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 .
Response to Arguments
Applicant’s arguments with respect to claims 1,9,16 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1,2,3,6,8,9,10,11,14,15,16,17,18,19,20 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. (US 20130196677, hereinafter Smith) in view of Khasnabish et al. (US 20210329466, hereinafter Khasnabish)
Regarding claim 1, Smith discloses a computer-implemented method for dynamic sharing of a radio access network, comprising:
determining a radio access network excess RAN capacity factor (Par. 137; The Dynamin Spectrum Controller (DSC) may communicate with the Dynamic Spectrum Policy Controller (DPC) data regarding excess capacity of the network; The current excess capacity quantifies the available capacity thus constitutes a capacity factor; Par. 135: Lines 1-4; The DSA enables spectrum providers to determine RF usage and availability);
in response to the radio access network excess capacity factor exceeding a predetermined threshold, issuing a radio access network bandwidth offer (Par. 167: Lines: 3-5; The primary provider may auction available spectrum resources);
receiving, at the RAN resource exchange server, a radio access network bandwidth offer response from a user, wherein the bandwidth offer response includes a localized geographical region (Par. 177: 1-5; The request from the secondary network for spectrum resources may be based on a geographic boundary; Par. 353: Lines 7-12; The request message is based on pre-defined criteria such as the geographic location of the UE; (Par. 363: Lines 6-13; The DPC (RAN resource exchange server) evaluates a resource bid from a network provide);
evaluating the radio access network bandwidth offer response (Par. 363: Lines 6-13; The DPC evaluates a resource bid from a network provide );
and providing a portion of the radio access network to the user based on the evaluating of the radio access network bandwidth offer response (Par. 363: 15-23; When the bid is accepted, Network 1 is able to assign resources to Network 2 which enables the establishment of a communication session with the UE belonging to Network 2).
Smith does not disclose training a machine learning system to predict times of excess RAN resource availability based on input data from data services; and issuing a bid request based on the predicted times of the excess RAN resource availability, as part of the radio access network bandwidth offer, the bid request includes sending a message to a RAN resource exchange server via a computer network.
Khasnabish, however, discloses training a machine learning system to predict times of excess RAN resource availability based on input data from data services (Par. 105: Spectrum availability at the RAN is derived using machine learning of historic spectrum utilization and services accessed at different times using spectrum from the RAN; The predictive models provide probabilities that different UEs will access services at different times, thereby predicting when spectrum resources will be available and unavailable).
Furthermore, Smith discloses issuing a request for spectrum resources in a bidding process and transmitting request messages between network entities that manage spectrum allocation (Par. 177: Lines 1–5; a secondary network transmits a request for spectrum resources; Par. 353: Lines 7–12; the request message is transmitted based on criteria such as geographic location of the UE; Par. 363: Lines 6–13; the Dynamic Policy Controller evaluates a resource bid from a network provider), which corresponds to issuing a bid request and sending a message to a RAN resource exchange server via a computer network. However, Smith does not disclose issuing the bid request based on predicted times of excess RAN resource availability.
Khasnabish, however, discloses predicting spectrum availability at one or more RANs using artificial intelligence and/or machine learning derived from historical spectrum utilization data, wherein predictive models generated from historic usage provide probabilities that different UEs will access services at different times (Par. 105). Predicting spectrum availability at different times corresponds to predicting times of excess RAN resource availability, which can be used to determine when spectrum resources are expected to become available.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Smith to incorporate the machine learning based prediction of spectrum availability as taught by Khasnabish in order to predict when excess RAN resources are expected to become available based on historical spectrum utilization and service access patterns. A person of ordinary skill in the art would have been motivated to incorporate such predictive techniques because predicting future spectrum availability allows a network operator to proactively initiate spectrum sharing and bidding processes rather than relying solely on reactive detection of excess capacity. Doing so would improve the efficiency and utilization of radio access network resources by enabling bandwidth offers and bid requests to be issued at times when excess capacity is predicted to occur, thereby facilitating more effective allocation of spectrum resources and reducing delays associated with waiting for capacity to become available.
Regarding claim 2 as applied to claim 1, Smith discloses wherein the bandwidth offer includes metadata that includes a spectrum allocation (Par. 142: Lines 6; In order to optimize the spectrum assignment, the bandwidth and the location of the spectrum in the frequency band are taken into consideration; Par. 176: Lines 1-4; Policy and resource criteria imposed include availability of spectrum and availability of bandwidth; Par. 354: Lines 10-14; Bid will only be accepted if it complies with the policies and rules).
Regarding claim 3 as applied to claim 1, Smith discloses wherein the bandwidth offer includes metadata that includes a quality-of-service (QoS) dataset (Par. 142: QoS is a factor used in determining the best available spectrum; Par. 177: The DSA enables a secondary network to request spectrum resources based on factors such as QoS; Par. 202: Lines 1-4; During the bidding process, the DSA implements a rule set that include required QoS).
Regarding claim 6 as applied to claim 1, Smith discloses wherein the evaluating includes computing a capacity projection (Par. 135: Lines 1-5; A spectrum provider is able to monitor its RF spectrum usage and availability, and make the available RF spectrum for use by another provider; Par. 137: The availability can be determined using capacity policy criteria data. This data may include current excess capacity and expected future capacity).
Regarding claim 8 as applied to claim 1, Smith discloses further comprising generating a bid score based on the bandwidth offer response, wherein the bid score is a function of payment terms (Par. 363: Lines 6-11; The bid is evaluated based on rules and requirements that include pricing; Par. 371: Lines 15-17; The bid may be accepted if the price requirement is satisfied; Par. 453: Lines 3-4; Bidding information includes information such as minimum price, starting price, bid increments, etc.; The auction logic selects winners based on terms that include pricing, which is effectively scoring).
