DETAILED ACTION
This office action is a response to the application 18/400,937 filed on December 29, 2023.
Claims 1-20 are pending.
Claims 1-4, 6-15 and 17-20 are rejected.
Claims 5 and 16 are objected to.
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, 2, 6, 12, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. U.S. Patent Application Publication 2021/0250245, hereinafter Li, in view of Shetty et al. U.S. Patent Application Publication 2023/0362658, hereinafter Shetty, and Chen et al. U.S. Patent Application Publication 2024/0284191, hereinafter Chen.
Regarding Claim 1, Li discloses a process for detecting capacity breaches in an area of interest (AOI) of a radio access network (RAN) (Abstract; Figure 1-3, 7 and 9; Paragraph [0003 and 0015] Predicting/forecasting an out of capacity time for one or more access points in a cellular communication network), the process comprising:
generating a subscriber growth model in the AOI of the RAN (Paragraph [0016-0017] and 0018] Via social network systems and application use data from a plurality of users (number of samples that includes numerous metrics corresponding to user), the system is operable to predict a time when the area of interest will reach a capacity threshold. These metrics are utilized to draft one or more models for identifying cells of interest that have or will network capacity.);
querying data for cells in the AOI of the RAN over a sampling period and extrapolating the data using the subscriber growth model to generate forecast indicators for the cells and for sectors associated with the cells; comparing the forecast indicators to capacity thresholds to forecast sector capacity breaches at the sectors (Paragraph [0016, 0025-0030 and 0064] Particular embodiments of the system may use the data (e.g., application names, application types, time duration, quality of experience, network speed, latency, network coverage, network traffic volume, number of samples, etc.) collected at the application level to generate models for identifying the cells that have network capacity issues or are predicted to have network capacity issue in a future time. The system may collect data samples associated with a cell of interest and aggregate the collected data samples into a series of data points; In particular embodiments, the system may identify one or more areas of interest covering one or more access points for predicting the amount of time until these access points are out of capacity. As an example, the system may identify an area covering one or more cells with network congestion as a geographic area of interest.” Li suggests the inclusion of sectors, as well as cells, when they are required for network enhancement).
Li discloses forecasting sector capacity breach in a radio access network but fails to disclose forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach.
However, Shetty more specifically teaches forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach (Figure 1-3 and 6; Paragraph [0056-0076] Monitoring utilization of radio resources of the SA network and the radio resources of the NSA network by a RIC; Method 300 can interchangeably allocate radio resources for NSA users and SA users in an overlapping area of coverage. The SA network or 5G core network may include an SA-gNB, an SA-RU, one or more SA-vDUs, and one or more SA-vCUs. The NSA network or 4G core network may include an NSA-gNB, an NSA-RU, one or more NSA-vDUs, and one or more NSA-vCUs. The SA-RU and the NSA-RU are in the NR coverage overlapped with the LTE coverage. The RIC is configured to detect the overload of the NSA users and the SA users. The SA-gNB and the NSA-gNB are configured to dynamically share the SA-RU and NSA-RU for the SA users and NSA users; The RIC 202 may detect a need for additional bandwidth for one of NSA users and SA users based upon KPI and send instructions to one of SA-vCUs or NSA-vCUs for dynamically allocating a frequency bandwidth to one of the SA users or the NSA users for interchangeably providing additional bandwidth to one of the NSA users or the SA users when one of the NSA users or SA users needs additional bandwidth; When there is a need for NSA resources in an area, the vDUs and RUs of NSA are re-purposed to connect to vCUs of SA to provide the additional bandwidth to SA users; the reallocation of radio resources associated with the vDU with excess capacity may include allocating a portion of the frequency band utilized by the vDU with excess capacity to an updated vDU instantiated in the SA network or the NSA network having high radio resource utilization).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li with the teachings of Shetty. - The method provides a RIC-based mechanism to improve the spectral efficiency and dynamically share the distribution unit (DU) or radio unit (RU) software between NSA and SA based on the key performance indicators (KPIs), and provides solutions for the operator to re-purpose the frequency or frequency band between the NSA and SA users, which improves spectral efficiency and also for migration from the NSA network to the SA network or vice versa (Shetty Abstract; Paragraph [0001-0003 and 0017-0024]).
