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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/14/2023 and 04/11/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
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 non-obviousness.
Claims 1, 7- 8, 12-13, 15-16 and 19 are rejected under 35 U.S.C. § 103 as being unpatentable over Zhu et al. (US 20220124588 A1), hereinafter Zhu, in view of Yeh et al. (US 20230072769 A1), hereinafter Yeh.
Regarding Claim 1:
Zhu teaches a system, comprising: interface circuitry; and processing circuitry to ([0289] "The compute node 1950 includes processing circuitry in the form of one or more processors 1952"; [0297] "The communication circuitry 1966 is a hardware element, or collection of hardware elements, used to communicate over one or more networks"; and [0302] "applicable means for communicating (e.g., receiving, transmitting, etc.) may be embodied by such communications circuitry");
receive, via the interface circuitry, performance data indicating a performance of a plurality of wireless networks ([0025] "a network device (or MX node) may simultaneously connect to multiple networks using individual links of the same or different RATs (e.g., LTE, WiFi, 5G, etc.; … The convergence layer Rx entity performs end-to-end (e2e) QoS measurements (e.g., loss, delay, throughput, and/or any other like measurements (or combinations thereof) such as any of those discussed herein) based on received data and/or control packets"; and [0037] "QoS measurements for C1 are more favorable than QoS measurements for C2");
determine, based on the performance data, one or more configuration settings to be adjusted for one or more of the wireless networks ([0036] "a receiver entity (Rx) selects the connection for data transfer based on, for example, quality of service (QoS)-related measurements"; [0037] "If MX1 detects a better link than C1 based on QoS-related measurements, MX1 will send another TSM to steer"; and [0052] "The TSU carries traffic splitting/steering configuration parameters (e.g., split ratio, and the like)");
adjust the one or more configuration settings for one or more of the wireless networks ([0052] "is used to configure traffic splitting/steering for one or multiple flows; … may steer traffic to link x by setting the split ratio of link x to be 1 and the split ratio of other links to be 0").
Zhu does not teach, wherein the wireless networks are based on a plurality of wireless technologies having different respective frequency spectrums, and wherein the performance data is based on a plurality of protocol layers of the wireless technologies.
Yeh teaches wherein the wireless networks are based on a plurality of wireless technologies having different respective frequency spectrums, and wherein the performance data is based on a plurality of protocol layers of the wireless technologies; by disclosing deployed networks that differ by access technology and frequency band ([0024] "the deployed networks are disparate in various features, such as access technology (RAT), coverage area per access network node, deployed frequency band and bandwidth, and backhaul capabilities"), and combinations of performance statistics associated with multiple protocol layers [0042] "different types of operational parameters (or combinations of operational parameters)"; and [0045] "per user/UE performance statistics (e.g., PDCP throughput, RLC layer latency, MAC layer latency, etc.)".
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Yeh's disclosed different frequency bands to the respective RAT-based networks and use Yeh's disclosed layer-specific performance statistics in Zhu's system, thereby providing broader performance information for selecting and configuring the wireless networks. Yeh identifies the benefit of multi-RAT aggregation (Yeh [0024]).
Regarding Claim 7: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu further teaches to determine, based on the performance data, the one or more configuration settings to be adjusted for one or more of the wireless networks is further to: determine, based on the performance data and one or more traffic flow objectives, the one or more configuration settings to be adjusted for one or more of the wireless networks, wherein the one or more traffic flow objectives indicate a priority among a plurality of traffic flows on the wireless networks by disclosing a steering decision based on QoS measurements ([0037] "If MX1 detects a better link than C1 based on QoS-related measurements, MX1 will send another TSM to steer"); traffic-splitting and steering settings ([0052] "The TSU carries traffic splitting/steering configuration parameters (e.g., split ratio, and the like) and is used to configure traffic splitting/steering for one or multiple flows"); network-path selection based on application objectives ([0093] "provides mechanisms for the flexible selection of network paths in an MX communication environment 700, based on the application needs and/or requirements, as well as adapt to dynamic network conditions when multiple network connections serve a client device 701"); and priority among different flows ([0472] "QoS is the ability to provide different priorities to different applications, users, or flows"); and ([0477] "the precedence, preferences, and/or prioritization a packet belonging to a particular data flow receives in relation to other traffic of other data flows").
