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 .
1. This action is responsive to the application filed on 04/02/2025.
2. Claims 1-15 are pending.
3. Claims 1-15 are rejected.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/02/2025 and 10/30/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. IN202441028017 from Republic of India, filed on 04/04/2024.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3, 4, 7, 8, 11-14 are rejected under 35 U.S.C. 103 as being unpatentable over Dan Weil et al (US 20230155648 A1), hereinafter “Weil” in view of Joey Chou et al (WO 2020242987 A1), hereinafter “Chou”.
Regarding Claim 1, Weil discloses a method of optimizing Radio Access Network-based Notification Area (RNA) in the case a user equipment (UE) transitions to radio resource control inactive (RRC_INACTIVE) state (Weil, Fig 1, Paragraphs 0024-0025, system includes wireless networks, which include one or more RANs and base stations, which server a plurality of user equipment, which operate in an RCC connected, idle, or inactive mode), the method comprising:
detecting, by a radio intelligent controller (RIC) using artificial intelligence (AI) and/or machine learning (ML) technique, an anomaly cell based on at least one of the following factors:
key performance indicators (KPIs), performance measurements (PMs), configuration parameters (CMs), fault management (FM) data, and trace data (Weil, Paragraph 0033, wireless network includes a network optimizing system (NOS), which is integrated in other systems, wherein the NOS uses a model trained using a machine learning algorithm to estimate an impact, on a given cell and/or neighbor cells of the given cell, of reconfiguring an M-MIMO antenna of a given cell. Paragraph 0050, PMC includes a prediction unit connected to a training set generator, which uses a machine learning for predicting impacts of antenna configuration of a given cell and/or neighbors thereof. Paragraph 0052, based on received data (e.g., predicted impact data) it will indicate one or more predicted key performance indicators (KPIs) related to coverage, load, throughput, interference, and/or handoffs of the M-MIMO antenna (e.g., cell) and neighbors thereof);
determining, by the RIC, based on the at least one of the factors, a cause for the detected anomaly cell (Weil, Paragraph 0052, using KPIs to determine coverage, load, throughput, interference, and/or handoffs of the M-MIMO antenna (e.g., cell)).
However, Weil fails to explicitly disclose and recommending, by the RIC to a gNodeB associated with the RNA having the anomaly cell, at least one of the following actions: a) exclude the anomaly cell from the RNA, and b) disable new radio resource control (RRC) connections from the UE.
Chou, from the same or similar field of endeavor, discloses and recommending, by the RIC to a gNodeB associated with the RNA having the anomaly cell, at least one of the following actions:
a) exclude the anomaly cell from the RNA, and b) disable new radio resource control (RRC) connections from the UE (Chou, Fig 11C, Paragraphs 0182-0189, load balancing optimization (LBO) is activated by the intelligent controller (RIC). Performance measurements (e.g., number of RCC connection establishments/releases, a number of abnormal releases, a number of handover failures, and/or a number of call drops) are received and analyzed by the RIC. One or more corrective actions to balance traffic load among neighboring base stations is performed by the RIC, based at least in part on the LBO performance not meeting the performance target, wherein the one or more actions include updating performance targets for the LBO function, disabling the LBO functions, and/or determining actions to optimize traffic load distributions among neighboring cells. One or more actions also may include configuring handover and/or reselection parameters of a cell or cell neighbors and/or initiating a changing of virtualized resources. RIC also performs at least one LBO action, which include requesting the O-DU and/or the O-CU to update UE selection, cell selection and/or handover parameters, requesting the SMOFW to change the virtualized resources; and/or receiving a notification from the IMFW indicating virtualized resources have been changed).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Weil in view of Chou in order to further modify the method of managing massive MIMO antennas in a wireless network from the teachings of Weil with the method of new radio load balancing and mobility robustness from the teachings of Chou.
One of ordinary skill in the art would have been motivated because by monitoring the performance of the system the users will be provided with a higher quality of service by using a redirecting the traffic to less congested cells, for example (Chou – Paragraphs 0144, 0182-0189).
Regarding Claim 3, the combination of Weil and Chou disclose the method according to claim 1 above, where Weil further discloses wherein at least one of:
the FM data relate to network alarms; and the trace data relate to state and contextual information; and the KPI is a function of at least one of the PMs, CMs, FMs and the trace data (Weil, Paragraph 0056, one or more KPIs (e.g., one or more next states of the M-MIMO antenna). Paragraph 0103, KPIs include a coverage parameter, a load parameter, a throughput parameter, an interference parameter, an inter-beam handoff parameter, an inter-site handoff parameter, or a combination thereof).
Regarding Claim 4, the combination of Weil and Chou disclose the method according to claim 3 above, where Chou further discloses wherein the disabling of new RRC connections includes disabling RRCResumeRequest procedure for the anomaly cell (Chou, Paragraphs 0189, 0197, requesting to update UE selection, cell selection, and/or handover parameters).
Regarding Claim 7, the combination of Weil and Chou disclose the method according to claim 3 above, where Chou further discloses wherein the disabling of new RRC connections includes disabling RRCResumeRequest procedure for the anomaly cell (Chou, Paragraphs 0189, 0197, requesting to update UE selection, cell selection, and/or handover parameters).
