DETAILED ACTION
This Action is in response to Applicant’s amendment filed on May 4, 2026. Claims 1-20 are still pending in the present application. This Action is made FINAL.
Information Disclosure Statements
The information disclosure statement submitted on May 01, 2026 has been considered by the Examiner and made of record in the application file.
Drawings
The replacement drawings sheets received on May 4, 2026 are accepted.
Claim Objections
Claim 17 is objected to because of the following informalities: The first comma in “select, a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS” is unnecessary. Appropriate correction is required.
Claim Rejections – 35 USC 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office Action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which
the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 8-9, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Wu (US 20230143942 A1) in view of Su et al. (US 20190281504 A1).
Consider claim 1, Wu discloses a method comprising:
sending the preferred configuration of the UE to a base station via a UE assistance information (UAI) framework (referring to Figure 1A, the “UE 102 includes processing hardware 150 in an example implementation includes a UE RRC controller 152 configured to manage RRC configurations, such as UE preferred configurations” (see paragraph 0057). It furthermore “transmits 532A a UE assistance information message including a first preferred configuration to the MN 104A” (see paragraph 0178) implying the use of a
transceiver in the UE));
receiving a new configuration of the UE from the base station after the base station determines the new configuration based on the preferred configuration (“In response to receiving the UE assistance information message, the SN 106A then generates 536A a second DU configuration in response to receiving the first preferred configuration…after generating the second DU configuration, the SN 106A sends 538A an RRC reconfiguration message including the second DU configuration to the MN 104A, which in turn transmits 540A the RRC reconfiguration message to the UE 102” (see Figure 5A, paragraphs 0180 and 0181)); and
configuring the UE according to the new configuration (“In response, the UE 102 can transmit 542A an RRC reconfiguration complete message to the MN 104A” (see paragraph 0181)).
However, Wu fails to disclose a method comprising estimating, by a user equipment (UE), based on side information about the UE, a power consumption and a quality of service (QoS) achievable by multiple candidate configurations of the UE; and selecting, by the UE, a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS.
In the same field of endeavor, Su et al. disclose a method comprising:
estimating, by a user equipment (UE), based on side information about the UE, a power
consumption and a quality of service (QoS) achievable by multiple candidate configurations of the UE (“Running the preferred BWP estimation algorithm may include the UE hypothesizing all possible UL and DL BWPs respectively and estimate the associated power consumption and QoS metrics”. These estimations may be based on “power for PDCCH monitoring; power for PDSCH reception; power for PUSCH transmission; power for PUCCH transmission; power for measurement; power for beam management; power of sleep” and “PDSCH/PUSCH bandwidth, code rate, scheduling interval, and/or various other parameters, for each possible BWP” for the power consumption and QoS, respectively (see paragraph 0134). In accordance with paragraph 0074 of Applicant’s specification, information regarding internal status of application and sensor measurements of the UE is equivalent to side information); and
selecting, by the UE, a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS (“The wireless device could then further select a possible bandwidth part configuration that has a lowest expected power consumption among the possible bandwidth part configurations that are expected to meet current QoS requirements of the wireless device as the preferred bandwidth part configuration” (see paragraph 0103)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Wu to inform the selection of a UE configuration with estimates of the power consumption and QoS as disclosed by Su et al. in order to select the optimal configuration with respect to energy efficiency and QoS.
Consider claim 8, and as applied to claim 1 above, Wu fails to disclose wherein the preferred configuration of the UE comprises at least one of: a preferred connected mode discontinuous reception (CDRX) configuration; a preferred maximum aggregated bandwidth; a preferred maximum number of component carriers; a preferred maximum number of multiple-input multiple-output (MIMO) layers; and a preferred scheduling offset for cross-slot scheduling.
In the same field of endeavor, Su et al. disclose wherein the preferred configuration of the UE comprises at least one of: a preferred connected mode discontinuous reception (CDRX) configuration; a preferred maximum aggregated bandwidth; a preferred maximum number of component carriers; a preferred maximum number of multiple-input multiple-output (MIMO) layers; and a preferred scheduling offset for cross-slot scheduling (“the bandwidth part configuration could encompass any of a variety of possible parameters…physical downlink shared channel (PDSCH) configuration (e.g., in the case of a DL BWP) and its associated parameters (e.g., maxNrofCodeWordsScheduledByDCI, maximum number of MIMO layers, etc.)” (see paragraph 0086)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Wu to incorporate the technique disclosed in Su et al. in order to include pertinent information when sending the preferred configuration to the BS.
