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 .
DETAILED ACTION
This action is in response to filing on 11/29/2023.
Claims 1-30 are pending in this application.
Claims 1-30 are currently rejected.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/07/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement 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.
Claims 1-7, 9-14, 18-27, and 29-30 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Ryden (Pub. No.: US 2023/0370181 A1).
Regarding claim 1, Ryden teaches
An apparatus of a user equipment (UE) for wireless communication (Ryden [0088]: user equipment (UE) for wireless communication), comprising:
at least one memory (Ryden [0088]: memory); and
at least one processor coupled to the at least one memory (Ryden [0089]: memory providing instructions to be executed by the processor), wherein the at least one processor is configured to:
obtain information indicative of one or more configured performance values corresponding to interference prediction by the UE (Ryden fig. 9: 901 receiving configuration information to measure on a set of resources and predict interference measurement from said set of resources; Ryden [0080]: performance metric describing accuracy of historical predictions);
determine a recommended configuration of interference measurement resources (IMRs) and interference prediction resources for the interference prediction by the UE (Ryden fig. 9 and [0099]: measuring on a set of resources (IMRs) used for prediction of the future interference measurement on the set of resources (interference prediction resources); the configuration is changed by the network entity based on the predictions which were determined using the measurement on a set of resources), wherein the recommended configuration is associated with the one or more configured performance values and one or more performance capabilities of an interference prediction machine learning network associated with the UE (Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0080]: “the UE signals capabilities in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions”; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity); and
transmit, to the network entity, information indicative of the recommended configuration for the interference prediction by the UE (Ryden [0062] and fig. 9: 905 of fig. 9 shows the transmitting from the communication device (UE) to the network node (network entity) interference prediction information; Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0005]: network entity is able to use the information to change configuration (using the recommended configuration)).
Regarding claim 2, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the at least one processor is further configured to:
transmit, to the network entity, information indicative of the one or more performance capabilities of the interference prediction machine learning network (Ryden figs. 9, 10, and [0080]: the UE signals capabilities [to the network entity] in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity).
Regarding claim 3, Ryden teaches
The apparatus of claim 2 (the limitations of parent claim 2 as indicated above), wherein the one or more performance capabilities of the interference prediction machine learning network and the recommended configuration of IMRs and interference prediction resources are included in an interference prediction report transmitted to the network entity by the UE (Ryden [0043], [0074], fig. 9, and fig. 10: received user equipment (UE) data from measurement reports; Ryden figs. 9, 10, and [0080]: the UE signals capabilities [to the network entity] in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity).
Regarding claim 4, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the at least one processor is further configured to:
receive, from the network entity, in response to the recommended configuration transmitted by the UE, scheduling information corresponding to a plurality of IMRs and interference prediction resources scheduled for the UE by the network entity (Ryden fig. 10, [0106-0108]: 1005 “configure the communication device [UE] to report a condition [scheduling information] related to the at least one prediction of future interference to the network node [network entity]”, receiving information from the network entity in response to the recommendation transmitted by the UE (1003) to report a condition (scheduling information received)).
Regarding claim 5, Ryden teaches
The apparatus of claim 4 (the limitations of parent claim 4 as indicated above), wherein the at least one processor is further configured to:
determine, using the interference prediction machine learning network, a predicted interference value, wherein the predicted interference value is determined using the plurality of IMRs and interference prediction resources. (Ryden [0050]: predicted future interference values from signals; Ryden [0005]: machine learning, ML, model to predict a future interference measurement from the set of resources)
Regarding claim 6, Ryden teaches
The apparatus of claim 5 (the limitations of parent claim 5 as indicated above), wherein:
the one or more configured performance values includes a configured interference prediction accuracy threshold value (Ryden [0052], [0068], and [0080]: the UE can, e.g., indicate when it has created an accurate prediction mode) and a configured interference prediction confidence threshold value (Ryden [0056] and [0074]: the prediction can optionally include a confidence interval of the predicted interference estimate);
the predicted interference value is associated with an accuracy value greater than or equal to the configured interference prediction accuracy threshold value (Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network); and
the predicted interference value is associated with a confidence value greater than or equal to the configured interference prediction confidence threshold value (Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network).
