DETAILED ACTION
This office action is a response to the amendment and arguments filed on June 29, 2026.
Claims 1, 2, 4, 6-12, 14 and 16-20 are pending.
Claims 1, 2, 4, 6-12, 14 and 16-20 are rejected.
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 Arguments
Applicant’s arguments with respect to claim(s) 1, 2, 4, 6-12, 14 and 16-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The rejection has been revised and set forth below according to the amended claims (See Office Action).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, 7, 10, 11, 14, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ryden et al. U.S. Patent Application Publication 2023/0370181, hereinafter Ryden, in view of Li et al. WIPO Publication WO 2024/065372, hereinafter Li.
Regarding Claim 1, Ryden discloses a method implemented by a wireless transmit receive unit (WTRU), the method (Abstract; Figure 1-3, 5-8, 11-21) comprising:
receiving from a network an indication of a time instance of a historical reference Interference Measurement Resource (IMR) set or an indication of a coefficient for interference scaling relative to historical reference set; Determining historical channel measurements based on a plurality of measurement resources (Paragraph [0005-0007] Configuring the communication device to measure on a set of resources and to build a machine learning model to predict future interference measurements from the set of resources; Paragraph [0062, 0102-0104] Receiving interference prediction 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; In some embodiments, the set of resources take into account historical information of a communication device or a communication device related configuration.).
determining a CSI prediction value for a future CSI prediction instance based on the historical channel measurements (Paragraph [0107] the configuring (901) includes a configuration of at least one of the following: a time-frequency resource for use in predicting the at least one prediction of future interference, indicating to the communication device to build the at least one prediction of future interference using a transmitted reference signal of the communication device, a resource used for a periodic Channel State Information Interference Measurement, CSI-IM, and indicating to the communication device to build the ML model based on historical interference of the communication device with a neighboring network node);
determining a quality-based metric for the future CSI prediction instance based on (i) the historical channel measurements and (ii) the time instance of the historical reference IMR or the coefficient for interference scaling relative to the historical reference set (Paragraph [0083-0122] In some embodiments, an interference prediction report can comprise a predicted time-instance. For example: subframe number, slot index, and system frame number. Or an absolute time using Coordinated Universal Time (UTC); a predicted time-window; predicted resources; a predicted reference signal (e.g. SSB, CSI-RS); predicted time-frequency resources; a predicted interference value using the available reporting metrics (e.g., SINR, RSRQ, RSRP, RSSI, CQI, Interference plus Noise estimate); a probability that the interference power is above or below a certain threshold value; a predicted throughput value or throughput increase or decrease based on the predicted interference and the current serving cell quality in terms of serving cell link beam quality (serving cell CSI); a predicted throughput value or throughput increase or decrease based on the predicted interference and the predicted current serving cell quality in terms of serving cell link beam quality (serving cell CSI); a confidence interval of the predicted interference value, for example that the predicted value is within a certain interval with 90% probability or a standard deviation value of the predicted information, etc; In some embodiments, the at least one prediction of future interference based on a historical interference measurement 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. The method further includes signaling (1203), to the network node, an indication that the communication device is able to use the ML model to learn which signals are from a neighboring network node and from the serving network node, respectively, wherein indication is based on the communication device observing at least one of a reference signal received power, RSRP, measurement, a reference signal received quality, RSRQ, measurement, and a reference signal strength indicator, RSSI, measurement over a time period).
Ryden readily discloses reception of an indication of a time instance of historical reference Interference Measurement resource set and determining historical measurements, CSI prediction and quality based metrics for future CSI predictions but may not get into specific detail regarding determining historical channel measurements based on a plurality of measurement resources; determining a CSI prediction value for a future CSI prediction instance based on the historical channel measurements; determining a quality-based metric for the future CSI prediction instance based on (the historical channel measurements, and (ii) the time instance of the historical reference IMR or the coefficient for interference scaling relative to the historical reference set and sending an indication of the quality-based metric and the CSI prediction value for the future CSI prediction instance to the network.
