A Digital Twin-Based Simulation and Intelligent Network Operations Framework for 6G Networks

The rapid evolution of sixth-generation (6G) wireless networks is expected to introduce highly heterogeneous network infrastructures, dynamic traffic conditions, stringent latency requirements, and increased demands for reliability, scalability, and intelligent network management. These characteristics make conventional network management approaches insufficient for evaluating complex network behavior under changing traffic, mobility, resource utilization, and failure conditions. This paper presents a digital twin-based simulation and intelligent network operations framework for 6G networks that provides an integrated environment for modeling, monitoring, analyzing, and optimizing network operations. The proposed framework represents heterogeneous network nodes, communication links, traffic flows, network slices, mobility conditions, propagation characteristics, and resource states using a structured simulation model. A capacity-aware routing mechanism is employed to determine feasible paths while supporting flow rerouting when network resources become unavailable or degraded. The framework further incorporates network slicing for differentiated traffic classes, mobility and handover modeling, propagation delay and free-space path-loss estimation, failure injection and recovery, and immutable digital twin snapshots for maintaining consistent representations of network states. Network analytics are used to evaluate key performance indicators including availability, flow success rate, utilization, throughput, latency, bandwidth, active flows, and energy consumption. An explainable optimization module analyzes these metrics and generates rule-based recommendations for congestion reduction, latency improvement, energy efficiency, and network recovery. The framework is implemented as a self-contained simulation environment with a graphical network operations interface, enabling controlled and reproducible experimentation using deterministic synthetic telemetry. The proposed approach provides a unified platform for studying 6G network behavior and demonstrates how digital twin modeling, simulation-driven analytics, failure-aware routing, and intelligent operational recommendations can support more reliable and adaptive network management.