DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-14 are pending in Instant Application.
Priority
Examiner acknowledges Applicant’s claim to priority benefits of KOREA, REPUBLIC OF 10-2021-0169015 filed 11/30/2021 and this application is a 371 of PCT/KR2022/018615 filed 11/23/2022.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 5/30/2024 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered if signed and initialed by the Examiner.
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 of this title, 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, 13 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Securing the Wireless Emergency Alerts System. Communications of the ACM. Vol. M Issue 10, October 2021), and further in view of O-RAN (O-RAN: Towards an Open and Smart RAN. White Paper. October 2018).
As per claim 1, Lee disclose 1. A method performed by a terminal in a wireless communication system, the method comprising:
receiving, by the terminal, a master information block (MIB) from a base station (see lines 20-23 in the right column on page 85 and line 32 in the right column on page 86 to line 3 in the left column on page 87, receiving MIB from a base station);
obtaining a first system information block based on the received MIB (see lines 20-23 in the right column on page 85 and line 32 in the right column on page 86 to line 3 in the left column on page 87, obtaining/acquiring SIB1 on the received MIB);
obtaining a second system information block based on the first system information block (see lines 20-23 in the right column on page 85 and line 32 in the right column on page 86 to line 3 in the left column on page 87, obtaining / acquiring SIB2 on the basis of the SIB1); and
performing communication with the base station based on the second system information block (see lines 20-23 in the right column on page 85 and line 32 in the right column on page 86 to line 3 in the left column on page 87, communicating with the base station on the basis of the SIB2).
Lee however does not explicitly disclose in that the former is characterized in that a second system information block includes AI/machine learning (ML) model group information and message information related to AI/ML model groups. However, this different feature could be derived through simple design changes to the feature in Dl wherein ML-based model information can be provided through an SIB message (see lines 14-20 in the right column on page 85 and figure 14).
O-RAN however disclose wherein a second system information block includes artificial intelligence (AI)/machine learning (ML) model group information and message information related to an AI/ML model group (see page 13, wherein a base station exposes terminal-level information to support AI/ML models).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of wherein a second system information block includes artificial intelligence (AI)/machine learning (ML) model group information and message information related to an AI/ML model group, as taught by O-RAN, in the system of Lee, so as to enable network management online learning and offline training of AI/ML models, see O-RAN, page 13.
Claims 2, 7, 9 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Securing the Wireless Emergency Alerts System. Communications of the ACM. Vol. M Issue 10, October 2021), in view of O-RAN (O-RAN: Towards an Open and Smart RAN. White Paper, October 2018) and further in view of Jeon et al (US Pub. No.:2022/0294666).
As per claim 2, the combination of Lee and O-RAN disclose the method of claim 1.
The combination of Lee and O-RAN however does not explicitly disclose wherein the AI/ML model group information included in a second system information block includes at least any one of AI/ML model group number information, update indication information per AI/ML model group, valid area information per AI/ML model group, and resource scheduling information for a message related to the AI/ML model group.
Jeon however disclose wherein an AI/ML model group information included in a second system information block includes at least any one of AI/ML model group number information, update indication information per AI/ML model group, valid area information per AI/ML model group, and resource scheduling information for a message related to the AI/ML model group (see Fig.4, para. 0081, Fig.5, para. 0083, Fig.6, para. 0087, Fig.7, para. 0089, 0097, 0100-0102, 0112, Table 1 and 2, an AI/ML model group information included in a second system information block includes an AI/ML model group number information, part of or all the configuration information is broadcasted as a part of cell-specific information, for example by system information such as MIB, SIB1 or other SIBs, the enabling/disabling of ML approach, ML model and/or model parameters for certain operation/use case can be broadcasted, such as the enabling/disabling of ML approach, which ML model to be used and/or model parameters are broadcasted / update indication information per AI/ML model group. TABLE 2 provides an example (new parameter indicated in boldface) of sending the configuration information via SIB1, where K operation modes are predefined and one mode can be configured. In other examples, multiple modes can be configured).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of an AI/ML model group information included in a second system information block includes at least any one of AI/ML model group number information, update indication information per AI/ML model group, valid area information per AI/ML model group, and resource scheduling information for a message related to the AI/ML model group, as taught by Jeon, in the system of Lee and O-RAN, so as to enable receiving, at a UE from a base station, ML/AI configuration information for one of UL channel prediction, DL channel estimation, or cell selection/reselection. The ML/AI configuration information includes: one or more of enabling/disabling an ML approach for the UL channel prediction, the DL channel estimation, or cell selection/reselection; one or more ML models to be used for the UL channel prediction, the DL channel estimation, or cell selection/reselection; trained model parameters for the one or more ML models for the UL channel prediction, the DL channel estimation, or cell selection/reselection; and/or whether ML model parameters for the UL channel prediction, the DL channel estimation, or cell selection/reselection received from the UE at the base station will be used, see Jeon, see para. 0006-0008.
