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 .
This action is in response to the applicant’s communication filed on 06/29/2026
Claims 1-20 are pending
Claim Objections
Claim 12 objected to because of the following informalities: the recitation “dedicated energy harvesting techniques comprising as solar energy, vibration energy, and/or wireless power transfer” is grammatically incorrect due to the phrase “comprising as”. Appropriate correction is required.
Response to Arguments
Applicant’s arguments, see page 8, filed 6/29/2026, with respect to 101 rejections have been fully considered and are persuasive. The 101 rejections of claims 3 and 4 have been withdrawn.
Applicant’s arguments filed 6/29/2026 with respect to the 103 rejections have been fully considered, but they are not persuasive. Applicant’s arguments on pages 11-12, applicant argues “that neither Höglund nor Lu nor their combination teach, suggest or fairly disclose the unique combination of features of claim 1 as amended including and without limitation the features of using an algorithm to predict the energy level of a WD, wherein the predicting is based no received parameters and, based on determining that the predicted energy level of the WD is insufficient for a network node of a communication network to communicate with the WD”. Examiner respectfully disagrees because Höglund teaches receiving, from the WD, energy harvesting parameters including “energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting” (Par. [0081]). Lu further teaches predicting future energy availability, including “real-time prediction of future harvested energy” (Page 2), and teaches determining whether sufficient energy is available based on the predicted harvested energy (Page 5, “In this step, we need to check at run-time the energy availability and adjust the scheduling. If the available energy is not enough for a task's scheduling/DVFS, we must make adjustments to deal with the energy shortage”; Page 5, equation 18, “where ES(stm) is the remaining energy in the ESU at time stm; EH(stm,ftm) is the predicted harvested energy between stm and ftm using one of the prediction methods in section IV, and ED(stm,ftm) is the effective energy dissipation of tm”; Page 6, “The adaptive adjustment method in Algorithm 3 makes sure that the system has sufficient energy to execute the task based on the computation of effective energy dissipation and the prediction on future harvested energy”). Accordingly, Applicant’s argument does not overcome the rejection.
Applicant’s arguments on pages 12-13, Applicant further argues “Both Höglund and Lu are silent on assisting the WD to harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD” and “neither Vannithamby nor Elshafie nor Muhammad nor their combination cure these deficiencies of Höglund in view of Lu”. Examiner respectfully disagrees because Elshafie teaches (Par. [0044], “a first device (e.g., a UE, a base station, any sidelink enabled device) may be configured to perform energy harvesting by converting received radio frequency power associated with wireless signals received from a second device (e.g., a UE, a base station, any sidelink enabled device) to DC power”; Par. [0044], “the second device may transmit signals with a determined radio frequency power to the first device”; Par. [0045], “Based on receiving the signaling indicating the one or more parameters, the second device may adjust a radio frequency power of signals transmitted to the first wireless device. For example, the second device may adjust the radio frequency power of signals transmitted to the first wireless device to increase an efficiency of the energy harvesting performed by the first device”). Accordingly, Applicant’s argument does not overcome the rejection.
Applicant’s arguments on page 13, Applicant further argues that “Claim 15 has been amended in a manner similar to claim 1, but from the wireless device (WD) perspective” and incorporates the arguments presented with respect to claim 1. Examiner respectfully disagrees because claim 15 is rejected for substantially the same reasons as discussed above with respect to claim 1.
Applicant’s arguments on page 13, Applicant further argues that “claims 2-14 depend from and include all of the features of independent claim 1” and “similarly, claims 16-20 depend from and include all of the features of independent claim 15”. Applicant does not present separate arguments directed to the additional limitations of claims 2-14 and 16-20. Accordingly, the rejections of claims 2-14 and 16-20 are maintained.
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.
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.
Claim(s) 1, 3-6, 9-10, 13-15, 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Höglund et al. USPGPUB 2024/0292335 A1 (hereinafter Höglund) in view of Lu et al. (Accurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded Systems, 2010) (hereinafter Lu), and further in view of Elshafie et al. USPGPUB 2022/0385109 A1 (hereinafter Elshafie).
