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 .
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d).
Information Disclosure Statement
3. The information disclosure statement(s) submitted on September 3, 2024 has/have been considered by the Examiner and made of record in the application file.
Specification
4. The amendments to Paragraph [001] of the specification received on April 4, 2024. These amendments to the specification are accepted.
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 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.
Claim Rejections - 35 USC § 103
5. 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 of this title, 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 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Ekman et al. (U.S. Patent Application Publication # 2025/0260472 A1), in view of Zhu et al. (U.S. Patent Application Publication # 2024/0064724 A1), and Yu et al. (U.S. Patent Application Publication # 2019/0173562 A1).
Regarding claim 1, Ekman et al. teach a method (Fig(s).2 and 6A-6B) comprising:
transmitting a set of static beams (read as static subset of beams (Fig.6 @ 606B; Paragraph [0080])) by a network (Fig(s).2 and 6B @ 606B) and based on that, predicting a set of dynamic beams for a UE (Fig.6A @ 602A),
wherein the set of predicted beams are formed dynamically based on the UE (Fig.6A @ 600); and
However, Ekman et al. fail to explicitly teach wherein the set of predicted beams are formed dynamically based on a location of the UE,
transmitting during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Zhu et al. teach a method wherein the set of predicted beams are formed dynamically based on a location of the UE. (read as “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of improving beam prediction for devices using a communication network.
However, Ekman et al. and Zhu et al. fail to explicitly teach transmitting during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Yu et al. teach a method for transmitting during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station (read as “… the base station 202 may transfer the information on the beam being used during the BRRS transmission.”(Fig.2 @ 202 and 230; Paragraph [0084]) Also, “the base station 202 may map tag indexes up to “0, 1, . . . , N−1” to N beam IDs using RRC or MAC-CE.”(Paragraph [0084])),
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction. (read as beam ID (Paragraph [0084]); For example, “The N base station beam IDs may be equal to the N base station beam IDs included in the serving beam list.”(Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claim 8, Ekman et al. teach a base station (Fig(s).2, 6A-6B, 11, and 16-17) configured to:
transmit at least a set of static beams(read as static subset of beams (Fig.6 @ 606B; Paragraph [0080])) by a network (Fig(s).2 and 6B @ 606B) and based on that, predicting a set of dynamic beams for a UE (Fig.6A @ 602A),
wherein the set of predicted beams are formed dynamically based on the UE (Fig.6A @ 600);
However, Ekman et al. fail to explicitly teach wherein the set of predicted beams are formed dynamically based on a location of the UE; and
transmit during the beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with the base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Zhu et al. teach a method wherein the set of predicted beams are formed dynamically based on a location of the UE. (read as “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of improving beam prediction for devices using a communication network.
However, Ekman et al. and Zhu et al. fail to explicitly teach transmit during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Yu et al. teach a method to transmit during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station (read as “… the base station 202 may transfer the information on the beam being used during the BRRS transmission.”(Fig.2 @ 202 and 230; Paragraph [0084]) Also, “the base station 202 may map tag indexes up to “0, 1, . . . , N−1” to N beam IDs using RRC or MAC-CE.”(Paragraph [0084])),
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction. (read as beam ID (Paragraph [0084]); For example, “The N base station beam IDs may be equal to the N base station beam IDs included in the serving beam list.”(Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claim 15, Ekman et al. teach a non-transitory computer-readable storage medium (Fig(s).11 @ 1106) storing executable instructions (Fig.17 @ 1732) that, in response to execution, cause one or more processors (Fig(s).11 @ 1104 and 17 @ 1730) of a base station (Fig(s).2, 6A-6B, 11, and 17) to perform operations, comprising:
transmit at least a set of static beams(read as static subset of beams (Fig.6 @ 606B; Paragraph [0080])) by a network (Fig(s).2 and 6B @ 606B) and based on that, predicting a set of dynamic beams for a UE (Fig.6A @ 602A),
wherein the set of predicted beams are formed dynamically based on the UE (Fig.6A @ 600);
However, Ekman et al. fail to explicitly teach wherein the set of predicted beams are formed dynamically based on a location of the UE; and
transmit during the beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with the base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Zhu et al. teach a method wherein the set of predicted beams are formed dynamically based on a location of the UE. (read as “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of improving beam prediction for devices using a communication network.