Consider claim 9, Wu discloses a user equipment (UE) comprising a processor (see Figure 1, the processing hardware 150) and a transceiver operably connected to the processor, the transceiver configured to:
send the preferred configuration of the UE to a base station via a UE assistance information (UAI) framework (referring to Figure 1A, the “UE 102 includes processing hardware 150 in an example implementation includes a UE RRC controller 152 configured to manage RRC configurations, such as UE preferred configurations” (see paragraph 0057). It furthermore “transmits 532A a UE assistance information message including a first preferred configuration to the MN 104A” (see paragraph 0178) implying the use of a transceiver in the UE);
receive a new configuration of the UE from the base station after the base station determines the new configuration based on the preferred configuration “In response to receiving the UE assistance information message, the SN 106A then generates 536A a second DU configuration in response to receiving the first preferred configuration…after generating the second DU configuration, the SN 106A sends 538A an RRC reconfiguration message including the second DU configuration to the MN 104A, which in turn transmits 540A the RRC reconfiguration message to the UE 102” (see paragraphs 0180 and 0181) implying the use of a transceiver in the UE), and
wherein the processor is further configured to configure the UE according to the new configuration (“In response, the UE 102 can transmit 542A an RRC reconfiguration complete message to the MN 104A” (see paragraph 0181)).
However, Wu fails to disclose a processor configured to estimate, based on side information about the UE, a power consumption and a quality of service (QoS) achievable by multiple candidate configurations of the UE; and select a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS.
In the same field of endeavor, Su et al. disclose a processor configured to:
estimate, based on side information about the UE, a power consumption and a quality of service (QoS) achievable by multiple candidate configurations of the UE (“Running the preferred BWP estimation algorithm may include the UE hypothesizing all possible UL and DL BWPs respectively and estimate the associated power consumption and QoS metrics”. These estimations may be based on “power for PDCCH monitoring; power for PDSCH reception; power for PUSCH transmission; power for PUCCH transmission; power for measurement; power for beam management; power of sleep” and “PDSCH/PUSCH bandwidth, code rate, scheduling interval, and/or various other parameters, for each possible BWP” for the power consumption and QoS, respectively (see paragraph 0134). In accordance with paragraph 0074 of Applicant’s specification, information regarding internal status of application and sensor measurements of the UE is equivalent to side information); and
select a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS (“The wireless device could then further select a possible bandwidth part configuration that has a lowest expected power consumption among the possible bandwidth part configurations that are expected to meet current QoS requirements of the wireless device as the preferred bandwidth part configuration” (see paragraph 0103)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the UE disclosed by Wu to inform the selection of a UE configuration with estimates of the power consumption and QoS as disclosed by Su et al. in order to select the optimal configuration with respect to energy efficiency and
QoS.
Consider claim 16, and as applied to claim 9 above, Wu fails to disclose wherein the preferred configuration of the UE comprises at least one of: a preferred connected mode discontinuous reception (CDRX) configuration; a preferred maximum aggregated bandwidth; a preferred maximum number of component carriers; a preferred maximum number of multiple-
input multiple-output (MIMO) layers; and a preferred scheduling offset for cross-slot scheduling.
In the same field of endeavor, Su et al. disclose wherein the preferred configuration of the UE comprises at least one of: a preferred connected mode discontinuous reception (CDRX) configuration; a preferred maximum aggregated bandwidth; a preferred maximum number of component carriers; a preferred maximum number of multiple-input multiple-output (MIMO) layers; and a preferred scheduling offset for cross-slot scheduling (“the bandwidth part configuration could encompass any of a variety of possible parameters…physical downlink shared channel (PDSCH) configuration (e.g., in the case of a DL BWP) and its associated parameters (e.g., maxNrofCodeWordsScheduledByDCI, maximum number of MIMO layers, etc.)” (see paragraph 0086)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device disclosed by Wu to incorporate the technique disclosed in Su et al. in order to include pertinent information when sending the preferred configuration to the BS.
