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 . Claims 1-20 have been submitted for examination.
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.
Claims 1-12, 14-16 and 18-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Lee et al (hereinafter Lee) US Publication No 20230306304 in view of Yanfei Dong (hereinafter Dong) US Publication No 20200285898.
As per claim 1, Lee teaches:
A user equipment (UE) for wireless communication, comprising:
at least one memory;
(Paragraph [0018])
and at least one processor coupled with the at least one memory (Paragraph [0018]) and configured to cause the UE to:
transmit, to a network equipment over a physical channel, a first signaling indicating a first training dataset report that identifies a training dataset corresponding to a machine learning or artificial intelligence algorithm,
(Paragraphs [0008]-[0009] and [0041])
the training dataset including multiple datapoints and being partitioned into multiple dataset groups each including one or more of the multiple datapoints, each of the multiple dataset groups being associated with a first label and a second label, the first label corresponding to a temporal or time-domain related parameter,
(Paragraphs [0012], [0022], [0058], [0081], [0135]-[0136], wherein the labelling is based on time point and characteristic of the data)
the second label being at least one of a weight or a value associated with a characteristic of the dataset;
(Abstract and paragraphs [0022], [0121], [0135]-[0136])
update the second label after transmission of the first signaling;
(Abstract and paragraphs [0022], [0070], [0121], [0135]-[0136])
update the training dataset, based on at least one of the first label or the second label, by at least one of updating a subset of values of the second label of the multiple dataset groups,
(Abstract and paragraphs [0021]-[0022], [0074] and [0083])
Lee teaches updating training dataset but does explicitly teach updating training detest by removing data, however in analogous art of data management, Dong teaches:
update the training dataset, based on at least one of the first label or the second label, by at least one of updating a subset of values of the second label of the multiple dataset groups, removing a dataset group of the multiple dataset groups, or adding a new dataset group to the dataset;
(Paragraphs [0012], [0019]-[0020], [0054]-[0055] and [0059])
and transmit, to the network equipment over the physical channel, a second signaling indicating a second training dataset report that includes updated information corresponding to the updated training dataset.
(Fig. 1 and paragraphs [0021]-[0022], [0042], [0044]-[0045])
Therefore, it would have been obvious to a person in the ordinary skill in the art at the time of the filling of the invention to combine Lee and Dong by incorporating the teaching of Dong into the method of Lee. One having ordinary skill in the art would have found it motivated to use the content management of Dong into the system of Lee for the purpose of managing data or improving performance of classification and boots prediction accuracy.
As per claim 2, Lee and Dong teach:
The UE of claim 1, wherein the physical channel is an uplink channel.
(Paragraphs [0068] and [0072])(Dong)
As per claim 3, Lee and Dong teach:
The UE of claim 1, wherein a number of the multiple dataset groups is bounded by a maximum value of a number of dataset groups.
(Paragraphs [0051])(Dong)
As per claim 4, Lee and Dong teach:
The UE of claim 1, wherein the temporal or time-domain related parameter is at least one of a time stamp or a time duration.
(Paragraphs [0012]-[0014] and [0059])(Lee)
As per claim 5, Lee and Dong teach:
The UE of claim 1, wherein the first label is one of: a time duration that comprises parameters corresponding to at least one of a start time, or a time interval and a time periodicity; a time stamp that corresponds to one of a time of transmission of the datapoints of a dataset group, or a time of collection of the datapoints of the dataset group; or a combination thereof.
(Paragraphs [0012]-[0014] and [0059])(Lee)
As per claim 6, Lee and Dong teach:
The UE of claim 1, wherein the weight of the dataset group is selected from a codebook of values associated with the weight.
(Paragraphs [0061], [0065])(Dong)
As per claim 7, Lee and Dong teach:
The UE of claim 1, wherein the weight of the dataset group is updated based on an event, and the event is: based on a configuration for updating the dataset, one of a periodic or a semipersistent event;
(Paragraphs [0021, [0026] and [0067])(Dong)
triggered by at least one of a network configuration signal, a downlink control information, or a medium access control element (MAC-CE) signal; or a combination thereof.