As per claim 7, the combination of Lee and O-RAN disclose the method of claim 1.
The combination of Lee and O-RAN however does not explicitly disclose wherein the terminal receives a message related to at least one or more AI/ML model groups based on the message information related to the AI/ML model group, and wherein the message related to the AI/ML model group includes at least any one of the number of AI/ML models in the AI/ML model group, an index of each AI/ML model in the AI/ML model group, and feedback information related to AI/ML model performance.
Jeon however disclose wherein a terminal receives a message related to at least one or more AI/ML model groups based on the message information related to the AI/ML model group, and wherein the message related to the AI/ML model group includes at least any one of the number of AI/ML models in the AI/ML model group, an index of each AI/ML model in the AI/ML model group, and feedback information related to AI/ML model performance (see Fig.4, para. 0081, Fig.5, para. 0083, Fig.6, para. 0087, Fig.7, para. 0089, 0097, 0100-0102, 0112, Table 1 and 2, a terminal receives a message related to at least one or more AI/ML model groups based on the message information related to the AI/ML model group, part of or all the configuration information is broadcasted as a part of cell-specific information, for example by system information such as MIB, SIB1 or other SIBs, the enabling/disabling of ML approach, ML model and/or model parameters for certain operation/use case can be broadcasted, such as the enabling/disabling of ML approach, which ML model to be used and/or model parameters are broadcasted / update indication information per AI/ML model group. TABLE 2 provides an example (new parameter indicated in boldface) of sending the configuration information via SIB1, where K operation modes are predefined and one mode can be configured. In other examples, multiple modes can be configured).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of wherein a terminal receives a message related to at least one or more AI/ML model groups based on the message information related to the AI/ML model group, and wherein the message related to the AI/ML model group includes at least any one of the number of AI/ML models in the AI/ML model group, an index of each AI/ML model in the AI/ML model group, and feedback information related to AI/ML model performance, as taught by Jeon, in the system of Lee and O-RAN, so as to enable receiving, at a UE from a base station, ML/AI configuration information for one of UL channel prediction, DL channel estimation, or cell selection/reselection. The ML/AI configuration information includes: one or more of enabling/disabling an ML approach for the UL channel prediction, the DL channel estimation, or cell selection/reselection; one or more ML models to be used for the UL channel prediction, the DL channel estimation, or cell selection/reselection; trained model parameters for the one or more ML models for the UL channel prediction, the DL channel estimation, or cell selection/reselection; and/or whether ML model parameters for the UL channel prediction, the DL channel estimation, or cell selection/reselection received from the UE at the base station will be used, see Jeon, see para. 0006-0008.
As per claim 9, the combination of Lee and O-RAN disclose the method of claim 1.
The combination of Lee and O-RAN however does not explicitly disclose wherein the AI/ML model group is grouped based on at least any one of performance evaluation data, an AI/ML model type, an AI/ML model coefficient quantization level, an AI/ML model procedure, and AI/ML capability and AI/ML version.