Regarding claim 1, Höglund teaches a method, performed in a network node of a communication network (Par. [0016] “a method implemented in a core node for communication with a wireless device and a network node is provided”), enabling a prediction of an energy level of an energy harvesting wireless device (WD) (Par. [0080] - [0081] “Core node 15 is configured to receive (Block S134) indication that a wireless device uses energy harvesting … the indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting” – such parameters characterize the current and expected energy availability of the wireless device and therefore enable the network node to determine device operation based on the device’s available energy.) the method comprising:
receiving, from the WD, control signaling comprising information assisting the network node (Par. [0112] “To support the entering of this state at network node 16 side, some additional information (as specified in one or more of the examples and/or tables above) related to energy harvesting could be used as and/or as part of assistance information, e.g., that wireless device 22 reports to network node 16”; Par. [0113] “triggering by any activity from wireless device 22, e.g., mobile originated transmission in the uplink, either transmission of user-plane data or control signaling (RAU/TAU, etc.).”),
receiving, from the WD, control signaling comprising parameters for use in predicting the energy level of the WD, wherein the parameters comprise energy harvesting properties and parameters associated with current use of the WD (Par. [0081] “indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting.”);
Höglund does not explicitly teach an algorithm to predict the energy level of the energy harvesting wireless device;
predicting, using the algorithm, the energy level of the WD, wherein the predicting is based on the received parameters required by the algorithm for predicting the energy level of the WD;
based on determining that the predicted energy level of the WD is insufficient for communicating with the WD:
assisting the WD to harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD.
However, Lu teaches an algorithm to predict the energy level of the energy harvesting wireless device (Page 2, “real-time prediction of future harvested energy … the harvested energy is the most important part that determines the energy availability in an EH-RTES.; Page 8, “proposed the concept of effective energy dissipation that define a unique quantity to accurately quantify the energy dissipation of the system. It includes not only the energy demand by the electronic circuit, but also the energy overhead incurred by energy flowing among different system components. We also addressed the need in run-time prediction of future harvested energy. These two contributions significantly improve the accuracy of energy availability computation for the proposed Model Accurate Predictive DVFS algorithm);
predicting, using the algorithm, the energy level of the WD, wherein the predicting is based on the received parameters required by the algorithm for predicting the energy level of the WD (Page 2, “In this paper, we consider a typical EH-RTES that consists of three major modules: energy harvesting module (EHM), energy storage module (ESM) and energy dissipation module (EDM)”; Table 1, Page 3, key parameters to the system include “Output voltage and current of the EHM, Output voltage and current of the ESM, Supply voltage and current of the EDM, Output voltage, current and conversion efficiency of ECM1, Input voltage, current and conversion efficiency of ECM2, Total capacity and charge/discharge efficiency of the ESM, Harvested energy from EHM, remaining energy in ESU, and the effective energy dissipation” – these parameters are used to predict effective energy dissipation which, when combined with the prediction on future harvested energy, Page. 8, “significantly improves the accuracy of energy availability computation for the proposed Model-Accurate Predictive DVFS algorithm”); and
based on determining that the predicted energy level of the WD is insufficient for communicating with the WD (Page 5, - equation 18 compares the remaining energy + predicted harvested energy to the effective energy dissipation of a task to determine if energy level is sufficient for a task; Page 6, “adaptive adjustment method in Algorithm 3 makes sure that the system has sufficient energy to execute the task based on the computation of effective energy dissipation and the prediction on future harvested energy”; Page 8, “These two contributions significantly improve the accuracy of energy availability computation for the proposed Model Accurate Predictive DVFS algorithm” – communication is a system task requiring energy resources).
Höglund and Lu are analogous art because they are from the same field of endeavor. They both relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, and incorporate predicting energy availability and determining whether sufficient energy is available based ont eh predicted harvested energy, as taught by Lu.
