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
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) [ 1, 2, 3, 5, 6, 11, 13, 14, 17, 18, 22, 24 and 26 ] is/are rejected under 35 U.S.C. 102 a (1) as being anticipated by Kumar (US 20230093963 A1)] hereon after Kumar.
Regarding claim 1, Kumar teaches; A method for determining a model for use by a terminal, performed by the terminal, the method comprising: [0227] a method of wireless communication comprises: receiving, by a wireless communication device, an indication for usage of artificial intelligence (AI) based IDLE/INACTIVE state procedures; determining, by the wireless communication device, an AI model for IDLE/INACTIVE state procedures based on based on wireless communication device capability; retrieving, by the wireless communication device, the determined AI model from memory; and setting, by the wireless communication device, the retrieved AI model for IDLE/INACTIVE state procedures, such as described with reference to FIG. 9, receiving model indication information from an access network device; [0157] At 910, the base station 105 transmits an AI model indication message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) an AI model indication message (e.g., AI model configuration message or configuration transmission 452) to indicate to the UE 115 the AI model based operations for one or more RRC IDLE or RRC INACTIVE state procedures is configured, and determining, based on the model indication information, a target model for use by the terminal, [0158] At 915, the UE 115 determines an AI model responsive to the AI model indication message. For example, the UE 115 may select an AI model based on AI model configuration information stored at the UE 115. To illustrate, the UE 115 may select an AI model from a list of models available based on prioritization information, device information, network configuration, etc.
Regarding claim 2, Kumar teaches generating, in response to a presence of a first model currently used in the terminal, the target model by modifying the first model based on the model indication information. [0221] the wireless communication device further: receives AI model training configuration information; trains (e.g., adjusts) the AI model for IDLE/INACTIVE state procedures periodically based on the AI model training configuration information; logs timing information and adjustment coefficients (e.g., weights, models, deltas, gradients, etc.) used for training the AI model to generate logged AI model training information; and reports the logged AI model training information.
Regarding claim 3, Kumar teaches wherein the first model is inherent to the terminal, or predefined, or generated based on model indication information last sent by the access network device, or obtained through training by the terminal, or obtained through joint training by the terminal and the access network device.[0165] In some implementations, the UE 115 may select the AI model to use autonomously or independent of network input. In such implementations, the UE may have its own AI model (or multiple AI models) for IDLE and INACTIVE state operations … Upon receiving such indication, UE may use stored (e.g., pre-cached) or set AI model for AI based IDLE/INACTIVE state operations.
Regarding claim 5, Kumar teaches receiving a broadcast message of the access network device, wherein the broadcast message comprises the model indication information; [0142] At 715, the base station 105 transmits AI model configuration information in a SIB message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) a SIB message (e.g., AI model configuration message or configuration transmission 452) to the UE 115 which includes the AI model configuration information (e.g., 442) for one or more RRC IDLE or RRC INACTIVE state procedures, or, receiving a unicast message of the access network device, wherein the unicast message comprises the model indication information; [0119] In some implementations, the AI model configuration message is sent to multiple UEs. In other implementations, the AI model configuration message is a PDCCH transmission, such as a DCI, or a MAC CE, or a sidelink transmission, or, receiving a multicast message of the access network device, wherein the multicast message comprises the model indication information, [0137] To illustrate, the UE 115 may acquire the AI model through techniques similar to the AI model request, such as multicast and broadcast services (MBS), sidelink communications, broadcast control channel (BCCH) messages, system information block (SIB) messages, or non-access stratum (NAS) small data transfers.
Regarding claim 6, Kumar teaches wherein receiving the broadcast message of the access network device comprises: receiving a system information block (SIB) of the access network device, wherein the SIB comprises the model indication information or, wherein receiving the unicast message or multicast message of the access network device [0142] At 715, the base station 105 transmits AI model configuration information in a SIB message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) a SIB message (e.g., AI model configuration message or configuration transmission 452) to the UE 115 which includes the AI model configuration information (e.g., 442) for one or more RRC IDLE or RRC INACTIVE state procedures, comprises one of: receiving media access control control unit (MAC CE) signaling of the access network device, wherein the MAC CE signaling comprises the model indication information; receiving radio resource control (RRC) signaling of the access network device, wherein the RRC signaling comprises the model indication information [0089] In some implementations, control information may be communicated via UE 115 and base station 105. For example, the control information may be communicated using Medium Access Control (MAC) Control Element (MAC CE) transmissions, Radio Resource Control (RRC) transmissions, sidelink control information (SCI) transmissions, another transmission, or a combination thereof; or receiving downlink control information (DCI) signaling of the access network device, wherein the DCI signaling comprises the model indication information. [0119] In some implementations, the AI model configuration message is sent to multiple UEs. In other implementations, the AI model configuration message is a PDCCH transmission, such as a DCI, or a MAC CE, or a sidelink transmission.