Regarding Claim 8: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu further teaches wherein the one or more configuration settings comprise one or more of: a modulation setting; a transmission power setting; an operating channel setting; a radio resource management setting; or a quality of service setting by disclosing configurations applied to packets of a data flow ([0477] "one or more parameters, characteristics, and/or configurations to be applied to packets belonging to a data flow"); and parameters controlling QoS forwarding treatment ([0479] "node specific parameters that control the QoS forwarding treatment (e.g., scheduling weights, admission thresholds, queue management thresholds, link layer protocol configuration, etc.)").
Regarding Claim 12: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu further teaches wherein three or more of the wireless networks are based on three or more of the following wireless technologies: Bluetooth; Wi-Fi; cellular technology; or IEEE 802.15.4 Low-Rate Wireless Personal Area Network technology by disclosing an architecture capable of combining any number of networks and access types ([0105] "The architecture is extendable to combine any number of networks, as well as any choice of participating network/access types"), including Wi-Fi and cellular links ([0108] "may include, for example, WiFi links, LTE cellular links, 5G/NR cellular links"), and Bluetooth and IEEE 802.15.4 links ([0108] "may additionally or alternatively include short-range radio links such as, for example, Bluetooth® or BLE, IEEE 802.15.4 based protocols"). Selecting at least three of these disclosed technologies for three wireless networks would have been a predictable implementation of Zhu's expressly disclosed architecture.
Regarding claims [13, 15 and 16] (CRM), and claim 19 (method) are rejected under the same reasoning as claim [1, 7 and 8] (system).
Claims 2-5. 14 and 20 are rejected under 35 U.S.C. § 103 as being unpatentable over Zhu in view of Yeh, and further in view of Diener et al. (US 20040137915 A1), hereinafter Diener.
Regarding Claim 2: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu further teaches wherein the performance data comprises: one or more quality of service (QoS) metrics for one or more of the wireless networks; by disclosing selection based on QoS-related measurements ([0036] "a receiver entity (Rx) selects the connection for data transfer based on, for example, quality of service (QoS)-related measurements"), including QoS measurements for multiple connections (paragraph [0037] "QoS measurements for C1 are more favorable than QoS measurements for C2").
Zhu and Yeh do not teach radio frequency (RF) spectrum data, wherein the RF spectrum data is based on an analysis of RF signals detected at a plurality of frequencies by one or more RF receivers, wherein the one or more RF receivers are independent of the plurality of wireless networks.
Diener teaches radio frequency (RF) spectrum data, wherein the RF spectrum data is based on an analysis of RF signals detected at a plurality of frequencies by one or more RF receivers, wherein the one or more RF receivers are independent of the plurality of wireless networks by disclosing radio sensor devices ([0031] "The system comprises one or more radio sensor devices"), each having a spectrum-monitoring receiver and spectrum-analysis system ([0031] "The spectrum monitoring section comprises a radio receiver capable of receiving radio signals in a radio frequency band, a spectrum analysis system coupled to the radio receiver for generating spectrum (radio frequency) activity information representative of the (radio frequency) activity in the frequency band"); a sensor-overlay network (paragraph [0048] "deployment of a plurality of sensors 2000(1) to 2000(N) shown in FIG. 1 in various locations or zones where activity associated with any of the plurality of signal types is occurring in the frequency band to form a sensor overlay network"); and frequency-resolved FFT data ([0051] "a 256 frequency bin FFT block that provides (I and Q) FFT data for each of 256 frequency bins that span the bandwidth of frequency band of interest"); and a separately controlled monitoring radio (paragraph [0057] "The processor 2700 may generate signals to control the radio 2110 independently of the radio transceiver 2510"), with a wired server connection ([0057] "there is also an LAN interface block (e.g., Ethernet) that is coupled to the processor 2700 to enable the sensor to communicate with the server with a wired LAN connection"). These separate sensor-overlay and radio-control disclosures suggest that the spectrum-monitoring receivers are independent of the wireless networks.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Diener's independently controlled spectrum-monitoring receivers into the Zhu-Yeh system, thereby providing frequency-resolved RF-spectrum information for performance-based wireless-network configuration (Diener [0065]).
Regarding Claim 3: Zhu in view of Yeh and Diener teaches the system of Claim 2 as discussed above.
