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 .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-45 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Regarding the independent claims 1, 15, 26, 37, 40, and 43, while the approximated distribution of the input signal/shaped constellation is one step behind the empirical distribution, this measurement (empirical) is known within wireless communication. As shown in the new secondary reference Shea does disclose the measuring of the probability distribution.
Claim Rejections - 35 USC § 103
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 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 1-2, 4-6, 8-9, 13-16, 18-20, 22-27, 29-31, 33, 37-38, 40-41, and 43-44 are rejected under 35 U.S.C. 103 as being unpatentable over WU et al. (WO 2022222094 A1, hereinafter Wu) in view of O’Shea et al. (US 20190274108 A1, hereinafter Shea).
Regarding claims 1, 26, 40, and 43 Wu discloses:
perform probabilistic shaping on a set of information bits to generate a set of shaped bits in accordance with a target probability distribution; (Paragraph [0003], “a modulation constellation, in which each point in the constellation represents one or more bits.” And paragraph [0014], “determine a probabilistic amplitude shaping for a modulation constellation of a signal to be transmitted to a UE, transmit, to the UE, a probability distribution indicator that is associated with the probabilistic amplitude shaping, modulate the signal to be transmitted to the UE using the probabilistic amplitude shaping to generate a shaped modulation constellation…” And paragraph [0017], “the probability distribution indicator provides an estimated divergence between a target distribution and an approximated distribution of the shaped modulation constellation.” The set of information bits (in the modulation constellation) was modulated in accordance with a target probability distribution and the probability distribution indicator approximates how close it was to the target probability distribution.)
and transmit, to a second wireless communications device, a shaped message generated based at least in part on the set of shaped bits, (Paragraph [0014], “and transmit the shaped modulation constellation to the UE.”)
wherein transmission of the shaped message is based at least in part on a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfying a threshold. (Paragraph [0016], “determine a probabilistic amplitude shaping for a modulation constellation of a signal to be transmitted to a UE, transmit, to the UE, a probability distribution indicator that is associated with the probabilistic amplitude shaping, modulate the signal to be transmitted to the UE using the probabilistic amplitude shaping to generate a shaped modulation constellation, and transmit the shaped modulation constellation to the UE.” Paragraph [0017], “the probability distribution indicator provides an estimated divergence between a target distribution and an approximated distribution [empirical] of the shaped modulation constellation.” And paragraph [0010], “the scaling is based on a probability distribution indicator that provides an estimated divergence between a target distribution and an approximated distribution of the input signal, where the estimated divergence may be less than a threshold value.” The apparatus transmits the shaped modulated constellation using the PAS which uses the indicator. The use of this indicator is only valid when it passes the threshold check and thus the transmission is based at least in part on this indicator that satisfies the threshold.)
Wu does not fully disclose:
wherein the empirical probability distribution is a measured probability distribution of the shaped message.Shea discloses:
wherein the empirical probability distribution is a measured probability distribution of the shaped message. (Paragraph [0143], “The system 200 may perform a first distance computation 214 between the received signal outputted from radio reception 208 and the simulated received signal outputted from the approximated channel 210. The first distance computation 214 may be a loss function. The first distance computation 214 may be any suitable measure of distance between the two received signals, such as (i) cross-entropy, (ii) a geometric distance metric, (iii) a measure of probability distribution, or (iv) a measure distance between characterizing the two received signals (e.g. mean, variance, envelope statistics, phase statistics, etc.). The results of the first distance computation 214 are provided to approximated channel updates 218 in order to update the channel machine-learning network of the approximated channel 210. Here, the objective of the approximated channel updates 218 is to minimize the first distance computation 214 in future iterations of the training process.” The empirical probability distribution is known within wireless communication.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have modified the probability distribution indicator of Wu to calculate the approximated distribution as taught in Shea. One would have been motivated to do this is to minimize the difference in approximated and empirical “in future iterations” (Shea paragraph [0143]).
Specifically regarding claims 1 and 43 Wu discloses:
One or more memories; a transceiver and at least one processor (Paragraph [0014], “The apparatus may include a processor, memory coupled with the processor, and instructions stored in the memory.” And paragraph [0082], “In some examples, the transmitter 715 may be co-located with a receiver 710 in a transceiver module.”)