One of ordinary skill in the art would have been motivated to improve “achieving best system performance under energy harvesting constraints” as suggested by Lu (Page 1).
Höglund and Lu do not explicitly teach assisting the WD to harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD.
However, Elshafie teaches assisting the WD to harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD (Par. [0044], “a first device (e.g., a UE, a base station, any sidelink enabled device) may be configured to perform energy harvesting by converting received radio frequency power associated with wireless signals received from a second device (e.g., a UE, a base station, any sidelink enabled device) to DC power”; Par. [0044], “Par. [0044], “the second device may transmit signals with a determined radio frequency power to the first device”; Par. [0045], “Based on receiving the signaling indicating the one or more parameters, the second device may adjust a radio frequency power of signals transmitted to the first wireless device. For example, the second device may adjust the radio frequency power of signals transmitted to the first wireless device to increase an efficiency of the energy harvesting performed by the first device”).
Höglund, Lu, and Elshafie are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device and predicts energy availability, as taught by Höglund and Lu, and incorporate assisting the wireless device to harvest energy by transmitting radio frequency power to the wireless device, as taught by Elshafie.
One of ordinary skill in the art would have been motivated to improve the efficiency of energy harvesting performed by the wireless device, as suggested by Elshafie (Par. [0045]).
Regarding claim 3, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
predicting, by the network node using the algorithm, the energy level of the WD, wherein the predicting is based on parameters required by the algorithm for predicting the energy level of the WD (Page 2, “In this paper, we consider a typical EH-RTES that consists of three major modules: energy harvesting module (EHM), energy storage module (ESM) and energy dissipation module (EDM)”; Table 1, Page 3, key parameters to the system include “Output voltage and current of the EHM, Output voltage and current of the ESM, Supply voltage and current of the EDM, Output voltage, current and conversion efficiency of ECM1, Input voltage, current and conversion efficiency of ECM2, Total capacity and charge/discharge efficiency of the ESM, Harvested energy from EHM, remaining energy in ESU, and the effective energy dissipation” – these parameters are used to predict effective energy dissipation which, when combined with the prediction on future harvested energy, Page. 8, “significantly improves the accuracy of energy availability computation for the proposed Model-Accurate Predictive DVFS algorithm”).
Regarding claim 4, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
determining, by the network node, based on the predicted energy level of the WD, whether the energy level of the WD is sufficient for communicating with the WD (Page 5, - equation 18 compares the remaining energy + predicted harvested energy to the effective energy dissipation of a task to determine if energy level is sufficient for a task; Page 6, “adaptive adjustment method in Algorithm 3 makes sure that the system has sufficient energy to execute the task based on the computation of effective energy dissipation and the prediction on future harvested energy”; Page 8, “These two contributions significantly improve the accuracy of energy availability computation for the proposed Model Accurate Predictive DVFS algorithm” – communication is a system task requiring energy resources.).
Regarding claim 5, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
upon determining that the energy level of the WD is sufficient (Page. 6, “adaptive adjustment method in Algorithm 3 makes sure that the system has sufficient energy to execute the task based on the computation of effective energy dissipation and the prediction on future harvested energy”), scheduling communication with the WD based on the predicted energy level (Page 6, Algorithm 3: Overall MAP-DVFS Algorithm table, “get initial schedule for tasks in Q using Algorithm 1, balance workload using Algorithm 2, adjust scheduling using Algorithm 3”– because communication operations performed by a wireless device are system tasks that consume energy resources, scheduling tasks based on predicted energy availability would include scheduling communication tasks when sufficient energy is available.).
Regarding claim 6, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises upon determining that the energy level of the WD is insufficient, performing at least one of:
refraining from scheduling communication with the WD for a time period while preserving a UE context for the WD (Page 5, “If the scheduling/DVFS from Step 2 is invalidated by energy shortage, the task should not be removed from Q right away. Instead, we are going to first try to delay the task execution” – delaying task execution corresponds to refraining from scheduling communication until sufficient energy is available),
setting the WD in a power limited sub-state in which the WD is harvesting energy and unavailable for communications while the UE context for the WD is preserved, and
assisting the WD to harvest energy from a dedicated radio frequency by performing a wireless power transfer.
