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 .
This action is in response to the application filed on 06/12/2024.
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non–statutory subject matter.
Claims 20 recite a “computer readable storage medium”, with nothing in the specification specifically limiting this medium from being a transitory medium (i.e. such as a signal medium), which is considered non–statutory. Further, the USPTO Official Gazette from week #8 of 2010 (Feb 23, 2010), Volume 1351 page 212 specifically explains that the addition of the term "non–transitory" before the computer readable medium will alleviate any issues with 35 USC 101 rejections, since the claims would no longer cover non statutory subject matter.
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 of this title, 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.
Claim(s) 1-5, 7-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (WIPO. Pub. CN108322895) in view of Hirzallah et al. (U.S. Pub. 20240406927).
Regarding claim 1 Zhu disclose a method, comprising:
sending a short message service (SMS) to a target device, via a short message service center (SMSC) para. 56, “receiving the user home-location SMSC based on the SMPP: sending the short message to the user terminal by the submitt_sm message”;
receiving, from the target device, a delivery report based on the sent SMS through the SMSC para. 57, “the user terminal returns the short message response to the receiving user home address SMSC”.
Zhu does not specifically disclose providing the delivery report as an input to a pretrained machine learning model, deriving one or more fingerprints from the delivery report, thereby creating a target data model based on the one or more fingerprints, predicting, based on the target data model, a location of the target device.
However, Hirzallah teach, providing the delivery report as an input to a pretrained machine learning model para. 141, “the UE reports the measurements of the downlink reference signals received from one or more TRPs to the LMF (e.g., LMF 270)”;
deriving one or more fingerprints from the delivery report, thereby creating a target data model based on the one or more fingerprints para. 143, “The LMF then applies an AI/ML positioning model to the measurements of the uplink reference signal(s) to obtain a target location of the UE”;
predicting, based on the target data model, a location of the target device para. 141, “the UE reports the measurements of the downlink reference signals received from one or more TRPs to the LMF (e.g., LMF 270)”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can analyze through large language models algorithms data related to the user equipments position. The motivation for doing so would have been to study the data and predict the next location that the UE could located.
Regarding claim 2 Zhu does not specifically disclose, wherein the delivery report is triggered by receipt of the SMS at the target device.
However, Hirzallah teach, wherein the delivery report is triggered by receipt of the SMS at the target device para. 14, “obtaining the sending state corresponding to the first short message, at least one of the following first information is carried in the response information of the short message query request, sending the response information”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can promptly respond to trigger messages according to the preestablished configuration. The motivation for doing so would have been to minimize the delay between the nodes in the network.
Regarding claim 3 Zhu does not specifically disclose, wherein the delivery report comprises one or more delays from the target device.
However, Hirzallah teach, wherein the delivery report comprises one or more delays from the target device para. 2, “only waiting for the returned state report (Cmpp_Deliver) to determine the sending state of the short message, and the state report return may have a long delay”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu to be able to account for all the time involved in the processing and responding to the trigger message. The motivation for doing so would have been to be able to estimate the total delay of the response.
Regarding claim 4 Zhu does not specifically disclose, wherein the one or more delays comprise a processing delay, a routing delay, and/or a propagation delay.
However, Hirzallah teach, wherein the one or more delays comprise a processing delay, a routing delay, and/or a propagation delay para. 2, “The channel estimate represents the intensity of a radio frequency (RF) signal (e.g., a positioning reference signal (PRS)) received through a multipath channel as a function of time delay, and may be referred to as the channel energy response (CER), channel impulse response (CIR), or power delay profile (PDP) of the channel”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu to be able to account for all the time involved in the processing and handling of information regarding the response triggered. The motivation for doing so would have been to be able to estimate the total delay of the response before it arrives.
Regarding claim 5 Zhu does not specifically disclose, wherein the trained machine learning model is an artificial neural network.
However, Hirzallah teach, wherein the trained machine learning model is an artificial neural network para. 131, “Another example of a machine learning model is a neural network”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can evaluate and recognize complex patterns in the data reported. The motivation for doing so would have been to use the data obtained as a result for pattern predictions.
Regarding claim 7 Zhu does not specifically disclose, wherein the one or more fingerprints comprise a time delay based on the target device location.
However, Hirzallah teach, wherein the one or more fingerprints comprise a time delay based on the target device location para. 244, “The RAN node of any of clauses 67 to 68, wherein the inputs to the one or more machine learning models comprise: a channel impulse response (CIR), a power delay profile (PDP), a delay profile (DP), a channel frequency response (CFR), a correlation of the CIR or the CFR of different transmission-reception points (TRPs)”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu to be able to account for all the time involved in the processing and handling of information being handled. The motivation for doing so would have been to estimate the total delay according to the amount of data transmitted.
