DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, anycorrection of the statutory basis for the rejection will not be considered a new ground ofrejection if the prior art relied upon, and the rationale supporting the rejection, would bethe same under either status.
Response to Amendment
The proposed reply filed on 03/05/2026 has been entered. Claims 1, 3-6, 8, 10-13, 15 and 17-19 have been amended. Claims 1-20 are pending in the application.
Rejection withdrawn
The outstanding double patenting rejections of Claims 1, 3-8, 10-15 and 17-19 are withdrawn in light of Applicant's amendment to Claims 1, 3-6, 8, 10-13, 15 and 17-19 filed on 03/05/2026.
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 non-obviousness.
Claim(s) 1, 8 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xing et al. (US 11,552,725 B2) in view of (Wang et al. (US 2022/0255875 A1).
Regarding claim 1, Xing et al. teach a device, comprising: one or more processors configured to: identify a plurality of radio Key Performance Indicators ("KPIs") associated with a plurality of User Equipment ("UEs") that are connected to a radio access network ("RAN") (Figs. 1 and 6, [20, 68, 69, 73], a base station 104, in accordance with various examples. As shown, a base station 104 can include processor(s) 602, memory 604, and transmission hardware 606. The memory 604 can store service attributes 608, network attributes 610, operator policies 612, and/or an OFDM numerology selector 614. The processor(s) 602 may also be responsible for executing all computer applications stored in the memory 604. Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. The base stations 104 can include a gNode B (gNB) that uses 5G New Radio (NR) wireless access technology to connect to UEs 102),
Xing et al. teach wherein each radio KPI is associated with wireless communications between a respective UE and the RAN (Fig. 1, [55], network attributes can define specific frequency bands supported by base stations 104 in licensed and/or unlicensed spectrum. For example, 5G NR base stations 104 can be set to use a 600 MHz band known as n71 in 3GPP standards, a 28 GHz band known as n257 in 3GPP standards, and/or a 39 GHz band known as n260 in 3GPP standards. Network conditions can also include radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions),
Xing et al. teach identify a plurality of service categories associated with the plurality of UEs, wherein each UE is associated with a respective service category (Figs. 1 and 6, [48, 80], the core network 106 can review traffic for different services from one or more UEs 102 connected to one or more base stations 104, and categorize or identify services for the base stations 104. The base station 104 can analyze data packets at a SDAP layer 302 or other protocol layer higher than the physical layer 310 to identify a service, a service category, a QoS Flow ID, and/or associated performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters),
Xing et al. teach wherein each service category is associated with a respective set of Quality of Service ("QoS") parameters (Figs. 1 and 3, [30], at the SDAP layer 302, a Quality of Service (QoS) flow can be mapped to a particular data radio bearer between a UE 102 and a base station 104, and a corresponding QoS flow ID can also be marked in data packets of the QoS flow. Accordingly, a base station 104 can identify traffic associated with particular services or service categories, and/or desired performance attributes for those services or service categories, at the SDAP layer 302 based on parameters such as a QoS flow ID and/or an associated QoS Class Identifier (QCI)),
Xing et al. teach determine a respective priority weight for each UE of the plurality of UEs, wherein a particular priority weight for a particular UE, of the plurality of UEs, is based on: a particular set of radio KPIs associated with the particular UE, and a particular set of QoS parameters associated with a particular service category associated with the particular UE (Figs. 1 and 6, [50, 72-73], a service associated with a QoS Flow ID that corresponds to QoS parameters indicating that data for the service should be delivered at a high priority and at a low latency may be considered a URLLC service. As another example, a service associated with QoS parameters indicating that data for the service is to be delivered at a high guaranteed bitrate may be considered an eMBB service. The Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. Service attributes 608 can also include parameters associated with such known services, such as performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters. In other examples, the service attributes 608 can include information that can associate QoS Class Identifier (QCI) flow IDs, service categories, or other attributes of a service with one or more performance goals, performance requirements, or specific parameters),
Xing et al. teach and schedule traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1, 6, [46, 75], the base station 104 can review data packets of a request for a new service, determine an OFDM numerology to use for that service, and then use that OFDM numerology for subsequent transmissions associated with the service. An OFDM numerology selector 614 can include data and/or computer-executable instructions that can determine one or more OFDM numerologies for communications with a UE 102, based at least in part on services being used by the UE 102. The portions of the OFDM numerology selector 614 can also be considered part of a Radio Resource Manager or other element that schedules data transmissions on different subcarriers 402).
