Framework for constructing the dependency graph for open ran conflict detection

Abstract

Embodiments of the disclosure describe a method is disclosed. The method includes receiving a plurality of control parameters from a plurality of applications. The plurality of applications is associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture. The method further includes generating, based on the plurality of received control parameters, one or more dependency graphs. The method further includes determining, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

Description

PCT / US25 / 14547 05 February 2025 (05.02.2025)FRAMEWORK FOR CONSTRUCTING THE DEPENDENCY GRAPH FOR OPEN RAN CONFLICT DETECTIONCROSS REFERENCE TO RELATED APPLICATION(S)

[0001] This application claims priority based on India Patent Application No. 202411075768, filed October 7, 2024 in the Indian Patent Office, the entire disclosure of which is incorporated herein by reference.FIELD

[0002] The present disclosure relates to the framework for constructing the dependency graph for Open Radio Access Network (RAN) conflict detection.BACKGROUND

[0003] The information disclosed in this background section is only for enhancement of understanding of the general background of the disclosure and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

[0004] In Open Radio Access Network (O-RAN) architecture, a RAN Intelligent Controller (RIC) serves as a crucial component for enhancing network performance and facilitating intelligent resource management. The RIC is categorized into two main platforms, based on their operational time scales, such as a Near-Real-Time RIC (near-RT RIC) and a Non- Real-Time RIC (non-RT RIC). The non-RT RIC operates on a time scale exceeding one second and serves as a host for one or more resource applications (rApps). In contrast, the near-RT RIC functions within a sub-second to one-second time frame and accommodates one or more execution applications (xApps).

[0005] The input to the one or more rApps generally comprises comprehensive network- wide data, outputs from Artificial Intelligence and Machine Learning (AI / ML) models manifestingPCT / US25 / 14547 05 February 2025 (05.02.2025) as recommendations or predictions and operator-defined policies. The outputs generated by the one or more rApps include configuration modifications communicated via an 01 interface and policy recommendations directed to the near-RT RIC through an Al interface.

[0006] Conversely, the one or more xApps receive inputs primarily consisting of real-time network data, policy directives from the non-RT RIC, and outputs from the AI / ML models. The operational output of the one or more xApps consists of control and optimization commands that are transmitted directly to one or more Radio Access Network (RAN) nodes over an E2 interface.

[0007] Given the concurrent operation of multiple rApps and xApps, there exists a potential for conflicting outputs from these applications. Such conflicts could result in system instability or degradation of performance, necessitating robust conflict resolution mechanisms to ensure seamless integration and functionality within the network architecture.SUMMARY

[0008] This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the disclosure. This summary is neither intended to identify key or essential inventive concepts of the disclosure nor is it intended for determining the scope of the disclosure.

[0009] According to one embodiment of the present disclosure, a method is disclosed. The method includes receiving a plurality of control parameters from a plurality of applications. The plurality of applications is associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture. The method further includes generating, based on the plurality of received control parameters, one or more dependency graphs. The method further includes determining, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0010] According to one embodiment of the present disclosure, an apparatus is disclosed. The apparatus is configured to receive a plurality of control parameters from a plurality of applications. The plurality of applications is associated with at least one of a non-real-time RANPCT / US25 / 14547 05 February 2025 (05.02.2025)Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture. The apparatus is further configured to generate, based on the plurality of received control parameters, one or more dependency graphs. The apparatus is further configured to determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0011] According to one embodiment of the present disclosure, a non-transitory computer- readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by an apparatus, the apparatus comprising one or more processors. The one or more processors are configured to receive a plurality of control parameters from a plurality of applications. The plurality of applications is associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture. The one or more processors are further configured to generate, based on the plurality of received control parameters, one or more dependency graphs. The one or more processors are further configured to determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0012] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the disclosure and are therefore not to be considered limiting of its scope. The disclosure will be described and explained with additional specificity and detail in the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Features, aspects, and advantages of embodiments of the disclosure will be described below with reference to the accompanying drawings, in which like reference numerals denote like elements, and wherein:PCT / US25 / 14547 05 February 2025 (05.02.2025)FIG. 1 illustrates a method for constructing a dependency graph for an Open Radio Access Network (ORAN) conflict detection, according to an embodiment as disclosed herein;FIG. 2 illustrates a functional dependency graph, according to an embodiment as disclosed herein;FIG. 3 illustrates a Key Performance Indicator (KPI)-based dependency graph, according to an embodiment as disclosed herein;FIG. 4 illustrates an example scenario for determining one or more conflicts among the plurality of applications by utilizing the functional dependency graph, according to an embodiment as disclosed herein;FIG. 5 illustrates an example scenario for determining the one or more conflicts among the plurality of applications by utilizing the KPI-based dependency graph, according to an embodiment as disclosed herein;FIG. 6 is a flow diagram illustrating a method for determining the one or more conflicts among the plurality of applications based on one or more generated dependency graphs, according to an embodiment as disclosed herein; andFIG. 7 illustrates a diagram of example components of an apparatus, according to an embodiment as disclosed herein.DETAILED DESCRIPTION

[0014] The following detailed description of example embodiments refers to the accompanying drawings. The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. Further, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). Additionally, the flowchart and description of operations provided below relate to one of the various embodiments. It should be noted that it is possible to make other embodiments that do not exactly match the flowchart and its description. It is understood that inPCT / US25 / 14547 05 February 2025 (05.02.2025) other embodiments one or more operations may be omitted, one or more operations may be added, one or more operations may be performed simultaneously (at least in part).

[0015] It will be apparent that systems and / or methods, described herein, may be implemented in different forms of hardware, software, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It is understood that software and hardware may be designed to implement the systems and / or methods based on the description herein.

[0016] Even though particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of implementations includes each dependent claim in combination with every other claim in the claim set.

[0017] No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items, and may be used interchangeably with “one or more.” Also, as used herein, the terms “has,” “have,” “having,” “include,” “including,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Furthermore, expressions such as “at least one of [A] and [B],” “[A] and / or [B],” or “at least one of [A] or [B]” are to be understood as including only A, only B, or both A and B.

[0018] The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations.

[0019] Certain existing mechanisms explore the use of Conflict Detection and Mitigation functionality (ConMit functionality) or a Conflict Detection and Mitigation Framework (CDMF).PCT / US25 / 14547 05 February 2025 (05.02.2025)This functionality can be integrated into Non-RT RIC platforms, Near-RT RIC platforms, or implemented as helper rApps or xApps. The ConMit or CDMF’s main goal is to ensure that the actions of xApps and rApps do not conflict with each other or with operator-defined policies. The CDMF includes three key procedures, which are given below. a. Conflict detection, which identifies potential and actual conflicts (direct, indirect, or implicit); b. Conflict resolution, which addresses ongoing conflicts beyond just enabling or disabling xApps; and c. Conflict avoidance, which guides to help xApps prevent future conflicts.

