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
Claims 1-10, 13-22 are objected to because of the following informalities:
Regarding claims 1, 13, it is suggested to put the acronym (RIS) recited in line 4 inside parentheses.
Claims 2-10, 14-22 are objected to by virtue of their dependency on claim 1 and 13 respectively.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 13-22 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 13, the limitation that recites a “network node” recited in line 2 is vague and indefinite because the network node (e.g., machine) multiple parts or elements (e.g. , processor, hardware) for implementing the claim function. In other word, a network node is made up of multiple parts.
Claims 14-22 are rejected by virtue of their dependency on claim 13.
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.
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.
The factual inquiries 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.
Claims 1-5, 7-10, 13-17, 19-22 are rejected under 35 U.S.C. 103 as being unpatentable over ELSHAFIE et al (US 2025/0007590 A1) in view of LIU CHANG et al (“Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications”, December 7, 2021).
Regarding claims 1, 13, ELSHAFIE et al (US 2025/0007590 A1) discloses a method performed by a network node (see, a base station which configures an RSI to relay signals over a set of beams to determine a preferred beam to communicate with one or more UEs in zone, section 0049-0050, fig. 1 to fig. 2, base station 105/gNB 105 coupled to the RIS 205, fig. 6, the base station includes a processor implicitly coupled to a communication manager 620, section 0122-0127, 0222 ) for handling beam-based communication (see, the set of beams associated with each zone to serve a UE, section 0049-0050) between a terminal (fig. 1 to fig. 2, UEs 115 in the coverage area of the base station 105, the base station, section 0049-0050) and a radio network node in a wireless communications network (fig. 1 to fig. 2, , wireless communication system 100/network 110a that supports beamforming based on zones, section 0053-0056), the wireless communication network comprising a Reconfigurable Intelligent Surface, RIS (see, fig. 2, the base station/gNB or eNB or the RSI as part implicitly of the base station by virtue of configuration with the RIS with a set of beams, section 0077) , for reflecting radio signals between the terminal and the radio network node (see, the RSI to reflect incoming signals in one or more directions or in direction of UE based on base station configuration, section 0048-0049), which RIS is controlled by the network node (see, the RIS is configured by the base station, section 0049-0050), the method comprising: predicting (see, the RIS is deployed to aid in network communications, the RSI based on configuration received from the base station, determines preferred beam of the UE including each set of beams for a UE in the group of UEs, section 083-0084, 0089-0090) for terminal (fig. 1 to fig. 2, the base station services multiple UES, transmits information to the ones or more UEs 115 using beamformed communications, section 0077-0079), one or more first communication parameters (see, parameters of a beam (e.g., phase, width, angles at different time instances), zone identifier associated with beams, section 0081-0083, 0084, 0087) to be used for the beam-based communication between the terminal and the radio network node (see, the base station identifying and transmits one or more beams (e.g., phase and amplitude of the beams) to be used in the zones for the UEs in the group, section 0083-0085).
ELSAPHIE ‘590 discloses all the claim limitations but fails to explicitly disclose: predicting, for each terminal, one or more first communication parameters to be used for the beam-based communication between the terminal and the radio network node, which beam-based communication satisfies one or more criteria; configuring each terminal, radio network node and RIS based on the predicted one or more first communication parameters; in response to a predicted change in wireless communications network, estimating for each terminal, one or more second communication parameters to be used for the beam-based communication between the terminal and the radio network node; and based on an evaluation of the predicted change taking one or more present parameters into account, updating the configuration of each terminal, radio network node and RIS according to the one or more second communication parameters in order to handle the beam-based communication.
However, LIU CHANG et al (“Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications”, December 7, 2021, KIDS) discloses: predicting, for each terminal, one or more first communication parameters to be used for the beam-based communication between the terminal and the radio network node (see, abstract, page 2, section II, page 3-4, predicting beamforming matrix with LoS-aware phase shift matrix at the IRS and the AP for all users in the matrix), which beam-based communication satisfies one or more criteria (page 2 to page 3, page 4-5, see, predicted beamforming matrix, parameters that implicitly satisfy performance criterion) ; configuring each terminal, radio network node and RIS based on the predicted one or more first communication parameters (page 2 to page 3, see, multiple users or single antenna users where the AP obtains historical locations through previous uplink transmission, and predicts LoS-based IRSD phase shift matrix to be adopted, predicting of beamforming matrix with size, predicting communication parameters for each of the terminal); in response to a predicted change in wireless communications network (page 2, page 3, page 5, fig. 2, see, predicted beamforming parameters and ICSI-aware instantaneous and real time beamforming), estimating for each terminal, one or more second communication parameters to be used for the beam-based communication between the terminal and the radio network node (page 3, page 5 to page, see, update based on predicted beamforming matrix, parameters/slots for said each of the users/terminals/channel estimation with respect to each respective terminal) and based on an evaluation of the predicted change taking one or more present parameters into account (page 5, section II.C, page 3, page 5 to page, see, update based on predicted beamforming matrix, parameters/slots for said each of the users/terminals/channel estimation with respect to each respective terminal) updating the configuration of each terminal (page 3, page to page 6,discloses optimization update with respect to each of the K users or terminals), radio network node and RIS according to the one or more second communication parameters in order to handle the beam-based communication (see, the predictive change by obtaining the effective channel state information associated with parameters/slots for said each of the K users, updating of the beamforming matrix accordingly, fig. 2, page 2 to page 6).