Regarding claim 7, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Elshafie further teaches wherein the method comprises:
transmitting, to the WD, a message configuring the WD to harvest energy (Par. [0161] “communications manager 920 may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or otherwise in cooperation with the receiver 910, the transmitter 915, or both “; Par. [0167] “The receiver 1010 may provide a means for receiving information such as packets, user data, control information, or any combination thereof associated with various information channels (e.g., control channels, data channels, information channels related to signaling for energy harvesting at a device).”).
Regarding claim 9, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
Receiving, from the WD, control signaling comprising training data for updating the algorithm for predicting the energy level of the WD (Page 2, “exponentially Weighted Moving-Average (EWMA) model was designed to predict solar energy based on weighted current time-slot energy and historical average”; Page 4, “moving average uses the N past observation data to calculate the next prediction time series value”; Page 4, “The exponential smoothing approach [21] is widely used for short-time forecasting. Although it also employs weighting factors for past values, the weighting factors decay exponentially with the distance of the past values of the time series from the present time.”– Moving average models and exponential smoothing both estimate future harvested energy based on historical observation data. Because these algorithms compute updated predictions using previously observed energy measurements and incorporate new observations as they become available, the historical observations function as training data used to update the prediction algorithm.).
Regarding claim 10, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
updating the algorithm for predicting the energy level of the WD based on the training data (Page 2, “exponentially Weighted Moving-Average (EWMA) model was designed to predict solar energy based on weighted current time-slot energy and historical average”; Page 4, “moving average uses the N past observation data to calculate the next prediction time series value”; Page 4, “The exponential smoothing approach [21] is widely used for short-time forecasting. Although it also employs weighting factors for past values, the weighting factors decay exponentially with the distance of the past values of the time series from the present time.”– Moving average models and exponential smoothing both estimate future harvested energy based on historical observation data. Because these algorithms incorporate newly observed energy measurements when computing subsequent predictions, the prediction model is updated based on the historical observation data used as training data.).
Regarding claim 13, the combination of Höglund, Lu, Elshafie teaches all the limitations of the base claims as outlined above.
Höglund further teaches wherein the parameters associated with the current use are indicative of one or more of an energy consumption, environmental conditions, location, traffic behavior, and current ability to harvest energy of the WD (Par. [0081] “the indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting”).
Regarding claim 14, the combination of Höglund, Lu, Elshafie teaches all the limitations of the base claims as outlined above.
Höglund further teaches wherein the parameters associated with the current use are indicative the WD's ability to harvest energy during current use. (Par. [0081] “the indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting”).
Regarding claim 15, Höglund teaches a method, performed in an energy harvesting wireless device, (WD) of a communication network (Par. [0016] “a method implemented in a core node for communication with a wireless device and a network node is provided”), enabling a prediction of an energy level of the energy harvesting wireless device, (WD) by a network node (Par. [0080] - [0081] “Core node 15 is configured to receive (Block S134) indication that a wireless device uses energy harvesting … the indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting” – such parameters characterize the current and expected energy availability of the wireless device and therefore enable the network node to determine device operation based on the device’s available energy.), the method comprising:
transmitting, to the network node, control signaling comprising information assisting the network node (Par. [0112] “To support the entering of this state at network node 16 side, some additional information (as specified in one or more of the examples and/or tables above) related to energy harvesting could be used as and/or as part of assistance information, e.g., that wireless device 22 reports to network node 16”; Par. [0113] “triggering by any activity from wireless device 22, e.g., mobile originated transmission in the uplink, either transmission of user-plane data or control signaling (RAU/TAU, etc.).”),
transmitting, to the network node, control signaling comprising parameters for use by the algorithm in predicting the energy level of the WD, wherein the parameters comprise harvesting properties and parameters associated with a current use of the WD (Par. [0081] “indication indicates at least one of: energy harvesting capability; a minimum energy level for operation; a current energy level; an energy harvesting rate; an energy harvesting time for operation; an energy harvesting service support; a time before energy level harvesting; and a minimum energy level for reporting.”).
