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 § 103
1. 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.
2. Claim(s) 47-66 is/are rejected under 35 U.S.C. 103 as being unpatentable over Soldati (US PG Pub. No. 2024/0196252) in view of Lunardi (US PG Pub. No. 2023/0403606).
As per claim 47:
Soldati teaches a method of a first Radio Access Network (RAN) node (see abstract: teaches a method performed by a first node in the RAN), the method comprising:
receiving a first message from a second RAN node (see Figure 4, paragraph [0061] disclose a method performed by the first node in the RAN. See Figure 4, step 420, paragraph [0062], obtaining a record of resource status information describing usage, during a historical time period, of RAN resources controlled by a second node in the RAN. Figure 6, paragraph [0065], clearly disclose said first resource utilization message which is equivalent to said resource status information is received by the first network node 610 from the second network node 620), wherein the first message includes a first information element (see paragraph [0062], the record of status resource information describes a usage), and wherein the first information element indicates a type of object on which the first RAN node performs a prediction (see paragraph [0093], the record of resource status information received by the first node from the second node describing usage during a historical time period. Figure 7e illustrates the metrics (construed as said type of object) that may be included in the record status information received. The metrics include items 701a-701n as listed in figure 7e);
performing the prediction to generate predicted information (see Figure 4, step 430 and paragraph [0062], predicting, based on the obtained record, record status information describing usage of RAN resources controlled by the second node during a future time period), wherein the predicted information includes usage of Physical Resource Blocks (PRBs) per Synchronization Signal Block (SSB) for traffic in Downlink and Uplink (see paragraph [0183], the second resource utilization message transmitted by the first network node to the third network node includes [0190], predicted radio resource status, e.g., per-cell or per-SSB areas usage of DL and/or UL PRB (in total), for GBR and for non-GBR, per-cell or per-SSB areas usage of DL and/or UL scheduling PDCCH CCE);
and sending a second message (see paragraph [0183], the second resource utilization message is sent by the first network node to the third network node)…, wherein the second message includes the predicted information (see paragraphs [0184]-[0194], list several predicted information),
wherein Artificial Intelligence / Machine Learning (AI/ML) for RAN is supported as a RAN function, and wherein the predicted information is related to the AI/ML for RAN (see paragraph [0059], disclose predicted values can be derived based on the actual and predicted status of resources in a given RAN node and may also be derived based on the actual and predicted status of resources in other neighbor RAN Nodes. The predicted status of resource use can be obtained using rules based or other processes, using Artificial Intelligence or Machine Learning AI/ML algorithms and models found in literature, please see paragraph [0060]. The estimates or prediction of resource utilization, such as load metrics, could be exchanged indirectly between the third node and the second node via the first node, please see paragraph [0060]. Thus, it is evident that the respective first, second and third nodes support said AL/ML algorithm/model).
Soldati does not clearly teach sending said second message to …the second RAN node as claimed.
Lunardi teaches sending said second message to …the second RAN node (see paragraph [0137], the second RAN node may receive the predicted resource status information from the first RAN node).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to implement the reception of predicted resource status information (as disclosed in Lunardi) into Soldati as a way of enabling the receiving node to derive the best link adaptation policy to adopt (please see paragraph [0164] of Lunardi). Therefore, providing the receiving device with predicted resource status information helps to determine resources consumed or available in a given area of coverage (please see paragraph [0028] of Lunardi).
As per claim 48:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the AI/ML for RAN is supported by the second RAN node (Soldati, the predicted status of resource use can be obtained using rules based or other processes, using Artificial Intelligence or Machine Learning AI/ML algorithms and models found in literature, please see paragraph [0060]. The estimates or prediction of resource utilization, such as load metrics, could be exchanged indirectly between the third node and the second node via the first node, please see paragraph [0060]. Thus, it is evident that the respective first, second and third nodes support said AL/ML algorithm/model).
As per claim 49:
Soldati in view of Lunardi teaches the method according to claim 47.
Soldati does not clearly teach wherein the first message includes a second information element, and wherein the second information element indicates a point in time to which the prediction applies.
Lunardi teaches wherein the first message includes a second information element, and wherein the second information element indicates a point in time to which the prediction applies (see paragraph [0132], through signaling of the RNN structure and weights from the second network node, in addition to the observed load values in time series (t-1, t-2, …t-N), the first network node can generate a sequence of load information predictions by feeding the predicted value back into the RNN).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the inputs of load information together with the time series (as disclosed in Lunardi) into Soldati as a way of enabling the first network node to predict sequence of load information at future times (please see paragraph [0132] of Lunardi).