Xing et al. is teaching of controlling the flow of data, based on KPI, service category and priority, between the RAN and UEs. Xing et al., however, fail to expressly disclose of scheduling traffic based on determined priority. (Emphasis added).
Regarding claim 1, Wang et al. teach and schedule traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1 and 2C, [0062, 0068, 0074], the traffic is classified into small and large transactions, and then assigned different QCI weights. The new weights are provided to a RAN scheduler in an eNodeB, for example, which will automatically prioritize the traffic by allocating different resources. One or more traffic flows are received at traffic classifier 242 and at scheduler 246. The traffic flows may include any type of data for transmission over the radio access network to user equipment. The scheduler 246 receives the weight information from the weight adjustor 244 and determines a priority for each data flow. In general, small data flows are favored over large data flows. The scheduler 246 determines priority for data flows on downlinks to user equipment and on uplinks from user equipment to the RAN. The priority information for uplinks may be communicated by the scheduler to the user equipment on a downlink transmission for subsequent use by the user equipment).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Xing et al. by incorporating the features as taught by Wang et al. in order to provide a more effective and efficient system that is capable of scheduling traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs. The motivation is to support an improved method for an enhanced network with data flow differentiation (see [0001]).
Regarding claim 8, Xing et al. teach a non-transitory computer-readable medium, storing a plurality of processor-executable instructions to: identify a plurality of radio Key Performance Indicators ("KPIs") associated with a plurality of User Equipment ("UEs") that are connected to a radio access network ("RAN") (Figs. 1 and 6, [20, 69-70, 73], the processor(s) 602 may also be responsible for executing all computer applications stored in the memory 604, which can be associated with common types of volatile (RAM) and/or nonvolatile (ROM) memory. The processor(s) 602 may also be responsible for executing all computer applications stored in the memory 604. Any other non-transitory medium which can be used to store the desired information and which can be accessed by the base station 104. Any such non-transitory computer-readable media may be part of the base station 104. Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. The base stations 104 can include a gNode B (gNB) that uses 5G New Radio (NR) wireless access technology to connect to UEs 102),
Xing et al. teach wherein each radio KPI is associated with wireless communications between a respective UE and the RAN (Fig. 1, [55], network attributes can define specific frequency bands supported by base stations 104 in licensed and/or unlicensed spectrum. For example, 5G NR base stations 104 can be set to use a 600 MHz band known as n71 in 3GPP standards, a 28 GHz band known as n257 in 3GPP standards, and/or a 39 GHz band known as n260 in 3GPP standards. Network conditions can also include radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions),
Xing et al. teach identify a plurality of service categories associated with the plurality of UEs, wherein each particular UE is associated with a respective service category (Figs. 1 and 6, [48, 80], the core network 106 can review traffic for different services from one or more UEs 102 connected to one or more base stations 104, and categorize or identify services for the base stations 104. The base station 104 can analyze data packets at a SDAP layer 302 or other protocol layer higher than the physical layer 310 to identify a service, a service category, a QoS Flow ID, and/or associated performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters),
Xing et al. teach wherein each UE is associated with a respective service category wherein each service category is associated with a respective set of Quality of Service ("QoS") parameters (Figs. 1 and 3, [30], at the SDAP layer 302, a Quality of Service (QoS) flow can be mapped to a particular data radio bearer between a UE 102 and a base station 104, and a corresponding QoS flow ID can also be marked in data packets of the QoS flow. Accordingly, a base station 104 can identify traffic associated with particular services or service categories, and/or desired performance attributes for those services or service categories, at the SDAP layer 302 based on parameters such as a QoS flow ID and/or an associated QoS Class Identifier (QCI)),
Xing et al. teach determine a respective priority weight for each UE of the plurality of UEs, wherein a particular priority weight for a particular UE, of the plurality of UEs, is based on: a particular set of radio KPIs associated with the particular UE, and a particular set of QoS parameters associated with a particular service category associated with the particular UE (Figs. 1 and 6, [50, 72-73], a service associated with a QoS Flow ID that corresponds to QoS parameters indicating that data for the service should be delivered at a high priority and at a low latency may be considered a URLLC service. As another example, a service associated with QoS parameters indicating that data for the service is to be delivered at a high guaranteed bitrate may be considered an eMBB service. The Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. Service attributes 608 can also include parameters associated with such known services, such as performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters. In other examples, the service attributes 608 can include information that can associate QoS Class Identifier (QCI) flow IDs, service categories, or other attributes of a service with one or more performance goals, performance requirements, or specific parameters),
Xing et al. teach and schedule traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1, 6, [46, 75], the base station 104 can review data packets of a request for a new service, determine an OFDM numerology to use for that service, and then use that OFDM numerology for subsequent transmissions associated with the service. An OFDM numerology selector 614 can include data and/or computer-executable instructions that can determine one or more OFDM numerologies for communications with a UE 102, based at least in part on services being used by the UE 102. The portions of the OFDM numerology selector 614 can also be considered part of a Radio Resource Manager or other element that schedules data transmissions on different subcarriers 402).
