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 .
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- 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (WO-20210155553 A1) in view of Isaksson et al (US 20200413316 A1).
Regarding claims 1, 10, 20, Lee et al, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; page 7, paragraph 30), comprising: inputting (the AI device 1500 may include a communication part 1510, an input part 1520 ; the communication part 1510 can transmit and receive sensor information, a user input, a learning model, and a control signal with external devices; page 46, paragraph 327), by a terminal (smart phone), target information into an artificial intelligence model (fig. 15: the input part 1520 may include a camera for inputting a video signal, a microphone for receiving an audio signal, and a user input part for receiving information from a user; page 46, paragraph 328-329 ), to obtain an output result (the AI device 1500 may also include a communication part 1510, a learning processor 1530, a sensing part 1540, an output part 1550, a memory 1560, and a processor 1570; furthermore, the input part 1520 can acquire input data to be used when acquiring an output using learning data and a learning model for model learning; the input part 1520 may obtain raw input data, in which case the processor 1570 or the learning processor 1530 may extract input features; note that the processor 1570 may obtain the intention information for the user input and determine the user's requirements based on the obtained intention information ; page 47, paragraph 331-333), wherein the target information comprises information about a camped cell of the terminal and information about a neighbor cell of the terminal (read as: the target information is information of multiple cells and information of neighboring cells of the multiple cells; note that for each target NR frequency and for each RAT other than NR, a specific value for the cell reselection timer may be defined, which is applicable when evaluating reselection within NR or towards other RAT; the UE can camp on the higher priority cell among the cells in the best cell group of a frequency; the member of the best cell group may be determined by measured cell quality value of each cell; for instance, the best cell group may comprise, among neighbor cells on which a measurement is performed, the highest ranked cell and one or more neighbor cells whose cell quality value is within a configured threshold range from the cell quality value of the highest ranked cell; to distinguish the higher priority cell, the UE may compare the cell identity of a cell with the list of higher priority cells received from a network; page 36, paragraph 251, 256-258; page 49, paragraph 340-341), and the output result of the AI model (fig. `5: AI device 1500) comprises information about the terminal to be reselected to the neighbor cell (the target information is information of a certain cell and information of a neighboring cell; operation performed by the mobile device can be to determine whether to select the target cell as a cell after reselection or handover or handover during subsequent cell reselection or handover ; the wireless device may measure a quality of serving cell and neighbor cells; the wireless device may determine a best cell group of a frequency based on the measurement results; the wireless device may camp on a higher priority cell when the higher priority cell is included in the best cell group; the wireless device may identify one or more neighbor cells among the plurality of neighbor cells whose ranking value is within the threshold range of/from a ranking value of the highest ranked cell; page 36, page 37, paragraph 251, 256-258) ; and determining, by the terminal based on the output result, whether to be reselected to the neighbor cell (operation performed by the mobile device, may be machine learning based on the information of multiple cells and the information of neighbor cells of multiple cells to determine the cell reselection or handover model, and then any cell, the cell reselection can be completed autonomously and quickly based on the cell reselection or handover obtained from training; note that the target information includes information about a camped cell of the terminal and information about a neighbor cell of the terminal, and the output result includes information about the terminal to be reselected to the neighbor cell ; the UE 1210 may identify a highest ranked cell among a plurality of neighbor cells based on a result of a measurement on the plurality of neighbor cells; the UE 1210 may perform a cell reselection to a cell among the one or more neighbor cells based on that an ID of the cell is included in the IDs of higher priority cells; page 39-40, paragraph 274-291). Furthermore, the output part 1550 may generate an output related to visual, auditory, tactile, the output part 1550 may also include a display unit for outputting visual information, a speaker for outputting auditory information, and a haptic module for outputting tactile information (page, 46-49; paragraph 331-333, 337). Note the AI server 1620 may receive the input data from the AI devices 1610a to 1610e, infer the result value with respect to the received input data using the learning model, generate a response and/or a control command based on the inferred result value, and transmit the generated data to the AI devices 1610a to 1610e. Alternatively, the AI devices 1610a to 1610e may directly infer a result value for the input data using a learning model, and generate a response and/or a control command based on the inferred result value (page, 48-49; paragraph 337, 341;page 37, paragraph 256-259; page 39-40, paragraph 274-291).