Li in view of Shetty disclose forecasting of a capacity breach and disclose relocating of connections and users but may not explicitly disclose identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach.
However, Chen more specifically teaches identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach (Paragraph [0029-0044] more sites are added/deployed, it may be possible for that same vCU to be placed/instantiated at a more central location to accommodate vDUs at those additional sites. In this regard, the location/placement of the vCU may be modified/adjusted to be relocated from the local hub to a more central/centralized hub; if the traffic at the local site increases, the vCU might not have sufficient computational capacity or resources to adequately support the incremental traffic, such that it might make sense to reassign/reallocate a portion of the responsibilities of the vCU to other vCUs (or other instances of the vCU that may be instantiated at the local site).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty with the teachings of Chen. The method provide for a reduced-cost implementation of a VRAN network or system, while at the same time enhancing performance based on dynamic factors or conditions (Chen Abstract; Paragraph [0001-0003]).
Regarding Claim 2, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen further disclose wherein forecasting the vDU capacity breach further comprises: forecasting a number of RRC connections per DU during a busy hour; and detecting a vDU capacity breach in response to the number of RRC connections per DU exceeding a capacity threshold (Li Paragraph [0003, 0021 and 0032-0033] Particular embodiments described here relate to a method of predicting the amount of time until an access point of a communication network is out of capacity based on network performance data collected at the application level. The system may first collect network performance data at the application level over a period of time (e.g., W weeks) and aggregate the collected data samples into a series of data points. Each data point may be aggregated based on data samples of the same hour of one week (e.g., each data point having a network traffic value of one hour aggregated over one week); Shetty Paragraph [0028, 0052-0061] High utilization and number of RRC connections over periods of time to determine demand for radio resources and which have excess capacity; Chen Paragraph [0026] Forecasting and information on number/amount of users and subscribers).
Regarding Claim 6, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen further disclose wherein identifying the capacity expansion further comprises identifying a number of DU servers for addition to the RAN (Shetty Paragraph [0052-0087]; Chen Paragraph [0029-0044]).
Regarding Claim 12, Li discloses a process for detecting capacity breaches in an area of interest (AOI) of a radio access network (RAN) (Abstract; Figure 1-3, 7 and 9; Paragraph [0003 and 0015] Predicting/forecasting an out of capacity time for one or more access points in a cellular communication network), the process comprising:
querying data RAN data over a sampling period and extrapolating the data using a subscriber growth model to generate forecast indicators for cells and for sectors associated with the cells; comparing the forecast indicators to capacity thresholds to forecast a sector capacity breach in the AOI of the RAN (Paragraph [0016-0017] and 0018] Via social network systems and application use data from a plurality of users (number of samples that includes numerous metrics corresponding to user), the system is operable to predict a time when the area of interest will reach a capacity threshold. These metrics are utilized to draft one or more models for identifying cells of interest that have or will network capacity; Paragraph [0016, 0025-0030 and 0064] Particular embodiments of the system may use the data (e.g., application names, application types, time duration, quality of experience, network speed, latency, network coverage, network traffic volume, number of samples, etc.) collected at the application level to generate models for identifying the cells that have network capacity issues or are predicted to have network capacity issue in a future time. The system may collect data samples associated with a cell of interest and aggregate the collected data samples into a series of data points; In particular embodiments, the system may identify one or more areas of interest covering one or more access points for predicting the amount of time until these access points are out of capacity. As an example, the system may identify an area covering one or more cells with network congestion as a geographic area of interest.” Li suggests the inclusion of sectors, as well as cells, when they are required for network enhancement).
Li discloses forecasting sector capacity breach in a radio access network but fails to disclose forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach.