Consider claim 17, Wu discloses a non-transitory computer readable medium comprising program code (“UE 102 is equipped with processing hardware 150 that can include one or more general-purpose processors such as CPUs and non-transitory computer-readable
memory storing machine-readable instructions” (see paragraph 0057),
that, when executed by a processor of a device, causes the device to:
send the preferred configuration of the UE to a base station via a UE assistance information (UAI) framework (“the UE 102 transmits 532A a UE assistance information
message including a first preferred configuration to the MN 104A” (see paragraph 0178));
receive a new configuration of the UE from the base station after the base station determines the new configuration based on the preferred configuration (“In response to receiving the UE assistance information message, the SN 106A then generates 536A a second DU configuration in response to receiving the first preferred configuration…after generating the second DU configuration, the SN 106A sends 538A an RRC reconfiguration message including the second DU configuration to the MN 104A, which in turn transmits 540A the RRC reconfiguration message to the UE 102” (see paragraphs 0180 and 0181)); and
configure the UE according to the new configuration (“In response, the UE 102 can transmit 542A an RRC reconfiguration complete message to the MN 104A” (see paragraph 0181)).
However, Wu fails to disclose wherein the device is caused to estimate, based on side information about a user equipment (UE), a power consumption and a quality of service (QoS) achievable by multiple candidate configurations of the UE; and select a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS.
In the same field of endeavor, Su et al. disclose wherein the device is caused to estimate,
based on side information about a user equipment (UE), a power consumption and a quality of
service (QoS) achievable by multiple candidate configurations of the UE (“Running the preferred BWP estimation algorithm may include the UE hypothesizing all possible UL and DL BWPs respectively and estimate the associated power consumption and QoS metrics”. These estimations may be based on “power for PDCCH monitoring; power for PDSCH reception; power for PUSCH transmission; power for PUCCH transmission; power for measurement; power for beam management; power of sleep” and “PDSCH/PUSCH bandwidth, code rate, scheduling interval, and/or various other parameters, for each possible BWP” for the power consumption and QoS, respectively (see paragraph 0134). In accordance with paragraph 0074 of Applicant’s specification, information regarding internal status of application and sensor measurements of the UE is equivalent to side information); and
select a preferred configuration of the UE based on the estimation, wherein the preferred configuration of the UE is selected from the multiple candidate configurations in order to minimize power consumption of the UE while maintaining a satisfactory QoS (“The wireless device could then further select a possible bandwidth part configuration that has a lowest expected power consumption among the possible bandwidth part configurations that are expected to meet current QoS requirements of the wireless device as the preferred bandwidth part configuration” (see paragraph 0103)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu to inform the selection of a UE configuration with estimates of the power consumption and QoS as disclosed by Su et al. in order to select the optimal configuration
with respect to energy efficiency and QoS.
Claims 2, 10, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wu (US 20230143942 A1) in view of Su et al. (US 20190281504 A1), and further in view of
Mukherjee et al. (US 20140036748 A1).
Consider claim 2, and as applied to claim 1 above, Wu as modified by Su et al. fails to disclose a method further comprising determining whether the preferred configuration of the UE is different from a current configuration of the UE wherein the preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE.
In the same field of endeavor, Mukherjee et al. disclose a method further comprising determining whether the preferred configuration of the UE is different from a current configuration of the UE (see Figure 6, at block 602 “the UE determines if it wants to provide a UE DRX preference indication to the network or eNB to initiate a change in the DRX state of the UE” (see paragraph 0123)),
wherein the preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE (see Figure 6, at block 604 the DRX preference indication is sent to the network (see paragraph 0123)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Wu and modified by Su et al. to determine that the preferred configuration is distinct from the one already in use prior to sending it to the base station as disclosed by Mukherjee et al., in order to prevent sending redundant communications in the case that the preferred configuration is not
distinct.
Consider claim 10, and as applied to claim 9 above, Wu as modified by Su et al. fails to
disclose wherein: the processor is configured to determine whether the preferred configuration of the UE is different from a current configuration of the UE, and the preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE.
