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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claim 27 objected to because of the following informalities: Claim 27 appears to be written in independent form, however as currently written, it appears to depend on claim 1, thus combining a method and apparatus type claim through the dependency. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 9-12 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claim 8 outlines a list of transmitted information in an or statement form. Dependent claims 9-12 further define each category of transmitted information, however the dependent claims fail to account for the possibility that the defined information has not been transmitted as defined in claim 8 as only one of the list must be included in order to fulfil the requirement of claim 8. For example, if per claim 8, radio channel characteristic information is obtained, and the other three forms of information are not, there would be no antecedent basis for the dependent claims. Examiner recommends adding the text “In the case that” to further define that the definition is for a specific case rather than a blanket statement.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-4,6-16,18-21 and 27 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et. al. (US 20230155702 A1) hereafter Wang.
Regarding Claim 1:
Wang discloses:
A method for transmitting a data channel model, comprising: receiving, by a first node, data transmission requirement information transmitted from a second node; ([0023] With reference to the first aspect, in some implementations of the first aspect, the method further includes: the first communications apparatus receives first indication information, where the first indication information is used to indicate the first communications apparatus to perform channel learning model training.) determining, by the first node, a data channel model matching the data transmission requirement information at least according to the data transmission requirement information; ([¶0025] Based on the foregoing technical solution, the second communications apparatus may indicate, by using signaling, the first communications apparatus to determine whether the first channel learning model is applicable, so that when finding that the first channel learning model is not applicable, the second communications apparatus indicates, in a timely manner, the first communications apparatus to perform verification, to reduce a delay of determining whether the first channel learning model is applicable. In addition, when finding, in a timely manner, that first channel learning is not applicable, the second communications apparatus may update the first channel learning model in a timely manner, to avoid degradation of communication performance caused when the first channel learning model is not applicable.) and transmitting the data channel model matching the data transmission requirement information to the second node. ([¶0044] Based on the foregoing solution, when determining that the first channel learning model is not applicable, the first communications apparatus may determine one or more configuration parameters used to update the first channel learning model and the one or more configuration parameters used to update the second channel learning model, and send the one or more configuration parameters used to update the second channel learning model to the second communications apparatus, so that the second communications apparatus may update the second channel learning model. Further, there is relatively good performance when the first communications apparatus and the second communications apparatus perform information transmission based on an updated first channel learning model and an updated second channel learning model. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 2:
Wang discloses the limitations of parent claims.
Wang discloses:
The method according to claim 1, wherein the data transmission requirement information comprises at least one of the following: data transmission modeling information, or second node modeling information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information.)
Regarding Claim 3:
Wang discloses the limitations of parent claims.
Wang discloses:
The method according to claim 1, wherein the data transmission requirement information comprises at least one of the following: first index information, first version information, or a collection of information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 4:
Wang discloses the limitations of parent claims.