Jeon however disclose wherein an AI/ML model group is grouped based on at least any one of performance evaluation data, an AI/ML model type, an AI/ML model coefficient quantization level, an AI/ML model procedure, and AI/ML capability and AI/ML version (see Fig.4, para. 0081, Fig.5, para. 0083, Fig.6, para. 0087, Fig.7, para. 0089, 0097, 0100-0102, 0112, Table 1 and 2, an AI/ML model group information included in a second system information block includes an AI/ML model group number information, part of or all the configuration information can be broadcasted as a part of cell-specific information, for example by system information such as MIB, SIB1 or other SIBs, the enabling/disabling of ML approach, ML model and/or model parameters for certain operation/use case can be broadcasted, such as the enabling/disabling of ML approach, which ML model to be used and/or model parameters are broadcasted / update indication information per AI/ML model group. TABLE 2 provides an example (new parameter indicated in boldface) of sending the configuration information via SIB1, where K operation modes are predefined and one mode can be configured. In other examples, multiple modes can be configured).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of wherein an AI/ML model group is grouped based on at least any one of performance evaluation data, an AI/ML model type, an AI/ML model coefficient quantization level, an AI/ML model procedure, and AI/ML capability and AI/ML version, as taught by Jeon, in the system of Lee and O-RAN, so as to enable receiving, at a UE from a base station, ML/AI configuration information for one of UL channel prediction, DL channel estimation, or cell selection/reselection. The ML/AI configuration information includes: one or more of enabling/disabling an ML approach for the UL channel prediction, the DL channel estimation, or cell selection/reselection; one or more ML models to be used for the UL channel prediction, the DL channel estimation, or cell selection/reselection; trained model parameters for the one or more ML models for the UL channel prediction, the DL channel estimation, or cell selection/reselection; and/or whether ML model parameters for the UL channel prediction, the DL channel estimation, or cell selection/reselection received from the UE at the base station will be used, see Jeon, see para. 0006-0008.
As per claim 11, the combination of Lee and O-RAN disclose the method of claim 1.
The combination of Lee and O-RAN however does not explicitly disclose wherein based on the terminal receiving at least any one of a short message and downlink control information (DCI) after receiving AI/ML model information, the terminal receives the second system information block, and the short message and the DCI include information indicating update of the AI/ML model.
Jeon however disclose wherein based on a terminal receiving at least any one of a short message and downlink control information (DCI) after receiving AI/ML model information, the terminal receives the second system information block, and the short message and the DCI include information indicating update of the AI/ML model (see Fig.4, para. 0081, Fig.5, para. 0083, Fig.6, para. 0087, Fig.7, para. 0089, 0097, 0100-0102, 0112, Table 1 and 2, an AI/ML model group information included in a second system information block includes an AI/ML model group number information, part of or all the configuration information can be broadcasted as a part of cell-specific information, for example by system information such as MIB, SIB1 or other SIBs, the enabling/disabling of ML approach, ML model and/or model parameters for certain operation/use case can be broadcasted, such as the enabling/disabling of ML approach, which ML model to be used and/or model parameters are broadcasted / update indication information per AI/ML model group. TABLE 2 provides an example (new parameter indicated in boldface) of sending the configuration information via SIB1, where K operation modes are predefined and one mode can be configured. In other examples, multiple modes can be configured).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of wherein based on a terminal receiving at least any one of a short message and downlink control information (DCI) after receiving AI/ML model information, the terminal receives the second system information block, and the short message and the DCI include information indicating update of the AI/ML model, as taught by Jeon, in the system of Lee and O-RAN, so as to enable receiving, at a UE from a base station, ML/AI configuration information for one of UL channel prediction, DL channel estimation, or cell selection/reselection. The ML/AI configuration information includes: one or more of enabling/disabling an ML approach for the UL channel prediction, the DL channel estimation, or cell selection/reselection; one or more ML models to be used for the UL channel prediction, the DL channel estimation, or cell selection/reselection; trained model parameters for the one or more ML models for the UL channel prediction, the DL channel estimation, or cell selection/reselection; and/or whether ML model parameters for the UL channel prediction, the DL channel estimation, or cell selection/reselection received from the UE at the base station will be used, see Jeon, see para. 0006-0008.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Securing the Wireless Emergency Alerts System. Communications of the ACM. Vol. M Issue 10, October 2021), in view of O-RAN (O-RAN: Towards an Open and Smart RAN. White Paper. October 2018) and further in view of Lee et al (WO2017-196056A2).
