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 § 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, 7-8 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Parichehrehteroujeni et al (US 20230232298) (hereinafter Parichehrehteroujeni) in view of Gupta (US 2020/0367164).
Regarding claim 1, Parichehrehteroujeni discloses an apparatus for an access node (e.g., Fig. 2, e.g., Source eNB/gNB 20), comprising: a memory interface to send or receive, to or from a data storage device, measurement information for measurement signaling between a first next generation radio access network (NG-RAN) node (e.g., Source eNB/gNB 20) and a second NG-RAN node (e.g., Target eNB/gNB 22)(see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the communication circuitry 1720 is configured to transmit and/or receive information to and/or from one or more other nodes); and processor circuitry communicatively coupled to the memory interface (see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the network node 1700 includes processing circuitry 1710), the processor circuitry to:
generate a handover request message (see Parichehrehteroujeni, Fig. 2, p. [0005-0006], e.g., handover request 24), the handover request message to request a preparation of resources for a handover of a user equipment (UE), the handover request message to include an information element (IE) with one or more parameters to request measurement information (see Fig. 3, e.g., UE measurement 42) according to the one or more parameters (see Parichehrehteroujeni, p. [0006], e.g., the HANDOVER REQUEST message 24 may comprise a number of user specific information elements (IE) which shall be used by the target network node to serve the user device in case of successful handover preparation), the measurement information to comprise feedback information to train the ML model (see Parichehrehteroujeni, p. [0143-0145], e.g., Machine learning (ML) can be used to find a predictive function for a given dataset); and send an indication to transmit the handover request message from the first NG-RAN node to the second NG-RAN node (see Parichehrehteroujeni, Fig. 4, p. [0106], e.g., transmitting an indication 36 that the source node 32 wants feedback associated 44 to one or more target cells).
However, Parichehrehteroujeni does not expressly disclose the processor circuitry to: initiate execution of a machine learning (ML) model by the first NG-RAN node to select an energy saving state for the first NG-RAN node, the second NG-RAN node or a user equipment (UE).
Gupta discloses the above recited limitations (see Gupta, Fig. 1, p. [0018-0019], e.g., the processor 30 also maintains and operates a machine learning engine 35 to generate rules 52 with the training data 50 to be stored in the memory 15. In particular, the processor 30 may execute instructions stored on the memory 15 to implement the machine learning engine 35 and to collect analytics information from the apparatus 10 to provide to the machine learning engine. The rules 52 are used to determine if the network interface 20 is to be switched from the power-saving state to a powered state in the presence of the wireless network).
It would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to incorporate Gupta’s teachings into Parichehrehteroujeni.
The suggestion/motivation would have been to use the training data to generate rules to determine if the network interface is to be switched from the power-saving state to the powered state in the presence of the wireless network as suggested by Gupta.
Regarding claim 7, the combined teachings of Parichehrehteroujeni and Gupta disclose the apparatus of claim 1, comprising a signaling service between the first NG- RAN node and the second NG-RAN node, the signaling service to transmit the handover request message from the first NG-RAN node to the second NG-RAN node over an Xn interface in accordance with an Xn application protocol (XnAP) (see Parichehrehteroujeni, p. [0254], e.g., Network connection interface 1911 may be configured to include a receiver and a transmitter interface used to communicate with one or more other devices over a communication network according to one or more communication protocols, such as Ethernet, TCP/IP, SONET, ATM, or the like).
Regarding claim 8, Parichehrehteroujeni discloses an apparatus for an access node (e.g., Fig. 2, e.g., Target eNB/gNB 22), comprising: a memory interface to send or receive, to or from a data storage device, measurement information for measurement signaling between a first next generation radio access network (NG-RAN) node and a second NG-RAN node (e.g., Source eNB/gNB 20) and a second NG-RAN node (e.g., Target eNB/gNB 22)(see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the communication circuitry 1720 is configured to transmit and/or receive information to and/or from one or more other nodes); and processor circuitry communicatively coupled to the memory interface (see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the network node 1700 includes processing circuitry 1710), the processor circuitry to: decode a resource status update message received from the second NG-RAN node by the first NG-RAN node in response to a resource status request message sent by the first NG-RAN node to the second NG-RAN node (see Parichehrehteroujeni, p. [0107], e.g., feedback information 44), the resource status update message to include an information element (IE) with one or more parameters to indicate measurement information requested in the resource status request message (see Parichehrehteroujeni, p. [0006], e.g., the HANDOVER REQUEST message 24 may comprise a number of user specific information elements (IE) which shall be used by the target network node to serve the user device in case of successful handover preparation), the measurement information to comprise feedback information to train the ML model (see Parichehrehteroujeni, p. [0143-0145], e.g., Machine learning (ML) can be used to find a predictive function for a given dataset); and train the ML model with the feedback information from the second NG-RAN node (see Parichehrehteroujeni, p. [0145-0148], e.g., the feedback request 36 to the target node 34 also includes a list of feature information that resides on the target node 34, which can be used to improve the prediction of one or more values related to the feedback information 44 element).