However, Li more specifically teaches determining historical channel measurements based on a plurality of measurement resources (Figure 2-4; Paragraph [0130-0136] At 410, in some examples, the UE 115-b may receive, from the network entity 105-b, RRC signaling indicating a slot offset between a first slot for a CSI report and a prediction reference resource during a future slot. In some examples, a future reference resource described herein may be an example of the prediction reference resource. In some examples, a predicted CSI measurement may be based on the prediction reference resource. In some cases, the prediction reference resource during the future slot may be offset from a measurement reference resource in time by the slotoffset indicated by the RRC signaling. For example, the prediction reference resources may be offset from the measurement reference resource by npredict slots. At 415, the UE 115-b may receive, from the network entity 105-b, a second control message indicating a set of parameters for the CSI report for the beam prediction associated with the CMRs, IMRs, or both, based on the capability of the UE 115-b. For example, the second control message may configure one or more CSI report settings at the UE 115-b. The CSI report settings may include one or more parameters indicating whether channel measurements are associated with predictions or historically-based measurements. Additionally, or alternatively, the CSI report settings may include one or more parameters indicating whether interference measurements are associated with predictions or historically-based measurements; That is the device receives from the network configuration information and network assistance information for CSI prediction.)
determining a CSI prediction value for a future CSI prediction instance based on the historical channel measurements; determining a quality-based metric for the future CSI prediction instance based on (the historical channel measurements, and (ii) the time instance of the historical reference IMR or the coefficient for interference scaling relative to the historical reference set (Figure 2-4; Paragraph [0130-0136] In some examples, predicting CSI measurements associated with the CMRs may be based at least on a time restriction for channel measurements not being configured. For example, the time restriction may be explicitly configured to be not configured when channel measurements are associated with predictions, or the time restriction may be implicitly not configured based on the channel measurements being associated with predictions. In some examples, predicting CSI measurements associated with the IMRs may be based on a time restriction for interference measurements not being configured; Paragraph [0163-0164]);
and sending an indication of the quality-based metric and the CSI prediction value for the future CSI prediction instance to the network (Figure 2-4; Paragraph [0137] At 420, the UE 115-b may transmit, to the network entity 105-b the CSI report indicating predicted CSI measurements for a set of beams during the future slot, based on the set of parameters for the CSI report. In some examples, the predicted CSI measurements may be based on predicted measurements of CMRs or interference measurements of IMRs, both of which may be during or prior to the future slot in time. In some other examples, the predicted CSI measurements may include a predicted channel quality indicator, a predicted rank indicator, a predicted precoder matrix indicator, or any combination thereof, for the set of beams during the future slot).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden with the teachings of Li. Li provides a solution which enables predicting non-measured beam qualities using a machine learning model reduces power consumption and overhead, and predicting future beam blockages and failures reduce latency and increase throughput. The power consumption or latency of the UE or the network entity is offset by the other device being used for beam predictions, while both the UE and the network entity have increased power consumption or latency due to training the model. The method provides a timeline to perform channel measurement predictions or interference measurement predictions, which improves reliability for CSI reports carrying channel predictions or interference predictions, thus reducing overhead and power consumption from measurement-based CSI reports (Li Abstract; Paragraph [0001-0021]).
Regarding Claim 4, Ryden in view of Li disclose the method of Claim 1. Ryden in view of Li further disclose wherein the CSI prediction value for the future CSI prediction instance is based on the CSI measurements of the historical channel measurements (Li Paragraph [0100-0117] A CSI report setting associated with historic measurements may include parameters such that the time restriction for measurements is configured or not configured. For example, if the network entity 105-a configures the UE 115-a with a CSI report setting for a CSI report such that channels are to be derived based on historic measurements for the CSI report, a time restriction parameter associated with channel measurements may be configured (e.g., set to be configured) or not configured (e.g., set not to be configured).