(Paragraphs [0021, [0026] and [0067])(Dong)
As per claim 8, Lee and Dong teach:
The UE of claim 1, wherein a dataset group associated with a time stamp corresponding to a former value is replaced with a dataset group associated with a time stamp corresponding to a more recent value.
(Paragraphs [0012], [0014] , [0061] and [0106])(Lee)
As per claim 9, Lee and Dong teach:
The UE of claim 1, wherein a dataset point is associated, based on one or more characteristics of the dataset point, with a dataset group of the multiple dataset groups.
(Abstract and paragraphs [0022], [0121], [0135]-[0136])(Lee)
As per claim 10, Lee and Dong teach:
The UE of claim 9, wherein a characteristic in the one or more characteristics of the dataset point is an observable characteristic that is derived via at least one of: a deterministic formula of a value of the dataset point; a transformed variant of the value of the dataset point based on a transformation operation; or a normalization of the value of the dataset point with respect to one or more values of other dataset points.
(Abstract and paragraphs [0006], [0093])(Lee)
As per claim 11, Lee and Dong teach:
The UE of claim 9, wherein the characteristic in the one or more characteristics of the dataset point is an unobservable characteristic that corresponds to at least one of: a parameter that identifies whether the dataset point is classified as an outlier or a common point; a statistical correlation parameter corresponding to an approximate distribution associated with the dataset; or a parameter corresponding to a power-delay profile corresponding to an approximate distribution associated with the dataset.
(Abstract or Paragraphs [0007], [0012], [0018], [0021] and [0048] and [0074])(Lee)
As per claim 12, Lee and Dong teach:
The UE of claim 1, wherein the training dataset corresponds to at least one of channel state information (CSI), precoding information, or beam-based information, and wherein a first dataset group of the multiple dataset groups is at least one of: associated with one or more of a time stamp corresponding to a time of collection of the CSI, a time of signaling data corresponding to the CSI, a time interval at which the first dataset group is valid, or a value corresponding to one or more of a weight or a probability of occurrence, wherein a larger value corresponds to a stronger correlation of dataset points of the first dataset group with the CSI and a smaller value corresponds to a weaker correlation of dataset points of the first dataset group with the CSI; or classified based on an observable characteristic of the CSI that includes one or more of channel taps, a ratio of a maximum value of a singular value to a minimum value of the singular value of a channel matrix or a precoding matrix, a power-delay profile associated with the CSI, or an unobservable characteristic of the CSI that is based on an observable characteristic.
(Abstract and paragraphs [0022], [0121], [0135]-[0136])(Lee)
As per claim 14, Lee and Dong teach:
The UE of claim 1, wherein the training dataset corresponds to positioning information, and wherein a first dataset group of the multiple dataset groups is at least one of: associated with one or more of a time stamp corresponding to a time of collection of the positioning information, a time of signaling data corresponding to the positioning information, a time interval at which the first dataset group is valid, or a value corresponding to one or more of a weight or a probability of occurrence, wherein a larger value corresponds to a stronger correlation of dataset points of the first dataset group with an actual position, and a smaller value corresponds to a weaker correlation of dataset points of the first dataset group with the actual position; or classified based on an observable characteristic of the position that includes one or more of an angle of arrival, an angle of departure, a round-trip time, or a time-difference of arrival, or an unobservable characteristic of the actual position that is based on an observable characteristic.
(Abstract and paragraphs [0022], [0121], [0135]-[0136])(Lee)
As per claim 15, Lee and Dong teach:
The UE of claim 14, wherein the observable characteristic is one or more of a flag on whether a channel associated with the positioning information corresponds to an indoor or outdoor UE based on one or more of the values of the angle of arrival, the angle of departure, the round-trip time, or the time-difference of arrival.