Xing et al. is teaching of controlling the flow of data, based on KPI, service category and priority, between the RAN and UEs. Xing et al., however, fail to expressly disclose of scheduling traffic based on determined priority. (Emphasis added).
Regarding claim 8, Wang et al. teach and schedule traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1 and 2C, [0062, 0068, 0074], the traffic is classified into small and large transactions, and then assigned different QCI weights. The new weights are provided to a RAN scheduler in an eNodeB, for example, which will automatically prioritize the traffic by allocating different resources. One or more traffic flows are received at traffic classifier 242 and at scheduler 246. The traffic flows may include any type of data for transmission over the radio access network to user equipment. The scheduler 246 receives the weight information from the weight adjustor 244 and determines a priority for each data flow. In general, small data flows are favored over large data flows. The scheduler 246 determines priority for data flows on downlinks to user equipment and on uplinks from user equipment to the RAN. The priority information for uplinks may be communicated by the scheduler to the user equipment on a downlink transmission for subsequent use by the user equipment).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Xing et al. by incorporating the features as taught by Wang et al. in order to provide a more effective and efficient system that is capable of scheduling traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs. The motivation is to support an improved method for an enhanced network with data flow differentiation (see [0001]).
Regarding claim 15, Xing et al. teach A method, comprising: identifying a plurality of radio Key Performance Indicators ("KPIs") associated with a plurality of User Equipment ("UEs") that are connected to a radio access network ("RAN") (Figs. 1 and 6, [20, 68, 69, 73], a base station 104, in accordance with various examples. As shown, a base station 104 can include processor(s) 602, memory 604, and transmission hardware 606. The memory 604 can store service attributes 608, network attributes 610, operator policies 612, and/or an OFDM numerology selector 614. The processor(s) 602 may also be responsible for executing all computer applications stored in the memory 604. Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. The base stations 104 can include a gNode B (gNB) that uses 5G New Radio (NR) wireless access technology to connect to UEs 102),
Xing et al. teach wherein each radio KPI is associated with wireless communications between a respective UE and the RAN (Fig. 1, [55], network attributes can define specific frequency bands supported by base stations 104 in licensed and/or unlicensed spectrum. For example, 5G NR base stations 104 can be set to use a 600 MHz band known as n71 in 3GPP standards, a 28 GHz band known as n257 in 3GPP standards, and/or a 39 GHz band known as n260 in 3GPP standards. Network conditions can also include radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions),
Xing et al. teach identifying a plurality of service categories associated with the plurality of UEs, wherein each particular UE is associated with a respective service category (Figs. 1 and 6, [48, 80], the core network 106 can review traffic for different services from one or more UEs 102 connected to one or more base stations 104, and categorize or identify services for the base stations 104. The base station 104 can analyze data packets at a SDAP layer 302 or other protocol layer higher than the physical layer 310 to identify a service, a service category, a QoS Flow ID, and/or associated performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters),
Xing et al. teach wherein each service category is associated with a respective set of Quality of Service ("QoS") parameters (Figs. 1 and 3, [30], at the SDAP layer 302, a Quality of Service (QoS) flow can be mapped to a particular data radio bearer between a UE 102 and a base station 104, and a corresponding QoS flow ID can also be marked in data packets of the QoS flow. Accordingly, a base station 104 can identify traffic associated with particular services or service categories, and/or desired performance attributes for those services or service categories, at the SDAP layer 302 based on parameters such as a QoS flow ID and/or an associated QoS Class Identifier (QCI)),
