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 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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Azizi (US 20190364492)
Regarding claim 1, 10 and 19, Azizi teaches a method for accessing, by a mobile terminal, a network cell, comprising:
obtaining location information of the mobile terminal ([1011] FIG. 96, prediction engine 9600 may collect a variety of high-level context information, including ..location information (e.g., from a GNSS such as a GPS));
predicting a first area without network service or with weak network service (poor radio coverage), and a second area with normal network service (strong/improved radio coverage) that the mobile terminal is predicted to enter after passing through the first area, based on the location information of the terminal, ([1001] “a terminal device may utilize context information to optimize power consumption... terminal device may predict when or where the poor and strong radio coverage will occur and schedule radio activity such as cell scans and/or data transfers based on the predictions”; [1003] “by anticipating when or where a user will be in poor radio coverage along a known route; a terminal device may, for example, suspend cell scans and/or data transfer until improved radio coverage is expected”. Thus, the system predicts/anticipates when and where the weak/poor signal service area is and suspends any scanning until the radio coverage is expected/predicted to be improved/strong.)
wherein the first area and the second area are on a travel route of the mobile terminal ([1003] this disclosure may apply high-level context information to optimize radio activity on predicted radio conditions... to predict user travel routes and subsequently optimize radio activity such as cell scans and data transfer along predicted routes... terminal devices may predict which network access nodes will be available along a predicted travel route)
obtaining second area information (predicted travel routes including where strong radio coverage is) before the mobile terminal arrives at a first area ([1001] “a terminal device may utilize context information to optimize power consumption... terminal device may predict when or where the poor and strong radio coverage will occur and schedule radio activity such as cell scans and/or data transfers based on the predictions”; [1003] “by anticipating when or where a user will be in poor radio coverage along a known route; a terminal device may, for example, suspend cell scans and/or data transfer until improved radio coverage is expected”. Thus, the system predicts/anticipates when and where the weak/poor signal service area is first and then suspends any scanning until the radio coverage is predicted/expected to be improved/strong. Thus, the system predicts the first area of weak service signal first and then the second area with strong/improved/normal service signal.) and
performing a network cell search and accessing a searched network cell based on the obtained second area information, in response to detecting that the mobile terminal enters the second area ([1003] this disclosure may apply high-level context information to optimize radio activity on predicted radio conditions... to predict user travel routes and subsequently optimize radio activity such as cell scans and data transfer along predicted routes... terminal devices may predict which network access nodes will be available along a predicted travel route and may utilize such information to make radio and radio access selections, such as selecting certain cells, certain networks [1011] “terminal device 9102 may utilize context information... to evaluate context information to predict user travel routes and radio conditions and to subsequently control radio activity based thereon” [1003] “by anticipating when or where a user will be in poor radio coverage along a known route; a terminal device may, for example, suspend cell scans and/or data transfer until improved radio coverage is expected”).
With further regard to claims 10 and 19, Azizi teaches a processor; and a memory ([0313] As shown in FIG. 3, terminal device 200 may include...memory 312 and one or more processors).
Regarding claim 2, 11 and 20, Azizi teaches the method according to claim 1, wherein the predicting of the first area (predict when or where the poor coverage) and the second area and obtaining of first area information and the second area information (predict when or where the strong coverage), are based on historical trip feature data of the mobile terminal and the location information of the mobile terminal ([1001] “a terminal device may utilize context information to optimize power consumption .. a terminal device may predict when or where the poor and strong radio coverage will occur and schedule radio activity such as cell scans and/or data transfers based on the predictions”; [1036] “prediction engine 9600 may monitor radio-related information over a windowed time period ... Prediction engine 9600 may also obtain other context information, such as one or more of location information, user-generated movement information, or time/sensory information, and utilize the historical sequence of radio conditions along with the other context information (such as current location... ) in order to predict a future sequence of radio conditions (e.g., in the order of milliseconds or seconds in the future).”).
