T-Mobile USA, Inc.

Patent Trials and Appeals Board

Jul 27, 2021

2020002317 (P.T.A.B. Jul. 27, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
15/149,052 05/06/2016 Michael John Prochniak TMBLE.095A 2995
118591 7590 07/27/2021
KNOBBE, MARTENS, OLSON & BEAR, LLP
T-Mobile USA, Inc. (TMBLE)
2040 Main Street, Fourteenth Floor
Irvine, CA 92614
EXAMINER
DU, HUNG K
ART UNIT PAPER NUMBER
2647
NOTIFICATION DATE DELIVERY MODE
07/27/2021 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
efiling@knobbe.com
jayna.cartee@knobbe.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________________

Ex parte MICHAEL JOHN PROCHNIAK,
BRANDON KANNIER, MARTIN JAMES TALL, and
MATTHEW BRYAN TAUNTON
____________________

Appeal 2020-002317
Application 15/149,052
Technology Center 2600
____________________

Before JOHN A. EVANS, JUSTIN BUSCH, and
JOHN P. PINKERTON, Administrative Patent Judges.

PINKERTON, Administrative Patent Judge.

DECISION ON APPEAL
Appellant1 appeals under 35 U.S.C. § 134(a) from the Examiner’s
Non-Final Rejection of claims 1–23. Claims 24 and 25 are canceled.
Because the claims on appeal have been twice rejected, we have jurisdiction
pursuant to 35 U.S.C. §§ 6 and 134(a). Ex parte Lemoine, 46 USPQ2d
1420, 1423 (BPAI 1994) (precedential).
We AFFIRM.

1 We use the word “Appellant” to refer to “applicant” as defined in
37 C.F.R. § 1.42. Appellant identifies T-Mobile USA, Inc. as the real party
in interest. Appeal Br. 3.
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STATEMENT OF THE CASE
Introduction
Appellant generally describes the disclosed and claimed invention as
relating “to the management of network infrastructure equipment . . .
utilizing intermediate performance thresholds and trend performance
thresholds to characterize functionality of the infrastructure equipment
according to collected performance information.” Spec. ¶ 9.2
Claims 1, 6, and 17 are independent. Claim 1, which is reproduced
below, is representative of the subject matter on appeal:
42. A method for managing infrastructure equipment
comprising:
obtaining hardware performance information for an
individual infrastructure component, wherein the hardware
performance information corresponds to data collected during
operation of the individual infrastructure component in a
wireless network;
storing the hardware performance information;
identifying one or more intermediate hardware
performance thresholds corresponding to performance
information collected from the individual infrastructure
component;
characterizing a functionality of the individual
infrastructure component based on applying the identified one or
more intermediate hardware performance thresholds;
generating a notification based on a characterization of the
functionality as likely to fail;

2 Our Decision refers to the Non-Final Office Action mailed July 17, 2018
(“Non-Final Act.”); Appellant’s Appeal Brief filed June 28, 2019 (“Appeal
Br.”) and Reply Brief filed Jan. 30, 2019 (“Reply Br.”); the Examiner’s
Answer mailed Dec. 2, 2019 (“Ans.”); and the Specification filed May 6,
2016, as amended on September 20, 2017 (“Spec.”).
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identifying one or more trend hardware performance
thresholds corresponding to a set of performance information
collected from the individual infrastructure component, wherein
the set of performance information includes at least one historical
performance information;
characterizing a second functionality of the individual
infrastructure component based on applying the identified one or
more trend hardware performance thresholds; and
generating a notification based on a characterization of the
second functionality as likely to fail.
Appeal Br. 18 (Claims App.).
Rejections on Appeal
The Examiner rejects claims 1–23 under the following grounds:
Claims 35 U.S.C. § Reference(s) Citation
1, 2, 4, 6, 7, 9,
12–15, 17–21,
23–25
103 Tektumanidze,
3
Henderson4
Non–Final Act.
3–13
5, 16, 22 103 Tektumanidze, Henderson, Foster5
Non–Final Act.
13–15
8, 10 103 Tektumanidze, Henderson, Xing6
Non–Final Act.
15–16
3, 11 103 Tektumanidze, Henderson, Lee7
Non–Final Act.
16–17

