Cross-Segment Slice Controller for Unified RAN-Core Policy Enforcement

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Solution Overview

Problem

Current E2E orchestration solutions lack a comprehensive methodology for policy enforcement across different network segments, are often siloed, and lack flexibility in real-world deployments with existing SDN and SDR technologies, making it difficult to identify the root cause of issues in virtualized communication systems.

Innovation Solution

An intelligent module/management system (IM) with an intelligent E2E orchestration platform (IEOP) and a cross-segment slice controller (CSSC) that integrates AI/ML to dynamically coordinate RAN and core network slice management, enabling adaptive resource use and proactive network self-recovery, facilitating cross-segment slicing and efficient resource management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If siloed E2E orchestration solutions are used, then network segment management is simplified, but comprehensive policy enforcement across segments becomes difficult

Engineering Contradiction:

Improvenetwork segment managementVSAvoidcomprehensive policy enforcement

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent merges previously siloed E2E orchestration solutions into a unified framework that coordinates RAN and core network segments through a common policy enforcement mechanism. The cross-segment slice controller integrates multiple network segments under a single management domain, enabling comprehensive policy enforcement while maintaining operational simplicity through centralized coordination.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The cross-segment slice controller acts as an intermediary between RAN and core network segments, facilitating coordinated policy enforcement. This mediator component translates high-level orchestration policies into segment-specific actions, resolving the complexity of cross-segment enforcement while maintaining simplified segment-level management.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Extent of automation

If existing SDN and SDR technologies are deployed, then network virtualization is achieved, but flexibility in real-world deployments is reduced

Engineering Contradiction:

Improvenetwork virtualizationVSAvoidflexibility in real-world deployments

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The patent introduces dynamic adaptation capabilities to the E2E orchestration framework, enabling real-time adjustments to network slicing configurations based on actual deployment conditions. The system can dynamically modify slice parameters, resource allocations, and policy enforcement mechanisms to adapt to varying real-world network conditions while maintaining the automation benefits of SDN/SDR virtualization.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system enables flexible parameter changes in network slice configurations to accommodate different deployment scenarios. By allowing dynamic modification of slicing parameters, resource allocation policies, and control mechanisms, the framework maintains adaptability despite the underlying virtualized architecture of SDN and SDR technologies.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If AI/ML is integrated for dynamic coordination, then network self-recovery is enabled, but system complexity increases

Engineering Contradiction:

Improvenetwork self-recoveryVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements network self-recovery capabilities where the system automatically detects, analyzes, and responds to failures using integrated AI/ML components. The cross-segment slice controller autonomously executes recovery actions by selecting appropriate remediation strategies from learned patterns, enabling the network to service itself without external intervention while managing complexity through automated decision-making.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system incorporates feedback mechanisms where AI/ML models continuously learn from network operational data and failure patterns. This feedback loop enables the system to improve its self-recovery capabilities over time, adapting to new failure modes and optimizing response strategies while managing complexity through data-driven learning rather than rigid pre-programming.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250330875A1Intelligent machine learning (ML)-enabled end-to-end (E2E) automated orchestration for collaborative next-generation wireless wireline convergence (WWC)

Publication Date: 2025.10.23 AT&T INTELLECTUAL PROPERTY I L P

AI summary

Aspects of the subject disclosure may include, for example, a system including a cross-segment slice controller (CSSC) configured to interface with a software-defined network (SDN) controller and a software-defined radio (SDR) controller. The SDN controller may be associated with a core network and the SDR controller may be associated with a radio access network (RAN). The system further includes a machine learning (ML) component configured to obtain and analyze data regarding the core network and the RAN, and an intelligent end-to-end (E2E) orchestration platform (IEOP) configured to coordinate with the SDN controller and the SDR controller via the CSSC based on outputs of the ML component to provide dynamic cross-segment network slice management. Other embodiments are disclosed.