Dynamic spectrum access (DSA) is one way to utilize and efficiently manage the frequency spectrum for wireless communications. One of DSA's implementation at the physical and medium access and controls layers through cognitive radio (CR). CR and other DSA methods at those layers offer better solutions for reaching and interconnecting users or things, especially those in the rural areas, including unconnected internet-of-things (IoT) devices. This work aims to survey current technologies and standards for DSA. In particular, the comparisons are those of unutilized bands that were allocated for television broadcasting, which is known as television white space (TVWS). The paper provides an overview of TVWS, its elements, different architecture depending on the chosen application, and to show potential gaps for future techniques and technologies for TVWS systems and research.
Wireless multipath propagation causes different paths taken by the signal due to interacting objects present in the environment producing multipath components (MPCs). Cluster-based channel models characterize the wireless channel, and different approaches are utilized to cluster the MPCs. Data mining requires different techniques such as visualization to extract important information and find patterns and clusters in the data. A Graphical User Interface (GUI) is developed in this paper to aid the visualization and the manual clustering of MPCs using t-distributed Stochastic Neighborhood Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). The clustering results of Simultaneous Clustering and Model Selection (SCAMS) are used in this paper. The datasets are embedded into low-dimensional projection and are manually re-clustered. The manual clustering was performed visually and interactively, which achieves a higher Jaccard membership index with a low value of 0.3368, a median of 0.4697, and a high value of 0.8884 for all the datasets.
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