As per claim 10, the combination of Lee and O-RAN disclose the method of claim 1.
The combination of Lee and O-RAN however does not explicitly disclose wherein based on the terminal performing initial access, the terminal obtains the MIB and the first system information block, wherein based on the second system information block being broadcast, the terminal obtains the second system information block based on the first system information block, and wherein based on the second system information block being not broadcast, the terminal obtains the second system information block based on an on-demand request.
Lee however disclose wherein based on a terminal performing initial access, the terminal obtains the MIB and the first system information block, wherein based on the second system information block being broadcast, the terminal obtains the second system information block based on the first system information block, and wherein based on the second system information block being not broadcast, the terminal obtains the second system information block based on an on-demand request (see para. 0081, 0082, 0102, the SIB1 includes scheduling information of another SIB; thereafter, a terminal can
receive SIB2 information including ACB information; and for on-demand system information, the
terminal in a cell request system information, and a network having received the request can
transmit the requested system information to the terminal).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide the functionality of wherein based on a terminal performing initial access, the terminal obtains the MIB and the first system information block, wherein based on the second system information block being broadcast, the terminal obtains the second system information block based on the first system information block, and wherein based on the second system information block being not broadcast, the terminal obtains the second system information block based on an on-demand request, as taught by Lee, in the system of Lee and O-RAN, so as to provide a method for requesting, by a user equipment (UE), a system information block (SIB) in a wireless communication system, receiving an SIB list including one or more SIBs supported by a cell from a radio access network (RAN); receiving, from the RAN, SIB broadcast information indicating whether an SIB supported by the cell is broadcast in a broadcast control channel (BCCH) period; detecting a missing SIB based on the SIB list and the SIB broadcast information; and requesting the missing SIB from the RAN, see Lee, see para. 0008-0014.
As per claim 13, claim 13 (a method performed by a base station) is rejected the same way as claim 1.
As per claim 14, claim 14 is rejected the same way as claim 1. Lee also disclose A terminal (see col. 2, para, 3, a user equipment) in a wireless communication system, the terminal comprising: a transceiver(see col. 2, para, 3, a user equipment with a transceiver for transmitting and receiving messages); and a processor (see col. 2, para, 3, a user equipment with CPU / a processor).
Allowable Subject Matter
Claims 3-6. 8 and 12 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Madadi et al (US Pub. No.:2022/0338189) – see Fig.4, para. 0105-0106, “At operation 402, the BS sends CSI related configuration to the UE including the enabling and disabling of the AI based CSI feedback mechanism. When AI based CSI feedback is enabled, at operation 403, the BS then sends the AI/ML related configuration information to UE, which can include information about the AI/ML model used, in one embodiment the AI/ML model used could be an auto-encoder with encoding at UE and decoding at BS and the trained model parameters of the model. In one embodiment, the model training can be performed offline (e.g., model training is performed outside of the network), and the trained model parameters which may include and is not limited to values of the weights, biases, activation functions and different neural network layers used, can be sent to the BS and to UEs. In this embodiment, the BS is aware of the ML model being used at the UE for CSI feedback (received by the BS at operation 404) and is capable of interpreting the feedback information sent by the UE, i.e., in the example of an auto-encoder based CSI feedback BS will use appropriate decoder to interpret the feedback sent by the UE. Part of or all the configuration information can be broadcasted as a part of cell-specific information, for example by system information such as MIB, SIB1 or other SIBs.”.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAKERAM JANGBAHADUR whose telephone number is (571)272-1335. The examiner can normally be reached on M-F 7 am - 4 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ian Moore can be reached on 571-272-3085. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LAKERAM JANGBAHADUR/
Primary Examiner, Art Unit 2469
Prosecution Insights