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Open AccessLetter

A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation

1
Faculty of Computing and Telecommunications, Poznań University of Technology, 61-131 Poznań, Poland
2
Department of Information Systems and Technology, Mid Sweden University, 851 70 Sundsvall, Sweden
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(15), 4136; https://doi.org/10.3390/s20154136
Received: 23 June 2020 / Revised: 22 July 2020 / Accepted: 22 July 2020 / Published: 25 July 2020
(This article belongs to the Section Sensors Letters)
The energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires the estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimation is an accurate extraction of the signal and noise samples in a received signal time frame. In this paper, we propose a low-complexity and accurate signal samples detection algorithm as compared to well-known methods, which is also blind to the PU activity distribution. The proposed algorithm is analyzed in a semi-experimental simulation setup for its accuracy and time complexity in recognizing signal and noise samples, and its use in channel occupancy estimation, under varying occupancy and SNR of the PU signal. The results confirm its suitability for acquiring the necessary information on the dynamic behavior of PU, which is otherwise assumed to be known in the literature. View Full-Text
Keywords: discontinuous signals; blind detection; rank order filtering; primary user traffic discontinuous signals; blind detection; rank order filtering; primary user traffic
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Nikonowicz, J.; Mahmood, A.; Gidlund, M. A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation. Sensors 2020, 20, 4136.

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