[0020] However, several challenges are encountered in the ConMit functionality / CDMF, which are mentioned herein. Existing ConMit functionality is not easily adaptable for future enhancements and fails to effectively track different types of conflicts. Integrating the CDMF into existing 0-RAN architectures adds complexity, increasing design and development costs and timelines. Additionally, the extra processing layer may introduce latency in handling RAN control messages, affecting the near-real-time capabilities needed for time-sensitive applications. As the number of xApps increases, scalability issues may arise, leading to performance bottlenecks in conflict detection and resolution. The effectiveness of implicit conflict detection relies on accurate performance monitoring data; any inaccuracies can result in undetected conflicts, harming network performance. Furthermore, adding more components can increase resource consumption, impacting overall RIC and network efficiency. Variability in implementation across different 0- RAN deployments may lead to inconsistent performance due to a lack of standardized conflict detection and resolution methods. Consequently, there is a need for an alternative solution, which is elaborated upon throughout the disclosure.

[0021] In one or more embodiments, in response to the challenges identified in the existing ConMit functionality / CDMF, the disclosed method focuses on enhancing conflict detection through the implementation of a dependency graph, also referred to as a conflict detection matrix, as described in conjunction with FIG. 1 to FIG. 7. This dependency graph approach aims to effectively identify direct, indirect, and implicit conflicts among the rApps and xApps. The disclosed method involves using one or more outputs generated by the rApps and xApps as inputsPCT / US25 / 14547 05 February 2025 (05.02.2025) to the dependency graph. By mapping these one or more outputs, the disclosed method may systematically analyze one or more relationships and dependencies between different applications. This dependency graph approach facilitates the detection of potential conflicts, where actions taken by one application may negatively impact another or violate operator-defined policies. The disclosed method emphasizes the construction of a clear and manageable dependency graph. The design allows for easy addition of new applications and features without major changes. Such flexibility proves crucial for supporting ongoing improvements. Maintaining relevance as technology advances becomes possible through this dependency graph approach.

[0022] Implementing this dependency graph approach directly addresses several challenges faced by the existing ConMit functionality / CDMF. The disclosed method provides a robust mechanism for tracking various types of conflicts, which is currently insufficient. Additionally, the structured design of the dependency graph may simplify integration with existing 0-RAN architectures, potentially mitigating complexity and associated costs. Furthermore, as the number of rApps and xApps increases, the dependency graph may scale accordingly, allowing for efficient conflict detection without the performance bottlenecks observed in traditional mechanisms. This scalability is crucial for preserving the near-real-time capabilities essential for time-sensitive applications.

[0023] Referring now to the drawings, and more particularly to FIGS. 1 to 7, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.

[0024] FIG. 1 illustrates a method 100 for constructing a dependency graph for an Open Radio Access Network (ORAN) conflict detection, according to an embodiment as disclosed herein. The method 100 may execute multiple operations to construct the dependency graph for the ORAN conflict detection, which are given below. In other words, FIG.1 illustrates a framework for constructing the dependency graph.

[0025] At operation 101, the method 100 includes receiving a plurality of control parameters from a plurality of applications (e.g., 101a,...., lOln). Examples of the control parameters may include, but are not limited to, one or more 01 parameters, one or more E2 parameters, and one or more Al policy parameters. The plurality of applications (e.g., 101a,....,PCT / US25 / 14547 05 February 2025 (05.02.2025)10 In) is associated with at least one of a non-real-time RAN Intelligent Controller (non-RT RIC) and a near-real-time RIC (near-RT RIC) of an Open Radio Access Network (ORAN) architecture. The non-RT RIC is primarily responsible for long-term optimization strategies, utilizing data analytics and machine learning techniques to enhance network performance over extended periods. Conversely, the near-RT RIC operates with lower latency requirements, facilitating real-time adjustments and optimizations based on immediate network conditions. The applications from which these control parameters are derived include, but are not limited to, Non-real-time applications (rApps), which focus on strategic network management and resource allocation, and Near-real-time applications (xApps), which emphasize rapid decision-making and dynamic resource management in response to fluctuating network demands.

[0026] For instance, consider a scenario where a streaming service provider utilizes both rApps and xApps within the ORAN architecture. The non-RT RIC receives control parameters from the rApps that analyze user engagement metrics and long-term bandwidth consumption trends. These control parameters might indicate a growing demand for high-definition content during peak hours. Simultaneously, the near-RT RIC receives real-time data from xApps that monitor current network load and user experience metrics.

[0027] In one or more embodiments, the method 100 includes receiving the one or more 01 parameters associated with the rApps. Subsequently, these 01 parameters are transmitted to southbound RAN nodes via an 01 interface for dynamic cell configuration optimization. For instance, consider a scenario where the rApp monitors user density and traffic patterns. It collects the one or more 01 parameters related to user demand and network load. These parameters are sent to southbound RAN nodes, which dynamically adjust cell configurations such as sectorization and power levels to accommodate increased traffic during peak hours, ensuring optimal network performance and user experience.

[0028] In one or more embodiments, the method 100 includes receiving the one or more E2 parameters related to the xApps. These E2 parameters are then communicated to RAN nodes through an E2 interface to dynamically configure functionalities of at least one of an ORAN Centralized Unit (O-CU) and an ORAN Distributed Unit (0-DU). For instance, consider a scenario where the xApp analyzes real-time video streaming demands from attendees. It receives E2PCT / US25 / 14547 05 February 2025 (05.02.2025) parameters indicating current bandwidth usage and user experience metrics. This data is transmitted to the RAN nodes via the E2 interface, enabling adjustments in the O-CU and O-DU functionalities, such as prioritizing bandwidth for streaming services, thereby enhancing the viewing experience for users.

[0029] In one or more embodiments, the method 100 includes receiving the one or more Al policy parameters from the non-real-time RIC, which are subsequently forwarded to the near- real-time RIC. These policies are transmitted via an Al interface to manage the O-CU and O-DU functionalities. For instance, consider a scenario where the non-real-time RIC analyzes historical data to establish Al policy parameters for resource allocation during different times of the day. These Al policy parameters are forwarded to the near-real-time RIC, which utilizes the Al interface to implement one or more policies (a set of rules or guidelines). For instance, during high-demand periods, the policies may dictate that specific resources be allocated to critical applications, such as emergency services, ensuring reliable communication when it matters most.

[0030] In one or more embodiments, the method 100 includes receiving various control parameters from multiple applications, which may represent potential sources of conflict. Consider a scenario where multiple applications operate simultaneously. For instance, a traffic management xApp collects real-time data to optimize traffic flow, while a video streaming rApp monitors user engagement to ensure high-quality streaming. The traffic management xApp may require additional bandwidth during peak hours for emergency vehicle routing, while the video streaming rApp seeks to maintain high-definition video quality for users. The competing demands for network resources can create a conflict, as described in conjunction with FIG. 4 and FIG. 5.

