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 .
Information Disclosure Statement
The Information Disclosure Statement filed on 02/16/2024 complies with 37 CFR 1.97. Therefore, the information referred therein has been considered.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-7, 10-18, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yang et al. (US 2021/0135963).
Regarding claim 1, Yang discloses a method of operating a user equipment, UE, in a wireless communications system, comprising: generating a prediction regarding a condition relating to overheating of the UE ([0026], “In FIG. 1B, assume that the first UE 104 is in an elevated temperature state 124 based on the first UE 104 detecting an elevated temperature (e.g., a temperature in a particular temperature range, such as a temperature range that satisfies the first temperature threshold and does not satisfy the second temperature threshold).”); and reporting the prediction to a network node of the wireless communications system ([0027], “As shown by reference number 126, the first UE 104 may send the thermal report to the network device 102.”).
Regarding claim 2, Yang discloses the method of Claim 1, further comprising: receiving a configuration from the network node for reporting the prediction regarding the condition relating to overheating ([0053], “The network device 102, upon receipt of the thermal report and as shown by reference number 148, may determine (e.g., via comparison of the high temperature with the first temperature threshold, the second temperature threshold, and/or the third temperature threshold) that the high temperature satisfies the second temperature threshold. Based on the high temperature satisfying the second temperature threshold, the network device 102 may select a second network action, as shown by reference number 150, from the plurality of network actions described above.”), wherein the prediction regarding the condition relating to overheating is generated according to the configuration ([0054], “As another example, the network device 102 may select the second network action from a ranked listing of the plurality of network actions. The network device 102 may generate the ranked listing based on a determination of potential impacts of the plurality of network actions on reducing temperature.”).
Regarding claim 3, Yang discloses the method of Claim 1, wherein the condition relating to overheating comprises a predicted temperature of the UE and/or a predicted duration of the overheating condition ([0052], “In FIG. 1C, assume that the first UE 104 is in a high temperature state 144, which indicates a high temperature (e.g., a temperature in a particular range, such as a temperature range that satisfies the second temperature threshold and does not satisfy the third temperature threshold). Similar to that described above, the first UE 104 may generate the thermal report by compiling information from a memory and/or one or more sensors (e.g., a temperature sensor, a voltmeter, and/or the like) of the first UE 104.”).
Regarding claim 4, Yang discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating is generated using a machine learning model ([0034], “In some implementations, the network device 102 may use one or more artificial intelligence techniques, such as machine learning, deep learning, and/or the like to select the first network action from the plurality of network actions to mitigate the elevated temperature.”).
Regarding claim 5, Yang discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating is generated based on a plurality of features relating to wireless communications by the UE ([0026], “In accordance with the configuration, the first UE 104 may generate a thermal report by compiling information from a memory and/or one or more sensors (e.g., a temperature sensor, a voltmeter, and/or the like). The thermal report may indicate the elevated temperature and/or satisfaction of the first temperature threshold.”).
Regarding claim 6, Yang discloses the method of Claim 5, wherein the plurality of features comprise at least one of a bandwidth allocated to the UE, a number of configured multiple input multiple output, MIMO, layers of the UE, a number of carriers assigned to the UE, a throughput of communications with the UE, a buffer size in the UE, and sensor information collected by the UE ([0026], “In accordance with the configuration, the first UE 104 may generate a thermal report by compiling information from a memory and/or one or more sensors (e.g., a temperature sensor, a voltmeter, and/or the like). The thermal report may indicate the elevated temperature and/or satisfaction of the first temperature threshold.”).
Regarding claim 7, Yang discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating comprises a time window within which the prediction regarding the condition relating to overheating is expected to occur ([0035], “historical data relating to results of taking the network actions (also referred to as result parameters) (e.g., whether the elevated temperatures were reduced, how much the elevated temperatures were reduced, at what rate the elevated temperatures were reduced, an amount of time to reduce the elevated temperatures to satisfy a temperature threshold or no longer satisfy a temperature threshold, and/or the like); and/or the like.”).
Regarding claim 10, Yang discloses the method of Claim 9, wherein the predetermined time period is configured by the network node ([0021], “The series of operations may include detecting that the network device 102 performed a network action, setting a timer, and after the timer satisfies a time threshold, determining that a temperature of the UE satisfies a temperature threshold.”).