However, Shetty more specifically teaches forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach (Figure 1-3 and 6; Paragraph [0056-0076] Monitoring utilization of radio resources of the SA network and the radio resources of the NSA network by a RIC; Method 300 can interchangeably allocate radio resources for NSA users and SA users in an overlapping area of coverage. The SA network or 5G core network may include an SA-gNB, an SA-RU, one or more SA-vDUs, and one or more SA-vCUs. The NSA network or 4G core network may include an NSA-gNB, an NSA-RU, one or more NSA-vDUs, and one or more NSA-vCUs. The SA-RU and the NSA-RU are in the NR coverage overlapped with the LTE coverage. The RIC is configured to detect the overload of the NSA users and the SA users. The SA-gNB and the NSA-gNB are configured to dynamically share the SA-RU and NSA-RU for the SA users and NSA users; The RIC 202 may detect a need for additional bandwidth for one of NSA users and SA users based upon KPI and send instructions to one of SA-vCUs or NSA-vCUs for dynamically allocating a frequency bandwidth to one of the SA users or the NSA users for interchangeably providing additional bandwidth to one of the NSA users or the SA users when one of the NSA users or SA users needs additional bandwidth; When there is a need for NSA resources in an area, the vDUs and RUs of NSA are re-purposed to connect to vCUs of SA to provide the additional bandwidth to SA users; the reallocation of radio resources associated with the vDU with excess capacity may include allocating a portion of the frequency band utilized by the vDU with excess capacity to an updated vDU instantiated in the SA network or the NSA network having high radio resource utilization).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li with the teachings of Shetty. - The method provides a RIC-based mechanism to improve the spectral efficiency and dynamically share the distribution unit (DU) or radio unit (RU) software between NSA and SA based on the key performance indicators (KPIs), and provides solutions for the operator to re-purpose the frequency or frequency band between the NSA and SA users, which improves spectral efficiency and also for migration from the NSA network to the SA network or vice versa (Shetty Abstract; Paragraph [0001-0003 and 0017-0024]).
Li in view of Shetty disclose forecasting of a capacity breach and disclose relocating of connections and users but may not explicitly disclose identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach.
However, Chen more specifically teaches identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach (Paragraph [0029-0044] more sites are added/deployed, it may be possible for that same vCU to be placed/instantiated at a more central location to accommodate vDUs at those additional sites. In this regard, the location/placement of the vCU may be modified/adjusted to be relocated from the local hub to a more central/centralized hub; if the traffic at the local site increases, the vCU might not have sufficient computational capacity or resources to adequately support the incremental traffic, such that it might make sense to reassign/reallocate a portion of the responsibilities of the vCU to other vCUs (or other instances of the vCU that may be instantiated at the local site).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty with the teachings of Chen. The method provide for a reduced-cost implementation of a VRAN network or system, while at the same time enhancing performance based on dynamic factors or conditions (Chen Abstract; Paragraph [0001-0003]).
Regarding Claim 13, Li in view of Shetty and Chen disclose the process of Claim 12. Li in view of Shetty and Chen further disclose wherein forecasting the vDU capacity breach further comprises: forecasting a number of RRC connections per DU during a busy hour; and detecting a vDU capacity breach in response to the number of RRC connections per DU exceeding a capacity threshold (Li Paragraph [0003, 0021 and 0032-0033] Particular embodiments described here relate to a method of predicting the amount of time until an access point of a communication network is out of capacity based on network performance data collected at the application level. The system may first collect network performance data at the application level over a period of time (e.g., W weeks) and aggregate the collected data samples into a series of data points. Each data point may be aggregated based on data samples of the same hour of one week (e.g., each data point having a network traffic value of one hour aggregated over one week); Shetty Paragraph [0028, 0052-0061] High utilization and number of RRC connections over periods of time to determine demand for radio resources and which have excess capacity; Chen Paragraph [0026] Forecasting and information on number/amount of users and subscribers).
Regarding Claim 20, Li discloses a process for detecting capacity breach in an area of interest (AOI) of a radio access network (RAN) (Abstract; Figure 1-3, 7 and 9; Paragraph [0003 and 0015] Predicting/forecasting an out of capacity time for one or more access points in a cellular communication network), the process comprising:
comparing forecast indicators associated with sectors in an AOI to capacity thresholds to forecast a sector capacity breach (Paragraph [0016, 0025-0030 and 0064] Particular embodiments of the system may use the data (e.g., application names, application types, time duration, quality of experience, network speed, latency, network coverage, network traffic volume, number of samples, etc.) collected at the application level to generate models for identifying the cells that have network capacity issues or are predicted to have network capacity issue in a future time. The system may collect data samples associated with a cell of interest and aggregate the collected data samples into a series of data points; In particular embodiments, the system may identify one or more areas of interest covering one or more access points for predicting the amount of time until these access points are out of capacity. As an example, the system may identify an area covering one or more cells with network congestion as a geographic area of interest.” Li suggests the inclusion of sectors, as well as cells, when they are required for network enhancement).
