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
2. Claims 1, 7, 8, 14, 15 and 21 are amended. Claim 22-23 are added. Claims 1, 3-8, 10-15 and 17-23 are pending.
Response to Arguments
Applicant’s arguments, filed on 3/2/2026 with respect to claims 1, 3-8, 10-15 and 17-21, have been considered but are moot in view of new grounds of rejection.
Claim Rejections - 35 USC § 103
4. 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 of this title, 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.
5. Claims 1, 3-5, 7-8, 10-12, 14-15, 17-19 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Jassal et al. (US. Pub. No. 2020/0366326 A1) in view of Chavva et al. (US. Pub. No. 2021/0351885 A1).
Regarding claim 1, Jassal discloses a method for information processing (See Abstract), applied to a user equipment (UE) (See Fig. 1; UE 102), the method comprising:
sending a target information indication (See Par. [52], [76], [87] of Jassal for a reference to the UE estimates the channel conditions and transmits a CSI report to the network side),
wherein an indication way to indicate the target information indication is a first type of target information indication way or a second type of target information indication way (See Par. [52], [57]-[58], [60]-[61] of Jassal for a reference to that two ways are indicated to transmit the CSI report from the UE to the network side based on the UE capability. If the UE is capable to support Artificial Intelligence (AI) tasks [When parameters are configured on the UE’s AI module SIM card], the CSI is reported using the AI module. Otherwise, the CSI is reported without using the AI module), and sending first information (See Par. [76] of Jassal for a reference to the AI-capable UE responds to the network with a UE capability response message indicating its AI capability for communication purposes), wherein the first information is configured to indicate whether the UE utilizes the first type of target information indication way to send the target information indication (See Par. [70], [76]-[77], [98] and Fig. 6-7 of Jassal for a reference to sending a UE capability response message indicating whether AI module is activated or not. The UE uses default parameters stored in its internal memory to configure its AI module for a given task. Task is performed using the AI module if it was activated based on the configured parameters).
Jassal does not explicitly disclose wherein the method further comprises: receiving third information, wherein the third information comprises configuration parameters used at the network side; and determining the indication way of the target information indication based on the third information, the target information being channel state information (CSI).
However, Chavva discloses wherein the method further comprises: receiving third information, wherein the third information comprises configuration parameters used at the network side (See Par. [107], [149] and Fig. 2 & 8 of Chavva for a reference to receiving a feedback configuration, by the UE 601, from the gNB 607 (Fig. 8; Step 801), which includes feedback configuration parameters for CSI-RS, including at least one Information Element (IE) such as CSI-MeasConfig, CSI-ResourceConfig, and CSI-ReportConfig); and
determining the indication way of the target information indication based on the third information, the target information being channel state information (CSI) (See Par. [33], [54], [190]-[194] and Fig. 17 of Chavva for a reference to that based on the received feedback configuration parameters, the UE determines a plurality of radio parameters for a connection between the UE and the gNB, and computes, by a neural network (602c) in the UE, values of CSI feedback parameters, and generates, by the neural network (602c), a CSI report. The neural network (602c) of the UE determines whether online training is enabled or not. CSI report is generated according to the determination).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the teaching of Chavva to Jassal. The motivation for combination would be to improve the system’s performance, by improving the accuracy of prediction and increase the optimality of the CSI report by predicting probable values of the feedback parameters at future time instances, using the at least one ML based model, and including the predicted feedback parameters in the CSI report. (Chavva; Par. [86])
Regarding claim 3, the combination of Jassal and Chavva, specifically Jassal discloses wherein the sending the target information indication comprises:
utilizing the first type of target information indication way to send the target information indication when the UE has an ability to support the first type of target information indication way (See Par. [52], [57]-[58], [60]-[62] and Fig. 6 of Jassal for a reference that based on the capability response message sent by the UE, it is determined if the UE supports AI tasks. If a SIM card with configured parameters is installed on the UE’s AI module, it is activated, and the CSI report is transmitted using the AI module); and
utilizing the second type of target information indication way to send the target information indication when the UE does not have the ability to support the first type of target information indication way (See Par. [57]-[58], [60]-[62] and Fig. 6 of Jassal for a reference that based on the capability response message sent by the UE, it is determined if the UE supports AI tasks. If a SIM card with configured parameters is not installed on the UE’s AI module, it is not activated, and the CSI report is transmitted without using the AI module).