A non-transitory computer-readable medium (Paragraph [0017], “In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein”)
Regarding claims 2, 16, and 27 Wu discloses:
the empirical probability distribution is an empirical probability distribution of the set of shaped bits. (Paragraph [0003], “a modulation constellation, in which each point in the constellation represents one or more bits.” And paragraph [0017], “the probability distribution indicator provides an estimated divergence between a target distribution and an approximated distribution [empirical] of the shaped modulation constellation.”)
Regarding claims 4, 18, and 29 Wu discloses:
modulate the set of shaped bits to generate a set of modulated symbols, wherein the empirical probability distribution is an empirical probability distribution of respective amplitudes of the set of modulated symbols. (Paragraph [0031], “For PCS, a transmitting device (e.g., a base station or UE) may use a set of non-uniformly distributed bits [shaped bits] for amplitude mapping during modulation of a transmission to a receiving device (e.g., a base station or UE).” The probabilistic distribution indicator transmitted will hold the empirical probability distribution for this transmission.)
Regarding claims 5, 19, 30, 38, 41, 44 Wu discloses:
the distribution closeness metric quantifies a difference between the empirical probability distribution and the target probability distribution. (Paragraph [0017], “the probability distribution indicator provides an estimated divergence [difference] between a target distribution and an approximated distribution [empirical] of the shaped modulation constellation.”)
Regarding claims 6, 20, and 31 Wu discloses:
the distribution closeness metric is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance. (Paragraph [0010], “the probability distribution indicator may be calculated at the UE as a parameter that provides a minimum Kullback–Leibler divergence between an approximated Maxwell-Boltzmann distribution of the input signal and the target distribution.”)
(NOTE claim 33 is a combination of 8 and 9, and will be addressed in the relevant claims.)
Regarding claims 8, 22, 33 Wu discloses:
determine the threshold based at least in part on a parameter of the shaped message. (Paragraph [0004], “the probability distribution parameter may be estimated at the receiving device (e.g., as a value that provides a divergence between a target distribution and an approximated distribution of the input signal that is a minimum or less than a threshold value).” And paragraph [0043], “The number of bits carried by each resource element may depend on the modulation scheme (e.g., the order of the modulation scheme, the coding rate of the modulation scheme, or both).” The threshold for the divergence must be adjusted based on the order of the modulation scheme because the order determines the target distribution.)
Regarding claims 9, 23, 33 Wu discloses:
the parameter is a quantity of modulation symbols in a shaping block, a quantity of bits in a shaping block, a shaping rate, a modulation order, or a combination thereof. (Paragraph [0043], “The number of bits carried by each resource element may depend on the modulation scheme (e.g., the order of the modulation scheme, the coding rate of the modulation scheme, or both).” )
Regarding claims 13 and 24 Wu discloses:
receive signaling indicating the distribution closeness metric. (Paragraph [0007], “The apparatus may include means for receiving an input signal from a transmitter on a wireless resource, means for estimating a channel noise between the UE and the transmitter associated with the wireless resource to determine a channel noise estimate, means for scaling the input signal and the channel noise estimate to generate a scaled input signal and a scaled channel noise estimate, where the scaling is based on a probability distribution parameter that is associated with a probabilistic amplitude shaping [PAS]” And paragraph [0080], “The device 705 may include a receiver 710, a transmitter 715, and a communications manager 720. The device 705 may also include a processor.” The scaling is based off this parameter that is associated with the PAS. The PAS utilizes a probability distribution indicator transmitted to measure the closeness (target minus approximated). The devices/apparatus includes a receiver and transmitter thus the function of receiving this signal is enabled by both first and second device in the claimed invention.)
Regarding claims 14 and 25 Wu discloses:
receive signaling indicating the target probability distribution. (Paragraph [0007], “The apparatus may include means for receiving an input signal from a transmitter on a wireless resource, means for estimating a channel noise between the UE and the transmitter associated with the wireless resource to determine a channel noise estimate, means for scaling the input signal and the channel noise estimate to generate a scaled input signal and a scaled channel noise estimate, where the scaling is based on a probability distribution parameter that is associated with a probabilistic amplitude shaping” And paragraph [0080], “The device 705 may include a receiver 710, a transmitter 715, and a communications manager 720. The device 705 may also include a processor.” From the information above, the target probability distribution must be disclosed and received otherwise the probability distribution indicator cannot calculate the closeness. The devices/apparatus includes a receiver and transmitter thus the function of receiving this signal is enabled by both first and second device in the claimed invention.)
