A User-to-User Resource Reselling Game in Open RAN with Buffer Rollover

2025-09-22

AI Summary

To address dynamic, heterogeneous user demands and low spectral efficiency in O-RAN, this paper proposes a PRB resale-based resource allocation mechanism among users. We formulate a novel game-theoretic model integrating buffer status and inter-slot demand accumulation, and introduce a “buffer rollback” mechanism to accurately capture intra-user queue dynamics. We rigorously prove the existence and uniqueness of the Nash equilibrium. Furthermore, we design a distributed iterative bidding algorithm ensuring rapid convergence. The mechanism is deeply aligned with O-RAN’s virtualized architecture, enabling fine-grained, low-latency dynamic resource re-allocation. Experimental results demonstrate that, compared to baseline schemes, our approach reduces packet loss rate by 30.5%, decreases spectrum waste by 50.7%, and significantly improves social welfare.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Algorithm Configuration

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

The development of the Open RAN (O-RAN) framework helps enable network slicing through its virtualization, interoperability, and flexibility. To improve spectral efficiency and better meet users' dynamic and heterogeneous service demands, O-RAN's flexibility further presents an opportunity for resource reselling of unused physical resource blocks (PRBs) across users. In this work, we propose a novel game-based user-to-user PRB reselling model in the O-RAN setting, which models the carryover of unmet demand across time slots, along with how users' internal buffer states relate to any PRBs purchased. We formulate the interplay between the users as a strategic game, with each participant aiming to maximize their own payoffs, and we prove the existence and uniqueness of the Nash equilibrium (NE) in the game. We furthermore propose an iterative bidding mechanism that converges to this NE. Extensive simulations show that our best approach reduces data loss by 30.5% and spectrum resource wastage by 50.7% while significantly improving social welfare, compared to its absence.

Problem

• Modeling user-to-user resource reselling in Open RAN networks
• Addressing unmet demand carryover across time slots
• Optimizing spectrum efficiency while reducing data loss

Innovation

• Game-based user-to-user PRB reselling model
• Strategic game with proven Nash equilibrium existence
• Iterative bidding mechanism converging to equilibrium