Generalised Potential Game-Based Resource Allocation in SDN-Enabled O-RAN Systems

Abstract

The evolution of wireless networks toward 6G and Open Radio Access Network (O-RAN) architectures brings unprecedented demands for flexible and energy-efficient resource allocation mechanisms. A key challenge is to allocate radio resources effectively among heterogeneous units while satisfying diverse quality-of-service (QoS) requirements. Traditional allocation methods often fail to capture energy efficiency considerations or lack adaptability in highly dynamic and decentralized environments. To address this, we formulate the resource allocation problem as a non-cooperative game among SDN-enabled Central Units (CUs) and Distributed Units (DUs), where each player’s utility captures a trade-off between throughput gains and resource costs under threshold-based SINR QoS constraints. We show that the game admits an exact generalized potential function, guaranteeing the existence of a pure-strategy Nash equilibrium and convergence under sequential best response dynamics. The SDN controller supervises the network by adjusting system-level parameters, such as the resource price, to guide the network toward efficient and fair allocations. This formulation provides a rigorous and tractable framework for distributed spectrum sharing in 6G O-RAN systems, with the potential to support intelligent and adaptive control in future wireless networks. The proposed framework is evaluated against both classical resource allocation strategies (equal and greedy allocation) and advanced optimization-based and game-theoretic baselines, including convex optimization, proportional fairness, water-filling, and Stackelberg formulations, and shows competitive performance.