In the same field of endeavor, Mukherjee et al. disclose wherein: the processor is configured to determine whether the preferred configuration of the UE is different from a current configuration of the UE (see Figure 6, at block 602 “the UE determines if it wants to provide a UE DRX preference indication to the network or eNB to initiate a change in the DRX state of the UE” (see paragraph 0123)), and
the preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE (see Figure 6, at block 604 the DRX preference indication is sent to the network (see paragraph 0123)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the UE disclosed by Wu and modified by Su et al. to determine that the preferred configuration is distinct from the one already in use prior to sending it to the base station as disclosed by Mukherjee et al., in order to prevent sending redundant communications in the case that the preferred configuration is not distinct.
Consider claim 18, and as applied to claim 17 above, Wu as modified by Su et al. fails
to disclose wherein: the program code further causes the device to determine whether the
preferred configuration of the UE is different from a current configuration of the UE, and the
preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE.
In the same field of endeavor, Mukherjee et al. disclose wherein: the program code further causes the device to determine whether the preferred configuration of the UE is different from a current configuration of the UE (see Figure 6, at block 602 “the UE determines if it wants to provide a UE DRX preference indication to the network or eNB to initiate a change in the DRX state of the UE” (see paragraph 0123)), and
the preferred configuration of the UE is sent to the base station in response to a determination that the preferred configuration of the UE is different from the current configuration of the UE (see Figure 6, at block 604 the DRX preference indication is sent to the network (see paragraph 0123)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu and modified by Su et al. to determine that the preferred configuration is distinct from the one already in use prior to sending it to the base station as disclosed by Mukherjee et al., in order to prevent sending redundant communications in the case that the preferred configuration is not distinct.
Claims 3, 5-7, 11, 13-15, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wu (US 20230143942 A1) in view of Su et al. (US 20190281504 A1), further in view of Arora et al. (US 20200136975 A1), and further in view of Vankayala et al. (US 20220278728
A1).
Consider claim 3, and as applied to claim 1 above, Wu fails to disclose wherein the side information about the UE comprises at least one of: an identification of applications executing on the UE; a network traffic forecast determined using artificial intelligence; and a predicted
channel condition determined using artificial intelligence.
In the same field of endeavor, Su et al. disclose an identification of applications executing on the UE (“information available at the UE for determining the preferred BWP configuration could include any or all of the size of file to download/upload from/to the network; throughput requirements of active applications (voice call, music/video streaming, etc.)” (see paragraph 0133)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the method disclosed by Wu by incorporating the technique disclosed by Su et al. in order to account for the effect of applications on power usage.
However, Wu, as modified by Su et al., fails to disclose a network traffic forecast determined using artificial intelligence.
In the same field of endeavor, Arora et al. disclose a network traffic forecast determined using artificial intelligence (“The system applies two machine learning techniques that are used together. The first technique uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic at future times” (see paragraph 0003)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the method disclosed by Wu, as modified
by Su et al., by incorporating the technique disclosed by Arora et al. in order to better inform the
generated UE configuration.
However, Wu, as modified by Su et al. and Arora et al. fail to disclose a predicted channel condition determined using artificial intelligence.
In the same field of endeavor, Vankayala et al. disclose a predicted channel condition determined using artificial intelligence (“a method and a system for intelligently predicting a channel quality indicator (CQI), a pre-coding matrix index (PMI), and a rank index (RI) in a wireless communication network using machine learning” (see paragraph 0007)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the method disclosed by Wu, as modified
by Su et al. and Arora et al. by incorporating the technique disclosed by Vankayala et al. in order to better inform the generated UE configuration.
Consider claim 5, and as applied to claim 3 above, Wu, as modified by Su et al. and Arora et al., fails to disclose determining the predicted channel condition using a trained encoder-decoder based channel condition prediction network that receives time series channel quality history as an input.
In the same field of endeavor, Vankayala et al. disclose determining the predicted channel condition using a trained encoder-decoder based channel condition prediction network that receives time series channel quality history as an input (Figure 2 depicts a channel condition prediction network wherein “the UE may be controlled by the BS to periodically or aperiodically for measuring or monitoring the CQS information (such as the CQI, the PMI and the RI)” (see paragraph 0066). Subsequently, “one or more CQI reports, one or more PMI reports and one or more RI reports associated with at least one first frequency band are fed as input to the input layer (202) of the neural network (NN)” (see Figure 2, paragraph 0075). “The encoder/decoder (910) is configured to decode downlink information received from the BS (504) and send encoded information, for example the predicted CQI, PMI and RI of at least the second frequency band, to the BS (504)” (see Figures 5 and 9, paragraph 0126)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Wu. as modified by Su et al. and Arora et al. by incorporating the technique disclosed by Vankayala et al. in order to better inform the generated UE configuration by anticipating future UE operating conditions.
