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 Status
This office action is in response to the communication(s) filed on 01/24/2024.
Claim(s) 1-6, 11-19, 23, and 36-39 is/are currently presenting for examination.
Claim(s) 1 and 23 is/are independent claim(s).
Claim(s) 1-6, 11-19, 23, and 36-39 is/are rejected.
This action has been made NON-FINAL.
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)(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.
(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.
Claim(s) 1, 18-19, 23, and 36-39 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US_20220052827_A1_Vitthaladevuni.
Regarding claim 1, Vitthaladevuni discloses a method for feeding back channel state information (Vitthaladevuni figures 6-8), comprising: determining a neural network parameter (Vitthaladevuni figure 7, elements 702-704), and constructing an encoder according to the neural network parameter (Vitthaladevuni figure 7, elements 706-710); compressing channel information with the encoder to obtain channel state information (Vitthaladevuni figure 7, element 712); and feeding back the channel state information (Vitthaladevuni figure 7 element 714 ).
Regarding claim 18, Vitthaladevuni discloses the method according to claim 1, wherein the determining the neural network parameter, and constructing the encoder according to the neural network parameter comprises: selecting, according to channel factor information, a neural network parameter of one AutoEncoder from pre-configured candidate neural network parameters of a set of at least one AutoEncoder as the neural network parameter; wherein each AutoEncoder comprises a pair of encoder and decoder (Vitthaladevuni paragraph 86, “The UE trains the encoder 610 and decoder 620, and occasionally transmits the decoder coefficients to the base station. At a higher frequency, the UE sends the outputs of the encoder 610 (e.g., channel state feedback or compressed output of the encoder 610) to the base station. As the UE moves from location to location, the weights of the decoder 620 may change. That is, when the channel environment changes, the decoder weights (e.g., coefficients) may change. Updated decoder coefficients can thus be fed back to the base station from the UE to reflect the changing environment. In other words, the UE can train the decoder 620, and not just the encoder 610, based on the existing environment. The coefficients can be sent from the UE in accordance with timelines configured by RRC signaling. In one configuration, the coefficients are sent less frequently in comparison to a frequency of the channel state feedback. Each UE sends the decoder coefficients and the encoder coefficients”).
Regarding claim 19, Vitthaladevuni discloses the method according to claim 1, wherein the determining the neural network parameter, and constructing the encoder according to the neural network parameter comprises: receiving neural network parameter information (Vitthaladevuni figure 7, elements 702-704); and determining the neural network parameter according to the neural network parameter information (Vitthaladevuni figure 7, element 706-712).
Regarding claim 23, Vitthaladevuni discloses the limitations as set forth in claim 1.
Regarding claim 36, Vitthaladevuni discloses the terminal, comprising: at least one processor; and a memory having at least one computer program stored thereon which, when executed by the at least one processor, causes the at least one processor to implement the method for feeding back channel state information according to claim 1; and at least one I/O interface connected between the at least one processor and the memory and configured to enable information interaction between the at least one processor and the memory (Vitthaladevuni figure 3, paragraphs 55-57).
Regarding claim 37, Vitthaladevuni discloses the base station, comprising: at least one processor; and a memory having at least one computer program stored thereon which, when executed by the at least one processor, causes the at least one processor to implement the method for receiving channel state information according to claim 23; and at least one I/O interface connected between the at least one processor and the memory and configured to enable information interaction between the at least one processor and the memory (Vitthaladevuni figure 7, element 706-712).
Regarding claim 38, Vitthaladevuni discloses a non-transitory computer-readable storage medium having a computer program stored thereon which, when executed by a processor, causes the method for feeding back channel state information according to claim 1 to be implemented (Vitthaladevuni figure 7, element 706-712).
Regarding claim 39, Vitthaladevuni discloses a non-transitory computer-readable storage medium having a computer program stored thereon which, when executed by a processor, causes the method for receiving channel state information according to claim 23 to be implemented (Vitthaladevuni figure 7, element 706-712).
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 2-6, 11, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over US_20220052827_A1_Vitthaladevuni in view of US_20240154675_A1_Shi.