Regarding Claim 7, Ryden in view of Li disclose the method of Claim 1. Ryden in view of Li further disclose wherein the quality-based prediction metric for the future CSI prediction instance comprises one or more of a rank indication (RI), a channel quality indicator (CQI) or a Signal-to-Interference-plus-Noise Ratio (SINR) for the future CSI prediction instance (Li Paragraph [0100] CQI, PMI, rank indicator, SINR for prediction and reporting).
Regarding Claim 10, Ryden in view of Li disclose the method of Claim 1. Ryden in view of Li further disclose wherein determining the quality-based metric for the future CSI prediction instance comprises predicting a Rank Indicator (RI) quality-based metric or a Channel Quality Information (CQI) quality-based metric for the future CSI prediction instance based on Artificial Intelligence Machine Learning (AIML) model; and wherein the AIML model has inputs comprising one or more of: the CSI prediction value, a Signal-to-Interference-plus-Noise Ratio (SINR), an estimated interference, a WTRU trajectory, or an indication of future expected estimated blockages (Li Paragraph [0043-0044] Machine learning AI modeling to predict channel measurements including CSI prediction values and estimated interference; Paragraph [0100] SINR, CQI, PMI, RI).
Regarding Claim 11, see the rejection of Claim 1. Claim 11 is an apparatus claim corresponding to the method of Claim 1 with the same features. Thus, the same rejection applies as the rejection of Claim 1. See Figure 6 and 13-21 of Ryden and Figure 1 and 5-8 of Li for corresponding structure.
Regarding Claim 14, Ryden in view of Li disclose the WTRU of Claim 11. Ryden in view of Li further disclose wherein the CSI prediction value for the future CSI prediction instance is based on the CSI measurements of the historical channel measurements (Li Paragraph [0100-0117] A CSI report setting associated with historic measurements may include parameters such that the time restriction for measurements is configured or not configured. For example, if the network entity 105-a configures the UE 115-a with a CSI report setting for a CSI report such that channels are to be derived based on historic measurements for the CSI report, a time restriction parameter associated with channel measurements may be configured (e.g., set to be configured) or not configured (e.g., set not to be configured)).
Regarding Claim 16, Ryden in view of Li disclose the WTRU of Claim 13. Ryden in view of Li further disclose receiving, from the network, configuration information wherein the configuration information comprises an indication of the channel measurement resources for determining the CSI measurements (Li Paragraph [0100-0117]).
Regarding Claim 17, Ryden in view of Li disclose the WTRU of Claim 11. Ryden in view of Li further disclose wherein the quality-based metric for the future CSI prediction instance comprises one or more of a rank indication (RI), a channel quality indicator (CQI) or a Signal-to-Interference-plus-Noise Ratio (SINR) for the future CSI prediction instance (Li Paragraph [0100] CQI, PMI, rank indicator, SINR for prediction and reporting).
Regarding Claim 20, Ryden in view of Li disclose the WTRU of Claim 11. Ryden in view of Li further disclose wherein the processor is configured to: determine the quality-based metric for the future CSI prediction instance based on a Rank Indicator (RI) quality-based metric or a Channel Quality Information (CQI) quality-based metric using an Artificial Intelligence Machine Learning (AIML) model, wherein the AIML model has inputs comprising one or more of: the CSI prediction value, a Signal-to-Interference-plus-Noise Ratio (SINR), an estimated interference, a WTRU trajectory, or an indication of future expected estimated blockages (Li Paragraph [0043-0044] Machine learning AI modeling to predict channel measurements including CSI prediction values and estimated interference; Paragraph [0100] SINR, CQI, PMI, RI).
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Ryden in view of Li as applied to claim 1 above, and further in view of Pezeshiki et al. U.S. Patent Application Publication 2025/0287219, hereinafter Pezeshiki.
Regarding Claim 2, Ryden in view of Li disclose the method of Claim 1. Ryden in view of Li fail to disclose receiving an indication of a future expected blockage, wherein the indication of the future expected blockage comprises one or more of: blockage information embedded into the coefficient for interference scaling, a condition used to determine blockage information, or an indication of a likelihood of a blockage at a future instance, and adjusting the quality-based metric based on the received indication of the future expected blockage.