Wang discloses:
The method according to claim 3, wherein after the receiving, by a first node, data transmission requirement information transmitted from a second node, the method further comprises: in a case that the data transmission requirement information is the first index information and/or first version information, finding, by the first node, data transmission modeling information and/or second node modeling information corresponding to the first index information and/or the first version information from locally stored information; or, in a case that the data transmission requirement information is the collection of information, decoding, by the first node, the collection of information, and obtaining specific information of the data transmission modeling information and/or specific information comprised in the second node modeling information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 6:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the data transmission modeling information comprises at least one of the following: a peak transmission rate requirement of data transmission requirements, a transmission delay requirement of the data transmission requirements, a service type of the data transmission requirements, a transmission time distribution of the data transmission requirements, or a transmission rate distribution of the transmission time distribution of the data transmission requirements. ([¶0288] The first preset threshold may be predefined in a protocol, may be indicated by the second communications apparatus to the first communications apparatus, or may be preconfigured. This is not limited in this embodiment of this application. [¶0289] The long-term statistical characteristic of the target channel may include at least one of the following: a rank value, a large-scale characteristic, a channel covariance matrix, a channel correlation matrix, a coherent time, a coherent bandwidth, and the like.[¶0290] The large-scale characteristic of the channel may be one or more of the following: a delay spread, a Doppler spread, a Doppler shift, an average gain, an average delay, an angle of arrival (AOA), an angle of arrival spread (AAS), an angle of departure (AOD), an angle of departure spread (ADS), a spatial RX parameter, and a spatial correlation. [0292] For example, if the first communications apparatus is a terminal device, and the second communications apparatus is a network device, the terminal device may determine the long-term statistical characteristic of the target channel based on the reference signal and/or the data signal sent by the network device. The reference signal may be at least one of a CSI-RS, a DMRS, a PTRS, a TRS, and an SSB, and the data signal may be at least one of a signal transmitted on the PDSCH and a signal transmitted on the PDCCH. The target channel may be a downlink channel. [¶0293] Optionally, when the variation of the long-term statistical characteristic of the target channel is greater than or equal to (or greater than) the first preset threshold, it indicates that the channel feature or the channel environment between the first communications apparatus and the second communications apparatus changes relatively greatly, and therefore the first communications apparatus may determine that the first channel learning model is not applicable. When the long-term statistical characteristic of the target channel is less than (or less than or equal to) the first preset threshold, it indicates that there is a relatively stable channel feature or channel environment between the first communications apparatus and the second communications apparatus, and therefore the first communications apparatus may determine that the first channel learning model is applicable. [¶0294] For example, the long-term statistical characteristic of the target channel is the rank value. When determining that the rank value changes relatively greatly, the first communications apparatus may determine that the first channel learning model is not applicable. For example, when determining that a variation of the rank value is greater than or equal to a preset threshold #1 (an example of the first preset threshold), the first communications apparatus may determine that the first channel learning model is not applicable. The preset threshold #1 may be R.sub.1, and R.sub.1 is a positive integer. For example, R.sub.1 is 2. That is, when the variation of the rank value is greater than or equal to 2, the first communications apparatus may determine that the first channel learning model is not applicable. For example, when the first communications apparatus moves from an environment in which there are sparse reflectors to an environment in which there are abundant reflectors, a quantity of paths on the target channel is increased, and therefore the rank value changes. In this case, the first channel learning model may no longer be applicable. A larger rank value indicates that an applicable channel learning model may be more complex, for example, the channel learning model may include a larger quantity of layers. For example, when the first communications apparatus moves from an indoor scenario to an outdoor scenario, the statistical characteristic of the channel also changes, and the first communications apparatus may determine that the first channel learning model may not be applicable. [¶0295] For example, the long-term statistical characteristic of the target channel is the Doppler shift. When determining that the Doppler shift changes relatively greatly, the first communications apparatus may determine that the first channel learning model is not applicable. Usually, the Doppler shift may refer to a change in a phase and a frequency that is caused due to a propagation distance difference when a mobile station moves in a specific direction at a constant rate. The Doppler shift reveals a rule in which an attribute of a wave changes during movement. For example, when a variation of the Doppler shift is greater than or equal to a preset threshold #2 (an example of the first preset threshold), the first communications apparatus may determine that the first channel learning model is not applicable. The preset threshold #2 may be F.sub.2, and F.sub.2 is a real number. For example, F.sub.2 is 2. That is, when the variation of the Doppler shift is greater than or equal to 2, the first communications apparatus may determine that the first channel learning model is not applicable. For example, the Doppler shift may reflect a moving speed of the first communications apparatus. When the first communications apparatus moves from a walking scenario to a vehicle-mounted scenario, the moving speed of the first communications apparatus is increased, and the first channel learning model may no longer be applicable. For example, the Doppler shift is related to the moving speed of the first communications apparatus and an angle between a moving direction of the first communications apparatus and an incident direction of a radio wave. A formula of calculating the Doppler shift may be as follows:)
Regarding Claim 7:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the second node modeling information comprises at least one of the following: location distribution information of the second node, type information of the second node, basic information of the second node, or communication configuration information supported by the second node. ([¶0034] With reference to the first aspect, in some implementations of the first aspect, the method further includes: the first communications apparatus determines, based on a first parameter, the one or more configuration parameters used to update the second channel learning model, where the first parameter includes at least one of the following: a cell identifier of a cell in which the first communications apparatus is located, a scenario in which the first communications apparatus is located, a type of the first communications apparatus, and a geographical location in which the first communications apparatus is located.)