Regarding claim 2, Vitthaladevuni discloses the method according to claim 1, but does not disclose wherein compressing the channel information with the encoder to obtain the channel state information comprises: pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder; and compressing the pre-processed channel information with the encoder to obtain the channel state information.
Shi discloses wherein compressing the channel information with the encoder to obtain the channel state information comprises: pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder; and compressing the pre-processed channel information with the encoder to obtain the channel state information (Shi paragraph 95, “Because an encoder in an auto-encoder may compress information into a low-dimensional representation, and a decoder in the auto-encoder may further obtain original information with proportionate precision through reconstruction, the auto-encoder well matches a transmission scenario that is limited by air interface overheads such as CSI feedback… The output result is generally a low-dimensional representation of the original input, and the low-dimensional representation may also be referred to as a compressed representation (compressed representation)… An auto-encoder technology is often used for data compression (at the transmitter) and restoration (at the receiver)…”, paragraph 96, “FIG. 5 is a schematic diagram of a CSI feedback framework based on an AI architecture... A preprocessing result is input into the encoder, and a low-dimensional code word D is obtained through compression...”, paragraph 107, “…the UE may preprocess the three-dimensional matrix, to obtain a sparse representation of the downlink channel. …”, and figures 5, 6, 10).
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Shi’s UE may preprocess the three-dimensional matrix, to obtain a sparse representation of the downlink channel in Vitthaladevuni’s system to reduce the amount of data that needs to be processed and stored, and to reduce Feedback Overhead. This method for improving the system of Vitthaladevuni was within the ordinary ability of one of ordinary skill in the art based on the teachings of Shi. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vitthaladevuni and Shi to obtain the invention as specified in claim 2.
Regarding claim 3, Vitthaladevuni and Shi disclose the method according to claim 2, and Shi further discloses wherein pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder comprises: determining a group number K of the channel information according to the dimension of the channel information and the dimension of the input data of the encoder; and dividing the channel information into K groups to obtain K groups of channel information as the pre-processed channel information, wherein each group of channel information has a dimension matched with the dimension of the input data of the encoder, where K is a positive integer (Shi figure 8, paragraphs 13-27, K column vectors, and K is a positive integer, paragraph 95, “Because an encoder in an auto-encoder may compress information into a low-dimensional representation, and a decoder in the auto-encoder may further obtain original information with proportionate precision through reconstruction, the auto-encoder well matches a transmission scenario that is limited by air interface overheads such as CSI feedback… The output result is generally a low-dimensional representation of the original input, and the low-dimensional representation may also be referred to as a compressed representation (compressed representation)… An auto-encoder technology is often used for data compression (at the transmitter) and restoration (at the receiver)…”, paragraph 96, “FIG. 5 is a schematic diagram of a CSI feedback framework based on an AI architecture... A preprocessing result is input into the encoder, and a low-dimensional code word D is obtained through compression...”, paragraph 107, “…the UE may preprocess the three-dimensional matrix, to obtain a sparse representation of the downlink channel. …”, and figures 5, 6, 10).
Regarding claim 4, Vitthaladevuni and Shi disclose the method according to claim 2, and Shi further discloses wherein pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder comprises: determining, according to a channel parameter, a group number K of the channel information (Shi paragraphs 13-27, K column vectors, and K is a positive integer, paragraph 129, “…where a dimension of a matrix of the downlink MIMO channel may be N.sub.tx*N.sub.rx*N.sub.RB. N.sub.tx represents a quantity of transmit antenna ports, including transmit antenna ports in different polarization directions. N.sub.rx represents a quantity of receive antenna ports, including receive antenna ports in different polarization directions”, and paragraph 132, “where H may be N.sub.tx*N.sub.sb-dimensional. N.sub.sb represents a quantity of frequency domain sub-bands, and a granularity of the frequency domain sub-band may be two resource blocks (resource blocks, RBs), four RBs, or the like. An example in which the granularity of the frequency domain sub-band is four RBs is used, where N.sub.sb=N.sub.RB/4.”); and dividing the channel information into K groups according to the channel parameter to obtain K groups of channel information as the pre-processed channel information, wherein each group of channel information has a dimension matched with the dimension of the input data of the encoder, where K is a positive integer (Shi paragraphs 129-135), and the channel parameter comprises at least one of: a number of antenna polarization directions (Shi paragraph 129, “…where a dimension of a matrix of the downlink MIMO channel may be N.sub.tx*N.sub.rx*N.sub.RB. N.sub.tx represents a quantity of transmit antenna ports, including transmit antenna ports in different polarization directions. N.sub.rx represents a quantity of receive antenna ports, including receive antenna ports in different polarization directions”), a number of antennas, a number of data streams, a number of time domain sampling point sets, or a number of frequency domain granularity sets (Shi paragraph 132, “where H may be N.sub.tx*N.sub.sb-dimensional. N.sub.sb represents a quantity of frequency domain sub-bands, and a granularity of the frequency domain sub-band may be two resource blocks (resource blocks, RBs), four RBs, or the like. An example in which the granularity of the frequency domain sub-band is four RBs is used, where N.sub.sb=N.sub.RB/4.”).