Li discloses forecasting sector capacity breach in a radio access network but fails to disclose forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach.
However, Shetty more specifically teaches forecasting a virtual distributed unit (vDU) capacity breach in response to forecasting the sector capacity breach; forecasting a virtual central unit (vCU) capacity breach in response to forecasting the sector capacity breach (Figure 1-3 and 6; Paragraph [0056-0076] Monitoring utilization of radio resources of the SA network and the radio resources of the NSA network by a RIC; Method 300 can interchangeably allocate radio resources for NSA users and SA users in an overlapping area of coverage. The SA network or 5G core network may include an SA-gNB, an SA-RU, one or more SA-vDUs, and one or more SA-vCUs. The NSA network or 4G core network may include an NSA-gNB, an NSA-RU, one or more NSA-vDUs, and one or more NSA-vCUs. The SA-RU and the NSA-RU are in the NR coverage overlapped with the LTE coverage. The RIC is configured to detect the overload of the NSA users and the SA users. The SA-gNB and the NSA-gNB are configured to dynamically share the SA-RU and NSA-RU for the SA users and NSA users; The RIC 202 may detect a need for additional bandwidth for one of NSA users and SA users based upon KPI and send instructions to one of SA-vCUs or NSA-vCUs for dynamically allocating a frequency bandwidth to one of the SA users or the NSA users for interchangeably providing additional bandwidth to one of the NSA users or the SA users when one of the NSA users or SA users needs additional bandwidth; When there is a need for NSA resources in an area, the vDUs and RUs of NSA are re-purposed to connect to vCUs of SA to provide the additional bandwidth to SA users; the reallocation of radio resources associated with the vDU with excess capacity may include allocating a portion of the frequency band utilized by the vDU with excess capacity to an updated vDU instantiated in the SA network or the NSA network having high radio resource utilization).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li with the teachings of Shetty. - The method provides a RIC-based mechanism to improve the spectral efficiency and dynamically share the distribution unit (DU) or radio unit (RU) software between NSA and SA based on the key performance indicators (KPIs), and provides solutions for the operator to re-purpose the frequency or frequency band between the NSA and SA users, which improves spectral efficiency and also for migration from the NSA network to the SA network or vice versa (Shetty Abstract; Paragraph [0001-0003 and 0017-0024]).
Li in view of Shetty disclose forecasting of a capacity breach and disclose relocating of connections and users but may not explicitly disclose identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach.
However, Chen more specifically teaches identifying a capacity expansion in response to the vDU capacity breach or the vCU capacity breach (Paragraph [0029-0044] more sites are added/deployed, it may be possible for that same vCU to be placed/instantiated at a more central location to accommodate vDUs at those additional sites. In this regard, the location/placement of the vCU may be modified/adjusted to be relocated from the local hub to a more central/centralized hub; if the traffic at the local site increases, the vCU might not have sufficient computational capacity or resources to adequately support the incremental traffic, such that it might make sense to reassign/reallocate a portion of the responsibilities of the vCU to other vCUs (or other instances of the vCU that may be instantiated at the local site).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty with the teachings of Chen. The method provide for a reduced-cost implementation of a VRAN network or system, while at the same time enhancing performance based on dynamic factors or conditions (Chen Abstract; Paragraph [0001-0003]).
Claims 3, 4, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Shetty and Chen as applied to claim 1 and 12 above, and further in view of Li et al. U.S. Patent Application Publication 2023/0113822, hereinafter Li’822.
Regarding Claim 3 and 14, Li in view of Shetty and Chen disclose the process of Claim 1 and 12. Li in view of Shetty and Chen disclose forecasting vDU capacity but fail to explicitly disclose forecasting a number cells per DU during a busy hour; and detecting a vDU capacity breach in response to the number of cells per DU exceeding a capacity threshold.