Regarding Claim 8:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the determining, by the first node, a data channel model matching the data transmission requirement information at least according to the data transmission requirement information further comprises: determining, by the first node, the data channel model matching the data transmission requirement information by further obtaining at least one of the following information: radio wave propagation characteristic information, radio channel characteristic information, environmental information, or network configuration information. ([¶0286] In an implementation, the first communications apparatus may determine, based on a long-term statistical characteristic of a target channel, whether the channel learning model is applicable. For example, when the first communications apparatus determines that the long-term statistical characteristic of the target channel changes relatively greatly, it indicates that a channel feature or a channel environment between the first communications apparatus and the second communications apparatus changes relatively greatly. Therefore, the first communications apparatus may determine that the channel learning model is not applicable.)
Regarding Claim 9:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the radio wave propagation characteristic information comprises at least one of the following: a used frequency band, or a propagation mode. ([¶0295] For example, the long-term statistical characteristic of the target channel is the Doppler shift. When determining that the Doppler shift changes relatively greatly, the first communications apparatus may determine that the first channel learning model is not applicable. Usually, the Doppler shift may refer to a change in a phase and a frequency that is caused due to a propagation distance difference when a mobile station moves in a specific direction at a constant rate. The Doppler shift reveals a rule in which an attribute of a wave changes during movement. For example, when a variation of the Doppler shift is greater than or equal to a preset threshold #2 (an example of the first preset threshold), the first communications apparatus may determine that the first channel learning model is not applicable. The preset threshold #2 may be F.sub.2, and F.sub.2 is a real number. For example, F.sub.2 is 2. That is, when the variation of the Doppler shift is greater than or equal to 2, the first communications apparatus may determine that the first channel learning model is not applicable. For example, the Doppler shift may reflect a moving speed of the first communications apparatus. When the first communications apparatus moves from a walking scenario to a vehicle-mounted scenario, the moving speed of the first communications apparatus is increased, and the first channel learning model may no longer be applicable. For example, the Doppler shift is related to the moving speed of the first communications apparatus and an angle between a moving direction of the first communications apparatus and an incident direction of a radio wave.)
Regarding Claim 10:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the radio channel characteristic information comprises at least one of the following: a large-scale fading characteristic, a small-scale fading characteristic, a time domain change rule of a radio channel, a frequency domain change rule of the radio channel, a space domain change rule of the radio channel, or a change rule of the radio channel under a determined application scenario. ([¶0295] For example, the long-term statistical characteristic of the target channel is the Doppler shift. When determining that the Doppler shift changes relatively greatly, the first communications apparatus may determine that the first channel learning model is not applicable. Usually, the Doppler shift may refer to a change in a phase and a frequency that is caused due to a propagation distance difference when a mobile station moves in a specific direction at a constant rate. The Doppler shift reveals a rule in which an attribute of a wave changes during movement. For example, when a variation of the Doppler shift is greater than or equal to a preset threshold #2 (an example of the first preset threshold), the first communications apparatus may determine that the first channel learning model is not applicable. The preset threshold #2 may be F.sub.2, and F.sub.2 is a real number. For example, F.sub.2 is 2. That is, when the variation of the Doppler shift is greater than or equal to 2, the first communications apparatus may determine that the first channel learning model is not applicable. For example, the Doppler shift may reflect a moving speed of the first communications apparatus. When the first communications apparatus moves from a walking scenario to a vehicle-mounted scenario, the moving speed of the first communications apparatus is increased, and the first channel learning model may no longer be applicable. For example, the Doppler shift is related to the moving speed of the first communications apparatus and an angle between a moving direction of the first communications apparatus and an incident direction of a radio wave.)