Regarding Claim 8, the combination of Weil and Chou disclose the method according to claim 1 above, where Chou further discloses further comprising:
withdrawing, by the RIC, the at least one recommended action once the anomaly cell starts operating normally, wherein the withdrawal of the recommended action is based on at least one of the following conditions being met: i) the RIC successfully determines the cause of the anomaly at the anomaly cell and resolves the anomaly; ii) the RIC receives at least one of cell shutdown and cell restart trigger notification; and iii) a specified period of time for automatic withdrawal of the recommended action has elapsed (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 11, the combination of Weil and Chou disclose the method according to claim 3 above, where Chou discloses further comprising: withdrawing, by the RIC, the at least one recommended action once the anomaly cell starts operating normally (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 12, the combination of Weil and Chou disclose the method according to claim 11 above, where Chou discloses wherein the withdrawal of the recommended action is based on at least one of the following conditions being met: i) the RIC successfully determines the cause of the anomaly at the anomaly cell and resolves the anomaly; ii) the RIC receives at least one of cell shutdown and cell restart trigger notification; and iii) a specified period of time for automatic withdrawal of the recommended action has elapsed (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 13, the combination of Weil and Chou disclose the method according to claim 4 above, where Chou discloses further comprising: withdrawing, by the RIC, the at least one recommended action once the anomaly cell starts operating normally (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 14, the combination of Weil and Chou disclose the method according to claim 13 above, where Chou discloses wherein the withdrawal of the recommended action is based on at least one of the following conditions being met: i) the RIC successfully determines the cause of the anomaly at the anomaly cell and resolves the anomaly; ii) the RIC receives at least one of cell shutdown and cell restart trigger notification; and iii) a specified period of time for automatic withdrawal of the recommended action has elapsed (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Claims 2, 5, 6, 9, 10, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Weil in view of Chou and in further view of Oner Orhan et al (US 20220124543 A1), hereinafter “Orhan”.
Regarding Claim 2, the combination of Weil and Chou disclose the method according to claim 1 above.
However, the combination of Weil and Chou fail to explicitly disclose wherein the AI/ML technique is one of Support Vector Machine (SVM) or Isolation Forest technique.
Orhan, from the same or similar field of endeavor, discloses wherein the AI/ML technique is one of Support Vector Machine (SVM) or Isolation Forest technique (Orhan, Paragraph 0207, ML algorithms for classification may be referred to as a “classifier.” Examples of classifiers include linear classifiers, k-nearest neighbor (kNN), decision trees, random forests, support vector machines (SVMs), etc.).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Weil in view of Chou and in further view of Orhan in order to further modify the method of managing massive MIMO antennas in a wireless network from the teachings of Weil and the method of new radio load balancing and mobility robustness from the teachings of Chou with the method of graph neural and reinforcement learning techniques for connection management from the teachings of Orhan.
One of ordinary skill in the art would have been motivated because my using ML/AI for managing connections the system will optimize user associations and experience and fulfill the QoS requirements in a more efficient manner (Orhan – Paragraphs 0004-0005, 0021).
Regarding Claim 5, the combination of Weil, Chou, and Orhan disclose the method according to claim 2 above, where Weil further discloses wherein at least one of:
the FM data relate to network alarms; and the trace data relate to state and contextual information; and the KPI is a function of at least one of the PMs, CMs, FMs and the trace data (Weil, Paragraph 0056, one or more KPIs (e.g., one or more next states of the M-MIMO antenna). Paragraph 0103, KPIs include a coverage parameter, a load parameter, a throughput parameter, an interference parameter, an inter-beam handoff parameter, an inter-site handoff parameter, or a combination thereof).
Regarding Claim 6, the combination of Weil, Chou, and Orhan disclose the method according to claim 2 above, where Chou further discloses wherein the disabling of new RRC connections includes disabling RRCResumeRequest procedure for the anomaly cell (Chou, Paragraphs 0189, 0197, requesting to update UE selection, cell selection, and/or handover parameters).
Regarding Claim 9, the combination of Weil, Chou, and Orhan disclose the method according to claim 2 above, where Chou discloses further comprising: withdrawing, by the RIC, the at least one recommended action once the anomaly cell starts operating normally (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 10, the combination of Weil, Chou, and Orhan disclose the method according to claim 9 above, where Chou discloses wherein the withdrawal of the recommended action is based on at least one of the following conditions being met: i) the RIC successfully determines the cause of the anomaly at the anomaly cell and resolves the anomaly; ii) the RIC receives at least one of cell shutdown and cell restart trigger notification; and iii) a specified period of time for automatic withdrawal of the recommended action has elapsed (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Regarding Claim 15, the combination of Weil, Chou, and Orhan disclose the method according to claim 9 above, where Chou discloses further comprising: withdrawing, by the RIC, the at least one recommended action once the anomaly cell starts operating normally, wherein the withdrawal of the recommended action is based on at least one of the following conditions being met: i) the RIC successfully determines the cause of the anomaly at the anomaly cell and resolves the anomaly; ii) the RIC receives at least one of cell shutdown and cell restart trigger notification; and iii) a specified period of time for automatic withdrawal of the recommended action has elapsed (Chou, Paragraph 0187, updating performance targets and determining actions to optimize traffic load distributions among neighboring cells. Paragraph 0191, receiving load measurements and updating handover parameters).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. All the references listed on 892 are related to the subject matter of identifying anomalous cells using a radio intelligent controller.
Some of the prior art include:
US 20240073716 A1, which discloses a method of anomaly prediction in OpenRAN mobile networks.
US 20220124543 A1, which discloses a method of graph neural network and reinforcement learning techniques for connection management.
US 2013010938 A1, which discloses a method of determining handover criterion in a cellular wireless communication system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAVIER O GUZMAN whose telephone number is (571)270-0588. The examiner can normally be reached Monday - Friday 8 am to 4 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jorge L. Ortiz-Criado can be reached at (571)272-7624. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAVIER O GUZMAN/Primary Examiner, Art Unit 2496
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