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 Amendment
The indicated allowability of claims 2, 5-9, and 13 are withdrawn in view of applicant’s admitted prior art. Rejections based on the cited reference follow.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5, 10, 12, 14, 15, and 17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Mostafa Ahmed Elhamy et al: “Aggregate Preamble Sequence Design and Detection for Massive IoT With Deep Learning”, IEEE Transactions On Vehicular Technology, IEEE, USA, vol. 70, 9 March 2021.
Regarding to claims 1 and 12, Mostafa discloses a receiver (fig. 5) comprising at least one processor (implicitly shown) and at least one memory storing instructions (implicitly shown), the at least one memory and the instructions configured to, with the at least one processor, cause the receiver to: perform a correlation processing (correlator) of a first signal (y) received by the receiver and/or of a second signal which is derived from the first signal (page 5, left column line 10-12), and at least temporarily modify an output signal (c[n]) of the correlation processing using at least one neural network (DNN) of the receiver to generate a modified output signal (page 7, right column; equation 10), wherein the instructions, when executed by the at least one processor, cause the receiver to determine at least one random access preamble identifier (page 5, right column; equation 6) based on at least one of a) the output signal of the correlation processing and b) the modified output signal of the correlation processing (page 6, right column lines 5-7).
Regarding to claim 3, Mostafa discloses determine a weighted sum (v) of the output signal of the correlation processing and of the modified output signal of the correlation processing (page 7 paragraph 2; equation 9).
Regarding to claim 4, Mostafa discloses the receiver to determine a weight factor (w) for determining the weighted sum (page 7 paragraph 2).
Regarding to claims 5 and 17, Mostafa discloses determines a weight factor for determining a weighted sum based on at least one of the following elements: a) a first signal to noise ratio characterizing an estimated signal to noise ratio of the output signal of the correlation processing (page 8, right column paragraph 4), b) a second signal to noise ratio for which the weight factor equals 0.5, c) a predetermined slope parameter, which characterizes a sensitivity of the weight factor with respect to the first signal to noise ratio, wherein the instructions, when executed by the at least one processor, cause the receiver to determine the weight factor based on the equation: α = 1/1+e(SNRest-SNRtrans)/Slope, wherein α characterizes the weight factor, wherein SNRest characterizes the first signal to noise ratio (SNR-1), wherein SNRtrans characterizes the second signal to noise ratio, wherein Slope characterizes the slope parameter, and wherein e(*) characterizes the exponential function; and determines the weighted sum of the output signal of the correlation processing and of the modified output signal of the correlation processing (page 7 paragraph 2; equation 9).
Regarding to claim 10, Mostafa discloses the at least one neural network is configured to modify noise-related statistics of the output signal of the correlation processing (page 8, right column paragraph 4).
Regarding to claim 14, Mostafa discloses a wireless communications system comprising at least one receiver according to claim 1 (page 1, left column, “Introduction”).
Regarding to claim 15, Mostafa discloses a receiver for performing the method of claim 12 (page 1 Abstract), thus it is inherent the receiver include a non-transitory computer readable medium comprising program instructions for causing the receiver to perform the method.
Allowable Subject Matter
Claims 6-9 and 18-21 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.
Claims 13 and 16 allowed.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Duc T Duong whose telephone number is (571)272-3122. The examiner can normally be reached Mon-Fri; 9am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hassan 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.
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/DUC T DUONG/Primary Examiner, Art Unit 2467
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