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This article emphasizes the great potential of big data processing foradvanced user- and situation-oriented, so context-aware resource utilization infuture wireless networks. In particular, we consider the application ofdedicated, detailed, and rich-in-content maps and records called Radio ServiceMaps, (RSM) for unlocking the spectrum opportunities in 6G networks. Due to thecharacteristics of 5G, in the future, there will be a need for high convergenceof various types of wireless networks, such as cellular and theInternet-of-Things (IoT) networks, which are steadily growing and consequentlyconsidered as the studied use case in this work. We show that the 6G networksignificantly benefits from effective Dynamic Spectrum management (DSM) basedon RSM which provides rich and accurate knowledge of the radio context; aknowledge that is stored and processed within database-oriented subsystemsdesigned to support wireless networks for improving spectral efficiency. Inthis article, we discuss context-aware RSM subsystem architecture and operationfor DSM in convergent 6G radio and IoT networks. By providing varioususe-cases, we demonstrate that the accurate definition and access to the richcontext information lead to a significant improvement of the systemperformance. In consequence, we also claim that efficient big-data processingalgorithms will be necessary for future applications.

Beyond 5G: Big Data Processing for Better Spectrum Utilization