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 Objections
Claim 19 objected to because of the following informalities: Claim 19 is directed to a method claim but depending on non-transitory computer readable medium. Appropriate correction is required.
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.
Claim(s) 1, 2, 5-7, 9, 10, 13-15, 17, 18 and 20-23is/are rejected under 35 U.S.C. 103 as being unpatentable over Tarver (U.S. PG-PUB NO. 2023/0046481) in view of Bellamkonda (U.S. PG-PUB NO. 2022/0210789).
-Regarding claim 1, Tarver discloses an apparatus comprising: a wireless receiver configured to receive a respective plurality of receive signals from a respective receiving antenna of a plurality of receiving antennas (RX subarrays 904, FIG. 9A, 9B, paragraph 90); an interference mitigation circuit coupled to the respective receiving antenna (subtracts the self-interference estimate from each receiver to produce a residual signal, paragraph 106), the interference mitigation circuit configured to receive an interference mitigation mode signal (processor 960 learns the GMP coefficients via the following optimization for each transmit signal, paragraph 111) wherein, in response to the interference mitigation mode signal, the interference mitigation circuit is configured to mitigate the interference while receiving the plurality of receive signals (the processor 960 learns FIR filters of length K, hi,s;j,r[k], that minimize the squared error between all N*S PA estimated output signals and the jth receive signal, paragraph 113).
Tarver is silent to teaching that the interference mitigation circuit including a neural network and wherein the interference mitigation mode signal indicating two or more interference types of a plurality of interference types and to mitigate the interference of the plurality of interference types. However, the claimed limitation is well known in the art as evidenced by Bellamkonda.
In the same field of endeavor, Bellamkonda teaches the interference mitigation circuit including a neural network (paragraph 19) and wherein the interference mitigation mode signal indicating two or more interference types of a plurality of interference types and to mitigate the interference of the plurality of interference types (interference models 203, FIG. 3, paragraph 51).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Tarver with the teaching of Bellamkonda in order to reducing or eliminating the need for manual intervention in order to determine or implement such actions.
-Regarding claim 2, the combination further discloses the interference mitigation circuit is configured to mitigate the two or more interference types based on adjusting weights applied by the neural network for adjusted signals (Bellamkonda, one or more interference models associated with particular amounts and/or types of RF interference, paragraph 85).
-Regarding claim 5, the combination further discloses the interference mitigation mode signal indicates a full mode of operation, wherein in the full mode of operation, the interference mitigation circuit is configured to adjust the weights to a common set of values for all of the two or more interference types (Bellamkonda, set of sector models 201, such as example sector models 201-1, 201-2, and 201-M, paragraph 33).
-Regarding claim 6, the combination further disclose the interference mitigation mode signal indicates an individual mode of operation, wherein in the individual mode of operation, the interference mitigation circuit is configured to adjust the weights to a different set of values for each of the two or more interference types (Bellamkonda, interference models 203-1, 203-2, and 203-L, paragraph 33).
-Regarding claim 7, the combination further discloses he interference mitigation mode signal indicates a partial mode of operation, wherein in the partial mode of operation, the interference mitigation circuit is configured to adjust the weights to a first set of values for at least two of the two or more interference types, and adjust the weights to a second set of values for others of the two or more interference types (Bellamkonda, a set of actions/parameters 205, such as example actions/parameters 205-1, 205-2, and 205-N, paragraph 33).
-Regarding claim 9, Tarver discloses a non-transitory computer readable medium comprising instructions (paragraph 11) that, when executed, cause a wireless communication device to: receive a respective receive signal from a respective receiving antenna of a plurality of receiving antennas (RX subarrays 904, FIG. 9A, 9B, paragraph 90); and in response to the interference mitigation mode signal, mitigate interference while receiving the receive signal (the processor 960 learns FIR filters of length K, hi,s;j,r[k], that minimize the squared error between all N*S PA estimated output signals and the jth receive signal, paragraph 113).
Tarver is silent to teaching that receive an interference mitigation mode signal indicating two or more interference types of a plurality of interference types to mitigate. However, the claimed limitation is well known in the art as evidenced by Bellamkonda.