3 US 9,585,036 B1 (issued Feb. 28, 2017, “Tektumanidze”).
4 US 2014/0073303 Al (published Mar. 13, 2014, “Henderson”).
5 US 2014/0355484 Al (published Dec. 4, 2014, “Foster”).
6 US 2013/0090126 Al (published Apr. 11, 2013, “Xing”).
7 US 2015/0028816 Al (published Jan. 29, 2015, “Lee”).
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ANALYSIS
We have reviewed the Examiner’s rejections of claims 1–23 in light
of Appellant’s arguments in the Appeal Brief and the Reply Brief. See
Appeal Br. 8–17; Reply Br. 1–5. Any other arguments Appellant could have
made, but chose not to make, are waived. See 37 C.F.R. § 41.37(c)(1)(iv)
(2018). For the reasons discussed below, Appellant’s arguments are not
persuasive of error by the Examiner. Unless otherwise indicated, we agree
with, and adopt as our own, the Examiner’s findings of fact and conclusions
as set forth in the Non-Final Office Action from which this appeal is taken
and in the Answer. Non-Final Act. 2–17; Ans. 3–13. We provide the
following explanation for emphasis.
Appellant argues independent claim 1 and states that the rejections of
claims 2–23 are improper for at least the reasons set forth for claim 1. See
Appeal Br. 8–17. Accordingly, we select claim 1 as representative, and the
remaining claims stand or fall with claim 1. See 37 C.F.R. § 41.37(c)(1)(iv)
(2018).
The Examiner rejects claim 1 under 35 U.S.C. § 103 for obviousness
based on Tektumanidze and Henderson. Non–Final Act. 3–6; see also Ans.
3–6. Appellant argues that the cited prior art references, individually or in
combination, fail to teach or suggest “characterizing a functionality of the
individual infrastructure component based on applying the identified
one or more intermediate hardware performance thresholds.” Appeal
Br. 9–13 (emphasis added); Reply Br. 2–5. We consider this argument
below, but we are not persuaded that the Examiner erred.
The Examiner finds Tektumanidze teaches or suggests the
“characterizing” step because it describes creating a problem identification
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grid by applying threshold tests to performance parameter data for a mobile
wireless network component, such as a base station. See Non–Final Act. 2–
3 (citing Tektumanidze 7:45–48), 4 (citing Tektumanidze 10:50–11:9); Ans.
3–5 (additionally citing Tektumanidze 5:13–19, 8:45–9:42, 9:60–10:10,
10:18–35, 10:37–49, 11:9–11:26, Figs. 2–3).
Tektumanidze relates to identifying the impact of problematic mobile
wireless network components to facilitate network maintenance activities.
Tektumanidze 2:45–51. Figure 3 of Tektumanidze is reproduced below.

