DETAILED ACTION
This Office action is on response to the application filed on 12 February 2025.
Claims 1-8 are presented for examination.
Claim Objections
Claim 8 is objected to because of the following informalities:
Claim 8 claims that, “The signal anti-jamming method of claim 3 [[4]]…” while claim 3 claims “an anti-jamming apparatus”. 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.
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 13 is rejected under 35 U.S.C. 103 as being unpatentable over Jayaweera Kankanamge et al. US 2020/0153535 A1 (as Jayaweera hereafter).
As to claim 3, Jayaweera discloses, substantially the invention as claimed, including an anti-jamming apparatus (Figures 1-5, the communication device 100) comprising:
processing circuitry (Figures 1-5, the application or processing circuitry 102 or the controller) arranged to train each of receiving system and transmitting system using algorithms (machine algorithms) to determine the presence of a jamming signal and prevent (avoid) the interruption of signals sent to the receiving system or from the transmitting system (Abstract, Figures 1-5, and associated paragraphs, using the Machine Learning in a cognitive radio to avoid a jammer, [18], [19], [44]; [131]; [144], [149]; claim 1);
classify a detected signal on a sensing channel using an algorithm (a RL algorithm; a machine-learning trained classifier, [19] and/or jammer tracking policy learning 700 illustrated in Figure 7) to track the jamming signal, notify users of a potential jamming signal, adjust receiving systems and transmitting systems to alter operations to continue operation in the presence of a jamming signal (Abstract, Figures 1-5, and associated paragraphs, [18]-[20], [131]; [149]; claim 1);
after initial training of each of the receiving and transmitting system: the algorithm configures the receiving system to determine whether the jamming signal is present on a current receiving channel and the algorithm configures the transmitting system to communicate using an communications channel which is not jammed (Abstract, Figures 1-5, 6-11 and associated paragraphs, [94], “After the initial jammer tracking policy determination, the cognitive radio may start Learning Period #2, as shown in FIG. 8. The cognitive radio may, during this time, learn a cognitive anti jamming communications policy while also tracking the jammer and updating the sensing policy for effective jammer tracking 800. Thus, the jammer policy shown in FIG. 8 is coupled with the communication policy learning, which is shown in FIG. 9. The second learning period may begin at operation 802 in which the current sensing channel as is sensed and the time is incremented”; and [95]-[99]; Figure 9 illustrates a communications policy during Learning Period # 2, [100]-[109]; and [110], “At the end of the LP #2 shown in FIGS. 8 and 9, the cognitive radio may initiate a cognitive anti-jamming communications phase. In this phase the cognitive radio may use the teamed sensing and communications policies. FIG. 10 illustrates jammer tracking during a communication phase in accordance with some embodiments while FIG. 11 illustrates communication phase anti-jamming in accordance with some embodiments. In one embodiment, during the phase shown in FIGS. 10 and 11, the cognitive radio may explore random channels as denoted by two exploration rates, one for sensing policy and one for the cognitive anti jamming communications policy. This may allow the cognitive radio to continuously update its policies in order to keep up with time-varying channel and jammer dynamics”).
It would have been obvious to one of the ordinary skill in ML/AI technologies art to understand the claimed “determining the presence of a jamming signal and prevent the interruption of signals sent to the receiving system or from the transmitting system” corresponds to the Jayaweera’s sensing and communication system (S/C) policy using Reinforcement Learning (RL) methods to learn how to track the jammer accurately and how to avoid the jammer effectively.
Allowable Subject Matter
The following is an examiner’s statement of reasons for allowance:
The primary reasons for allowance of the claims are the inclusion of the prior art of record do not disclose the bold underlined claimed elements of “1. An apparatus comprising: a receiver system that receives, via a plurality of signal transmitter systems, multiple signals comprising a range of frequencies that carry information; a plurality of transmitter system that transmit, a number of frequencies for the receiver system to process the information; and an anti-jamming system comprising: a jamming signal detection system located within at least one transmitter system utilizing an algorithm comprising; removing or preventing a jamming signal from being received by a transmitter system wherein the algorithm is a series of steps comprising: taking a first measurement of the 2D cyclic-cross correlation between a discrete-time received signal vector and a known 5G PRS; detecting the presence of an AF, TD and FS jamming signal; estimating the strength of the AF, TD, and FS relay jamming signal using the peak value and the peak position lag; filtering out any AF relay jamming signal that is detected; and taking a second measurement of the 2D cyclic-cross correlation between the known PRS vector b and the received signal vector to determine if the AF jamming signal is eliminated; a control system, and a network, that within a coverage area of the receiver system via can determine the location of the transmitter system relative to the receiving system allowing reception of all signals at the receiver system and preventing jamming signals from interfering with the signals from the transmitting systems based on the position of the receiver system and transmitter systems” in instant independent claims 1, 4.
The prior art cited in this Office action is: Jayaweera Kankanamge et al. US 2020/0153535 A1.
Conclusion
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/HAI V NGUYEN/Primary Examiner, Art Unit 2649
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