Regarding claim 8 Zhu does not specifically disclose, further comprising sending a plurality of SMSs to the target device from a plurality of locations.
However, Hirzallah teach, further comprising sending a plurality of SMSs to the target device from a plurality of locations para. 116, “A location estimate may be referred to by other names, such as a position estimate, location, position, position fix, fix, or the like. A location estimate may be geodetic and comprise coordinates (e.g., latitude, longitude, and possibly altitude)”. The user equipment (UE) receive and transmit from multiple locations.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu to help the artificial neural network find better patterns. The motivation for doing so would have been to learn the correct patterns to use the data obtained as a result for pattern predictions.
Regarding claim 9 Zhu does not specifically disclose, wherein the target device location is stationary.
However, Hirzallah teach, wherein the target device location is stationary. para. 116, “A location estimate may be referred to by other names, such as a position estimate, location, position, position fix, fix, or the like. A location estimate may be geodetic and comprise coordinates (e.g., latitude, longitude, and possibly altitude)”. The user equipment (UE) receive and transmit from multiple locations and it would be obvious than it can transmit and/or receive from a stationary location, so estimating the location during that time will report the same value while it is fix at the same location.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can analyze through large language models algorithms data related to the user equipments position. The motivation for doing so would have been to study the data and predict the next location that the UE could located.
Regarding claim 10 Zhu does not specifically disclose, wherein the target device location is dynamic.
However, Hirzallah teach, wherein the target device location is dynamic para. 116, “A location estimate may be referred to by other names, such as a position estimate, location, position, position fix, fix, or the like. A location estimate may be geodetic and comprise coordinates (e.g., latitude, longitude, and possibly altitude)”. The user equipment (UE) receive and transmit from multiple locations and it would be obvious than it can transmit and/or receive while the user equipment dynamically moves and changes location, so estimating the location during that time will report different values.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can analyze through large language models algorithms data related to the user equipments position. The motivation for doing so would have been to study the data and predict the next location that the UE could located.
Regarding claim 11 Zhu does not specifically disclose, wherein the pretrained machine learning model is trained on a dataset of fingerprints of known locations of target devices.
However, Hirzallah teach, wherein the pretrained machine learning model is trained on a dataset of fingerprints of known locations of target devices para. 5, “the set of machine learning positioning capabilities includes a list of identifiers of a set of machine learning positioning functionalities supported by the RAN node”.
Zhu and Hirzallah are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hirzallah in the system of Zhu so the system can analyze through large language models algorithms data related to the user equipments position. The motivation for doing so would have been to study the data and predict the next location that the UE could located.
Claim 12 recites an system corresponding to the method of claim 1 and thus is rejected under the same reason set forth in the rejection of claim 1.
Claim 13 recites an apparatus corresponding to the method of claim 1 and thus is rejected under the same reason set forth in the rejection of claim 1.
Regarding claims 14-17 and 19 the limitations of claims 2-5 and 7, respectively, are rejected in the same manner as analyzed above with respect to claims 2-5 and 7, respectively.
Claim 20 recites a computer–program product corresponding to the apparatus of claim 1 and thus is rejected under the same reason set forth in the rejection of claim 1.
Claim(s) 6 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (WIPO. Pub. CN108322895) in view of Hirzallah et al. (U.S. Pub. 20240406927), further in view of Gill (U.S. Pub. 20210168572).
Regarding claim 6 Zhu and Hirzallah does not specifically disclose, wherein the artificial neural network is a multilayer perceptron classifier para. 208, “The correction unit for the synaptic weights of the ANN 25 neurons in accordance with a given correction step is configured to correct, as the ANN 21 is trained, the perceptron of the weight of the synaptic connections w (n) ANN in accordance with the following algorithm”.
Zhu, Hirzallah and Gill are analogous because they pertain to the field of wireless communication and, more specifically, to short message handling and processing.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Gill in the system of Zhu and Hirzallah so the system can analyze through large language models algorithms with data changing in real time. The motivation for doing so would have been to study the data and predict the next location that the UE could located.
Regarding claim 18 the limitations of claim 18 are rejected in the same manner as analyzed above with respect to claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Sendonaris et al. (U.S. Pub. 20160109582) which disclose(s) systems and methods for location positioning of user device.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAUL RIVAS whose telephone number is (571)270–5590. The examiner can normally be reached on Monday – Friday, from 8:30am to 5:00pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner' s supervisor, Sujoy K. Kundu, can be reached on (571) 272 - 8586. The fax phone number for the organization where this application or proceeding is assigned is 571–273–8300.
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/RR/
Examiner, Art Unit 2471
/SUJOY K KUNDU/ Supervisory Patent Examiner, Art Unit 2471
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