A spatial diversity cooperative spectrum sensing system based on blockchain and deep learning

Autor: Zhongshan XIAO, Chunqi WANG, Daquan FENG
Jazyk: čínština
Rok vydání: 2023
Předmět:
Zdroj: Dianxin kexue, Vol 39, Pp 49-63 (2023)
Druh dokumentu: article
ISSN: 1000-0801
DOI: 10.11959/j.issn.1000-0801.2023193
Popis: Cooperative spectrum sensing is a key technology in cognitive radio.A data-driven intelligent cooperative spectrum sensing system was proposed with spatial diversity running on a smart contract to address issues of security, privacy, incentive and hidden terminals in cooperative spectrum sensing.Specifically, a motivated spectrum sensing system was designed by taking advantage of the decentralization of blockchain technology and the immutability of data.Secondly, a deep learning-based approach was proposed to identify malicious users in the system.In addition, to achieve higher accuracy in recruiting sensing nodes more efficiently in the system, a hard decision cooperative spectrum sensing fusion algorithm based on performance weights and spatial diversity was designed.The experimental results indicate that the proposed solution outperforms traditional cooperative spectrum sensing algorithms in terms of security, privacy, motivation, and sensing accuracy.
Databáze: Directory of Open Access Journals