Regarding claim 3 and 12, Azizi teaches the method according to claim 2, wherein the historical trip feature data comprises at least one of a route area ([1118] “various aspects may utilize context information such as location information, velocity information, route information, etc., from vehicles 11902-11906 at roadside network access node 11900 in order to predict vehicle trajectories”), time information corresponding to the route area, route network information corresponding to the route area, user feature information, and traffic feature information ([1036] “terminal device 9102 may implement these aspects on a more fine-grained scale. For example, in addition or alternative to applications related to controlling radio activity during travel on roads or other longer paths (which may be in the order of minutes or hours), terminal device 9102 may control radio activity over much smaller durations of time (e.g., milliseconds or seconds). For example, prediction engine 9600 may monitor radio-related information over a windowed time period (e.g., in the order of seconds or milliseconds) to obtain a historical sequence of radio conditions, which may be a sequence of signal strength measurements, signal quality measurements, or other radio-related context information. Prediction engine 9600 may also obtain other context information, such as one or more of location information, user-generated movement information, or time/sensory information, and utilize the historical sequence of radio conditions along with the other context information (such as current location, accelerometer or gyroscope information, etc.) in order to predict a future sequence of radio conditions (e.g., in the order of milliseconds or seconds in the future). Prediction engine 9600 may then provide the future sequence of radio conditions to decision engine 9610, which may control radio activity based on the future sequence of radio conditions”; [1026] “decision module 9612 may continue receiving prediction results from learning engine 9702 and may continually evaluate predicted route information in 9712 to determine if the predicted route has changed. For example, while prediction engine 9600 may anticipate that a user will continue on a regular or planned route, a user may make other decisions that affect the predicted route, such as by stopping a car, taking a detour, being stuck in traffic, speeding up or down; alternatively, prediction engine 9600 may have mistakenly identified another route as a regular route”).
Regarding claim 4 and 13, Azizi teaches the teaches the method according to claim 2, wherein the first area and the second area are predicted, and the first area information and the second area are obtained, when a condition for triggering is detected, and wherein the condition for triggering comprises at least one of an expiration of a timing with a predetermined prediction period, a location change, a deviation from a trajectory, and a change in current network connection status ([1026] “decision module 9612 may continue receiving prediction results from learning engine 9702 and may continually evaluate predicted route information in 9712 to determine if the predicted route has changed. For example, while prediction engine 9600 may anticipate that a user will continue on a regular or planned route, a user may make other decisions that affect the predicted route, such as by stopping a car, taking a detour, being stuck in traffic, speeding up or down; alternatively, prediction engine 9600 may have mistakenly identified another route as a regular route. Decision module 9612 may thus continuously monitor the prediction results in 9712 to identify whether the predicted route has changed. If decision module 9612 determines that the predicted route has changed in 9712, decision module 9612 may update the expected poor radio condition time in 9714 and re-set the backoff timer at baseband modem 9206 in 9710. Decision module 9612 may continue monitoring prediction results and updating the backoff timer if necessary. Eventually, terminal device 9102 may reach the end of section 9504 and thus leave the expected poor radio condition area, which may coincide with the expiry of the backoff timer. Baseband modem 9206 may then switch to normal operation modes in 9716 and restart performing cell scans (e.g., according to cell scan triggering conditions). As opposed to section 9504 in which no cells may be available, baseband modem 9206 may re-detect network access node 9110 within range of terminal device 9102 and may subsequently re-establish a connection with network access node 9110. In other low signal conditions, such as when terminal device 9102 is at a cell edge and only a single cell is detectable, decision module 9612 may utilize the prediction results to set the backoff timer to coincide with an expected time when terminal device 9102 enters the coverage area of a stronger cell”; [1026] “decision module 9612 may continue receiving prediction results from learning engine 9702 and may continually evaluate predicted route information in 9712 to determine if the predicted route has changed. For example, while prediction engine 9600 may anticipate that a user will continue on a regular or planned route, a user may make other decisions that affect the predicted route, such as by stopping a car, taking a detour, being stuck in traffic, speeding up or down; alternatively, prediction engine 9600 may have mistakenly identified another route as a regular route.)