However, Parichehrehteroujeni does not expressly disclose the processor circuitry to: initiate execution of a machine learning (ML) model by the first NG-RAN node to select an energy saving state for the first NG-RAN node, the second NG-RAN node or a user equipment (UE).
Gupta discloses the above recited limitations (see Gupta, Fig. 1, p. [0018-0019], e.g., the processor 30 also maintains and operates a machine learning engine 35 to generate rules 52 with the training data 50 to be stored in the memory 15. In particular, the processor 30 may execute instructions stored on the memory 15 to implement the machine learning engine 35 and to collect analytics information from the apparatus 10 to provide to the machine learning engine. The rules 52 are used to determine if the network interface 20 is to be switched from the power-saving state to a powered state in the presence of the wireless network).
Regarding claim 12, Parichehrehteroujeni discloses an apparatus for an access node (e.g., Fig. 2, e.g., Source eNB/gNB 20), comprising: a memory interface to send or receive, to or from a data storage device, measurement information for measurement signaling between a first next generation radio access network (NG-RAN) node and a second NG-RAN node (e.g., Source eNB/gNB 20) and a second NG-RAN node (e.g., Target eNB/gNB 22)(see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the communication circuitry 1720 is configured to transmit and/or receive information to and/or from one or more other nodes); and processor circuitry communicatively coupled to the memory interface (see Parichehrehteroujeni, Fig. 17, p. [0214], e.g., the network node 1700 includes processing circuitry 1710), the processor circuitry to:
generate a resource status request message (see Parichehrehteroujeni, Fig. 2, p. [0005-0006], e.g., handover request 24), the resource status request message to include an information element (IE) with one or more parameters to indicate initiation of a request for measurement information according to the one or more parameters (see Parichehrehteroujeni, p. [0006], e.g., the HANDOVER REQUEST message 24 may comprise a number of user specific information elements (IE) which shall be used by the target network node to serve the user device in case of successful handover preparation), the measurement information (see Fig. 3, e.g., UE measurement 42) to comprise feedback information to train the ML model (see Parichehrehteroujeni, p. [0143-0145], e.g., Machine learning (ML) can be used to find a predictive function for a given dataset); and
send an indication to transmit the resource status request message from the first NG- RAN node to the second NG-RAN node (see Parichehrehteroujeni, Fig. 4, p. [0106], e.g., transmitting an indication 36 that the source node 32 wants feedback associated 44 to one or more target cells).
However, Parichehrehteroujeni does not expressly disclose the processor circuitry to: initiate execution of a machine learning (ML) model by the first NG-RAN node to select an energy saving state for the first NG-RAN node, the second NG-RAN node or a user equipment (UE).
Gupta discloses the above recited limitations (see Gupta, Fig. 1, p. [0018-0019], e.g., the processor 30 also maintains and operates a machine learning engine 35 to generate rules 52 with the training data 50 to be stored in the memory 15. In particular, the processor 30 may execute instructions stored on the memory 15 to implement the machine learning engine 35 and to collect analytics information from the apparatus 10 to provide to the machine learning engine. The rules 52 are used to determine if the network interface 20 is to be switched from the power-saving state to a powered state in the presence of the wireless network).
Claims 2-5, 9-11, 13, 15, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over the combined teachings of Parichehrehteroujeni and Gupta as applied to claims 1, 7-8 and 12 above, and further in view of Rahman et al (US 2023/0422127) (hereinafter Rahman).
Regarding claim 2, the combined teachings of Parichehrehteroujeni and Gupta do not expressly disclose the apparatus of claim 1, the IE to have an IE group name of periodic feedback for model training, a presence of optional, and a semantics description to indicate the IE is present when the first NG-RAN node requests feedback to improve the ML training.
Rahman discloses the above recited limitations (see Rahman, p. [0149], e.g., Table)
It would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to incorporate Rahman’s teachings into the combined teachings of Parichehrehteroujeni and Gupta. The suggestion/motivation would have been to provide LTE resource status request message to improve the connection for a wireless device as suggested by Rahman.
