Bayesian Mechanism Design Secures Blockchain Fees and Miner Revenue ∞ Research

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Briefing

The persistent challenge in blockchain systems has been designing transaction fee mechanisms (TFMs) that simultaneously ensure user truthfulness, miner collusion-proofness, and a positive miner revenue, a combination previously deemed impossible by foundational theory. This paper introduces a novel TFM within a Bayesian game setting, relaxing the stringent Dominant Strategy Incentive Compatibility (DSIC) for users to Bayesian Nash Incentive Compatibility (BNIC). It employs an “auxiliary mechanism method” and a multinomial logit (MNL) choice model to construct a TFM that is both BNIC and collusion-proof, while guaranteeing a constant-factor approximation of optimal miner revenue. This breakthrough fundamentally redefines the design space for blockchain economic protocols, enabling the creation of more robust, economically viable, and incentive-aligned transaction fee systems crucial for the long-term sustainability and security of decentralized architectures.

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Context

Prior to this research, the prevailing understanding in blockchain mechanism design faced a theoretical impasse. It was deemed impossible to construct a transaction fee mechanism that simultaneously offered dominant strategy incentive compatibility for users, collusion resistance for miners, and a non-zero miner revenue. This limitation posed a significant challenge for ensuring both the fairness of transaction ordering and the economic sustainability of mining operations in decentralized networks.

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Analysis

The core innovation lies in shifting the incentive compatibility paradigm from Dominant Strategy Incentive Compatibility (DSIC) to Bayesian Nash Incentive Compatibility (BNIC) within a Bayesian game framework. DSIC demands truthfulness regardless of others’ actions, a very strong condition. BNIC, by contrast, requires truthfulness given beliefs about others’ strategies, a more realistic assumption in complex, distributed systems where participants have incomplete information. The paper introduces an “auxiliary mechanism method” that bridges these two concepts, allowing for the design of a TFM that achieves both BNIC for users and collusion-proofness for miners.

This TFM is built upon a multinomial logit (MNL) choice model, which captures user behavior in selecting transaction inclusion based on fees. This approach fundamentally differs from previous designs by leveraging a more nuanced game-theoretic model to overcome the prior impossibility result, demonstrating that a balance between strong incentives and sustainable miner revenue is achievable.

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Parameters

Core Concept ∞ Bayesian Nash Incentive Compatibility (BNIC)
New System/Protocol ∞ Auxiliary Mechanism Method
Key Model ∞ Multinomial Logit (MNL) Choice Model
Key Authors ∞ Chen, X. et al.
Publication ∞ Operations Research (2025)

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Outlook

This research opens new avenues for mechanism design in decentralized systems, extending beyond transaction fees to other resource allocation problems where strong incentive compatibility may be overly restrictive. Future work could explore the application of the auxiliary mechanism method in diverse blockchain contexts, such as decentralized finance (DeFi) protocol design or resource allocation in layer-2 scaling solutions. The theoretical framework could also be extended to dynamic settings, considering how user valuations and miner behaviors evolve over time. Real-world applications within the next 3-5 years could include more sophisticated and robust fee markets for existing blockchains, leading to improved user experience and enhanced network stability.

This research decisively advances blockchain economic theory by proving the feasibility of incentive-compatible, revenue-generating transaction fee mechanisms, overcoming a fundamental prior impossibility result.

Signal Acquired from ∞ arXiv.org