Blockchain and timely auction mechanism-based spectrum management

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-01-02 DOI:10.1016/j.future.2024.107703
Hongyi Zhang , Mingqian Liu , Yunfei Chen , Nan Zhao
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Abstract

The rapid development of 5G/B5G communication networks and the exponential growth of next-generation wireless devices require more advanced and dynamic spectrum management and control architecture. Dynamic spectrum management and control based on blockchain is efficient and robust, but the cost of traditional consensus mechanisms is too high. In this paper, we propose a new spectrum management and control architecture based on blockchain and deep reinforcement learning, which proposes a new energy-saving consensus mechanism called proof of hierarchy to encourage blockchain users to perform spectrum sensing and detect spectrum violations. Meanwhile, we propose a timely auction mechanism based on deep reinforcement learning for dynamic spectrum management, achieving secure, efficient, and dynamic allocation of spectrum resources. Through intelligent resource allocation and trusted transaction mechanism, efficient spectrum management is realized to improve spectrum utilization and alleviate the shortage of spectrum resources. The simulation verifies the effectiveness of the proposed architecture. We construct a spectrum management scenario and compare it with the traditional spectrum management method. The experimental results show that the proposed architecture can allocate spectrum resources more efficiently and provide a better user experience.
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b区块链和基于及时拍卖机制的频谱管理
5G/B5G通信网络的快速发展和下一代无线设备的指数级增长需要更先进和动态的频谱管理和控制架构。基于区块链的动态频谱管理与控制具有高效和鲁棒性,但传统共识机制的成本过高。在本文中,我们提出了一种基于区块链和深度强化学习的新的频谱管理和控制架构,该架构提出了一种新的节能共识机制,称为层次证明,以鼓励区块链用户进行频谱感知和频谱违规检测。同时,我们提出了一种基于深度强化学习的动态频谱管理及时拍卖机制,实现了频谱资源的安全、高效、动态分配。通过智能资源分配和可信交易机制,实现高效的频谱管理,提高频谱利用率,缓解频谱资源短缺的问题。仿真结果验证了该体系结构的有效性。构建了一个频谱管理场景,并与传统的频谱管理方法进行了比较。实验结果表明,该架构可以更有效地分配频谱资源,提供更好的用户体验。
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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