Regarding claim 11, Kumar teaches A method for determining a model for use by a terminal, performed by an access network device, the method comprising: sending model indication information to the terminal, wherein the model indication information is configured to indicate a target model for use by the terminal [0157] At 910, the base station 105 transmits an AI model indication message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) an AI model indication message (e.g., AI model configuration message or configuration transmission 452) to indicate to the UE 115 the AI model based operations for one or more RRC IDLE or RRC INACTIVE state procedures is configured.
Regarding claim 13, Kumar teaches wherein sending the model indication information to the terminal comprises: sending a broadcast message to the terminal, wherein the broadcast message comprises the model indication information; [0157] At 910, the base station 105 transmits an AI model indication message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) an AI model indication message (e.g., AI model configuration message or configuration transmission 452) or, sending a unicast message to the terminal, wherein the unicast message comprises the model indication information; [0119] In other implementations, the AI model configuration message is a PDCCH transmission, such as a DCI, or a MAC CE, or a sidelink transmission, or, sending a multicast message to the terminal, wherein the multicast message comprises the model indication information. [0137] the UE 115 may acquire the AI model through techniques similar to the AI model request, such as multicast and broadcast services (MBS), sidelink communications, broadcast control channel (BCCH) messages, system information block (SIB) messages, or non-access stratum (NAS) small data transfers. Alternatively, the UE 115 may receive the AI model from another UE via D2D communications.
Regarding claim 14, Kumar teaches wherein sending the broadcast message to the terminal comprises: sending a system information block (SIB) to the terminal, wherein the SIB comprises the model indication information_ or, sending the unicast message or multicast message to the terminal comprises one of: [0142] At 715, the base station 105 transmits AI model configuration information in a SIB message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) a SIB message (e.g., AI model configuration message or configuration transmission 452) to the UE 115 which includes the AI model configuration information (e.g., 442) for one or more RRC IDLE or RRC INACTIVE state procedures, sending media access control control unit (MAC CE) signaling to the terminal, wherein the MAC CE signaling comprises the model indication information; sending radio resource control (RRC) signaling to the terminal, wherein the RRC signaling comprises the model indication information; [0089] In some implementations, control information may be communicated via UE 115 and base station 105. For example, the control information may be communicated using Medium Access Control (MAC) Control Element (MAC CE) transmissions, Radio Resource Control (RRC) transmissions, sidelink control information (SCI) transmissions, another transmission, or a combination thereof, or sending downlink control information (DCI) signaling to the terminal, wherein the DCI signaling comprises the model indication information, [0119] In some implementations, the AI model configuration message is sent to multiple UEs. In other implementations, the AI model configuration message is a PDCCH transmission, such as a DCI, or a MAC CE, or a sidelink transmission.
Regarding claim 17, Kumar teaches wherein the MAC CE signaling, the RRC signaling, or the DCI signaling carries an effective time parameter, [0091] The AI model configuration information data 406 may indicate or enable determination of AI models to be used for RRC IDLE and INACTIVE state operations. The AI model configuration information data 406 may include or correspond to RRC IDLE/INACTIVE model configuration information, validity area information of the model configuration, validity time information of the model configuration
Regarding claim 18, Kumar teaches determining model parameter information, [0107] In the example of FIG. 4, the base station 105 generates and transmits a configuration transmission 452. The base station 105 generates the configuration transmission 452 which includes or indicates AI model configuration information 406. The AI model configuration information 406 may include model identification information, such as model ID or NNF ID. The model identification information alternatively may include parameter information which indicates a particular model.
Regarding claim 22, Kumar teaches A communication device, comprising a processor and a memory in which a computer program is stored, [0090] UE 115 can include a variety of components (e.g., structural, hardware components) used for carrying out one or more functions described herein. For example, these components can includes processor 402, memory 404, transmitter 410, receiver 412, encoder, 413, decoder 414, AI manager 415, RRC state manager 416, and antennas 252a-r, wherein the processor executes the computer program stored in the memory to cause the communication device to perform the method of claim 1, [0196] UE 115 includes controller/processor 280, which operates to execute logic or computer instructions stored in memory 282, as well as controlling the components of UE 115 that provide the features and functionality of UE 115.