Regrading claim 9, Smith discloses an electronic computation device comprising: a processor; a memory couple to the processor, the memory containing instructions, that when executed by the processor, cause the electronic computing device to (A electronic computing device capable of performing the recited functions necessarily includes the stated components).
The remaining limitations of claim 9 have been addressed in the rejection of claim 1. Therefore, all the limitations of claim 9 have been addressed.
Regarding claim 10 as applied to claim 9, the rejection of claim 2 addresses the limitations of claim 10. Therefore, the limitations of claim 10 have been addressed.
Regarding claim 11 as applied to claim 9, the rejection of claim 3 addresses the limitations of claim 11. Therefore, the limitations of claim 11 have been addressed.
Regarding claim 14 as applied to claim 9, the rejection of claim 6 addresses the limitations of claim 14. Therefore, the limitations of claim 14 are addressed.
Regarding claim 15 as applied to claim 9, the rejection of claim 8 addresses the limitations of claim 15. Therefore, the limitations of claim 15 have been addressed.
Regarding claim 16, Smith discloses a computer program product for an electronic computation device comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the electronic computation device to (The recited functions necessarily include a computer program with executable instructions executed by a processor).
The remaining limitations of claim 16 have been addressed in the rejection of claim 1. Therefore, the limitations of claim 16 have been addressed.
Regarding claim 17 as applied to claim 16, the rejection of claim 2 addresses the limitations of claim 17. Therefore, the limitations of claim 17 have been addressed.
Regarding claim 18 as applied to claim 16, the rejection of claim 3 addresses the limitations of claim 18. Therefore, the limitations of claim 18 have been addressed.
Regarding claim 19 as applied to claim 16, the rejection of claim 6 addresses the limitations of claim 19. Therefore, the limitations of claim 19 are addressed.
Regarding claim 20 as applied to claim 16, the rejection of claim 8 addresses the limitations of claim 20. Therefore, the limitations of claim 20 have been addressed.
Claims 4,12 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. (US 20130196677, hereinafter Smith) in view of Khasnabish et al. (US 20210329466, hereinafter Khasnabish) in further view of Luoto et al. (CN 107431931, hereinafter Luoto).
Regarding claim 4 as applied to claim 1, Smith discloses offering spectrum resources to another network using policies and rules that uses time to allocate resources (Par. 176: Host network may use time (e.g., defining time and days) for allocating resources). Smith also discloses the second network requesting spectrum resources based on time (e.g., when resources are requested) (Par. 177: Lines 1-3; The second network can request spectrum resources based on when they are required ).
Smith in view of Khasnabish does not disclose wherein the bandwidth offer response includes a time and duration, wherein the duration is in a range from one hour to 48 hours.
Luoto, however, talks about frequency sharing for a predefined window length (Pg. 6: Lines 31-35; The time window for spectrum sharing can be a defined time such as 1 hour or 1 day).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the resource requesting/bidding system that uses time as a factor of Smith in view of Khasnabish with the fixed time of Luoto so that the bandwidth offer response includes a time and a duration in a fixed range. Doing so merely applies a known scheduling practice to simplify coordination and enforcement.
Regrading claim 12 as applied to claim 9, the rejection of claim 4 addressed the limitations of claim 12. Therefore, the limitations of claim 12 have been addressed.
Claims 5,13 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. (US 20130196677, hereinafter Smith) in view of Khasnabish et al. (US 20210329466, hereinafter Khasnabish) in further view of Wambugu et al. (US 20200090648, hereinafter Wambugu).
Regarding claim 5 as applied to claim 1, Smith in view of Khasnabish discloses a bandwidth offer but does not disclose wherein the bandwidth offer is based on an event schedule obtained from social media.
Wambugu, however, discloses analyzing network congestion based on a calendar of events obtained from social media (Par. 77: Lines 7-11; Network congestion is analyzed based on expected evens based on a calendar and social media feeds).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the bandwidth offer of Smith in view of Khasnabish, with the ability to analyze network congestion using a calendar of events from social media of Wambugu. Using widely available social data to anticipate demand and time is a routine data-source substitution that improves congestion forecasting without changing its fundamental operation.
Regarding claim 13 as applied to claim 9, the rejection of claim 5 addresses the limitations of claim 13. Therefore, the limitations of claim 13 have been addressed.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. (US 20130196677, hereinafter Smith) in view of Khasnabish et al. (US 20210329466, hereinafter Khasnabish) in further view of Yang et al. (US 20210377903, hereinafter Yang).
Regrading claim 7 as applied to claim 6, Smith in view of Khasnabish disclose evaluating but does not disclose wherein the evaluating is based on crowdsourced location service data.
Yang, however, discloses predicting future spectrum usage based on measuring spectrum exhaustion during surged in traffic demands from events such as concerts (Par. 29: Predicted broadcast spectrum can be measured using spectrum exhaustion during traffic surges from events (i.e. crowdsourced location data)).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the evaluation of a spectrum offer of Smith in view of Khasnabish with the ability to use crowdsources location data to predict usage of Yang. Leveraging crowd signals as an input into Smith in view of Khasnabish’s capacity prediction is a straightforward use of known data to improve accuracy, involves no technological incompatibility, and would have been expected to work with predictable success to arrive at the claimed limitation.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FABIAN BOTELLO whose telephone number is (571)272-4439. The examiner can normally be reached Monday - Friday 8:30 am - 5:30 pm.
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/FABIAN BOTELLO/Examiner, Art Unit 2648
/WESLEY L KIM/Supervisory Patent Examiner, Art Unit 2648