Regarding claim 11, Yang discloses the method of Claim 9, wherein the predetermined time period is transmitted to the network node in a report that includes the prediction ([0099], “In some implementations, process 400 can further include setting a timer and obtaining the second thermal report from the user equipment after the timer satisfies a time threshold. In some implementations, process 400 can further include repeating, one or more times and based on the updated temperature of the user equipment satisfying the temperature threshold, the determining, the selecting, and the selectively performing until the updated temperature of the user equipment no longer satisfies the temperature threshold.”).
Regarding claim 12, Yang discloses the method of Claim 8, wherein the prediction is only reported to the network node ([0021], “For example, the configuration may indicate that that the UE is to send an updated thermal report to the network device 102 after the UE determines that further thermal mitigation is needed.”) if the confidence level is greater than a threshold level ([0040], “In some implementations, the output of the model may include a plurality of scores for a plurality of network actions. In this case, the network device 102 may select at least one of the plurality of network actions based on the plurality of scores. In some implementations, the network device 102 may select two or more network actions to perform and may determine an order for performing the two or more network actions based on their scores.”).
Regarding claim 13, Yang discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating ([0035], “In some implementations, the network device 102 may generate a model for use in thermal mitigation. For example, the network device 102 may train a model using historical data”) comprises a prediction of an onset of an overheating condition or a prediction of an end of an overheating condition ([0035], “historical data relating to results of taking the network actions (also referred to as result parameters) (e.g., whether the elevated temperatures were reduced, how much the elevated temperatures were reduced, at what rate the elevated temperatures were reduced, an amount of time to reduce the elevated temperatures to satisfy a temperature threshold or no longer satisfy a temperature threshold, and/or the like); and/or the like.”).
Regarding claim 14, Yang discloses the method of Claim 1, further comprising transmitting a recommended action for the network node to take to address the predicted condition relating to overheating ([0014], “To mitigate any potential harm caused by overheating, the network device 102 may communicate with the UE. For example, the network device 102 may determine a configuration for the UE.”).
Regarding claim 15, Yang discloses the method of Claim 14, wherein the recommended action comprises at least one of reducing a bandwidth allocated to the UE, reducing a number of configured MIMO layers of the UE, reducing a number of carriers assigned to the UE, and reducing a throughput of communications with the UE ([0030], “The network device 102 may order network actions within the ranked listing from network actions having the most potential impact on reducing temperature (e.g., listed at a top of the ranked listing) to network actions having the least potential impact on reducing temperature (e.g., listed at a bottom of the ranked listing). Differences in potential impact may be attributed to different types of the plurality of network actions (e.g., adjusting MIMO layers compared to de-configuring one or more NR SCGs) or different degrees of application of the plurality of network actions (e.g., reducing the number of CCs exponentially compared to reducing the number of CCs linearly).”).
Regarding claim 16, Yang discloses the method of Claim 14, further comprising generating and transmitting to the network node an estimate of an amount of time overheating condition is expected to continue after the recommended action is taken ([0021], “The UE may determine that further thermal mitigation is needed by performing a series of operations. The series of operations may include detecting that the network device 102 performed a network action, setting a timer, and after the timer satisfies a time threshold, determining that a temperature of the UE satisfies a temperature threshold.”).
Regarding claim 17, Yang discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating comprises a prediction of an end of an overheating condition ([0046], “In another example, the first amount of time may be selected by the network operator and/or the network device 102 (e.g., via machine learning, historical data analysis, and/or the like) to be a minimum amount of time to resolve the elevated temperature state 124 (e.g., reduce the elevated temperature to a temperature that does not satisfy the first temperature threshold).”), and wherein the prediction is included in a report that also includes a report of the onset of the overheating condition ([0048], “Assume that the elevated temperature of the first UE 104 has decreased to a normal temperature (e.g., a temperature in a particular temperature range, such as a temperature range that does not satisfy any of the first temperature threshold, the second temperature threshold, and the third temperature threshold), such that the first UE 104 is in a normal temperature state 138. Complying with the request from the network device 102, and in a manner similar to that described above in connection with reference number 126, the first UE 104 may generate and send the updated thermal report to the network device 102, as shown by reference number 140, via one or more packets on an uplink channel.”).
