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 (IDS) submitted on 10/14/24 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 8, 11-14, and 18-20 are objected to because of the following informalities:
Regarding claim 8, on line 3, it appears that the word “a” is missing before the word “radio”.
Regarding claim 11, on line 2, it appears that the word “a” is missing before the word “radio”.
Regarding claim 12, on line 2, it appears that the word “a” is missing before the word “radio”.
Regarding claim 13, on line 3, it appears that the word “a” is missing before the word “radio”.
Claim 14 is also objected to as being dependent on claim 13 and containing the same deficiency.
Regarding claim 18, on line 1, it appears that the word “a” is missing before the word “radio”. Also, on line 7, it appears that the word “a” is missing before the word “radio”.
Regarding claim 19, on line 3, it appears that the word “a” is missing before the word “radio”.
Claim 20 is also objected to as being dependent on claim 19 and containing the same deficiency.
Appropriate correction is required.
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.
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.
Claim(s) 1, 2, 6-10, and 15-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. (U.S. 12,022,312) (hereinafter “Hu”) in view of Kim (U.S. 2026/0214486).
Regarding claim 1, Hu teaches a master base station (first apparatus) that includes a central processing unit 901 (processor) coupled to a memory 905 that stores a program (instructions) as shown in Figure 9 and spoken of on column 17, lines 24-31; where the master base station generates (prepares) an MDT measurement configuration message (measurement collection configuration), and, after determining the UE (second apparatus) for which MDT measurement is configured, the master base station delivers (transmits) the MDT measurement configuration message to the UE as shown in steps 702-704 of Figure 7 and spoken of on column 15, lines 43-58; where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (plurality of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66; and where the UE obtains power headroom information of the serving cells of the master base station and the secondary base station, and reports the power headroom information (MDT measurement report) to the master base station as shown in step 704 of Figure 7 and spoken of on column 15, line 66 – column 16, line 2.
Hu does not explicitly teach “at least one MDT measurement report comprising terminal device trajectory measurements collected based on the measurement collection configuration”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting taught in Kim as additional MDT measurement configuration information in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 2, Hu further teaches where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (set of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66.
Regarding claim 6, Hu does not explicitly teach “wherein the first apparatus is further caused to: applying machine learning (ML) model training on at least one ML model by using the terminal device trajectory measurements collected at the measurement granularity”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162]; and where a first node sends AI/ML data or UE measurement reports together with other input data for Model Training to an OAM 930 as spoken of on page 23, paragraph [0223].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting as taught in Kim as well as the use of reporting data for ML model training as taught in Kim in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 7, Hu does not explicitly teach “wherein the first apparatus is further caused to: perform at least one of the following based on the terminal device trajectory measurements: trouble shooting, performance analysis at a cell level or at a node level, or ML training or retraining by using the terminal device trajectory measurements as input data samples”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162]; and where a first node sends AI/ML data or UE measurement reports together with other input data for Model Training to an OAM 930 as spoken of on page 23, paragraph [0223].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting as taught in Kim as well as the use of reporting data for ML model training as taught in Kim in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 8, Hu does not explicitly teach “wherein the first apparatus comprises a network device for implementing Operation Administration and Maintenance (OAM) and the at least one second apparatus comprises one of a centralized unit or a distributed unit in radio access network”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162]; and where a first node sends AI/ML data or UE measurement reports together with other input data for Model Training to an OAM 930 as spoken of on page 23, paragraph [0223].
Kim also teaches where a split CU/DU architecture of a gNB (second apparatus) may be utilized where AI/ML model training is located in the OAM and AI/ML model inference is located in a gNB-CU (centralized unit) as spoken of on page 15, paragraph [0156].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting as taught in Kim as well as the use of reporting data for ML model training as taught in Kim in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 9, Hu teaches a master base station (first apparatus) that includes a central processing unit 901 (processor) coupled to a memory 905 that stores a program (instructions) as shown in Figure 9 and spoken of on column 17, lines 24-31; where the master base station generates (prepares) an MDT measurement configuration message (measurement collection configuration), and, after determining the UE (second apparatus) for which MDT measurement is configured, the master base station delivers (transmits) the MDT measurement configuration message to (received by) the UE as shown in steps 702-704 of Figure 7 and spoken of on column 15, lines 43-58; where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (plurality of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66; where the UE obtains power headroom information of the serving cells of the master base station and the secondary base station, and reports the power headroom information (MDT measurement report) to the master base station as shown in step 704 of Figure 7 and spoken of on column 15, line 66 – column 16, line 2; and where UEs provide a radio communication function and a processing function (typically via a processor and memory) as spoken of on column 7, lines 20-28.