Zhu further teaches wherein the one or more QoS metrics indicate one or more of: demodulation errors; data transmission errors; signal quality; network layer performance; or transport layer performance by disclosing signal-quality measurements ([0092] "signal strength measurements, signal quality measurements, and/or the like").
Regarding Claim 4: Zhu in view of Yeh and Diener teaches the system of Claim 2 as discussed above.
Zhu further teaches wherein the performance data further comprises spatiotemporal performance data, wherein the spatiotemporal performance data indicates a performance of one or more of the wireless networks based on time and location by disclosing measurement reports containing signal-quality data ([0092] "signal strength measurements, signal quality measurements, and/or the like"), wherein ([0092] "Each measurement report is tagged with a timestamp and the location of the measurement").
Regarding Claim 5: Zhu in view of Yeh and Diener teaches the system of Claim 2 as discussed above.
Zhu further teaches wherein the processing circuitry to determine, based on the performance data, the one or more configuration settings to be adjusted for one or more of the wireless networks is further to ([0289] "The compute node 1950 includes processing circuitry in the form of one or more processors 1952"; and [0036] "a receiver entity (Rx) selects the connection for data transfer based on, for example, quality of service (QoS)-related measurements").
Zhu and Yeh do not teach detecting, based on the RF spectrum data, one or more sources of signal interference for one or more of the wireless networks.
Diener teaches detecting, based on the RF spectrum data, one or more sources of signal interference for one or more of the wireless networks by disclosing spectrum-based detection and location of RF sources ([0031] "sophisticated features to detect, classify, and locate sources of RF activity"; reports identifying interference sources ([0087] "known and unknown interferer devices"); and analysis of spectrum data for interference ([0065] "Analyze the spectrum, protocol, and location data"; [0065] "interference and cold spots").
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate Diener’s independently controlled spectrum-monitoring receivers into the Zhu-Yeh system, thereby providing frequency-resolved RF-spectrum information for performance-based wireless-network configuration (Diener [0065]).
Regarding claim 14 (CRM), and claim 20 (method) are rejected under the same reasoning as claim 2 (system).
Claim 6 is rejected under 35 U.S.C. § 103 as being unpatentable over Zhu in view of Yeh and Diener, as applied to Claim 5 above, and further in view of Merlin et al. (US 2013/0195081 A1), hereinafter Merlin.
Regarding Claim 6: Zhu in view of Yeh and Diener teaches the system of Claim 5 as discussed above.
Zhu in view of Yeh does not teach, while Diener teaches wherein the one or more sources of signal interference include transmissions from a plurality of devices ([0046] "there are multiple devices that at some point in their modes of operation transmit or emit signals within a common frequency band"; [0046] "there will inevitably be interference between signals of one or more devices"; and [0046] "Multiple WLAN APs 1050(1) to 1050(N) may be operating in the region, each of which has one or more associated client STAs 1030(1) to 1030(N)").
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Diener's independently controlled spectrum-monitoring receivers into the Zhu-Yeh system, thereby providing frequency-resolved RF-spectrum information for performance-based wireless-network configuration (Diener [0065]).
Zhu in view of Yeh and Diener does not teach wherein the respective devices have physically independent housings.
Merlin teaches wherein the respective devices have physically independent housings by disclosing spatially separated devices ( [0003] "several interacting spatially-separated devices"), in which each wireless device may be an AP or STA ([0039] "the wireless device 202 may comprise the AP 104 or one of the STAs 106") and may include its own housing, transmitter, and receiver ([0043] "The wireless device 202 may also include a housing 208 that may include a transmitter 210 and a receiver 212 to allow transmission and reception of data").
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement each of Diener's multiple WLAN APs and client stations as Merlin's spatially separated, housed wireless device, thereby providing physically independent housings while preserving wireless transmission and reception.
Claims 9 and 18 are rejected under 35 U.S.C. § 103 as being unpatentable over Zhu in view of Yeh, as applied to Claim 1 above, and further in view of Mayor et al. (US 20220141715 A1), hereinafter Mayor.
Regarding Claim 9: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu and Yeh do not teach wherein the protocol layers comprise a physical layer, a network layer, and a transport layer.