Xing et al. teach determining a respective priority weight for each UE of the plurality of UEs, wherein a particular priority weight for a particular UE, of the plurality of UEs, is based on: a particular set of radio KPIs associated with the particular UE, and a particular set of QoS parameters associated with a particular service category associated with the particular UE (Figs. 1 and 6, [50, 72-73], a service associated with a QoS Flow ID that corresponds to QoS parameters indicating that data for the service should be delivered at a high priority and at a low latency may be considered a URLLC service. As another example, a service associated with QoS parameters indicating that data for the service is to be delivered at a high guaranteed bitrate may be considered an eMBB service. The Network attributes 610 can include information about supported frequency bands in licensed and/or unlicensed spectrum, radio frequency link conditions, key performance indicators, current loads on a base station 104 and/or other base stations 104, interference levels, mobility capabilities of UEs 102, movement speeds of UEs 102, and/or other network conditions. Service attributes 608 can also include parameters associated with such known services, such as performance goals or requirements related to latency, reliability, availability, data rate, and/or packet loss, a QCI, QoS parameters, QoE parameters, a priority level, a package length, an SPID, an ARP, and/or other parameters. In other examples, the service attributes 608 can include information that can associate QoS Class Identifier (QCI) flow IDs, service categories, or other attributes of a service with one or more performance goals, performance requirements, or specific parameters),
Xing et al. teach and scheduling traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1, 6, [46, 75], the base station 104 can review data packets of a request for a new service, determine an OFDM numerology to use for that service, and then use that OFDM numerology for subsequent transmissions associated with the service. An OFDM numerology selector 614 can include data and/or computer-executable instructions that can determine one or more OFDM numerologies for communications with a UE 102, based at least in part on services being used by the UE 102. The portions of the OFDM numerology selector 614 can also be considered part of a Radio Resource Manager or other element that schedules data transmissions on different subcarriers 402).
Xing et al. is teaching of controlling the flow of data, based on KPI, service category and priority, between the RAN and UEs. Xing et al., however, fail to expressly disclose of scheduling traffic based on determined priority. (Emphasis added).
Regarding claim 15, Wang et al. teach and schedule traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs (Figs. 1 and 2C, [0062, 0068, 0074], the traffic is classified into small and large transactions, and then assigned different QCI weights. The new weights are provided to a RAN scheduler in an eNodeB, for example, which will automatically prioritize the traffic by allocating different resources. One or more traffic flows are received at traffic classifier 242 and at scheduler 246. The traffic flows may include any type of data for transmission over the radio access network to user equipment. The scheduler 246 receives the weight information from the weight adjustor 244 and determines a priority for each data flow. In general, small data flows are favored over large data flows. The scheduler 246 determines priority for data flows on downlinks to user equipment and on uplinks from user equipment to the RAN. The priority information for uplinks may be communicated by the scheduler to the user equipment on a downlink transmission for subsequent use by the user equipment).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Xing et al. by incorporating the features as taught by Wang et al. in order to provide a more effective and efficient system that is capable of scheduling traffic, between the RAN and the plurality of UEs, based on the determined priority weights for the plurality of UEs. The motivation is to support an improved method for an enhanced network with data flow differentiation (see [0001]).
Claim(s) 2, 6-7, 9, 13-14, 16 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xing et al. (US 11,552,725 B2) in view of Wang et al. (US 2022/0255875 A1) as applied to claims 1, 8 and 15 above, and further in view of Panigrahi et al. (US 2023/0037228 A1).
Xing et al. and Wang et al. disclose the claimed limitations as described in paragraph 6 above.