However, Ekman et al. and Zhu et al. fail to explicitly teach transmit during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station,
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction.
Yu et al. teach a method to transmit during beam prediction configuration, a corresponding beam topology identifier to the UE that assist the UE, using a well-defined association between the set of transmitted and predicted beams, to predict one or more best beams from the set of predicted beams for communicating with a base station (read as “… the base station 202 may transfer the information on the beam being used during the BRRS transmission.”(Fig.2 @ 202 and 230; Paragraph [0084]) Also, “the base station 202 may map tag indexes up to “0, 1, . . . , N−1” to N beam IDs using RRC or MAC-CE.”(Paragraph [0084])),
wherein the beam topology identifier defines a unique association between the set of transmitted beams and the set of predicted beams for efficient beam identification and prediction. (read as beam ID (Paragraph [0084]); For example, “The N base station beam IDs may be equal to the N base station beam IDs included in the serving beam list.”(Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 2, 9, and 16, and as applied to claims 1, 8, and 15 above, Ekman et al. teach “Systems and methods are disclosed for beam subset selection and validation.”(Fig(s).2., 6A-6B, 11, and 17; Abstract) Also, Ekman et al. teach if the set of predicted beams have been transmitted earlier to the UE for predicting one or more best beams, for communicating with the base station. (Fig.6A)
Zhu et al. teach “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041])
However, Ekman et al. and Zhu et al. fail to explicitly teach wherein the transmitted beam topology identifier is configured based on one or more predefined rules between the set of transmitted and predicted beams established between the base station and the UE,
Yu et al. teach a base station wherein the transmitted beam topology identifier is configured based on one or more predefined rules between the set of transmitted and predicted beams established between the base station and the UE (read as a base station transmitting capable to transmit a beam ID (Fig.2 @ 202 and 230;Paragraph [0084])),
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 3, 10, and 17, and as applied to claims 2, 9, and 16 above, Ekman et al. teach “Systems and methods are disclosed for beam subset selection and validation.”(Fig(s).2., 6A-6B, 11, and 17; Abstract)
Zhu et al. teach “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041])
However, Ekman et al. and Zhu et al. fail to explicitly teach wherein the one or more predefined rules are established using association between beam identification related parameters including at least:
beam IDs,
a predefined offset in respect of Transmission beam angle,
a predefined offset in respect of reception beam angle,
a predefined mathematical relation,
azimuth angle information, and
elevation angle information.
Yu et al. teach a base station (Fig.2 @ 202) wherein the one or more predefined rules are established using association between beam identification related parameters including at least:
beam IDs (read as beam IDs (Paragraph [0084])),
a predefined offset in respect of Transmission beam angle,
a predefined offset in respect of reception beam angle,
a predefined mathematical relation,
azimuth angle information, and
elevation angle information.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 4, 11, and 18, and as applied to claims 1, 8, and 15 above, Ekman et al. teach a method (Fig(s).6A-6B and 7-8), a base station (Fig(s).2, 11, and 16-17), and a non-transitory computer-readable storage medium (Fig.11 @ 1106) wherein if the set of predicted beams have not been transmitted earlier to the UE for predicting one or more best beams, the method further comprises:
transmitting an indication to the UE that the association between the set of transmitted beams and the set of predicted beams is dynamic (Fig(s).2, 6A, 11 @ 1112, 14, 16-17);
receiving, from the UE, one or more beam identification related parameters, for communicating with the base station (Fig(s).2, 7-8, 11 @ 1114, 14-16);
establishing an association between the set of transmitted beams and the set of predicted beams, based on the received one or more beam identification related parameters (Fig(s).2, 6A-6B, 7-8, and 11 @ 1104); and
Zhu et al. teach “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041])
However, Ekman et al. and Zhu et al. fail to explicitly teach generating a beam topology identifier based on the established association,
wherein the generated beam topology identifier is specific to a session established between the base station and the UE.
Yu et al. teach a base station (Fig.2 @ 202) teach generating a beam topology identifier based on the established association (read as beam ID (Paragraph [0084])),
wherein the generated beam topology identifier is specific to a session established between the base station and the UE. (read as “The N base station beam IDs may be equal to the N base station beam IDs included in the serving beam list.”(Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 5, 12, and 19, and as applied to claims 4, 11, and 18 above, Ekman et al. teach “Systems and methods are disclosed for beam subset selection and validation.”(Fig(s).2., 6A-6B, 11, and 17; Abstract)
Zhu et al. teach “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041])
However, Ekman et al. and Zhu et al. fail to explicitly teach wherein the one or more beam identification related parameters received from the UE include at least one of:
3db beamwidth,
beam boresight direction,
positioning information of the UE,
azimuth and elevation angle information, and
Beam ID information.