However, Lee et al, does not specifically teach that the AI model is determined based on first AI model information, and the first AI model information is used to indicate at least one of the following: an AI model identifier; AI model state information; an activation condition for the AI model; operation cycle information for the AI model; a validity period of the AI model; a valid area for the AI model; a time-frequency resource for AI model requests; first description information related to an AI model input parameter, wherein the first description information comprises a default-able identifier of each input parameter; or a default value for the AI model input parameter.
On the other hand, Isaksson et al, from the same field of endeavor, teaches that the AI model (the radio network node provides to the wireless communication device 10, the indicator indicating the model and the one or more trained model parameters for the model; the first radio network node 12 sends an index that points to a predetermined model, to which the wireless communication device 10 applies the one or more trained model parameters that is sent by the first radio network node 12; note that the model is for triggering a process of a handover procedure, a cell reselection procedure, and a beam reselection procedure paragraph, 0054, 0057) is determined based on first AI model information (the data is associated with measurements performed by the one or more wireless communication devices such as measurement values, ID of beams or cells; the wireless communication device 10 may be instructed by the wireless communications network 1 to perform these processes such as transmitting measurement reports and/or performing a handover; furthermore, the wireless communication device 10 selects the model based on the indicator e.g. from a list with indexed models already preconfigured at the wireless communication device 10; paragraph 0050, 0053, 0057-0058), and the first AI model information (a cell or a beam of the wireless communications network; neighbor cell; trigger a handover event and send information such as measurement reports about serving and neighboring cells or beams to the first radio network node 12 serving the wireless communication device 10 ; in addition, the indicator may be sent as system information, such as in a system information block or in a master information block for a cell; paragraph 0043-0044; paragraph 0046-0049) is used to indicate at least one of the following: an AI model identifier; AI model state information (Channel state information reference signal resource becomes better than a C1 threshold; Primary cell becomes worse than a first threshold and the neighbor cell becomes better than a second threshold ; neighbor cell becomes better than a B1 threshold; paragraph 0013-0018; paragraph 0079-0080); an activation condition for the AI model; operation cycle information for the AI model; a validity period of the AI model (the training may be performed off-line during a limited period; paragraph 0053-0054); a valid area for the AI model (the first service area 11 may be referred to as a source beam, and the first radio network node 12 serves and communicates with the wireless communication device 10 in form of DL transmissions to the wireless communication device 10 ; a second radio network node 13 may further provide radio coverage over a second service area 14, also referred to as a second beam/beam group, of a second radio access technology, such as NR, LTE, W-Fi, WiMAX or similar; in addition, the first radio network node 12 sends an index that points to a predetermined model, to which the wireless communication device 10 applies the one or more trained model parameters that is sent by the first radio network node 12; paragraph 0039-0041; paragraph 0056-0057); a time-frequency resource for AI model requests (measured RSRP and/or RSRQ of neighboring beams or cells on serving frequency and/or other frequencies than the serving frequency, timing Advance for the serving cell or beam, pre-coder matrix index, time series of the RSRP and identities of the past serving beams for the wireless communication device that is currently served by this very beam, and block error rate ; paragraph 0042, 0059); first description information related to an AI model input parameter (trained model parameters, and the model may be a neural network which may be multivariate and time-dependent in that the model takes historical data into account; the model with the one or more trained model parameters is used at the wireless communication device 10 to trigger a process at the wireless communication device 10 such as triggering sending measurement reports to the first radio network node 12 that will decide when to do handover and to which cell; paragraph 0042, 0045), wherein the first description information comprises a default-able identifier of each input parameter; or a default value for the AI model input parameter (perform a handover to a target cell/beam, where the target radio network node informs the source radio network node that a handover occurred and attaches input data used, i.e. all or some of the input data, e.g. a last value of a serving beam used; paragraph 0048-0049, 0053). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to apply the technique of Isaksson to the communication system of Lee in order to provide a method performed by a wireless communication device for managing communication in a wireless communications network.
Regarding claim 2, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the information about the camped cell comprises at least one of the following: an angle of the boresight direction of a first network device; load information of the first network device; or a radio signal measurement result for the first network device (perform necessary measurements for the cell reselection evaluation procedure; the UE should perform a measurement on neighbor cells, and select a cell among them to perform a cell reselection based on the measurement ; page 37, page 257-259), wherein the first network device is a network device corresponding to the camped cell (identifying one or more neighbor cells among the plurality of neighbor cells whose ranking value is within the threshold range of a ranking value of the highest ranked cell; and performing a cell reselection to a cell among the one or more neighbor cells based on that an ID of the cell is included in the IDs of higher priority cells; page 38, page 264-271).