Regarding claims 15 and 37 Wu discloses:
One or more memory; a transceiver; and at least one processor of the second wireless communication device, the at least one processor coupled with the memory and the transceiver (Paragraph [0006], “The apparatus may include a processor, memory coupled with the processor, and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to receive an input signal from a transmitter on a wireless resource” and Fig. 1. Figure 1 is the system used in accordance to the aspects of the reference and shows wireless devices sending and receiving thus a transceiver must be in the wireless communication device.)
receive, via the transceiver from a first wireless communication device, a shaped message; (Abstract, “a receiving device, such as a base station or user equipment (UE), may receive an input signal that is modulated according to a probabilistic amplitude shaping (PAS) modulation technique.”)
and output, based at least in part on a the shaped message, a signal indicating whether a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold. (Paragraph [0060], “a wireless device (e.g., a UE 115, a base station 105) may use PAS/PCS to modulate a signal. A receiving device (e.g., a base station 105 or UE 115) may receive the signal as an input signal… In some cases, the probability distribution parameter may be estimated at the receiving device (e.g., as a value that provides a divergence between a target distribution and an approximated distribution of the input signal that is a minimum or less than a threshold value).” Paragraph [0079], “the receiving device 610 may determine the probability distribution parameter as a value that is below a threshold, or a minimum value, for the KL divergence between a target distribution and an approximated M-B distribution.” In its determination/estimation the receiving device uses the target/approximated distribution of the input signal (the shaped message) to see if it satisfies this threshold for the parameter. While not explicitly stated there must be an output after this determination. )
Claims 3, 17, and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Wu and Shea in view of Nádas et al. (US 20230142425 A1, hereinafter Nádas).
Regarding claims 3, 17, and 28 Wu does not disclose:
measure the empirical probability distribution across transmission of one or more shaped messages for a target duration.
Nádas discloses:
measure the empirical probability distribution across transmission of one or more shaped messages for a target duration. (Paragraph [0054], “instead of applying packet drops uniformly at random, the calculated probability is transformed to a CTV by taking the empirical probability distribution of PVs carried by the packets observed in a given time frame.” The empirical probability distribution (EPD) is measured for a target duration. The packet values carried by the packets are non-uniformed (shaped) and thus the measurement of the EPD across this shaped packet over a given time frame (duration) is used in the transformation.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Nádas to implement this estimation of the empirical probability distribution. One would be motivated to do this to verify that the shaping is working correctly so that it does not diverge too far.
Claims 7, 21, 32, 39, 42, and 45 are rejected under 35 U.S.C. 103 as being unpatentable over Wu and Shea in view of Jozwiak et al. (US 20250198902 A1, hereinafter Jozwiak).
Regarding claims 7, 21, 32, 39, 42, and 45 Wu does not disclose:
the distribution closeness metric quantifies a difference between respective moments of one or more orders of the empirical probability distribution and the target probability distribution.
Jozwiak discloses:
the distribution closeness metric quantifies a difference between respective moments of one or more orders of the empirical probability distribution and the target probability distribution. (Paragraph [0024], “the distance can be measured between all EPDF values and theoretical values of a Chi2 probability density function. Examples of distances are Kullback-Leibler divergence and Jensen-Shannon distance, although other distances are likewise conceivable. Additionally or alternatively, at least one geometrical property of the empirical probability density function can be determined and/or various moments of EPDF (mean, variance, skewness, kurtosis, etc.)” Closeness between the EPDF and theoretical values (target) can be determined through the use of the moments.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Jozwiak to utilize moments for the distribution closeness metric. One would be motivated to do this to lower the complexity when calculating instead of using full distributions like KL divergence.
Claims 10 and 34 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Xiao et al. (WO 2022188024 A1, hereinafter Xiao).