[0031] At operation 102, the method 100 includes generating, by a dependency graph generator, one or more dependency graphs based on the plurality of received control parameters. The one or more dependency graphs as a pre-configured or auto-generated conflict detection matrix that correlates the plurality of the identified control parameters with a corresponding plurality of identified possible system impacts. Examples of the one or more dependency graphs may include a functional dependency graph and a Key Performance Indicator (KPI)-based dependency graph, as illustrated in FIG. 2 and FIG. 3. To generate the one or more dependency graphs, the method 100 may execute multiple operations, which are given below.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0032] At operations 103, 104, and 105, the method 100 includes identifying a plurality of possible system impacts caused by one or more changes in the configuration of a network associated with the plurality of control parameters. The method 100 further includes categorizing the plurality of identified possible system impacts based on a nature of system impact into at least one of one or more functional Areas of Influence (Aol) and one or more Key Performance Indicator (KPI)-based Aol. The method 100 further includes identifying a plurality of the control parameters causing the plurality of identified possible system impacts. The method 100 further includes categorizing the plurality of the identified control parameters into predefined parameter groups based on parameter characteristics. Examples of the parameter characteristics may include, but are not limited to, cell configuration parameters, handover (HO) parameters, cell coverage parameters, cell-edge parameters, and cell-resource parameters.

[0033] In the context of the dependency graph, the disclosed method 100 categorizes control parameters into several distinct classifications (e.g., 103a,..., 103n), for example, which are given below. Collectively, these classifications provide a comprehensive framework for understanding how various control parameters influence cellular network operations and performance. a. The cell configuration parameters encompass essential identifiers such as Physical Cell Identifier (PCI) and Radio Source Identifier (RSI), which are critical for the operational integrity of the cellular network. b. The handover(HO) parameters are identified as those variables that significantly alter the handover behavior of a cell, with examples including Cell Individual Offset (CIO) and measurement thresholds that dictate the criteria for initiating handover processes. c. The cell coverage parameters are defined as those that have a direct impact on the geographical coverage of the cell, exemplified by the configuration of Radio Frequency (RF) channels, which determines the effective range and quality of the signal. d. The cell-edge parameters are specified as those that affect the performance at the periphery of the cell coverage area. A pertinent example is the configuration of thePCT / US25 / 14547 05 February 2025 (05.02.2025)Proportional Fair (PF) scheduler's alpha-beta settings, which play a crucial role in managing resource allocation at the cell edge. e. The cell-resource parameters are categorized as those that govern the utilization of cell resources. This includes parameters that regulate network slicing, thereby optimizing resource allocation and enhancing the overall performance of the cellular network.

[0034] In one embodiment, the system impacts are categorized into different Aol based on the operator’s and RAN vendor’s expertise.

[0035] In one embodiment, the method 100 includes identifying the one or more functional Aols based on an output of the plurality of applications 101, which may relate to operation 105. The one or more functional Aols are utilized to generate the functional dependency graph, as described in conjunction with FIG. 2. The one or more functional Aols correspond to one or more changes in one or more characteristics of a cell that are not necessarily quantifiable. The one or more functional Aols may include, but is not limited to, a serving cell coverage, a serving cell Radio Resource Management (RRM), a serving cell-neighbor cell Handover (HO) boundary, a serving cell-neighbor cell interference, and a non-specific Aol.

[0036] In one embodiment, the method 100 includes identifying the one or more KPI-based Aols based on a resulting impact on one or more KPIs due to one or more RAN operations, which may relate to operation 105. The one or more KPI-based Aols are utilized to generate the KPIbased dependency graph, as described in conjunction with FIG. 3. The one or more KPI-based Aols correspond to one or more changes in a set of KPIs of a cell that are typically quantifiable. The one or more KPI-based Aols may include, but is not limited to, a mobility, an integrity, a utilization, a retainability, an accessibility, an energy efficiency, and an availability.

[0037] In one embodiment, the method 100 includes each of the one or more functional Aols and one or more KPI-based Aols are further characterized by a scope of the one or more system impacts related to one or more impacted RAN nodes. Herein, the scope defines an extent of the system impact related to the one or more RAN nodes, including a cluster comprising of several cells, neighbor cells with overlapping coverage areas, a specific neighbor, or a serving cell.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0038] In one embodiment, the method 100 includes mapping the one or more identified control parameters or predefined control parameter groups to the corresponding one or more functional Aols and one or more KPI-based Aols. This mapping is based on inputs from operators and RAN vendors, as well as historical data that tracks changes in the identified control parameters. These changes are analyzed to determine their specific impacts on the system.

[0039] In one embodiment, the method 100 includes generating the one or more dependency graphs based on the mapping. The method 100 further includes generating one or more relationships between the one or more identified control parameters, and each of the one or more functional Aols and one or more KPI-based Aols based on the mapping.

[0040] At operations 106 and 107 the method 100 includes analyzing the one or more generated relationships between the one or more identified control parameters and each Aol identifies potential conflict scenarios. The method 100 further includes classifying the one or more identified control parameters, by a conflict detector, as being in conflict occurs when two or more identified control parameters map to the same Aol based on a result of analysis. As a result, the method 100 determines one or more conflicts among the plurality of applications 101 including one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts, as described in conjunction with FIG. 4 and FIG. 5.

[0041] FIG. 2 illustrates a functional dependency graph 200, according to an embodiment as disclosed herein. To generate the functional dependency graph 200, the method may execute multiple operations, which are given below.

[0042] At operation 201, the disclosed method identifies one or more control parameters that are responsible for specific system impacts. These one or more control parameters are primarily derived from the outputs of rApps and xApps 101. Subsequently, the method groups related parameters in such a manner that each group is associated with the type of change it induces within the cell environment. Each category of control parameter encompasses cell attributes, which may be sourced from the configuration database or defined as system parameters.

[0043] At operation 202, following this, the disclosed method maps each group of control parameters to the one or more functional Aols (e.g., 202a,. .. , 202e) during the construction of the dependency graph. This mapping process culminates in the generation of the functionalPCT / US25 / 14547 05 February 2025 (05.02.2025) dependency graph 200, which serves as a visual representation of the interrelationships among the control parameters and their respective impacts.

[0044] Herein, the one or more functional Aols are derived from the objectives of the RAN operations, as indicated by the outputs of the rApps and xApps. For instance, a RAN operation aimed at optimizing HO decisions or minimizing inter-cell interference will identify specific targets namely, the HO boundary and inter-cell interference as functional Aols. This approach enables the detection of potential conflicts associated with these Aols prior to the application of control parameters from multiple xApps and rApps to the RAN nodes, thereby facilitating a preemptive action framework.

[0045] The illustrated dependency graph 200 represents several functional Aols along with their associated scopes of system impact, for example, which are given below. Collectively, these functional Aols illustrate the multifaceted nature of system impacts within the dependency graph 200, highlighting the interconnectedness of various parameters and their implications for network operations. a. Serving cell configuration 202a is a vital functional Aol that encompasses the parameters governing one or more operational settings of the serving cell. b. Serving cell-neighbor cell handover (HO) boundary 202b serves as the functional Aol, wherein the system impact is observed at the handover boundary between the serving cell and its neighboring cells. This impact is confined to the handover boundary itself, highlighting the significance of precise boundary management to ensure seamless transitions for users moving between cells. c. Serving cell coverage 202c is identified as the functional Aol, where the system impact pertains to the coverage area of the serving cell. This impact extends to neighboring cells that possess overlapping coverage, thereby influencing their operational effectiveness and user experience. d. Serving cell-neighbor cell interference 202d is recognized as the functional Aol that affects cell-edge performance in both the serving cell and its neighboring cells. The scope of this impact is specifically limited to the serving cell and the designated neighboring cells, emphasizing the necessity for interference managementPCT / US25 / 14547 05 February 2025 (05.02.2025) strategies to enhance overall network performance and user experience at the cell edges. e. Serving cell radio resource management (RRM) 202e is another critical Aol, with its system impact focused solely on the radio resource management processes within the serving cell. This localized impact underscores the importance of efficient resource allocation and management strategies to optimize performance within that specific cell.