Regarding claim 3, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the information about the neighbor cell comprises at least one of the following: a cell identifier of a second network device (the UE 1210 may perform a cell reselection to a cell among the one or more neighbor cells based on that an ID of the cell is included in the IDs of higher priority cells; page 40, paragraph 287-291); a service type supported by the second network device (select a cell among them to perform a cell reselection based on the measurement result; the UE may need to reselect a proper cell based on certain criteria so that the UE be provided with a service of good quality from the reselected cell ; page 37, paragraph 2558-259) ; radio resource information supported by the second network device; a slice type supported by the second network device; an angle of the boresight direction of the second network device; load information of the second network device; a radio signal measurement result for the second network device ; or historical information generated by the second network device in a process of serving the terminal, wherein the second network device is a network device corresponding to the neighbor cell (page 39, paragraph 274-281).
Regarding claim 4, Lee et al as modified , discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the target information further comprises information about the terminal, and the information about the terminal comprises at least one of the following: state information of the terminal (receiving a connection release message from a network upon which the wireless device leaving a connected state; receiving a configuration of a threshold range from the network); a service requirement type prediction parameter of the terminal; or a historical service cell identifier list of the terminal (the processor 1570 may store the collected history information in the memory 1560 and the learning processor 1530, and transmit to an external device such as the AI server; the collected history information can be used to update the learning model ; furthermore, an RRC state indicates whether an RRC layer of the UE is logically connected to an RRC layer of the E-UTRAN. In LTE/LTE-A, when the RRC connection is established between the RRC layer of the UE and the RRC layer of the E-UTRAN, the UE is in the RRC connected state (RRC_CONNECTED). Otherwise, the UE is in the RRC idle state (RRC_IDLE); page 23, paragraph 138-142).
Regarding claim 5, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the state information of the terminal comprises at least one of the following: position information of the terminal; or mobility information of the terminal (connected mode mobility procedures, based on the Mobility Restrictions received from the AMF; UE configuration Update procedure for access and mobility management related parameters ; page 34- 35, paragraph 231, 240-244). Regarding claim 6, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the radio signal measurement result for the first network device comprises at least one of the following: reference signal receiving power (RSRP) of a reference signal of the first network device (the ranking value that is determined according to the cell-ranking criterion R may be referred to as R value, Q.sub.meas RSRP measurement quantity used in cell reselections; in addition, the cell reselection criteria may comprise intra-frequency cell reselection criteria and/or inter-frequency cell reselection criteria with equal priority ; page, paragraph); or reference signal receiving quality (RSRQ) of the reference signal of the first network device (a beam may comprise at least one of an SS/PBCH block (or, synchronization signal block (SSB) or a channel state information reference signal ; the parameter ThreshSS-BlocksConsolidation may indicate a threshold for a consolidation of layer 1 measurements per reference signal (RS) index and/or beam index; page 23, paragraph 138-142; page 26-27, paragraph151-161).
Regarding claim 7, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the radio signal measurement result of the second network device comprises at least one of the following: RSRP of a reference signal of the second network device ; or RSRQ of the reference signal of the second network device (the ranking value that is determined according to the cell-ranking criterion R may be referred to as R value, abl06 Q.sub.meas RSRP measurement quantity used in cell reselections; the cell reselection criteria may comprise intra-frequency cell reselection criteria and/or inter-frequency cell reselection criteria with equal priority; page 26-27, paragraph 151-161).
Regarding claim 8, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the historical information comprises at least one of the following: a historical switching report of the terminal on the second network device; a historical radio link failure report of the terminal on the second network device (the UE may transit to RRC_IDLE from RRC_CONNECTED when detach, RRC connection release and/or connection failure (e.g., radio link failure (RLF) as occurred; the UE may transit to RRC_IDLE from RRC_CONNECTED when detach, RRC connection release and/or connection failure (e.g., radio link failure (RLF)) has occurred); a random access report of the terminal on the second network device; or a historical service state of the terminal on the second network device (the UE may transit to RRC_INACTIVE from RRC_INACTIVE when RRC connection is suspended, and transit to RRC_CONNECTED from RRC_INACTIVE when RRC connection is resume; the UE may transit to RRC_IDLE from RRC_INACTIVE when connection failure such as radio link failure RLF has occurred ;see fig. 9 for details; page 35 paragraph 240-247).
