  This article emphasizes the great potential of big data processing for
advanced user- and situation-oriented, so 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, (RSM) 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 the
Internet-of-Things (IoT) networks, which are steadily growing and consequently
considered as the studied use case in this work. We show that the 6G network
significantly benefits from effective Dynamic Spectrum management (DSM) based
on RSM which provides 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 the accurate definition and access to the rich
context information lead to a significant improvement of the system
performance. In consequence, we also claim that efficient big-data processing
algorithms will be necessary for future applications.