Hu does not explicitly teach “collect, based on the measurement collection configuration, terminal device trajectory measurements from at least one terminal device in at least a part of the plurality of cells; and transmit, to the first apparatus, an MDT measurement report comprising the terminal device trajectory measurements”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting taught in Kim as additional MDT measurement configuration information in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 10, Hu further teaches where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (set of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66.
Regarding claim 15, Hu does not explicitly teach “wherein the first apparatus comprises a network device for implementing Operation Administration and Maintenance (OAM) and the at least one second apparatus comprises one of a centralized unit or a distributed unit in radio access network”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162]; and where a first node sends AI/ML data or UE measurement reports together with other input data for Model Training to an OAM 930 as spoken of on page 23, paragraph [0223].
Kim also teaches where a split CU/DU architecture of a gNB (second apparatus) may be utilized where AI/ML model training is located in the OAM and AI/ML model inference is located in a gNB-CU (centralized unit) as spoken of on page 15, paragraph [0156].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting as taught in Kim as well as the use of reporting data for ML model training as taught in Kim in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 16, Hu teaches a master base station (first apparatus) that includes a central processing unit 901 (processor) coupled to a memory 905 that stores a program (instructions) as shown in Figure 9 and spoken of on column 17, lines 24-31; where the master base station generates (prepares) an MDT measurement configuration message (measurement collection configuration), and, after determining the UE (second apparatus) for which MDT measurement is configured, the master base station delivers (transmits) the MDT measurement configuration message to (received by) the UE as shown in steps 702-704 of Figure 7 and spoken of on column 15, lines 43-58; where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (plurality of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66; where the UE obtains power headroom information of the serving cells of the master base station and the secondary base station, and reports the power headroom information (MDT measurement report) to the master base station as shown in step 704 of Figure 7 and spoken of on column 15, line 66 – column 16, line 2; and where UEs provide a radio communication function and a processing function (typically via a processor and memory) as spoken of on column 7, lines 20-28.
Hu does not explicitly teach “collect, based on the measurement collection configuration, terminal device trajectory measurements from at least one terminal device in at least a part of the plurality of cells; and transmit, to the first apparatus, an MDT measurement report comprising the terminal device trajectory measurements”.
However, Kim teaches a method and apparatus for implementing AI/ML in a dual connectivity network, where a UE (terminal device) may perform immediate Minimization of Drive Test (MDT) measurement together with available location reporting (trajectory measurements collected) as spoken of on page 17, paragraph [0162].
Given the above references, it would have been obvious to someone of ordinary skill in the art, before the effective filing date of the invention, to apply the location reporting taught in Kim as additional MDT measurement configuration information in the system of Hu in order to further improve accuracy of a cell measurement result by factoring location information into the MDT measurement along with the other above listed parameters as spoken of on column 1, lines 52-65 of Hu.
Regarding claim 17, Hu further teaches where the MDT measurement configuration message includes a reference signal type, reference signal configuration information, an average quality of beams of a reference signal, a reference signal combination threshold, as well as power headroom measurement (collectively a list having a measurement granularity) of serving cells (set of cells) of the master base station and a secondary base station (second apparatus) as spoken of on column 10, lines 27-32, as well as column 15, lines 59-66.
Allowable Subject Matter
Claims 3-5, 11-14, and 18-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. References considered relevant to this application are listed in the attached “Notice of References Cited” (PTO-892).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J. MOORE, JR., whose telephone number is (571)272-3168. The examiner can normally be reached M-F (9am-4pm).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hassan A. Phillips can be reached at (571)272-3940. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL J MOORE JR/Primary Examiner, Art Unit 2467
Prosecution Insights