Regarding claim 5 and 14, Azizi teaches the method according to claim 2, wherein the first area and the second area are predicted, and the first area information and the second area information are obtained in a server or locally in the mobile terminal ([1010] “FIG. 96 shows a functional diagram of terminal device 9102 in accordance with some aspects. As shown in FIG. 96, prediction engine 9600 may include preprocessing module 9602, local repository 9604, and local learning module 9606 while decision engine 9610 may include decision module 9612. As will be described in detail, prediction engine 9600 may receive context information as input, which prediction engine 9600 may, for example, process, store, and evaluate in order to make predictions about expected user behavior including in particular user travel routes”; Prediction engine is part of the terminal device, thus the predicting occurs locally).
Regarding claim 6 and 15, Azizi teaches the method according to claim 2, wherein the first area information comprises time required to pass through the first area under a preset condition, and wherein the second area information comprises at least one of network cell information, network signal strength of the network cell, network coverage of the network cell, network connection speed, network type, and network access status of the second area (The examiner notes that this limitation holds little weight since it does not positively recite an active step being performed or specific structure performing a function. [1118] “various aspects may utilize context information such as location information, velocity information, route information, etc., from vehicles 11902-11906 at roadside network access node 11900 in order to predict vehicle trajectories” [1036] “prediction engine 9600 may monitor radio-related information over a windowed time period (e.g., in the order of seconds or milliseconds) to obtain a historical sequence of radio conditions, which may be a sequence of signal strength measurements, signal quality measurements, or other radio-related context information. Prediction engine 9600 may also obtain other context information, such as one or more of location information, user-generated movement information, or time/sensory information, and utilize the historical sequence of radio conditions along with the other context information (such as current location, accelerometer or gyroscope information, etc.) in order to predict a future sequence of radio conditions (e.g., in the order of milliseconds or seconds in the future). Prediction engine 9600 may then provide the future sequence of radio conditions to decision engine 9610, which may control radio activity based on the future sequence of radio conditions.).
Regarding claim 7 and 16, Azizi teaches the method according to claim 6, wherein the network cell information of the second area is information on a network cell which the mobile terminal prefers to access in the second area (The examiner notes that the wherein limitation holds little weight as it does not positively recite an active step nor does it recite any specific structure performing a specific function. Nonetheless, this limitation was addressed for compact prosecution purpose. [3607] In Example 1293, the subject matter of Example 1280 can optionally include wherein the predicted radio conditions indicate predicted radio conditions of one or more first network access nodes of the one or more first areas and predicted radio conditions of one or more second network access nodes of the one or more second areas, and wherein controlling the radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas includes selecting a first serving access node from the one or more first network access nodes while traveling in the one or more first areas based on the predicted radio conditions, and selecting a second serving access node from the one or more second network access nodes while traveling in the one or more second areas based on the predicted radio conditions.).
Regarding claim 8 and 17, Azizi teaches the method according to claim 1, further comprising: after the obtaining the second area information, detecting whether the mobile terminal enters the second area, based on at least one of a positioning result of the mobile terminal, a network signal change of the mobile terminal, and time elapsed since the mobile terminal arrives at the first area ([3597] “In Example 1283, the subject matter of Example 1282 can optionally include wherein controlling the radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas further includes triggering cell scans after entering the one or more second areas. [3598] In Example 1284, the subject matter of Example 1281 can optionally further include determining that a user is currently traveling in the one or more first areas, and determining that the predicted route runs through the one or more second areas, wherein controlling the radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas includes suspending cell scans while traveling in the one or more first areas until the one or more second areas is reached.”)