In view of the above, it 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 to modify the combined RIS-based beam communications system and apparatus of ELSAFIE ‘590 and LIU CHANG by implementing the Dee[ Learning predictive beamforming for IRS assisted multi-user communications for predicting phase shifts based on channel estimation as taught by Chang LIU. The motivation would have been to provide optimization and a reduction in signal overhead.
ELSAFIE ‘590 discloses all the claim limitations but fails to explicitly disclose: Regarding claims 2, 14, the method according to claim 1, wherein predicting the one or more first communication parameters and estimating the one or more second communication parameters is based on a machine learning process.
Regarding claims 3, 15, the method according to claim 2, further comprising: obtaining feedback comprising measurement data related to the beam-based communication between the terminal and the radio network node; and updating the machine learning process based on the obtained feedback.
However, LIU CHANG et al (“Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications”, December 7, 2021) discloses: Regarding claims 2, 14, the method according to claim 1, wherein predicting the one or more first communication parameters (see, rejection above, page 4 to page 6, discloses connected neural network,, training-based algorithm, predictive beamforming using channel estimations, matrix update) and estimating the one or more second communication parameters is based on a machine learning process (see, rejection above, page 4 to page 6, discloses connected neural network,, training-based algorithm, predictive beamforming using channel estimations, matrix update).
Regarding claims 3, 15, the method according to claim 2, further comprising: obtaining feedback comprising measurement data related to the beam-based communication between the terminal (page 3, page 4, page 5 to page 6, discloses channel estimations/conditions to obtain effective ICSI) and the radio network node; and updating the machine learning process based on the obtained feedback (page 3 to page 65, updating implicitly based on learning algorithm).
In view of the above, it 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 to modify the combined RIS-based beam communications system and apparatus of ELSAFIE ‘590 and LIU CHANG by implementing the Deep Learning predictive beamforming for IRS assisted multi-user communications for predicting phase shifts based on channel estimation as taught by Chang LIU. The motivation would have been to provide optimization and a reduction in signal overhead.
Regarding claims 4,16, ELSAFIE ‘590 discloses the method according to claim 1, wherein the one or more criteria comprises any one or more out of: a criterium related to high data rate communications; a criterium related high capacity communications; a criterium related high reliability communications (see, ultra reliable low latency communications, low-latency functions which include prioritization of services, section 0067); and a criterium related low latency communications (see, ultra reliable low latency communications, low-latency functions which include prioritization of services, section 0067).
Regarding claims 5, 17, ELSAFIE ‘590 discloses the method according to claim 1, further comprising evaluating the predicted change (see, updating the set of beams associated with zone of the UE, section 0096- 0099) in the wireless communications network by monitoring the one or more present parameters see, measurements based on the reference signal is related to the zone ID of the UE,s section 0093-0096), which one or more present parameters comprises any one or more out of: the movement of each terminal (see, the base station reconfigures the RIS with an updated set of beams to serve the zone, different UES in the zone, section 0096-0099); the number of terminals operating in the wireless communications network; the number of RISs operating in the wireless communications network; and the number of radio network nodes operating in the wireless communications network.
Regarding claims 7, 19, ELSAFIE ‘590 discloses the method according to claim 1, wherein the one or more first communication parameters comprises any one or more out of: one or more first parameters related to a first beam to be used for communication between the terminal and the radio network node (see, the set of beams to service UEs or group of UEs 115 in location including updated beam for the zone, section 0087-0090); and one or more first parameters related to the RIS for controlling the reflecting of radio signals related to the first beam; and one or more first parameters related to the radio network node associated to the first beam; and wherein the one or more second communication parameters comprises any one or more out of: one or more second parameters related to a second beam to be used for communication between the terminal and the radio network node; one or more second parameters related to the RIS for controlling the reflecting of radio signals related to the second beam; and one or more second parameters related to the radio network node associated to the second beam.
