DETAILED ACTION
This office action is responsive to communications filed on August 15, 2024. Claims 1-20 are pending in the application.
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 .
Information Disclosure Statement
The Information Disclosure Statements filed on 8/15/2024 and 5/14/2026 have been considered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter.
Claim 14 is drawn to “a computer program product, comprising computer program instructions”. Since claim 14 only recites a computer program product/instructions, it is merely software, per se. Software, per se is not statutory because it is not limited to a process, machine, article of manufacture, or composition of matter. Instead, it merely describes computer executable instructions at a conceptual level without explicitly tying them to hardware such as a memory or non-transitory computer-readable storage medium. This rejection may be overcome by amending the claim to recite that the computer program code is comprised in a non-transitory computer-readable storage medium. However, Examiner notes that amending claim 14 in such a way would make it substantially similar in scope to independent claim 13, thus rendering claim 14 as being redundant.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3 and 12-14 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Nirula et al. (US 2019/0353800).
Regarding Claim 1, Nirula teaches a communication sensing method, comprising:
acquiring a reference signal from a satellite and a sensing signal of a target area (“FIG. 3 illustrates multipath effects on SV measurements for example SV 280-4 by UE 100 at a point in time. As shown in FIG. 3, UE 100 may be located at point L 310 at a time t … The signals received by UE 100 may include Line of Sight (LOS) signals received directly from SV 280-4, which follow path P=SL, and multipath signals (e.g. from ground reflection), reflected at point G 360, which follow path SG and GL” – See [0051]; “GNSS receiver 140 may be enabled to receive signals associated with one or more SPS/GNSS resources. Received SPS/GNSS signals may be stored in memory 130 and/or used by processor(s) 150 to determine a position of UE 100 or derive other positioning related measurements. In some embodiments, GNSS receiver 140 may include a code phase receiver and a carrier phase receiver, which may measure carrier wave related information. The carrier wave, which typically has a much higher frequency than the pseudo random noise (PRN) (code phase) sequence that it carries, may facilitate more accurate position determination and/or positioning related measurements. The term “code phase measurements” refer to measurements using a Coarse Acquisition (C/A) code receiver, which uses the information contained in the PRN sequence to calculate the position of UE 100. The term “carrier phase measurements” refer to measurements using a carrier phase receiver, which uses the carrier signal to calculate positions. The carrier signal may take the form, for example for GPS, of the signal L1 at 1575.42 MHz (which carries both a status message and a pseudo-random code for timing) and the L2 signal at 1227.60 MHz (which carries a more precise military pseudo-random code)” – See [0025]; “In some embodiments, UE 100 may determine its velocity based, in part, on GNSS doppler measurements (e.g. based on signals received by GNSS Receiver 140), which may make use of the doppler effect. The doppler effect pertains to an observed change in frequency of a received signal (e.g. at a receiver) relative to the frequency of the transmitted signal (e.g. by a transmitter) on account of relative motion between the receiver and the transmitter” – See [0026]; “Multipath from ground reflections of the signal from SV 280-4 may result in a lower GNSS doppler measurement change being observed at UE 100 (relative to that observed from a LOS signal from SV 280-4 without multipath). Thus, the accuracy and reliability of velocity and other positioning related measurements that are based on GNSS doppler measurements may be detrimentally impacted. For example, when multipath from ground reflections is present, distance traveled computations based on integrated speed from GNSS doppler measurements may be statistically lower when compared to the actual or true distance traveled by UE 100” – See [0052]; See also Fig. 3; The UE acquires a measurement signal (reference signal) from a satellite and also acquires a reflected/multipath signal (sensing signal) of a target area L); and
determining an actual value of a communication characteristic parameter of the target area based on the reference signal and the sensing signal (“Multipath from ground reflections of the signal from SV 280-4 may result in a lower GNSS doppler measurement change being observed at UE 100 (relative to that observed from a LOS signal from SV 280-4 without multipath)” – See [0052]; “For example, errors induced by multipath (e.g. ground reflections) in doppler based measurements from satellite positioning systems may be mitigated thereby facilitating greater accuracy and improved reliability. In some embodiments, statistical techniques and/or machine learning techniques may be used to mitigate error arising from multipath (e.g. ground reflections). In some embodiments, the methods may comprise an offline phase, where statistical techniques (e.g. linear regression, least squares, etc.) are used to determine relationships between GNSS doppler measurements and truth/reference measurements and obtain a mathematical model. In some embodiments, during operation (e.g. following mathematical model creation) GNSS doppler measurements (e.g. as measured by UE 100) and/or IMU measurements and/or sensor measurements and/or other parameters may be input to the mathematical model, which may output corresponding GNSS estimates (corresponding to the GNSS doppler measurements) and/or a corrected velocity of UE 100 (based, in part, on the input data)” – See [0055]; Based on the reference signal and the sensing signal, a communication characteristic (e.g., doppler measurement, velocity, etc.) is determined).
