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5. Change Detection Based Segmentation and Modeling of LTE Spectrum Tenancy

   https://doi.org/10.1109/GLOBECOM38437.2019.9013749  

   Zou, Rui ; Wang, Wenye ( December 2019 , IEEE GLOBECOM)

   Abstract—The mainstay of current spectrum access grants exclusive rights to proprietary occupants who exhibit tidal traffic patterns, leading to low usage of valuable spectrum resources. To remedy this situation, Dynamic Spectrum Access (DSA) is proposed to allow Secondary Users (SUs) to opportunistically exploit idle spectrum slices left by Primary Users (PUs). The key to the success of DSA lies in SUs’ knowledge on radio activities of PUs. To enhance the understanding of PU spectrum tenancy patterns, various mathematical models have been proposed to describe spectrum occupancy dynamics. However, there are still two overlooked aspects in existing studies on spectrum tenancy modeling, i.e., time-varying spectrum tenancy patterns and multi- ple channels within the same Radio Access Technology (RAT). To address the two issues, we apply a change detection algorithm to discover time points where spectrum tenancy patterns vary, and propose to characterize spectrum usage in a multi-channel RAT by the Vector Autoregressive (VAR) model. Through analyzing LTE spectrum tenancy data with the algorithm and the model, we validate that the segment size discovered by the online change detection method coincides with the one obtained by brute force, and VAR outperforms the widely adopted on/off model. 

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