Höglund does not explicitly teach an algorithm to predict the energy level of the energy harvesting wireless device; and
receiving assistance from the network node in harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD.
However, Lu teaches an algorithm to predict the energy level of the energy harvesting wireless device (Page 2, “real-time prediction of future harvested energy … the harvested energy is the most important part that determines the energy availability in an EH-RTES.; Page 8, “proposed the concept of effective energy dissipation that define a unique quantity to accurately quantify the energy dissipation of the system. It includes not only the energy demand by the electronic circuit, but also the energy overhead incurred by energy flowing among different system components. We also addressed the need in run-time prediction of future harvested energy. These two contributions significantly improve the accuracy of energy availability computation for the proposed Model Accurate Predictive DVFS algorithm).
Höglund and Lu are analogous art because they are from the same field of endeavor. They both relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, and incorporate using data to predict the energy level of an energy harvesting wireless device, as taught by Lu.
One of ordinary skill in the art would have been motivated to improve “achieving best system performance under energy harvesting constraints” as suggested by Lu (Page 1).
Höglund and Lu do not explicitly teach receiving assistance from the network node in harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD.
However, Elshafie teaches receiving assistance from the network node in harvest energy from a dedicated energy source by an on-purpose energy transmission from the dedicated energy source to the WD (Par. [0044], “a first device (e.g., a UE, a base station, any sidelink enabled device) may be configured to perform energy harvesting by converting received radio frequency power associated with wireless signals received from a second device (e.g., a UE, a base station, any sidelink enabled device) to DC power”; Par. [0044], “Par. [0044], “the second device may transmit signals with a determined radio frequency power to the first device”; Par. [0045], “Based on receiving the signaling indicating the one or more parameters, the second device may adjust a radio frequency power of signals transmitted to the first wireless device. For example, the second device may adjust the radio frequency power of signals transmitted to the first wireless device to increase an efficiency of the energy harvesting performed by the first device”).
Höglund, Lu, and Elshafie are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device and predicts energy availability, as taught by Höglund and Lu, and incorporate assisting the wireless device to harvest energy by transmitting radio frequency power to the wireless device, as taught by Elshafie.
One of ordinary skill in the art would have been motivated to improve the efficiency of energy harvesting performed by the wireless device, as suggested by Elshafie (Par. [0045]).
Regarding claim 18, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises:
Transmitting, to the network node, control signaling comprising training data for updating the algorithm for predicting the energy level of the WD (Page 2, “exponentially Weighted Moving-Average (EWMA) model was designed to predict solar energy based on weighted current time-slot energy and historical average”; Page 4, “moving average uses the N past observation data to calculate the next prediction time series value”; Page 4, “The exponential smoothing approach [21] is widely used for short-time forecasting. Although it also employs weighting factors for past values, the weighting factors decay exponentially with the distance of the past values of the time series from the present time.”– Moving average models and exponential smoothing both estimate future harvested energy based on historical observation data. Because these algorithms compute updated predictions using previously observed energy measurements and incorporate new observations as they become available, the historical observations function as training data used to update the prediction algorithm.).
Regarding claim 19, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund further teaches wherein the method comprises:
Indicating, to the network node, that the WD is able to harvest energy (Par. [0014] “signaling is introduced to inform the CN (e.g., core node) that the wireless device is operating using energy harvesting”).