Regarding claim 18, Yang discloses the method of Claim 1, further comprising: generating a prediction of an expected time when the overheating condition will require network intervention ([0046], “In another example, the first amount of time may be selected by the network operator and/or the network device 102 (e.g., via machine learning, historical data analysis, and/or the like) to be a minimum amount of time to resolve the elevated temperature state 124 (e.g., reduce the elevated temperature to a temperature that does not satisfy the first temperature threshold).”); and transmitting the prediction of the expected time when the overheating condition will require network intervention to the network node ([0046], “In some implementations, for example when the configuration of the first UE 104 includes UE-based reporting, the first UE 104 may set the timer for the first amount of time after detecting that the network device 102 performed the first network action.”).
Regarding claim 20, Yang discloses the method of Claim 1, further comprising: receiving a conditional configuration from the network node ([0022], “For example, as shown respectively by reference numbers 112, 114, and 116, the network device 102 may send first configuration instructions to the first UE 104, second configuration instructions to the second UE 106, and nth configuration instructions to the nth UE 108. In some implementations, the first configuration instructions may be different from the second configuration instructions and/or the nth configuration instructions.”); and applying the conditional configuration in response to one of the following events: a predetermined overheating condition is reached ([0026], “In FIG. 1B, assume that the first UE 104 is in an elevated temperature state 124 based on the first UE 104 detecting an elevated temperature (e.g., a temperature in a particular temperature range, such as a temperature range that satisfies the first temperature threshold and does not satisfy the second temperature threshold). In accordance with the configuration, the first UE 104 may generate a thermal report by compiling information from a memory and/or one or more sensors (e.g., a temperature sensor, a voltmeter, and/or the like).”), a predicted overheating condition is reported, and a predetermined time period has elapsed following the time that the predetermined overheating condition is reached or that the predicted overheating condition was reported ([0026], “The thermal report may indicate the elevated temperature and/or satisfaction of the first temperature threshold. As described above, the thermal report may include additional content (e.g., specifying a type of the first UE 104, a type of wireless network connection used by the first UE 104, an operating mode of the first UE 104, a battery state of the first UE 104, a capability of the first UE 104, a location of the first UE 104, a thermal history of the first UE 104, and/or the like).”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 2021/0135963) in view of Cili et al. (US 2021/0382534).
Regarding claim 8, Yang does not disclose the confidence level associated with the prediction. Cili discloses the method of Claim 1, wherein the prediction regarding the condition relating to overheating comprises a confidence level associated with the prediction ([0076], “In some instances, the decision whether to perform thermal mitigation action, and/or the decision of which thermal mitigation action(s) to take, may further be based at least in part on the confidence level for the thermal status prediction.”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang in view of Cili to have the confidence level associated with the prediction. The motivation would have been to improve and maintain user experience and comfort (e.g., Cili [0063]).
Regarding claim 9, Yang does not disclose the time period. Cili discloses the method of Claim 8, wherein the confidence level comprises a percentage likelihood of the condition relating to overheating occurring within a predetermined time period ([0074], “For example, as one possibility, the thermal status prediction algorithm perform binary classification to classify the thermal pressure of the wireless device as normal thermal pressure (e.g., if device operating temperature is predicted to not extend beyond a desired operating range within a specified amount of time) or abnormal thermal pressure (e.g., if device operating temperature is predicted to extend beyond the desired operating range within the specified amount of time, absent thermal mitigation action).”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang in view of Cili to have the time period. The motivation would have been to improve and maintain user experience and comfort (e.g., Cili [0063]).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 2021/0135963) in view of Li et al. (US 2023/0262706).
Regarding claim 19, Yang does not disclose the prohibit timer. Li discloses the method of Claim 1, further comprising: determining the status of a prohibit timer before reporting the prediction to the network node; wherein the prediction is only reported to the network node after the prohibit timer has expired ([0058], “The base station may allow the UE to report the computation capability resource assistance information or forbid the UE from doing so by sending the control signaling. In order to forbid the terminal from frequently reporting the assistance information, a forbidding timer may be adopted, for example, the UE may be set to report after the forbidding timer does not run any more or to report when the forbidding timer overruns;”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang in view of Li to have the prohibit timer. The motivation would have been to reduce signaling overhead (e.g., Li [0036]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nick A Sundara whose telephone number is (571)272-6749. The examiner can normally be reached M-TH 7:30-5:30 EST.
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/NICK ANON SUNDARA/Examiner, Art Unit 2479 /JAE Y LEE/Supervisory Patent Examiner, Art Unit 2479