[0046] In one or more embodiments, the disclosed method identifies a few special Aols (non-specific Aol) that are relevant only to certain outputs from the r / xApps. For instance, some outputs may necessitate a sector restart. These special Aols require unique handling and are not included in the fundamental Aols defined previously. Additionally, there are configuration parameters for serving cells that can affect all Aols. For instance, adjusting the cell on / off setting could render other control parameters unnecessary.

[0047] In one or more embodiments, Table-1 illustrates a JavaScript Object Notation (JSON) schema for providing the functional Aol dependency graph 200 serves as a structured framework for defining the relationships and dependencies among various functional Aols within the system.PCT / US25 / 14547 05 February 2025 (05.02.2025)Table-1

[0048] FIG. 3 illustrates the Key Performance Indicator (KPI)-based dependency graph 300, according to an embodiment as disclosed herein. To generate the KPI-based dependency graph 300, the method may execute multiple operations, which are given below.

[0049] At operation 301, the disclosed method identifies one or more control parameters that are responsible for specific system impacts. These one or more control parameters are primarily derived from the outputs of rApps and xApps 101. Subsequently, the method groups related parameters in such a manner that each group is associated with the type of change it inducesPCT / US25 / 14547 05 February 2025 (05.02.2025) within the cell environment. Each category of control parameter encompasses cell attributes, which may be sourced from the configuration database or defined as system parameters.

[0050] At operation 302, following this, the disclosed method maps each group of control parameters to the one or more KPI-based Aols (e.g., 302a, . .. , 302e) during the construction of the dependency graph. This mapping process culminates in the generation of the KPI-based dependency graph 300, which serves as a visual representation of the interrelationships among the control parameters and their respective impacts.

[0051] Herein, the KPI-based Aols are established based on the observed impact of RAN operations, specifically those executed by the r / xApps 101, on key performance indicators (KPIs). For instance, when a RAN operation is conducted to enhance HO decisions or to reduce inter-cell interference, specific KPIs become relevant. In these scenarios, KPIs associated with handover performance, such as a handover success rate, and those related to cell-edge performance, such as cell edge throughput, constitute the KPI-based Aols. Furthermore, it is feasible to identify conflicts by analyzing the monitored KPIs from multiple r / xApps 101 that are implemented across the RAN nodes. This analysis enables the detection of discrepancies or competing demands that may arise from the simultaneous optimization efforts of different r / xApps 101.

[0052] To generate the KPI-based dependency graph 300, it is essential to first identify critical KPIs that are routinely monitored to assess system performance. These identified KPIs serve as the foundation for deriving KPI-Based Aols, which can be further expanded based on the operator’s strategic intents and policies, for example, which are given below. a. Availability 302a: The availability of a cell to provide necessary resources is critically analyzed within this Aol. The scope is defined at a serving cell level, assessing the capacity and reliability of the cell to meet user demands and service requirements. b. Energy efficiency 302b: This Aol focuses on the system’s influence on energy conservation within the network. The analysis is conducted at a cluster level, providing insights into energy-saving measures and their effectiveness in enhancing overall network sustainability.PCT / US25 / 14547 05 February 2025 (05.02.2025) c. Mobility (Inter-cell and Intra-cell) 302c: The impact of the system on mobility performance within the network is a primary focus. This Aol specifically examines the interactions and performance metrics related to neighboring cells, enabling a comprehensive understanding of mobility dynamics. d. Integrity, utilization, and retainability 302d: This Aol evaluates the system’s effect on resource utilization and the allocation of resources necessary to maintain defined service quality levels and ensure the retention of requested services. The analysis is particularly relevant in areas where neighboring cells have overlapping coverage, allowing for a detailed assessment of resource efficiency and service continuity. e. Accessibility 302e: the impact of the system on one or more initial service requests made by users within a specific cell is scrutinized. The scope of this Aol also encompasses neighboring cells with overlapping coverage, facilitating an understanding of user accessibility and service initiation.

[0053] In one or more embodiments, Table-2 illustrates the JSON schema for providing the KPI-based dependency graph 300 serves as a structured framework for defining the relationships and dependencies among various KPI-based Aols within the system.PCT / US25 / 14547 05 February 2025 (05.02.2025)Table-2

[0054] FIG. 4 illustrates an example scenario 400 for determining the one or more conflicts among the plurality of applications 101 by utilizing the functional dependency graph, according to an embodiment as disclosed herein.

[0055] At operation 401, the one or more control parameters are primarily derived from the outputs of rApps and xApps (e g., energy saving 101a, Mobility Robustness Optimization / Mobility Load Balancing (MRO / MLB) 101b, Capacity and Coverage Optimization (CCO) 101c, interference mitigation lOld, and Quality of Service (QoS) / Quality of Experience (QoE) lOle,PCT / US25 / 14547 05 February 2025 (05.02.2025) etc ). Subsequently, the method groups related parameters in such a manner that each group is associated with the type of change it induces within the cell environment. Each category of control parameter encompasses cell attributes, which may be sourced from the configuration database or defined as system parameters. At operation 402, following this, the disclosed method maps each group of control parameters to the one or more functional Aols (e.g., 402a, 402b, 402c, 402d, and 402e) during the construction of the functional dependency graph. This mapping process culminates in the generation of the functional dependency graph, which serves as a visual representation of the interrelationships among the control parameters and their respective impacts. Based on the analysis of mapping and interrelationships within the functional dependency graph, the disclosed method identifies potential conflicts among multiple applications.

[0056] For instance, consider a scenario involving the MRO and MLB 101b. In this context, the MRO application generates control outputs that are mapped to a specific group of HO parameters, such as a Cell Individual Offset (CIO). Similarly, the MLB application also maps its control outputs to the same group of HO parameters, including the CIO. When a Conflict Mitigation (ConMit) functionality evaluates the outputs from both applications, the ConMit conducts a comparative analysis to determine if the control outputs reference identical parameters. In this example scenario 400, it is conceivable that the MRO application determines a modification to the CIO parameter is necessary for the transition between cells A and B. Concurrently, the MLB application may also suggest an adjustment to the CIO parameter for the same transition between cells A and B. This situation exemplifies the direct conflict, which can be effectively represented within the functional dependency graph. The functional dependency graph illustrates the interdependencies and potential conflicts between the applications (e.g., 101a, 101b, .. . , lOle), facilitating a structured approach to conflict resolution and optimization within the network management framework.