Regarding claim 2, Wang et al. teach wherein scheduling the traffic includes allocating radio resources of the RAN in accordance with the determined priority weights (Figs. 1 and 2C, [0018], the data flows are assigned for radio communication between a radio access network and user equipment in an area served by the radio access network, and wherein the classifying is based on a predetermined size criterion. Other aspects of the subject disclosure include reducing priority of data flows classified as large data flows relative to priority of data flows classified as small data flows so that the data flows classified as small data flows have priority for radio communication between the radio access network and the user equipment, scheduling the data flows for radio communication, including assigning radio resources to the data flows according to priorities of the data flows and communicating the data flows between the radio access network and the user equipment based on assigned radio resources).
Regarding claim 9, Wang et al. teach wherein scheduling the traffic includes allocating radio resources of the RAN in accordance with the determined priority weights (Figs. 1 and 2C, [0018], the data flows are assigned for radio communication between a radio access network and user equipment in an area served by the radio access network, and wherein the classifying is based on a predetermined size criterion. Other aspects of the subject disclosure include reducing priority of data flows classified as large data flows relative to priority of data flows classified as small data flows so that the data flows classified as small data flows have priority for radio communication between the radio access network and the user equipment, scheduling the data flows for radio communication, including assigning radio resources to the data flows according to priorities of the data flows and communicating the data flows between the radio access network and the user equipment based on assigned radio resources).
Regarding claim 16, Wang et al. teach wherein scheduling the traffic includes allocating radio resources of the RAN in accordance with the determined priority weights (Figs. 1 and 2C, [0018], the data flows are assigned for radio communication between a radio access network and user equipment in an area served by the radio access network, and wherein the classifying is based on a predetermined size criterion. Other aspects of the subject disclosure include reducing priority of data flows classified as large data flows relative to priority of data flows classified as small data flows so that the data flows classified as small data flows have priority for radio communication between the radio access network and the user equipment, scheduling the data flows for radio communication, including assigning radio resources to the data flows according to priorities of the data flows and communicating the data flows between the radio access network and the user equipment based on assigned radio resources).
Xing et al. and Wang et al. do not expressly disclose the following features: regarding claim 6, wherein the particular UE is a first UE of the plurality of UEs, [[is]] wherein the particular set of radio KPIs associated with the first UE is a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs; regarding claim 7, wherein the plurality of UEs are connected to a same base station of the RAN; regarding claim 13, wherein the particular UE is a first UE of the plurality of UEs, wherein the particular set of radio KPIs associated with the first UE is a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs; Regarding claim 14, wherein the plurality of UEs are connected to a same base station of the RAN; regarding claim 19, wherein the particular UE is a first UE[[,]] of the plurality of UEs, wherein the particular set of radio KPIs associated with the first UE is a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs; regarding claim 20, wherein the plurality of UEs are connected to a same base station of the RAN.
Regarding claim 6, Panigrahi et al. teach wherein a first UE, of the plurality of UEs, is associated with a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs (Figs. 1-3, [0061], each of the sCATs are defined and distinguished by a set of Key Performance Indicators (KPIs) such as data rate, throughput, latency, reliability, etc. It is to be understood by a person having ordinary skill in the art or person skilled in the art that the above examples of KPIs shall not be construed as limiting the scope of the present disclosure. In a general workflow, User Equipment (UEs) requests for RAN resources to the gNB. The smallest unit of the RAN resource is termed as Physical Resource Block (PRB) which represents a fragment of frequency and time domain. UEs demand for resources with different KPIs as per the application demand and accordingly they fall under one of the three sCAT categories. For example, UE on which a YouTube® application is running requires relatively high data-rate connection with moderate latency whereas, a vehicular UE on which a V2I (Vehicle to Infrastructure) application is running demands for a moderate data-rate but low latency connection).
Regarding claim 7, Panigrahi et al. teach wherein the plurality of UEs are connected to a same base station of the RAN (Figs. 1-2, [0060], users or UEs are connected to the network through 5G enhanced Node B (gNB) (note: the gNB (gNodeB) is the fundamental component of the 5G Radio Access Network (RAN), acting as the 5G base station that wirelessly connects user devices (UEs) to the 5G core network). Users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of application).
