Design of Trading Mechanism and Blockchain-Based Spectrum Administration System for Space-Air-Ground Integrated Networks

Design of Trading Mechanism and Blockchain-Based Spectrum Administration System for Space-Air-Ground Integrated Networks

연구 분야: Networking

학회: 2024 Global Conference on Communications and Information Technologies (GCCIT)

Complete connectivity and high-quality service are provided via a space-air-ground integrated network (SAGIN). Because it brings together devices from several untrusted authorities, an integrated network like this raises security risks. While blockchain's decentralized ledger features promise to address SAGIN's security flaws, they also pose the risk of incurring intolerable latency due to sequential request validation and consuming vast amounts of storage space required to maintain a full copy of the chain on each node in a large-scale networks. In order to facilitate the required inter-segment cooperation, it becomes conceivable to use several parallel blockchains for the effective management of various SAGIN with blockchain collaboration technology segments. To that aim, we present SAGIN's collaborative blockchain architecture as a means to an end—the efficient and safe administration of varied resources. While blockchain cooperation is possible, each section of SAGIN—the air, ground, and space networks—maintains its own specifically constructed blockchain. In SAGIN, spectrum management has become crucial as the number of wireless gadgets and services continues to skyrocket. Reliable spectrum sensing under lower signal-to-noise ratio (SNR) is still a major barrier for spectrum management, despite the fact that efforts to provide dynamic spectrum access are showing promise in promoting more spectrum sharing. To enhance the performance of spectrum sensing, a deep neural network-based detection structure is constructed to extract features data-drivenly from the received signal's covariance matrix. This approach is based on the idea that artificial intelligence (AI) can provide intelligence to wireless networks through learning and data mining. A method for blindly defining thresholds without using the system's past knowledge is suggested in order to eradicate the effect of noise uncertainty. The suggested scheme's detection effectiveness is enhanced in a low SNR dom... Show More