However, Li’822 more specifically teaches forecasting a number cells per DU during a busy hour; and detecting a vDU capacity breach in response to the number of cells per DU exceeding a capacity threshold (Paragraph [0004-0005 and 0041-0053] The system may determine, for each identified area, a first average network speed during busy hours of the communication network and a second average network speed during non-busy hours of the communication network. The system may calculate a ratio of the difference between the first and second average network speeds to the first or second average network speed and use the ratio as a network performance metric to gauge the network performance and the quality of the user experience in that area; f determining root causes of low quality of experience (QoE) of a communication network based on a number of QoE metrics (e.g., download speed, download speed of busy hours, latency) and root-cause metrics (e.g., signal strength, congestion indicator, number of samples). The system may firstly collect application usage data in a number of areas (e.g., cells, tiles, regions) over a duration of N days (e.g., 7 days, 28 days). Then, the system may preprocess the collected data for filtering and cleaning and aggregate the collected data into data points per hour per individual day or per hour all N days. After that, the system may determine one or more QoE metrics and root-cause metrics based on the cleaned and aggregated data. The system may use a first set of criteria to determine low QoE in one or more areas of interest (e.g., cells, tiles, regions). For example, the system may use one or more predetermined low QoE thresholds (e.g., an absolute value threshold, a percentage threshold, a percentile threshold) to identify the low QoE cells based on one or more QoE metrics (e.g., download speed, download speed of busy hours, latency).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Li’822. The method enables optimizing the communication network and improving the user experience of end users of the communication network based on generated solution recommendations (Li’822 Abstract; Paragraph [0002-0005]).
Regarding Claim 4 and 15, Li in view of Shetty and Chen disclose the process of Claim 1 and 12. Li in view of Shetty and Chen disclose forecasting vDU capacity but fail to explicitly disclose wherein forecasting the vDU capacity breach further comprises: forecasting physical throughput of the vDU during a busy hour; and detecting a vDU capacity breach in response to the physical throughput of the vDU exceeding a maximum DU capacity.
However, Li’822 more specifically teaches forecasting physical throughput of the vDU during a busy hour; and detecting a vDU capacity breach in response to the physical throughput of the vDU exceeding a maximum DU capacity (Paragraph [0004-0005 and 0041-0053] The system may determine, for each identified area, a first average network speed during busy hours of the communication network and a second average network speed during non-busy hours of the communication network. The system may calculate a ratio of the difference between the first and second average network speeds to the first or second average network speed and use the ratio as a network performance metric to gauge the network performance and the quality of the user experience in that area; f determining root causes of low quality of experience (QoE) of a communication network based on a number of QoE metrics (e.g., download speed, download speed of busy hours, latency) and root-cause metrics (e.g., signal strength, congestion indicator, number of samples). The system may firstly collect application usage data in a number of areas (e.g., cells, tiles, regions) over a duration of N days (e.g., 7 days, 28 days). Then, the system may preprocess the collected data for filtering and cleaning and aggregate the collected data into data points per hour per individual day or per hour all N days. After that, the system may determine one or more QoE metrics and root-cause metrics based on the cleaned and aggregated data. The system may use a first set of criteria to determine low QoE in one or more areas of interest (e.g., cells, tiles, regions). For example, the system may use one or more predetermined low QoE thresholds (e.g., an absolute value threshold, a percentage threshold, a percentile threshold) to identify the low QoE cells based on one or more QoE metrics (e.g., download speed, download speed of busy hours, latency).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Li’822. The method enables optimizing the communication network and improving the user experience of end users of the communication network based on generated solution recommendations (Li’822 Abstract; Paragraph [0002-0005]).
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Shetty and Chen as applied to claim 1 and 12 above, and further in view of Kumar et al. U.S. Patent Application Publication 2023/0236897, hereinafter Kumar.
Regarding Claim 7 and 17, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen fail to disclose wherein identifying the capacity expansion further comprises identifying a number of container clusters for addition to the RAN.
However, Kumar more specifically teaches wherein identifying the capacity expansion further comprises identifying a number of container clusters for addition to the RAN (Paragraph [0050-0069] On-demand container clusters for addition to the network utilizing the current number of container clusters and prediction model taking into account history of available resources of different clusters).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Kumar. The apparatus learns resources and execution times needed to process incoming workloads of the first workload type and the second workload type in a set of one or more clusters in a container-based computing environment, thus ensuring efficient, flexible and cost-effective process for managing containerized workloads (Kumar Abstract; Paragraph [0001-0007]).