Consider claim 6, and as applied to claim 3 above, Wu in combination with Su et al., Arora et al., and Vankayala et al. discloses a method comprising determining a quality of service (QoS) metric of the UE based on the network traffic forecast and the predicted channel condition (in Su et al., “the wireless device could determine expected values for such [QoS] metrics for each respective bandwidth part being assessed based at least in part on one or more of… expected code rate for the respective bandwidth part configuration” (see paragraph 0104). Arora et al. and Vankayala et al. disclose a network traffic forecast and predicted channel condition, respectively).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize predicted network traffic and channel condition to forecast the QoS metric in the near future as disclosed by Su et al. in order to better inform the UE when determining the new configuration.
Consider claim 7, and as applied to claim 3 above, Wu in combination with Su et al.,
Arora et al., and Vankayala et al. discloses a method comprising estimating a power
consumption of the UE based on the network traffic forecast and the predicted channel condition (in Su et al., “the wireless device may determine the expected power consumption of the wireless device for a respective bandwidth part configuration by determining an estimated power consumption and an estimated operating duty cycle for the wireless device when using the respective bandwidth part configuration for each of physical downlink control channel monitoring, physical downlink shared channel reception, physical uplink shared channel transmission, physical uplink control channel transmission, measurement activities, beam management activities, and sleep activities” (see paragraph 0105). Interpretably, these values are dependent on the network traffic forecast and predicted channel condition determined when assessing the QoS of a given BWP. Arora et al. and Vankayala et al. disclose a network traffic forecast and predicted channel condition, respectively).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize predicted network traffic and channel condition to forecast the UE power consumption in the near future as disclosed by Su et al. in order to better inform the UE when determining the new configuration.
Consider claim 11, and as applied to claim 9 above, Wu fails to disclose wherein the side information about the UE comprises at least one of: an identification of applications executing on the UE; a network traffic forecast determined using artificial intelligence; and a predicted channel condition determined using artificial intelligence.
In the same field of endeavor, Su et al. disclose an identification of applications executing on the UE (“information available at the UE for determining the preferred BWP configuration could include any or all of the size of file to download/upload from/to the network; throughput requirements of active applications (voice call, music/video
streaming, etc.)” (see paragraph 0133)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device disclosed by Wu by incorporating the technique disclosed by Su et al. in order to account for the effect of applications on power usage.
However, Wu as modified by Su et al. fail to disclose a network traffic forecast
determined using artificial intelligence.
In the same field of endeavor, Arora et al. disclose a network traffic forecast determined using artificial intelligence (“The system applies two machine learning techniques that are used together. The first technique uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic at future times” (see paragraph 0003)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device disclosed by Wu as modified by Su et al. by incorporating the technique disclosed by Arora et al. in order to use an AI-predicted network forecast to better inform the generated UE configuration.
However, Wu as modified by Su et al. and Arora et al. fail to disclose a predicted channel condition determined using artificial intelligence.
In the same field of endeavor, Vankayala et al. disclose a predicted channel condition determined using artificial intelligence (“a method and a system for intelligently predicting a channel quality indicator (CQI), a pre-coding matrix index (PMI), and a rank index (RI) in a wireless communication network using machine learning” (see paragraph
0007)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device disclosed by Wu and modified by Su et al. and Arora et al. by incorporating the technique disclosed by Vankayala et al. in order
to use an AI-predicted channel condition to better inform the generated UE configuration.
Consider claim 13, and as applied to claim 11 above, Wu as modified by Su et al. and Arora fails to disclose wherein the processor is further configured to determine the predicted channel condition using a trained encoder-decoder based channel condition prediction network
that receives time series channel quality history as an input.