Regarding claim 9, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein: the load information comprises at least one of the following: a physical resource block utilization rate; the number of radio resource control connections (paragraph 133-134); the number of stored sessions of an inactive terminal (at RRC connection re-establishment/ handover, one serving cell provides the security input; this cell is referred to as the Primary Cell (PCell); the PCell is a cell, operating on the primary frequency, in which the UE either performs the initial connection establishment procedure or initiates the connection re-establishment procedure; page 23-25, paragraph 129-133); or time stamp information, and the radio resource information supported by the second network device comprises at least one of the following: a bandwidth supported by the second network device; whether the second network device supports carrier aggregation; a carrier aggregation combination supported by the second network device (in carrier aggregation, two or more CCs are aggregated; a UE may simultaneously receive or transmit on one or multiple CCs depending on its capabilities; CA is supported for both contiguous and non-contiguous CCs; when CA is configured the UE only has one radio resource control connection with the network ; whether the second network device supports dual connectivity; or a dual connectivity combination supported by the second network device (for dual connectivity operation, the term Special Cell (SpCell) refers to the PCell of the master cell group or the PSCell of the secondary cell group ; an SpCell supports PUCCH transmission and contention-based random access, and is always activated ; page 23-25, paragraph 129-133).
Regarding claim 11, Lee et al, as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the output result comprises indication information, and the indication information is used to indicate whether to be reselected to the neighbor cell (perform necessary measurements for the cell reselection evaluation procedure; perform necessary measurements for the cell reselection evaluation procedure; the UE should perform a measurement on neighbor cells, and select a cell among them to perform a cell reselection based on the measurement; page 37, page 257-259; (operation performed by the mobile device, may be machine learning based on the information of multiple cells and the information of neighbor cells of multiple cells to determine the cell reselection or handover model, and then any cell, the cell reselection can be completed autonomously and quickly based on the cell reselection or handover obtained from training; note that the target information includes information about a camped cell of the terminal and information about a neighbor cell of the terminal, and the output result includes information about the terminal to be reselected to the neighbor cell ; the UE 1210 may identify a highest ranked cell among a plurality of neighbor cells based on a result of a measurement on the plurality of neighbor cells; the UE 1210 may perform a cell reselection to a cell among the one or more neighbor cells based on that an ID of the cell is included in the IDs of higher priority cells; page 39-40, paragraph 274-291).
Regarding claim 12, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), further comprising: when the terminal determines to be reselected to the neighbor cell, initiating, by the terminal, a random access request to the neighbor cell, wherein the random access request carries a random access report, and the random access report comprises at least one of the following: a cell reselection type identifier ; an AI model input parameter and a parameter value for the AI model input parameter (model parameters are parameters determined through learning, including deflection of neurons and/or weights of synaptic connections; the hyper-parameter means a parameter to be set in the machine learning algorithm before learning, and includes a learning rate, a repetition number, a mini batch size, an initialization function ; page 47-48; paragraph 333-337); the AI model identifier; a default list of the AI model input parameter; and a default value list of default values for the AI model input parameter (the processor 1570 may then control the components of the AI device 1500 to perform the determined operation; the processor 1570 may request, retrieve, receive, and/or utilize data in the learning processor 1530 and/or the memory 1560, and may control the components of the AI device 1500 to execute the predicted operation and/or the operation determined to be desirable among the at least one executable operation (page, 46-49; paragraph 331-333, 337).
Regarding claims 13, 14, Lee et al, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), comprising: sending (the AI device 1500 may include a communication part 1510, an input part 1520 ; the communication part 1510 can transmit and receive sensor information, a user input, a learning model, and a control signal with external devices; page 46, paragraph 327), by a first network device, first artificial intelligence model information (fig. 15: the input part 1520 may include a camera for inputting a video signal, a microphone for receiving an audio signal, and a user input part for receiving information from a user; page 46, paragraph 328-329 ), wherein the first AI model information is information about an AI model used for cell reselection (the cell reselection criteria may comprise intra-frequency cell reselection criteria and/or inter-frequency cell reselection criteria with equal priority (read as: the target information is information of multiple cells and information of neighboring cells of the multiple cells; note that for each target NR frequency and for each RAT other than NR, a specific value for the cell reselection timer may be defined, which is applicable when evaluating reselection within NR or towards other RAT; the UE can camp on the higher priority cell among the cells in the best cell group of a frequency; the member of the best cell group may be determined by measured cell quality value of each cell; for instance, the best cell group may comprise, among neighbor cells on which a measurement is performed, the highest ranked cell and one or more neighbor cells whose cell quality value is within a configured threshold range from the cell quality value of the highest ranked cell; to distinguish the higher priority cell, the UE may compare the cell identity of a cell with the list of higher priority cells received from a network; page 36, paragraph 251, 256-258; page 49, paragraph 340-341).