Regarding claim 7, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the one or more configured performance values includes one or more of a configured prediction accuracy or a configured prediction confidence associated with the interference prediction by the UE (Ryden [0052] and [0068]: the UE can, e.g., indicate when it has created an accurate prediction mode; Ryden figs. 9, 10, and [0080]: the UE signals capabilities predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions).
Regarding claim 9, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the one or more configured performance values includes a minimum interference prediction accuracy for interference prediction using the interference prediction machine learning network (Ryden [0080]: “minimum value of the accuracy”), or a minimum interference prediction confidence for interference prediction using the interference prediction machine learning network.
Regarding claim 10, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the performance capabilities of the interference prediction machine learning network are indicative of a duration of time for which the one or more configured performance values are valid (Ryden [0057]: the UE sends the predictions periodically, wherein the network configures the associated periodic intervals (duration of time for predictions)).
Regarding claim 11, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the recommended configuration is indicative of a type of reference signal for the IMRs (Ryden [0050] (see types below)), and wherein the type of reference signal for the IMRs comprises one of Channel State Information (CSI)-Reference Signal (CSI-RS) (Ryden [0050]: CSI-RS), CSI-Interference Measurement (CSI-IM) (Ryden [0050]: CSI-IM; only one of the list is required per the claim language, multiple were mapped for the purpose of compact prosecution), Physical Downlink Shared Channel (PDSCH)-Demodulation Reference Signal (PDSCH-DMRS), or PDSCH-null tones.
Regarding claim 12, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the recommended configuration is indicative of one or more of a respective periodicity of the IMRs or a respective periodicity of the interference prediction resources. (Ryden [0057]: the UE sends the predictions periodically, wherein the network configures the associated periodic intervals)
Regarding claim 13, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the recommended configuration is indicative of a quantity of IMRs associated with each respective interference prediction resource of a plurality of interference prediction resources for the UE. (Ryden [0065]: selected set of resources (quantity of IMRs); [0050]: the network can request a UE to build a prediction model related to a certain resource, e.g. a set of resources not intended for any traffic in source cell)
Regarding claim 14, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein the recommended configuration is indicative of a time separation between IMRs and interference prediction resources scheduled for the UE by the network entity based on the recommended configuration. (Ryden [0052]: the gNB configures the UE to measure on a set of time-frequency resources. For example, where the UE serving cell are transmitting reference signals, or do not have any scheduled traffic, in order to enable the UE to predict a set of future interference values from neighboring nodes. The observation time can be a fixed time, or the UE can, e.g., indicate when it has created an accurate prediction model; [0062] Various embodiments of the present disclosure include receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource. The resource describes the signal type or time-frequency location where the UE should predict the interference magnitude.; [0071]: based on the UE capabilities, the gNB configures the UE of the time-frequency resources of which the UE can use for predicting a future interference value. For example, based on the time-frequency resources where there is no traffic in the UE serving cell.; [0074] In some embodiments, the gNB also configures a prediction reporting condition to the UE, for example: to report its predictions related to a future resource, such as related to a certain reference signal or related to a time-frequency resource represented by one or more sub-band indices plus a subframe number(s); to report periodical prediction of next T time-instances; to report a specific confidence interval of the predictions, for example, the UE reported confidence interval can be based on 90% certainty, or the predicted value is within the confidence interval range; and/or to report the predictions when certain configured conditions are met.)