Regarding claim 4, the combination of Jassal and Chavva, specifically Jassal discloses wherein the first type of target information indication way represents an artificial intelligence (AI)-based channel state information indication way (See Par. [57]-[61], [64] and Fig. 6 of Jassal for a reference that upon the activation of the Artificial Intelligence (AI) module, it is determined that the UE supports the AI tasks. In this case the CSI report is transmitted to the network side using the AI module); and
the second type of target information indication way represents a non-AI-based channel state information indication way (See Par. [57]-[58], [60]-[62] and Fig. 6 of Jassal for a reference that if the AI module is not activated [SIM card with configuration parameters is not installed on the AI module], it is determined that the UE does not support the AI tasks. In this case the CSI report is transmitted to the network side without using the AI module).
Regarding claim 5, the combination of Jassal and Chavva, specifically Jassal discloses wherein the first information is carried by one of the following information: UE capability information, information comprised in a random access process, radio resource control (RRC) signaling and uplink control information (UCI) (See Par. [53], [76]-[77], [102] of Jassal for a reference to the first information that indicates the UE capability to support the AI tasks is exchanged with the network side in a UE capability message that may be an RRC message).
Regarding claim 7, the combination of Jassal and Chavva, specifically Jassal discloses method of claim 1, further comprising:
wherein the third information further comprises at least one of the followings: an indication of a way to send the target information indication; whether a network side has an ability to support the first type of target information indication way; or capabilities that the network side has (See Par. [77], [81] of Jassal for a reference to the higher layer signaling 134 containing task assignment to and configuration of the AI module), wherein the third information comprises a first bit or a second bit, wherein the first bit is used to directly indicate the target information indication way; the second bit is used to indicate configuration parameters used at the network side or all capabilities of the network side, the UE determines whether the network side has the ability to support the first type of target information indication way based on the second bit (See Par. [77], [81]-[82] and Fig. 7 of Jassal for a reference to the network sends higher layer signalling at 134 containing task assignment to the AI module [information bit that indicates the UE capability to support AI, which is the first target indication way; First bit option is selected and cited])
Regarding claim 8, the claim is interpreted and rejected for the same reason as set forth in claim 1, including a user equipment (UE) (See Jassal; Fig. 11A; UE 1310), comprising: a memory (See Jassal; Fig. 11A; Memory 1408); a transceiver (See Jassal; Fig. 11A; Transceiver 1402); and a processor coupled to the memory and the transceiver (See Jassal; Fig. 11A; Processor 1400).
Regarding claim 10, the claim is interpreted and rejected for the same reason as set forth in claim 3.
Regarding claim 11, the claim is interpreted and rejected for the same reason as set forth in claim 4.
Regarding claim 12, the claim is interpreted and rejected for the same reason as set forth in claim 5.
Regarding claim 14, the claim is interpreted and rejected for the same reason as set forth in claim 7.