Regarding Claim 11:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the environmental information comprises at least one of the following: geographical location information of a radio communication network, topographic information of the radio communication network, weather condition information of the radio communication network, or electromagnetic interference information of the radio communication network. ([¶0061] With reference to the third aspect, in some implementations of the third aspect, that a first communications apparatus determines whether a first channel learning model is applicable includes: when a scenario changes, the first communications apparatus determines that the first channel learning model is not applicable; or when a scenario does not change, the first communications apparatus determines that the first channel learning model is applicable, where the scenario includes at least one of the following: an indoor still scenario, an outdoor still scenario, a low-speed moving scenario, a high-speed moving scenario, a suburban scenario, an urban scenario, a macro base station, a micro base station, a vehicle-mounted scenario, a vehicle-to-another device scenario, and a scenario defined in a 3GPP protocol.)
Regarding Claim 12:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the network configuration information comprises at least one of the following: network topology information, network node location information, network node basic information, or network supported communication configuration information. ([¶0810] Further, the terminal device may send information about the capability of the terminal device to the network device, in other words, the terminal device may report the capability of the terminal device to the network device. For example, the terminal device may report whether channel learning model training is supported, or report a terminal type.)
Regarding Claim 13:
Wang discloses the limitations of parent claims.
Wang discloses:
A method for receiving a data channel model, comprising: transmitting, by a second node, data transmission requirement information to a first node; ([¶0025] Based on the foregoing technical solution, the second communications apparatus may indicate, by using signaling, the first communications apparatus to determine whether the first channel learning model is applicable, so that when finding that the first channel learning model is not applicable, the second communications apparatus indicates, in a timely manner, the first communications apparatus to perform verification, to reduce a delay of determining whether the first channel learning model is applicable. In addition, when finding, in a timely manner, that first channel learning is not applicable, the second communications apparatus may update the first channel learning model in a timely manner, to avoid degradation of communication performance caused when the first channel learning model is not applicable.). and receiving, by the second node, data channel model information determined at least according to the data transmission requirement information transmitted from the first node, and obtaining, from the data channel model information, at least one of the following: N functional modules, or configuration information of M functional modules, wherein N and M are integers greater than or equal to 1. ([¶0044] Based on the foregoing solution, when determining that the first channel learning model is not applicable, the first communications apparatus may determine one or more configuration parameters used to update the first channel learning model and the one or more configuration parameters used to update the second channel learning model, and send the one or more configuration parameters used to update the second channel learning model to the second communications apparatus, so that the second communications apparatus may update the second channel learning model. Further, there is relatively good performance when the first communications apparatus and the second communications apparatus perform information transmission based on an updated first channel learning model and an updated second channel learning model. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 14:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the data transmission requirement information comprises at least one of the following: data transmission modeling information, or second node modeling information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information.)
Regarding Claim 15:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein the data transmission requirement information comprises at least one of the following: first index information, first version information, or a collection of information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 16:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein after the transmitting, by a second node, data transmission requirement information to a first node, the method further comprises: in a case that the data transmission requirement information is the first index information and/or first version information, finding, by the second node, data transmission modeling information and/or second node modeling information corresponding to the first index information and/or the first version information from locally stored information; or, in a case that the data transmission requirement information is the collection of information, decoding, by the second node, the collection of information, and obtaining specific information of the data transmission modeling information and/or specific information comprised in the second node modeling information. ([¶0043] With reference to the second aspect, in some implementations of the second aspect, the first message is further used to indicate one or more configuration parameters used to update the second channel learning model, and the second channel learning model is used to determine the second channel information based on the first channel information. [¶0192] A configuration parameter of the channel learning model in this step may be one or more of a transformation algorithm, a weight vector, a weight matrix, a bias vector, a bias matrix, an activation function, a quantity of dimensions of an input layer, a quantity of dimensions of an output layer, a quantity of hidden layers, a quantity of neurons at the hidden layer, and the like.)