In the same field of endeavor, Vankayala et al. disclose determining the predicted channel condition using a trained encoder-decoder based channel condition prediction network that receives time series channel quality history as an input (Figure 2 depicts a channel condition prediction network wherein “the UE may be controlled by the BS to periodically or aperiodically for measuring or monitoring the CQS information (such as the CQI, the PMI and the RI)” (see paragraph 0066). Subsequently, “one or more CQI reports, one or more PMI reports and one or more RI reports associated with at least one first frequency band are fed as input to the input layer (202) of the neural network (NN)” (see Figure 2, paragraph 0075). “The encoder/decoder (910) is configured to decode downlink information received from the BS (504) and send encoded information, for example the predicted CQI, PMI and RI of at least the second frequency band, to the BS (504)” (see Figures 5 and 9, paragraph 0126)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the device disclosed by Wu as modified
by Su et al. and Arora by incorporating the technique disclosed by Vankayala et al. in order to
better inform the generated UE configuration by anticipating future UE operating conditions.
Consider claim 14, and as applied to claim 11 above, Su et al. in combination with Wu, Arora et al., and Vankayala et al. disclose wherein the processor is further configured to determine a quality of service (QoS) metric of the UE based on the network traffic forecast and the predicted channel condition (in Su et al., “the wireless device could determine expected values for such [QoS] metrics for each respective bandwidth part being assessed based at least in part on one or more of… expected radio channel conditions, expected code rate for the respective bandwidth part configuration” (see paragraph 0104). Arora et al. and Vankayala et al. disclose a network traffic forecast and predicted channel condition, respectively).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize predicted network traffic and channel condition to forecast the QoS metric in the near future as disclosed by Su et al. in order to better inform the UE when determining the new configuration.
Consider claim 15, and as applied to claim 11 above, Su et al. in combination with Wu, Arora et al., and Vankayala et al. disclose wherein the processor is further configured to estimate a power consumption of the UE based on the network traffic forecast and the predicted channel condition (in Su et al., “the wireless device may determine the expected power consumption of the wireless device for a respective bandwidth part configuration by determining an estimated power consumption and an estimated operating duty cycle for the wireless device when using the respective bandwidth part configuration for each of physical downlink control channel monitoring, physical downlink shared channel reception, physical uplink shared channel transmission, physical uplink control channel transmission, measurement activities, beam management activities, and sleep activities” (see paragraph 0105). Interpretably, these values are dependent on the network traffic forecast and predicted channel condition determined when assessing the QoS of a given BWP. Arora et al. and Vankayala et al.
disclose a network traffic forecast and predicted channel condition, respectively).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize predicted network traffic and channel condition to forecast the UE power consumption in the near future as disclosed by Su et al. in order to better inform the UE when determining the new configuration.
Consider claim 19, and as applied to claim 17 above, Wu fails to disclose a non-transitory computer readable medium wherein the side information about the UE comprises at least one of: an identification of applications executing on the UE; a network traffic forecast determined using artificial intelligence; and a predicted channel condition determined using artificial intelligence.
In the same field of endeavor, Su et al. disclose an identification of applications executing on the UE (“information available at the UE for determining the preferred BWP configuration could include any or all of the size of file to download/upload from/to the network; throughput requirements of active applications (voice call, music/video streaming, etc.)” (see paragraph 0133)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu by incorporating the technique disclosed by Su et al. in order to
account for the effect of applications on power usage.
However, Wu as modified by Su et al. fail to disclose a network traffic forecast
determined using artificial intelligence.
In the same field of endeavor, Arora et al. disclose a network traffic forecast determined using artificial intelligence (“The system applies two machine learning techniques that are used together. The first technique uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic
at future times” (see paragraph 0003)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu and modified by Su et al. by incorporating the technique disclosed by Arora et al. in order to use an AI-predicted network forecast to better inform the generated UE configuration.
However, Wu as modified by Su et al. and Arora et al. fail to disclose a predicted channel condition determined using artificial intelligence.
In the same field of endeavor, Vankayala et al. disclose a predicted channel condition determined using artificial intelligence (“a method and a system for intelligently predicting a channel quality indicator (CQI), a pre-coding matrix index (PMI), and a rank index (RI) in a wireless communication network using machine learning” (see paragraph 0007)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu and modified by Su et al. and Arora et al. by incorporating the technique disclosed by Vankayala et al. in order to use an AI-predicted channel condition to
better inform the generated UE configuration.