Regarding claim 15, Jassal discloses a network device (See Jassal; Fig. 11B; BS 1370), comprising: a memory (See Jassal; Fig. 11B; Memory 1458); a transceiver (See Jassal; Fig. 11B; Tx 1452 & Rx 1454); and a processor coupled to the memory and the transceiver (See Jassal; Fig. 11B; Processor 1450), wherein the transceiver is configured for:
receiving a target information indication, wherein an indication way to indicate the target information indication is a first type of target information indication way or a second type of target information indication way (See Par. [60]-[62], [76]-[77] and Fig. 6-7 of Jassal for a reference to receiving, from the UE, a UE capability response message indicating whether AI module is activated or not. It is activated when parameters are configured on the SIM card installed on the AI module. In this case the CSI report is sent using the AI module. It is not activated when parameters are not configured on the SIM card installed on the AI module. In this case, AI is not supported, and the CSI report is sent without using the AI module);
receiving first information (See Par. [76] of Jassal for a reference to the network device receives, from AI-capable UE, a UE capability response message indicating its AI capability for communication purposes), wherein the first information is configured to indicate whether the UE utilizes the first type of target information indication way to send the target information indication (See Par. [70], [76]-[77], [98] and Fig. 6-7 of Jassal for a reference to sending a UE capability response message indicating whether AI module is activated or not. The UE uses default parameters stored in its internal memory to configure its AI module for a given task. Task is performed using the AI module if it was activated based on the configured parameters); and
obtaining target information from the target information indication by utilizing an obtaining way corresponding to the first type of target information indication way or by utilizing an obtaining way corresponding to the second type of target information indication way (See Par. [52], [57]-[58], [60]-[62] and Fig. 6 of Jassal for a reference that based on the capability response message sent by the UE, it is determined if the UE supports AI tasks. If a SIM card with configured parameters is installed on the UE’s AI module, it is activated, and the CSI report is received using the AI module of the UE. If a SIM card with configured parameters is not installed on the UE’s AI module, it is not activated, and the CSI report is received without using the AI module of the UE).
Jassal does not explicitly disclose wherein the method further comprises: receiving third information, wherein the third information comprises configuration parameters used at the network side; and determining the indication way of the target information indication based on the third information, the target information being channel state information (CSI).
However, Chavva discloses wherein the method further comprises: receiving third information, wherein the third information comprises configuration parameters used at the network side (See Par. [107], [149] and Fig. 2 & 8 of Chavva for a reference to receiving a feedback configuration, by the UE 601, from the gNB 607 (Fig. 8; Step 801), which includes feedback configuration parameters for CSI-RS, including at least one Information Element (IE) such as CSI-MeasConfig, CSI-ResourceConfig, and CSI-ReportConfig); and
determining the indication way of the target information indication based on the third information, the target information being channel state information (CSI) (See Par. [33], [54], [190]-[194] and Fig. 17 of Chavva for a reference to that based on the received feedback configuration parameters, the UE determines a plurality of radio parameters for a connection between the UE and the gNB, and computes, by a neural network (602c) in the UE, values of CSI feedback parameters, and generates, by the neural network (602c), a CSI report. The neural network (602c) of the UE determines whether online training is enabled or not. CSI report is generated according to the determination).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the teaching of Chavva to Jassal. The motivation for combination would be to improve the system’s performance, by improving the accuracy of prediction and increase the optimality of the CSI report by predicting probable values of the feedback parameters at future time instances, using the at least one ML based model, and including the predicted feedback parameters in the CSI report. (Chavva; Par. [86])
Regarding claim 17, the combination of Jassal and Chavva, specifically Jassal discloses wherein the transceiver is further configured for: determining, based on the first information, the indication way of the target information indication (See Par. [52], [57]-[58], [60]-[62] and Fig. 6 of Jassal for a reference that based on the capability response message sent by the UE, it is determined if the UE supports AI tasks. If a SIM card with configured parameters is installed on the UE’s AI module, it is activated, and the CSI report is transmitted using the AI module).
Regarding claim 18, the claim is interpreted and rejected for the same reason as set forth in claim 4.
Regarding claim 19, the claim is interpreted and rejected for the same reason as set forth in claim 5.
Regarding claim 21, the claim is interpreted and rejected for the same reason as set forth in claim 7.
6. Claims 6, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Jassal et al in view of Chavva et al. and further in view of Liang et al. (US. Pub. No. 2021/0076303 A1).
Regarding claim 6, the combination of Jassal and Chavva does not explicitly disclose wherein the information comprised in the random access process comprises one of the followings: Message A in a two-step random access process; Msg1 in a four-step random access process; and Msg3 in the four-step random access process.
However, Liang discloses wherein the information comprised in the random access process comprises one of the followings: Message A in a two-step random access process; Msg1 in a four-step random access process; and Msg3 in the four-step random access process (See Par. [140], [238], [240]-[242] of Jassal for a reference to the UE sends a first signaling to the network side in a random access (RACH) process. The first signaling is a message 1 (Msg1) type. The information carried in the first signaling is the AI value based on the UE capability).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the teaching of Liang to the combination of Jassal and Chavva. The motivation for combination would be to improve the system’s performance by increasing the quantity of UEs that are allowed to access the network through increasing the UEs’ configuration diversity. (Liang; Par. [137])
Regarding claim 13, the claim is interpreted and rejected for the same reason as set forth in claim 6.