Regarding Claim 18:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein after the obtaining, from the data channel model information, at least one of the following: N functional modules, and configuration information of M functional modules, the method further comprises: using, by the second node, the N functional modules in a data transmission process; and/or generating, by the second node, the M functional modules according to the configuration information of M functional modules, and using the M functional modules in a data transmission process. ([¶0033] Based on the foregoing solution, when determining that the first channel learning model is not applicable, the second communications apparatus may determine the one or more configuration parameters used to update the first channel learning model and one or more configuration parameters used to update the second channel learning model, and send the one or more configuration parameters used to update the first channel learning model to the first communications apparatus, so that the first communications apparatus may update the first channel learning model. Further, there is relatively good performance when the first communications apparatus and the second communications apparatus perform information transmission based on an updated first channel learning model and an updated second channel learning model.)
Regarding Claim 19:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein other functional modules required by the second node in the data transmission process are determined in one of the following manners: indicated by the first node, configured according to a local default of the second node, or determined by the second node. ([¶0031] Based on the foregoing solution, when determining that the first channel learning model is not applicable, the first communications apparatus may determine one or more configuration parameters used to update the first channel learning model and the one or more configuration parameters used to update the second channel learning model, and send the one or more configuration parameters used to update the second channel learning model to the second communications apparatus, so that the second communications apparatus may update the second channel learning model. Further, there is relatively good performance when the first communications apparatus and the second communications apparatus perform information transmission based on an updated first channel learning model and an updated second channel learning model.)
Regarding Claim 20:
Wang discloses:
A method for transmitting information, comprising: receiving, by a second node, a first type of control information transmitted from a first node, wherein the first type of control information is configured to indicate a data channel generation mode; ([¶0148) In addition, the terminal device may further include sensors such as an intelligent printer, a train detector, and a gas station. Main functions include collecting data (some terminal devices), receiving control information and downlink data of a network device, sending [¶0300] The first scheduling information may include at least one of the following: a modulation and coding scheme (MCS) indication, a transport block size (TBS) indication, a rank indication, an antenna port indication, and the like. The first scheduling information may be downlink control information (DCI) at a physical layer, or may be scheduling information in higher layer signaling. Specifically, for content and an indication manner included in the first scheduling information, refer to the conventional technology. For brevity, details are not described in this embodiment of this application.) wherein the data channel generation mode comprises at least one of the following: a stored first data channel generation mode, or a second data channel generation mode for determining a data channel by means of a data channel model; wherein the data channel model is determined in the following manners: data transmission requirement information transmitted from the second node is received by the first node; and the data channel model matching the data transmission requirement information is determined at least according to the data transmission requirement information. ([¶0299] In another implementation, the first communications apparatus may determine, based on received first scheduling information, whether the first channel learning model is applicable. The first scheduling information may be determined by the second communications apparatus based on the second channel information, and the second communications apparatus may send the first scheduling information to the first communications apparatus. [¶0301] The MCS indication may be used to indicate a modulation scheme (or a modulation order) and a code rate for data transmission. For example, an indication manner in the following table may be used for the MCS indication (Table 1 and Table 2). A modulation order in the second column and a target code rate may be determined by indicating an MCS index in the first column in the following table. A modulation order 2 represents quadrature phase shift keying (QPSK), a modulation order 4 represents 16 quadrature amplitude modulation (16QAM, quadrature amplitude modulation), a modulation order 6 represents 64QAM, and a modulation order 6 represents 256QAM. Alternatively, another indication manner may be used for the MCS indication. Specifically, this is not limited in this application. For example, the modulation scheme and the code rate may be separately indicated. [¶0311] The scheduling information of the data may reflect a quality status of a channel. Therefore, the first communications apparatus may determine appropriate scheduling information (namely, the second scheduling information) of the data based on the measured target channel (or an actual channel). The second communications apparatus may determine the second channel information based on the second channel learning model and the first channel information fed back by the first communications apparatus, and may determine the scheduling information (namely, the first scheduling information) of the data based on the second channel information. When there is a relatively large difference between the second scheduling information determined by the first communications apparatus and the first scheduling information indicated by the second communications apparatus to the first communications apparatus, it indicates that there is a relatively large difference between the second channel information and the target channel information, in other words, the first channel learning model is not applicable. Therefore, the first communications apparatus may determine, in at least one of the following manners, whether the first channel learning model is applicable.)
