An Optimal Framework for Integrating O-RAN and MEC via Pooled DU/CU Deployment

This work formulates a joint placement and resource allocation problem for the integration of the O-RAN architecture with Multi-access Edge Computing (MEC) resources and solves it using a comprehensive mixed-integer linear programming (MILP) model. The proposed model jointly minimises deployment costs for Distributed Units (DUs) and Central Units (CUs), as well as application-layer workloads, while considering transmission and processing delays. Additionally, our model incorporates the pooling of O-DU resources (pO-DU) under strict delay constraints, enabling efficient resource pooling at the edge to accommodate varying traffic demands and reduce operational and capital expenditures (OPEX and CAPEX). Moreover, the framework leverages the RAN Intelligent Controller (RIC) to orchestrate control functions while coordinating with MEC resources for computationally intensive tasks, ensuring that each network slice meets its capacity and latency requirements. Consequently, the framework also optimises offloading to MEC or cloud servers to meet latency and data-processing requirements. Simulation results demonstrate that the proposed solution effectively balances cost, latency, and resource utilisation, providing valuable insights for operators seeking to deploy next-generation networks with integrated O-RAN and MEC capabilities.