Regarding claim 13, Panigrahi et al. teach wherein the particular UE is a first UE of the plurality of UEs, wherein the particular set of radio KPIs associated with the first UE is a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs (Figs. 1-3, [0061], each of the sCATs are defined and distinguished by a set of Key Performance Indicators (KPIs) such as data rate, throughput, latency, reliability, etc. It is to be understood by a person having ordinary skill in the art or person skilled in the art that the above examples of KPIs shall not be construed as limiting the scope of the present disclosure. In a general workflow, User Equipment (UEs) requests for RAN resources to the gNB. The smallest unit of the RAN resource is termed as Physical Resource Block (PRB) which represents a fragment of frequency and time domain. UEs demand for resources with different KPIs as per the application demand and accordingly they fall under one of the three sCAT categories. For example, UE on which a YouTube® application is running requires relatively high data-rate connection with moderate latency whereas, a vehicular UE on which a V2I (Vehicle to Infrastructure) application is running demands for a moderate data-rate but low latency connection).
Regarding claim 14, Panigrahi et al. teach wherein the plurality of UEs are connected to a same base station of the RAN (Figs. 1-2, [0060], users or UEs are connected to the network through 5G enhanced Node B (gNB) (note: the gNB (gNodeB) is the fundamental component of the 5G Radio Access Network (RAN), acting as the 5G base station that wirelessly connects user devices (UEs) to the 5G core network). Users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of application).
Regarding claim 19, Panigrahi et al. teach wherein the particular UE is a first UE[[,]] of the plurality of UEs, wherein the particular set of radio KPIs associated with the first UE is a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs (Figs. 1-3, [0061], each of the sCATs are defined and distinguished by a set of Key Performance Indicators (KPIs) such as data rate, throughput, latency, reliability, etc. It is to be understood by a person having ordinary skill in the art or person skilled in the art that the above examples of KPIs shall not be construed as limiting the scope of the present disclosure. In a general workflow, User Equipment (UEs) requests for RAN resources to the gNB. The smallest unit of the RAN resource is termed as Physical Resource Block (PRB) which represents a fragment of frequency and time domain. UEs demand for resources with different KPIs as per the application demand and accordingly they fall under one of the three sCAT categories. For example, UE on which a YouTube® application is running requires relatively high data-rate connection with moderate latency whereas, a vehicular UE on which a V2I (Vehicle to Infrastructure) application is running demands for a moderate data-rate but low latency connection).
Regarding claim 20, Panigrahi et al. teach wherein the plurality of UEs are connected to a same base station of the RAN (Figs. 1-2, [0060], users or UEs are connected to the network through 5G enhanced Node B (gNB) (note: the gNB (gNodeB) is the fundamental component of the 5G Radio Access Network (RAN), acting as the 5G base station that wirelessly connects user devices (UEs) to the 5G core network). Users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of application).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Xing et al. with Wang et al. by incorporating the features as taught by Panigrahi et al. in order to provide a more effective and efficient system that is capable of associating first UE with a first set of radio KPIs, and wherein a second UE, of the plurality of UEs, is associated with a different second set of radio KPIs and the plurality of UEs are connected to a same base station of the RAN. The motivation is to support an improved method for application-aware dynamic slicing in Radio Access Network (see [0002]).
Claim(s) 3 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xing et al. (US 11,552,725 B2) in view of Wang et al. (US 2022/0255875 A1) as applied to claims 1, 8 and 15 above, and further in view of Gordaychik (US 2019/0363843 A1).
Xing et al. and Wang et al. disclose the claimed limitations as described in paragraph 6 above. Xing et al. and Wang et al. do not expressly disclose the following features: regarding claim 3, wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE; regarding claim 10, wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE.
Regarding claim 3, Gordaychik teaches wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE (Fig. 1, [0081], UE capabilities may also correspond to QoS instances or supported QoS instances. In one embodiment, there may be a particular QoS identifier used to indicate QoS levels of an LTE or 5G or beyond network device or UE. A bitrate capability may be measured in kilobits, megabits, gigabits per second. There may also be a priority (or QoS specific) level specific to LTE or 5g. Other priority methods may operate based on PPPP or using a KPI, VQI or 5QI. Any parameter or level indicated may be represented by an integer (signed or unsigned) or Boolean data type. Or any other type for that matter. QoS may also indicate a service type for example IPv4 or a traffic class in v6. QoS may be based on traffic flow (having a traffic flow ID) which may be associated with a radio bearer. QoS parameters or thresholds may change based on application specific information or other information).