Regarding claim 3, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 1, the IE to have an IE group name of report characteristics, a presence of optional, an IE type and reference of a bitstring with a size of 32 bits, and a semantics description for one or more bits in a bitmap, wherein each position in the bitmap indicates a measurement object the second NG-RAN is requested to report (see Rahman, p. [0149], e.g., Table).
Regarding claim 4, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 1, the IE to have an IE group name of report characteristics, a presence of optional, an IE type and reference of a bitstring with a size of 32 bits, and a semantics description for one or more bits in a bitmap, wherein each position in the bitmap indicates a measurement object the second NG-RAN is requested to report, the bitmap to have a sixth bit to represent average cell throughput (see Rahman, p. [0149], e.g., Table).
Regarding claim 5, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 1, the IE to have an IE group name of feedback periodicity, a presence of optional, an IE type and reference of enumerated with values of 500 milliseconds (ms), 1000 ms, 2000 ms, 5000 ms, 10000 ms, 1 minute, 5 minutes or 10 minutes, and a semantics description that indicates periodicity can be used for reporting of current cell capacity, cell throughput, and current resource availability, wherein the semantics description to further indicate when the IE is not present the feedback is a one- time feedback (see Rahman, p. [0149], e.g., Table).
Regarding claim 9, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 8, the IE to have an IE group name of cell measurement result, a cell measurement result item, a predicted average throughput over a defined interval, a prediction interval, a confidence level of a prediction, a quantized histogram of an artificial intelligence (AI) model error, an average time for a user equipment (UE) to connect to a cell, an average cell throughput, or UE information (see Rahman, p. [0155], e.g., Table, p. [0156-0158], e.g., load information relating to traffic load information, may further be communicated such as, e.g. a number of active UEs, number of RRC connected UEs).
Regarding claim 10, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 8, the processor circuitry to decode subsequent resource status update messages periodically received from the second NG-RAN node with updated measurement information (see Parichehrehteroujeni, p. [0152], e.g., the source node 32 still requests to receive feedback information 44 from the target node 32. This can be used to evaluate or update the ML model).
Regarding claim 11, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 8, comprising a signaling service between the first NG- RAN node and the second NG-RAN node, the signaling service to receive the resource status update message from the second NG-RAN node by the first NG-RAN node over an Xn interface in accordance with an Xn application protocol (XnAP) (see Parichehrehteroujeni, p. [0254], e.g., Network connection interface 1911 may be configured to include a receiver and a transmitter interface used to communicate with one or more other devices over a communication network according to one or more communication protocols, such as Ethernet, TCP/IP, SONET, ATM, or the like).
Regarding claim 13, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 12, the IE to have an IE group name of report characteristics with a semantics description for one or more bits in a bitmap, wherein each position in the bitmap indicates a measurement object the second NG-RAN is requested to report (see Rahman, p. [0149], e.g., Table).
Regarding claim 15, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 12, the IE to have an IE group name of prediction interval, a presence of optional, an IE type and reference of enumerated with values for 5 minutes, 10 minutes, 30 minutes or 60 minutes, and a semantics description that when a seventh bit and an eighth bit of a bitmap are present, then the IE indicates a defined interval over which the prediction has been made (see Rahman, p. [0149], e.g., Table).
Regarding claim 19, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 12, the IE to have an IE group name of feedback stop trigger for ML training, a presence of optional, an IE type and reference of enumerated with values for a specific time duration, a user equipment (UE) goes to idle, or the UE handover to another cell, and a semantics description that it is present only when a reporting periodicity is present (see Rahman, p. [0146], e.g., The periodic update may further be configured to trigger every set time interval such as e.g. every 100 ms, 1 s, 2 s, 10 s, 30 s, or 60 s, or whenever the load has changed a specified amount, e.g. 5% or 10 Mbit/s or 100 physical resource blocks/10 ms, up or down).
Regarding claim 20, the combined teachings of Parichehrehteroujeni, Gupta and Rahman disclose the apparatus of claim 12, the IE to have an IE group name of feedback duration, a presence of optional, an IE type and reference of enumerated with values of 10 seconds or 100 seconds, and a semantics description that it is present when a feedback stop trigger for ML training is set to a specific time duration (see Rahman, p. [0146], e.g., The periodic update may further be configured to trigger every set time interval such as e.g. every 100 ms, 1 s, 2 s, 10 s, 30 s, or 60 s, or whenever the load has changed a specified amount, e.g. 5% or 10 Mbit/s or 100 physical resource blocks/10 ms, up or down).
Allowable Subject Matter
Claims 6, 14 and 16-18 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
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/MINH TRANG T NGUYEN/Primary Examiner, Art Unit 2477