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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/11/24 is being considered by the examiner.
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.
Claim(s) 1- is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Song et al. (US 2024/0422629) in view of Kim (WO 2024/039149).
Regarding claim 1, Song teaches an apparatus (UE) for wireless communications, comprising:
at least one memory comprising instructions; and
at least one processor configured to execute the instructions and cause the apparatus to:
obtain one or more channel measurements (AI model input information) corresponding to a first beam (signal/beam quality) received from a first serving cell (serving cell) (see “Step 201: User equipment UE receives a measurement reporting configuration sent by a network-side device” [par 45] and “In this embodiment of this application, the measurement reporting configuration includes at least one of the following:…AI model input information…” [par 46] and “Optionally, in this embodiment of this application, the AI model input information includes at least one of the following: signal quality of a serving cell of the network side device and/or signal quality of a neighboring cell of the UE at a target time…or a beam angle and beam quality of the UE at the target time and/or a historical time” [par 49] which suggests that UE obtains AI model input information which may include measurements of signal quality and/or beam quality of a serving cell);
determine, based on the one or more channel measurements, one or more parameters (predicted signal/beam quality) corresponding to a second serving cell (neighboring cell) (see “Optionally, in this embodiment of this application, the AI model output information includes at least one of the following: at least one predicted signal quality…or at least one beam quality, where the at least one predicted signal quality is signal quality of the serving cell of the network-side device and/or signal quality of the neighboring cell of the UE at at least one first time…” [par 50] which suggests UE determines a predicted signal quality and/or beam quality of a neighboring cell based on the AI model input information); and
transmit, based on the one or more parameters, an uplink signal (random access request) to the second serving cell (see “Step 302: The UE initiates a random access request to the target cell according to the handover command, where the random access request is used for requesting access to
the target cell” [par 80]).
Regarding claim 2, Song teaches the apparatus of claim 1, wherein the at least one processor is configured to determine the one or more parameters corresponding to the second serving cell based on a linkage (AI model) between the one or more channel measurements corresponding to the first beam and the one or more parameters corresponding to the second serving cell (the AI model [par 49-50] reads on the claimed “linkage between the one or more channel measurements corresponding to the first beam and the one or more parameters corresponding to the second serving cell” because it is used to infer or derive the predicted beam quality of the neighboring cell from the signal quality of the serving cell).
Regarding claim 3, Song teaches the apparatus of claim 2, wherein the linkage is based on a table or function that maps the one or more channel measurements corresponding to the first beam to the one or more parameters corresponding to the second serving cell (the AI model [par 49-50] may be stored in a table or perform a function).
Regarding claim 4, Song teaches the apparatus of claim 1, wherein the first beam is associated with a first frequency and the uplink signal is associated with a second frequency (see “Optionally, in this embodiment of this application, the AI model input information includes at least one of the following:… current frequency information of the UE and/or other frequency information or radio access technology RAT information…” [par 49] which suggests the serving cell and neighboring cell may operate in differing frequencies).
Regarding claim 5, Song teaches the apparatus of claim 1, wherein the first serving cell is associated with a master cell group (MCG) and the second serving cell is associated with a secondary cell group (SCG) (see “It should be noted that in the embodiments of this application, only a base station in an NR system is used as an example for description, but a specific type of the base station is not limited” [par 22] which suggests the serving cell and/or neighboring cell may be associated with a MCG/SCG since MCG and SCG refer to frameworks of a NR system).
Regarding claim 6, Song teaches the apparatus of claim 1, wherein the one or more channel measurements include at least one of a reference signal received power (RSRP), a received signal strength indicator (RSSI), a reference signal quality (RSRQ), a power delay profile (PDP), an angle of arrival, and a channel quality indicator (CQI) (see “Optionally, in this embodiment of this application,
the signal quality includes at least one of the following: reference signal received power (RSRP), reference signal received quality (RSRQ), or a signal to interference plus noise ratio (SINR)” [par 57]).
Regarding claim 7, Song teaches the apparatus of claim 1, wherein the one or more parameters include at least one of an angle of arrival, an angle of departure, an angular spread, a synchronization signal block (SSB) index, and a channel state information reference signal (CSI-RS) resource identifier (the beam quality [par 50] may include the claimed “one or more parameters” since they are beam parameters).
Regarding claim 8, Song teaches the apparatus of claim 1, wherein the uplink signal includes a random access channel (RACH) message (see “Step 302: The UE initiates a random access request
to the target cell according to the handover command, where the random access request is used for requesting access to the target cell” [par 80]).