As per claim 50:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the predicted information is related to a predicted number of active User Equipments (UEs) (Soldati, see paragraph [0095], explicitly states “number of active wireless devices served by the second node (701a)”).
As per claim 51:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the predicted information includes SSB Area Downlink (DL) Guaranteed Bitrate (GBR) Physical Resource Block (PRB) usage, SSB Area Uplink (UL) GBR PRB usage, SSB Area DL non-GBR PRB usage, SSB Area UL non-GBR PRB usage, SSB Area DL Total PRB usage, and SSB Area UL Total PRB usage (Soldati, see paragraph [0190], explicitly states “Predicted Radio Resource Status, e.g., per-cell or per-SSB areas usage of DL and/or UL PRB (in total, for GBR and for non-GBR), per-cell or per-SSB areas usage of DL and/or UL scheduling PDCCH CCE”).
As per claim 52:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the first information element is a Report Characteristics (Soldati, see paragraph [0187], explicitly states: “Predicted QoS Characteristics: GBR, PDB, PER etc.”).
As per claim 53:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the predicted information is a Radio Resource Status (Soldati, paragraph [0190] explicitly states: “Predicted Radio Resource Status”).
As per claim 54:
Soldati in view of Lunardi teaches the method according to claim 49.
Soldati does not clearly teach wherein the second information element is a Prediction Time.
Lunardi teaches wherein the second information element is a Prediction Time (see paragraph [0103], “time window for which the prediction is considered valid”).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the inputs of load information together with the time series (as disclosed in Lunardi) into Soldati as a way of enabling the first network node to predict sequence of load information at future times (please see paragraph [0132] of Lunardi).
As per claim 55:
Soldati in view of Lunardi teaches the method according to claim 47, wherein the first RAN node is a Next Generation RAN (NG-RAN) node, wherein the second RAN node is an NG-RAN node (Soldati, paragraph [0264] explicitly states: “the first network node, the second network node and the third network node can be any type of node in the group of: evolved NodeB (eNB), NG-RAN node (also knowns as gNB), …”).
Soldati does not clearly teach wherein the first message is an Xn message, and wherein the second message is an Xn message.
Lunardi teaches wherein the first message is an Xn message, and wherein the second message is an Xn message (see paragraph [0596], explicitly states: “Xn impact: Signaling between neighboring nodes of information regarding current or predicted radio conditions, that can serve as input to AI/ML models for prediction of radio resource management policies”).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to implement the reception of predicted resource status information (as disclosed in Lunardi) into Soldati as a way of enabling the receiving node to derive the best link adaptation policy to adopt (please see paragraph [0164] of Lunardi). Therefore, providing the receiving device with predicted resource status information helps to determine resources consumed or available in a given area of coverage (please see paragraph [0028] of Lunardi).
As per claim 56:
Soldati teaches a first Radio Access Network (RAN) node (see Figure 6, first network node 610. Paragraph [0264] explicitly states: “the first network node, the second network node and the third network node can be any type of node in the group of: evolved NodeB (eNB), NG-RAN node (also knowns as gNB), …”) comprising:
a memory (see Figure 19, memory 1904);
and a processor coupled with the memory (see Figure 19, memory 1904 coupled to processor 1902), wherein the processor is configured to:
receive a first message from a second RAN node (see Figure 4, paragraph [0061] disclose a method performed by the first node in the RAN. See Figure 4, step 420, paragraph [0062], obtaining a record of resource status information describing usage, during a historical time period, of RAN resources controlled by a second node in the RAN. Figure 6, paragraph [0065], clearly disclose said first resource utilization message which is equivalent to said resource status information is received by the first network node 610 from the second network node 620), wherein the first message includes a first information element (see paragraph [0062], the record of status resource information describes a usage), and wherein the first information element indicates a type of object on which the first RAN node performs a prediction (see paragraph [0093], the record of resource status information received by the first node from the second node describing usage during a historical time period. Figure 7e illustrates the metrics (construed as said type of object) that may be included in the record status information received. The metrics include items 701a-701n as listed in figure 7e);
perform the prediction to generate predicted information (see Figure 4, step 430 and paragraph [0062], predicting, based on the obtained record, record status information describing usage of RAN resources controlled by the second node during a future time period), wherein the predicted information includes usage of Physical Resource Blocks (PRBs) per Synchronization Signal Block (SSB) for traffic in Downlink and Uplink (see paragraph [0183], the second resource utilization message transmitted by the first network node to the third network node includes [0190], predicted radio resource status, e.g., per-cell or per-SSB areas usage of DL and/or UL PRB (in total), for GBR and for non-GBR, per-cell or per-SSB areas usage of DL and/or UL scheduling PDCCH CCE);
and send a second message (see paragraph [0183], the second resource utilization message is sent by the first network node to the third network node)…, wherein the second message includes the predicted information (see paragraphs [0184]-[0194], list several predicted information),
wherein Artificial Intelligence / Machine Learning (AI/ML) for RAN is supported as a RAN function, and wherein the predicted information is related to the AI/ML for RAN (see paragraph [0059], disclose predicted values can be derived based on the actual and predicted status of resources in a given RAN node and may also be derived based on the actual and predicted status of resources in other neighbor RAN Nodes. The predicted status of resource use can be obtained using rules based or other processes, using Artificial Intelligence or Machine Learning AI/ML algorithms and models found in literature, please see paragraph [0060]. The estimates or prediction of resource utilization, such as load metrics, could be exchanged indirectly between the third node and the second node via the first node, please see paragraph [0060]. Thus, it is evident that the respective first, second and third nodes support said AL/ML algorithm/model).