Regarding claim 18, Ryden teaches
An apparatus of a network entity for wireless communication (Ryden [0090-0092] and [0092]: network node for wireless communication), comprising:
at least one memory (Ryden [0090-0092] and fig. 7: memory); and
at least one processor coupled to the at least one memory (Ryden [0090-0092] and fig. 7: processor coupled to memory), wherein the at least one processor is configured to:
transmit, to a user equipment (UE), information indicative of one or more configured performance values corresponding to interference prediction by the UE (Ryden fig. 9: 901/903 sending communication with configuration information to measure on a set of resources and predict interference measurement from said set of resources; Ryden [0080]: performance metric describing accuracy of historical predictions);
receive, from the UE, information indicative of a recommended configuration of interference measurement resources (IMRs) and interference prediction resources for the interference prediction by the UE (Ryden fig. 9 and [0099]: measuring on a set of resources (IMRs) used for prediction of the future interference measurement on the set of resources (interference prediction resources); the configuration is changed by the network entity based on the predictions received which were determined using the measurement on a set of resources), wherein the recommended configuration is associated with the one or more configured performance values and one or more performance capabilities of an interference prediction machine learning network associated with the UE (Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0080]: “the UE signals capabilities in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions”; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity); and
configure a plurality of IMRs and interference prediction resources for the UE based on the information indicative of the recommended configuration (Ryden [0062] and fig. 9: 905 of fig. 9 shows the transmitting from the communication device (UE) to the network node (network entity) interference prediction information; Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0005]: network entity is able to use the information to change configuration (using the recommended configuration)).
Regarding claim 19, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above), wherein the at least one processor is further configured to: receive, from the UE, information indicative of the one or more performance capabilities of the interference prediction machine learning network (Ryden figs. 9, 10, and [0080]: the UE signals capabilities [to the network entity] in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to be received by the network entity).
Regarding claim 20, Ryden teaches
The apparatus of claim 19 (the limitations of parent claim 19 as indicated above), wherein the performance capabilities of the interference prediction machine learning network are indicative of a future time slot where the interference prediction by the UE is associated with respective performance values below the one or more configured performance values.(Ryden [0071]: based on the UE capabilities, the gNB configures the UE of the time-frequency resources of which the UE can use for predicting a future interference value. For example, based on the time-frequency resources where there is no traffic in the UE serving cell.; [0074] In some embodiments, the gNB also configures a prediction reporting condition to the UE, for example: to report its predictions related to a future resource, such as related to a certain reference signal or related to a time-frequency resource represented by one or more sub-band indices plus a subframe number(s); to report periodical prediction of next T time-instances; to report a specific confidence interval of the predictions, for example, the UE reported confidence interval can be based on 90% certainty, or the predicted value is within the confidence interval range; and/or to report the predictions when certain configured conditions are met; Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network)
Regarding claim 21, Ryden teaches
The apparatus of claim 19 (the limitations of parent claim 19 as indicated above), wherein the at least one processor is configured to:
determine a second configuration of IMRs and interference prediction resources for the UE, wherein the second configuration is based on the performance capabilities of the interference prediction machine learning network, the one or more configured performance values, and at least a portion of the recommended configuration from the UE (Ryden [0102]: the at least one prediction of future interference received from the communication device based on a historical interference measurement (historical interference measurement being the first recommended configuration from the UE) comprises historical observations of the communication device of interference values from a specific resource, wherein the specific resource indicates a signal type or a time-frequency location where the communication device can predict an interference magnitude (in order to use the historical data for a second configuration, the first configuration would have had to have been previously calculated); Ryden [0099-0100]: changing a network configuration for the communication device based on the received at least one prediction of future interference, changing a network configuration includes a scheduling, an inter-frequency handover decision, an intra-frequency handover decision, or at least one link-adaptation setting).
