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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 04/13/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/13/2026 has been considered and placed on record.
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.
Claim(s) 1, 3, 4, 6-10 and 12, 14-17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ebrahimzad et al. (US 10,587,358 B1, hereinafter, “Ebrahimzad”) in views of HERATH et al. (US 2020/0092057 A1, hereinafter, “Herath”), and CAMMERER, et al., "Trainable communication systems: Concepts and prototype," IEEE Transactions on Communications, arXiv: 1911.13055v2 [CS.IT], 14 pages (hereinafter, “Cammerer”, provided in the 04/13/2026 IDS).
Consider 10, Ebrahimzad teaches a first computing system (see figure 1 (102), figure 2 and figure 8) comprising: one or more non-transitory computer-readable storage media including instructions (see at least col. 20 lines 43-49 and claim 1); and one or more processors coupled to the storage media, the one or more processors configured to execute the instructions (see at least col. 20 lines 43-49 and claim 1) to: access a stream of coded bits (see at least abstract figure 2 (202) and col. 8 line 65-col. 9 line 25, Ebrahimzad teaches accessing a stream of coded ‘client’ bits); generate a plurality of sub-streams of coded bits based on the accessed stream of coded bits (see at least figure 2 (219, 220) and col. 9 lines 22-27, Ebrahimzad teaches generating coded ‘shaped’ bits based on the accessed stream of coded ‘client’ bits); map, based on a bit-mapper model, the plurality of sub-stream of coded bits to a plurality of intermediate symbols, respectively (see at least figure 2 (222 and output 203) and col. 9 lines 42-55, Ebrahimzad teaches respectively mapping the plurality of coded bits to a plurality of symbols using a symbol selection model); generate, based on a symbol-mapper model, a plurality of constellation symbols from the plurality of intermediate symbols (see at least figure 2 (224, 205), col. 8 line 65-col. 9 line 15, col. 9 lines 42-55 and col. 13 line 64 to col. 14 line 7, Ebrahimzad teaches generating final shaped symbols for constellation from the plurality of symbols using quadrant selection model) ; and transmit a signal generated based on the plurality of constellation symbols to a second computing system (see figure 1 and figure 8 (via 864) and description thereof).
Ebrahimzad teaches map, based on a bit-mapper model, the plurality of sub-stream of coded bits to a plurality of intermediate symbols, respectively (see above), however, did not particularly teach map, based on a plurality of bit-mapper models, the plurality of sub-stream of coded bits to a plurality of intermediate symbols, respectively. Herath teaches said technique (see at least paras. 78-80, figure 2a (204) and figure 2c, where Herath teaches mapping, using plurality bit-symbol mappers (fig. 2c), a plurality of sub-stream of coded bits to respective plurality of symbols).
It would have been obvious to one of ordinary skill in the art at the time of the application to modify the invention of Ebrahimzad and teach map, based on a plurality of bit-mapper models, the plurality of sub-stream of coded bits to a plurality of intermediate symbols, respectively, as taught by Herath, thereby, having efficient communication medium (para. 233).
Ebrahimzad teaches map, based on a bit-mapper model, the plurality of sub-stream of coded bits to a plurality of intermediate symbols, respectively (see above), however, did not particularly teach each of the bit-mapper models is a machine-learning model trained based on minimizing an average transmission power for signals given a particular bit error rate for signal transmission. Cammerer teaches said technique (see at least figures 5, 14, 15 and page 13 (section b), Cammerer teaches a bit mapper in a neural network model trained to minimizing the dB (power) of average SNR of transmitted signals at a particular BER).
It would have been obvious to one of ordinary skill in the art at the time of the application to modify the invention of Ebrahimzad and teach each of the bit-mapper models is a machine-learning model trained based on minimizing an average transmission power for signals given a particular bit error rate for signal transmission, as taught by Cammerer, thereby, having efficient communication link.
Consider claim 1: all the limitations of method claim 1 are included in the apparatus claim 10, therefore, claim 1 has been subjected to the same rejection applied to claim 10.
Consider claim 17: all the limitations of the computer readable storage media claim 17 are included in the apparatus claim 10, therefore, claim 17 has been subjected to the same rejection applied to claim 10.
Consider claims 6 and 14, Ebrahimzad in views of Herath and Cammerer teaches generating the plurality of sub-streams of coded bits comprises dividing the accessed stream of coded bits into the plurality of sub-streams of coded bits based on a serial-to-parallel conversion (see at least figure 2c (bit subset generator), paras. 79, 123, 142 and 159 in Herath, where Herath teaches generating the plurality of sub-streams by converting serial input sequence into parallel sub-streams (i.e., dividing input c into plurality of sub-streams in fig. 2c)).
Consider claims 8 and 15, Ebrahimzad in views of Herath and Cammerer teaches receiving, at the first computing system from the second computing, a plurality of parameters via a signaling channel, wherein the plurality of parameters comprise one or more of a number of the plurality of intermediate symbols, a number of the plurality of constellation symbols, a scaling factor, a modulation and coding scheme (MCS), or a bit assignment for signaling (see at least figure 5 (MA signature), paras. 147-149, 181-182 in Herath, where Herath teaches receiving at least bit assignment and MCS index from the second computing device).
Consider claims 9 and 16, Ebrahimzad in views of Herath and Cammerer teaches generating the signal further based on the plurality of parameters (see at least figure 5 (530 or 540) in Herath).
Consider claim 3, Ebrahimzad in views of Herath and Cammerer teaches the machine-learning model associated with each of the bit-mapper models comprises one or more neural networks (see at introduction and section II in Cammerer).
Consider claim 4, 12 and 19, Ebrahimzad in views of Herath and Cammerer teaches wherein two or more of the plurality of sub-streams comprise different numbers of coded bits (see at least figure 2c (two or more sub-streams (c1, c2,…cm), paras. 15 and 143 in Herath, where Herath teaches two or more subsets of streams may comprise different number of bits).
Consider claim 7, Ebrahimzad in views of Herath and Cammerer teaches wherein the symbol-mapper model is a machine-learning model comprising one or more neural networks (see at introduction and section II in Cammerer)
Allowable Subject Matter
Claims 5, 13 and 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FITWI Y HAILEGIORGIS whose telephone number is (571)270-1881. The examiner can normally be reached M-F 10AM-6PM.
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FITWI Y. HAILEGIORGIS
Primary Examiner
Art Unit 2632
/FITWI Y HAILEGIORGIS/ Examiner, Art Unit 2632
Prosecution Insights