CTNF 18/066,222 CTNF 86960 DETAILED ACTION The office action is responsive to an application filed on 12/14/22 and is being examined under the first inventor to file provisions of the AIA. Claims 1-20 are pending. Priority Acknowledgment is made of applicant's claim for priority to U.S. Provisional Patent Application 63/039,305 filed on 6/15/20. Claim Objections 07-29-01 AIA Claim 15 is objected to because of the following informalities: Claim 15 recites the limitation "the traffic model" in lines 9 and 12 of the claim. There is insufficient antecedent basis for this limitation in the claim . Appropriate correction is required. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under the broadest reasonable interpretation, the claims cover performance of the limitation in the mind or by pencil and paper and as a mathematical concept. Claims 1, 15 and 20 Regarding step 1 , claims 1, 15 and 20 are directed towards a method, apparatus and medium which has the claims fall within the eligible statutory categories of processes, machines, manufactures and composition of matter under 35 U.S.C. 101. Claim 1 Regarding step 2A, prong 1, claim 1 recites “ determining a traffic model, a number of packets to be run for each use case, and a seed value for the Monte Carlo simulation, wherein the traffic model includes multiple packet sizes and a distribution corresponding to the multiple packet sizes ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraphs [0005] and [0060] of the specification. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 1 recites “ and determining a recommended configuration of processor cores for the data stack based on the simulation result ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Regarding step 2A, prong 2, the limitation of “ receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g). Also, the limitation of “ performing the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim language also does not include a computer or components of a computer, but if written with, for example, a processor, the claim language would still not be eligible under 35 U.S.C. 101. For example, adding the phrase "by a processor" to the claim language, would encompass the processor be recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, the additional element of a processor does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Regarding Step 2B , the limitation of “ receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II). Also, the limitation of “ performing the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim(s) docs/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a processor amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b). Claim 15 Regarding step 2A, prong 1, claim 15 recites “ determine a number of packets to be run for each use case, and a seed value for the Monte Carlo simulation, wherein the traffic model includes multiple packet sizes and a distribution corresponding to the multiple packet sizes ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraphs [0005] and [0060] of the specification. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 15 recites “ and determine a recommended configuration of processor cores for the data stack based on the simulation result ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Regarding step 2A, prong 2, the limitation of “ receive an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g). Also, the limitation of “ perform the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim includes the additional elements of a processor and a memory. The processor and memory are recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Regarding Step 2B , the limitation of “ receive an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II). Also, the limitation of “ perform the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the processor and medium amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b). Claim 20 Regarding step 2A, prong 1, claim 20 recites “ determining a traffic model, a number of packets to be run for each use case, and a seed value for the Monte Carlo simulation, wherein the traffic model includes multiple packet sizes and a distribution corresponding to the multiple packet sizes ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraphs [0005] and [0060] of the specification. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 20 recites “ and determining a recommended configuration of processor cores for the data stack based on the simulation result .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Regarding step 2A, prong 2, the limitation of “ receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g). Also, the limitation of “ performing the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim includes the additional elements of a processor and a medium. The processor and medium are recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Regarding Step 2B , the limitation of “ receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, a processor specification, and a user-specified function ” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II). Also, the limitation of “ performing the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is, what the use case is or what the seed value is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the processor and medium amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b). Claims 2 and 17 Dependent claims 2 and 17 recite “ generating, prior to performing the Monte Carlo simulation, an instruction mapping for each of the one or more use cases ”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the instruction mapping is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Dependent claims 2 and 17 recite “ wherein the instruction mapping includes a total number of instructions (I) per second per component carrier .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 3 Dependent claim 3 recites “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A); a maximum data rate (R); a packet size (S); and a total number of component carriers (N). ”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the instructions are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Also, this limitation can calculate the total number of instructions (I) per second per component carrier. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Claim 4 Dependent claim 4 recites “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N). ”. This limitation is calculating the total number of instructions per second per component carrier (I). Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Claim 5 Dependent claim 5 recites “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A); a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P); and a slot duration (T) .”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the instructions are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Claim 6 Dependent claim 6 recites “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T). ”. This limitation is calculating the total number of instructions per second per component carrier (I). Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Claim 7 Dependent claim 7 recites “ performing the Monte Carlo simulation based on the input and the traffic model until the number of packets to be run for each use case is reached .”