21:
Wang discloses the limitations of parent claims.
Wang discloses:
wherein in a case that the data channel generation manner indicated by the first type of control information is the first data channel generation manner, a second type of control information is detected by the second node; ([¶0148) In addition, the terminal device may further include sensors such as an intelligent printer, a train detector, and a gas station. Main functions include collecting data (some terminal devices), receiving control information and downlink data of a network device, sending [¶0300] The first scheduling information may include at least one of the following: a modulation and coding scheme (MCS) indication, a transport block size (TBS) indication, a rank indication, an antenna port indication, and the like. The first scheduling information may be downlink control information (DCI) at a physical layer, or may be scheduling information in higher layer signaling. Specifically, for content and an indication manner included in the first scheduling information, refer to the conventional technology. For brevity, details are not described in this embodiment of this application.) and data transmission on a first type of data channel is completed according to scheduling information of the first type of data channel carried in the second type of control information, after the second type of control information is detected by the second node; or, in a case that the data channel generation manner indicated by the first type of control information is the second data channel generation manner, data transmission on the second data channel is completed according to the data channel model. ([¶0299] In another implementation, the first communications apparatus may determine, based on received first scheduling information, whether the first channel learning model is applicable. The first scheduling information may be determined by the second communications apparatus based on the second channel information, and the second communications apparatus may send the first scheduling information to the first communications apparatus. [¶0301] The MCS indication may be used to indicate a modulation scheme (or a modulation order) and a code rate for data transmission. For example, an indication manner in the following table may be used for the MCS indication (Table 1 and Table 2). A modulation order in the second column and a target code rate may be determined by indicating an MCS index in the first column in the following table. A modulation order 2 represents quadrature phase shift keying (QPSK), a modulation order 4 represents 16 quadrature amplitude modulation (16QAM, quadrature amplitude modulation), a modulation order 6 represents 64QAM, and a modulation order 6 represents 256QAM. Alternatively, another indication manner may be used for the MCS indication. Specifically, this is not limited in this application. For example, the modulation scheme and the code rate may be separately indicated. [¶0311] The scheduling information of the data may reflect a quality status of a channel. Therefore, the first communications apparatus may determine appropriate scheduling information (namely, the second scheduling information) of the data based on the measured target channel (or an actual channel). The second communications apparatus may determine the second channel information based on the second channel learning model and the first channel information fed back by the first communications apparatus, and may determine the scheduling information (namely, the first scheduling information) of the data based on the second channel information. When there is a relatively large difference between the second scheduling information determined by the first communications apparatus and the first scheduling information indicated by the second communications apparatus to the first communications apparatus, it indicates that there is a relatively large difference between the second channel information and the target channel information, in other words, the first channel learning model is not applicable. Therefore, the first communications apparatus may determine, in at least one of the following manners, whether the first channel learning model is applicable.)
Regarding Claim 27:
Wang discloses the limitations of parent claims.
Wang discloses:
An electronic apparatus, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to implement the method according to claim 1. ([¶0103] According to a ninth aspect, a communications apparatus is provided, and includes a processor. The processor is coupled to a memory, and may be configured to execute instructions in the memory, to implement the method in any one of the possible implementations of the first aspect and the third aspect. Optionally, the communications apparatus further includes the memory. Optionally, the communications apparatus further includes a communications interface, and the processor is coupled to the communications interface.)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUGH MARK ASHLEY whose telephone number is (571)272-0199. The examiner can normally be reached M-F 8-430.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Asad Nawaz can be reached at (571) 272-3988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUGH MARK ASHLEY/Examiner, Art Unit 2463
/ASAD M NAWAZ/Supervisory Patent Examiner, Art Unit 2463
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