Regarding claim 22, Ryden teaches
The apparatus of claim 21 (the limitations of parent claim 21 as indicated above), wherein, to configure the plurality of IMRs and interference prediction resources, the at least one processor is configured to:
transmit, to the UE, in response to the recommended configuration received from the UE, scheduling information indicative of the second configuration of IMRs and interference prediction resources. (Ryden [0099-0100]: changing a network configuration for the communication device based on the received at least one prediction of future interference, changing a network configuration includes a scheduling (via transmission to the UE), an inter-frequency handover decision, an intra-frequency handover decision, or at least one link-adaptation setting; Ryden [0058]: the UE's serving gNB uses said information to, e.g., configure its link-adaptation or scheduling decisions)
Regarding claim 23, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above), wherein: the one or more configured performance values includes a configured interference prediction accuracy threshold value (Ryden [0052], [0068], and [0080]: the UE can, e.g., indicate when it has created an accurate prediction mode) and a configured interference prediction confidence threshold value (Ryden [0056] and [0074]: the prediction can optionally include a confidence interval of the predicted interference estimate); and
the at least one processor is configured to receive, from the UE, a predicted interference value determined based on the plurality of IMRs and interference prediction resources (Ryden [0050]: predicted future interference values from signals; Ryden [0005]: machine learning, ML, model to predict a future interference measurement from the set of resources; Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network).
Regarding claim 24, Ryden teaches
The apparatus of claim 23 (the limitations of parent claim 23 as indicated above), wherein: the predicted interference value is associated with an accuracy value greater than or equal to the configured interference prediction accuracy threshold value (Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network); and the predicted interference value is associated with a confidence value greater than or equal to the configured interference prediction confidence threshold value (Ryden [0057]: the UE sends the predictions in an event triggered way, such as, the UE sends the predicted values only if the predicted values are above a threshold or below a threshold, or in between a first threshold and a second threshold, wherein the said thresholds and the said event is configured by the network).
Regarding claim 25, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above), wherein the recommended configuration is indicative of a type of reference signal for the IMRs (Ryden [0050] (see types below)), and wherein the type of reference signal for the IMRs comprises one of Channel State Information (CSI)-Reference Signal (CSI-RS) (Ryden [0050]: CSI-RS), CSI-Interference Measurement (CSI-IM) (Ryden [0050]: CSI-IM; only one of the list is required per the claim language, multiple were mapped for the purpose of compact prosecution), Physical Downlink Shared Channel (PDSCH)-Demodulation Reference Signal (PDSCH-DMRS), or PDSCH-null tones.
Regarding claim 26, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above), wherein the recommended configuration is indicative of one or more of a respective periodicity of the IMRs or a respective periodicity of the interference prediction resources. (Ryden [0057]: the UE sends the predictions periodically, wherein the network configures the associated periodic intervals)
Regarding claim 27, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above), wherein the recommended configuration is indicative of one or more of a quantity of IMRs associated with each respective interference prediction resource of a plurality of interference prediction resources for the UE, or a time separation between IMRs and interference prediction resources scheduled for the UE by the network entity based on the recommended configuration. (Ryden [0065]: selected set of resources (quantity of IMRs); [0050]: the network can request a UE to build a prediction model related to a certain resource, e.g. a set of resources not intended for any traffic in source cell; Ryden [0052]: the gNB configures the UE to measure on a set of time-frequency resources. For example, where the UE serving cell are transmitting reference signals, or do not have any scheduled traffic, in order to enable the UE to predict a set of future interference values from neighboring nodes. The observation time can be a fixed time, or the UE can, e.g., indicate when it has created an accurate prediction model; [0062] Various embodiments of the present disclosure include receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource. The resource describes the signal type or time-frequency location where the UE should predict the interference magnitude.; [0071]: based on the UE capabilities, the gNB configures the UE of the time-frequency resources of which the UE can use for predicting a future interference value. For example, based on the time-frequency resources where there is no traffic in the UE serving cell.; [0074] In some embodiments, the gNB also configures a prediction reporting condition to the UE, for example: to report its predictions related to a future resource, such as related to a certain reference signal or related to a time-frequency resource represented by one or more sub-band indices plus a subframe number(s); to report periodical prediction of next T time-instances; to report a specific confidence interval of the predictions, for example, the UE reported confidence interval can be based on 90% certainty, or the predicted value is within the confidence interval range; and/or to report the predictions when certain configured conditions are met.)