Figure 3 of Tektumanidze is a flowchart summarizing a set of operations for
identifying network performance issues to be addressed by network
technicians. Id. at 3:47–54, 9:44–10:49, Fig. 3; see also id. at Figs. 2, 4.
At step 300, the system acquires and stores a set of performance-
parameter data points for one or more mobile wireless network components
in a geographical area covering a plurality of cell sites. Id. at 9:60–66, Fig. 3
(step 300). The set of performance parameter data points can have one or
more data types, including CPU usage, dropped call percentage, and key
performance indicators (KPI) such as Received Quality (RSRQ), Reference
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Signal Received Power (RSRP), and radio signal strength. Id. at 9:62–63,
Fig. 2 (items 200, 210, 290). And each data point can be assigned a
particular geographical location, such as (1) the location of the base station
associated with the one or more mobile wireless network components or (2)
the location of the mobile wireless device receiving or generating the radio
signal. Id. at 9:66–10:17.
At step 310, by applying one or more threshold tests to the acquired
and stored data points, the system’s problem impact server can create a
problem impact grid for the geographical area of interest. Id. at 10:18–21,
10:29–36, 10:50–11:9, Figs. 3 (step 310), 4 (step 400), 5. The problem
impact grid can identify specific areas (squares in a grid) within the
geographic area of interest and the associated degree of impact of the
particular problem (for example, a CPU usage or Radio signal strength
value). See id. at 10:29–36, Fig. 5. Additional mathematical operations can
be performed on the problem impact grid (and revisions thereof) to
determine the extent and severity of a problem area and to identify
additional problem areas. Id. at 11:39–50, 11:57–67, 12:11–18, Figs. 4
(steps 410, 420), 6–8.
And, at step 320, based upon the problem impact grid, the problem
impact server can generate a listing representing a prioritized set of specific
network component performance issues arranged in order of highest to
lowest impact based upon the impact score values assigned to squares of the
problem impact grid. Id. at 10:37–49.
Appellant argues the Examiner erred in finding Tektumanidze teaches
or suggests the “characterizing” step for two main reasons. See Reply Br.
2–5; Appeal Br. 9–13. First, Appellant argues the Examiner’s rationale—
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that identifying a performance parameter problem in Tektumanidze indicates
an infrastructure component problem—“erroneously assumes that
identifying a performance issue in a grid square necessarily identifies a
problem with an infrastructure component in the grid square.” Reply Br. 2;
Appeal Br. 9–13. In particular, Appellant asserts that “[a]n indication of a
dropped call problem (or other performance issue detected by the system
taught in Tektumanidze) may have any number of root causes,” and “it is not
appropriate to infer, as the Examiner does, that any performance problem
detected by the system taught in Tektumanidze is caused by an issue with
the functionality of the infrastructure equipment in the geographic area
where the problem is detected.” Appeal Br. 10. Appellant also asserts that
Tektumanidze does not teach or suggest applying “intermediate” hardware
performance thresholds because its network performance measurements are
not available immediately for testing, but instead are collected over an
extended period of time before being used to determine whether there is a
network problem. Id. at 11–12 (citing Tektumanidze 10:64:11:9; Spec.
¶ 12).
Second, Appellant disputes the Examiner’s finding that
Tektumanidze teaches or suggests the “characterizing” step because it
describes user-created tests for filtering network components. Reply Br. 2–
5. Appellant asserts that the cited description of Tektumanidze “does not
contain any disclosures regarding user-created tests or tests that ‘filter out’
network components.” Instead, Appellant argues that “Tektumanidze
discloses . . . that its system performs a variety of tests that evaluate to a ‘l’
or ‘0’ and are used to calculate a ‘problem impact score’ for each grid
square,” but “there is no teaching or suggestion that the system . . .
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characterizes the functionality of an individual infrastructure component
based on the results of such tests.” Reply Br. 3. Appellant adds that, in
Tektumanidze, there is no apparent correlation between a wireless network
performance issue (identified by a particular grid square value) and a
particular hardware infrastructure component in the wireless network. Reply
Br. 4–5; Appeal Br. 11–13.
We are not persuaded of Examiner error. Rather, for the reasons
stated below, we agree with the Examiner that Tektumanidze teaches or at
least suggests the “characterizing” step of claim 1 with its description of
creating a problem identification grid by applying threshold tests to
performance parameter data for a mobile wireless network component. See,
e.g., Non–Final Act. 2–4 (citing Tektumanidze 7:10–20, 7:45–48, 10:50–
11:9, Fig. 2); Ans. 3–5 (additionally citing Tektumanidze 5:13–19, 8:45–
9:42, 9:60–10:10, 10:18–35, 10:37–49, 11:9–11:26, Figs. 2–3); see also
Tektumanidze 8:59–64, 9:12–15, 9:26–31, 10:9–17, 12:39–53, Figs. 3–4.
Contrary to Appellant’s arguments, Tektumanidze at least suggests
the “characterizing” step because the value of a particular grid square may
be determined on the basis of a wireless network performance parameter
collected directly from or for a particular infrastructure component of the
wireless network. For example, as the Examiner finds, one of the wireless
network performance parameters that may be used to create a problem
identification grid (including individual grid square values) is a CPU usage
parameter, which Tektumanidze describes is “for a particular network
component” and “represents the percentage (e.g., maximum or average) of
non-idle process CPU cycles over a time period—a potential indicator of
whether additional, or more powerful, processors are needed for the