Yu et al. teach a base station (Fig.2 @ 202) wherein the one or more beam identification related parameters received from the UE include at least one of:
3db beamwidth,
beam boresight direction,
positioning information of the UE,
azimuth, and elevation angle information, and
BeamID information. (read as beam ID (Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 6, 13, and 20, and as applied to claims 1, 8, and 15 above, Ekman et al. teach “Systems and methods are disclosed for beam subset selection and validation.”(Fig(s).2., 6A-6B, 11, and 17; Abstract)
Zhu et al. teach “the machine learned algorithms can enable predicting the serving beam for different UE locations and time instances, …”(Fig.4 @ 420; Paragraph [0041])
Ekman et al. and Zhu et al. fail to explicitly teach wherein the beam topology identifier is transmitted to the UE using at least one of:
Radio Resource Control (RRC) signaling or
Medium Access Control signaling.
Yu et al. teach a method wherein the beam topology identifier (read as BEAM ID (Paragraph [0084])) is transmitted to the UE using at least one of:
Radio Resource Control (RRC) signaling (read as RRC (Paragraph [0084])) or
Medium Access Control (MAC) signaling. (read as MAC-CE (Paragraph [0084]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE or RRC with beam IDs as taught by Yu et al. and the function for beam prediction based on UE locations as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Regarding claims 7 and 14, and as applied to claims 1 and 8 above, Ekman et al. teach “Systems and methods are disclosed for beam subset selection and validation.”(Fig(s).2., 6A-6B, 11, and 17; Abstract)
Yu et al. teach “… the base station 202 may transfer the information on the beam being used during the BRRS transmission.”(Fig.2 @ 202 and 230; Paragraph [0084]) Also, Yu et al. teach “the base station 202 may map tag indexes up to “0, 1, . . . , N−1” to N beam IDs using RRC or MAC-CE.”(Paragraph [0084]) Also, Yu et al. teach “The N base station beam IDs may be equal to the N base station beam IDs included in the serving beam list.”(Paragraph [0084])
However, Ekman et al. and Yu et al. fail to explicitly teach wherein the set of transmitted beam is broadcast beams and is common for all the UE.
Zhu et al. teach a base station (Fig(s).2A @ 205, 4 @ 410, and 9 @ 900) wherein the set of transmitted beams is broadcast beams and is common for all the UE. (read as “Processor 904 (and possibly transceivers 902A/902B) may control the RF or wireless transceiver 902A or 902B to receive, send, broadcast or transmit signals or data.”(Fig(s).2A, Paragraph [0119]))
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to employ the function for generating and transmitting a MAC-CE or RRC with beam IDs as taught by Yu et al. and the function for broadcasting beam data as taught by Zhu et al. with the base station as taught by Ekman et al. for the purpose of enhancing beam selection by devices in a communication network.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure:
Zhou et al. (“Beam-forecast: Facilitating mobile 60 GHz networks via model-driven beam steering”, 2017) teach “… Beam-forecast, a novel model-driven beam steering approach that can sustain high performance for mobile 60 GHz links. Beam-forecast is built on the observation that 60 GHz channel profiles at nearby locations are highly-correlated. By exploiting this correlation, Beam-forecast can reconstruct the channel profile as the Tx/Rx moves, without explicit channel scanning.”(Abstract, page 1)
Fryking et al. (U.S. Patent Application Publication # 2024/0421887 A1) teach “A computer-implemented method (400), performed by a network node (120), for determining a candidate beam for a beam transition by a wireless communications device (100) in a beam grid,…”(Abstract)
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Commissioner for Patents
P.O. Box 1450
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Any inquiry concerning this communication or early communications from the Examiner should be directed to Salvador E. Rivas whose telephone number is (571) 270-1784. The examiner can normally be reached on Monday-Friday from 7:00AM to 3:30PM.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Un C. Cho can be reached on (571) 272- 7919. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/SALVADOR E RIVAS/Primary Examiner, Art Unit 2413
June 12, 2026
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