Regarding claim 20, the claim is interpreted and rejected for the same reason as set forth in claim 6.
7. Claims 22-23 are rejected under 35 U.S.C. 103 as being unpatentable over Jassal et al in view of Chavva et al. in view of Ji et al. (US. Pub. No. 2019/0373592 A1) and further in view of Yao et al. (US. Pub. No. 2019/0050711 A1).
Regarding claim 22, Jassal discloses wherein the method further comprises: receiving at least one set of parameter information (See Par. [14], [66], [68] and Fig. 2; 211 of Jassal for a reference to the UE receives a push message carrying AI module configuration parameters from the network side); wherein the parameter information is neural network parameter information that is used when the UE utilizes the first type of target information indication way (See Par. [60]-[70] and Fig. 6-7 of Jassal for a reference to that when the UE is turned on, The UE checks if AI (Neural) capabilities are supported by the UE. If yes, the AI-based parameters, configured by the network, is used and AI module is activated).
The combination of Jassal and Chavva does not explicitly disclose wherein in a case that at least two sets of parameter information are received at the UE, the method further comprises: receiving a first notification configured to notify the parameter information that is activated; wherein the neural network parameter information comprises at least one of: convolution kernel information, a step size of convolution kernel or pooling layer parameters.
However, Ji discloses wherein in a case that at least two sets of parameter information are received at the UE, the method further comprises: receiving a first notification configured to notify the parameter information that is activated (See Par. [141]-[142], [173] of Ji for a reference to several possible parameter sets [four possible parameter sets] may be configured by using higher layer signaling such as radio resource control (RRC) signaling. The network device sends physical layer signaling [DCI signaling] to activate parameter set from the four possible parameter sets. Therefore, the UE can determine an activated parameter set in the plurality of parameter sets).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the teaching of Ji to the combination of Jassal and Chavva. The motivation for combination would be to improve the system’s performance, by determining spatial information for transmitting an uplink signal through the configuration received from the network device. (Ji; Par. [54])
The combination of Jassal, Chavva and Ji does not explicitly disclose wherein the neural network parameter information comprises at least one of: convolution kernel information, a step size of convolution kernel or pooling layer parameters.
However, Yao discloses wherein the neural network parameter information comprises at least one of: convolution kernel information, a step size of convolution kernel or pooling layer parameters (See Par. [66], [108] of Yao for a reference to parameter information of the convolutional neural network includes among other parameters: weights of a pooling layer, size of the convolution kernel of each convolution layer, number of pooling layers, size of each pooling layer, number of fully connected layers and size of each fully connected layer).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the teaching of Yao to the combination of Jassal, Chavva and Ji. The motivation for combination would be to improve the system’s performance, by improving the ability of generalization of the neural network, when a preset number of neurons among the neurons of the fully connected layer are discarded at each iteration. (Yao; Par. [107])
Regarding claim 23, the claim is interpreted and rejected for the same reason as set forth in claim 22.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bedekar et al. (US. Pub. No. 2020/0252142 A1) discloses techniques for secondary cell selection in wireless communication systems.
Lin et al. (US. Pub. No. 2020/0163590 A1) discloses a fall detection method, device and system.
Zhang et al. (US. Pub. No. 2018/0220425 A1) discloses a resource allocation method, an apparatus, and a wireless access system.
9. 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 extension fee 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 date of this final action.
10. Any inquiry concerning this communication from the examiner should be directed to RASHA FAYED whose telephone number is (571) 270-3804. The examiner can normally be reached on M-F 8:00AM-4:30PM.
If attempts to reach the examiner by telephone are unsuccessful, the supervisory Examiner, Un Cho can be reached on (571)272-7919. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/R.K.F/Examiner, Art Unit 2413
/UN C CHO/Supervisory Patent Examiner, Art Unit 2413
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