Regarding claim 29, Ryden teaches
A method for wireless communication by a user equipment (UE) (Ryden [0088]: user equipment (UE) for wireless communication), comprising:
obtaining information indicative of one or more configured performance values corresponding to interference prediction by the UE (Ryden fig. 9: 901 receiving configuration information to measure on a set of resources and predict interference measurement from said set of resources; Ryden [0080]: performance metric describing accuracy of historical predictions);
determining a recommended configuration of interference measurement resources (IMRs) and interference prediction resources for the interference prediction by the UE (Ryden fig. 9 and [0099]: measuring on a set of resources (IMRs) used for prediction of the future interference measurement on the set of resources (interference prediction resources); the configuration is changed by the network entity based on the predictions which were determined using the measurement on a set of resources), wherein the recommended configuration is associated with the one or more configured performance values and one or more performance capabilities of an interference prediction machine learning network associated with the UE (Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0080]: “the UE signals capabilities in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions”; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity); and
transmitting, to the network entity, information indicative of the recommended configuration for the interference prediction by the UE (Ryden [0062] and fig. 9: 905 of fig. 9 shows the transmitting from the communication device (UE) to the network node (network entity) interference prediction information; Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0005]: network entity is able to use the information to change configuration (using the recommended configuration)).
Regarding claim 30, Ryden teaches
A method for wireless communication by a network entity (Ryden [0090-0092] and [0092]: network node for wireless communication), comprising:
transmitting, to a user equipment (UE), information indicative of one or more configured performance values corresponding to interference prediction by the UE (Ryden fig. 9: 901/903 sending communication with configuration information to measure on a set of resources and predict interference measurement from said set of resources; Ryden [0080]: performance metric describing accuracy of historical predictions);
receiving, from the UE, information indicative of a recommended configuration of interference measurement resources (IMRs) and interference prediction resources for the interference prediction by the UE (Ryden fig. 9 and [0099]: measuring on a set of resources (IMRs) used for prediction of the future interference measurement on the set of resources (interference prediction resources); the configuration is changed by the network entity based on the predictions received which were determined using the measurement on a set of resources), wherein the recommended configuration is associated with the one or more configured performance values and one or more performance capabilities of an interference prediction machine learning network associated with the UE (Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0080]: “the UE signals capabilities in predicting a future interference measurement for a certain resource. The capabilities can also include a performance metric describing the accuracy of the historical predictions”; Ryden fig. 9, 10, and [0005-0007]: machine learning model for prediction and transmitting from the UE to the network entity); and
configuring a plurality of IMRs and interference prediction resources for the UE based on the information indicative of the recommended configuration (Ryden [0062] and fig. 9: 905 of fig. 9 shows the transmitting from the communication device (UE) to the network node (network entity) interference prediction information; Ryden [0062]: receiving interference predictions from the UE, based on the UE's historical observations of interference values from a specific resource; Ryden [0005]: network entity is able to use the information to change configuration (using the recommended configuration)).
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Ryden (Pub. No.: US 2023/0370181 A1) in view of Tang (Pub. No.: US 2017/0230137 A1).
Regarding claim 8, Ryden teaches
The apparatus of claim 7 (the limitations of parent claim 7 as indicated above),
While Ryden does teach a prediction accuracy value ([0052] and [0068]), Ryden does not explicitly recite a mean square error value.
However, Tang, in the analogous art of interference prediction, teaches
wherein the configured prediction accuracy comprises a configured threshold value of a Mean Square Error (MSE) associated with the interference prediction by the UE (Tang [0118]: mean square error used, associated with interference prediction as those values are used in interference prediction [0017-0020], further, the term associated can be to any degree, and the value is calculated in the process for interference prediction and is therefore associated).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ryden to incorporate the teachings of Tang and have the configured prediction accuracy comprises a configured threshold value of a Mean Square Error (MSE) associated with the interference prediction by the UE. Doing so would allow the value to be used for SINR prediction (Tang [0118]).