[0057] For another instance, consider a scenario involving two specific applications such as the CCO application 101c and the MLB application 101b. The CCO application 101c correlates its control outputs with parameters related to cell coverage, such as antenna tilt. Conversely, the MLB application 101b correlates its control outputs with HO parameters, such as the CIO. Notably, both parameter groups are associated with the same Aols, specifically the HO boundary 402b andPCT / US25 / 14547 05 February 2025 (05.02.2025) the inter-cell interference 402d. This scenario illustrates how indirect conflicts can be effectively represented within the functional dependency graph, highlighting the intricate interdependencies that may arise between the operational domains of the two applications (101c and 101b).

[0058] FIG. 5 illustrates an example scenario 500 for determining the one or more conflicts among the plurality of applications 101 by utilizing the KPI-based dependency graph, according to an embodiment as disclosed herein.

[0059] At operation 501, the one or more control parameters are primarily derived from the outputs of rApps and xApps (e.g., energy saving 101a, CCO 101b, MRO / MLB 101c, interference mitigation 101 d, and QoS / QoE lOle, etc.). Subsequently, the method groups related parameters in such a manner that each group is associated with the type of change it induces within the cell environment. Each category of control parameter encompasses cell attributes, which may be sourced from the configuration database or defined as system parameters. At operation 502, following this, the disclosed method maps each group of control parameters to the one or more KPI-based Aols (e.g., 502a, 502b, 502c, 502d, and 502e) during the construction of the KPI-based dependency graph. This mapping process culminates in the generation of the KPI-based dependency graph, which serves as a visual representation of the interrelationships among the control parameters and their respective impacts. Based on the analysis of mapping and interrelationships within the KPI-based dependency graph, the disclosed method identifies potential conflicts among multiple applications.

[0060] For instance, consider a scenario involving two applications: interference mitigation application lOld and the QoS / QoE application lOle. The interference mitigation application lOld correlates its control outputs with parameters pertaining to the cell edge parameters, such as scheduling coefficients based on the path loss threshold. In contrast, the QoS / QoE application 101 e aligns its control outputs with the cell resource parameters, exemplified by Guaranteed Bit Rate (GBR) resource reservations. Both parameter groups are mapped to the same KPI-based Aol, which includes metrics such as Integrity, Utilization, and Retainability 502d. This scenario serves as a prime example of how the implicit conflicts are represented within the KPI-based dependency graph, illustrating the complex interdependencies that can arise between the operational objectives of the two applications.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0061] FIG. 6 is a flow diagram illustrating a method 600 for determining the one or more conflicts among the plurality of applications 101 based on one or more generated dependency graphs, according to an embodiment as disclosed herein. The method 600 may execute multiple operations to determine the one or more conflicts, which are given below.

[0062] At operation 601, the method 600 includes receiving the plurality of control parameters from the plurality of applications 101. At operation 602, the method 600 includes generating one or more dependency graphs based on the plurality of received control parameters. At operation 603, the method 600 includes determining one or more conflicts among the plurality of applications 101 based on the one or more generated dependency graphs. The one or more conflicts may include at least one of the one or more direct conflicts, the one or more indirect conflicts, and the one or more implicit conflicts. Further, a detailed description related to the various steps of FIG. 6 is covered in the description related to FIG. 1, FIG. 2, FIG. 3, FIG. 4, and FIG. 5, and is omitted herein for the sake of brevity.

[0063] FIG. 7 illustrates a diagram of example components of an apparatus 700, according to an embodiment as disclosed herein. As shown in FIG. 7, the apparatus 700 comprises a processor 710, a memory 720, a storage component 730, an input component 740, an output component 750, a communication interface 760, and a bus 770. In one embodiment, the apparatus 700 may relates to a network entity associated with the ORAN architecture or any other network entity associated with telecommunication system.

[0064] The processor 710, as used herein, means any type of computational circuit that may comprise hardware elements and software elements. The processor 710 may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and / or one or more single core processors, a distributed processing system, or the like. The processor 710 may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Accelerated Processing Unit (APU), an Application-Specific Integrated Circuit (ASIC), or another type of processing component.

[0065] The memory 720 includes a non-transitory computer readable medium. Memory 720 includes a Random-Access Memory (RAM), a Read Only Memory (ROM), and / or another type of dynamic or static storage device (e.g., a flash memory, a magnetic memory, and / or anPCT / US25 / 14547 05 February 2025 (05.02.2025) optical memory) that stores information and / or instructions for use by processor 710. The memory 720 comprises machine-readable instructions which are executable by the processor 710. These machine-readable instructions when executed by the processor 710 cause the processor 710 to perform one or more method steps of an embodiment described above.

[0066] The storage component 730 stores information and / or software related to the operation and use of the apparatus 700. For example, the storage component 730 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optic disk, and / or a solid-state disk), a Compact Disc (CD), a Digital Versatile Disc (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive.

[0067] The input component 740 is configured to receive information, such as user input. For example, the input component 740 may include, but not be limited to, a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and / or a microphone. Additionally, or alternatively, the input component 740 may include a sensor for sensing information (e.g., a Global Positioning System (GPS), an accelerometer, a gyroscope, and / or an actuator).

[0068] The output component 750 is configured to provide output information from the apparatus 700. For example, the output component 750 may be, but is not limited to, a display, a speaker, instructions to an external device, and / or one or more Light-Emitting Diodes (LEDs).

[0069] The communication interface 760 is an interface that provides a communication connection to other devices, such as external devices and internal devices. The connection by the communication interface 760 can be a wired connection, a wireless connection, or a combination of wired and wireless connections, and can be a direct connection or an indirect connection via a communication network that exists between the apparatus 700 and other devices. In other words, the standard of the communication interface 760 is not limited.

[0070] The bus 770 acts as an interconnect between the processor 710, the memory 720, the storage component 730, the input component 740, the output component 750, and the communication interface 760 of the apparatus 700. The bus 770 may include a wired interconnection or a wireless interconnection.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0071] The number and arrangement of components are shown in FIG. 7 are provided as an example. In practice, the apparatus 700 may include additional components, fewer components, different components, or differently arranged components than those shown in FIG. 7. Additionally, or alternatively, a set of components (e.g., one or more components) of the apparatus 700 may perform one or more functions described as being performed by another set of components of the apparatus 700. Further, one or more method steps described in any of the embodiments may be performed utilizing the apparatus 700 in communication with one another. Further, a detailed description related to the various operations to determine the one or more conflicts among the plurality of applications 101 of the apparatus 700 is covered in the description related to FIG. 1 to FIG. 6, and is omitted herein for the sake of brevity.