Regarding claim 5, Vitthaladevuni and Shi disclose the method according to claim 4, and Shi further discloses wherein dividing the channel information into K groups according to the channel parameter comprises at least one of: grouping the channel information according to the number of antenna polarization directions (Shi paragraph 129, “…where a dimension of a matrix of the downlink MIMO channel may be N.sub.tx*N.sub.rx*N.sub.RB. N.sub.tx represents a quantity of transmit antenna ports, including transmit antenna ports in different polarization directions. N.sub.rx represents a quantity of receive antenna ports, including receive antenna ports in different polarization directions”); grouping the channel information according to the number of antennas; grouping the channel information according to the number of data streams; grouping the channel information according to the number of time domain sampling point sets; or grouping the channel information according to the number of frequency domain granularity sets (Shi paragraph 132, “where H may be N.sub.tx*N.sub.sb-dimensional. N.sub.sb represents a quantity of frequency domain sub-bands, and a granularity of the frequency domain sub-band may be two resource blocks (resource blocks, RBs), four RBs, or the like. An example in which the granularity of the frequency domain sub-band is four RBs is used, where N.sub.sb=N.sub.RB/4.”).
Regarding claim 6, Vitthaladevuni and Shi disclose the method according to claim 5, and Shi further discloses wherein dividing the channel information into K groups according to the channel parameter comprises at least one of: dividing channel information corresponding to a same polarization direction into a same group of channel information (Shi paragraph 129, “…where a dimension of a matrix of the downlink MIMO channel may be N.sub.tx*N.sub.rx*N.sub.RB. N.sub.tx represents a quantity of transmit antenna ports, including transmit antenna ports in different polarization directions. N.sub.rx represents a quantity of receive antenna ports, including receive antenna ports in different polarization directions”); dividing channel information corresponding to a same antenna group into a same group of channel information, where the antenna group comprises at least one of a transmitting antenna group of a receiving antenna group; dividing channel information corresponding to a same data stream into a same group of channel information; dividing channel information corresponding to a same sampling point set into a same group of channel information; or dividing channel information corresponding to a same frequency domain granularity set into a same group of channel information (Shi paragraph 132, “where H may be N.sub.tx*N.sub.sb-dimensional. N.sub.sb represents a quantity of frequency domain sub-bands, and a granularity of the frequency domain sub-band may be two resource blocks (resource blocks, RBs), four RBs, or the like. An example in which the granularity of the frequency domain sub-band is four RBs is used, where N.sub.sb=N.sub.RB/4.”).