Claims 4, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wu (US 20230143942 A1) in view of Su et al. (US 20190281504 A1), further in view of Arora et al. (US 20200136975 A1), further in view of Vankayala et al. (US 20220278728 A1) and further in view of Gupta Hyde (US 20230188233 A1).
Consider claim 4, and as applied to claim 3 above, Wu as modified by Su et al., Arora et al., and Vankayala et al. partially discloses a method further comprising determining the network traffic forecast using a trained encoder-decoder based traffic forecast network that receives time series traffic history as an input (Arora et al. teach a technique that “uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic at future times” (see paragraph 0003)).
However, Wu as modified by Su et al., Arora et al., and Vankayala et al. fails to disclose wherein the trained model is based on an encoder-decoder format.
In the same field of endeavor, Gupta Hyde et al. disclose a device to improve wireless network energy efficiency wherein a machine learning model is based on an encoder-decoder format (“The neural network may be any kind of neural network, such as a convolutional neural network, an auto-encoder network” (see paragraph 0043)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Wu and modified by Su et al., Arora et al., and Vankayala et al. by incorporating the encoder-decoder format disclosed by Gupta Hyde et al. in order to use a neural network format best suited to
produce an accurate traffic forecast using the input data.
Consider claim 12, and as applied to claim 11 above, Wu as modified by Su et al.,
Arora et al., and Vankayala et al. partially discloses a device further comprising determining the network traffic forecast using a trained encoder-decoder based traffic forecast network that receives time series traffic history as an input (Arora et al. teach a technique that “uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic at future times” (see paragraph 0003)).
However, Wu as modified by Su et al., Arora et al., and Vankayala et al. fails to disclose wherein the trained model is based on an encoder-decoder format.
In the same field of endeavor, Gupta Hyde et al. disclose a device to improve wireless network energy efficiency wherein a machine learning model is based on an encoder-decoder format (“The neural network may be any kind of neural network, such as a convolutional neural network, an auto-encoder network” (see paragraph 0043)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device disclosed by Wu and modified by Su et al., Arora et al., and Vankayala et al. by incorporating the encoder-decoder format disclosed by Gupta Hyde et al. in order to use a neural network format best suited to produce an accurate traffic forecast using the input data.
Consider claim 20, and as applied to claim 19 above, Wu as modified by Su et al., Arora et al., and Vankayala et al. partially discloses a non-transitory computer readable medium further comprising determining the network traffic forecast using a trained encoder-decoder based traffic forecast network that receives time series traffic history as an input (Arora et al. teach a technique that “uses a traffic forecasting model, which has been trained using time series data indicating historical traffic data to predict expected levels of traffic at future times” (see paragraph 0003)).
However, Wu as modified by Su et al., Arora et al., and Vankayala et al. fails to disclose wherein the trained model is based on an encoder-decoder format.
In the same field of endeavor, Gupta Hyde et al. disclose a device to improve wireless
network energy efficiency wherein a machine learning model is based on an encoder-decoder format (“The neural network may be any kind of neural network, such as a convolutional neural network, an auto-encoder network” (see paragraph 0043)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the non-transitory computer readable medium disclosed by Wu and modified by Su et al., Arora et al., and Vankayala et al. by incorporating the encoder-decoder format disclosed by Gupta Hyde et al. in order to use a neural network format best suited to produce an accurate traffic forecast using the input data.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new grounds 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. Newly cited reference, Su et al., teach a device wherein the UE estimates, based on side information about the UE, power consumption and QoS achievable by multiple candidate configurations of the UE and selects a preferred configuration to minimize power consumption while maintaining a satisfactory QOS, rendering claims 1, 9, and 17 unpatentable under 35 U.S.C. § 103. Similarly, newly cited reference, Mukherjee et al., teach a device wherein it is determined whether the preferred configuration is distinct from the current configuration prior to sending the preferred configuration to the BS, rendering claims 2, 10, and 18 unpatentable under 35 U.S.C. § 103.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/ALEXANDER WU/Examiner, Art Unit 2642
/Rafael Pérez-Gutiérrez/Supervisory Patent Examiner, Art Unit 2642
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