DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Introduction
The claims 1-19 are pending in this application. This is a non-final office action in response to Application Number 18/513,811 filed on 20 November 2023. The instant application is a CON of PCT/CN2022/092285 filed on 11 May 2022 and also claims foreign priority to Chinese Application 202110541055.3 filed on 18 May 2021. The applicant of record is Huawei Technologies Co., LTD. and the inventors of record are Qi Wang, Qi Yan, Ruituo Jiang, and Nanbin Wang.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 2 January 2025 and 4 June 2025 were filed after the filing date of the instant application on 20 November 2023 and before the mailing date of the first office action on the merits. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
The claims have been considered according to the latest Patent Eligibility Guidelines and are considered eligible.
Allowable Subject Matter
Claims 3-12 and 17 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.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 13-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (U.S. Patent Publication 2021/0120434) in view of Axmon et al. (U.S. Patent Publication 2019/0229817).
Regarding claim 1, Wang disclosed a method for determining a traffic statistics result, the method comprising:
obtaining a first data set, the first data set comprising a plurality of pieces of data collected within a first time period (see Wang Fig. 9 #1 collecting beam data that includes communication data and data for predicting traffic demand change events | [0107]: “There may be a plurality of beams for a 5G base station, each beam may provide wireless service to users independently, and data about service users of the beams will be used to cluster the beam clusters...” | [0108]: “In exemplary embodiments of the disclosure, before the at least one beam cluster is formed from beams of a base station, beam data of beams of the base station is collected. The base station or a server for energy saving performs beam data collection in real time, and stores the collected beam data in a database…”), each piece of data in the first data set comprises a traffic measurement value and level measurement values of n beams (examiner notes that applicant’s specification [0079] explains that throughput is an example of a traffic measurement and [0071] explains that RSRP (reference signal received power) is an example of a level measurement value; examiner also notes that “n beams” can be interpreted as one beam or multiple beams | see Wang [0107]: “…The service features include service distribution in time and in space (for example, statistics of beam number, time and the number of accessed users), service type (for example, statistics of beam number and users' moving speeds, or, statistics of beam number and a QoS Class Identifier (QCI) of signals, or, statistics of beam number and an uplink/downlink data ratio, etc.), and volume of the service traffic (for example, statistics of beam number, and throughput, Resource Block (RB) usage rate, or number of accessed users or time, etc.)…” | [0108]: “…Here, the beam data may at least include communication data. The communication data may include at least one of the following: user location information, current time information, service type information about a beam, service traffic information about a beam, service distribution information about a beam, synchronization signal period information about a beam, transmitting power information about a beam, signal quality information, beam number information. Here, the location information includes, but is not limited to, a geographical location. Taking the geographical location as an example, in addition to longitude and latitude information, the geographical location may be corresponding administrative area information, or a mapped index of a processed geographical location, or, the beam index id also corresponds to a small area…” | [0109]: “Specifically, the beam data may include wireless data from base stations or terminals, that is, conventional data in a communication system, which may also be referred to as communication data; these data belong to conventional wireless data and may be used as the most basic input. These basic wireless data include user location, time, service type of a beam, service distribution, service traffic of a beam, period of a synchronization signal of a beam, transmitting power, signal quality, beam number, etc. The measurement of service traffic (that is, the volume of services) may be the throughput of base station, the RB usage rate, the number of IP data packets, the number of accessed users, etc.; the service type may be classified according to the moving speed (for example, according to different levels of speed (30 km/h, 60 km/h, 120 km/h, etc.)), or according to the QCI (for example, video, voice, data, etc.), or according to the uplink/downlink data ratio (for example, Virtual Reality (VR)) services (uplink data is more than downlink data) and video watching services (downlink data is more than uplink data); or other classification methods.”), and the traffic measurement value comprises an uplink traffic measurement value and/or a downlink traffic measurement value (see Wang [0107]: “…The service features include…statistics of beam number and an uplink/downlink data ratio, etc.)…” | [0109]: “…the service type may be classified according to…the uplink/downlink data ratio (for example, Virtual Reality (VR)) services (uplink data is more than downlink data) and video watching services (downlink data is more than uplink data)…”);
determining, based on the level measurement values of the n beams of each piece of data and center coordinates of a first grid (see Axmon combination below regarding the claimed “center coordinates of a first grid”), a second data set associated with the first grid in the first data set (examiner notes that this limitation allows for a variety of interpretations that include determining historical measurements, measurements associated with a beam change, a redirected/reflected/interrupted beam, candidate beams, determining updated and/or additional measurements for the first set of measurements, etc. Additionally, this second data set does not necessarily include the same type of data as included in the first data set. Examiner recommends amending the claims to clarify the intended interpretation || see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station, the RB usage rate, the amount of IP data packet, and the number of accessed users. The service type refers to the classification of the service. The service may be classified according to moving speed, or according to the QCI classification, or according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”), the center coordinates of the first grid being represented by level values of n beams (Axmon combination below); and
determining, based on each traffic measurement value comprised in the each piece of data in the second data set, uplink traffic or downlink traffic corresponding to the first grid in the first time period (examiner notes that this limitation also allows for a variety of interpretations, e.g., using measurement data when: determining if traffic is UL or DL, classifying type of service traffic, determining the UL/DL traffic that corresponds to the beam, etc. Examiner recommends amending the claims to further clarify the desired interpretation | see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station, the RB usage rate, the amount of IP data packet, and the number of accessed users. The service type refers to the classification of the service. The service may be classified according to moving speed, or according to the QCI classification, or according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”).