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the input is or what the use case is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Claim 8 Dependent claim 8 recites “ determining, based on the simulation result, a total MIPS per component carrier ”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the simulation result is or how the component carrier is associated with the simulation result. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". “ and determining, based on the total MIPS per component carrier, a total cycles per second, a total number of MIPS, and a total number of Million Cycles per Second (Mcps) .”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the component carrier is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Claim 9 Dependent claim 9 recites “ determining the recommended configuration of processor cores for the data stack based on the total cycles per second, the total number of MIPS, and the total number of Mcps .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Also, this limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the total cycles per second, the total number of MIPS or the total number of Mcps and how they’re associated with processor cores for the data stack. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Claim 10 Dependent claim 10 recites “ wherein the requirement for the one or more use cases includes a type of Radio Access Technology (RAT), a Maximum Data Rate (MDR), a SubCarrier Spacing (SCS), a number of Component Carriers (CCs), and/or a number of Logical Channels (LCs). ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 11 Dependent claim 11 recites “ wherein the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 12 Dependent claim 12 recites “ wherein the processor specification includes: a clock rate; a local Cycles Per Instruction (CPI); an external CPI; and/or a processor load threshold .”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 13 Dependent claim 13 recites “ wherein the user-specified function includes information indicating one or more of the following: a number of instructions to be executed; an execution frequency for the instructions to be executed; and/or information indicating that the instructions to be executed are downlink (DL) or uplink (UL) .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 14 Dependent claim 14 recites “ wherein the user-specified function includes: a main-processor functional partition to be deployed on a data-plane main processor ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Dependent claim 14 recites “ a micro-controller functional partition to be deployed on a data-plane micro controller; and/or a data-plane-hardware (DPHW) functional partition to be deployed on data plane hardware .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 16 Dependent claim 16 recites “ wherein: the requirement for the one or more use cases includes a type of Radio Access Technology (RAT), a Maximum Data Rate (MDR), a SubCarrier Spacing (SCS), a number of Component Carriers (CCs), and/or a number of Logical Channels (LCs) ”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Dependent claim 16 recites “ the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases ”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Dependent claim 16 recites “ and the user specified function includes (i) a main-processor functional partition to be deployed on a data-plane main processor, (ii) a micro-controller functional partition to be deployed on a data-plane micro controller, and/or (iii) a data-plane-hardware (DPHW) functional partition to be deployed on data plane hardware .”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas. Claim 18 Dependent claim 18 recites “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A); a maximum data rate (R); a packet size (S); and a total number of component carriers (N) ”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the instructions are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Also, this limitation can calculate the total number of instructions (I) per second per component carrier. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Dependent claim 18 recites “ and wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N) .”. This limitation is calculating the total number of instructions per second per component carrier (I). Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Claim 19 Dependent claim 19 recites “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A); a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P); and a slot duration (T) ”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the instructions are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Dependent claim 19 recites “ and wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T) .”. This limitation is calculating the total number of instructions per second per component carrier (I). Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas. Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claim(s) 1-3, 5, 7-10, 13-14 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over online reference in view of online reference Interference-Aware Radio Resource Allocation for 5G Ultra-Reliable Low-Latency Communication, written by Malik et al. in view of Zhao et al. (WO 2017/007727) (from IDS dated 1/18/24). With respect to claim 1 , Malik et al. discloses “ receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases ” as [Malik et al. (Pg. 2, sec. 2 Rate Maximization Problem Formulation, 2 nd paragraph, “ To improve the link reliability and reduce the retransmissions, it is crucial to improve the SINR of user in the presence of inter-cell interference with an appropriate resource allocation scheme. Therefore, in this paper, a multi-cell cellular network, where each cell comprises of three sectors, is studied and the focus is on the uplink transmission where user expect inter-cell interference from the neighboring cell uplink users in the same resource as shown in Figure 1 .”, Malik et al. Pg. 4, sec. 4A, Simulation setup, 1 st paragraph, “ For the performance analysis, we have considered a regular hexagonal multi-cell cellular network with three sectors in each cell and an inter-site distance of 500 m. The simulation assumption and parameters are derived from the 3GPP standard [14] as presented in Table I. The total frame transmission is assumed to be 10 ms with mini-slot of 1 ms. Each mini-slot consist of one PRB of 180 kHz, comprising of 12 subcarriers with 15 kHz subcarrier spacing. Furthermore, the retransmission factor is computed based on MCL for different coverage classes and presented in Figure 2 .”, Fig. 1)]; “ determining a traffic model, a number of packets to be run for each use case ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT ”)]; “ and a seed value for the Monte Carlo simulation ” as [Malik et al. (Pg. 4, sec. B Simulation results, 1 st paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations .”, Table 1, The examiner considers the values in Table 1 of the Malik et al. reference to be the seed value, since it’s the initial values of the parameters for the simulation)]; “ wherein the traffic model includes multiple packet sizes and a distribution corresponding to the multiple packet sizes ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT ”)]; “ performing the Monte Carlo simulation based on the input, the traffic model, the number of packets to be run for each use case, and the seed value so as to generate a simulation result ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT ”, Malik et al. Pg. 4, sec. B Simulation results, 1 st – 2 nd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”, Table 1, Figs. 2-4)]; “ and determining a recommended configuration of processor cores for the data stack based on the simulation result .” as [Malik et al. (Pg. 4, sec B Simulation results, 1 st – 3 rd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”, etc., Fig. 3 and 4, The examiner considers the results from the proposed algorithm used in the Monte Carlo simulations to be the recommended configuration, since the results of the proposed algorithm gives a reduction in retransmissions)]; While Malik et al. teaches receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases, Malik et al. does not explicitly disclose “A method for a performance analysis on a data stack of a user equipment (UE); receiving an input for a Monte Carlo simulation, the input including a requirement for a processor specification, and a user-specified function” Zhao et al. discloses “ A method for a performance analysis on a data stack of a user equipment (UE) ” as [Zhao et al. (paragraph [0053] “ The operations described in this specification can be performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources. The term "data processing apparatus" or "computing device" encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations of the foregoing The apparatus can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC ”)]; “ receiving an input for a Monte Carlo simulation, the input including a requirement for a processor specification, and a user-specified function ” as [Zhao et al. (paragraph [0021] “ In other implementations, the failure generator 204 can receive user instructions for the generation of possible failures. For example, a user may- wish to run "what-if analysis" to determine the consequences if a specific failure occurs. In these cases, the user can indicate to the failure generator 204 which links and network devices should fail and how they should fail .”, Zhao et al. paragraph [0055] “ Processor s suitable for the execution of a computer program include, by way of example, both general and special purpose micro processor s, and any one or more processor s of any kind of computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both .”)]; Malik et al. and Zhao et al. are analogous art because they are from the same field endeavor of analyzing the traffic flows of signals within a network. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. of receiving an input for a Monte Carlo simulation, the input including a requirement for one or more use cases by incorporating a method for a performance analysis on a data stack of a user equipment (UE); receiving an input for a Monte Carlo simulation, the input including a requirement for a processor specification, and a user-specified function as taught by Zhao et al. for the purpose of determining traffic flow availability for a parallelized network. Malik et al. in view of Zhao et al. teaches a method for a performance analysis on a data stack of a user equipment (UE); receiving an input for a Monte Carlo simulation, the input including a requirement for a processor specification, and a user-specified function. The motivation for doing so would have been because Zhao et al. teaches that by determining traffic flow availability for a parallelized network, the ability to provide service at a level that the customer comfortable at can be accomplished. This allows for the network to provide accessible service (Zhao et al. paragraph [0002] – [0003]). With respect to claim 2 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Zhao et al. further discloses “ generating, prior to performing the Monte Carlo simulation, an instruction mapping for each of the one or more use cases ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Malik et al. discloses “ wherein the instruction mapping includes a total number of instructions (I) per second per component carrier .” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%), two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors), this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”)]; With respect to claim 3 , the combination of Malik et al. and Zhao et al. discloses the method of claim 2 above, and Malik et al. further discloses “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a maximum data rate (R) ” as [Malik et al. (Pg. 2, sec. 2A Interference Allowance, 1 st paragraph, “ The minimum overall data rate demand of each m th user of cell b in time-slot t can be mapped to the minimum data rate demand, R min m,b,t , in each time-slot t, allocated to that specific user. Furthermore, the minimum data rate demand in time-slot can be translate into a specific minimum required SINR, denoted by γ req m,b,t . ”, Malik et al. Pg. 3, sec. 3A Proposed Resource Allocation Scheme, 1 st paragraph, “ In the first step, the proposed algorithm initially assign the resource blocks to each user based on the rate/SINR required (γ req m,b,t ) by the user for the uplink transmission .”)]; “ a packet size (S) ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT .”)]; “ and a total number of component carriers (N) .” as [Malik et al. (Pg. 2, sec. 2A Interference Allowance, Fig. 1, The examiner considers the cells as the component carriers, since the instructions can be transmitted through them.)]; Zhao et al. discloses “ a number of instructions for the user specified function (A) ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; With respect to claim 5 , the combination of Malik et al. and Zhao et al. discloses the method of claim 2 above, and Zhao et al. further discloses “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A) ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Malik et al. discloses “ a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P) ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 1 st – 2 nd paragraph, “ For the performance analysis, we have considered a regular hexagonal multi-cell cellular network with three sectors in each cell and an inter-site distance of 500 m. The simulation assumption and parameters are derived from the 3GPP standard [14] as presented in Table I. The total frame transmission is assumed to be 10 ms with mini-slot of 1 ms. Each mini-slot consist of one PRB of 180 kHz, comprising of 12 subcarriers with 15 kHz subcarrier spacing. Furthermore, the retransmission factor is computed based on MCL for different coverage classes and presented in Figure 2 [11]. The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%), two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors), this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”)]; “ and a slot duration (T) .” as [Malik et al. (Pg. 4, subsection C Link Adaptation Parameter Selection, “ After the power allocation, the respective SINR of each user is determined and the corresponding MCL is calculated based on (1). With the MCL, the retransmission factor is selected along with the MCS. The algorithm then reassigns the time-slots along with the needed retransmissions. The detailed algorithm is listed in Algorithm 1 .”, Malik et al. (Pg. 4, sec. 4A, Simulation setup, 1 st paragraph, “ For the performance analysis, we have considered a regular hexagonal multi-cell cellular network with three sectors in each cell and an inter-site distance of 500 m. The simulation assumption and parameters are derived from the 3GPP standard [14] as presented in Table I. The total frame transmission is assumed to be 10 ms with mini-slot of 1 ms. Each mini-slot consist of one PRB of 180 kHz, comprising of 12 subcarriers with 15 kHz subcarrier spacing. Furthermore, the retransmission factor is computed based on MCL for different coverage classes and presented in Figure 2 [11]. ”)]; With respect to claim 7 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Malik et al. further discloses “ performing the Monte Carlo simulation based on the input and the traffic model until the number of packets to be run for each use case is reached .” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%), two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors), this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”, Malik et al. Pg. 4, sec B Simulation results, 1 st – 2 nd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”)]; With respect to claim 8 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Malik et al. further discloses “ determining, based on the simulation result, a total MIPS per component carrier ” as [Malik et al. (Pg. 4, sec. B Simulation results, 1 st – 3 rd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”, Figs. 3-5)]; “ and determining, based on the total MIPS per component carrier, a total number of MIPS ” as [Malik et al. (Pg. 4, sec. B Simulation results, 1 st – 3 rd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”, Figs. 3-5)]; Zhao et al. discloses “ and determining, based on the total MIPS per component carrier, a total cycles per second, and a total number of Million Cycles per Second (Mcps) .” as [Zhao et al. (paragraph [0031] “ In some implementations, as illustrated in Figure 3, the method 300 cycle s a predetermined number of times, generating and testing a new failure sample each cycle . Because the network can include SRLGs, different failures in the physical network can result m the same updated logical topology model In these instances, the network availability calculator can review the past cycle s to determine if a traffic engineering calculation has been calculated for the current logical topology model before proceeding to the next step of method 300, For example, if the network availability calculator determines the present failure sample results in a logical topology model analyzed in a previous cycle , the network availability calculator may memorialize the failure sample as having generated the same logical topology model as a previous cycle and return to step 308 of the method 300 to generate a new failure sample .”)]; With respect to claim 9 , the combination of Malik et al. and Zhao et al. discloses the method of claim 8 above, and Malik et al. further discloses “ determining the recommended configuration of processor cores for the data stack based on the total cycles per second, the total number of MIPS, and the total number of Mcps .” as [Malik et al. (Pg. 4, sec B Simulation results, 1 st – 3 rd paragraph, “ In this subsection, the performance of the proposed algorithm is investigated in both single-cell and multi-cell scenario with Monte-Carlo simulations. The performance evaluation in terms of average information rate and average latency with different penetration losses is presented and discussed in detail. With the simulation parameters presented in Table I, the simulations are run for uniformly distributed users for 500 iterations. The results are first generated for average information rate per sector with 25 dB penetration loss as shown in Figure 3. The results present a comparison of single-cell, multi-cell with RRS and multi-cell with IARR in-terms of average information rate. It can be seen that the impact of inter-cell interference is quite significant in a multi-cell environment. However, the proposed algorithm significantly improves the performance by mitigating the impact of inter-cell interference and improve the link reliability. ”, etc., Fig. 3 and 4)]; With respect to claim 10 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Malik et al. further discloses “ wherein the requirement for the one or more use cases includes a type of Radio Access Technology (RAT), a Maximum Data Rate (MDR), a SubCarrier Spacing (SCS), a number of Component Carriers (CCs), and/or a number of Logical Channels (LCs) .” as [Malik et al. (Pg. 1, right col., last paragraph “ This paper presents an interference-aware radio resource (IARR) allocation for uplink users with an aim to improve the signal-to-interference-ratio (SINR) and reduce the retransmissions .”, Malik et al. Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%) , two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors) , this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”, Having an interference-aware radio resource (IARR) demonstrates that there’s a Radio Access Technology (RAT), since RAT enables wireless communication between devices and a network and IARR monitors and mitigates signal disruption with a network)]; With respect to claim 13 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Zhao et al. further discloses “ wherein the user-specified function includes information indicating one or more of the following: a number of instructions to be executed ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data . Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Malik et al. discloses “ an execution frequency for the instructions to be executed ” as [Malik et al. (Pg. 4, Table 1, Frequency Band , With there being data transmitted and retransmitted demonstrates that there are instructions being executed, since the data is being transmitted to a particular location in the network)]; “ and/or information indicating that the instructions to be executed are downlink (DL) or uplink (UL) .” as [Malik et al. (Pg. 1, right col., last paragraph “ This paper presents an interference-aware radio resource (IARR) allocation for uplink users with an aim to improve the signal-to-interference-ratio (SINR) and reduce the retransmissions. ”, Malik et al. Pg. 2, sec. 2 Rate Maximization Problem Formulation, 2 nd paragraph, “ To improve the link reliability and reduce the retransmissions, it is crucial to improve the SINR of user in the presence of inter-cell interference with an appropriate resource allocation scheme. Therefore, in this paper, a multi-cell cellular network, where each cell comprises of three sectors, is studied and the focus is on the uplink transmission where user expect inter-cell interference from the neighboring cell uplink users in the same resource as shown in Figure 1 .”, Fig. 1)]; With respect to claim 14 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Zhao et al. further discloses “ wherein the user-specified function includes: a main-processor functional partition to be deployed on a data-plane main processor; a micro-controller functional partition to be deployed on a data-plane micro controller; and/or a data-plane-hardware (DPHW) functional partition to be deployed on data plane hardware .” as [Zhao et al. (paragraph [0051] “ Implementations of the subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware , including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them .”)]; With respect to claim 20 , Zhao et al. discloses “ A non-transitory, computer-readable medium having processor instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform a method ” as [Zhao et al. (paragraph [0005] “ According to another aspect of the disclosure, computer readable medium includes processor executable instructions. Execution of the processor executable instructions causes at least one processor to receive an indication of a physical topology, a logical topology, and a plurality of traffic demands .”)]; The other limitations of the claim recite the same substantive limitations as claim 1 above and are rejected using the same teachings. 