Regarding claim 11, Vitthaladevuni and Shi disclose the method according to claim 3, wherein compressing the pre-processed channel information with the encoder to obtain the channel state information comprises: compressing each of the K groups of channel information with the encoder, respectively, to obtain K groups of channel state information (Shi paragraph 95, “Because an encoder in an auto-encoder may compress information into a low-dimensional representation, and a decoder in the auto-encoder may further obtain original information with proportionate precision through reconstruction, the auto-encoder well matches a transmission scenario that is limited by air interface overheads such as CSI feedback… The output result is generally a low-dimensional representation of the original input, and the low-dimensional representation may also be referred to as a compressed representation (compressed representation)… An auto-encoder technology is often used for data compression (at the transmitter) and restoration (at the receiver)…”, paragraph 96, “FIG. 5 is a schematic diagram of a CSI feedback framework based on an AI architecture... A preprocessing result is input into the encoder, and a low-dimensional code word D is obtained through compression...”, paragraph 107, “…the UE may preprocess the three-dimensional matrix, to obtain a sparse representation of the downlink channel. …”, and paragraphs 138, 154. And paragraphs 13-27, K column vectors, and K is a positive integer).
Regarding claim 14, Vitthaladevuni and Shi disclose the method according to claim 2, and Shi further discloses wherein pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder comprises: downsampling the channel information to obtain downsampled channel information as the pre-processed channel information, wherein the downsampled channel information has a dimension matched with the dimension of the input data of the encoder (Shi paragraph 95, “Because an encoder in an auto-encoder may compress information into a low-dimensional representation, and a decoder in the auto-encoder may further obtain original information with proportionate precision through reconstruction, the auto-encoder well matches a transmission scenario that is limited by air interface overheads such as CSI feedback… The output result is generally a low-dimensional representation of the original input, and the low-dimensional representation may also be referred to as a compressed representation (compressed representation)… An auto-encoder technology is often used for data compression (at the transmitter) and restoration (at the receiver)…”, paragraph 96, “FIG. 5 is a schematic diagram of a CSI feedback framework based on an AI architecture... A preprocessing result is input into the encoder, and a low-dimensional code word D is obtained through compression...”, paragraph 107, “…the UE may preprocess the three-dimensional matrix, to obtain a sparse representation of the downlink channel. …”, and figures 5, 6, 10).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over US_20220052827_A1_Vitthaladevuni in view of US_20240154675_A1_Shi and US_20200136704_A1_Liu.
Regarding claim 12, Vitthaladevuni and Shi disclose the method according to claim 11, but do not disclose further comprising: after compressing each of the K groups of channel information with the encoder, respectively, to obtain K groups of channel state information, acquiring and feeding back an inter-group phase of the groups of channel information.
Liu discloses after compressing each of the K groups of channel information with the encoder, respectively, to obtain K groups of channel state information, acquiring and feeding back an inter-group phase of the groups of channel information (Luo paragraph 105, “By using a signal which has the inter-group phase difference in the first direction and is transmitted or received via the antenna 1120, the communication apparatus 1100 may obtain a state of a channel in the first direction between the communication apparatus 1100 and the communication apparatus 1200. The state of the channel may be a state of an uplink channel from the communication apparatus 1200 to the communication apparatus 1100, may also be a state of a downlink channel from the communication apparatus 1100 to the communication apparatus 1200. The state of the channel may include channel quality, channel direction (e.g., a channel steering vector, an angle of arrival or an optimal beam for the communication apparatus 1200, etc).”).
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Liu’s using a signal which has the inter-group phase difference in the first direction and is transmitted or received via the antenna, the communication apparatus may obtain a state of a channel in the first direction between the communication apparatuses in Vitthaladevuni and Shi’s system to reduce interference between groups of users and enhance spectral efficiency. This method for improving the system of Vitthaladevuni and Shi was within the ordinary ability of one of ordinary skill in the art based on the teachings of Liu. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vitthaladevuni, Shi and Liu to obtain the invention as specified in claim 12.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over US_20220052827_A1_Vitthaladevuni in view of US_20240154675_A1_Shi and US_20200244329_A1_Xiao.
Regarding claim 13, Vitthaladevuni and Shi disclose the method according to claim 11, but do not disclose further comprising: after compressing each of the K groups of channel information with the encoder, respectively, to obtain K groups of channel state information, performing, according to group indexes corresponding to the K groups of channel state information, joint coding on the K groups of channel state information.
Xiao discloses after compressing each of the K groups of channel information with the encoder, respectively, to obtain K groups of channel state information, performing, according to group indexes corresponding to the K groups of channel state information, joint coding on the K groups of channel state information (Xiao paragraphs 253-260).