Regarding claim 20, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Lu further teaches wherein the method comprises, upon the energy level of the WD being insufficient for communication with the network node, performing at least one of:
harvesting energy,
refraining from communicating with the network node (Page 5, “If the scheduling/DVFS from Step 2 is invalidated by energy shortage, the task should not be removed from Q right away. Instead, we are going to first try to delay the task execution” – delaying task execution corresponds to refraining from scheduling communication until sufficient energy is available),
entering a power limited sub-state (Page 2, “Based on this algorithm, the task is executed at full speed of the processor if sufficient energy is available to the system; otherwise, the task is slowed down and the processor executes it in a lower frequency and lower power state”),
configuring a harvesting device or receiver of the WD to harvest energy from dedicated radio frequency by wireless power transfer” are optional claim limitations that are not addressed in this rejection.
Claim(s) 2, 11-12, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Höglund et al. USPGPUB 2024/0292335 A1 (hereinafter Höglund) in view of Lu et al. (Accurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded Systems, 2010) (hereinafter Lu) and Elshafie et al. USPGPUB 2022/0385109 A1 (hereinafter Elshafie), and further in view of Vannithamby US 9,271,242 B2 (hereinafter Vannithamby).
Regarding claim 2, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund, Lu, and Elshafie further do not explicitly teach wherein the method comprises:
communicating a message initiating using prediction of the energy level of the WD in the network node.
However, Vannithamby teaches wherein the method comprises:
communicating a message initiating using prediction of the energy level of the WD in the network node (Fig. 3, Fig. 5 , Col. 9 “Communications 35 including, for example, triggering messages to trigger communication between the UE 15 and the core network 25, messages sent by the UE to indicate that the UE is an energy-harvesting device and/or to include energy storage information of the energy-harvesting device, and/or communications scheduled based on the energy storage information may occur over any suitable combination of modules and/or interfaces in the system architecture 200 of FIG. 2.” – a scheduled communication based on the energy storage information could initiate using prediction of the energy level of the WD in the network node.).
Höglund, Lu, Elshafie, and Vannithamby are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, Lu and Elshafie, and incorporate triggering messages based on energy storage information, as taught by Vannithamby.
One of ordinary skill in the art would have been motivated to reduce inefficient operation of the energy storage device due to wasted energy, lost opportunity to harvest energy, and potentially failed transmission/reception as suggested by Vannithamby (Col. 1).
Regarding claim 11, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund and Lu do not explicitly teach wherein the energy harvesting properties are indicative of one or more of energy harvesting techniques which the WD has currently selected for energy harvesting.
However, Vannithamby teaches wherein the energy harvesting properties are indicative of one or more of energy harvesting techniques which the WD has currently selected for energy harvesting (Col. 8, “message may identify one or more of a type of energy source, an expected energy-harvesting pattern, energy storage capability, energy storage capacity and/or energy storage level. For example, Table 1 describes example message content according to some embodiments”).
Höglund, Lu, and Vannithamby are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund and Lu, and incorporate triggering messages based on energy storage information, as taught by Vannithamby.
One of ordinary skill in the art would have been motivated to reduce inefficient operation of the energy storage device due to wasted energy, lost opportunity to harvest energy, and potentially failed transmission/reception as suggested by Vannithamby (Col. 1).
Regarding claim 12, the combination of Höglund, Lu, Elshafie, and Vannithamby teaches all the limitations of the base claims as outlined above.
Vannithamby further teaches wherein the energy harvesting techniques comprise one or more of ambient energy harvesting techniques or dedicated energy harvesting techniques comprising as solar energy, vibration energy, and/or wireless power transfer (Col. 5, “UE 15 may be configured to independently harvest or generate energy for operation of the UE 15 using any suitable means including, for example, solar, mechanical, radio frequency (RF) or other means”).
Regarding claim 16, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund, Lu, and Elshafie do not explicitly teach wherein the method comprises:
communicating a message initiating using prediction of the energy level of the WD in the network node.
