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 .
Claim Rejections - 35 USC § 102
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 1-2, 5-7, 10-12, 15-17 and 20-23 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Patent Pub. 2022/0149904 to Timo et al.
Considering claims 1, 11 and 16, Timo et al. show and disclose a user equipment (UE) for wireless communication (see Fig. 16 and section [0320]), comprising: one or more memories (see section [0082]); and one or more processors, coupled to the one or more memories (see section [0082]), configured to cause the device UE to: obtain a first channel state information (CSI) instance for a downlink channel (see Fig. 15 and section [0273]); encode, using a CSI encoder and based at least on one or more encoder weights that correspond to a trained neural network model, the first CSI instance into first encoded CSI, wherein the trained neural network model includes the CSI encoder and a CSI decoder (see Fig. 15 and sections [0268] through [0278] and [0287]); and
transmit the first encoded CSI to a network node as CSI feedback (see Figs. 5 and 14 and sections [0144] and [0253] to [0262]).
Considering claims 2, 12 and 17, and as applied to claims 1, 11, and 16 above, Timo et al. show and disclose a user equipment (UE) further configured to receive configuration information associated with the trained neural network model (see Figs. 3 and 4 and sections [0158] and [0263] through [0269]).
Considering claims 5, 15 and 20, and as applied to claims 1, 11, and 16 above, Timo et al. show and disclose a user equipment (UE), wherein the one or more processors, to cause the UE to encode the first CSI instance into the first encoded CSI, are configured to cause the UE to: generate the first encoded CSI as a compressed representation of the first CSI instance (see Fig. 15 and sections [0272] through [0277]).
Considering claim 6, and as applied to claim 1 above, Timo et al. show and disclose a user equipment (UE), wherein the one or more processors, to cause the UE to encode the first CSI instance into the first encoded CSI, are configured to cause the UE to: generate the first encoded CSI to have a smaller size than the first CSI instance (see Fig. 15 and sections [0272] through [0277]).
Considering claim 7, and as applied to claim 1 above, Timo et al. show and disclose a user equipment (UE) wherein the CSI instance includes one or more of a rank indicator (RI), one or more beam indices, a pre-coding matrix indicator (PMI), or a coefficient indicating an amplitude or phase (see section [0050]).
Considering claim 10, and as applied to claim 1 above, Timo et al. show and disclose a user equipment (UE) wherein the one or more processors, to cause the UE to encode the first CSI instance, are configured to: cause the UE to encode the first CSI instance into a binary sequence (see section [0276]).
Considering claim 21, and as applied to claim 1 above, Timo et al. show and describe a user equipment (UE) wherein the first encoded CSI is transmitted as a payload on a physical uplink shared channel (PUSCH) or a physical uplink control channel (PUCCH) (see Fig. 3 and section [0128]).
Considering claim 22, and as applied to claim 1 above, Timo et al. show and describe a user equipment (UE) wherein the first CSI instance comprises a downlink channel estimate based on a CSI reference signal (CSI-RS) (see section [0271]).
Considering claim 23, and as applied to claim 1 above, Timo et al. show and describe a user equipment (UE) wherein the CSI encoder is configured based at least in part on one or more encoder structures of the trained neural network model (see section [0291]).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
2. Claims 4, 14, 19 are rejected under 35 U.S.C. 103(a) as being unpatentable over U.S. Patent Pub. 2022/0149904 to Timo et al. in view of U.S. Patent Pub. 2022/0385336 to Yajnanarayana et al.
Regarding claims 4, 14 and 19 which recite “receive one or more encoder structures of the trained neural network model or the one or more encoder weights”, although Timo et al. teaches the specified structures, as it does not explicitly teach receiving the pre-trained structure to the UE, Yajnanarayana et al. is added.
In an analogous art, Yajnanarayana et al. discloses methods and devices for communication of measurement results in coordinated multipoint performed by a wireless device, radio access node and training agent. See Fig. 5 and section [0054], where it is taught “In step 504, the Radio Access node causes the representation of the encoder part of the autoencoder to be transmitted to a wireless device. This … may involve sending the representation of the encoder part to one or more managed TPs for transmission to the Wireless Device”.
Therefore, as both Timo et al. and Yajnanarayana et al. teach methods for communication of measurement results and as Yajnanarayana et al. explicitly teaches an encoder part being sent to a user equipment, it would have been obvious to one of ordinary skill in the art at or before the time of invention to modify Timo et al. by implementing the distribution of the pre-trained encoder segment to the user equipment as taught in Yajnanarayana et al.
This would simply be moving the operation from one device to another, as Timo et al. teach constructing the encoder on the user device itself.
Claim 8 is rejected under 35 U.S.C. 103(a) as being unpatentable over U.S. Patent Pub. 2022/0149904 to Timo et al. in view of U.S. Patent Pub. 2021/0144779 to Vahdat et al.
Regarding claim 8, which recites “wherein the one or more processors, to cause the UE to encode the CSI instance into encoded CSI, are configured to cause the UE to: encode the CSI instance into an intermediate encoded CSI, and encode the intermediate encoded CSI into the encoded CSI based at least in part on the intermediate encoded CSI and at least a portion of previously encoded CSI”, Vahdat is added.
In an analogous art, Vahdat discloses methods and devices for communication of CSI measurements. See for example, Fig. 9 steps 902 to 914, as described in sections [0106] to [0108] which teach generating a "first CSI" which is then fed back into the process (in steps 912 and/or 914, which therefore used as "intermediate" CSI, and then results in a "first encoded CSI which is based on previously encoded CSI and intermediate CSI", created and output in step 910, as now recited.
Therefore, as both Timo et al. and Vahdat et al. teach methods for CSI measurements, and as Vahdat et al. explicitly teaches using previously encoded CSI to form the current CSI, it would have been obvious to one of ordinary skill in the art at or before the time of invention to modify Timo et al. by implementing the CSI feedback of Vahdat, for the reasons as taught in Vahdat.
Claim 9 is rejected under 35 U.S.C. 103(a) as being unpatentable over U.S. Patent Pub. 2022/0149904 to Timo et al. in view of U.S. Patent Pub. 2021/0351885 to Chavva et al.
Regarding claim 9, which recites “wherein the CSI instance includes channel estimate and interference information, wherein the one or more processors, to cause the UE to encode the CSI instance, are configured to cause the UE to: encode the channel estimate into an encoded channel estimate, encode the interference information into encoded interference information, and jointly encode the encoded channel estimate and the encoded interference information into the first encoded CSI”, Chavva is added.
In an analogous art, Chavva teaches a wireless system which uses neural networks for CSI. See for example, Fig. 6B, and the "neural network 602c", which uses the previously obtained CSI weights (and their correlation to the currently obtained CSI) to encode new CSI information as described in section [0144]. See also sections [0091] to [0092], [0105] and [0118], of Chavva which teach measuring interference which is included in the CSI, as recited.
Therefore, as both Timo et al. and Chavva teach methods for CSI measurements, and as Chavva explicitly teaches using previously encoded CSI and interference to form the current CSI, it would have been obvious to one of ordinary skill in the art at or before the time of invention to modify Timo et al. by implementing the CSI feedback and interference of Chavva, for the reasons as taught in Chavva.
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/STEVEN S KELLEY/Primary Examiner, Art Unit 2646
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