However, Pezeshiki teaches receiving an indication of a future expected blockage, wherein the indication of the future expected blockage comprises one or more of: blockage information embedded into the coefficient for interference scaling, a condition used to determine blockage information, or an indication of a likelihood of a blockage at a future instance, and adjusting the quality-based metric based on the received indication of the future expected blockage (Pezeshiki Paragraph [0086] a model may be trained using a set of observations. The set of observations may be obtained from training data (e.g., historical data), such as data gathered during one or more processes described herein; Paragraph [0066-0067] UE may receive configuration from the network node. The configuration information may include a configuration for blockage prediction using wireless sensing. In some aspects, the configuration may indicate content to include in a report indicating predicted blockage information. For example, the configuration may indicate one or more values to be included in the predicted blockage information. In some aspects, the configuration may indicate one or more parameters associated with a model for blockage prediction, such as one or more parameters for training the model, one or more outputs to be generated by the model, or the like. In some aspects, the configuration information may be based at least in part on capability information transmitted by the UE, which may indicate a capability for blockage prediction, one or more requested parameters for the model, or the like).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden in view of Li with the teachings of Pezeshiki. The method enabled a network node to perform mitigating action such as proactively switching downlink beam to avoid beam failure due to predicted blockage event (Pezeshiki Abstract; Paragraph [0001-0007 and 0077]).
Regarding Claim 12, Ryden in view of Li disclose the WTRU of Claim 11. Ryden in view of Li fail to disclose wherein the processor is configured to: receive an indication of a future expected blockage, and wherein the indication of the future expected blockage comprises one or more of: blockage information embedded into the coefficient for interference scaling, a condition used to determine blockage information, or an indication of a likelihood of a blockage at a future instance, and adjust the quality-based metric based on the received indication of the future expected blockage.
However, Pezeshiki teaches wherein the processor is configured to: receive an indication of a future expected blockage, and wherein the indication of the future expected blockage comprises one or more of: blockage information embedded into the coefficient for interference scaling, a condition used to determine blockage information, or an indication of a likelihood of a blockage at a future instance, and adjust the quality-based metric based on the received indication of the future expected blockage.(Pezeshiki Paragraph [0086] a model may be trained using a set of observations. The set of observations may be obtained from training data (e.g., historical data), such as data gathered during one or more processes described herein; Paragraph [0066-0067] UE may receive configuration from the network node. The configuration information may include a configuration for blockage prediction using wireless sensing. In some aspects, the configuration may indicate content to include in a report indicating predicted blockage information. For example, the configuration may indicate one or more values to be included in the predicted blockage information. In some aspects, the configuration may indicate one or more parameters associated with a model for blockage prediction, such as one or more parameters for training the model, one or more outputs to be generated by the model, or the like. In some aspects, the configuration information may be based at least in part on capability information transmitted by the UE, which may indicate a capability for blockage prediction, one or more requested parameters for the model, or the like).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden in view of Li with the teachings of Pezeshiki. The method enabled a network node to perform mitigating action such as proactively switching downlink beam to avoid beam failure due to predicted blockage event (Pezeshiki Abstract; Paragraph [0001-0007 and 0077]).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Ryden in view of Li as applied to claim 1 above, and further in view of Yoshimoto et al. U.S. Patent Application Publication 2017/0111133, hereinafter Yoshimoto.
Regarding Claim 6, Ryden in view of Li disclose the method of Claim 1. Ryden in view of Li disclose receiving, from the network, configuration information and indication of measurement resources but not a type wherein the configuration information comprises an indication of the channel measurement resources for determining the CSI measurements and an indication of a type of the assistance information.