However, Vannithamby teaches wherein the method comprises:
communicating a message initiating using prediction of the energy level of the WD in the network node (Fig. 3, Fig. 5 , Col. 9 “Communications 35 including, for example, triggering messages to trigger communication between the UE 15 and the core network 25, messages sent by the UE to indicate that the UE is an energy-harvesting device and/or to include energy storage information of the energy-harvesting device, and/or communications scheduled based on the energy storage information may occur over any suitable combination of modules and/or interfaces in the system architecture 200 of FIG. 2.” – a scheduled communication based on the energy storage information could initiate using prediction of the energy level of the WD in the network node.).
Höglund, Lu, Elshafie, and Vannithamby are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, Lu, and Elshafie, and incorporate triggering messages based on energy storage information, as taught by Vannithamby.
One of ordinary skill in the art would have been motivated to reduce inefficient operation of the energy storage device due to wasted energy, lost opportunity to harvest energy, and potentially failed transmission/reception as suggested by Vannithamby (Col. 1).
Claim(s) 8, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Höglund et al. USPGPUB 2024/0292335 A1 (hereinafter Höglund) in view of Lu et al. (Accurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded Systems, 2010) (hereinafter Lu) and Elshafie et al. USPGPUB 2022/0385109 A1 (hereinafter Elshafie), and further in view of Muhammad et al. (Harvested Energy Prediction Schemes for Wireless Sensor Networks: Performance Evaluation and Enhancements, 2017) (hereinafter Muhammad).
Regarding claim 8, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund and Lu do not explicitly teach wherein the method comprises:
receiving, from the WD, control signaling comprising updated parameters required by the algorithm for predicting the energy level of the WD.
However, Muhammad teaches wherein the method comprises:
receiving, from the WD, control signaling comprising updated parameters required by the algorithm for predicting the energy level of the WD (Page 6, “The primary objective of the updater module in lPro-Energy is to refresh the existing entries in the pool. Initially, the pool contains previously harvested values for the past 30 days. After the completion of a day, the updater removes the oldest entry and adds the recently harvested day in the pool.”).
Höglund, Lu, Elshafie, and Muhammad are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, Lu, and Elshafie, and incorporate updating communicated energy harvesting device parameters, as taught by Muhammad.
One of ordinary skill in the art would have been motivated to “give freshness to the pool which in turn leads to significant performance enhancement” for energy prediction models as suggested by Muhammad (Page 6).
Regarding claim 17, the combination of Höglund, Lu, and Elshafie teaches all the limitations of the base claims as outlined above.
Höglund, Lu, and Elshafie do not explicitly teach wherein the method comprises:
receiving, from the WD, control signaling comprising updated parameters required by the algorithm for predicting the energy level of the WD.
However, Muhammad teaches wherein the method comprises:
receiving, from the WD, control signaling comprising updated parameters required by the algorithm for predicting the energy level of the WD (Page 6, “The primary objective of the Updater module in lPro-Energy is to refresh the existing entries in the pool. Initially, the pool contains previously harvested values for the past 30 days. After the completion of a day, the Updater removes the oldest entry and adds the recently harvested day in the pool.”).
Höglund, Lu, Elshafie, and Muhammad are analogous art because they are from the same field of endeavor. They all relate to energy harvesting systems.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above communication network that receives energy harvesting state information from a wireless device, as taught by Höglund, Lu, and Elshafie, and incorporate updating communicated energy harvesting device parameters, as taught by Muhammad.
One of ordinary skill in the art would have been motivated to “give freshness to the pool which in turn leads to significant performance enhancement” for energy prediction models as suggested by Muhammad (Page 6).
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Elfstrom et al. [US 20150305054 A1] teaches a method for power optimized transmission scheduling in an energy harvesting machine to machine device, comprising an internal power storage and an internal energy harvesting source and being configured for communication with a mobile communications network via a wireless link.
Li et al. [US 2014/0011543 A1] teaches an apparatus and method for wireless communication networks with energy harvesting.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/PETER XU/ Examiner, Art Unit 2119
/MOHAMMAD ALI/Supervisory Patent Examiner, Art Unit 2119
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