Regarding claim 9 and 18, Azizi teaches the method according to claim 8, further comprising: determining whether the mobile terminal arrives at the first area based on the positioning result of the mobile terminal ([3597] “In Example 1283, the subject matter of Example 1282 can optionally include wherein controlling the radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas further includes triggering cell scans after entering the one or more second areas.” [3598] “In Example 1284, the subject matter of Example 1281 can optionally further include determining that a user is currently traveling in the one or more first areas, and determining that the predicted route runs through the one or more second areas, wherein controlling the radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas includes suspending cell scans while traveling in the one or more first areas until the one or more second areas is reached.”)
Response to Arguments
Applicant's arguments filed 1/20/2026 have been fully considered but they are not persuasive.
Applicants argues that,
“Azizi fails to disclose or render obvious "obtaining first area information, the first area information including a predicted time required for the mobile terminal to pass through the first area; ... starting a timer set for a duration based on the predicted time required for the mobile terminal to pass through the first area; in response to an expiry of the timer, detecting whether the mobile terminal enters the second area; and in response to detecting that the mobile terminal enters the second area, performing a network cell search and accessing a searched network cell based on the obtained second area information."
The examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “starting a timer set for a duration based on the predicted time required for the mobile terminal to pass through the first area; in response to an expiry of the timer,” … in response to detecting that the mobile terminal enters the second area) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicants argues that,
“Azizi does not disclose "obtaining second area information including information about at least one network cell in the second area before the mobile terminal arrives at the first area; and performing a network cell search and accessing a searched network cell based on the obtained second area information, in response to detecting that the mobile terminal enters the second area" of amended claim 1.”
Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
The examiner respectfully disagrees. Azizi does teach obtaining second area information including information about at least one network cell in the second area before the mobile terminal arrives at the first area ([1001] a terminal device may predict when or where... strong radio coverage will occur ([1003] “by anticipating when or where a user will be in poor radio coverage along a known route; a terminal device may, for example, suspend cell scans and/or data transfer until improved radio coverage is expected”. Thus, the system predicts/anticipates when and where the weak/poor signal service area is first and then suspends any scanning until the radio coverage is predicted/expected to be improved/strong. Thus, the system predicts the first area of weak service signal first and then the second area with strong/improved/normal service signal.);
performing a network cell search and accessing a searched network cell based on the obtained second area information, in response to detecting that the mobile terminal enters the second area ([1003] this disclosure may apply high-level context information to optimize radio activity on predicted radio conditions .. to predict user travel routes and subsequently optimize radio activity such as cell scans and data transfer along predicted routes.. terminal devices may predict which network access nodes will be available along a predicted travel route and may utilize such information to make radio and radio access selections, such as selecting certain cells, certain networks [1011] “terminal device 9102 may utilize context information .. to evaluate context information to predict user travel routes and radio conditions and to subsequently control radio activity based thereon” [1003] “by anticipating when or where a user will be in poor radio coverage along a known route; a terminal device may, for example, suspend cell scans and/or data transfer until improved radio coverage is expected”).
Applicants argues that,
Azizi does not disclose that "when it is predicted that a mobile terminal is going to pass through an first area in which a network service is weak or absent and an area with a normal network service sequentially, the terminal device obtains information about the area with a normal network service before the terminal device enters the area in which a network service is weak or absent, and accesses a network cell based on the obtained information, when the mobile terminal enters the second area".
The examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “when it is predicted… terminal device obtains information about the area with a normal network service before the terminal device enters the area in which a network service is weak or absent”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant seems to argue that “when” a first area of weak service is first predicted, then obtain the “second area of good service”. The examiner submits that such “when” limitation is not being claimed. The claim only recites the “predicting” of the first and second area but there is no recitation of “when…”.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUNG L LAM whose telephone number is (571)272-6497. The examiner can normally be reached Monday -Thursday 9-5pm.
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/DUNG L LAM/Examiner, Art Unit 2646 /JEANETTE J PARKER/Supervisory Patent Examiner, Art Unit 2646
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