Regarding claim 9, Song teaches the apparatus of claim 1, wherein the at least one processor is further configured to cause the apparatus to:
identify, based on the one or more parameters, a plurality of beams associated with the second serving cell (see “…AI model output information includes….at least one beam quality….of the neighboring cell…” [par 50] which suggests at least one or “a plurality of beams associated with the second serving cell”);
obtain at least one channel measurement corresponding to the plurality of beams (see “Optionally, in this embodiment of this application, the signal quality includes at least one of the following: reference signal received power (RSRP), reference signal received quality (RSRQ), or a signal to interference plus” which suggests in combination with par 50 that the predicted signal/beam quality is a measurement value); and
select at least one beam from the plurality of beams for transmitting the uplink signal to the second serving cell (see “Optionally, in this embodiment of this application, the target cell may be selected by the UE based on the inference result, or configured by the network-side device for the UE based on the received inference result” [par 79]).
Regarding claim 10, Song teaches the apparatus of claim 1, wherein the at least one processor is further configured to cause the apparatus to:
transmit the one or more parameters (measurement report) to the first serving cell (see “…perform AI model inference on at least one neighboring cell based on the AI model input and output information in the network-side device and the AI model inference trigger condition, determine, based on the inference result, whether to trigger measurement reporting, and then report a measurement report when a predicted signal or a real signal meets a condition…” [par 76]);
receive, from the first serving cell, an indication of a plurality of beams associated with the second serving cell, wherein the indication is based on the one or more parameters (Optionally, in this embodiment of this application, the target cell may be selected by the UE based on the inference result, or configured by the network-side device for the UE based on the received inference result” [par79] which suggests handover candidate cells may be configured by UE based on the received inference result);
obtain at least one channel measurement corresponding to the plurality of beams (see “Optionally, in this embodiment of this application, the target cell may be selected by the UE based on the inference result, or configured by the network-side device for the UE based on the received inference result” [par 79] and “In a possible implementation, the inference result includes at least one of the following: predicted signal quality of the at least one handover candidate cell within the total duration of the AI model prediction output or real signal quality of the at least one handover candidate cell” [par 141] which in combination suggests the inference result includes real signal quality of the at least one handover candidate or “plurality of beams”); and
select at least one beam from the plurality of beams for transmitting the uplink signal to the second serving cell (see “Optionally, in this embodiment of this application, the target cell may be selected by the UE based on the inference result, or configured by the network-side device” [par 79]).
Regarding claim 11, Song teaches the apparatus of claim 1, wherein the at least one processor is further configured to cause the apparatus to:
transmit the one or more parameters (measurement report) to the first serving cell (see “…perform AI model inference on at least one neighboring cell based on the AI model input and output information in the network-side device and the AI model inference trigger condition, determine, based on the inference result, whether to trigger measurement reporting, and then report a measurement report when a predicted signal or a real signal meets a condition…” [par 76]);
receive, from the first serving cell, an indication of a preferred beam (inference result) associated with the second serving cell, wherein the indication is based on the one or more parameters (see “Optionally, in this embodiment of this application, the target cell may be selected by the UE based on the inference result, or configured by the network-side device for the UE based on the received inference result” [par 79]); and
select the preferred beam for transmitting the uplink signal to the second serving cell (see par 79 which suggests UE selects target cell based on inference result).
Regarding claim 12, Song teaches the apparatus of claim 1, wherein the at least one processor is further configured to cause the apparatus to:
determine, based on the one or more channel measurements, one or more additional parameters corresponding to a third serving cell (see “…the UE performs AI model inference on the neighboring cell B and the neighboring cell C based on the measurement reporting configuration” [par 119] which suggests the UE performs inference for neighboring cell C and neighboring cell B which reads on the claimed “third serving cell”).
Regarding claim 13, Song teaches the apparatus of claim 12, wherein the at least one processor is further configured to cause the apparatus to:
transmit the one or more additional parameters (signal quality prediction values of neighboring cell B/C and a corresponding cell identifier associated with the third serving cell to the first serving cell (see “Step 44: The UE obtains signal quality prediction values of the serving cell of the network-side device, and the neighboring cell B and the neighboring cell C at each time li.t within a time tsub3 ~tsub3+T through inference, and reports a third measurement report to the network-side device” [par 12]).
Regarding claim 14, Song teaches the apparatus of claim 1, wherein the at least one processor is further configured to cause the apparatus to:
obtain one or more additional channel measurements corresponding to a second beam received from a third serving cell (see “the UE performs AI model inference on the neighboring cell B and the neighboring cell C based on the measurement reporting configuration” [par 119] wherein real measurements are used to determine the inference).
Regarding claim 15, Song teaches the apparatus of claim 14, wherein the first beam and the second beam are associated with different frequencies (see “Optionally, in this embodiment of this application, the AI model input information includes at least one of the following:… current frequency information of the UE and/or other frequency information or radio access technology RAT information…” [par 49] which suggests the serving cell and neighboring cell(s) may operate in differing frequencies).
Claims 16 and 30 recite subject matter similar to claim 1 and is therefore rejected on the same basis.
Claims 17-29 recite subject matter similar to claim 2-15 respectively and are therefore rejected on the same basis of the respective claim.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nam T Huynh whose telephone number is (571)272-5970. The examiner can normally be reached 9am-5pm.
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/NAM T HUYNH/Primary Examiner, Art Unit 2647
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