Regarding claim 10, Gordaychik teaches wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE (Fig. 1, [0081], UE capabilities may also correspond to QoS instances or supported QoS instances. In one embodiment, there may be a particular QoS identifier used to indicate QoS levels of an LTE or 5G or beyond network device or UE. A bitrate capability may be measured in kilobits, megabits, gigabits per second. There may also be a priority (or QoS specific) level specific to LTE or 5g. Other priority methods may operate based on PPPP or using a KPI, VQI or 5QI. Any parameter or level indicated may be represented by an integer (signed or unsigned) or Boolean data type. Or any other type for that matter. QoS may also indicate a service type for example IPv4 or a traffic class in v6. QoS may be based on traffic flow (having a traffic flow ID) which may be associated with a radio bearer. QoS parameters or thresholds may change based on application specific information or other information).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Xing et al. with Wang et al. by incorporating the features as taught by Gordaychik in order to provide a more effective and efficient system that is capable of associating service category with the particular UE is further based on a set of traffic types, a set of traffic types. The motivation is to support an improved method for transmitting a capability identifier of the UE, to a next generation Node B (see [0002]).
Claim(s) 4, 11 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xing et al. (US 11,552,725 B2) in view of Wang et al. (US 2022/0255875 A1) and Gordaychik (US 2019/0363843 A1) as applied to claims 1, 8 and 15 above, and further in view of Panigrahi et al. (US 2023/0037228 A1).
Xing et al., Wang et al. and Gordaychik disclose the claimed limitations as described in paragraph 6 above. Xing et al.,
Regarding claim 17, Gordaychik teaches wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE, (Fig. 1, [0081], UE capabilities may also correspond to QoS instances or supported QoS instances. In one embodiment, there may be a particular QoS identifier used to indicate QoS levels of an LTE or 5G or beyond network device or UE. A bitrate capability may be measured in kilobits, megabits, gigabits per second. There may also be a priority (or QoS specific) level specific to LTE or 5g. Other priority methods may operate based on PPPP or using a KPI, VQI or 5QI. Any parameter or level indicated may be represented by an integer (signed or unsigned) or Boolean data type. Or any other type for that matter. QoS may also indicate a service type for example IPv4 or a traffic class in v6. QoS may be based on traffic flow (having a traffic flow ID) which may be associated with a radio bearer. QoS parameters or thresholds may change based on application specific information or other information).
Xing et al., Wang et al. and Gordaychik do not expressly disclose the following features: regarding claim 4, wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE; regarding claim 11, wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE; regarding claim 17, wherein the particular service category associated with the particular UE is further based on at least one of: a set of traffic types associated with the particular UE, or a device type of the particular UE, wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE.
Regarding claim 4, Panigrahi et al. teach wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE (Fig. 1-2, [0060], users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of applications as explained above, different types of Quality of Services or Key Performance Indicator (KPI) requirements in terms of bandwidth, latency, and reliability, etc., can be mapped to the applications).
Regarding claim 11, Panigrahi et al. teach wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE (Fig. 1-2, [0060], users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of applications as explained above, different types of Quality of Services or Key Performance Indicator (KPI) requirements in terms of bandwidth, latency, and reliability, etc., can be mapped to the applications).
Regarding claim 17, Panigrahi et al. teach wherein the set of QoS parameters associated with the particular service category include at least one of: a network slice associated with traffic sent or received by the particular UE, one or more latency thresholds associated with traffic sent or received by the particular UE, or one or more throughput thresholds associated with traffic sent or received by the particular UE (Fig. 1-2, [0060], users can run one or more than one application which can be mapped to different service categories (sCATs) as eMMB, mMTC, URLLC type as per the standards. Based on the applications' requirements, the 5G network manager allocates resource(s) or slices to UEs. For this, gNB periodically collects data requests from the connected UEs. Since UEs can be hosting various types of applications as explained above, different types of Quality of Services or Key Performance Indicator (KPI) requirements in terms of bandwidth, latency, and reliability, etc., can be mapped to the applications).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Panigrahi et al. with Wang et al. and Gordaychik by incorporating the features as taught by Panigrahi et al. in order to provide a more effective and efficient system that is capable of associating the set of QoS parameters with the particular service category of one or more latency thresholds associated with traffic sent or received by the particular UE. The motivation is to support an improved method for application-aware dynamic slicing in Radio Access Network (see [0002]).
