Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

• 成果类型: Article
• 署名作者: Gao, Lin; Shou, Biying; Chen, Ying-Ju; Huang, Jianwei
• 署名单位: Harbin Institute of Technology; City University of Hong Kong; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology; Chinese University of Hong Kong
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2016.1507
• 发表日期: 2016
• 页码: 794-821
• 关键词: cognitive radio; long-term; networks

摘要

Dynamic spectrum access is a new paradigm of secondary spectrum utilization and sharing. It allows unlicensed secondary users (SUs) to exploit the opportunistically underutilized licensed spectrum. Market mechanism is a widely used promising means to regulate the consuming behaviours of users and, hence, achieve the efficient allocation and consumption of limited resources. In this paper, we propose and study a hybrid secondary spectrum market consisting of both the futures market and the spot market, in which SUs (buyers) purchase underutilized licensed spectrum from a spectrum regulator (SR), either through predefined contracts via the futures market, or through spot transactions via the spot market. We focus on the optimal spectrum allocation among SUs in an exogenous hybrid market that maximizes the secondary spectrum utilization efficiency. The problem is challenging because of the stochasticity and asymmetry of network information. To solve this problem, we first derive an off-line optimal allocation policy that maximizes the ex ante expected spectrum utilization efficiency based on the stochastic distribution of network information. We then propose an online Vickrey-Clarke-Groves (VCG) auction that determines the real-time allocation and pricing of every spectrum based on the realized network information and the prederived off-line policy. We further show that with the spatial frequency reuse, the proposed VCG auction is NP-hard; hence, it is not suitable for online implementation, especially in a large-scale market. To this end, we propose a heuristics approach based on an online VCG-like mechanism with polynomial-time complexity, and further characterize the corresponding performance loss bound analytically. We finally provide extensive numerical results to evaluate the performance of the proposed solutions.