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Xiao’s joint encoding the CSI parameter in Vitthaladevuni and Shi’s system to improved efficiency and reduced overhead signalling. This method for improving the system of Vitthaladevuni and Shi was within the ordinary ability of one of ordinary skill in the art based on the teachings of Xiao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vitthaladevuni, Shi and Xiao to obtain the invention as specified in claim 13.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US_20220052827_A1_Vitthaladevuni in view of US_20240154675_A1_Shi and US_20200091970_A1_Lee.
Regarding claim 15, Vitthaladevuni and Shi disclose the method according to claim 14, but do not disclose wherein downsampling the channel information comprises at least one of: performing downsampling on the channel information in an antenna dimension; performing downsampling on the channel information in a time domain sampling point dimension; or performing downsampling on the channel information in a frequency domain granularity dimension.
Lee discloses wherein downsampling the channel information comprises at least one of: performing downsampling on the channel information in an antenna dimension; performing downsampling on the channel information in a time domain sampling point dimension; or performing downsampling on the channel information in a frequency domain granularity dimension (Lee paragraph 60, “…the method 200 generates a smoothed beamforming feedback matrix using the original feedback granularity, that is, a down-sampled ratio of 1. …”, paragraph 83, “…the method 250 generates a smoothed beamforming feedback matrix using the original feedback granularity, that is, a down-sampled ratio of 1…”).
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Lee’s downsampling in Vitthaladevuni and Shi’s system to Optimize the CSI feedback. This method for improving the system of Vitthaladevuni and Shi was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vitthaladevuni, Shi and Lee to obtain the invention as specified in claim 15.
Claim(s) 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over US_20220052827_A1_Vitthaladevuni in view of US_20240154675_A1_Shi and US_20230318675_A1_Xu.
Regarding claim 16, Vitthaladevuni and Shi disclose the method according to claim 2, but do not disclose wherein pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder comprises: performing zero padding on the channel information to obtain zero-padded channel information as the pre-processed channel information, wherein the zero-padded channel information has a dimension matched with the dimension of the input data of the encoder.
Xu discloses wherein pre-processing the channel information so that the pre-processed channel information has a dimension matched with a dimension of input data of the encoder comprises: performing zero padding on the channel information to obtain zero-padded channel information as the pre-processed channel information, wherein the zero-padded channel information has a dimension matched with the dimension of the input data of the encoder (Xu paragraph 30, “…obtaining second CSI transformation information, where the second CSI transformation information includes an N-dimensional cluster sparse domain coefficient, and the N-dimensional cluster sparse domain coefficient is obtained by padding zeros to the L cluster sparse domain coefficients; and performing a cluster sparse domain inverse transformation on the second CSI transformation information based on the cluster sparse transformation basis, to obtain the first CSI transformation information. In this way, the second communication apparatus can transform the L-dimensional cluster sparse domain coefficient into the N-dimensional cluster sparse domain coefficient in a zero-padding manner, to perform subsequent processing…”).
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Xu’s zero-padding in Vitthaladevuni and Shi’s system to standardize input dimensions. This method for improving the system of Vitthaladevuni and Shi was within the ordinary ability of one of ordinary skill in the art based on the teachings of Xu. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vitthaladevuni, Shi and Xu to obtain the invention as specified in claim 16.
Regarding claim 17, Vitthaladevuni, Shi and Xu disclose the method according to claim 16, and Xu further discloses wherein performing zero padding on the channel information comprising at least one of: performing zero padding on the channel information in an antenna dimension in the same polarization direction; performing zero padding on the channel information in a time domain sampling point dimension (Xu paragraph 10, “…the statistical covariance matrix is determined based on sample values of a plurality of N-dimensional beam domain coefficients…”); or performing zero padding on the channel information in a frequency domain granularity dimension.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WEIBIN HUANG whose telephone number is (571)270-3695. The examiner can normally be reached Monday - Friday 9:30AM - 6:00PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sujoy Kundu can be reached at (571)272-8586. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/W.H/Examiner, Art Unit 2471
/MOHAMMAD S ADHAMI/Primary Examiner, Art Unit 2471