Regarding Claim 2, Nirula teaches the method of Claim 1. Nirula further teaches that the communication characteristic parameter comprises a delay and/or a Doppler frequency shift (“Because the trajectories of SVs can be known, the doppler shift for signals transmitted by a particular SV is predictable and may be used in UE positioning determination. In instances where the UE is also moving independently (e.g. due to user movement), the doppler shift may vary from the expected or predicted shift. These variations (relative to a predicted or expected doppler shift) in doppler shift for the SV may be used to determine a velocity (speed and direction of travel) of a UE” – See [0020]; “a signal received from an SV may be analyzed and processed to determine variations in doppler frequency shift relative to a nominal or expected doppler frequency shift for the satellite” – See [0028]; The characteristic includes a doppler frequency shift).
Regarding Claim 3, Nirula teaches the method of Claim 2. Nirula further teaches determining a predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area (“The mathematical model may output a doppler estimate (e.g. based on statistical techniques) based on the input parameters. The predictive model may be obtained based on machine learning and may predict a doppler estimate based on the input parameters” – See [0019]; A predicted value of the doppler shift (communication characteristic parameter of the target area) is determined based on the measured/actual value of the doppler shift in the target area).
Claims 12 and 13 are rejected based on reasoning similar to Claim 1.
Regarding Claim 14, Nirula teaches the method of Claim 1. Nirula further teaches a computer program product, comprising computer program instructions, wherein the computer program instructions, upon being executed by a processor, implement the communication sensing method according to Claim 1 (“Any machine-readable medium tangibly embodying instructions may be used in implementing the methodologies described herein. For example, software or program code (e.g. PE 156) may be stored in a computer-readable medium which may form part of memory 130 coupled to processor(s) 150. The program code (e.g. PE 156) may be read and executed by processor(s) 150” – See [0034]).
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 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Kumar et al. (US 2022/0166566).
Regarding Claim 4, Nirula teaches the method of Claim 3. Nirula does not explicitly teach determining configuration information of a communication resource based on the predicted value of the communication characteristic parameter of the target area.
However, Kumar teaches determining configuration information of a communication resource based on the predicted value of the communication characteristic parameter of the target area (“In some cases, the number or amount of RS resources that are determined in the allocation of the RS resources may be different for different Doppler shift thresholds. In other words, the BS 110a may determine different DMRS densities and allocate different numbers or amounts of RS resources (e.g., DMRSs) depending on whether the Doppler shift associated with the one or more uplink signals exceeds different Doppler shift thresholds” – See [0070]; Based on the value of the doppler shift (predicted value of the communication characteristic), a number of RS resources (configuration information of a communication resource) is determined for the UE).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include determining configuration information of a communication resource based on the predicted value of the communication characteristic parameter of the target area. Motivation for doing so would be to enable higher RS density for UEs with a higher speed/doppler shift, so that channel estimation can be improved (See Kumar, [0048]).
Regarding Claim 5, Nirula in view of Kumar teaches the method of Claim 4. Kumar further teaches that the configuration information of the communication resource comprises one or more of: a first resource proportion, a second resource proportion, and a service type supported by a resource block; the first resource proportion is used to characterize a ratio of a number of time domain units occupied by the reference signal in the resource block to a number of time domain units included in the resource block; and the second resource proportion is used to characterize a ratio of a number of frequency domain units occupied by the reference signal in the resource block to a number of frequency domain units included in the resource block (“According to aspects, based on the determined density of the RSs for the UE 120a, the BS 110a may determine an allocation of RS resources for the UE 120a, which may refer to the number of RSs within a slot as well as time and frequency resources (e.g., symbols) within the slot for carrying the RSs” – See [0066]; The configuration includes a first and second proportion, wherein the first proportion characterizes a density/ratio of RS resources in the time domain and the second proportion characterizes a density/ratio of RS resources in the frequency domain).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Ding et al. (US 2021/0314197).
Regarding Claim 9, Nirula teaches the method of Claim 3. Nirula does not explicitly teach that determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment.