Soldati does not clearly teach sending said second message to …the second RAN node as claimed.
Lunardi teaches sending said second message to …the second RAN node (see paragraph [0137], the second RAN node may receive the predicted resource status information from the first RAN node).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to implement the reception of predicted resource status information (as disclosed in Lunardi) into Soldati as a way of enabling the receiving node to derive the best link adaptation policy to adopt (please see paragraph [0164] of Lunardi). Therefore, providing the receiving device with predicted resource status information helps to determine resources consumed or available in a given area of coverage (please see paragraph [0028] of Lunardi).
Claim 57 is rejected in the same scope as claim 48.
Claim 58 is rejected in the same scope as claim 49.
Claim 59 is rejected in the same scope as claim 50.
Claim 60 is rejected in the same scope as claim 51.
Claim 61 is rejected in the same scope as claim 52.
Claim 62 is rejected in the same scope as claim 53.
Claim 63 is rejected in the same scope as claim 54.
Claim 64 is rejected in the same scope as claim 55.
As per claim 65:
Soldati teaches a method of a User Equipment (UE) (see paragraph [0164], disclose ability of node to derive from the resource utilization prediction which modulation and coding scheme to adopt for a UE served by the node), the method comprising:
communicating with a first Radio Access Network (RAN) node (paragraph [0164] disclose UE is served by the node and thus there is communication. Paragraph [0165] disclose node could be first RAN node),
wherein the first RAN node is configured to:
receive a first message from a second RAN node (see Figure 4, paragraph [0061] disclose a method performed by the first node in the RAN. See Figure 4, step 420, paragraph [0062], obtaining a record of resource status information describing usage, during a historical time period, of RAN resources controlled by a second node in the RAN. Figure 6, paragraph [0065], clearly disclose said first resource utilization message which is equivalent to said resource status information is received by the first network node 610 from the second network node 620), wherein the first message includes a first information element (see paragraph [0062], the record of status resource information describes a usage), and wherein the first information element indicates a type of object on which the first RAN node performs a prediction (see paragraph [0093], the record of resource status information received by the first node from the second node describing usage during a historical time period. Figure 7e illustrates the metrics (construed as said type of object) that may be included in the record status information received. The metrics include items 701a-701n as listed in figure 7e);
perform the prediction to generate predicted information (see Figure 4, step 430 and paragraph [0062], predicting, based on the obtained record, record status information describing usage of RAN resources controlled by the second node during a future time period), wherein the predicted information includes usage of Physical Resource Blocks (PRBs) per Synchronization Signal Block (SSB) for traffic in Downlink and Uplink (see paragraph [0183], the second resource utilization message transmitted by the first network node to the third network node includes [0190], predicted radio resource status, e.g., per-cell or per-SSB areas usage of DL and/or UL PRB (in total), for GBR and for non-GBR, per-cell or per-SSB areas usage of DL and/or UL scheduling PDCCH CCE);
and send a second message (see paragraph [0183], the second resource utilization message is sent by the first network node to the third network node)…, wherein the second message includes the predicted information (see paragraphs [0184]-[0194], list several predicted information),
wherein Artificial Intelligence / Machine Learning (AI/ML) for RAN is supported as a RAN function, and wherein the predicted information is related to the AI/ML for RAN (see paragraph [0059], disclose predicted values can be derived based on the actual and predicted status of resources in a given RAN node and may also be derived based on the actual and predicted status of resources in other neighbor RAN Nodes. The predicted status of resource use can be obtained using rules based or other processes, using Artificial Intelligence or Machine Learning AI/ML algorithms and models found in literature, please see paragraph [0060]. The estimates or prediction of resource utilization, such as load metrics, could be exchanged indirectly between the third node and the second node via the first node, please see paragraph [0060]. Thus, it is evident that the respective first, second and third nodes support said AL/ML algorithm/model).