Regarding claims 8, 20, ELSAFIE ‘590 as modified by LIU CHANG discloses the method according to claim 7, wherein the one or more first communication parameters further comprises any one or more out of: one or more first parameters related to an additional first beam to be used for communication between the terminal and the radio network node (section 0095-0099+, LUI, see, page 2 to page 6, updating and predicted parameters for the beams), which additional first beam has a communication path that is different from the first beam; one or more first parameters related to the RIS for controlling the of reflecting radio signals related to the additional first beam; and one or more first parameters related to the radio network node associated to the additional first beam; and wherein the one or more second communication parameters further comprises any one or more out of: one or more second parameters related to an additional second beam to be used for communication between the terminal and the radio network node; one or more second parameters related to the RIS for controlling the reflecting of radio signals related to the additional second beam; and one or more second parameters related to the radio network node associated to the additional second beam.
Regarding claims 9, 21, ELSAFIE ‘590 discloses the method according to claim 1, wherein predicting the one or more first communication parameters (see, RSRP, RSPQ, SINR measurements that are feedback to the base station via the RIS in relation to one or more associated beams, section 0095-0096) for a terminal is based on the location of the terminal (see, measurements based on the reference signal is related to the zone ID of the UE,s section 0093-0096).
Regarding claims 10, 22, ELSAFIE ‘590 as modified by LIU CHANG discloses t the method according to claim 1, wherein the predicted change in the wireless communications network comprises any one or more out of: a change of location of at least one terminal (see, page 2, section II, discloses location based change); a change of the number of terminals operating in the wireless communications network; a change of the number of RISs operating in the wireless communications network; and a change of the number of radio network nodes operating in the wireless communications network.
Claims 6, 18 are rejected under 35 U.S.C. 103 as being unpatentable over ELSHAFIE et al (US 2025/0007590 A1) in view of LIU CHANG et al (“Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications”, December 7, 2021) as applied to claims 1, 13 above, and further in view of HAIJA et al (US 2024/0072849 A1, PCT/CN2021/094772, filed on May 20, 2021).
ELSAFIE ‘590 and LIU CHANG discloses all the claim limitations but fails to explicitly disclose: Regarding claims 6, 18, the method according claim 1, further comprising: dividing a communication bandwidth used for the beam-based communication in the wireless communications network into at least two sub-bands, wherein the at least two sub-bands are allocated based on the one or more criteria.
However, HAIJA et al (US 2024/0072849 A1, PCT/CN2021/094772, filed on May 20, 2021) from a similar field of endeavor discloses: Regarding claims 6, 18, the method according to 5 claim 1, further comprising: dividing a communication bandwidth used for the beam-based communication in the wireless communications network into at least two sub-bands (see, the RIS is part of the TRP or base station or gNB which performs resource allocation (e.g., FDMA, section 0077), section 0093, 0095, 0117-0120, the RIS is configured based on time division multiplexing to redirect from the transmitter to the receiver and redirect from the receiver to the transmitter in different transmission resources based on beam directions or angles with signal strength that satisfies a threshold, section 0026), wherein the at least two sub-bands are allocated based on the one or more criteria (see, time division multiplexing to redirect from the transmitter to the receiver and redirect from the receiver to the transmitter in different transmission resources based on beam directions or angles with signal strength that satisfies a threshold, section 0026).
In view of the above, it 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 to modify the combined RIS-based beam communications system and apparatus of ELSAFIE ‘590 and LIU CHANG by implementing he AI/ML two-way RIS for beam sweep redirection based on the channel estimation as taught by HAIJA ‘849. The motivation would have been to provide optimization based on prediction (section 0112).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Medra et al (US 2025/0047328 A1, PCT/CN2022/075877, filed on February 10, 2022) discloses RIS dire redirect signals with robust beams, computing phase information with respect to beam parameters and AI/ML (section 0127, 0142-0166).
Sahraei et al (US 2025/0007566 A1) discloses reflected beams from the RIS based on measurement (section 0101-0112, 0124).
BAYESTEH et al (US 2021/0302561 A1) reflected beams from the RIS based on measurement, beam sweeping (section 0122, 0131-0145).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CANDAL ELPENORD whose telephone number is (571)270-3123. The examiner can normally be reached 9 am -6 pm M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kwang B Yao can be reached at 571 272-3182. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CANDAL ELPENORD/Primary Examiner, Art Unit 2473
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