Mayor teaches wherein the protocol layers comprise a physical layer, a network layer, and a transport layer by disclosing simultaneous monitoring of all protocol-stack layers (paragraph [0098] "is designed to monitor all Internet protocol stack layers (i.e. physical, link, network, transport, and application layers) simultaneously").
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Zhu and Yeh with Mayor's simultaneous physical-, network-, and transport-layer monitoring, thereby providing a more complete multilayer basis for wireless-network configuration decisions (Mayor [0099]).
Regarding claim 18 (CRM) is rejected under the same reasoning as claim 9 (system).
Claim 10 is rejected under 35 U.S.C. § 103 as being unpatentable over Zhu in view of Yeh, as applied to Claim 1 above, and further in view of Kheirkhah et al. (WO 2023059932 A1), hereinafter Kheirkhah.
Regarding Claim 10: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu and Yeh do not teach wherein: the wireless technologies are based on corresponding protocol stacks; and the performance data is based on the protocol layers from multiple levels of the protocol stacks.
Kheirkhah teaches wherein: the wireless technologies are based on corresponding protocol stacks; and the performance data is based on the protocol layers from multiple levels of the protocol stacks (paragraph [0151] "with each radio protocol stack (e.g., 5G-NR and/or Wi-Fi)"); (paragraph [0159] "LLC, MAC, PHY of a Wi-Fi stack 508 and/or RRC, PDCP, RLC, MAC, PHY of a 5G stack 510"); (paragraph [0228] "several network related data parameters (e.g., measurements and statistics) from different radio protocol stacks and/or layers").
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Zhu and Yeh with Kheirkhah's corresponding protocol stacks and multilevel measurements, thereby providing more complete information for steering traffic across different access links (Kheirkhah [0143]).
Claims 11 and 17 are rejected under 35 U.S.C. § 103 as being unpatentable over Zhu in view of Yeh, as applied to Claim 1 above, and further in view of Bogineni et al. (US 20200196155 A1), hereinafter Bogineni.
Regarding Claim 11: Zhu in view of Yeh teaches the system of Claim 1 as discussed above.
Zhu and Yeh do not teach wherein the one or more configuration settings are determined based on a machine learning (ML) model, wherein the ML model is trained to infer configuration adjustments based on past performance data for the wireless technologies.
Bogineni teaches wherein the one or more configuration settings are determined based on a machine learning (ML) model, wherein the ML model is trained to infer configuration adjustments based on past performance data for the wireless technologies by disclosing multiple wireless access technologies ([0016] "the access technologies provided by the network can include 5G long-term evolution (LTE), 5G new radio (NR) frequency range 1 (FR1), 5G NR FR2, narrowband Internet of Things (NB-IoT)"); network-performance data (paragraph [0017] "data indicating bit rates through network resources"; [0017] "data indicating collision and packet drop rates associated with the network"; [0017] "data indicating latencies associated with the network"; [0017] "time-series monitoring data associated with the network"); use of an ML model to determine actions ([0021] "process the core data, the edge data, the RAN data, and/or the analytics data, with a machine learning model, to determine one or more actions"); training the model using historical network and RAN data and historical actions ([0022] "perform a training operation on the machine learning model with historical data"; [0022] "historical RAN data for RANs associated with the networks"; [0022] "information indicating historical actions performed by the core domains of the networks, edge domains of the networks, and/or the RANs"); predictions based on the historical data ([0024] "use the partitions and/or branches to perform predictions (e.g., information indicating one or more actions performed in the networks and/or the RANs)"); and a predicted configuration action ([0048] "cause the base station of the RAN to select a particular band and/or a particular physical resource block (PRB) for the RAN"). Together, these disclosures suggest training the ML model to infer a band or PRB configuration adjustment from past performance data for the disclosed wireless technologies.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use Bogineni's historically trained ML model in the Zhu-Yeh system, thereby automating configuration decisions from past network-performance and action data. Bogineni identifies the benefit of ML automation (Bogineni [0049]).
Regarding claim 17 (CRM) is rejected under the same reasoning as claim 11 (system).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HASAN CHEEMA whose telephone number is (571)272-8722. The examiner can normally be reached Mon-Fri 8:00-5:00 EST. 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, Ayman Abaza can be reached at (571) 270-0422. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/H.A.C./Examiner, Art Unit 2465
/AYMAN A ABAZA/Primary Examiner, Art Unit 2465
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