Wang did not explicitly disclose using “center coordinates of a first grid” when determining a second data set and that “the center coordinates of the first grid being represented by level values of n beams”. Examiner also notes that “n beams” can be interpreted as a single beam.
However in a related art, Axmon disclosed a spherical coordinate system for making TRP measurements (see Axmon Fig. 1, [0032]) that are used to determine the total power transmitted by an antenna when connected to an active transmitter (see Axmon [0031]). Figures 5A-5D illustrate four kinds of reference measurement sampling grids used to perform over-the-air measurements (see Axmon [0036]). The grid density may be relaxed when sampling points are further away from the center (see Axmon [0047]) and a low density sampling grid’s coverage is defined based on a circle of a constant radius with the beam peak as the center point (see Axmon [0097]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Wang and Axmon to further describe how beam spaces are arranged and the role of beam measurements in the arrangement of the beam speace. Incorporating Axmon’s teachings would enable TRP measurements to be executed more quickly leading to cost savings and increased capacity of constrained resources (see Axmon [0008]), as well as increased accuracy of TRP measurements (see Axmon [0033]) and reduced test time (see Axmon [0044]).
Regarding claim 2, Wang-Axmon disclosed the method according to claim 1, further comprising: obtaining center coordinates and a radius that correspond to each grid of a plurality of grids in n-dimensional beam space, the plurality of grids comprising the first grid (Axmon disclosed a spherical coordinate system for making TRP measurements (see Axmon Fig. 1, [0032]) that are used to determine the total power transmitted by an antenna when connected to an active transmitter (see Axmon [0031]). Figures 5A-5D illustrate four kinds of reference measurement sampling grids used to perform over-the-air measurements (see Axmon [0036]). The grid density may be relaxed when sampling points are further away from the center (see Axmon [0047]) and a low density sampling grid’s coverage is defined based on a circle of a constant radius with the beam peak as the center point (see Axmon [0097]).).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Wang and Axmon to further describe how beam spaces are arranged and the role of beam measurements in the arrangement of the beam speace. Incorporating Axmon’s teachings would enable TRP measurements to be executed more quickly leading to cost savings and increased capacity of constrained resources (see Axmon [0008]), as well as increased accuracy of TRP measurements (see Axmon [0033]) and reduced test time (see Axmon [0044]).
Regarding claim 13, Wang-Axmon disclosed the method according to claim 1, wherein the uplink traffic corresponding to the first grid in the first time period is determined based on data that is in the second data set and that comprises an uplink traffic measurement value (see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station…The service type refers to the classification of the service. The service may be classified…according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”); and
the downlink traffic corresponding to the first grid in the first time period is determined based on data that is in the second data set and that comprises a downlink traffic measurement value (see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station…The service type refers to the classification of the service. The service may be classified…according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”).
Regarding claim 14, Wang-Axmon disclosed the method according to claim 1, further comprising: sending the uplink traffic or the downlink traffic corresponding to the first grid in the first time period to a server (see Wang [0108]: server collects beam data | [0165]: data is transmitted to server | [0265]: server performs beam configuration).