(Abstract and paragraphs [0022], [0121], [0135]-[0136])(Lee)
As per claim 16, Lee and Dong teach:
The UE of claim 1, wherein the training dataset corresponds to mobility information, and wherein a first dataset group of the multiple dataset groups is at least one of: associated with one or more of a time stamp corresponding to a time of collection of the mobility information or cell association information, a time of signaling data corresponding to the cell association, a time interval at which the first dataset group is valid, or a value corresponding to one or more of a weight or a probability of occurrence, wherein a larger value corresponds to a stronger correlation of dataset points of the first dataset group with a heuristic cell association or selection, and a smaller value corresponds to a weaker correlation of dataset points of the first dataset group with the heuristic cell association or selection; or classified based on an observable characteristic of the UE mobility that includes one or more of reference signal received power (RSRP), signal-to-interference-and-noise ratio (SINR), beam-based information, channel state information (CSI), or an unobservable characteristic of the mobility information that is based on an observable characteristic.
(Abstract and paragraphs [0022], [0121], [0135]-[0136])(Lee)
Claim 18 is a base station claim corresponding to Claim 1 and it is rejected under the same rational as claim 1.
Claim 19 is a processor claim corresponding to Claim 1 and it is rejected under the same rational as claim 1.
Claim 20 is a method claim corresponding to Claim 1 and it is rejected under the same rational as claim 1.
Claim 13 is rejected under 35 U.S.C. 103(a) as being unpatentable over Lee and Dong in view of Tsui et al (hereinafter Tsui) US Publication No 20120309445.
As per claim 13, Lee and Dong do not explicitly teach observable characteristic is one or more of a flag on whether a channel associated with the CSI corresponds to a line-of-sight (LoS) or non-line-of-sight (NLoS) channel based on a number of dominant basis indices of a transformed frequency-domain basis, the dominant basis indices corresponding to indices with a minimum power threshold, however in analogous art of data management, Tsui teaches:
observable characteristic is one or more of a flag on whether a channel associated with the CSI corresponds to a line-of-sight (LoS) or non-line-of-sight (NLoS) channel based on a number of dominant basis indices of a transformed frequency-domain basis, the dominant basis indices corresponding to indices with a minimum power threshold.
(Paragraphs [0045], [0051], [0078], [0094])
Therefore, it would have been obvious to a person in the ordinary skill in the art at the time of the filling of the invention to combine Lee and Dong and Tsui by incorporating the teaching of Tsui into the method of Lee and Dong. One having ordinary skill in the art would have found it motivated to use the content management of Tsui into the system of Lee and Dong for the purpose of managing data based device resource.
Claim 17 is rejected under 35 U.S.C. 103(a) as being unpatentable over Lee and Dong in view of Sangwon Kim (hereinafter Kim) US Publication No 20220007261.
As per claim 17, Lee and Dong do not explicitly teach observable characteristic is a flag on whether the UE is associated with a best cell based on one or more of values of the RSRP, values of the SINR, beam-based information, or CSI, however in analogous art of data management, Kim teaches:
observable characteristic is a flag on whether the UE is associated with a best cell based on one or more of values of the RSRP, values of the SINR, beam-based information, or CSI.
(Paragraph [0192])
Therefore, it would have been obvious to a person in the ordinary skill in the art at the time of the filling of the invention to combine Lee and Dong and Kim by incorporating the teaching of Kim into the method of Lee and Dong. One having ordinary skill in the art would have found it motivated to use the content management of Kim into the system of Lee and Dong for the purpose of optimizing channel usage
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Tarek Chbouki whose telephone number is 571-2703154. The examiner can normally be reached on Mon-Fri 9:00 am to 6:00 pm EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aleksandr Kerzhner can be reached at 571-2701760. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TAREK CHBOUKI/ Primary Examiner, Art Unit 2165 9/15/2026
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