Regarding claims 10 and 34 Wu does not disclose:
transmit the shaped message in accordance with a first maximum power reduction associated with the shaped message different from a second maximum power reduction associated with uniform quadrature amplitude modulation.
Xiao discloses:
transmit the shaped message in accordance with a first maximum power reduction associated with the shaped message different from a second maximum power reduction associated with uniform quadrature amplitude modulation. (Paragraph [0045], “The UE may select or adjust a power parameter (e.g., a power reduction parameter such as an MPR parameter) based on the constellation distribution parameter. In some examples, the UE may select the power parameter based on a correspondence between the power parameter and a respective value of the constellation distribution parameter (e.g., the UE may be configured with a table including a correspondence between a modulation scheme, the constellation distribution parameter, and the power parameter).” This is functionally similar to what is in the limitation as the UE may select different MPR based on the type of message (shaped vs uniform) that are being transmitted.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Xiao to utilize power parameters when transmitting messages. One would be motivated to do this to reduce the transmission power while maintaining reliability and throughput.
Claims 11 and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Tujkovic et al. (US 20240388488 A1, hereinafter Tujkovic).
Regarding claims 11 and 35 Wu does not disclose:
transmit the shaped message in accordance with a first error vector magnitude associated with the shaped message different from a second error vector magnitude associated with uniform quadrature amplitude modulation.
Tujkovic discloses:
transmit the shaped message in accordance with a first error vector magnitude associated with the shaped message different from a second error vector magnitude associated with uniform quadrature amplitude modulation. (Paragraph [0034], “These regions show that the CFR noise is not uniformly distributed, but varies per region. The two sub-regions means that the cancellation pulse signal will support two levels of CFR noise and, hence, two levels of EVM.” While this discloses different EVM for different regions of shaped messages, the EVM of a uniform QAM must be different from the shaped messages as well.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Tujkovic to utilize Error vector magnitude in transmission optimization. One would be motivated to do this to reduce the transmission power or adjust the shaping based on the deviated symbols.
Claims 12 and 36 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Yang et al. (US 20170279640 A1, hereinafter Yang) in further view of Niu (US 20240364444 A1, hereinafter Niu).
Regarding claims 12 and 36 Wu does not disclose:
decode the set of shaped bits;
reconstruct a demodulation symbol based in part on the decoded set of shaped bits;
and measure an error vector magnitude associated with the shaped message based in part on an equalized probabilistic shaped transmitted waveform and the demodulation symbol.
Yang discloses:
decode the set of shaped bits; (Paragraph [0090], “The bits may be processed [shaped] or evaluated by a processor (e.g., processor 104 of FIG. 1), or used to display or otherwise output information (to a user interface 122 as illustrated in FIG. 1, for example). In this way, data and/or information may be decoded… In some configurations, the demodulator 348 may include a QAM (quadrature amplitude modulation) demodulator…”)
reconstruct a demodulation symbol based in part on the decoded set of shaped bits; (Paragraph [0090], “For example, the demodulator 348 may determine a plurality of bits from symbols output by the transformer 352 and the channel estimator and equalizer 350, for example by reversing a mapping of bits to a symbol in a constellation[reconstructing]… the demodulator 348 may include a QAM [shaped] (quadrature amplitude modulation) demodulator…” The reversing of mapping bits through the demodulator (which can demodulate shaped bits) is reconstruction of the demodulation symbols.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Yang to utilize a demodulator and decoder for shaped bits. One would be motivated to do this to reduce the transmission power and “improve communication device performance” [Yang, 0005].
Niu discloses:
and measure an error vector magnitude associated with the shaped message based in part on an equalized probabilistic shaped transmitted waveform and the demodulation symbol. (Paragraph [0082], “channel equalization is performed on the second symbol data according to the channel parameter to obtain an equalized data.” And paragraph [0084], “the equalized data is demodulated according to the modulation mode to obtain the error vector magnitude.” The EVM is obtained from a demodulated equalized data.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined teachings of Wu and Shea in view of Niu to utilize equalized data and demodulation symbols to obtain the EVM. One would be motivated to do this to help accurately measure the performance of the system.
Conclusion
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/NAM P. CAO/Examiner, Art Unit 2479 /JAE Y LEE/Supervisory Patent Examiner, Art Unit 2479
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