In the same field of endeavor, Bellamkonda teaches receive an interference mitigation mode signal indicating two or more interference types of a plurality of interference types to mitigate (interference models 203, FIG. 3, paragraph 51).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Tarver with the teaching of Bellamkonda in order to reducing or eliminating the need for manual intervention in order to determine or implement such actions.
-Regarding claim 10, the combination further discloses the instructions are further executable to cause the wireless communication device to mitigate the two or more interference types by adjusting weights by the neural network for adjusted signals (Bellamkonda, one or more interference models associated with particular amounts and/or types of RF interference, paragraph 85).
-Regarding claim 13, the combination further discloses cause the wireless communication device to, in response to the interference mitigation mode signal indicating a full mode of operation, adjusting the weights to a common set of values for all of the two or more interference types (Bellamkonda, set of sector models 201, such as example sector models 201-1, 201-2, and 201-M, paragraph 33).
-Regarding claim 14, the combination further discloses the executable instructions are further configured to cause the wireless communication device to, in response to the interference mitigation mode signal indicating an individual mode of operation, adjusting the weights to different sets of values for each of the two or more interference types (Bellamkonda, interference models 203-1, 203-2, and 203-L, paragraph 33).
-Regarding claim 15, the combination further discloses the executable instructions are further configured to cause the wireless communication device to, in response to the interference mitigation mode signal indicates a partial mode of operation, adjusting the weights to a first set of values for at least two of the two or more interference types, and adjusting the weights to a second set of values for others of the two or more interference types (Bellamkonda, a set of actions/parameters 205, such as example actions/parameters 205-1, 205-2, and 205-N, paragraph 33).
-Regarding claim 17, Tarver discloses a method, comprising: receiving a respective plurality of receive signals from a respective receiving antenna of a plurality of receiving antennas (RX subarrays 904, FIG. 9A, 9B, paragraph 90); and in response to the interference mitigation mode signal, mitigating interference of the plurality of interference while receiving the plurality of receive signals (the processor 960 learns FIR filters of length K, hi,s;j,r[k], that minimize the squared error between all N*S PA estimated output signals and the jth receive signal, paragraph 113).
Tarver is silent to teaching that receiving an interference mitigation mode signal indicating two or more interference types of a plurality of interference types to mitigate. However, the claimed limitation is well known in the art as evidenced by Bellamkonda.
In the same field of endeavor, Bellamkonda teaches receiving an interference mitigation mode signal indicating two or more interference types of a plurality of interference types to mitigate (interference models 203, FIG. 3, paragraph 51).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Tarver with the teaching of Bellamkonda in order to reducing or eliminating the need for manual intervention in order to determine or implement such actions.
-Regarding claim 18, the combination further discloses mitigating the two or more interference types by adjusting weights by a neural network for adjusted signals (Bellamkonda, paragraph 19).
-Regarding claim 21, the combination further discloses in response to the interference mitigation mode signal indicating a full mode of operation, adjusting the weights to a common set of values for all of the two or more interference types (Bellamkonda, set of sector models 201, such as example sector models 201-1, 201-2, and 201-M, paragraph 33).
-Regarding claim 22, the combination further discloses in response to the interference mitigation mode signal indicating an individual mode of operation, adjusting the weights to a different set of values for each of the two or more interference types (Bellamkonda, interference models 203-1, 203-2, and 203-L, paragraph 33).
-Regarding claim 23, the combination further discloses in response to the interference mitigation mode signal indicating a partial mode of operation, adjusting the weights to a first set of values for at least two of the two or more interference types, and adjusting the weights to a second set of values for others of the two or more interference types (Bellamkonda, a set of actions/parameters 205, such as example actions/parameters 205-1, 205-2, and 205-N, paragraph 33).
Claim(s) 3, 4, 8, 11, 12, 16 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tarver (U.S. PG-PUB NO. 2023/0046481) in view of Bellamkonda (U.S. PG-PUB NO. 2022/0210789) and further in view of Luo (U.S. PG-PUB NO. 2021/0320678).
