSI processing. (Interpreted as First information can also include first thresholds. The first threshold is: the maximum latency of the AI model’s execution part when the terminal device uses the AI model to execute communication services. For example, a communication service consists of multiple parts, and the terminal device uses AI models to execute one or more of the multiple parts of that communication service, see para [0142]. If the request message is used to indicate the first communication scenario, the fourth information includes the first AI model used by the terminal device for the first communication scenario, see para [0131])
Regarding claim 6 and 15,
Wang teaches the method according to claim 1, further comprising: sending model information of an AI model used for CSI processing to the terminal; and receiving the AI-based CSI processing capability of the terminal reported by the terminal, wherein the AI-based CSI processing capability is determined by the terminal based on the model information. (Interpreted as the first threshold is: the maximum latency of the AI model’s execution part when the terminal device uses the AI model to execute communication services. For example, a communication service consists of multiple parts, and the terminal device uses AI models to execute one or more of the multiple parts of that communication service. When terminal devices communicate with network devices, they can use AI models for CSI encoding, and network devices can use AI models for CSI decoding. In this communication scenario, the first threshold represents the maximum delay when the terminal device uses the AI model for CSI encoding, see para [0142])
Regarding claim 7 and 16,
Wang teaches the method according to claim 1, further comprising: configuring an allowed latency for AI-based CSI processing for the terminal based on the AI-based CSI processing capability. (Interpreted as in this communication scenario, the first threshold represents the maximum delay when the terminal device uses the AI model for CSI encoding. If the delay of the terminal device using the first AI model for CSI encoding exceeds the maximum delay indicated by the first threshold, it’s considered that applying the first AI model for communication services cannot meet the delay requirements, see para [0142])
Regarding claim 9 and 18,
Wang teaches the method according to claim 1, further comprising: receiving indication information reported by the terminal, wherein the indication information is configured to indicate switching from a first CSI processing mode to a second CSI processing mode, and wherein the first CSI processing mode is an AI-based CSI processing mode, and the second CSI processing mode is a CSI processing mode other than the AI-based CSI processing mode. (Interpreted as the terminal device receives the operating mode configuration information from the network device. The working mode configuration information is used to configure the operating mode for the terminal device to execute communication services. The working mode includes AI mode or non-AI mode. The AI mode is used to indicate the use of the first AI model to execute communication services, and the non-AI mode is used to indicate the use of traditional communication mode to execute communication services, see para [0388]. AI-based CSI and Traditional CSI para [0249])
Regarding claim 10 and 19,
Wang teaches the method according to claim 9, wherein the indication information is reported by the terminal to the network device, after the terminal switches, in response to the AI-based processing capability of the terminal not matching with a latency requirement, from the first CSI processing mode to the second CSI processing mode. (interpreted as If the request message sent by the network device to the first device is used to request the first device to determine whether the first AI model meets the delay requirements, the request message may include a first threshold, and the first device can use the first threshold to determine whether the first AI model meets the delay requirements, para [0185]. The terminal device receives the operating mode configuration information from the network device. The working mode configuration information is used to configure the operating mode for the terminal device to execute communication services. The working mode includes AI mode or non-AI mode. The AI mode is used to indicate the use of the first AI model to execute communication services, and the non-AI mode is used to indicate the use of traditional communication mode to execute communication services, see para [0388])
Regarding claim 22 and 23,
Wang teaches a network device, comprising: a processor; a memory for storing executable instructions; and a transceiver connected to the processor; wherein the processor is configured to load and execute the executable instructions to cause the method for determining the AI-based CSI processing capability according to claim 1 to be implemented. (0206] [0208])
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.
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable Wang (WO2023020516) further in view of Wu (Pub No 20240259069)
Regarding claim 8 and 17,
Wang teaches the method according to claim 1, further comprising: sending a switching instruction to the terminal in the case where a probability of error from the terminal increases when AI-based CSI compression is used, wherein the switching instruction is configured to indicate switching from a first CSI processing mode to a second CSI processing mode, and wherein the first CSI processing mode is an AI-based CSI processing mode, and the second CSI processing mode is a CSI processing mode other than the AI-based CSI processing mode. (interpreted as If the request message sent by the network device to the first device is used to request the first device to determine whether the first AI model meets the delay requirements, the request message may include a first threshold, and the first device can use the first threshold to determine whether the first AI model meets the delay requirements, para [0185]. The terminal device receives the operating mode configuration information from the network device. The working mode configuration information is used to configure the operating mode for the terminal device to execute communication services. The working mode includes AI mode or non-AI mode. The AI mode is used to indicate the use of the first AI model to execute communication services, and the non-AI mode is used to indicate the use of traditional communication mode to execute communication services, see para [0388])
However, Wang does not teach using NACK
Wu teaches using NACK. (Interpreted as the higher-layer packet is later provided to all protocol layers above the L2 layer, or various control signals can be provided to the L3 layer for processing. The controller/processor 459 also performs error detection using ACK and/or NACK protocols as a way to support HARQ operation, see para [0270])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the AI-based CSI requirement not being met as taught by Wang with the NACKS for error detection as taught by Wu with the motivation being to indicate when errors are detected.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BAO G NGUYEN whose telephone number is (571)272-7732. The examiner can normally be reached M-F 10pm - 6:30pm.
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/BAO G NGUYEN/Examiner, Art Unit 2461
/JASON E MATTIS/Primary Examiner, Art Unit 2461
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