However, Lee et al, does not specifically teach that the first AI model information is used to indicate at least one of the following: an AI model identifier; AI model state information; an activation condition for the AI model; operation cycle information for the AI model; a validity period of the AI model; a valid area for the AI model; a time-frequency resource for AI model requests; first description information related to an AI model input parameter, wherein the first description information comprises a default-able identifier of each input parameter; or a default value for the AI model input parameter.
On the other hand, Isaksson et al, from the same field of endeavor, teaches that the first AI model (the radio network node provides to the wireless communication device 10, the indicator indicating the model and the one or more trained model parameters for the model; the first radio network node 12 sends an index that points to a predetermined model, to which the wireless communication device 10 applies the one or more trained model parameters that is sent by the first radio network node 12; note that the model is for triggering a process of a handover procedure, a cell reselection procedure, and a beam reselection procedure paragraph, 0054, 0057) is used to indicate (the data is associated with measurements performed by the one or more wireless communication devices such as measurement values, ID of beams or cells; the wireless communication device 10 may be instructed by the wireless communications network 1 to perform these processes such as transmitting measurement reports and/or performing a handover; furthermore, the wireless communication device 10 selects the model based on the indicator e.g. from a list with indexed models already preconfigured at the wireless communication device 10; paragraph 0050, 0053, 0057-0058), and the first AI model information (a cell or a beam of the wireless communications network; neighbor cell; trigger a handover event and send information such as measurement reports about serving and neighboring cells or beams to the first radio network node 12 serving the wireless communication device 10 ; in addition, the indicator may be sent as system information, such as in a system information block or in a master information block for a cell; paragraph 0043-0044; paragraph 0046-0049) at least one of the following: an AI model identifier; AI model state information (Channel state information reference signal resource becomes better than a C1 threshold; Primary cell becomes worse than a first threshold and the neighbor cell becomes better than a second threshold ; neighbor cell becomes better than a B1 threshold; paragraph 0013-0018; paragraph 0079-0080); an activation condition for the AI model; operation cycle information for the AI model; a validity period of the AI model (the training may be performed off-line during a limited period; paragraph 0053-0054); a valid area for the AI model (the first service area 11 may be referred to as a source beam, and the first radio network node 12 serves and communicates with the wireless communication device 10 in form of DL transmissions to the wireless communication device 10 ; a second radio network node 13 may further provide radio coverage over a second service area 14, also referred to as a second beam/beam group, of a second radio access technology, such as NR, LTE, W-Fi, WiMAX or similar; in addition, the first radio network node 12 sends an index that points to a predetermined model, to which the wireless communication device 10 applies the one or more trained model parameters that is sent by the first radio network node 12; paragraph 0039-0041; paragraph 0056-0057); a time-frequency resource for AI model requests (measured RSRP and/or RSRQ of neighboring beams or cells on serving frequency and/or other frequencies than the serving frequency, timing Advance for the serving cell or beam, pre-coder matrix index, time series of the RSRP and identities of the past serving beams for the wireless communication device that is currently served by this very beam, and block error rate ; paragraph 0042, 0059); first description information related to an AI model input parameter (trained model parameters, and the model may be a neural network which may be multivariate and time-dependent in that the model takes historical data into account; the model with the one or more trained model parameters is used at the wireless communication device 10 to trigger a process at the wireless communication device 10 such as triggering sending measurement reports to the first radio network node 12 that will decide when to do handover and to which cell; paragraph 0042, 0045), wherein the first description information comprises a default-able identifier of each input parameter; or a default value for the AI model input parameter (perform a handover to a target cell/beam, where the target radio network node informs the source radio network node that a handover occurred and attaches input data used, i.e. all or some of the input data, e.g. a last value of a serving beam used; paragraph 0048-0049, 0053). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to apply the technique of Isaksson to the communication system of Lee in order to provide a method performed by a wireless communication device for managing communication in a wireless communications network.