Regarding claim 24, Kumar teaches A non-transitory computer-readable storage medium for storing instructions which, when executed by a processor, cause the processor to perform the method of claim 1 [0011] In an additional aspect of the disclosure, a non-transitory computer-readable medium stores instructions that, when executed by a processor, cause the processor to perform operations including receiving, by a wireless communication device.
Regarding claim 26, Kumar teaches wherein receiving the model indication information from the access network device comprises: receiving a broadcast message of the access network device, wherein the broadcast message comprises the model indication information; [0142] At 715, the base station 105 transmits AI model configuration information in a SIB message to the UE 115. For example, the AI manager 439 of the base station 105 generates and transmits (e.g., broadcasts) a SIB message (e.g., AI model configuration message or configuration transmission 452) to the UE 115 which includes the AI model configuration information (e.g., 442) for one or more RRC IDLE or RRC INACTIVE state procedures, or, receiving a unicast message of the access network device, wherein the unicast message comprises the model indication information; [0119] In some implementations, the AI model configuration message is sent to multiple UEs. In other implementations, the AI model configuration message is a PDCCH transmission, such as a DCI, or a MAC CE, or a sidelink transmission, or, receiving a multicast message of the access network device, wherein the multicast message comprises the model indication information, [0137] To illustrate, the UE 115 may acquire the AI model through techniques similar to the AI model request, such as multicast and broadcast services (MBS), sidelink communications, broadcast control channel (BCCH) messages, system information block (SIB) messages, or non-access stratum (NAS) small data transfers.
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.
Claim [19] are rejected under 35 U.S.C 103 as being unpatentable over Kumar in view of Anand (US 20210385682 A1).
In regards to claim 19, Kumar teaches the limitations of the parent claim.
Kumar does not teach receiving the model parameter information from a core network device.
However, Anand does teach receiving the model parameter information from a core network device. [0064] In an example embodiment, neural network support information (e.g., including hardware capability/availability information and possibly other information) and/or measurement information may be reported by the RAN node to the controller. In some embodiments, the neural network support information, e.g., such as the types of neural networks supported by the RAN node or the list of RAN functions for which a neural network may be used or hardware capability descriptors e.g., (indicating hardware capability or availability information
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Kumar and Anand before him or her, to modify the method of Kumar in include parameter information as taught by Anand.
The motivation for doing so would be improved network performance. (Paragraph 0056 by Anand)].
Claim [4,8,9,12,16 and 25] are rejected under 35 U.S.C 103 as being unpatentable over Kumar in view of Bao (US 20210185515 A1).
In regards to claim 8, Kumar teaches the limitations of the parent claim.
Kumar does not teach determining an effective time for the target model, wherein the effective time is a time X plus N time units, the time X being a time when the model indication information is received from the access network device, N being greater than or equal to 0, the time unit being one of: second, millisecond, microsecond, frame, subframe, slot, mini-slot, or symbol.
However, Bao does teach determining an effective time for the target model, wherein the effective time is a time X plus N time units, the time X being a time when the model indication information is received from the access network device, N being greater than or equal to 0, the time unit being one of: second, millisecond, microsecond, frame, subframe, slot, mini-slot, or symbol. [0142] UE 115-a may receive the parameters and initiate the timer, and may activate (e.g., apply) the neural network block for the digital domain baseband signals upon expiration of the timer. In some examples, UE 115-a may activate a counter (e.g., a symbol counter, a slot counter, or the like) upon receiving the neural network block parameters. In such examples, when UE 115-a determines that the counter has expired (e.g., the counter has counted a number of symbols, slots, or the like), UE 115-a may activate (e.g., apply) the neural network block for the digital domain baseband signal.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Kumar and Bao before him or her, to modify the method of Kumar in include time configurations as taught by Bao.
The motivation for doing so would be improved network signal throughput. (Paragraph 0080 by Bao)].
In regards to claim 9, Kumar teaches the limitations of the parent claim.
Kumar does not teach determining an effective time for the target model, wherein the effective time is a first moment that occurs after a moment when the terminal sends an acknowledgement character (ACK) in feedback of the MAC CE signaling, the RRC signaling, or the DCI signaling plus a preset length of time; or, determininq an effective time for the target model based on an effective time parameter and a time when the MAC CE signaling is received, wherein the MAC CE signalinq carries the effective time parameter; or, determininq an effective time for the target model based on an effective time parameter and a time when the RRC signaling is received, wherein the RRC signalinq carries the effective time parameter; or, determininq an effective time for the target model based on an effective time parameter and a time when the DCI signaling is received, wherein the DCI signalinq carriers the effective time parameter.