Regarding claim 15, the claim contains the limitations, substantially as claimed, as described in claim 1 above. Examiner notes that claim 1 describes a method whereas claim 15 describes an apparatus. Wang disclosed, as recited in claim 15: An apparatus, comprising:
an interface circuit, the interface circuit (see Wang Fig. 20 #1020 transceiver) is configured to:
receive a signal from a communication apparatus other than the apparatus (see Wang [0072]: base station and terminal are in communication with each other in uplink and downlink directions); and
transmit the signal to the processor, or send a signal from the processor to a communication apparatus other than the communication apparatus (see Wang [0072]: base station and terminal are in communication with each other in uplink and downlink directions); and
a processor in communication with the interface signal (see Wang Fig. 20 #1010 processor in communication with #1020 transceiver), the processor is configured to:
obtain a first data set, the first data set comprising a plurality of pieces of data collected within a first time period (see Wang Fig. 9 #1 collecting beam data that includes communication data and data for predicting traffic demand change events | [0107]: “There may be a plurality of beams for a 5G base station, each beam may provide wireless service to users independently, and data about service users of the beams will be used to cluster the beam clusters...” | [0108]: “In exemplary embodiments of the disclosure, before the at least one beam cluster is formed from beams of a base station, beam data of beams of the base station is collected. The base station or a server for energy saving performs beam data collection in real time, and stores the collected beam data in a database…”), each piece of data in the first data set comprises a traffic measurement value and level measurement values of n beams (examiner notes that applicant’s specification [0079] explains that throughput is an example of a traffic measurement and [0071] explains that RSRP (reference signal received power) is an example of a level measurement value; examiner also notes that “n beams” can be interpreted as one beam or multiple beams | see Wang [0107]: “…The service features include service distribution in time and in space (for example, statistics of beam number, time and the number of accessed users), service type (for example, statistics of beam number and users' moving speeds, or, statistics of beam number and a QoS Class Identifier (QCI) of signals, or, statistics of beam number and an uplink/downlink data ratio, etc.), and volume of the service traffic (for example, statistics of beam number, and throughput, Resource Block (RB) usage rate, or number of accessed users or time, etc.)…” | [0108]: “…Here, the beam data may at least include communication data. The communication data may include at least one of the following: user location information, current time information, service type information about a beam, service traffic information about a beam, service distribution information about a beam, synchronization signal period information about a beam, transmitting power information about a beam, signal quality information, beam number information. Here, the location information includes, but is not limited to, a geographical location. Taking the geographical location as an example, in addition to longitude and latitude information, the geographical location may be corresponding administrative area information, or a mapped index of a processed geographical location, or, the beam index id also corresponds to a small area…” | [0109]: “Specifically, the beam data may include wireless data from base stations or terminals, that is, conventional data in a communication system, which may also be referred to as communication data; these data belong to conventional wireless data and may be used as the most basic input. These basic wireless data include user location, time, service type of a beam, service distribution, service traffic of a beam, period of a synchronization signal of a beam, transmitting power, signal quality, beam number, etc. The measurement of service traffic (that is, the volume of services) may be the throughput of base station, the RB usage rate, the number of IP data packets, the number of accessed users, etc.; the service type may be classified according to the moving speed (for example, according to different levels of speed (30 km/h, 60 km/h, 120 km/h, etc.)), or according to the QCI (for example, video, voice, data, etc.), or according to the uplink/downlink data ratio (for example, Virtual Reality (VR)) services (uplink data is more than downlink data) and video watching services (downlink data is more than uplink data); or other classification methods.”), and the traffic measurement value comprises an uplink traffic measurement value and/or a downlink traffic measurement value (see Wang [0107]: “…The service features include…statistics of beam number and an uplink/downlink data ratio, etc.)…” | [0109]: “…the service type may be classified according to…the uplink/downlink data ratio (for example, Virtual Reality (VR)) services (uplink data is more than downlink data) and video watching services (downlink data is more than uplink data)…”);
determine, based on the level measurement values of the n beams of each piece of data and center coordinates of a first grid (see Axmon combination below regarding the claimed “center coordinates of a first grid”), a second data set associated with the first grid in the first data set (examiner notes that this limitation allows for a variety of interpretations that include determining historical measurements, measurements associated with a beam change, a redirected/reflected/interrupted beam, candidate beams, determining updated and/or additional measurements for the first set of measurements, etc. Additionally, this second data set does not necessarily include the same type of data as included in the first data set. Examiner recommends amending the claims to clarify the intended interpretation || see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station, the RB usage rate, the amount of IP data packet, and the number of accessed users. The service type refers to the classification of the service. The service may be classified according to moving speed, or according to the QCI classification, or according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”), the center coordinates of the first grid being represented by level values of n beams (Axmon combination below); and
determine, based on each traffic measurement value comprised in the each piece of data in the second data set, uplink traffic or downlink traffic corresponding to the first grid in the first time period (examiner notes that this limitation also allows for a variety of interpretations, e.g., using measurement data when: determining if traffic is UL or DL, classifying type of service traffic, determining the UL/DL traffic that corresponds to the beam, etc. Examiner recommends amending the claims to further clarify the desired interpretation | see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station, the RB usage rate, the amount of IP data packet, and the number of accessed users. The service type refers to the classification of the service. The service may be classified according to moving speed, or according to the QCI classification, or according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”).