[0072] The disclosed method / system has several advantages over the existing mechanism, for example, which are stated below, a. Enhanced conflict detection: The dependency graph effectively identifies various types of conflicts among rApps and xApps. By using outputs from applications (e.g., rApps and xApps) as inputs to the dependency graph, the approach allows for a detailed examination of how applications interact. For instance, if the xApp generates a report that influences decisions in the rApp, the graph can map this relationship, ensuring that any changes in one application are analyzed for their impact on others. b. Proactive conflict management: The dependency graph can identify situations where one application’s actions could negatively impact another. For example, if a network management xApp schedules maintenance during peak hours, it may conflict with the rApp that is managing user sessions. The graph can flag this potential issue before it occurs. In addition, the method provides a comprehensive mechanism for tracking conflicts that may arise from various interactions. For example, if multiple xApps are competing for resources, the dependency graph can help identify which applications are causing resource contention, enabling quicker resolution.PCT / US25 / 14547 05 February 2025 (05.02.2025) c. Flexibility for ongoing improvements: As technology evolves, new applications and features can be integrated without extensive rework. For instance, if an existing xApp is updated with an enhancement which changes the control output, the existing dependency graph framework can, in most cases, absorb this change, allowing it to interact with current applications without requiring a complete redesign. d. Scalability: The dependency graph can grow alongside the increasing number of rApps and xApps. For example, as more applications are deployed to manage different aspects of the network, the graph can expand to include these applications, ensuring that conflict detection remains efficient and effective. e. Preservation of real-time capabilities: Maintaining near-real-time functionality is crucial for applications that require immediate responses, such as those managing emergency services. The scalable nature of the dependency graph ensures that even as the number of applications (e.g., rApps and xApps) increases, the disclosed method can still operate efficiently, allowing for timely decision-making and action.

[0073] According to one embodiment of the present disclosure, a method is disclosed. The method includes receiving the plurality of control parameters from the plurality of applications 101. The plurality of applications 101 is associated with at least one of the non-real-time RIC and the near-real-time RIC of the ORAN architecture. The method further includes generating, based on the plurality of received control parameters, the one or more dependency graphs. The method further includes determining, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications 101. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0074] The method described in para

[0072] , the method includes identifying a plurality of possible system impacts caused by one or more changes in configuration of a network associated with the plurality of control parameters. The method further includes categorizing the plurality of identified possible system impacts based on the nature into at least one of the one or more functional Aol and the one or more KPI-based Aol. The method further includes identifying thePCT / US25 / 14547 05 February 2025 (05.02.2025) plurality of the control parameters causing the plurality of identified possible system impacts. The method further includes categorizing the plurality of the identified control parameters into predefined parameter groups based on parameter characteristics comprise at least one of the cell configuration parameters, the HO parameters, the cell coverage parameters, the cell-edge parameters, and the cell-resource parameters. The method further includes mapping the one or more identified control parameters or predefined control parameter groups to the corresponding one or more functional Aols and one or more KPI-based Aols based on either operator and RAN vendor inputs or historical data of changes in the one or more identified control parameters causing one or more specific system impacts. The method further includes generating, based on the mapping, the one or more dependency graphs, one or more relationships between the one or more identified control parameters, and each of the one or more functional Aols and one or more KPIbased Aols. The one or more dependency graph as a pre-configured or auto-generated conflict detection matrix that correlates the plurality of the identified control parameters with the corresponding plurality of identified possible system impacts.

[0075] The method described in any one of paragraphs

[0072] -

[0073] , the method includes identifying the one or more functional Aols based on the output of the plurality of applications 101. The one or more functional Aols correspond to one or more changes in one or more characteristics of the cell that are not necessarily quantifiable. The one or more functional Aols comprise at least one of the serving cell coverage, the serving cell RRM, the serving cell-neighbor cell HO boundary, the serving cell-neighbor cell interference, and the non-specific Aol.

[0076] The method described in any one of paragraphs

[0072] -

[0074] , the method includes identifying the one or more KPI-based Aols based on a resulting impact on one or more KPIs due to one or more RAN operations. The one or more KPI-based Aols correspond to one or more changes in the set of KPIs of a cell that are typically quantifiable. The one or more KPI-based Aols comprise at least one of the mobility, the integrity, the utilization, the retainability, the accessibility, the energy efficiency, and the availability.

[0077] The method described in any one of paragraphs

[0072] -

[0075] , each of the one or more functional Aols and one or more KPI-based Aols is further characterized by a scope of the one or more system impacts related to one or more impacted RAN nodes. The scope defines thePCT / US25 / 14547 05 February 2025 (05.02.2025) extent of the system impact related to the one or more RAN nodes, including the cluster comprising of several Cells, the neighbor cells with overlapping coverage areas, the specific neighbor, or the serving cell.

[0078] The method described in any one of paragraphs

[0072] -

[0076] , the one or more dependency graphs comprise at least one of a functional dependency graph and a KPI-based dependency graph.

[0079] The method described in any one of paragraphs

[0072] -

[0077] , the method includes analyzing the one or more generated relationships between the one or more identified control parameters and each Aol identifies potential conflict scenarios. The method further includes classifying, based on a result of analysis, the one or more identified control parameters as being in conflict occurs when two or more identified control parameters map to the same Aol.

[0080] The method described in any one of paragraphs

[0072] -

[0078] , the method includes receiving the one or more 01 parameters associated with the one or more rApps. The method further includes receiving the one or more E2 parameters associated with the one or more xApps. The method further includes receiving the one or more Al policy parameters received from the non-real-time RIC and passed to the near-real-time RIC. The plurality of control parameters represents the potential source of conflict.

[0081] The method described in any one of paragraphs

[0072] -

[0079] , the method includes transmitting the one or more 01 parameters associated with the rApps to one or more southbound RAN nodes via the 01 interface to dynamically configure the cell configuration to achieve optimal network optimization. The method further includes transmitting the one or more E2 parameters associated with the xApps to the one or more RAN nodes via the E2 interface to dynamically configure one or more functionalities of at least one of the O-CU and the 0-DU. The method further includes transmitting the one or more Al policies from the non-RT RIC platform to the near-RT RIC platform via the Al interface as the set of rules or guidelines for managing and controlling the one or more functionalities of at least one of the O-CU and the 0-DU.

[0082] The method described in any one of paragraphs

[0072] -

[0080] , the plurality of applications 101 comprises at least one of the rApps and the xApps.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0083] According to one embodiment of the present disclosure, an apparatus is disclosed. The apparatus is configured to receive the plurality of control parameters from the plurality of applications 101. The plurality of applications 101 is associated with at least one of the non-real- time RIC and the near-real-time RIC of the ORAN architecture. The apparatus is further configured to generate, based on the plurality of received control parameters, one or more dependency graphs. The apparatus is further configured to determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications 101. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0084] The apparatus described in para

[0082] , the apparatus is configured to identify a plurality of possible system impacts caused by one or more changes in configuration of a network associated with the plurality of control parameters. The apparatus is further configured to categorizing the plurality of identified possible system impacts based on the nature into at least one of the one or more functional Aol and the one or more KPI-based Aol. The apparatus is further configured to identify the plurality of the control parameters causing the plurality of identified possible system impacts. The apparatus is further configured to categorize the plurality of the identified control parameters into predefined parameter groups based on parameter characteristics comprise at least one of the cell configuration parameters, the HO parameters, the cell coverage parameters, the cell-edge parameters, and the cell-resource parameters. The apparatus is further configured to map the one or more identified control parameters or predefined control parameter groups to the corresponding one or more functional Aols and one or more KPI-based Aols based on either operator and RAN vendor inputs or historical data of changes in the one or more identified control parameters causing one or more specific system impacts. The apparatus is further configured to generate, based on the mapping, the one or more dependency graphs, one or more relationships between the one or more identified control parameters, and each of the one or more functional Aols and one or more KPI-based Aols. The one or more dependency graph as a preconfigured or auto-generated conflict detection matrix that correlates the plurality of the identified control parameters with the corresponding plurality of identified possible system impacts.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0085] The apparatus described in any one of paragraphs

[0082] -

[0083] , the apparatus is configured to identify the one or more functional Aols based on the output of the plurality of applications 101. The one or more functional Aols correspond to one or more changes in one or more characteristics of the cell that are not necessarily quantifiable. The one or more functional Aols comprise at least one of the serving cell coverage, the serving cell RRM, the serving cellneighbor cell HO boundary, the serving cell-neighbor cell interference, and the non-specific Aol.