07-21-aia AIA Claim (s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Malik et al. in view of Zhao et al. in further view of Vance et al. (KR 20160085691) (Translation). With respect to claim 11 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above, and Zhao et al. further discloses “ wherein the processor specification includes a number of main processors to be used for the one or more use cases .” as [Zhao et al. (paragraph [0055] “ Processor s suitable for the execution of a computer program include, by way of example, both general and special purpose micro processor s, and any one or more processor s of any kind of computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both .”)]; While the combination of Malik et al. and Zhao et al. teaches having a number of processors that are used for one or more use cases, Malik et al. and Zhao et al. do not explicitly disclose “wherein the processor specification includes a number of micro controllers to be used for the one or more use cases.” Vance et al. discloses “ wherein the processor specification includes a number of micro controllers to be used for the one or more use cases .” as [Vance et al. (Pg. 9, 5 th paragraph “ Now, an exemplary aspect of the system 100 will be described in more detail. In particular, FIG. 2shows a more detailed block diagram of an exemplary gauge adapter 120. For example, the input /output controller 128 may include a hardware interrupt data buffer 304, a RAM measurement buffer308, a CPU (or processor) 312 and a radio processor interface 316 And an application microcontroller 300 having a plurality of microcontrollers (not shown). The wireless network controller 124 may include an application-specific integrated circuit (ASIC) 320, a modem ASIC 324, and an antenna 326. The wireless processor ASIC 320 may include a microcontroller interface 328 , a processor 332 for encoding / decoding digital wireless packets (or frames), a data buffer 336, and a modem interface340 .”)]; Malik et al., Zhao et al. and Vance et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. and Zhao et al. of having a number of processors that are used for one or more use cases by incorporating wherein the processor specification includes a number of micro controllers to be used for the one or more use cases as taught by Vance et al. for the purpose of providing a method of communication for gauge measurement. Malik et al. in view of Zhao et al. in further view of Vance et al. teaches wherein the processor specification includes a number of micro controllers to be used for the one or more use cases. The motivation for doing so would have been because Vance et al. teaches that by providing a method of communication for gauge measurement, the ability to analyze communication signals of the wireless network can be accomplished. This allows for a way monitor the communication of the gauge measurements (Vance et al. Pg. 2, Background-Art, “In some cases, manufactured parts such as relatively large aircraft skins, etc.”, Pg. 2, Overview, 1 st – 2 nd paragraph, “Various embodiments are described below and illustrated in the associated drawings, etc.”) . 07-21-aia AIA Claim (s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Malik et al. in view of Zhao et al. in further view of online reference Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks, written by Josilo et al. With respect to claim 12 , the combination of Malik et al. and Zhao et al. discloses the method of claim 1 above. While the combination of Malik et al. and Zhao et al. teaches receiving an input for a Monte Carlo simulation where the input includes a requirement for a processor specification, Malik et al. and Zhao et al. do not explicitly disclose “wherein the processor specification includes: a clock rate; a local Cycles Per Instruction (CPI); an external CPI; and/or a processor load threshold.” Josilo et al. discloses “ wherein the processor specification includes: a clock rate; a local Cycles Per Instruction (CPI); an external CPI; and/or a processor load threshold .” as [Josilo et al. (Pg. 209, sec. 2.3.1, 1 st paragraph, “ In the case of local computing data need not be transmitted, but the task has to be processed using local computing power. We consider that the expected time it takes to complete MU i’s task locally consists of two parts [19]. The first part is the expected CPU execution time T 0iexe = L i CPI i *CC i , where CPI i and CC i are the average number of cycles per instruction and the clock cycle time, respectively, etc .”)]; Malik et al., Zhao et al. and Josilo et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. and Zhao et al. of receiving an input for a Monte Carlo simulation where the input includes a requirement for a processor specification by incorporating wherein the processor specification includes: a clock rate; a local Cycles Per Instruction (CPI); an external CPI; and/or a processor load threshold as taught by Josilo et al. for the purpose of having mobile devices to offload computations through multiple access points or through the base station to a mobile cloud. Malik et al. in view of Zhao et al. in further view of Josilo et al. teaches wherein the processor specification includes: a clock rate; a local Cycles Per Instruction (CPI); an external CPI; and/or a processor load threshold. The motivation for doing so would have been because Josilo et al. teaches that by having mobile devices to offload computations through multiple access points or through the base station to a mobile cloud, the ability to minimize computation costs can be accomplished. This allows for a way reduce slow response times and be more affordable (Joslio et al. Abstract, “ In this paper, we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs ”, Pg. 207, Introduction, 1 st – 2 nd paragraph, “ Mobile handsets are increasingly used for various computationally intensive, etc .”). Claim(s) 4, 6, 15 and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over online reference in view of Malik et al. in view of Zhao et al. in further view of online reference Design of Fire Detection System in Buildings based on Wireless Multimedia Sensor Networks, written by Wei et al. With respect to claim 4 , the combination of Malik et al. and Zhao et al. discloses the method of claim 3 above. While Malik et al. and Zhao et al. teaches the total number of instructions (I) per second per component carrier is calculated based on: a maximum data rate (R), a packet size (S), a number of instructions for the user specified function (A) and a total number of component carriers (N), Malik et al. and Zhao et al. do not explicitly disclose “wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N).” Wei et al. discloses “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N) .” as [Wei et al. (Pg. 3009, sec. 3A Data acquisition and processing module, 2 nd – 3 rd paragraph, “ 1) Microprocessor: Because the module needs to process images for fire image detection, thus it requires