Decentralized Blockchain-Based Dynamic Spectrum Acquisition for Wireless Downlink Communications

• Published in: IEEE transactions on signal processing Vol. 69; pp. 986 - 997
• Main Authors: Jiang, Miao, Li, Yiqing, Zhang, Qi, Zhang, Guangchi, Qin, Jiayin
• Format: Journal Article
• Language: English
• Published: New York IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Alternating direction method of multipliers (ADMM); Blockchain; Communications systems; Cryptography; Data communication; Data transmission; Downlinking; dynamic spectrum acquisition; Manganese; Optimization; Quadratures; Spectrum allocation; Transmission rate (communications); Virtual networks; Virtualization; Wireless communication; Wireless communications; wireless network virtualization; Wireless networks
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2021.3052830

Wireless network virtualization is a promising solution to improve spectrum efficiency. For a wireless downlink communication system with multiple mobile virtual network operators (MVNOs), we propose a decentralized blockchain-based dynamic spectrum acquisition scheme. Our proposed scheme aims to minimize the sum transmit power at all MVNOs while satisfying the average data transmission rate thresholds. For each MVNO, the required wireless spectrum to provide customized services to the mobile users (MUs) is predicted using the half-range Gauss-Hermite quadrature. Based on the predicted values, all the MVNOs carry out a blockchain-based distributed alternative direction method of multipliers to obtain the global optimal solution to the aforementioned sum transmit power minimization problem. To examine the effectiveness of our proposed scheme, with known system parameters, we also theoretically derive the semi-closed-form solution to the actually required sum transmit power minimization problem subject to data transmission rate constraints. Simulation results illustrate that our proposed dynamic spectrum acquisition scheme achieves almost the same minimum sum power as the non-causal scheme, which assumes the number of active MUs in all cells and all the channels are known non-causally for the optimal dynamic spectrum allocation.