-Regarding claim 3, the combination is silent to teaching that a first layer of multiplication/accumulation units (MAC units) of a plurality of layers of MAC units configured to mix the plurality of transmit signals as input data and delayed versions of respective outputs of the first layer of MAC units using a plurality of weights to generate first intermediate processing results; and additional layers of MAC units of the plurality of layers of MAC units, each additional layer of MAC units configured to mix the first intermediate processing results and delayed versions of respective outputs of the respective additional layer of MAC units using additional weights of the plurality of weights to generate second intermediate processing results. However, the claimed limitation is well known in the art as evidenced by Luo.
In the same field of endeavor, Luo teaches a first layer of multiplication/accumulation units (MAC units) of a plurality of layers of MAC units configured to mix the plurality of transmit signals as input data (MAC units 562a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the first layer of MAC units using a plurality of weights to generate first intermediate processing results (delay units 563a-c, FIG. 5D, paragraph 112); and additional layers of MAC units of the plurality of layers of MAC units, each additional layer of MAC units configured to mix the first intermediate processing results (MAC units 566a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the respective additional layer of MAC units using additional weights of the plurality of weights to generate second intermediate processing results (delay units 567a-c, FIG. 5D, paragraph 112).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination with the teaching of Luo in order to increase capacity of their respective communication network.
-Regarding claim 4, the combination further discloses the interference mitigation circuit is configured to provide the adjusted signals as output data, the output data based partly on the second intermediate processing results, and wherein each wireless receiver is configured to receive a corresponding adjusted signal of the plurality of adjusted signals (Luo, MAC units 566a-c, FIG. 5D, paragraph 112).
-Regarding claim 8, the combination further discloses a number of the plurality of layers of MAC units corresponds to a number of transmitting antennas of the plurality of transmitting antennas (Luo, input data to be transmitted from a plurality of antennas coupled to an electronic device 110 in which the recurrent neural network 512 is implemented, paragraph 95).
-Regarding claim 11, the combination further discloses the instructions are further executable to cause the wireless communication device to: mix, by a first layer of multiplication/accumulation units (MAC units) of a plurality of layers of MAC units of the neural network, the plurality of transmit signals as input data (Luo, MAC units 562a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the first layer of MAC units using a plurality of weights to generate first intermediate processing results (Luo, delay units 563a-c, FIG. 5D, paragraph 112); and mix, by each additional layer of additional layers of MAC units of the plurality of layers of MAC units, the first intermediate processing results (Luo, MAC units 566a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the respective additional layer of MAC units using additional weights of the plurality of weights to generate second intermediate processing results (Luo, delay units 567a-c, FIG. 5D, paragraph 112).
-Regarding claim 12, the combination further discloses provide the adjusted signals as output data, the output data based partly on the second intermediate processing results, and receive a corresponding adjusted signal of the adjusted signals (Luo, MAC units 566a-c, FIG. 5D, paragraph 112).
-Regarding claim 16, the combination further discloses a number of the plurality of layers of MAC units corresponds to a number of transmitting antennas of a plurality of transmitting antennas including the respective transmitting antenna (Luo, input data to be transmitted from a plurality of antennas coupled to an electronic device 110 in which the recurrent neural network 512 is implemented, paragraph 95).
-Regarding claim 19, the combination further discloses mixing, by a first layer of multiplication/accumulation units (MAC units) of a plurality of layers of MAC units of the neural network, the plurality of transmit signals as input data (Luo, MAC units 562a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the first layer of MAC units using a plurality of weights to generate first intermediate processing results (Luo, delay units 563a-c, FIG. 5D, paragraph 112); and mixing, by each additional layer of additional layers of MAC units of the plurality of layers of MAC units, the first intermediate processing results (Luo, MAC units 566a-c, FIG. 5D, paragraph 112) and delayed versions of respective outputs of the respective additional layer of MAC units using additional weights of the plurality of weights to generate second intermediate processing results (Luo, delay units 567a-c, FIG. 5D, paragraph 112).
-Regarding claim 20, the combination further discloses providing the adjusted signals as output data, the output data based partly on the second intermediate processing results, and receiving a corresponding adjusted signal of the plurality of adjusted signals (Luo, MAC units 566a-c, FIG. 5D, paragraph 112).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PING Y HSIEH whose telephone number is (571)270-3011. The examiner can normally be reached Monday-Friday, 9am-4pm.
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/PING Y HSIEH/ Primary Examiner, Art Unit 2664