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component.” See Ans. 4–6; Tektumanidze 9:12–15, 9:26–31, Fig. 2 (item
290). These descriptions of Tektumanidze would have suggested the
“characterizing” step because applying a threshold test to a CPU usage
parameter data point set would have created a problem identification grid
(including one or more grid square values) indicating whether a CPU of a
device in Tektumanidze’s wireless network architecture (for example, a
server) is consuming too much resources. See, e.g., Tektumanidze 9:60–
10:36, 10:50–11:9, Figs. 2 (item 290), 3 (steps 300, 310), 4 (step 400); see
also id. at 8:50–43 (“The performance parameters are potentially used to
detect any type of problem for purposes of determining an impact of the
problem. In that regard the performance parameters may indicate an actual
failure of a network component.”).
Tektumanidze’s wireless network performance parameters also
include key performance indicators (KPIs) that specify well-known radio-
signal quality measures such as RSRQ, RSRP, and radio signal strength.
Tektumanidze 8:59–64, Fig. 2 (item 210); see Non-Final Act. 3–4 (citing
Tektumanidze 7:10–20, Fig. 2 (item 210)). According to Tektumanidze, raw
performance data point sets for such KPIs can be collected from any of a
variety of mobile wireless network components, including base stations and
gateways. Id. at 7:10–15. Tektumanidze’s process of collecting a data point
set from a particular mobile wireless network component, and then
performing threshold testing thereon to create a problem identification grid,
would have suggested grid square values that describe the performance of
that particular network component—that is, “characterizing a functionality
of the individual infrastructure component.” See, e.g., id. at 7:10–15, 9:60–
10:36, 10:50–11:9, Figs. 2, 3 (steps 300, 310), 4 (step 400). Tektumanidze
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further describes that the problem impact grid square values resulting from
an initial threshold test of acquired performance parameters can indicate the
problem of “insufficient signal strength.” Id. at 12:39–53. This description
as well would have suggested the “characterizing” step because it suggests
that the base station is sending a mobile wireless device a signal that does
not have sufficient power or strength. See also id. at 8:50–54.
Tektumanidze’s teachings and suggestions are consistent with Appellant’s
Specification, which describes that an “intermediate performance threshold[]
can correspond to a . . . measured signal strength of a radio component.”
Spec. ¶¶ 13, 28.
Appellant argues that the prior art requires greater detail about how
the threshold testing of a particular performance parameter data point set—
and the results thereof—relates to the performance of a particular hardware
infrastructure component. See Reply Br. 4–5; Appeal Br. 11–13. But this
argument is not commensurate with the scope of claim 1, which is broadly
recited, and Appellant’s Specification does not provide a limiting definition
of either “individual infrastructure component” or “intermediate hardware
performance thresholds.” Instead, the Specification describes that
infrastructure equipment can include “a wide variety” of components
including various hardware components and associated software devices and
provides only non-limiting examples of intermediate hardware performance
thresholds. Spec. ¶¶ 2, 12, 27–29, 32. And even though the Specification
describes an embodiment in which “intermediate” performance thresholds
are used to evaluate immediately collected performance information (see id.
¶¶ 12, 25, 30), the claim language is not so limiting. Accordingly, we see no
problem with Tektumanidze’s threshold testing being applied to
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performance parameter data that has been collected over a period of time.
Appeal Br. 11–12.
It is true that Tektumanidze does not expressly disclose user-created
tests that filter out network components. Nor does Tektumanidze
specifically explain how each grid square value relates to the performance of
a particular network component. But, as discussed above, the Examiner’s
overall findings nevertheless show that Tektumanidze’s steps that are part of
the process for creating a problem identification grid would have, at least,
suggested the “characterizing” step as claimed. The test for obviousness is
not that the claimed invention must be expressly disclosed in any one or all
of the references but rather, what the combined teachings of the references
would have suggested to those of ordinary skill in the art. In re Keller, 642
F.2d 413, 426 (CCPA 1981). As applied here, we are not persuaded of error
because the Examiner has set forth sufficient evidence that the proposed
combination of Tektumanidze and Henderson would suggested the disputed
claim step to one of ordinary skill in the art.
Thus, for these reasons, we are not persuaded the Examiner erred in:
(1) finding that Tektumanidze teaches or at least suggests the
“characterizing” step of claim 1; and (2) concluding that Tektumanidze and
Henderson renders obvious the subject matter of claim 1 under 35 U.S.C.
§ 103.
Accordingly, we sustain the Examiner’s rejection of claim 1 under 35
U.S.C. § 103 for obviousness based on Tektumanidze and Henderson. For
the same reasons, we sustain the Examiner’s rejections of claims 2–23 under
35 U.S.C. § 103 for obviousness based at least on Tektumanidze and
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Henderson. As discussed above, Appellant does not argue the rejections of
these claims beyond the arguments advanced for claim 1.

DECISION
We affirm the Examiner’s rejections of claims 1–23.
SUMMARY
In summary:
Claim(s)
Rejected 35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1, 2, 4, 6, 7,
9, 12–15,
17–21, 23–
25
103 Tektumanidze, Henderson
1, 2, 4, 6, 7,
9, 12–15,
17–21, 23–
25

5, 16, 22 103 Tektumanidze, Henderson, Foster 5, 16, 22
8, 10 103 Tektumanidze, Henderson, Xing 8, 10
3, 11 103 Tektumanidze, Henderson, Lee 3, 11
Overall
Outcome 1–25

No period for taking any subsequent action in connection with this
appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv). See 37 C.F.R.
§ 41.50(f).
AFFIRMED