However, Ding teaches performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment (“an IIR filter can be applied to stabilize the estimated channel correlation, so the final input feature to the Doppler shift predictor is only one value—the IIR-filtered estimated channel correlation. In some embodiments of the present disclosure, the Doppler shift predictor is a multi-layer perceptron (MLP). FIG. 10 is a schematic depiction of a Doppler shift predictor according to one embodiment of the present disclosure using an infinite impulse response (IIR) filter to combine a plurality of channel correlations. For example, as shown in FIG. 10, assume the current TRS period is the n-th TRS period, then there are n estimated channel correlations C1(T), C2(T), . . . , Cn(T) supplied as inputs to an infinite impulse response (IIR) filter 1010, then the IIR filtered channel correlation of these n input channel correlations may be denoted as Cn(T). In the embodiment of FIG. 10, the Doppler shift predictor is implemented as a multi-layer perceptron configured to perform regression, where the MLP has an input layer 123 with a single node configured to receive the input IIR filtered channel correlation Cn(T) and to supply the filtered channel correlations to a hidden layer 125 having a plurality of nodes in association with a plurality of weights (or parameters). At each node, the input IIR filtered channel correlation Cn(T) is multiplied by the corresponding weight, and the product is passed through an activation function (e.g., a sigmoid function or a rectified linear unit (ReLU)). An output layer 127 having a single node configured to receive and combine inputs from the plurality of nodes of the hidden layer (e.g., multiply the outputs of the activation function of the nodes of the hidden layer with weights, sum the results and pass through an activation function to compute a predicted Doppler shift” – See [0090]; A weighted sum calculation is performed on Doppler shift values at a first moment to determine a predicted Doppler shift at a second moment).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment. Motivation for doing so would be to provide more information to the Doppler shift predictor about how the channel changes over time (See Ding, [0094]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Zeng et al. (US 2021/0211912).
Regarding Claim 10, Nirula teaches the method of Claim 3. Nirula does not explicitly teach that the determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model.
However, Zeng teaches inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model (“In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, determining the predicted channel state information timing parameter further may include operations, features, means, or instructions for measuring a Doppler shift, where the predicted channel state information timing parameter may be determined based on the Doppler shift” – See [0013]; The Doppler shift (communication characteristic parameter of the target area) is input into a timing prediction model to obtain a predicted timing parameter/value by the timing prediction model).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model. Motivation for doing so would be to enable the device to provide forward-looking estimates of channel state information to provide more accurate downlink channel feedback (See Zeng, [0083]).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Axmon et al. (US 2020/0091995).
Regarding Claim 11, Nirula teaches the method of Claim 1. Nirula does not explicitly teach that the sensing signal of the target area is acquired by: receiving at least one signal through a beam matching the target area; and screening out the sensing signal from the at least one signal received from the beam matching the target area.
However, Axmon teaches that the sensing signal of the target area is acquired by: receiving at least one signal through a beam matching the target area; and screening out the sensing signal from the at least one signal received from the beam matching the target area (“The reflections of the signal associated with the at least one first beam are cancelled from the signal received by the at least one second beam (step 407). This is done by filtering the signal received in the first reception beam through the determined differential propagation channel to create a replica of the signal transmitted by the aerial radio node as received by the second reception beam (step 409). The replica is then subtracted (or otherwise canceled) from the signal received by the second reception beam (step 411)” – See [0069]; A signal is received through a reception beam. The reflected signal (sensing signal) is filtered/cancelled from (screened out from) the received signal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula such that the sensing signal of the target area is acquired by: receiving at least one signal through a beam matching the target area; and screening out the sensing signal from the at least one signal received from the beam matching the target area. Motivation for doing so would be to improve service by canceling interference (See Axmon, [0054]).
Claims 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Kumar et al. (US 2022/0166566) and further in view of Ding et al. (US 2021/0314197).
Regarding Claim 15, Nirula in view of Kumar teaches the method of Claim 4. Nirula and Kumar do not explicitly teach that the determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment.
However, Ding teaches performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment (“an IIR filter can be applied to stabilize the estimated channel correlation, so the final input feature to the Doppler shift predictor is only one value—the IIR-filtered estimated channel correlation. In some embodiments of the present disclosure, the Doppler shift predictor is a multi-layer perceptron (MLP). FIG. 10 is a schematic depiction of a Doppler shift predictor according to one embodiment of the present disclosure using an infinite impulse response (IIR) filter to combine a plurality of channel correlations. For example, as shown in FIG. 10, assume the current TRS period is the n-th TRS period, then there are n estimated channel correlations C1(T), C2(T), . . . , Cn(T) supplied as inputs to an infinite impulse response (IIR) filter 1010, then the IIR filtered channel correlation of these n input channel correlations may be denoted as Cn(T). In the embodiment of FIG. 10, the Doppler shift predictor is implemented as a multi-layer perceptron configured to perform regression, where the MLP has an input layer 123 with a single node configured to receive the input IIR filtered channel correlation Cn(T) and to supply the filtered channel correlations to a hidden layer 125 having a plurality of nodes in association with a plurality of weights (or parameters). At each node, the input IIR filtered channel correlation Cn(T) is multiplied by the corresponding weight, and the product is passed through an activation function (e.g., a sigmoid function or a rectified linear unit (ReLU)). An output layer 127 having a single node configured to receive and combine inputs from the plurality of nodes of the hidden layer (e.g., multiply the outputs of the activation function of the nodes of the hidden layer with weights, sum the results and pass through an activation function to compute a predicted Doppler shift” – See [0090]; A weighted sum calculation is performed on Doppler shift values at a first moment to determine a predicted Doppler shift at a second moment).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment. Motivation for doing so would be to provide more information to the Doppler shift predictor about how the channel changes over time (See Ding, [0094]).