Soldati does not clearly teach send said second message to …the second RAN node as claimed.
Lunardi teaches send said second message to …the second RAN node (see paragraph [0137], the second RAN node may receive the predicted resource status information from the first RAN node).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to implement the reception of predicted resource status information (as disclosed in Lunardi) into Soldati as a way of enabling the receiving node to derive the best link adaptation policy to adopt (please see paragraph [0164] of Lunardi). Therefore, providing the receiving device with predicted resource status information helps to determine resources consumed or available in a given area of coverage (please see paragraph [0028] of Lunardi).
As per claim 66:
Soldati teaches a User Equipment (UE) (see Figure 24, paragraph [0412], wireless device 2400) comprising:
a memory (see Figure 24, memory 2415);
and a processor coupled with the memory (see Figure 24, memory 2415 coupled to processor 2401), wherein the processor is configured to:
communicate with a first Radio Access Network (RAN) node (see paragraph [0414], receiving unit 2402 configured to receive, from a first node in the RAN),
wherein the first RAN node is configured to:
receive a first message from a second RAN node (see Figure 4, paragraph [0061] disclose a method performed by the first node in the RAN. See Figure 4, step 420, paragraph [0062], obtaining a record of resource status information describing usage, during a historical time period, of RAN resources controlled by a second node in the RAN. Figure 6, paragraph [0065], clearly disclose said first resource utilization message which is equivalent to said resource status information is received by the first network node 610 from the second network node 620), wherein the first message includes a first information element (see paragraph [0062], the record of status resource information describes a usage), and wherein the first information element indicates a type of object on which the first RAN node performs a prediction (see paragraph [0093], the record of resource status information received by the first node from the second node describing usage during a historical time period. Figure 7e illustrates the metrics (construed as said type of object) that may be included in the record status information received. The metrics include items 701a-701n as listed in figure 7e);
perform the prediction to generate predicted information (see Figure 4, step 430 and paragraph [0062], predicting, based on the obtained record, record status information describing usage of RAN resources controlled by the second node during a future time period), wherein the predicted information includes usage of Physical Resource Blocks (PRBs) per Synchronization Signal Block (SSB) for traffic in Downlink and Uplink (see paragraph [0183], the second resource utilization message transmitted by the first network node to the third network node includes [0190], predicted radio resource status, e.g., per-cell or per-SSB areas usage of DL and/or UL PRB (in total), for GBR and for non-GBR, per-cell or per-SSB areas usage of DL and/or UL scheduling PDCCH CCE);
and send a second message (see paragraph [0183], the second resource utilization message is sent by the first network node to the third network node)…, wherein the second message includes the predicted information (see paragraphs [0184]-[0194], list several predicted information),
wherein Artificial Intelligence / Machine Learning (AI/ML) for RAN is supported as a RAN function, and wherein the predicted information is related to the AI/ML for RAN (see paragraph [0059], disclose predicted values can be derived based on the actual and predicted status of resources in a given RAN node and may also be derived based on the actual and predicted status of resources in other neighbor RAN Nodes. The predicted status of resource use can be obtained using rules based or other processes, using Artificial Intelligence or Machine Learning AI/ML algorithms and models found in literature, please see paragraph [0060]. The estimates or prediction of resource utilization, such as load metrics, could be exchanged indirectly between the third node and the second node via the first node, please see paragraph [0060]. Thus, it is evident that the respective first, second and third nodes support said AL/ML algorithm/model).
Soldati does not clearly teach send said second message to …the second RAN node as claimed.
Lunardi teaches send said second message to …the second RAN node (see paragraph [0137], the second RAN node may receive the predicted resource status information from the first RAN node).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to implement the reception of predicted resource status information (as disclosed in Lunardi) into Soldati as a way of enabling the receiving node to derive the best link adaptation policy to adopt (please see paragraph [0164] of Lunardi). Therefore, providing the receiving device with predicted resource status information helps to determine resources consumed or available in a given area of coverage (please see paragraph [0028] of Lunardi).
Conclusion
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PRINCE AKWASI. MENSAH
Examiner
Art Unit 2474
/PRINCE A MENSAH/ Examiner, Art Unit 2474
/Michael Thier/ Supervisory Patent Examiner, Art Unit 2474
Prosecution Insights