[0086] The apparatus described in any one of paragraphs

[0082] -

[0084] , the apparatus is configured to identify the one or more KPI-based Aols based on a resulting impact on one or more KPIs due to one or more RAN operations. The one or more KPI-based Aols correspond to one or more changes in the set of KPIs of a cell that are typically quantifiable. The one or more KPIbased Aols comprise at least one of the mobility, the integrity, the utilization, the retainability, the accessibility, the energy efficiency, and the availability.

[0087] The apparatus described in any one of paragraphs

[0082] -

[0085] , each of the one or more functional Aols and one or more KPI-based Aols is further characterized by a scope of the one or more system impacts related to one or more impacted RAN nodes. The scope defines the extent of the system impact related to the one or more RAN nodes, including the cluster comprising of several Cells, the neighbor cells with overlapping coverage areas, the specific neighbor, or the serving cell.

[0088] The apparatus described in any one of paragraphs

[0082] -

[0086] , the one or more dependency graphs comprise at least one of a functional dependency graph and a KPI-based dependency graph.

[0089] The apparatus described in any one of paragraphs

[0082] -

[0087] , the apparatus is configured to analyze the one or more generated relationships between the one or more identified control parameters and each Aol identifies potential conflict scenarios. The apparatus is further configured to classifying, based on a result of analysis, the one or more identified control parameters as being in conflict occurs when two or more identified control parameters map to the same Aol.

[0090] The apparatus described in any one of paragraphs

[0082] -

[0088] , the apparatus is configured to receive the one or more 01 parameters associated with the one or more rApps. ThePCT / US25 / 14547 05 February 2025 (05.02.2025) apparatus is further configured to receiving the one or more E2 parameters associated with the one or more xApps. The apparatus is further configured to receive the one or more Al policy parameters received from the non-real-time RIC and passed to the near-real-time RIC. The plurality of control parameters represents the potential source of conflict.

[0091] The apparatus described in any one of paragraphs

[0082] -

[0089] , the apparatus is configured to transmit the one or more 01 parameters associated with the rApps to one or more southbound RAN nodes via the 01 interface to dynamically configure the cell configuration to achieve optimal network optimization. The apparatus is further configured to transmit the one or more E2 parameters associated with the xApps to the one or more RAN nodes via the E2 interface to dynamically configure one or more functionalities of at least one of the 0-CU and the 0-DU. The apparatus is further configured to transmit the one or more Al policies from the non-RT RIC platform to the near-RT RIC platform via the Al interface as the set of rules or guidelines for managing and controlling the one or more functionalities of at least one of the 0-CU and the 0- DU.

[0092] The apparatus described in any one of paragraphs

[0082] -

[0090] , the plurality of applications 101 comprises at least one of the rApps and the xApps.

[0093] According to one embodiment of the present disclosure, a non-transitory computer- readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by an apparatus, the apparatus comprising one or more processors. The one or more processors are configured to receive the plurality of control parameters from the plurality of applications 101. The plurality of applications 101 is associated with at least one of the non-real- time RIC and the near-real-time RIC of the ORAN architecture. The one or more processors are further configured to generate, based on the plurality of received control parameters, one or more dependency graphs. The one or more processors are further configured to determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications 101. The one or more conflicts may include at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

[0094] The various actions, acts, blocks, steps, or the like in the flow diagrams may be performed in the order presented, in a different order, or simultaneously. Further, in somePCT / US25 / 14547 05 February 2025 (05.02.2025) embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.

[0095] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the elements. The elements can be at least one of a hardware device or a combination of hardware devices and software modules.

[0096] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

[0097] The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein.

[0098] Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.

[0099] Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims.PCT / US25 / 14547 05 February 2025 (05.02.2025)

[0100] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and / or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of at least one embodiment, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.

Claims

PCT / US25 / 14547 05 February 2025 (05.02.2025)We claim:

1. A method comprising: receiving a plurality of control parameters from a plurality of applications associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near- real-time RIC of an Open Radio Access Network (ORAN) architecture; generating, based on the plurality of received control parameters, one or more dependency graphs; and determining, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications comprise at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

2. The method according to claim 1, wherein generating the one or more dependency graphs comprises: identifying a plurality of possible system impacts caused by one or more changes in a configuration of a network associated with the plurality of parameters; categorizing the plurality of identified possible system impacts based on a nature into at least one of one or more functional Areas of Influence (Aol) and one or more Key Performance Indicator (KPI)-based Aol; identifying a plurality of the control parameters causing the plurality of identified possible system impacts; categorizing the plurality of the identified control parameters into predefined parameter groups based on parameter characteristics comprising at least one of cell configuration parameters, handover (HO) parameters, cell coverage parameters, cell-edge parameters, and cell-resource parameters; mapping the one or more identified control parameters or predefined control parameter groups to the corresponding one or more functional Aols and one or more KPIbased Aols based on either operator and RAN vendor inputs or historical data of changes in the one or more identified control parameters causing one or more specific system impacts; andPCT / US25 / 14547 05 February 2025 (05.02.2025) generating, based on the mapping, the one or more dependency graphs, one or more relationships between the one or more identified control parameters, and each of the one or more functional Aols and one or more KPI-based Aols, wherein the one or more dependency graphs as a pre-configured or autogenerated conflict detection matrix that correlates the plurality of the identified control parameters with a corresponding plurality of identified possible system impacts.

3. The method according to claim 2, comprising: identifying the one or more functional Aols based on an output of the plurality of applications, wherein the one or more functional Aols correspond to one or more changes in one or more characteristics of a cell that are not necessarily quantifiable, wherein the one or more functional Aols comprise at least one of a serving cell coverage, a serving cell Radio Resource Management (RRM), a serving cellneighbor cell Handover (HO) boundary, a serving cell-neighbor cell interference, and a non-specific Aol.

4. The method according to claim 2, comprising: identifying the one or more KPI-based Aols based on a resulting impact on one or more KPIs due to one or more RAN operations, wherein the one or more KPI-based Aols corresponds to one or more changes in a set of KPIs of a cell that are typically quantifiable, wherein the one or more KPI-based Aols comprise at least one of a mobility, an integrity, a utilization, a retainability, an accessibility, an energy efficiency, and an availability.