Claims 15-17 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Ryden (Pub. No.: US 2023/0370181 A1) in view of Marzban (Pub. No.: US 2023/0299815 A1).
Regarding claim 15, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein, to transmit the information indicative of the recommended configuration, the at least one processor is configured to…
While Ryden does disclose RRC messaging, Ryden does not explicitly recite static reporting using an RRC message.
However, Marzban, in the analogous art of interference prediction, teaches
perform static reporting using a Radio Resource Control (RRC) message indicative of the recommended configuration (Marzban [0087]: RRC message for static configuration).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ryden to incorporate the teachings of Marzban and perform static reporting using a Radio Resource Control (RRC) message indicative of the recommended configuration. Doing so would allow for interference prediction communications to be indicated between the BS and UE (Marzban [0087]).
Regarding claim 16, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein, to transmit the information indicative of the recommended configuration,…
Ryden does not appear to teach reporting using a MAC-CE.
However, Marzban, in the analogous art of interference prediction, teaches
the at least one processor is configured to perform semi-static reporting using a Media Access Control (MAC)-Control Element (MAC-CE) indicative of the recommended configuration (Marzban [0087]: MAC-CE for semi-static configuration).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ryden to incorporate the teachings of Marzban and perform semi-static reporting using a Media Access Control (MAC)-Control Element (MAC-CE) indicative of the recommended configuration. Doing so would allow for interference prediction communications to be indicated between the BS and UE (Marzban [0087]).
Regarding claim 17, Ryden teaches
The apparatus of claim 1 (the limitations of parent claim 1 as indicated above), wherein, to transmit the information indicative of the recommended configuration,…
Uplink communications disclosed, use of dynamic reporting using UCI is not explicitly taught.
However, Marzban, in the analogous art of interference prediction, teaches
the at least one processor is configured to perform dynamic reporting using Uplink Control Information (UCI) indicative of the recommended configuration (Marzban [0087]: carries UCI).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ryden to incorporate the teachings of Marzban and perform dynamic reporting using Uplink Control Information (UCI) indicative of the recommended configuration. Doing so would allow for carrying of uplink information such as scheduling requires, CQI, or feedback (Marzban [0082]).
Regarding claim 28, Ryden teaches
The apparatus of claim 18 (the limitations of parent claim 18 as indicated above),
Ryden does not appear to explicitly state that the information indicative of the recommended configuration is included in a Radio Resource Control (RRC) message, a Media Access Control (MAC)-Control Element (MAC-CE), or Uplink Control Information (UCI) received from the UE.
However, Marzban, in the analogous art of interference prediction, teaches
wherein the information indicative of the recommended configuration is included in a Radio Resource Control (RRC) message (Marzban [0087]: RRC message), a Media Access Control (MAC)-Control Element (MAC-CE), or Uplink Control Information (UCI) received from the UE.
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ryden to incorporate the teachings of Marzban and have the information indicative of the recommended configuration included in a Radio Resource Control (RRC) message, a Media Access Control (MAC)-Control Element (MAC-CE), or Uplink Control Information (UCI) received from the UE. Doing so would allow for interference prediction communications to be indicated between the BS and UE (Marzban [0087]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Bai (Pub. No.: US 2020/0259575 A1) discloses prediction of future channel conditions based on a set of measurements as well as indication of communication parameters.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHEL E MARKS whose telephone number is (703)756-1309. The examiner can normally be reached Mon-Fri 8:30am-6pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Charles C Jiang can be reached at (571)270-7191. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/R.E.M./Examiner, Art Unit 2412 /CHARLES C JIANG/Supervisory Patent Examiner, Art Unit 2412