However, Yoshimoto more specifically teaches wherein the configuration information comprises an indication of the channel measurement resources for determining the CSI measurements and an indication of a type of the assistance information (Paragraph [0015-0023] the information related to the channel state information reporting configuration includes a configuration in which first channel state information values which are one type of channel state information values for a system bandwidth are fed back, and a configuration in which the system bandwidth is divided into predetermined units and second channel state information values which are one type of channel state information values for the divided units are fed back, and in a case where the information related to the network assisted interference cancellation and removal function indicates that the function is applied, any one of the first channel state information value and the second channel state information value is an appropriate channel state information value in a case where the downlink signal is received without applying the network assisted interference cancellation and removal function, and the other value is an appropriate channel state information value in a case where the downlink signal is received by applying the network assisted interference cancellation and removal function).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden in view of Li with the teachings of Yoshimoto. Yoshimoto provides a solution where the efficient reception quality information is reported, when transmitting the reception quality information (Yoshimoto Abstract; Paragraph [0001-0005 and 0009-0024]).
Claim 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ryden in view of Li as applied to claim 1 and 11 above, and further in view of Lee et al. U.S. Patent Application Publication 2013/0208604, hereinafter Lee.
Regarding Claim 8 and 18, Ryden in view of Li disclose the method and WTRU of Claim 1 and 11. Ryden in view of Li briefly disclose wherein determining the quality-based metric for the future CSI prediction instance comprises determining an estimated interference value for the future CSI prediction instance based on the coefficient for interference scaling and the historical reference IMR.
However, Lee more specifically teaches wherein determining the quality-based metric for the future CSI prediction instance comprises determining an estimated interference value for the future CSI prediction instance based on the coefficient for interference scaling and the historical reference IMR (Paragraph [0191] UE may also be configured with an offset or a set of offsets. This set of offsets may be configured by the network either via higher layer signalling or a new information element in a DCI (such as the DCI used to trigger aperiodic feedback). The offsets may have at least one of the following meanings: a linear or logarithmic value to be added to the total interference measured by the UE where such an offset may be cumulative over the past several values indicated by the network; a scaling value to be used on the interference measured by the summation of all the configured interference measurement values for a specific CSI case; a scaling value to be used on a subset of the interference measured by UE; and the like. For example, a UE may be configured to estimate the interference by using two component IMRs possibly by two different IM methods. In this case, the UE may be configured to use the offset value to scale one of the two interference values measured by one of the IMRs. The UE may then add the scaled value to the non-scaled value to obtain the final interference estimate. Alternatively or additionally, multiple offsets may be used, each configured to scale a specific component of the interference measurement).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden in view of Li with the teachings of Lee. The distributed remote radio heads (RRHs) i.e. transmission point (TPs), to be considered as a separate antenna port, so that spatial multiplexing gain can be exploited, thus increasing user equipment (UE) throughput by geographically separated antenna ports and improve a peak/average system throughput by exploiting multi-user diversity gain, for example (Lee Abstract; Paragraph [0002-0005, 0038, 0090 and 0208]).
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ryden in view of Li as applied to claim 1 and 11 above, and further in view of Li et al. U.S. Patent Application Publication 2024/0413870, hereinafter Li’870.
Regarding Claim 9 and 19, Ryden in view of Li disclose the method and WTRU of Claim 1 and 11. Ryden in view of Li fail to explicitly wherein the quality-based metric for the future CSI prediction instance comprises a decreased Rank Indicator (RI) quality-based metric that is determined based on the indication of future expected blockages.
However, Li’870 more specifically teaches wherein the quality-based metric for the future CSI prediction instance comprises a decreased Rank Indicator (RI) quality-based metric that is determined based on the indication of future expected blockages (Paragraph [0081-0095] Quality and beam blockage prediction including rank indicator quality based metrics).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to modify the teachings of Ryden in view of Li with the teachings of Li’870. The apparatus enables improving reliability, security and scalability of the wireless communication system. The apparatus allows the UE to transmit the predicted quantities or the reliability information message based on predicted quantities over the future time window to the base station based on the CSI report setting, so that the UE can transmit the quantity change rate or the reliable information message to the base station in an efficient manner, thus improving performance of the UE (Li’870 Abstract; Paragraph [0001-0007, 0076 and 0082]).
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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IVAN O. LATORRE
Primary Examiner
Art Unit 2409
/IVAN O LATORRE/Primary Examiner, Art Unit 2409
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