a microprocessor with powerful calculating ability. We adopt the DSP chip TMS320C6205, produced by Texas Instruments, as the microprocessor. With performance of up to 1600 million instructions per second at a clock rate of 200 MHz, the TMS320C6205 offers cost-effective solutions to high-performance DSP programming challenges. The TMS320C6205 DSP possesses the operational flexibility of high-speed controllers and the numerical capability of array processors .”, Fig. 2, The Wei et al, reference teaches that up to 1600 million instructions per second can be used. This demonstrates that there’s a number of instructions per second that are being calculated)]; Malik et al., Zhao et al. and Wei et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. and Zhao et al. of the total number of instructions (I) per second per component carrier is calculated based on: a maximum data rate (R), a packet size (S), a number of instructions for the user specified function (A) and a total number of component carriers (N) by incorporating wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N) as taught by Wei et al. for the purpose of detecting a suspicious fire area in a building. Malik et al. in view of Zhao et al. in further view of Wei et al. teaches wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N). The motivation for doing so would have been because Wei et al. teaches that by transferring images of suspicious fire areas through a wireless network, the ability to detect a fire within a building more quickly can be accomplished. This allows a way to alert a fire more efficiently and quickly (Wei et al. Pg. 3008, sec. 1 Introduction 1 st – 3 rd paragraph, “Fire prevention has long been a research hotspot in building security area, etc.”). With respect to claim 6 , the combination of Malik et al. and Zhao et al. discloses the method of claim 5 above. While Malik et al. and Zhao et al. teaches the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A), a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P), and a slot duration (T), Malik et al. and Zhao et al. do not explicitly disclose “wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T).” Wei et al. discloses “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T) .” as [Wei et al. (Pg. 3009, sec. 3A Data acquisition and processing module, 2 nd – 3 rd paragraph, “ 1) Microprocessor: Because the module needs to process images for fire image detection, thus it requires a microprocessor with powerful calculating ability. We adopt the DSP chip TMS320C6205, produced by Texas Instruments, as the microprocessor. With performance of up to 1600 million instructions per second at a clock rate of 200 MHz, the TMS320C6205 offers cost-effective solutions to high-performance DSP programming challenges. The TMS320C6205 DSP possesses the operational flexibility of high-speed controllers and the numerical capability of array processors .”, Fig. 2, The Wei et al, reference teaches that up to 1600 million instructions per second can be used. This demonstrates that there’s a number of instructions per second that are being calculated)]; Malik et al., Zhao et al. and Wei et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. and Zhao et al. of the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A), a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P), and a slot duration (T) by incorporating wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T) as taught by Wei et al. for the purpose of detecting a suspicious fire area in a building. Malik et al. in view of Zhao et al. in further view of Wei et al. teaches wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T). The motivation for doing so would have been because Wei et al. teaches that by transferring images of suspicious fire areas through a wireless network, the ability to detect a fire within a building more quickly can be accomplished. This allows a way to alert a fire more efficiently and quickly (Wei et al. Pg. 3008, sec. 1 Introduction 1 st – 3 rd paragraph, “Fire prevention has long been a research hotspot in building security area, etc.”). With respect to claim 15 , Wei et al. discloses “ An apparatus for performing a Million Instructions per Second (MIPS) analysis for a data stack of a user equipment (UE) ” as [Wei et al. (Pg. 3009, sec. 3A Data acquisition and processing module, 2 nd – 3 rd paragraph, “ 1) Microprocessor: Because the module needs to process images for fire image detection, thus it requires a microprocessor with powerful calculating ability. We adopt the DSP chip TMS320C6205, produced by Texas Instruments, as the microprocessor. With performance of up to 1600 million instructions per second at a clock rate of 200 MHz, the TMS320C6205 offers cost-effective solutions to high-performance DSP programming challenges. The TMS320C6205 DSP possesses the operational flexibility of high-speed controllers and the numerical capability of array processors .”, Fig. 2)]; Malik et al., Zhao et al. and Wei et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al. and Zhao et al. of having a method for a performance analysis on a data stack of a user equipment (UE) by incorporating an apparatus for performing a Million Instructions per Second (MIPS) analysis for a data stack of a user equipment (UE) as taught by Wei et al. for the purpose of detecting a suspicious fire area in a building. Malik et al. in view of Zhao et al. in further view of Wei et al. teaches an apparatus for performing a Million Instructions per Second (MIPS) analysis for a data stack of a user equipment (UE). The motivation for doing so would have been because Wei et al. teaches that by transferring images of suspicious fire areas through a wireless network, the ability to detect a fire within a building more quickly can be accomplished. This allows a way to alert a fire more efficiently and quickly (Wei et al. Pg. 3008, sec. 1 Introduction 1 st – 3 rd paragraph, “Fire prevention has long been a research hotspot in building security area, etc.”). The other limitations of the claim recite the same substantive limitations of claim 1 above and are rejected using the same teachings. With respect to claim 17 , the combination of Malik et al., Zhao et al. and Wei et al. discloses the apparatus of claim 15 above, and Zhao et al. further discloses “ wherein the processor is further configured to: generate, prior to performing the Monte Carlo simulation, an instruction mapping for each of the one or more use cases ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Malik et al. discloses “ wherein the instruction mapping includes a total number of instructions (I) per second per component carrier .” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%), two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors), this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”)]; With respect to claim 18 , the combination of Malik et al., Zhao et al. and Wei et al. discloses the apparatus of claim 17 above, and Malik et al. further discloses “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a maximum data rate (R) ” as [Malik et al. (Pg. 2, sec. 2A Interference Allowance, 1 st paragraph, “ The minimum overall data rate demand of each m th user of cell b in time-slot t can be mapped to the minimum data rate demand, R min m,b,t , in each time-slot t, allocated to that specific user. Furthermore, the minimum data rate demand in time-slot can be translate into a specific minimum required SINR, denoted by γ req m,b,t . ”, Malik et al. Pg. 3, sec. 3A Proposed Resource Allocation Scheme, 1 st paragraph, “ In the first step, the proposed algorithm initially assign the resource blocks to each user based on the rate/SINR required (γ req m,b,t ) by the user for the uplink transmission .”)]; “ a packet size (S) ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT .”)]; “ and a total number of component carriers (N) .” as [Malik et al. (Pg. 2, sec. 2A Interference Allowance, Fig. 1, The examiner considers the cells as the component carriers, since the instructions can be transmitted through them.)]; Zhao et al. discloses “ a number of instructions for the user specified function (A) ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Wei et al. discloses “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*R) / (S*N) .” as [Wei et al. (Pg. 3009, sec. 3A Data acquisition and processing module, 2 nd – 3 rd paragraph, “ 1) Microprocessor: Because the module needs to process images for fire image detection, thus it requires a microprocessor with powerful calculating ability. We adopt the DSP chip TMS320C6205, produced by Texas Instruments, as the microprocessor. With performance of up to 1600 million instructions per second at a clock rate of 200 MHz, the TMS320C6205 offers cost-effective solutions to high-performance DSP programming challenges. The TMS320C6205 DSP possesses the operational flexibility of high-speed controllers and the numerical capability of array processors .”, Fig. 2, The Wei et al, reference teaches that up to 1600 million instructions per second can be used. This demonstrates that there’s a number of instructions per second that are being calculated)]; With respect to claim 19 , the combination of Malik et al., Zhao et al. and Wei et al. discloses the apparatus of claim 17 above, and Zhao et al. further discloses “ wherein the total number of instructions (I) per second per component carrier is calculated based on: a number of instructions for the user specified function (A) ” as [Zhao et al. (paragraph [0055] “ Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks .”)]; Malik et al. discloses “ a number of sub Protocol Data Unit of Media Access Control (MacSubPDUs) per slot, per component carrier (P) ” as [Malik et al. (Pg. 4, sec. 4A, Simulation setup, 1 st – 2 nd paragraph, “ For the performance analysis, we have considered a regular hexagonal multi-cell cellular network with three sectors in each cell and an inter-site distance of 500 m. The simulation assumption and parameters are derived from the 3GPP standard [14] as presented in Table I. The total frame transmission is assumed to be 10 ms with mini-slot of 1 ms. Each mini-slot consist of one PRB of 180 kHz, comprising of 12 subcarriers with 15 kHz subcarrier spacing. Furthermore, the retransmission factor is computed based on MCL for different coverage classes and presented in Figure 2 [11]. The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%), two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors), this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”)]; “ and a slot duration (T) .” as [Malik et al. (Pg. 4, subsection C Link Adaptation Parameter Selection, “ After the power allocation, the respective SINR of each user is determined and the corresponding MCL is calculated based on (1). With the MCL, the retransmission factor is selected along with the MCS. The algorithm then reassigns the time-slots along with the needed retransmissions. The detailed algorithm is listed in Algorithm 1 .”, Malik et al. (Pg. 4, sec. 4A, Simulation setup, 1 st paragraph, “ For the performance analysis, we have considered a regular hexagonal multi-cell cellular network with three sectors in each cell and an inter-site distance of 500 m. The simulation assumption and parameters are derived from the 3GPP standard [14] as presented in Table I. The total frame transmission is assumed to be 10 ms with mini-slot of 1 ms. Each mini-slot consist of one PRB of 180 kHz, comprising of 12 subcarriers with 15 kHz subcarrier spacing. Furthermore, the retransmission factor is computed based on MCL for different coverage classes and presented in Figure 2 [11]. ”)]; Wei et al. discloses “ wherein the total number of instructions per second per component carrier (I) is calculated based on the following equation: I = (A*P) / (T) .” as [Wei et al. (Pg. 3009, sec. 3A Data acquisition and processing module, 2 nd – 3 rd paragraph, “ 1) Microprocessor: Because the module needs to process images for fire image detection, thus it requires a microprocessor with powerful calculating ability. We adopt the DSP chip TMS320C6205, produced by Texas Instruments, as the microprocessor. With performance of up to 1600 million instructions per second at a clock rate of 200 MHz, the TMS320C6205 offers cost-effective solutions to high-performance DSP programming challenges. The TMS320C6205 DSP possesses the operational flexibility of high-speed controllers and the numerical capability of array processors .”, Fig. 2, The Wei et al, reference teaches that up to 1600 million instructions per second can be used. This demonstrates that there’s a number of instructions per second that are being calculated)]; 07-21-aia AIA Claim (s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over online reference in view of Malik et al. in view of Zhao et al. in further view of Wei et al. in further view of Vance et al. (KR 20160085691) (Translation). With respect to claim 16 , the combination of Malik et al., Zhao et al. and Wei et al. discloses the apparatus of claim 15 above, and Malik et al. further discloses “ wherein: the requirement for the one or more use cases includes a type of Radio Access Technology (RAT), a Maximum Data Rate (MDR), a SubCarrier Spacing (SCS), a number of Component Carriers (CCs), and/or a number of Logical Channels (LCs) ” as [Malik et al. (Pg. 1, right col., last paragraph “ This paper presents an interference-aware radio resource (IARR) allocation for uplink users with an aim to improve the signal-to-interference-ratio (SINR) and reduce the retransmissions .”, Malik et al. Pg. 4, sec. 4A, Simulation setup, 2 nd paragraph, “ The traffic of each user is modeled according to the 3GPP standard [14] annex E, Mobile Autonomous Reporting (MAR) periodic traffic model. the traffic model is characterized as follows: • Pareto distributed application payload size with alpha having a value of 2.5 and beta with a minimum and maximum value of 20 bytes and 200 bytes, respectively, is considered. As in IoT use-cases, reports are usually not very large in size. We assumed three different packet sizes of 27, 35 and 50 bytes with the percentage of 50%, 75%, and 90%. The men size is of 32 bytes. The assumption follows the parameters provided in Nokia evaluation document for NB-IoT . • The arrival time of packets from different users are distributed into various categories with constant inter-arrival time and device proportion of one day (40%) , two hours (40%), one hour (15%) and 30 minutes (5%) as in. Considering, 52 K devices per cell and the network of seven cells (each with three sectors) , this will lead to 21 cells in total and gives 143 reports per second per network as calculated in .”, Having an interference-aware radio resource (IARR) demonstrates that there’s a Radio Access Technology (RAT), since RAT enables wireless communication between devices and a network and