Blockchain-Enabled Dynamic Spectrum Trading for Next-Generation Wireless Networks
IEEE Open Journal of the Communications Society, cilt.7, ss.7000-7019, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 7
- Basım Tarihi: 2026
- Doi Numarası: 10.1109/ojcoms.2026.3702773
- Dergi Adı: IEEE Open Journal of the Communications Society
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Sayfa Sayıları: ss.7000-7019
- Anahtar Kelimeler: 5G mobile communication, 6G and beyond networks, 6G mobile communication, blockchain, next-generation wireless networks, radio spectrum management, resource management, smart contracts, Spectrum management, spectrum trading
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
The evolution toward 5G-Advanced, 6G, and beyond networks has intensified the need for more flexible and efficient spectrum management mechanisms, as traditional static spectrum allocation leads to significant underutilization. To address this challenge, this paper proposes a blockchain-based spectrum trading framework that enables secure, transparent, and automated spectrum trading between spectrum holders and spectrum buyers using Ethereum-based smart contracts. To motivate the need for dynamic spectrum access, we analyze fine-grained spatio-temporal cellular activity from the Milan city dataset, which records urban traffic demand across thousands of spatial grids at a 10-minute temporal resolution. From this data, we infer a normalized demand-based utilization index that reveals pronounced temporal variability and spatial heterogeneity in spectrum usage, even within high-demand regions, which indicates the presence of short-term and localized spectrum trading opportunities that cannot be exploited under current regulatory processes. We further employ a two-layer k-means clustering procedure to capture spatial demand heterogeneity across grids, demonstrating that traffic profiles vary significantly by location and thus create localized trading opportunities. Additionally, an ANN-based traffic load prediction example for a representative grid is included to illustrate how anticipating low-demand intervals can support proactive spectrum trading decisions. Building on these insights, the proposed framework operates at the spectrum access and coordination layer, independent of underlying PHY/MAC implementations, and automates spectrum discovery, matching, pricing, and settlement through smart contract execution. Interference-aware policy constraints are incorporated to ensure coexistence among neighboring deployments. Experimental results evaluate execution latency, transaction cost, and scalability, which demonstrate that spectrum access and reconfiguration can be achieved within seconds, compared to conventional coordination processes that require weeks. By combining data-driven evidence of spectrum underutilization with an executable blockchain-based coordination framework, this work provides a practical foundation for dynamic and reproducible spectrum trading in future cellular networks.