Abstract
Remote and rural areas are a challenge to deploy cost-efficient connectivity solutions. 5G technology needs lower frequencies, which calls for spectrum sharing for local networks. Spectrum sensing could complement traditional database approach for spectrum sharing in these areas. This paper studie
Highlights
Remote and rural area connectivity is a true challenge that can be solved by using lower frequency bands that are made available through shared spectrum access
The performance of a spectrum windowing based energy detection method WIBA was studied, and comparison was made with the well-studied localization algorithm based on double-thresholding (LAD) adjacent cluster combining (ACC) method
It can be concluded that the WIBA method has better detection probability than the LAD method with ACC parameter (LAD ACC) method
Summary
5th generation (5G) mobile communication networks present an evolution in the cellular network development bringing enhanced mobile broadband connectivity like discussed in CROWNCOM 2019 [1]. 5G networks target higher spectrum efficiency, lower latency, improved scalability and new application areas in digitalizing different sectors. 5G network related application areas for spectrum sensing include, e.g., mobile cellular systems [13], device-todevice (D2D) communication [14], and IoT [15]. One important application area for spectrum sensing is when multiple SUs share the spectrum In that case they could use sensing to determine if other SUs are present [16]. The performance of an efficient and blind ED-based spectrum sensing method, namely the windowing based (WIBA) signal detection method [19], is studied. In [1], AWGN and multipath sensing were considered, and the effect of the detection window length M to the detection performance in different channel situations was studied.
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