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Full title: Beyond 5G: Big Data Processing for Better Spectrum Utilization
This article emphasizes the great potential of big data processing for advanced user- and situation-oriented, context-aware resource utilization in future wireless networks. In particular, we consider the application of dedicated, detailed, and rich-in-content maps and records called radio-service maps (RSMs) for unlocking the spectrum opportunities in 6G networks.
Due to the characteristics of 5G, in the future, there will be a need for high convergence of various types of wireless networks, such as cellular and Internet of Things (IoT) networks, which are steadily growing and consequently considered as the studied use case in this article. We show that the 6G network significantly benefits from effective dynamic spectrum management (DSM) based on RSMs that provide rich and accurate knowledge of the radio context, a knowledge that is stored and processed within database-oriented subsystems designed to support wireless networks for improving spectral efficiency.
In this article, we discuss context-aware RSM subsystem architecture and operation for DSM in convergent 6G radio and IoT networks. By providing various use cases, we demonstrate that accurate definition of and access to the rich context information leads to a significant improvement of system performance. As a consequence, we also claim that efficient big data processing algorithms will be necessary in future applications.
Full Article: IEEE Transactions on Vehicular Technology, Volume 15, Number 3, September 2020 | 