Regarding Claim 16, Nirula in view of Kumar teaches the method of Claim 5. Nirula and Kumar do not explicitly teach that the determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment.
However, Ding teaches performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment (“an IIR filter can be applied to stabilize the estimated channel correlation, so the final input feature to the Doppler shift predictor is only one value—the IIR-filtered estimated channel correlation. In some embodiments of the present disclosure, the Doppler shift predictor is a multi-layer perceptron (MLP). FIG. 10 is a schematic depiction of a Doppler shift predictor according to one embodiment of the present disclosure using an infinite impulse response (IIR) filter to combine a plurality of channel correlations. For example, as shown in FIG. 10, assume the current TRS period is the n-th TRS period, then there are n estimated channel correlations C1(T), C2(T), . . . , Cn(T) supplied as inputs to an infinite impulse response (IIR) filter 1010, then the IIR filtered channel correlation of these n input channel correlations may be denoted as Cn(T). In the embodiment of FIG. 10, the Doppler shift predictor is implemented as a multi-layer perceptron configured to perform regression, where the MLP has an input layer 123 with a single node configured to receive the input IIR filtered channel correlation Cn(T) and to supply the filtered channel correlations to a hidden layer 125 having a plurality of nodes in association with a plurality of weights (or parameters). At each node, the input IIR filtered channel correlation Cn(T) is multiplied by the corresponding weight, and the product is passed through an activation function (e.g., a sigmoid function or a rectified linear unit (ReLU)). An output layer 127 having a single node configured to receive and combine inputs from the plurality of nodes of the hidden layer (e.g., multiply the outputs of the activation function of the nodes of the hidden layer with weights, sum the results and pass through an activation function to compute a predicted Doppler shift” – See [0090]; A weighted sum calculation is performed on Doppler shift values at a first moment to determine a predicted Doppler shift at a second moment).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include performing a weighted sum calculation on a first actual value of the communication characteristic parameter of the target area at a first moment and a first predicted value of the communication characteristic parameter of the target area at the first moment, so as to obtain a predicted value of the communication characteristic parameter of the target area at a second moment after the first moment. Motivation for doing so would be to provide more information to the Doppler shift predictor about how the channel changes over time (See Ding, [0094]).
Claims 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Nirula et al. (US 2019/0353800) in view of Kumar et al. (US 2022/0166566) and further in view of Zeng et al. (US 2021/0211912).
Regarding Claim 18, Nirula in view of Kumar teaches the method of Claim 4. Nirula and Kumar do not explicitly teach that the determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model.
However, Zeng teaches inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model (“In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, determining the predicted channel state information timing parameter further may include operations, features, means, or instructions for measuring a Doppler shift, where the predicted channel state information timing parameter may be determined based on the Doppler shift” – See [0013]; The Doppler shift (communication characteristic parameter of the target area) is input into a timing prediction model to obtain a predicted timing parameter/value by the timing prediction model).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model. Motivation for doing so would be to enable the device to provide forward-looking estimates of channel state information to provide more accurate downlink channel feedback (See Zeng, [0083]).
Regarding Claim 19, Nirula in view of Kumar teaches the method of Claim 5. Nirula and Kumar do not explicitly teach that the determining the predicted value of the communication characteristic parameter of the target area based on the actual value of the communication characteristic parameter of the target area comprises: inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model.
However, Zeng teaches inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model (“In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, determining the predicted channel state information timing parameter further may include operations, features, means, or instructions for measuring a Doppler shift, where the predicted channel state information timing parameter may be determined based on the Doppler shift” – See [0013]; The Doppler shift (communication characteristic parameter of the target area) is input into a timing prediction model to obtain a predicted timing parameter/value by the timing prediction model).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nirula to include inputting the actual value of the communication characteristic parameter of the target area into a timing prediction model, so as to obtain a predicted value of the communication characteristic parameter of the target area output by the timing prediction model. Motivation for doing so would be to enable the device to provide forward-looking estimates of channel state information to provide more accurate downlink channel feedback (See Zeng, [0083]).
Allowable Subject Matter
Claims 6-8, 17, and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Scott M Sciacca whose telephone number is (571)270-1919. The examiner can normally be reached Monday thru Friday, 7:30 A.M. - 5:00 P.M. EST.
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/SCOTT M SCIACCA/ Primary Examiner, Art Unit 2478
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