Wang did not explicitly disclose using “center coordinates of a first grid” when determining a second data set and that “the center coordinates of the first grid being represented by level values of n beams”. Examiner also notes that “n beams” can be interpreted as a single beam.
However in a related art, Axmon disclosed a spherical coordinate system for making TRP measurements (see Axmon Fig. 1, [0032]) that are used to determine the total power transmitted by an antenna when connected to an active transmitter (see Axmon [0031]). Figures 5A-5D illustrate four kinds of reference measurement sampling grids used to perform over-the-air measurements (see Axmon [0036]). The grid density may be relaxed when sampling points are further away from the center (see Axmon [0047]) and a low density sampling grid’s coverage is defined based on a circle of a constant radius with the beam peak as the center point (see Axmon [0097]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Wang and Axmon to further describe how beam spaces are arranged and the role of beam measurements in the arrangement of the beam speace. Incorporating Axmon’s teachings would enable TRP measurements to be executed more quickly leading to cost savings and increased capacity of constrained resources (see Axmon [0008]), as well as increased accuracy of TRP measurements (see Axmon [0033]) and reduced test time (see Axmon [0044]).
Regarding claim 16, the claim contains the limitations, substantially as claimed, as described in claim 2 above. Wang-Axmon disclosed, as recited in claim 16: The apparatus according to claim 15, the processor is further configured to: obtain center coordinates and a radius that correspond to each grid of a plurality of grids in n- dimensional beam space, the plurality of grids comprising the first grid (Axmon disclosed a spherical coordinate system for making TRP measurements (see Axmon Fig. 1, [0032]) that are used to determine the total power transmitted by an antenna when connected to an active transmitter (see Axmon [0031]). Figures 5A-5D illustrate four kinds of reference measurement sampling grids used to perform over-the-air measurements (see Axmon [0036]). The grid density may be relaxed when sampling points are further away from the center (see Axmon [0047]) and a low density sampling grid’s coverage is defined based on a circle of a constant radius with the beam peak as the center point (see Axmon [0097]).).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Wang and Axmon to further describe how beam spaces are arranged and the role of beam measurements in the arrangement of the beam speace. Incorporating Axmon’s teachings would enable TRP measurements to be executed more quickly leading to cost savings and increased capacity of constrained resources (see Axmon [0008]), as well as increased accuracy of TRP measurements (see Axmon [0033]) and reduced test time (see Axmon [0044]).
Regarding claim 18, the claim contains the limitations, substantially as claimed, as described in claim 13 above. Wang-Axmon disclosed, as recited in claim 18: The apparatus according to claim 15, wherein the uplink traffic corresponding to the first grid in the first time period is determined based on data that is in the second data set and that comprises an uplink traffic measurement value (see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station…The service type refers to the classification of the service. The service may be classified…according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”); and
the downlink traffic corresponding to the first grid in the first time period is determined based on data that is in the second data set and that comprises a downlink traffic measurement value (see Wang [0111]: “Specifically, the service features of each beam may be extracted in historical data of each beam in the database (for example, data in some previous days, such as X days), and at least one of service traffic, service type, service distribution, etc. of each beam is obtained. Here, the service traffic refers to time sequence data, and the specific measurement indicator may be at least one of the throughput of base station…The service type refers to the classification of the service. The service may be classified…according to the uplink/downlink data ratio, or according to other classification methods. The service distribution refers to service distribution in space, that is, statistics between beam number (or geographical location information about beams) and at least one of the number of accessed users, the RB usage rate, the QCI, the users' moving speeds, and a channel quality, etc.”).
Regarding claim 19, the claim contains the limitations, substantially as claimed, as described in claim 14 above. Wang-Axmon disclosed, as recited in claim 19: The apparatus according to claim 15, the processor is further configured to: send the uplink traffic or the downlink traffic corresponding to the first grid in the first time period to a server (see Wang [0108]: server collects beam data | [0165]: data is transmitted to server | [0265]: server performs beam configuration).
Conclusion
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/ANGELA WIDHALM DE RODRIGUEZ/Examiner, Art Unit 2443
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