Claims 8-11, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Shetty and Chen as applied to claim 1 above, and further in view of Gundavelli et al. U.S. Patent Application Publication 2023/0047867, hereinafter Gundavelli.
Regarding Claim 8, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen fail to explicitly disclose forecasting a fronthaul capacity breach in response to the sector capacity breaches.
However, Gundavelli more specifically teaches forecasting a fronthaul capacity breach in response to the sector capacity breaches (Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Gundavelli. The method enables effectively managing a user equipment connectivity across the WWA VRAN and a WLA access network (Gundavelli Abstract; Paragraph [0002 and 0012-0013]).
Regarding Claim 9, Li in view of Shetty, Chen and Gundavelli disclose the process of Claim 8. Li in view of Shetty, Chen and Gundavelli further disclose wherein the vDU capacity breach is forecast in response to the sector capacity breaches and in response to the fronthaul capacity breach (Gundavelli Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
Regarding Claim 10, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen fail to explicitly disclose forecasting a mid-haul capacity breach in response to the sector capacity breaches.
However, Gundavelli more specifically teaches forecasting a mid-haul capacity breach in response to the sector capacity breaches (Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Gundavelli. The method enables effectively managing a user equipment connectivity across the WWA VRAN and a WLA access network (Gundavelli Abstract; Paragraph [0002 and 0012-0013]).
Regarding Claim 11, Li in view of Shetty, Chen and Gundavelli disclose the process of Claim 10. Li in view of Shetty, Chen and Gundavelli further disclose wherein the vCU capacity breach is forecast in response to the sector capacity breaches and in response to the mid-haul capacity breach (Gundavelli Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
Regarding Claim 18, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen fail to explicitly disclose forecasting a fronthaul capacity breach in response to the sector capacity breach, wherein the vDU capacity breach is forecast in response to the sector capacity breach and in response to the fronthaul capacity breach.
However, Gundavelli more specifically teaches forecasting a fronthaul capacity breach in response to the sector capacity breach, wherein the vDU capacity breach is forecast in response to the sector capacity breach and in response to the fronthaul capacity breach (Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Gundavelli. The method enables effectively managing a user equipment connectivity across the WWA VRAN and a WLA access network (Gundavelli Abstract; Paragraph [0002 and 0012-0013]).
Regarding Claim 19, Li in view of Shetty and Chen disclose the process of Claim 1. Li in view of Shetty and Chen fail to explicitly disclose forecasting a mid-haul capacity breach in response to the sector capacity breach, wherein the vCU capacity breach is forecast in response to the sector capacity breach and in response to the mid-haul capacity breach.
However, Gundavelli more specifically teaches forecasting a mid-haul capacity breach in response to the sector capacity breach, wherein the vCU capacity breach is forecast in response to the sector capacity breach and in response to the mid-haul capacity breach (Paragraph [0019-0021 and 0052-0068] Monitoring and KPI performance metrics of performance and potential capacity limitations of vRAN disaggregated elements and fronthaul/midhaul/backhaul).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Li in view of Shetty and Chen with the teachings of Gundavelli. The method enables effectively managing a user equipment connectivity across the WWA VRAN and a WLA access network (Gundavelli Abstract; Paragraph [0002 and 0012-0013]).
Allowable Subject Matter
Claims 5 and 16 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 5 and 16, the prior art of record fail to disclose, alone or in any reasonable combination, as required by the dependent claim, “wherein forecasting the vDU capacity breach further comprises: forecasting a number of cell sites per container cluster that host vDUs; and detecting a vDU capacity breach comprising a container cluster breach in response to the number of cell sites per container cluster exceeding a capacity threshold.”
The Examiner notes the above limitation(s) are not taken alone but in view of the entirety of the claim language including any preceding claim limitations, any proceeding claim limitations, and any intervening claim limitations.
Conclusion
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IVAN O. LATORRE
Primary Examiner
Art Unit 2409
/IVAN O LATORRE/Primary Examiner, Art Unit 2409
Prosecution Insights