Claim(s) 5, 12 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xing et al. (US 11,552,725 B2) in view of (Wang et al. (US 2022/0255875 A1) as applied to claims 1, 8 and 15 above, and further in view of Lee (US 2022/0232579 A1).
Panigrahi et al. and Wang et al. disclose the claimed limitations as des cribbed in paragraph 6 above. Panigrahi et al. and Wang et al. do not expressly disclose the following features: regarding claim 5, wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN; regarding claim 12, wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN; regarding claim 18, wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN.
Regarding claim 5, Lee teaches wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN (Fig. 2, [0038], estimator 207 may include logic that calculates values of parameters relating to performance metrics and/or other types of metrics based on the collected metric information, as described herein. The values may relate to latency, throughput, error rate, reliability, packet loss, guaranteed flow bit rate (GFBR), guaranteed bit rate (GBR), non-GBR, maximum/minimum bit rate, response time, channel quality indicator (CQI), signal-to-noise ratio (SNR), a QoS Class Identifier (QCI) (e.g., 5G, LTE, etc.), Access Point Name-Aggregate Maximum Bit Rate (APN-AMBR), a UE-AMBR, Reflective QoS Attribute (RQA), Packet Delay Budget, priority level, Maximum Data Burst Volume (MDBV), and/or another type of key performance indicator (KPI), Quality of Experience (QoE), QoS, SLA, and/or Mean Opinion Score (MOS)).
Regarding claim 12, Lee teaches wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN (Fig. 2, [0038], estimator 207 may include logic that calculates values of parameters relating to performance metrics and/or other types of metrics based on the collected metric information, as described herein. The values may relate to latency, throughput, error rate, reliability, packet loss, guaranteed flow bit rate (GFBR), guaranteed bit rate (GBR), non-GBR, maximum/minimum bit rate, response time, channel quality indicator (CQI), signal-to-noise ratio (SNR), a QoS Class Identifier (QCI) (e.g., 5G, LTE, etc.), Access Point Name-Aggregate Maximum Bit Rate (APN-AMBR), a UE-AMBR, Reflective QoS Attribute (RQA), Packet Delay Budget, priority level, Maximum Data Burst Volume (MDBV), and/or another type of key performance indicator (KPI), Quality of Experience (QoE), QoS, SLA, and/or Mean Opinion Score (MOS)).
Regarding claim 18, Lee teaches wherein the particular set of radio KPIs associated with a particular UE include at least one of: Signal-to-Interference-and-Noise-Ratio ("SINR") associated with wireless communications between the particular UE and the RAN, Received Signal Strength Indicator ("RSSI") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Power ("RSRP") values associated with wireless communications between the particular UE and the RAN, Reference Signal Received Quality ("RSRQ") values associated with wireless communications between the particular UE and the RAN, or Channel Quality Indicator ("CQI") values associated with wireless communications between the particular UE and the RAN (Fig. 2, [0038], estimator 207 may include logic that calculates values of parameters relating to performance metrics and/or other types of metrics based on the collected metric information, as described herein. The values may relate to latency, throughput, error rate, reliability, packet loss, guaranteed flow bit rate (GFBR), guaranteed bit rate (GBR), non-GBR, maximum/minimum bit rate, response time, channel quality indicator (CQI), signal-to-noise ratio (SNR), a QoS Class Identifier (QCI) (e.g., 5G, LTE, etc.), Access Point Name-Aggregate Maximum Bit Rate (APN-AMBR), a UE-AMBR, Reflective QoS Attribute (RQA), Packet Delay Budget, priority level, Maximum Data Burst Volume (MDBV), and/or another type of key performance indicator (KPI), Quality of Experience (QoE), QoS, SLA, and/or Mean Opinion Score (MOS)).
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Panigrahi et al. with Wang et al. by incorporating the features as taught by Lee in order to provide a more effective and efficient system that is capable of associating with a particular UE, of the plurality of UEs, include Channel Quality Indicator ("CQI") values associated with wireless communications between the UE and the RAN. The motivation is to support an improved method for end-to-end network slice management service (see [0013]).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SYED M BOKHARI/Examiner, Art Unit 2473 5/26/2026
/KWANG B YAO/Supervisory Patent Examiner, Art Unit 2473
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