5. The method according to claim 2, wherein each of the one or more functional Aols and one or more KPI-based Aols is further characterized by a scope of the one or more system impacts related to one or more impacted RAN nodes; andPCT / US25 / 14547 05 February 2025 (05.02.2025) wherein the scope defines an extent of the system impact related to the one or more RAN nodes, including a cluster comprising of several Cells, neighbor cells with overlapping coverage areas, a specific neighbor, or a serving cell.

6. The method according to claim 1, wherein the one or more dependency graphs comprise at least one of a functional dependency graph and a KPI-based dependency graph.

7. The method according to claim 1, wherein determining the one or more conflicts comprising: analyzing the one or more generated relationships between the one or more identified control parameters and each Aol identifies potential conflict scenarios; and classifying, based on a result of analysis, the one or more identified control parameters as being in conflict occurs when two or more identified control parameters map to the same Aol.

8. The method according to claim 1, wherein receiving the plurality of control parameters from the plurality of applications comprises at least one of: receiving one or more 01 parameters associated with one or more Non-Real Time applications (rApps); receiving one or more E2 parameters associated with one or more Near-Real Time applications (xApps); and receiving one or more Al policy parameters received from the non-real-time RIC and passed to the near-real-time RIC; wherein the plurality of control parameters represents a potential source of conflict.

9. The method according to claim 8, comprising: transmitting the one or more 01 parameters associated with the rApps to one or more southbound RAN nodes via an 01 interface to dynamically configure a cell configuration to achieve optimal network optimization;PCT / US25 / 14547 05 February 2025 (05.02.2025) transmitting the one or more E2 parameters associated with the xApps to the one or more RAN nodes via an E2 interface to dynamically configure one or more functionalities of at least one of an ORAN Centralized Unit (O-CU) and an ORAN Distributed Unit (O-DU); and transmitting the one or more Al policies from the non-RT RIC platform to the near- RT RIC platform via the Al interface as a set of rules or guidelines for managing and controlling the one or more functionalities of at least one of the O-CU and the O-DU.

10. The method according to claim 1, wherein the plurality of applications comprises at least one of Non-Real Time applications (rApps) and Near-Real Time applications (xApps).

11. An apparatus, wherein the apparatus is configured to: receive a plurality of control parameters from a plurality of applications associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture; generate, based on the plurality of received control parameters, one or more dependency graphs; and determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications comprise at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

12. The apparatus according to claim 11, wherein to generate the one or more dependency graphs, the apparatus is configured to: identify a plurality of possible system impacts caused by one or more changes in a configuration of a network associated with the plurality of parameters; categorize the plurality of identified possible system impacts based on a nature into at least one of one or more functional Areas of Influence (Aol) and one or more Key Performance Indicator (KPI)-based Aol;PCT / US25 / 14547 05 February 2025 (05.02.2025) identify a plurality of the control parameters causing the plurality of identified possible system impacts; categorize the plurality of the identified control parameters into predefined parameter groups based on parameter characteristics comprising at least one of cell configuration parameters, handover (HO) parameters, cell coverage parameters, cell-edge parameters, and cell-resource parameters; map the one or more identified control parameters or predefined control parameter groups to the corresponding one or more functional Aols and one or more KPI-based Aols based on either operator and RAN vendor inputs or historical data of changes in the one or more identified control parameters causing one or more specific system impacts; and generate, based on the mapping, the one or more dependency graphs, one or more relationships between the one or more identified control parameters, and each of the one or more functional Aols and one or more KPI-based Aols, wherein the one or more dependency graphs as a pre-configured or autogenerated conflict detection matrix that correlates the plurality of the identified control parameters with a corresponding plurality of identified possible system impacts.

13. The apparatus according to claim 12, wherein the apparatus is configured to: identify the one or more functional Aols based on an output of the plurality of applications, wherein the one or more functional Aols correspond to one or more changes in one or more characteristics of a cell that are not necessarily quantifiable, wherein the one or more functional Aols comprise at least one of a serving cell coverage, a serving cell Radio Resource Management (RRM), a serving cellneighbor cell Handover (HO) boundary, a serving cell-neighbor cell interference, and a non-specific Aol.

14. The apparatus according to claim 12, the apparatus is configured to:PCT / US25 / 14547 05 February 2025 (05.02.2025) identify the one or more KPI-based Aols based on a resulting impact on one or more KPIs due to one or more RAN operations, wherein the one or more KPI-based Aols corresponds to one or more changes in a set of KPIs of a cell that are typically quantifiable, wherein the one or more KPI-based Aols comprise at least one of a mobility, an integrity, a utilization, a retainability, an accessibility, an energy efficiency, and an availability.

15. The apparatus according to claim 12, wherein each of the one or more functional Aols and one or more KPI-based Aols is further characterized by a scope of the one or more system impacts related to one or more impacted RAN nodes; and wherein the scope defines an extent of the system impact related to the one or more RAN nodes, including a cluster comprising of several Cells, neighbor cells with overlapping coverage areas, a specific neighbor, or a serving cell.

16. The apparatus according to claim 11, wherein the one or more dependency graphs comprise at least one of a functional dependency graph and a KPI-based dependency graph.

17. The apparatus according to claim 11, wherein to determine the one or more conflicts, the apparatus is configured to: analyze the one or more generated relationships between the one or more identified control parameters and each Aol identifies potential conflict scenarios; and classify, based on a result of analysis, the one or more identified control parameters as being in conflict occurs when two or more identified control parameters map to the same Aol.

18. The apparatus according to claim 11, wherein to receive the plurality of control parameters from the plurality of applications comprises at least one of, the apparatus is configured to:PCT / US25 / 14547 05 February 2025 (05.02.2025) receive one or more 01 parameters associated with one or more Non-Real Time applications (rApps); receive one or more E2 parameters associated with one or more Near-Real Time applications (xApps); and receive one or more Al policy parameters received from the non-real-time RIC and passed to the near-real-time RIC; wherein the plurality of control parameters represents a potential source of conflict.

19. The apparatus according to claim 18, the apparatus is configured to: transmit the one or more 01 parameters associated with the rApps to one or more southbound RAN nodes via an 01 interface to dynamically configure a cell configuration to achieve optimal network optimization; transmit the one or more E2 parameters associated with the xApps to the one or more RAN nodes via an E2 interface to dynamically configure one or more functionalities of at least one of an ORAN Centralized Unit (0-CU) and an ORAN Distributed Unit (0- DU); and transmit the one or more Al policies from the non-RT RIC platform to the near-RT RIC platform via the Al interface as a set of rules or guidelines for managing and controlling the one or more functionalities of at least one of the 0-CU and the 0-DU.

20. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by an apparatus, the apparatus comprising one or more processors, cause the one or more processors to: receive a plurality of control parameters from a plurality of applications associated with at least one of a non-real-time RAN Intelligent Controller (RIC) and a near-real-time RIC of an Open Radio Access Network (ORAN) architecture; generate, based on the plurality of received control parameters, one or more dependency graphs; andPCT / US25 / 14547 05 February 2025 (05.02.2025) determine, based on the one or more generated dependency graphs, one or more conflicts among the plurality of applications comprise at least one of one or more direct conflicts, one or more indirect conflicts, and one or more implicit conflicts.

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