However, Bao does teach determining an effective time for the target model, wherein the effective time is a first moment that occurs after a moment when the terminal sends an acknowledgement character (ACK) in feedback of the MAC CE signaling, the RRC signaling, or the DCI signaling plus a preset length of time;[0190] In some examples, UE 115-c in block 535 may initiate the timer upon receiving the neural network block parameters. Upon expiration of the timer, UE 115-c may activate in block 535 (e.g., begin using) the reconfigured neural network block or, determininq an effective time for the target model based on an effective time parameter and a time when the MAC CE signaling is received, wherein the MAC CE signalinq carries the effective time parameter; or, determininq an effective time for the target model based on an effective time parameter and a time when the RRC signaling is received, wherein the RRC signalinq carries the effective time parameter; [0190] If the neural network block is not critical (e.g., has a normal or non-critical priority), then the timing for using (e.g., applying) the neural network block may be indicated by base station 105-b (e.g., via RRC signaling). For example, an RRC message (e.g., at 530, 525, or otherwise (not shown)) may indicate a timer, or a transmission time interval (TTI) counter (e.g., a symbol counter, slot counter, or the like) or, determininq an effective time for the target model based on an effective time parameter and a time when the DCI signaling is received, wherein the DCI signalinq carriers the effective time parameter.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Kumar and Bao before him or her, to modify the method of Kumar in include time configurations as taught by Bao.
The motivation for doing so would be improved network signal throughput. (Paragraph 0080 by Bao)].
In regards to claim 16, Kumar teaches the limitations of the parent claim.
Kumar does not teach receiving an acknowledgement character (ACK) from the terminal in feedback of the MAC CE signaling, the RRC signaling, or the DCI signaling.
However, Bao does teach receiving an acknowledgement character (ACK) from the terminal in feedback [0271] The acknowledgement manager 1220 may receive, from the UE, an acknowledgment message indicating that the one or more neural network block parameters have been successfully received by the UE. In some examples, the acknowledgement manager 1220 may transmit, to the UE, an acknowledgement message based on the receiving of the request message, of the MAC CE signaling, [0189] f UE 115-c successfully receives the neural network block parameters at 530, then UE 115-c may send an ACK message at 540 (e.g., an ACK corresponding to the DCI message, MAC-CE, or PDSCH message), the RRC signaling, [0190] an RRC message (e.g., at 530, 525, or otherwise (not shown)) may indicate a timer, or a transmission time interval (TTI) counter (e.g., a symbol counter, slot counter, or the like) or the DCI signaling [0191] In some examples, during reconfiguration (e.g., via another RRC message or a DCI message).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Kumar and Bao before him or her, to modify the method of Kumar in include time configurations as taught by Bao.
The motivation for doing so would be improved network signal throughput. (Paragraph 0080 by Bao)].
In regards to claim 4,12 and 25, Kumar teaches the limitations of the parent claim.
Kumar does not teach wherein the model indication information comprises model parameter information, the model parameter information comprising at least one of: a model type parameter; a computation parameter matrix parameter of a neuron node; a bias parameter of the neuron node; an activation function parameter of the neuron node; a stride parameter; or a padding value parameter.
However, Bao does teach wherein the model indication information comprises model parameter information, the model parameter information comprising at least one of: a model type parameter; a computation parameter matrix parameter of a neuron node; a bias parameter of the neuron node; [0149] Each node of neural network block 300 may perform an activation function. For input nodes 305 of the input layer, the input values may be raw data or processed data (e.g., unprocessed numerical values) provided by a base station or configured at the UE 115. Each input node 305 may multiply one or more input values with one or more weights, and add a bias value, an activation function parameter of the neuron node; [0149] E ach hidden node may also perform an activation function on its received inputs (e.g., the outputs provided by input nodes 305). For example, hidden node 310-a may be configured with three weight values and a bias value (e.g., via one or more neural network block parameters as described in greater detail with reference to FIG. 5), a stride parameter; or a padding value parameter.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Kumar and Bao before him or her, to modify the method of Kumar in include model indication information as taught by Bao.
The motivation for doing so would be improved network signal throughput. (Paragraph 0080 by Bao)].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEHAB A ALAWDI whose telephone number is (571)270-3203. The examiner can normally be reached M-F 9-5.
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/SHEHAB A ALAWDI/Examiner, Art Unit 2466
/JAY P PATEL/Primary Examiner, Art Unit 2466
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