IARR monitors and mitigates signal disruption with a network)]; Zhao et al. discloses “ and the user specified function includes (i) a main-processor functional partition to be deployed on a data-plane main processor, (ii) a micro-controller functional partition to be deployed on a data-plane micro controller, and/or (iii) a data-plane-hardware (DPHW) functional partition to be deployed on data plane hardware .” as [Zhao et al. (paragraph [0051] “ Implementations of the subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware , including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them .”)]; While the combination of Malik et al., Zhao et al. and Wei et al. teaches having a number of processors that are used for one or more use cases, Malik et al., Zhao et al. and Wei et al. do not explicitly disclose “the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases” Vance et al. discloses “ the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases ” as [Vance et al. (Pg. 9, 5 th paragraph “ Now, an exemplary aspect of the system 100 will be described in more detail. In particular, FIG. 2shows a more detailed block diagram of an exemplary gauge adapter 120. For example, the input /output controller 128 may include a hardware interrupt data buffer 304, a RAM measurement buffer308, a CPU (or processor) 312 and a radio processor interface 316 And an application microcontroller 300 having a plurality of microcontrollers (not shown). The wireless network controller 124 may include an application-specific integrated circuit (ASIC) 320, a modem ASIC 324, and an antenna 326. The wireless processor ASIC 320 may include a microcontroller interface 328 , a processor 332 for encoding / decoding digital wireless packets (or frames), a data buffer 336, and a modem interface340 .”)]; Malik et al., Zhao et al., Wei et al. and Vance et al. are analogous art because they are from the same field endeavor of analyzing the transmission and receiving of communication signals. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art to modify the teachings of Malik et al., Zhao et al. and Wei et al. of having a number of processors that are used for one or more use cases by incorporating the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases as taught by Vance et al. for the purpose of providing a method of communication for gauge measurement. Malik et al. in view of Zhao et al. in further view of Wei et al. in further view of Vance et al. teaches the processor specification includes a number of main processors to be used and a number of micro controllers to be used for the one or more use cases. The motivation for doing so would have been because Vance et al. teaches that by providing a method of communication for gauge measurement, the ability to analyze communication signals of the wireless network can be accomplished. This allows for a way monitor the communication of the gauge measurements (Vance et al. Pg. 2, Background-Art, “In some cases, manufactured parts such as relatively large aircraft skins, etc.”, Pg. 2, Overview, 1 st – 2 nd paragraph, “Various embodiments are described below and illustrated in the associated drawings, etc.”) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The relevance of MacNaughtan et al (U.S. PGPub 2013/0211706) is estimating the speed of a mobile radio terminal traveling on at least one road segment . The relevance of online reference Full-System Analysis and Characterization of Interactive Smartphone Applications, written by Gutierrez et al. teaches characterizing the microarchitectural behavior of representative smartphone applications on a current generation mobile platform to identify trends that might impact future designs. Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD E COTHRAN whose telephone number is (571)270-5594. The examiner can normally be reached 9AM -5:30PM EST M-F. 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, Ryan F Pitaro can be reached at (571)272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /BERNARD E COTHRAN/Examiner, Art Unit 2188 /RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188 Application/Control Number: 18/066,222 Page 2 Art Unit: 2188 Application/Control Number: 18/066,222 Page 3 Art Unit: 2188 Application/Control Number: 18/066,222 Page 4 Art Unit: 2188 Application/Control Number: 18/066,222 Page 5 Art Unit: 2188 Application/Control Number: 18/066,222 Page 6 Art Unit: 2188 Application/Control Number: 18/066,222 Page 7 Art Unit: 2188 Application/Control Number: 18/066,222 Page 8 Art Unit: 2188 Application/Control Number: 18/066,222 Page 9 Art Unit: 2188 Application/Control Number: 18/066,222 Page 10 Art Unit: 2188 Application/Control Number: 18/066,222 Page 11 Art Unit: 2188 Application/Control Number: 18/066,222 Page 12 Art Unit: 2188 Application/Control Number: 18/066,222 Page 13 Art Unit: 2188 Application/Control Number: 18/066,222 Page 14 Art Unit: 2188 Application/Control Number: 18/066,222 Page 15 Art Unit: 2188 Application/Control Number: 18/066,222 Page 16 Art Unit: 2188 Application/Control Number: 18/066,222 Page 17 Art Unit: 2188 Application/Control Number: 18/066,222 Page 18 Art Unit: 2188 Application/Control Number: 18/066,222 Page 19 Art Unit: 2188 Application/Control Number: 18/066,222 Page 20 Art Unit: 2188 Application/Control Number: 18/066,222 Page 21 Art Unit: 2188 Application/Control Number: 18/066,222 Page 22 Art Unit: 2188 Application/Control Number: 18/066,222 Page 23 Art Unit: 2188 Application/Control Number: 18/066,222 Page 24 Art Unit: 2188 Application/Control Number: 18/066,222 Page 25 Art Unit: 2188 Application/Control Number: 18/066,222 Page 26 Art Unit: 2188 Application/Control Number: 18/066,222 Page 27 Art Unit: 2188 Application/Control Number: 18/066,222 Page 28 Art Unit: 2188 Application/Control Number: 18/066,222 Page 29 Art Unit: 2188 Application/Control Number: 18/066,222 Page 30 Art Unit: 2188 Application/Control Number: 18/066,222 Page 31 Art Unit: 2188 Application/Control Number: 18/066,222 Page 32 Art Unit: 2188 Application/Control Number: 18/066,222 Page 33 Art Unit: 2188 Application/Control Number: 18/066,222 Page 34 Art Unit: 2188 Application/Control Number: 18/066,222 Page 35 Art Unit: 2188 Application/Control Number: 18/066,222 Page 36 Art Unit: 2188 Application/Control Number: 18/066,222 Page 37 Art Unit: 2188 Application/Control Number: 18/066,222 Page 39 Art Unit: 2188 Application/Control Number: 18/066,222 Page 41 Art Unit: 2188 Application/Control Number: 18/066,222 Page 42 Art Unit: 2188 Application/Control Number: 18/066,222 Page 43 Art Unit: 2188 Application/Control Number: 18/066,222 Page 44 Art Unit: 2188 Application/Control Number: 18/066,222 Page 45 Art Unit: 2188 Application/Control Number: 18/066,222 Page 46 Art Unit: 2188 Application/Control Number: 18/066,222 Page 47 Art Unit: 2188 Application/Control Number: 18/066,222 Page 48 Art Unit: 2188 Application/Control Number: 18/066,222 Page 49 Art Unit: 2188 Application/Control Number: 18/066,222 Page 50 Art Unit: 2188 Application/Control Number: 18/066,222 Page 51 Art Unit: 2188 Application/Control Number: 18/066,222 Page 52 Art Unit: 2188 Application/Control Number: 18/066,222 Page 53 Art Unit: 2188 Application/Control Number: 18/066,222 Page 54 Art Unit: 2188 Application/Control Number: 18/066,222 Page 55 Art Unit: 2188 Application/Control Number: 18/066,222 Page 56 Art Unit: 2188
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