Regarding claim 15, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the first AI model information is carried in a last message sent by the first network device before the terminal enters an inactive state or an idle state, or the first AI model information is carried in a broadcast message that is sent by the first network device and that is received in a case that the terminal is in the inactive state or the idle state (the RRC context may be already established in the network and idle-to-active transitions can be handled in the RAN; the UE may be allowed to sleep in a similar way as in RRC_IDLE, and mobility may be handled through cell reselection without involvement of the network; the RRC_INCATIVE may be construed as a mix of the idle state and the connected state (at RRC connection re-establishment/ handover, one serving cell provides the security input; this cell is referred to as the Primary Cell (PCell); the PCell is a cell, operating on the primary frequency, in which the UE either performs the initial connection establishment procedure or initiates the connection re-establishment procedure; page 23-25, paragraph 129-133).
Regarding claim 16, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), further comprising: sending, by the first network device, load information to the terminal (load information of the first network device ; page 35 paragraph 240-247).
Regarding claim 17, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), comprising: sending (the AI device 1500 may include a communication part 1510, an input part 1520 ; the communication part 1510 can transmit and receive sensor information, a user input, a learning model, and a control signal with external devices; page 46, paragraph 327), by a second network device, information about a neighbor cell for cell reselection (read as: the target information is information of multiple cells and information of neighboring cells of the multiple cells; note that for each target NR frequency and for each RAT other than NR, a specific value for the cell reselection timer may be defined, which is applicable when evaluating reselection within NR or towards other RAT; the UE can camp on the higher priority cell among the cells in the best cell group of a frequency; the member of the best cell group may be determined by measured cell quality value of each cell; for instance, the best cell group may comprise, among neighbor cells on which a measurement is performed, the highest ranked cell and one or more neighbor cells whose cell quality value is within a configured threshold range from the cell quality value of the highest ranked cell; to distinguish the higher priority cell, the UE may compare the cell identity of a cell with the list of higher priority cells received from a network; page 36, paragraph 251, 256-258; page 49, paragraph 340-341), wherein the information about the neighbor cell comprises at least one of the following: a service type supported by the second network device (select a cell among them to perform a cell reselection based on the measurement result; the UE may need to reselect a proper cell based on certain criteria so that the UE be provided with a service of good quality from the reselected cell ; page 37, paragraph 2558-259); a slice type supported by the second network device; an angle of a boresight direction of the second network device; load information of the second network device; a radio signal measurement result for the second network device (perform necessary measurements for the cell reselection evaluation procedure); or a radio signal measurement result for the second network device, wherein the second network device is a network device corresponding to the neighbor cell (page 36, page 37, paragraph 251, 256-258).
Regarding claim 18, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the load information comprises at least one of the following: a physical resource block (PRB) utilization rate; the number of radio resource control connections; the number of stored sessions of an inactive terminal (at RRC connection re-establishment/ handover, one serving cell provides the security input; this cell is referred to as the Primary Cell (PCell); the PCell is a cell, operating on the primary frequency, in which the UE either performs the initial connection establishment procedure or initiates the connection re-establishment procedure; page 23-25, paragraph 129-133); or time stamp information (page 23, paragraph139-140).
Regarding claim 19, Lee et al as modified, discloses a cell reselection method (fig. 10: a method for performing a cell reselection to a cell among multiple cells; paragraph 30), wherein the information about the neighbor cell further comprises radio resource information supported by the second network device , and the radio resource information supported by the second network device comprises at least one of the following: a bandwidth supported by the second network device; whether the second network device supports carrier aggregation; a carrier aggregation combination supported by the second network device (in carrier aggregation, two or more CCs are aggregated; a UE may simultaneously receive or transmit on one or multiple CCs depending on its capabilities; CA is supported for both contiguous and non-contiguous CCs; when CA is configured the UE only has one radio resource control connection with the network; whether the second network device supports dual connectivity; or a dual connectivity combination supported by the second network device (page 23-25, paragraph 129-133).
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.
Conclusion
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MARCEAU MILORD
Examiner
Art Unit 2641
/MARCEAU MILORD/Primary Examiner, Art Unit 2641
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